motivational essay music

Table of Contents

Mood Music with English Lyrics

Music in a foreign language, music without lyrics.

Game & Movie Scores without Lyrics

Electronic Music

Ambient noise, the best music for writing: 32 playlists for inspiration & focus.

Music can set the tone when you’re writing a book . Or, it can help you avoid writer’s block by motivating you through the hard, boring work of sitting in your chair.

But it has to be the right music for you (and your book).

Some people can write to anything. Heavy metal, construction noises, or catchy pop tunes, nothing derails their focus.

I am not one of those. I need the music to match my mood or the mood I’m writing in. How am I supposed to write about the most challenging moments in my life while upbeat kids’ music is pounding in my headphones?

Some people can only write to music if there are no lyrics or if it’s in a foreign language they can’t understand. There’s no right answer for the “best” or “perfect” playlist. It’s just whatever works best for you.

You need something that will motivate you to write quickly and write well so you can get your published book into the world.

It may take some trial-and-error to figure it out. But here’s a list of options that have worked for me and other members of the Scribe Crew . I’ve broken our top recommendations down into categories, so you can try them out yourself.

32 Best Music Playlists & Songs to Listen to While You Write

Whether you need to psych yourself up to write or just want to match the tone of your book, here are some of our favorite options for a range of moods.

1. Morning Rhythm

This is upbeat but gentle music to ease you into the writing groove. There’s a little bit of everything here, from funk to soul to jazz.

Every song has a beat, so this list will motivate you without fading into the background.

2. Shoegaze Classics

Shoegaze was initially called “dream pop” when it emerged in the UK in the 1980s. It features ethereal, shimmery vocals, distorted guitars, and a lot of distortion.

Shoegaze is brooding music that somehow manages to be upbeat and depressing at the same time.

3. Have a Great Day!

You can probably guess from the name—this list is full of happy songs to brighten your day.

You’ll find tracks from Fleetwood Mac, Elton John, Steely Dan, Blondie, and Stevie Wonder.

If you’re stuck, it might help to get a dose of energy with familiar, fun music.

4. Chill + Atmospheric

Do you prefer melancholy music?

Do you like songs with haunting melodies?

Do you like the idea of writing on a rainy day?

If the answer to any of those questions is yes, give this playlist a shot.

5. Melantronic

Spotify describes this playlist as “beautiful electronic music for melancholy moments.”

There’s definitely some sadness here. But don’t expect a playlist that’s going to kill your spirit. These songs have solid beats.

Think Thom Yorke, Caribou, and Aphex Twin.

I’ve found that sometimes I like to write to music in a foreign language. The music is interesting enough to keep me motivated, but I don’t get distracted by the lyrics.

Here are some playlists we liked from around the world.

6. French Indie Pop

This playlist is full of dreamy, mellow French indie pop.

It’s heavy on electronic music and sparkly beats. Think more “low-key Paris” vibe than club-hopping.

7. Japanese City Pop

In the late 1970s and 1980s, the term “City Pop” described a type of music popular in Japan.

City pop borrowed heavily from Western music and had elements of jazz, soft rock, and funk.

If you like yacht rock or need some peppy music, give city pop a try.

8. Soweto Beat/Township Jive

Soweto is a township in South Africa that’s well known for music.

This playlist features mbaqanga music, a style of South African music with Zulu roots that originated in the early 1960s.

It’s upbeat and rhythmic, so it’s great for energetic bursts of writing.

9. Bhangra Bangers

If you like upbeat music that makes you nod your head, this is it.

Bhangra originated in the British Punjabi community during the late 20th century.

It’s got a little bit of traditional Indian folk music, a little bit of hip hop, and a lot of percussion.

10. Spanish Tapas Bar

Only listen to this if you’re looking for a jolt of energy.

This playlist features traditional flamenco and Spanish folk tunes with a quick tempo.

11. Korean Indie/Chill/R&B

This is the longest mix of Korean RnB, pop, ballads, and lo-fi songs on Spotify.

Clocking in at 54 hours, there’s a little bit of everything, from uplifting to downtempo.

If you get easily distracted by lyrics, you still have plenty of musical options.

Classical music, hip hop beats, instrumental versions of your favorite songs, and modern composers can help you find your focus.

12. Japanese Lofi HipHop

This is one of my favorite writing playlists. It’s a collection of lyric-less, Asian-inspired hip hop beats. It’s chill, but upbeat enough that it won’t put you to sleep. I write to this about 50% of the time.

13. Classical Music for Reading

If it’s good for reading, chances are it’s good for writing.

This 2.5-hour playlist features a sampling of pieces from Mozart, Chopin, Debussy, and other famous classical composers.

14. Minimalism

Minimalist compositions are perfect for writing.

They usually have repetitive patterns or pulses or steady drones. They’re easy to get sucked into (without giving them too much attention).

This mix features some of the most iconic minimalist composers: Philip Glass, Michael Nyman, and John Adams.

15. Instrumental Pop Covers

Try this if you like top-40 radio and pop classics but don’t want to lose your focus.

It’s got everything from basic guitar covers to full orchestral versions of songs you probably already know.

16. Composer Weekly: Ryuichi Sakamoto

Japanese musician Ryuichi Sakamoto has played many different styles of music over the course of his career.

Lately, he’s been recognized for his movie soundtracks and piano compositions.

This playlist is a 30-track introduction to his instrumental music. It’s sparse, dark, and contemplative.

17. Relaxing Spanish Guitar

Don’t underestimate the power of Spanish guitar.

It’s full of emotion, quick riffs, and rhythm. It may put some zest in your typing.

18. Ludovico Einaudi Complete Playlist

Ludovico Einaudi is an Italian pianist and composer.

He’s well known for his film and television scores, but this playlist features his solo releases, including a seven-part series called Seven Days Walking , which he released last year.

Game & Movie Scores without Lyrics

Some of the best composers in the world write for movies and video games.

Unless you’re using a specific movie or game to purposely set a mood, I recommend choosing one you’re not very familiar with. That way, the music won’t distract you.

19. DirecTV’s Movie Score Channel (Channel 822)

If you have DirectTV, make the most of your TV’s speakers and tune into the DirectTV Movie Score Channel.

Their non-stop instrumental music is the perfect soundtrack for writing your book.

20. Soundtracks for Studying

This playlist covers everything from Downton Abbey and Braveheart to Ratatouille and Sherlock .

Movie-wise, that’s a big range. But musically, all these songs strike the perfect balance between epic and lowkey so you can focus.

21. Minecraft Soundtrack

Minecraft is the bestselling video game of all time.

There are many reasons people love it, but 1 big reason is the music. It’s the kind of music that makes you feel happy without even realizing it.

It’s “barely there” but still optimistic and motivational.

22. Studio Ghibli Summer Night Piano Collection with Nature Sounds

Studio Ghibli is a famous Japanese animation studio. This 7-hour Youtube collection features piano performances of some of their gentlest music, overlaid with cricket noises.

If you’re looking for something soft and soothing, this is it.

There are many styles of electronic music: electronica, house, techno, drum and bass, jungle, garage, trance, IDM, etc.

If you’re already a fan of electronic music, you might have a favorite type.

While some people can write to rave tunes, most can’t. So, I’ve added some energetic playlists that aren’t too dancy or aggressive.

23. Brain Food

This is subtle, hypnotic electronic music that promotes focus or relaxation.

There aren’t any lyrics, which makes this a good option for people who are easily distracted.

24. Yoga Electronica

This playlist features downtempo deep house. That means it’s a perfect dose of energy without making you want to get up and dance.

You can latch onto the beats, but it’s repetitive enough to help you stay in the writing zone.

25. Mother Earth’s Plantasia

This is a cult classic electronic album by Mort Garson. It was first released to a limited audience in 1976, but it gained wider circulation when it was re-released in 2019.

The album features “warm Earth music” designed to help plants grow. It’s sweet, hopeful, and spacey.

If you like Moog synthesizers and fantasy, you’ll love Plantasia .

26. Women of Electronic

This list features women who make innovative electronic music. Most of the tracks have lyrics.

This playlist offers a wide range of styles. For example, Yaeji is a Korean-American artist who sings over house beats in a quiet, mellow voice.

Kaitlyn Aurelia Smith uses synthesizers to create layered, elaborate songs.

And Charlotte De Witte is a Belgian DJ known for her “dark and stripped-back” techno.

When we asked the Scribe Crew for playlist recommendations, this was by far the category that got the most responses.

Ambient noise is a great option if you hate working in total quiet but also get easily distracted by music.

It’s also a helpful workaround if you like working in coffee shops or coworking spaces but can’t right now because of the pandemic.

Ambient sounds can give you the impression that you’re out of the house even if you’re still sitting at your desk.

27. My Noise

This is, hands down, the coolest ambient noise and white noise generator.

It’s run by an engineer and sound designer who collects recordings from around the world.

It has everything from Tibetan bells and waterfalls to street recordings and gardens.

28. Coffitivity

Many writers love to write in coffee shops, but you may not have that option if you have a l imited time frame (or if you’re still under COVID lockdown).

Streaming background noise on Coffitivity can give you the feeling that you’re in a coffee shop even when you aren’t.

You can also choose between different levels of activity. For example, “Morning Murmur” is less hectic than “Lunchtime Lounge.”

29. Rain Sounds

I LOVE the Spotify playlist that features rain sounds. I like to curl up on a rainy day and just chill, and the rain sounds create that mood. It’s a gentle and soothing way I use to get into writing, and it helps keep me in my flow state once I get there.

30. 8 Hours of Ocean Sounds

These calming wave sounds were recorded at Playa de Piticabo in the Dominican Republic.

With 8 hours of recordings, you could literally listen to them all day if you want some soothing background noise while you write.

31. OM Chanting @ 417 Hz

These Om chants are repetitive and positive. They can help you tune out the outside world and get into a meditative pattern.

32. Binaural Beats: Focus

When you hear a slightly different tone in each ear, it creates a binaural beat. Your brain falls into sync with the difference between the tones’ frequencies and creates an auditory illusion.

Binaural beats can lower stress, promote creativity, and encourage relaxation. This playlist is designed to enhance your focus.

The Scribe Crew

11 Pieces of Inspiring Music for Writing

Inspiring music to help you start writing.

I love inspiring music that compels me to start writing. Music is a lot like a story: It has a beginning, crescendo, and an ending. Whether instrumental or with lyrics, music has been a lifeline of mine for years. A good song can lighten my chest or tear my heart out, and I love both feelings.

If you enjoy inspiring music for motivation, inspiration, pleasant background for writing, or simply to relish in good songs, I’ve curated a few pieces you may like.

So, here are some of my memorable songs, what they mean to me, and why you may like them.

Song 1: All I Have by NF

During the writing of my first novel draft for The New Dawn (working title), I listened to this song probably everyday for over a month. In the lyrics, NF talks about his raw desire to be a rapper, and why it’s so important to him.

This song helped me realize how powerfully I felt about writing my stories, and gave me validation that I was not crazy to put my effort into something creative.

When I felt my drive wavering, I loved listening to this song. To this day, it is one of my favorite listens. You may find it inspiring as well.

I am a huge fan of NF. If you liked All I Have, I encourage you to try his later albums as well. They are emotional, real, and clever.

Visit NF’s website here.

Song 2: Audiomachine

For some symphonic and electric scores to listen to while writing, you should try Audiomachine. They have a whole lot of albums, and many different moods of music.

Their scores can be beautiful, eerie, light, or dark. Highly recommend you give them a listen on YouTube , Spotify , or your music service of choice. I’ve linked to one of their YouTube playlists below to get you started.

Audiomachine is a also great starting place to find similar orchestral and cinematic artists.

Visit Audiomachine’s website.

Song 3: Eschaton by Tony Anderson and Chris Coleman

I have been listening to Eschaton on repeat for a few of the scenes I’m writing for my novel The New Dawn (working title).

It’s an instrumental song with a breathtaking crescendo—the strings just wash over me while I write. This piece puts me in a perfect mood for crafting emotionally charged scenes, and may do the same for you.

Song 4: Tommee Profitt, Artist and Producer

Tommee Profitt produces amazing cinematic music. I probably listen to at least one of his songs everyday, and am always inspired. Highly recommend giving his music a listen.

Below is the Cinematic Songs (Vol. 1) playlist to get you started.

Visit Tommee Profitt’s website.

Song 5: Chillstep and Epic Music Mixes

When I first started a writing habit, I listened to chillstep music mixes on Youtube while I wrote. I still go back to these mixes from time to time, because they are simply great.

I also recommend epic instrumental music mixes on YouTube. You can find both uplifting, dark, and emotional moods in these mixes. Just type what you’re looking for into YouTube’s search bar.

To get you started, I’ll link to a couple mixes I have enjoyed.

Song 6: Movie Soundtracks

When I stumble across a movie or TV show with a similar vibe to my own stories, I’ll look up the soundtrack and use it for inspiration.

However, sometimes soundtracks to my favorite movies and TV shows are never officially released. Or, they use songs from various artists and I don’t have time to track all that music down. When this happens, I’ll do a quick search on Spotify or YouTube, and if I’m lucky someone has made a playlist for me with those songs I want to find.

So give listening to a soundtrack of your favorite a shot.

Song 7: This Mountain by Faouzia

I love songs about overcoming obstacles, and This Mountain by Faouzia is a great one. As soon as I heard it I hit the like button on Spotify.

If you need a little courage to face your writing session, play this song.

Visit Faouzia’s website.

Song 8: Ruelle

I love Ruelle. Whether I’m searching for dark or light music, she has a unique, dramatic feel I enjoy. Whether for writing or listening throughout the day, Ruelle is a great option. Below is her Earth Glow playlist to get you started.

And again, she is a great place to start when searching for similar artists.

Visit Ruelle’s website.

Song 9: Got It In You by BANNERS

When you begin to seriously doubt your ability to write, or you feel like your effort isn’t paying off, listen to Got It In You by BANNERS and remember that you are capable of overcoming your struggle.

You are stronger than you think you are. Despite what you may feel sometimes, you have it in you to be a writer.

Also, check out BANNERS’s album Where The Shadow Ends —it’s an uplifting and inspiring one.

Visit BANNERS website.

Song 10: Toxic Thoughts by Faith Marie

Maybe it’s the typewriter sound in the background, but this song seems the perfect fit for a writer, especially one struggling with doubts, anxiety, or perfectionism.

Toxic Thoughts poetically carries you through a journey of struggling to write, and to having hope in overcoming the obstacles your mind presents. Plus, the music is beautiful.

Song 11: Lunatic by Andy Grammer

This is a fun song about writing—songwriting, but I think it can be adapted to fiction writing. I love this songs cause it gives us permission to be our creative selves, and to not worry about how other people may judge our life to be a bit weird.

Have faith in your dreams, and go for it.

Andy Grammer’s album Naive is another of my absolute favorite listens. Give it a try!

Visit Andy Grammer’s website.

I hope you find some pleasure and inspiration in my above selections. Inspiring music can be such a powerful tool for us, whether to lift our spirits or transport us into the world of our stories for writing.

Whether you’re a beginning fiction writer or looking for resources to help you hone your existing writing skills, join my newsletter for bonus content, updates, special offers, and INSTANT access to the Library of Resources!

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Sarah Siedenburg is a blogger, author, freelance proofreader, and copy editor with a passion for stories and helping beginner writers finish novels. In her past life she was hired as Editor for a start-up interior design magazine, although she knew very little about the world of luxury interior design when she began.

Her blog talks about all things creative writing, and she is the creator of the guidebooks Character Presentation: The Advanced Guide to Character Description and Before the First Draft: The Plantster’s Guide to Pre-Writing , as well as the online course “How to Write a Novel: An Email Course for Writers.” Sarah lives amongst the noble evergreens in the northwest corner of Washington state.

“The light shines in the darkness, and the darkness has not overcome it.” — John 1:5

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Writers in the Storm

A blog about writing.

10 Ideas For Inspiring Your Writing with Music

by Ellen Buikema

“Music gives a soul to the universe, wings to the mind, flight to the imagination and life to everything.” – Plato

Music, the art of sound through the use of rhythm, harmonies, and melodies, is food for the soul—divine, effective, mathematical – the science of sound. Its language is universal.

A tuneful writing exercise

Music has the ability to spark our imaginations. Here’s how to channel that muse into inspiration for your writing. Turn on a tune that you love and listen carefully.

Where does the music take you?
What memory does the music send you to?
How does the music make you feel?
Now use that song to envision a character or setting.
Then take a few minutes and write what the song inspired in you.

Music to get us motivated

For those weeks full of Mondays when nothing is going right, turn on a get-moving playlist to drag yourself to your writing space.

I’m a fan of “Happy” by Pharrell Williams. This song always brings a smile to my face and makes me feel peppier. One writer and filmmaker recommends “In One Ear” by Cage the Elephant, a very high energy, edgy sound. Here are 52 motivational songs to get you pumped.

Score your novel

Many writers choose music based on the mood of the scene they’re developing. While listening to Wagner’s “Ride of the Valkyries,” conjure writing scenes of slicing through the waves via tall ships or helicopters soaring through clouds on the way to battle. I’ve tried this but it doesn’t work for me. I always hear Elmer Fudd singing, “Kill the wabbit …” when I listen to this piece of the opera Die Walküre . I guess I watched too many Warner Brothers Cartoons growing up.

For romance, light classical music works well. “Iris” by the Goo Goo Dolls, used in the movie City of Angels , is a fine example. Here are 24 lovely examples in a one hour set to help with the mood.

Soundtracks swell as they maneuver your protagonist through a crime scene. Check out this crime thriller background music .

Australian science fiction author A.C. Flory uses music that fits the mood of what she’s writing. Every once in a while she shares the music she’s found that fits the mood of the piece perfectly. Here’s a recent example .

Music can transport you just about anywhere. I can remember slow dancing (okay, it was that eighth grade hug-and-waddle) to “Knights in White Satin” by the Moody Blues. If I need to return to the emotions of that time all I have to do is hear the tune and it all comes flying back to me. Not that I really want to revisit adolescence and all that teen angst. Ew . But if I need to make my way there, music is a fast ride back.

Songs from long ago or far away

If your setting is in a foreign land, music from that nation will help you get a feel for your characters and scenes. Let’s say that you are writing a scene that takes place in the American Southwest. An easy way to travel there is to listen to Native American music , deep and hauntingly calm.

If your setting is Spain, the Spanish guitar may lend inspiration. I chose Andrés Segovia for an example as I have seen him in concert and he was marvelous.

For scenes in the Australian outback listen to the drone of the didgeridoo . Lewis Burns, an ambassador of the Aboriginal Tradition, uses circular breathing for continuous sound. I can’t imagine how difficult this is to do.

Should we write while listening to music?

Neuroscientist will answer a resounding “No.” According to these scientists when we try to multitask, like write while listening to a song, or texting a friend and listening to a family member, our brain burns glucose at a faster rate and releases cortisol because our brain tries to give equal attention to all the incoming stimuli. They posit that writing while listening to music induces stress. That said, this does not seem to be the case.

Classical music played at a low volume may increase concentration. Low level ambient sound may improve creativity.

A friend grew up near an opera house in New York City. She did her homework while listening to the loud music emanating from the stage and orchestra pit. She prefers to write while listening to classical music set at a high volume. Experiences differ.

Music with or without lyrics

Instrumentals like jazz and classical can allow the world to slip away. Music with lyrics seems to be the problem child as songs with lyrics cause some writers distraction. There is always the possibility of the lyrics finding their way into dialogue.

An odd music related aside

According to one study published in 2012, people who ate at low-lit restaurants where soft music was played consumed 18% less food than those who ate in other restaurants. Not so good for the restaurant, but I wonder if writing in a low-lit writing cave while listening to soft sounds will cause less snacking.

Whatever you decide, the music you play while writing must inspire you and your book.

Do you listen to music while you write? Which comes first, the tune or the tale? How does music affect your work? Do you use music local to the story to help you get in the mood for writing those scenes?

* * * * * *

About Ellen

Author, speaker, and former teacher, Ellen L. Buikema has written non-fiction for parents and a series of chapter books for children with stories encouraging the development of empathy—sprinkling humor wherever possible. Her Works In Progress are, The Hobo Code , YA historical fiction and Crystal Memories , YA fantasy.

Find her at http://ellenbuikema.com or on Amazon .

Top Image by S. Hermann & F. Richter from Pixabay

23 comments on “10 Ideas For Inspiring Your Writing with Music”

Interesting post, and some good ideas. I listen to classical radio all day, and I'd find it hard to write in silence - or distracted by the sounds of the neighbourhood.

I am right there with you regarding neighborhood noise. That can really be jarring. When we lived in Mazatlan we were exposed to the blaring of various radios from open-air taxis and live bands traveling along the beach all afternoon and much of the night. Impossible music to write to, at least for me.

I can only write in two kinds of noise - absolute silence, to the tune of noise-canceling headphones, or the cacophony of a bar or coffeeshop. Bar noise is the best, because I worked in bars in college and I'm used to reading and studying in that environment. But that at-home peaceful quiet of an empty house is pretty awesome too. 🙂

Silence is blissful! I keep threatening to buy some noise-canceling headphones.

You make a good point regarding working in an enviroment that you are used to. That makes a lot of sense.

Like Jenny, I'm an absolute silence writer, too. Even on the most beautiful summer day, I can't write outdoors for long, as the damn cars and birds and flies are too distracting. (Cue eyeroll.) BUT, Ellen, you've inspired me to make a writing playlist that I can use to get the gears turning, and turn off when necessary.

Ooh! Send us your playlist when you have one.

I've tried writing outdoors but fall prey to the "Look! There's a squirrel" syndrome. I'm easily distracted.

I used to have a one-hour playlist. Mostly mood music, but a few with lyrics. It became so familiar I didn't "hear" it anymore, but it was part of the writing. Then, more recently when I was writing Remaking Morgan, which revolved around a classical pianist, I asked Alexa to play classical piano. What I discovered was the dog came in to listen, and I've been playing classical music in my office ever since. She seems to enjoy it.

So your playlist became white noise for you. Interesting! Do you keep the classical music at a low level while writing?

How wonderful that your pup enjoys the music, too.

Not exactly white noise, because the moods were still there. I keep the volume moderate--background. After all, dogs have excellent hearing! 🙂

I became a believer in the power of music to influence the content of writing when teaching English class to sophomores in high school. On a day when the minds of my students were rushing to summer vacation, I played three pieces of classical music (unfamiliar to most of them). Two of those pieces--Ravel's "Bolero" and Offenbach's "Gaite Parisienne" had pens pushing on paper! And my students finding they had something to say.

How awesome is that!

I know a fourth grade teacher who dims the lights, turns on a long stream of tiny orange lights, and plays spooky music during writing time just before Halloween. She calls it Spooky Writing. The students love it and write some interesting stories.

Did you use Ravel's "Bolero" before or after Blake Edwards' movie '10' ?

Ellen, this is a good one! In my case i like quiet while I'm actually writing, but I have developed a lengthy (over 6 hours) playlist of oldies -- Doors, Stones, Beachboys, and, yes, the Monkees' underrated "I'm Not Your Stepping Stone" -- that I listen to while I'm editing. So it depends on what stage the WIP is at. Thanks for a cool essay!

Thank you, James!

I love the Monkees and have endured lots of teasing because of it, at which I smile. My taste in music is eclectic.

I find it interesting that you listen to different tunes depending upon the writing stage.

Hi, Ellen. Yes, when I'm actually putting new words on paper I can't use the playlist (I agree with the neuroscientists you mention in the essay), but it seems to help when I'm revising. Maybe I can edit longer, waiting for "one more song." And I've taken my share of teasing for Monkees music, too. Great to find another fan!

I wrote 52 short stories in 52 weeks with music from Youtube.com https://www.youtube.com/watch?v=sAcj8me7wGI&t=7974s This is OCB Study and Relax Music (mostly piano).

This is lovely, Cheryl. Thank you for sharing.

Yes, I find I do more of my best work with music playing. Somehow it helps me focus, rather than causing a multi-task issue in my experience. I also use music to fit the approximate decade of my fiction and that really helps. I know some writers say it's better not to listen to songs with lyrics, but that doesn't bother me at all. There is something settling about music for me, and keeps me focused and in the chair. Without music in the background, I pop up out of the chair more often for all sorts of distractions like snacks, drinks, small chores that suddenly need attention etc. So I was happy to see this article. Music might not be good for everyone's concentration, but it is the best thing for me. Thanks for posting it.

We are all so different. You have to use what works best for you.

A good friend listens to punk rock when he is writing a rant. I like to listen to music with lyrics when I'm painting, but not while writing.

I'm happy that you've enjoyed the post!

Thank you, Ellen, I have a music score in my ALBINO WOMAN Story. Right now, I'm immersed in listening to poetry readings on You Tube. I intend to write a unique poem between each section of TOXIC TIMES.

Hi Elizabeth! I remember your Albino Woman story from critique group. You are so good with dark and gritty. I look forward to reading your next works.

I listen to music while I write. It serves several purposes: if I'm actually paying attention to the song, it may inspire a scene, it drowns out other noises in the background, and as part of TRT, it provides a neutral noise to drown out tinnitus.

Glad you've brought up the use of background noise to drown out tinnitus. Excellent point. Thank you Denise!

I suppose I am different to most here. I like listening to music, softly, in the background whilst I am writing. It does not affect me but it does infect me, the cadence, style and lyrics play with what I am writing. If I listen to "the cowboy Junkies" (just an example) the tale becomes more folksey, clever, homegrown. "KIng Crimson" and it grows esoteric and fulfilling, the poetry of Pete Sinfield, pumping up my lyricism. The huge crescendos bring words unused for years from me, only to be forgotten again when written, at times Bach and Tchaikovsky illicit similar verbose literacy. Yet the truly best for me (all will have their own choices) to encourage what I wish to write are Mike Oldfield and Tangerine Dream.

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Best Music to Listen to While Writing a Paper

Pooja Kashyap

Writing a paper can be challenging, especially when facing a looming deadline or struggling to develop ideas. Fortunately, music can be a powerful tool to help you stay focused and motivated while writing. But what is the best music to listen to while writing, and what features should you look for in a writing playlist? That’s where this post comes in. We’ll explore the best types of music to listen to while writing and provide tips for creating a writing playlist to help you stay focused and productive. Stay with us and read along!

What is the best music to listen to while writing?

The best music to listen to while writing is instrumental or ambient music with no lyrics. You should avoid music with lyrics because they can be distractive, interfering with your line of thought and making it difficult to concentrate on your work. On the other hand, instrumental music can help you get into a flow state and stay focused on writing your paper. Therefore, if you need music to listen to while writing, this class should be on your list.

What type of compositions can we consider instrumental? Many different types of instrumental music can be effective for writing, including classical, electronic, and jazz. Let’s look at these genres and explore their benefits for writing.

1. Classical music

Classical music is the art music of the Western world. It improves cognitive function and helps to boost concentration whenever you need to focus on highly engaging work. Classical music is good to listen to when you need to relieve stress and cool yourself off anxiety, leading to better mental strength to handle massive writing projects. In addition, listening to music before undertaking a creative task can increase divergent thinking and help you generate new ideas. Therefore, if you are looking for the best music to listen to when writing an essay, classical music may be your best option. Some great classical composers to listen to while writing include Bach, Beethoven, Mozart, and Chopin. These composers have a timeless quality that can help to create a calming and focused atmosphere for writing.

2. Electronic music

Electronic music, such as ambient or downtempo, can create a relaxed and focused atmosphere. The search for technical resources and modes of expression characterizes it. They have repetitive beats and soothing sounds that help to block out distractions and create a sense of flow. Some great electronic artists to listen to while writing include Brian Eno, Aphex Twin, and Boards of Canada. These artists create ambient and atmospheric music that can stimulate creativity and focus.

3. Jazz music

Jazz music is an excellent choice for writers looking for something more upbeat and lively. The improvisational nature of jazz can stimulate imagination and break up the monotony of a long writing session. It is good music to listen to when you need to focus and build on your creativity. Some remarkable jazz artists to listen to while writing include Miles Davis, John Coltrane, and Thelonious Monk. These artists are known for their innovative and dynamic compositions, which can help to keep you engaged and focused while writing.

Choosing the best music to listen to while writing a paper can be tricky when you are not a music major. It gets more challenging when you have several options, calling for needing expert opinion. Luckily, you can consult a paper writing service by CustomWritings to get a well-written descriptive custom essay on music to have a good reference for your choice. The company has experienced music writers and scholars who understand the different genres, their composition, and their impact on one’s emotions. As a result, they can help write quality description papers that cover the key characteristics of the specific music genres to help you make a decision. Consultations are free, and the cost of paper is cheap, so you don’t have to worry about spending much on the service.

Music to listen to while writing an essay: Top tips for making a good playlist

When choosing the best music to listen to while writing an essay, there are a few key features to look for. Here are some tips to help you create a writing playlist that will help you stay focused and productive:

Match the tone of your writing : One of the essential features of music to listen to while writing an essay is that it should match the tone and style of your writing. If you’re writing an article faster, such as a persuasive or argumentative essay, you may want to choose music with a more upbeat tempo. If you’re writing a reflective essay, you may want to select slower and more contemplative music. The choice of music ensures the environment is in sync with your thought process, leading to higher productivity.

Avoid distractions : When choosing music to listen to while writing an essay, avoiding anything that could be too distracting is essential. For instance, avoid music with lyrics, as the words could interfere with your thoughts and ideas. Instead, look for instrumental music or ambient sounds that can create a calming background for your writing. Such a choice will ensure that you get a bit of entertainment while at the same time having the chance to self-introspect and write well-thought-out essays.

Create a writing routine : Creating a writing routine can help you stay motivated and productive. One way to create a routine is to listen to the same music every time you write. This can help signal your brain that it’s time to focus and get to work. In addition, it enables you to train your brain to work within a given environment setup, saving you from having to endure chaos within your study space.

Use music as a reward : Another way to use music to enhance your writing is to use it as a reward. For example, you may want to listen to a favorite album or playlist after you’ve completed a certain amount of writing. This can motivate you to stay focused and productive, knowing you have a reward waiting for you when you finish. In addition, it helps you feel content with your work as you get the chance to reflect on the milestones covered.

Keep it simple : When it comes to music to listen to while writing an essay, it’s essential to keep it simple. Don’t spend too much time searching for the perfect playlist or the ideal album. Instead, choose music that you enjoy, and that helps you stay focused and productive. Writing becomes more pleasant, efficient, and effective with the right music.

Take a step to improve your writing experience

As a matter of fact, listening to music while writing is the best way to relax the brain and improve creativity. However, one must be careful when choosing the type of music to listen to at such crucial moments. This article has explored some pertinent issues relating to music and the writing world, including the best music genres to listen to while writing and some tips for developing a playlist. We hope this will be useful as you work toward writing quality papers.

Read Here: The Effects of Music on a Student’s Schoolwork

Written By:

Pooja Kashyap, a spirited wordsmith, avid reader, and music connoisseur, seamlessly blends her love for literature and melodies in a unique symphony of storytelling. As an intuitive writer, Pooja crafts literary compositions that transport readers into the enchanting world of musical tales, creating an immersive and harmonious experience. With a keen journalistic touch, she invites you to embark on an adventurous journey through her written narratives, promising a captivating fusion of words and melodies. Join Pooja Kashyap for a literary adventure where stories and music entwine, offering a harmonious escape for the soul.

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Motivational Songs to Get You Through Your Assignments

Posted by: Charlotte

Tags: advice ; exams ; mental health ; music ; studying

December 23, 2019

With the end of semester one done and dusted, and a new batch of modules ready to launch next month, many of us will be looking to power through our final few assignments and pieces of exam preparation over the Christmas break.

But what do you do when your motivation is fading, and the thought of slouching in front of the TV with a mince pie threatens to get the better of your study plans? For me, music is always the way forward, to kick me out of my funk and back into focused revision-mode! So here are my top picks for the best songs to get you through that final hour of work before you clock off for the holidays:

‘Survivor’- Destiny’s Child

This power pop anthem is the definition of a fist-pumping rouser – which makes it the perfect wake-up call when a morning of essay writing dawns!

‘Tubthumping’- Chumbawamba

Cheesy and cringe-worthy it may be, but when that word count seems to be slipping further from your reach, sometimes a bit of screaming along unashamedly to a footie classic is exactly what you need!

‘We Are The Champions’- Queen

With an opening that begs to be sung in a melancholy tone in front of a rain-streaked window, which builds to a symphonic chorus line that will have you reaching for the sky and feeling every bit the queen (see what I did there?)

‘Gold Steps’- Neck Deep

When the world feels rough, songs you can throw yourself around an imaginary mosh pit to are the perfect remedy! Packed full of rippling guitars and with lyrics that are as punchy as they are profound, you can’t go wrong with this classic pop-punk banger!

‘Deadweight’- I Prevail

For those with a taste for the heavier things in life, metalcore’s rising stars, I Prevail, have you covered. Need a track to motivate you to cut out those that drag you down? ‘Deadweight’ is the perfect companion.

‘Here Comes the Sun’- The Beatles

Sometimes, all you need when you’re stuck in the quagmire of referencing is a light-hearted little pick-me-up, in which case, you can’t beat this summery classic. If it ain’t broke!

‘This Is Me’- The Greatest Showman Movie Soundtrack

Yes, I know it’s been played to death, and yes, you probably were sick of hearing it everywhere this time last year! But a song about believing in yourself, shaking off negativity, and being unapologetically proud of your achievements? Sign me up!

‘Can’t Stop’ – Red Hot Chili Peppers

Feeling a little spaced-out and psychedelic? Why not match your music choices to that feeling, and indulge in some pumped up weirdness from the Red Hot Chili Peppers?

‘Rebel Girl’- Bikini Kill

Want to feel like a kick-ass queen who can conquer the world in under 3 minutes? Bikini Kill, recently reformed feminist punk legends, carry confidence in spades, alongside a grumbling bassline that is sure to stoke the fire in your belly back to full, flaming force!

‘Eye of the Tiger’- Survivor (from ‘Rocky’)

I can personally attest to the fact that this song is all that got me through the long slog of revising for my Physics GCSE papers, so rest assured that this can be the final push of pep into your step that will get you over the finish line to submitting that tricky assignment!

‘Stronger’ – Kanye West

Heartbeat-esque, pulsating synths, and that irresistibly repetitive chorus – what more could you ask for from a motivational track? Perfect for whether you’re making the Everest-like climb up the stairs to the library or flicking through books looking for that perfect reference.

‘Lose Yourself’- Eminem

The only danger with this uncompromising track is that you end up memorising all the lyrics rather than the flash cards you have just made (speaking from experience again here!), but when walking into an exam or heading for a meeting with your tutor to discuss an assignment, there’s nothing better for getting you walking with your shoulders back and your head held high.

‘High Hopes’- Panic! at the Disco

Another one that you’ve heard on every radio station the world over lately, I know, but that doesn’t detract from the elevating power of Brendon Urie’s soaring vocal lines, and the promise that you too will make it to where you deserve to be, once that final paper is submitted!

‘Titanium’- Sia

Throwing it back a little here – it’s hard to believe that this song will be 10 years old next year! Though 2011 seems like an age ago for many of us, this pure pop sensation still packs a great deal of punch!

‘Dog Days Are Over’- Florence and the Machine

As the end comes into sight, that tinkling piano starts automatically playing in the back of my mind, such is the pure elation contained within this song’s lyrics and melody! You’re almost at the finish line!

‘Right Back At It Again’- A Day to Remember

And at the end of it all, when you finally press submit on that assignment, and watch the notification pop up on your screen, you feel like reaching for the sky… that is, until you remember the next paper that is waiting for you! It might feel a little like groundhog day, but don’t worry – A Day to Remember have been there too, and they made it out alive! So, onwards and upwards!

What do you think of our list? Do you have any more songs that you want to add? Let us know by commenting below, and we’ll keep this playlist updated with all your best suggestions!

For more great studying tips and advice, check out Helena’s post on how to change up your study routine to keep that motivation going 👊

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Music: The Best Tool for Motivation

Categories: Motivation

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Published: Dec 5, 2018

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Ai or not ai a student suspects one of their peer reviewer was a bot, how to summarize a research article, loose vs lose, how to cite a blog, apa paraphrasing, reasons to look for inspiration in music essay sample, example.

The styles of music can vary greatly. It takes a discerning listener to classify a particular song, as it may have strains of several music trends. Besides trends, each culture produces its specific music. To me, music is more than just a way to relax and take a break. Music is my companion for life, my indicator of mood, my best adviser, and my own little world. I would never call music a hobby, as I cannot imagine my life without my favorite music. There is a playlist for when I am sad, for when I am happy, for when I am thoughtful, excited, angry, adventurous, or sleepy. Music helps me to cope with the emotions that I experience. Sometimes, music is a way to hide from everything and everyone. Other times, music is the best way to share my feelings with people I care about, or even with complete strangers. Music is the most inspirational phenomena I can think of for a multitude of reasons.

Music is a world of emotions and every time I hear a song I like, it shares some of these emotions with me. Music can bring up the most tender and anxious feelings. It can move you in time and space by bringing back special memories of which you were craving to relish. There were many cases when music sent shivers down my spine, so honest and strong were the tunes, so powerful the memories they awakened. I am sure it happened to everyone at least once, that a strong memory is somehow linked to a certain song or tune and whenever you hear it playing, you travel back to that situation in your thoughts, able to experience that it again (Connors 65). We sometimes forget how powerful music is and how inspirational its power can be.

In addition, music is able unite people like nothing else can (Poplars 45). Sports, mutual interests, and similar experiences can unite people in a substantial way. But what about those cases when people have nothing in common and are total strangers, yet they suddenly find themselves holding hands and singing along, dancing, or simply silently listening to captivating beats. Music is able to make complete strangers feel like they have connected to a kindred soul. If you have at least once been to a great live concert, you probably know what kind of inspiration I am talking about. It is difficult to describe this phenomenon with words, but is it not what proves again the power of music to inspire? You do not need to speak a foreign language to connect to somebody from a different background, using music instead of words. Music comes in handy in these cases. It inspired you to make new friends or learn more about a foreign culture.

Music is multi-dimensional—you can never get bored of it. While I have a number of favorite artists and bands, I also never stop exploring the musical amplitude and discovering new performers every day. Music adds flavor to my life and this flavor is different depending on “what dish I am eating.” Music can be so much more than an accompaniment—it is a full-fledged spice that can accentuate, muffle, or supplement any experience. If I were to leave for a deserted island and could only take a few items, my player and a couple of solar-charging batteries would be my choice. That way, I could adjust to the environment around me and find inspiration where others might find devastation and frustration.

Though music is nothing new, the creation of new melodies, rhythms, and symphonics will be created every day. In fact, I believe music has been around us for as long as we have existed (Lung 24). When I say that music is everywhere, I first of all mean that music comes from nature—the sound of crackling straw in the field, rustling trees in a grove, or the murmur of a fast mountain stream. Music in all of its forms is around us and the task is only to notice it and learn to appreciate how it can be shared. Music can be a source of inspiration for almost anyone, since it can be a unique key to suite any lock, even the most complicated and tenacious. Music has the power to make us want to smile at every stranger walking by, simply because we are hearing a transcendent song.

Cannus, Brian. Zen of Music . Brighton: Old Owl Press, 2012. Print.

Connors, Latasha. Musical Memories . Manchester: Random House, 2011. Print.

Poplars, Anna. Unification through Vibrations . New York: Penguin, 2008. Print.

Lung, Nicholas. Origin of Humankind is Music . Dallas: Vibrato Press, 2003. Print.

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431 Music Essay Topics & Ideas

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Music essay topics explore diverse areas of music for academic or personal writing. This comprehensive collection of ideas encourages intellectual curiosity with topics ranging from historical musicology to contemporary pop culture. It also offers thematic ideas, like examining musical elements, understanding music’s societal influences, or analyzing distinct music genres. Aspiring musicologists, students, or avid music enthusiasts will find this article highly valuable for its broad spectrum and adaptable nature, suitable for various writing levels and interests. In this case, people delve deeper into music’s rich legacy, challenging them to form original perspectives and contribute to the larger discourse on music. Hence, this article on many music essay topics is a valid resource for unlocking the academic and artistic potential of music.

Hot Music Essay Topics

The Cultural Impact of British Invasion Bands in the 1960s
Decoding the Evolution of Hip-Hop from the 1970s to Today
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The Pervasive Influence of Jazz on Contemporary Music Genres
Punk Rock as the Soundtrack of Rebellion and its Sociopolitical Significance
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Evolution of Pop Music Genre in the 21st Century
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Societal Relevance of Protest Songs in History
Examining the Relationship Between Music and Emotion
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Beatles’ Effect on Rock ‘n’ Roll Development
Comparison Between Baroque and Renaissance Music
Exploration of Music Therapy and Its Benefits
Film Scores: Music’s Pivotal Role in Cinema
Interrelation between Dance and Rhythm in Music
Globalization’s Impact on World Music Genres
Cultural Representation in Broadway Musicals
Feminism in Pop Music: Empowering or Exploitative?
Genre Fusion: How Reggae Influenced Hip-Hop
Psychological Effects of Music on Human Behavior
Depiction of Love in Country Music Lyrics
Dissecting the Business Model of Streaming Services in the Music Industry

Interesting Music Essay Topics

Unraveling the Impact of Music on Cognitive Development
Globalization and Its Influence on Music Genres
History and Evolution of Jazz: A Cultural Perspective
Healing Powers of Music: Fact or Fiction?
Pop Culture’s Influence on Contemporary Music
The Role of Music in Social Movements
Analyzing the Cultural Significance of Hip-Hop
The Science Behind Music’s Effect on Mood
Exploring the Artistic Value of Album Cover Designs
Autotune and Digitization: Blessing or Curse for the Music Industry?
Representation of Gender and Sexuality in Pop Music
Ethical Implications of Music Streaming Services
The Connection Between Music and Emotions: A Psychological Analysis
Evolution of Music Production Techniques: A Technological Study
Indie Music Scene: A Study of Its Growth and Impact
Music Festivals: Economic and Cultural Implications
Music Education: Its Importance in Schools
Role of Music in Film and Television: A Comprehensive Analysis
The Phenomenon of K-Pop: Cultural Exchange and Globalization
Copyright Laws and Their Impact on the Music Industry

100 General Music Essay Topics

The Future of Music: Exploring AI and Machine Learning
Nurturing Music Education in Schools
Ethical Considerations in Music Piracy
Women in the Music Industry: Breaking Barriers and Empowering Change
Reggae’s Global Impact on Music Styles
Unveiling the Popularity of K-Pop
Music’s Impact on Cognitive Development
Music Censorship: Perspectives from Around the World
Cultural Identity Formation and the Power of Music
The Interplay of Music and Politics
The Cinematic Power of Music: Exploring Soundtracks
The Music Festival Business: Strategies and Successes
The Emergence of Indie Music: A New Era of Creativity
Latin Music’s Influence on Global Pop Culture
Music’s Role in Enhancing Physical Performance
The Science Behind Sound: An Introduction to Acoustics
Exploring the History of Electronic Music
The British Invasion’s Impact on American Music
Music’s Therapeutic Role: Healing and Transforming Lives
Boy Bands and Girl Groups: Cultural Phenomena in Music
Motown Records: Shaping Music and Culture
Country Music’s Influence on American Identity
The Sociology of Music: Exploring Fan Culture and Subcultures
Music’s Emotional Power: Understanding Mood and Emotion
The Evolution of Music Videos: From MTV to YouTube
Reviving Vinyl Records in the Digital Age
The Beatles’ Enduring Legacy in Modern Music
Streaming Services and the Changing Landscape of Music Consumption
Unraveling the Psychology of Musical Preferences
Music Globalization: Bridging Cultures and Connecting Hearts
Music’s Role in Spiritual and Religious Practices
The Fusion of Music and Visual Arts
Music and Mindfulness: Exploring Meditation and Sound
Blues Music: A Cultural Significance
Opera’s Influence on Modern Theatrical Music
Transforming Music Production in the Digital Era
Music’s Impact on Childhood Development
Rock and Roll: Revolutionizing Social Change
Ethnomusicology: Understanding Music in Cultural Context
The Complex Relationship Between Music and Violence
Music’s Role in Promoting Social Inclusion
Punk Music’s Impact on Youth Culture: Rebellion, Expression, and Identity
Copyright Laws in Music: Balancing Protection and Creativity
Harnessing the Power of Music in Advertising: Soundtracks, Emotions, and Branding
LGBTQ+ Representation in the Music Industry: Breaking Barriers and Amplifying Voices
The Influence of Gospel Music on the R&B and Soul Genres: Roots and Inspirations
Music’s Cultural Role in Indigenous Communities: Tradition, Identity, and Resilience
Music’s Impact on Workplace Productivity: Boosting Focus, Motivation, and Performance
Disco’s Influence on Dance Music: Rhythm, Groove, and Dancefloor Revolution
Music as a Voice of Protest: From Folk Anthems to Punk Anthems
Grunge Music: The Rise of Alternative Rock and Its Lasting Impact
Music Sampling: Artistic Innovation or Plagiarism Debate?
The Influence of Rap Music on Modern Poetry: Rhyme, Rhythm, and Social Commentary
Music Technology’s Impact on Live Performances: Innovation, Integration, and Audience Experience
Music’s Narration in Film: Enhancing Emotion, Atmosphere, and Storytelling
The Evolution of Music Genres: Shaping Sounds, Styles, and Cultural Trends
From Vinyl to Digital: Exploring the Art of DJing and Its Technological Transformations
Music’s Role in Language Learning: Enhancing Linguistic Skills and Cultural Understanding
Music’s Contribution to Raising Awareness of Sustainable Development Goals
Exploring the Frontier of Music in Virtual Reality: Immersive Experiences and Creative Possibilities
The Role of Music in Video Games: Immersion, Atmosphere, and Player Engagement
Evolving Children’s Music: From Traditional Rhymes to Educational Entertainment
The Impact of Online Channels and Social Media on Music Promotion: Reaching Audiences, Building Communities
Classical Music’s Influence on Cognitive Abilities: Memory, Focus, and Mental Development
Flamenco Music’s Cultural Significance: Expressing Passion, Heritage, and Identity
The Evolution and Impact of Music Television Channels: Shaping Popular Culture and Music Consumption
Folk Music’s Influence on Modern Singer-Songwriters: Traditions, Storytelling, and Contemporary Expressions
Music’s Therapeutic Role in Dementia and Alzheimer’s Treatment: Memory, Connection, and Quality of Life
Broadway Musicals’ Influence on Popular Culture: Theatrical Magic, Showmanship, and Entertainment
The #MeToo Movement’s Impact on the Music Industry: Addressing Abuse, Empowering Change
Music’s Role in Teenage Identity Formation: Expression, Belonging, and Self-Discovery
African American Music Evolution: From Spirituals to Hip-Hop
The History and Influence of Bollywood Music: Celebrating India’s Cinematic Melodies
Music Genres’ Effect on Exercise Performance: Rhythm, Tempo, and Motivation
Music’s Role in Climate Change Awareness: Advocacy, Inspiration, and Environmental Impact
Heavy Metal Music: Evolution, Subgenres, and Cultural Influence
Mariachi Music’s Cultural Significance: Tradition, Celebration, and Mexican Heritage
Technology’s Influence on Music Creation: Digital Tools, Production Techniques, and Creative Possibilities
Music’s Role in Autism Therapy: Communication, Expression, and Emotional Support
Music’s Impact on Stress and Anxiety Reduction: Relaxation, Mindfulness, and Wellness
The Influence of Music on Sleep Quality: Relaxation, Sleep Patterns, and Sleep Hygiene
Evolving Music Criticism in the Digital Age: From Print to Online Platforms
Music’s Role in Multicultural Education: Celebrating Diversity, Promoting Inclusion
The History and Influence of Salsa Music: Rhythm, Dance, and Cultural Fusion
Music’s Impact on Consumer Behavior in Retail: Atmosphere, Branding, and Purchase Decisions
Music’s Influence on Memory Recall: Soundtracks, Nostalgia, and Emotional Connections
Music’s Role in Post-Traumatic Stress Disorder Treatment: Healing, Coping, and Resilience
The History and Influence of J-Pop Music: Pop Culture, Fashion, and Global Fanbase
The Impact of Music on Early Childhood Education: Development, Learning, and Creativity
Music’s Influence on the Perception of Time: Tempo, Rhythm, and Psychological Effects
Music’s Role in Community Development: Collaboration, Empowerment, and Social Change
Psychedelic Rock’s Influence on Contemporary Music: Innovation, Counterculture, and Sonic Exploration
Rehabilitation and Recovery: The Transformative Role of Music
Reggaeton Music: Cultural Origins, Influence, and Global Reach
Music’s Impact on Neuroplasticity: Brain Development, Learning, and Cognitive Abilities
Celtic Music’s Influence on Modern Folk Genres: Traditions, Melodies, and Cultural Connections
The Creative Spark: Music’s Role in Enhancing Creativity
Swing Music: The History, Style, and Enduring Appeal
The Role of Music in Pain Management: Soothing, Distraction, and Therapeutic Effects
Ambient Music’s Influence on Relaxation and Mindfulness: Creating Tranquil Soundscapes

Argumentative Music Essay Topics

Pop Music’s Influence on Youth: Impact or Exploitation?
The Appropriation vs. Appreciation Debate in Music
Evaluating the Effects of Digital Streaming on Artists’ Earnings
Autotune: Enhancing Music or Undermining Talent?
Exploitation in the Music Industry: A Reality Check
Does Music Genre Define Individual Personality Traits?
Impact of Explicit Content in Music: Artistic Freedom or Harmful Influence?
Music Censorship: Necessary Measure or Infringement of Rights?
Should Music Education Be Mandatory in Schools?
Influence of Western Music on Other Cultures: Cultural Exchange or Dominance?
The Commercialization of Indie Music: Evolution or Degradation?
Are Reality Music Shows Truly Beneficial for Aspiring Musicians?
Music Therapy: Genuine Healing Method or Placebo Effect?
Classical Music’s Relevance in the Modern Era: Declining or Evolving?
The Ethics of Sampling in Modern Music Production
Role of Music in Film: Essential Component or Marketing Tactic?
Is The Popularity of an Artist Reflective of Their Musical Talent?
Music Piracy: Fair Use or Unfair Practice?
Do Music Festivals Promote Cultural Integration or Commodification?
Boy Bands Phenomenon: Musical Skill or Mere Fan Frenzy?

Research Music Essay Topics

Analyzing the Evolution of Punk Rock Music
The Role of Folk Music in Preserving Cultural Heritage
Impacts of Technology on Music Production and Distribution
Understanding the Psychological Effects of Music Therapy
Classical Music: Its Influence on Modern Genres
Musical Improvisation: An Analysis of Jazz and Blues
The Impact of Social Issues on Hip-Hop Lyrics
Exploring the Economic Aspects of the Music Industry
Evolution of Music Videos: Artistic Expression or Commercial Endeavor?
The Effect of Digital Streaming on Independent Musicians
The Phenomenon of Boy Bands: Sociocultural Aspects
Censorship in Music: A Comparative Study Across Nations
Evaluating the Role of Soundtracks in Movies
Impact of Music Education on Child Development
The Relationship Between Dance and Music: A Cultural Exploration
Gender Representation in Music: A Critical Analysis
The Influence of Latin Music on Popular Culture
Ethnomusicology: Studying Music in Its Cultural Context
The Role of Music in Historical Events and Movements

World Music Essay Topics

African Music Traditions: Influence and Evolution
The Role of Music in Indigenous Cultures
Exploring the Diversity of Asian Music Genres
Flamenco: An Insight into Spanish Music and Dance
Celtic Music: Its Roots and Influence on Contemporary Genres
The Impact of Reggae on Global Music Culture
Analyzing the Musical Elements of Bollywood Film Scores
Samba: The Rhythmic Heartbeat of Brazil
Origins and Development of American Blues Music
Middle Eastern Music: Exploring Its Unique Characteristics
The Cultural Significance of Australian Aboriginal Music
Understanding the Evolution of European Classical Music
The Role of Music in Caribbean Festivals and Celebrations
The Influence of French Chanson on Popular Music
Traditional Music’s Role in Cultural Preservation: Case Study of Japanese Gagaku
The Impact of Greek Folk Music on Mediterranean Musical Traditions
The Intersection of Music and Religion in Indian Ragas
Exploring the Cultural Diversity in Mexican Music
The Historical Evolution of Russian Folk Music
Musical Instruments and Their Role in Defining Cultural Identity: The African Djembe as a Case Study

Hip-Hop Music Essay Topics

Hip-Hop: A Powerful Medium for Social Commentary
Examining the Influence of Hip-Hop on Fashion Trends
Roles of Sampling in the Artistic Identity of Hip-Hop
Exploring the Controversy: Does Hip-Hop Promote Violence?
The Cultural Significance of Beatboxing in Hip-Hop
Analyzing the Impact of Hip-Hop on Language and Slang
The Influence of Hip-Hop on Pop Culture
Feminism in Hip-Hop: Progress and Challenges
How Does Hip-Hop Music Address Racial Issues?
The Economics of the Hip-Hop Industry
Evolution of Dance Styles in Hip-Hop Culture
Hip-Hop’s Influence on Mental Health Discourse
East Coast vs. West Coast: The Hip-Hop Rivalry
The Impact of Digital Platforms on Hip-Hop Music Distribution
Analyzing the Role of DJs in Hip-Hop Culture
Hip-Hop and Its Influence on Global Music Genres
The Commercialization of Hip-Hop: Artistic Freedom or Selling Out?
Autobiographical Storytelling in Hip-Hop: A Tool for Empowerment

Pop Music Essay Topics

Gender Representation in the Pop Music Industry
The Global Impact of K-Pop: An Unstoppable Phenomenon
Influence of Pop Music on Teenagers’ Attitudes and Behaviors
Autotune: Enhancement or Detriment to Pop Music?
The Role of Music Videos in the Pop Culture Landscape
Analyzing the Success of Boy Bands in Pop Music
Cultural Appropriation Concerns in the Pop Music Industry
Power Dynamics: Examining the Business Behind Pop Music
How Social Media Transformed Pop Music Stardom
From Pop Divas to Feminist Icons: A Shift in Representation
Latin Pop’s Rising Influence on the Global Music Scene
Pop Music Lyrics: Reflection of Social Issues or Simple Entertainment?
Technology’s Role in Shaping the Sound of Modern Pop Music
Science of a Pop Hit: Factors that Influence Chart Success
Mental Health and Its Portrayal in Pop Music
Pop Music Collaborations: A Marketing Strategy or Artistic Choice?
The Influence of Western Pop Music in Non-Western Countries
Exploring the Relationship Between Pop Music and Dance
The Ethical Implications of Sampling in Pop Music

Rock Music Essay Topics

The Crossroads of Rock and Pop: Evolution of Pop Rock
Grunge Rock: Its Origins, Influence, and Decline
Influence of Rock Music on Fashion Trends Over the Decades
The Role of Rebellion Themes in Rock Music
Gender Representation and Dynamics in Rock Music
The Significance of Live Performances in the Rock Music Scene
The Fusion of Blues and Rock: A Historical Overview
How Technological Advances Shaped the Sound of Rock Music
Rock Music as a Tool for Social Activism and Change
Psychedelic Rock and Its Effect on the Music Industry
Heavy Metal: A Subgenre of Rock Music with Distinctive Features
How Has Punk Rock Challenged Mainstream Music Norms?
Rock Music in Movies: Enhancing Narrative and Emotion
Analyzing the Pioneers of Rock and Roll: Their Legacy and Influence
Cultural Impact of the British Invasion in the 1960s
The Evolution of Rock Music: From Roots to Contemporary Forms
Roles of Music Festivals in the Promotion of Rock Music
Examining the Lyrics of Rock Music: Sociopolitical Commentary
The Impact of Rock Music on Teenagers’ Behavioral Patterns
Exploring the Relationship Between Rock Music and Youth Culture

Dance Music Essay Topics

Dance Music and Its Role in Promoting Physical Health
The Rise and Influence of Dubstep in Contemporary Dance Music
The Business of Dance Music: From Record Labels to Streaming Platforms
Role of Technology in the Development of Electronic Dance Music
The Influence of Cultural Diversity on Dance Music Genres
Dance Music in Film: Enhancing Narrative and Atmosphere
Understanding the DJ’s Role in Shaping Dance Music Culture
Tracing the Origins and Evolution of House Music
The Social Impact of Club Culture on Dance Music
Music Production Techniques in Modern Dance Genres
Choreography and Dance Music: An Inseparable Pair
The Impact of Dance Music on Pop Culture
How Does Dance Music Shape Fashion Trends?
Commercialization of Dance Music: Pros and Cons
Exploration of Gender Dynamics in the Dance Music Scene
Dance Music Festivals: Impact on Tourism and Local Economies
Analyzing the Global Appeal of K-Pop Dance Music
The Relationship Between Dance Music and Youth Culture
Evolution of Dance Music: From Disco to Electronic

Relax Music Essay Topics

Science Behind Relaxing Music: How Does It Affect Our Brain?
Evolution of Relaxing Music: From Classical to New Age
The Role of Music in Yoga and Meditation Practices
Analyzing the Impact of Relaxing Music on Sleep Quality
Soundscapes in Relaxation Music: From Nature Sounds to White Noise
Relaxing Music and Its Influence on Stress and Anxiety Levels
The Significance of Tempo and Rhythm in Relaxing Music
The Use of Relaxing Music in Therapeutic Settings
Understanding the Cultural Differences in Relaxation Music
Relaxing Music in the Classroom: Does It Enhance Learning?
Impacts of Relaxing Music on Heart Rate and Blood Pressure
Roles of Relaxing Music in Improving Concentration and Focus
Relaxing Music and Its Effects on Post-Workout Recovery
Use of Relaxation Music in Maternity Wards and Its Effect on Newborns
Harmonic Structures Commonly Found in Relaxing Music
The Influence of Ambient Music on Mental Well-being
Roles of Music Therapy in Reducing Anxiety and Pain in Patients
Can Relaxing Music Enhance the Quality of Meditation?
Binaural Beats and Isochronic Tones: Do They Help in Relaxation?
Relaxing Music in Workplaces: Impact on Productivity and Employee Satisfaction

Indie Music Essay Topics

An Examination of the Business Strategies Employed in the Indie Music Scene
The Progressive Influence of Technology on Indie Music’s Growth
Decoding the Artistic Liberty Inherent in Indie Music Creation
Cultural Connotations and Impacts Linked to Indie Music: An Analysis
Indie Music’s Contributions to Fashion and Contemporary Lifestyle Phenomena
The Part Indie Music Plays in Challenging Dominant Pop Culture
Tracing the Evolution and Influence of Indie Music Within the Music Industry
A Comparative Study on the Unique Aesthetics Found in Indie Music
The Rise of DIY Practices in Indie Music Culture: An Ethnographic Perspective
The Correlation Between Indie Music and Socio-Political Discourse Advocacy
Indie Music Festivals: An Analysis of Their Distinctive Features and Attraction
Roles and Impacts of Internet Technology and Social Media in Advancing the Popularity of Indie Music
How Indie Music Affects Identity Development: A Psychological View?
Understanding the Intersection of Indie Music and Independent Cinema
Investigating Gender Depictions within the Indie Music Scene: A Thematic Study
The Challenges and Prospects Faced by Indie Artists in Today’s Digital Era
A Deep Dive into the Shifting Soundscapes in Indie Music Over Time
The Influence of Indie Music on Modern Youth Culture from a Sociological Angle
Indie Music as a Tool for Artistic and Cultural Dissent

Training Music Essay Topics

The Science Behind Music and Its Impact on Athletic Performance
Rhythmic Influence: How Music Affects Training Patterns
Understanding the Psychology of Training Music: A Detailed Analysis
Evaluating the Role of Music in Enhancing Concentration During Training
The Impact of Music Tempo on Training Intensity
Role of Training Music in Stress Reduction and Relaxation
The Use of Music in Rehabilitation Training: A Therapeutic Perspective
Music Preferences Among Athletes: An Ethnographic Study
How Training Music Facilitates Flow State in Athletes
Exploring the Relationship Between Music Genres and Training Types
Music’s Influence on Physical Endurance and Stamina
The Art of Curating Effective Training Music Playlists
Roles of Music in Reducing Perceived Exertion During Workouts
Harmonizing Heart Rate and Beat: Music’s Role in Cardio Training
Psychological Benefits of Incorporating Music into Fitness Training
Music and Mindfulness in Training: A New Approach
The Impact of Lyrics in Training Music on Athlete Motivation
The Interplay of Music and Training in Dance and Choreography
Sonic Branding: The Use of Music in Athletic Training Brands
Historical Development of Music Usage in Training Environments

Love Music Essay Topics

The Power of Love Ballads: Analyzing Their Emotional Impact on Listeners
Unveiling the Romantic Themes in Pop Music: A Comparative Analysis
Exploring the Evolution of Love Songs: From Classic to Contemporary
Melodies of Passion: Examining the Role of Music in Expressing Love and Desire
The Language of Love: Understanding Symbolism in Romantic Music Lyrics
Captivating Melodies, Enduring Love: A Study on Timeless Love Songs
Rhythm of the Heart: Analyzing the Role of Music in Strengthening Romantic Connections
Love in Every Note: Exploring the Intertwining of Music and Romantic Relationships
Harmonic Love Stories: Examining Musical Narratives of Love and Heartbreak
The Influence of Love Songs on Romantic Expectations and Perceptions of Love
The Soundtrack of Love: Investigating the Impact of Music on Relationship Satisfaction
Love Across Genres: Comparing the Expression of Love in Different Musical Styles
Musical Chemistry: Exploring the Role of Shared Music Preferences in Romantic Bonds
Unforgettable Duets: The Magic of Collaborative Love Songs
Musical Love Letters: Examining the Role of Music in Long-Distance Relationships
Love and Lyrical Evolution: Tracing the Changes in Romantic Themes in Music History
The Healing Power of Love Songs: Analyzing Their Therapeutic Effects on Emotional Well-Being
The Intersection of Love and Social Commentary in Music: Examining Love as a Catalyst for Change
Love in the Digital Age: Investigating the Influence of Streaming Platforms on Love Music Consumption

Metal Music Essay Topics

Tracing the Evolution of Metal Music: Unraveling Its Origins and Diverse Subgenres
Identity Formation and Subcultural Affiliation in Metal Music: Examining Its Influential Impacts
Shattering Gender Norms in Metal Music: Defying Stereotypes and Empowering Voices
Mental Health and Catharsis in Metal Music: Unleashing Its Profound Impact on Well-Being
Decoding the Themes and Symbolism in Metal Music Lyrics: Unveiling Perspectives and Social Commentary
The Political Potency of Metal Music: Galvanizing Activism and Fueling Protest Movements
Innovations and Controversies in Metal Music Production: Embracing Technological Advancements and Provocations
Globalization and Metal Music: Cross-Cultural Exchange and the Fusion of Sonic Landscapes
Aesthetics and Visual Imagery in Metal Music: Embodying Power through Striking Album Art and Electrifying Stage Performances
Spirituality, Religion, and Metal Music: Exploring Intersections and Controversial Explorations
Metal Music as a Catalyst for Subversion: Igniting Rebellion Through Its Countercultural Essence
Pop Culture Impact: Illuminating the Profound Influence of Metal Music on Fashion, Media, and Widespread Popularity
Language and Expression in Metal Music: Analyzing Lyrics and Communication within Vibrant Subcultural Communities
Historical and Cultural Contexts of Metal Music: Forging Identity, Revolting, and Carrying Cultural Significance
Metal Music Communities: Forging Unbreakable Bonds through Online Spaces, Fan Clubs, and Transformative Rituals
The Influence of Metal Music on Music Education: Navigating Challenges and Unleashing Transformative Possibilities in Pedagogy
Ethnic Identity and Metal Music: Representing, Appropriating, and Enriching Cultural Heritage
The Economic, Social, and Cultural Impacts of Metal Music Festivals in the Live Music Industry
Metal Music in the Digital Age: Navigating Digital Platforms, Streaming, and Thriving Online Communities
Empowerment, Catharsis, and Resilience: Unleashing the Transformative Potential of Metal Music on Health and Well-Being

Jazz Music Essay Topics

Unveiling the Influence and Significance: Exploring Jazz as a Catalyst for Cultural Revolution
The Art of Improvisation: Unraveling the Creative Process in Jazz Music
Examining the Contributions of Pioneering Musicians: The Innovators Who Shaped Jazz
Blending Genres and Pushing Musical Boundaries: The Fusion of Jazz with Other Styles
The Intersection of Music and Social Change: Jazz’s Role in the Civil Rights Movement
Analyzing the Elements that Define the Genre: The Aesthetics of Jazz Music
Nurturing the Next Generation of Jazz Musicians: The Importance of Jazz Education
Celebrating Black American Artistic Expression: Jazz and the Harlem Renaissance
Exploring Cultural Adaptations and Influences: Jazz in a Global Context
Unlocking the Secrets of Jazz Harmony and Structure: Composition and Arranging in Jazz Music
Celebrating Female Jazz Musicians and Their Contributions: The Role of Women in Jazz
Bridging Cultures through Rhythms and Sounds: Jazz and Its Fusion with Latin Music
Pushing the Boundaries of Musical Expression: Jazz and the Avant-Garde Movement
Tracing the Roots of the Genre: Jazz and Its Influences from African Rhythms
Examining the Unique Style and Artistry of Jazz Singers: Vocalists in Jazz Music
From Duke Ellington to Count Basie and Beyond: Exploring the Jazz Big Band Tradition
Embracing Technology while Preserving Tradition: Jazz in the Digital Age
Understanding the Essential Groove of the Genre: Jazz and the Concept of Swing
Preserving Jazz’s Worldwide Appeal and Adaptation: Jazz as a Global Language

Classical Music Essay Topics

The Influence of Musical Structure on Emotional Responses in Classical Compositions Explored
Gender Representation in Classical Music: A Comparative Study
Relationship Between Tempo and Perceived Expressiveness in Beethoven’s Symphonies Examined
Musical Devices Depicting Nature in Classical Orchestral Works Analyzed
Historical Context of Classical Music and Its Connection to Social Movements Explored
Instrumentation’s Role in Interpreting Baroque Music Investigated
Melodic Patterns in Mozart and Bach’s Piano Sonatas: A Comparative Study
Symbolism of Key Signatures in Classical Music Compositions Explored
Influence of Cultural Background on Classical Music Preferences Examined
Harmony’s Role in Classical Chamber Music Analyzed
Musical Techniques Creating Narrative Structures in Classical Operas Explored
Rhythm and Meter in Classical Symphonies: A Comparative Analysis
Connection Between Classical Music and Spatial Perception Explored
Representation of Mythological Themes in Classical Music Compositions Examined
Dynamics and Articulation’s Effect on Interpretation of Romantic Era Piano Music Explored
Role of Improvisation in Classical Music Performances Investigated
Connection Between Classical Music and Memory Retrieval Explored
Influence of National Identity on Classical Music Composers of the 19th Century Examined
Evolution of Orchestration Techniques in Classical Music Explored
Contrapuntal Techniques in Fugues by Classical Composers Examined

To Learn More, Read Relevant Articles

625 good nursing research topics, ideas, and ebp, 234 social media research topics & ideas.

Regular article
Open access
Published: 24 May 2020

PepMusic: motivational qualities of songs for daily activities

Yongsung Kim ORCID: orcid.org/0000-0002-2026-8050 1 ,
Luca Maria Aiello 2 &
Daniele Quercia 2 , 3

EPJ Data Science volume 9 , Article number: 13 ( 2020 ) Cite this article

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Music can motivate many daily activities as it can regulate mood, increase productivity and sports performance, and raise spirits. However, we know little about how to recommend songs that are motivational for people given their contexts and activities. As a first step towards dealing with this issue, we adopt a theory-driven approach and operationalize the Brunel Music Rating Inventory (BMRI) to identify motivational qualities of music from the audio signal. When we look at frequently listened songs for 14 common daily activities through the lens of motivational music qualities, we find that they are clustered into three high-level latent activity groups: calm, vibrant, and intense. We show that our BMRI features can accurately classify songs in the three classes, thus enabling tools to select and recommend activity-specific songs from existing music libraries without any input required from user. We present the results of a preliminary user evaluation of our song recommender (called PepMusic) and discuss the implications for recommending songs for daily activities.

1 Introduction

Music captures attention, raises spirits, triggers and regulates emotions, and increases work output [ 1 , 2 ]. To arouse the desired feelings, the type of music should match the type of activity [ 3 ]. For example, the music people commonly listen to when seeking motivation for a workout is usually different from the music one needs to delve into relaxation. Accordingly, people curate their activity-specific playlists either by putting together songs they deem appropriate, which might be time consuming or bothersome, or by drawing from existing popular playlists that have been suitably composed for the desired activity, which may lack personalization.

In an attempt to meet these user needs, previous work has looked into automatically recommending songs suited for a specific activity [ 4 – 7 ]. Many of them are dependent on a variety of signals [ 8 ] including music genre [ 9 ], popularity of the song [ 10 ], or demographic information of the user [ 11 ], which limits their generality. While others use audio signals, but they still focus on single activity, for example, recommending songs for running sessions [ 12 ]. This motivates the need for ways to recommend songs that are motivational for various activities.

A key challenge is thus to understand and identify which musical properties are motivational for which activity. Leveraging existing listening histories and their associated preference ratings could be a starting point [ 13 ]; however, the songs people like to listen to might not be motivational in the context of certain activities. One may survey and crowdsource user preferences by asking people to rate whether or not the song will be motivational for a given activity, but that would require large resources to acquire a large-scale dataset.

To address this challenge, we introduce the idea of propagating activity labels for songs by using latent “motivational” characteristics that can be identified from audio features. As opposed to previous approaches, we do not find similar songs that people listened to in the past for a given activity, but we do rely on latent “motivational” characteristics to recommend songs that may “motivate” people for the activity.

To achieve this goal, our main contributions depart from previous work in three main aspects:

Our selection of audio features is directly informed by the music psychology literature. For the first time, we operationalize the Brunel Music Rating Inventory (BMRI) [ 14 ], an instrument to assess the motivational qualities of music in exercise and sport, which we extend to other activities (Sect. 4 ).

We consider a set of common daily activities coming from established literature, and we map frequently listened songs during these activities to the motivational sound feature space and use clustering to identify prototypical motivational range for the activities. We find that these 14 common daily activities naturally fall into three main clusters representing three music archetypes: calm , vibrant , and intense (Sect. 5 ).

We train a “motivation-based” classifier to map song into those three archetypes (Sect. 6 ). We found that, with our best performing classifier, it achieved 88.9% accuracy for calm group, 86.7% for vibrant group, and 86.5% for intense group.

The rest of the paper is organized as follows. We first review related work to motivate the need for extracting audio-signal based on motivational qualities and identifying prototypical motivational ranges based on these audio-signal (Sect. 2 ). We then introduce our data collection process that led to 1k+ songs and their metadata from Spotify and YouTube for 14 common daily activities identified in previous literature [ 15 , 16 ] (Sect. 3 ). We present methods for extracting audio signal based on BMRI (Sect. 4 ), clustering songs to identify motivational range (Sect. 5 ), and training motivation-based classifiers (Sect. 6 ). We present a preliminary user evaluation to assess our “motivation-based” classifiers by asking users to rate whether or not they found the songs were good for each activity group (Sect. 7 ). We conclude our paper with the discussion of theoretical implications of gaining a better empirical understanding of the relationship between the motivational properties of music and daily activities, as well as practical implications of using such recommendations throughout a user’s daily life (Sect. 8 ).

2 Related work

Our research builds upon the literature in a variety of fields from music psychology and sports psychology, to music recommender systems, to music information retrieval.

Our daily activities can benefit much by listening to music. Research from music psychology and sports psychology shows that music can regulate moods and emotions [ 17 – 19 ], increase productivity, increase the intensity or endurance of exercise [ 20 , 21 ], encourage rhythmic movement, and evoke memories and raise spirits [ 2 ]. Motivated by this line of theoretical work, we base our classifier on features informed by psychometric measures reflecting motivational properties of music (Sect. 4 ).

Researchers have sought to improve music recommendation systems by incorporating different factors such as user context, user properties, and music content [ 8 ]. User context factors include location and time [ 22 – 24 ], physiological state [ 5 ], and emotion [ 25 , 26 ]. User properties include demographics [ 11 ], listening histories [ 10 ], and users’ music play sequence [ 27 ]. Music content factors include genre and artists [ 9 ], popularity [ 10 ], and music audio features [ 12 , 13 ].

There exists music recommender systems that recommend songs to motivate specific activities, such as driving [ 6 ], running [ 4 , 5 ], working [ 7 ], and traveling [ 24 ]. Baltrunas et al. study ways to incorporate factors such as driving style, mood, road type, weather, and traffic conditions to recommend songs for driving [ 6 ]. Systems like PersonalSoundTrack [ 4 ] and TripleBeat [ 5 ] use runner’s pace [ 4 ] and physiological state to recommend songs to motivate runners. FocusMusicRecommender estimates user’s concentration level and recommends songs to help users focus on work [ 7 ]. We are motivated by this prior work and we envision future music recommender systems that can recommend different sets of songs to motivate users’ current activities—especially considering that user activities will soon be more readily detectable thanks to the advance in context-aware computing and sensing capabilities.

A few approaches recommend songs for common activities by using audio features [ 12 , 13 ]. Core difference between prior work and our work is that we operationalize psychometric measures to extract music features that are related to motivational qualities. When we map the frequently listened songs for 14 common daily activities to motivational music feature space, we find that these 14 activities can be grouped into three latent activity groups: calm, vibrant, and intense (Sect. 4). The number of groupings resembles that of Yadati et al. [ 13 ] in which they also identified three high-level activity groups (relaxing, studying, exercising).

3 Data collection

We first need to choose a list of daily activities and pair them with songs that people listen to while engaged in those activities. Previous work in music information retrieval either defined an arbitrary set of activities [ 12 ], or mined user-generated content from platforms like Youtube to cluster activities that are frequently mentioned [ 13 ]. To ground our selection in established literature, we also relied on previous work that identified comprehensive taxonomies of daily activities that are generally conducted indoors or outdoors (with no specific relation to music) [ 15 , 16 ]. We found that the intersection of these two activity sources results in eleven main daily activities: intimate relations, socializing, pray and worship, relaxing, eating, preparing food, exercising, shopping, working, commuting, and napping.

To gather songs that are frequently listened to while engaging in these activities, we resorted to Spotify. Spotify is an appropriate database for our purpose because it is a widespread service (180 million monthly active users all over the world), and it publicly exposes playlists curated by a variety of users, along with rich metadata. We chose a simple set of keywords for each activity. If an activity was a verb, the keywords were the verb and the verb+“ing” (e.g., if an activity was driving, we searched for both “drive” and “driving”). If an activity was noun, we only queried the activity in its own noun form (e.g., if an activity was “office”, we only searched for “office”). We first submitted each keyword of an activity as a query to the Spotify search API Footnote 1 , and collected the top 100 among the returned playlists. This provided a wide coverage of both popular and rarer songs that people listen to when engaged in a certain activity. Because the retrieval policy of Spotify search was not transparent, the set of returned playlists was likely ranked according to a mix of factors, including not only the relevance but also the popularity or prestige of the playlist owner. To only include playlists that were relevant to the activity query, we filtered out those that contained the corresponding search term in neither their names nor in their description. We then retrieved the metadata of the songs contained in the remaining playlists and retained only the songs that occurred in at least two playlists. This allowed us to filter out songs that may reflect strong personal tastes and may not be necessarily associated with a specific activity.

We wanted to retain activities that have at least 100 unique songs for each activity for clustering and classification purposes. Based on preliminary observations for a few distinctive activities (such as running and sleeping), we found that 50 songs already provided a strong signal to distinguish activities; for robustness, we doubled that number. With this last filtering step, shopping, praying, cooking, napping, and socializing were excluded. Therefore, we replaced napping with sleeping, and socializing with partying and drinking. We also found that activity terms such as eating and working were associated with playlists with other purposes; for example, the most common playlist names and descriptions associated with eating were about eating disorder, and those associated with working concerned working out. Hence, we replaced eating with breakfast, lunch, and dinner, and replaced working with studying and office. Finally, we also expanded commuting with commuting and driving, and expanded exercising with exercising and running. With this procedure, we ended up with 14 common daily activities, namely, relaxing and sleeping, exercising, running, office, partying, drinking, sex, commuting, driving, breakfast, lunch, dinner, and studying .

As the Spotify API did not return audio files, we searched and downloaded each song on YouTube with a query composed by a song title and an artist, separated by a whitespace. We chose a song where the difference between the duration of the YouTube audio file and the song duration from the Spotify metadata was the smallest. This was an important step because even if it had the same title and artist the audio file downloaded could be quite different depending on the duration (e.g., a music video with a long narrative at the beginning of the song or a video from a live concert in which the artist talks to the audience). We manually inspected 300 songs at random to ensure that these songs were matching the title correctly. Among these 300 songs, 91.3% of them (274 out of 300) matched the title correctly. All mismatched songs belonged either to the relaxing or the sleeping category. The main cause of these mismatches (16 out of 26 cases) was the song not being available on YouTube due to copyright restrictions or to the low popularity of the artist or album (e.g., artist names or album names like “Study Music”, “Einstein Study Music Academy”). In the remaining 10 cases, 2 were “soft” mismatches (a slightly different version of the same song was selected), and the remaining 8 were actual mismatches, which accounted for about only 3% of the cases. We randomly sampled 100 songs from each activity, and we managed to collect 1107 songs for the 14 common daily activities overall (Fig. 1 ).

The number of songs per activity in our dataset. The dataset includes a total of 1107 songs for 14 common daily activities

4 Operationalizing Brunel Music Rating Inventory

The Brunel Music Rating Inventory (BMRI) is a psychometric measure to assess the motivational qualities of music in the exercise and sport domain. Factors that determine motivational qualities of music are rhythm response (i.e., rhythmical elements of music), musicality (i.e., pitch-related elements of music), cultural impact, and association [ 14 ]. Elements for the rhythm response factor include: rhythm, stimulative qualities of music (loudness and tempo [ 14 ]), and danceability. Elements for the musicality factor include: harmony (how the notes are combined), and melody (the tune). Cultural impact refers to the effect of music on an individual’s cultural experiences, whereas association refers to “extra-musical thoughts, feelings and images that the music may evoke [ 14 ].”

From the audio signal, we can extract music elements related to the first two factors out of the four. More specifically, we extracted music elements related to rhythm, tempo, harmony, melody, stimulative qualities of music (loudness and tempo [ 2 ]), and danceability. For each element, we use well-established third-party libraries or state-of-the-art music information retrieval techniques for accurate descriptors (Table 1 ).

For rhythm , we use Rhythm Patterns and Rhythm Histogram as descriptors. Rhythm Patterns describe amplitude modulations for a range of modulation frequencies (e.g., fluctuations or rhythm) on frequency bands that are within the human audible range. The algorithm computes a power spectrum that reflects human loudness sensation on 24 “critical bands”; see [ 28 ] for more details about how the algorithm transforms the spectral data of the music signal into the specific human loudness sensation. Then, it transforms the power spectrum into amplitude modulations on the individual critical bands. Because the notion of rhythm ends above 15 Hz on human hearing, it computes amplitude modulations for the modulation frequencies ranging from 0 to 10 Hz (i.e., 60 bins) on the individual critical bands. The algorithm thus outputs a feature vector that has 24*60 dimensions. In contrast to Rhythm Patterns, Rhythm Histogram describes a general rhythm. Rhythm Histogram sums up the magnitudes of all critical bands per modulation frequency ranging from 0 to 10 Hz (i.e., 60 bins) to form a histogram of “rhythmic energy”.

For stimulative qualities of music [ 2 ], we use tempo and loudness. We use beats per minute (BPM) and EBU R128 loudness as descriptors [ 30 ] for tempo and loudness, respectively.

The algorithm for danceability is derived from [ 31 ] and implemented in the Essentia audio analysis library [ 30 ]. The core idea behind the algorithm [ 31 ] is to use Detrended Fluctuation Analysis, which has the ability to indicate long-range correlations in non-stationary time series, to measure how the presence of strong and regular beats influence the DFA exponent α . For example, music with sudden, intense jumps result in a lower level of α than music with a smoother varying series of intensity values; this means that music with pronounced, regular beats has lower α values than music with a more “floating, steady nature” [ 31 ]. The algorithm outputs values range from 0 to 3 (higher value means the song is more danceable) [ 30 ].

For melody , we use Pitch Bihistogram as a descriptor. “Pitch bihistogram describes how often pairs of pitch classes occur within a window d of time.” In the implementation, to form a chromagram with 60 discrete bins, the algorithm wraps the pitch content to a single octave. The window length is set to $d=0.5$ in the [0,1] range and the feature values are normalized [ 29 ].

For harmony , we use a key and a chord as descriptors. The key and the scale of the key are computed given a pitch class profile (HPCP). For the chord, we compute the most frequent chord of the progression and the scale of the most frequent chord of the progression. In cases where multiple chords are equally frequent, the chord is hierarchically chosen from the circle of fifths. Valid chords are C, Em, G, Bm, D, F#m, A, C#m, E, G#m, B, D#m, F#, A#m, C#, Fm, G#, Cm, D#, Gm, A#, Dm, F, Am [ 30 ]. The scales of keys and chords are either “major” or “minor.”

While the Spotify API also provided some of these features such as danceability, at the time of writing, many of those APIs were in beta testing and did not provide details on how features were computed. Instead, we opted for open-source algorithms that provided extensive documentation, were published in peer-reviewed papers, and have become widely used in the music information retrieval community.

5 Clustering activities

Since we don’t have user ratings or labels to link activities to motivational music, we first use historical preferences of songs for different activities and map these songs to the BMRI sound feature space to identify motivational sound range for the activities.

We expect songs that are labeled with the same activity to be close to each other in the feature space. We also hypothesize that, when two activities need the same type of motivational stimula, their respective songs are clustered together in the latent feature space.

Given a set of n songs, represented by their d-dimensional feature vectors $(\mathbf{s}_{1}, \mathbf{s}_{2}, \ldots, \mathbf{s}_{n})$ , where $d = 1508$ ), we use k -means clustering to partition them into k clusters $(C_{1}, \ldots, C_{k})$ such that within-cluster sum of squares is minimized:

where $\mu_{i}$ is the centroid of cluster $C_{i}$ . We used the euclidean distance for K-means clustering and not a weighted distance function because we assumed all dimensions are equally important for our first study.

To identify optimal k for the clustering, we used both elbow criterion that looks at the “elbow” in a plot that shows the sum of squared errors (Fig. 2 ) and silhouette score (Fig. 3 ). As we can see from Fig. 2 , one may choose either 3 or 4 as k , while from Fig. 3 , one will choose 2 as k . Therefore, we choose median/mean of these possible cluster sizes as k , which leads to $k = 3$ .

Sums of squared errors (SSE) for number of clusters k in k-means clustering. Based on “elbow” criterion, $k=3$ or $k=4$ will be a choice of k in this figure

Silhouette score for number of clusters k in k-means clustering. Based on “elbow” criterion, $k=2$ will be a choice of k in this figure

Each cluster $C_{i}$ contains songs that might be labeled with a variety of activities. For each activity a , we aim to find its most representative cluster. To do that, for each cluster, we compute the ratio of the number of its songs labeled with a (denoted as $song^{a,c}$ ) over the total number of songs labeled with a :

and logically assign a to the cluster with the largest fraction.

5.1 Clustering results

When we looked at frequently listened songs for 14 common daily activities through the lens of motivational music qualities, they were clustered into 3 high-level groups that we call calm (containing ‘relaxing’ and ‘sleeping’), vibrant (‘commuting’, ‘driving’, ‘breakfast’, ‘lunch’, ‘dinner’, and ‘studying’), and intense (‘exercising’, ‘running’, ‘office’, ‘partying’, ‘drinking’, and ‘sex’). The grouping is summarized in Table 2 . Example songs in the calm group included compilations of nature sounds, instrumental and classical music. In the intense group, we found rock, electronic, and pop songs (e.g., Bonjovi’s “It’s my life”). The vibrant group included vivacious songs but less danceable compared to the intense group (e.g., The Beatles’ “Hey Jude”).

To get a visual cue about how the feature space differentiated songs belonging to different activities and activity groups, we ran a Principal Component Analysis (PCA) on the feature vectors of all the songs and plotted each song against the two largest PCA components (Fig. 4 ). In such 2-dimensional PCA space, calm songs were mostly located in the leftmost area; intense songs were on the right; and vibrant songs were in between them, partially mixed with the vibrant cluster.

Projection of the songs’ feature vectors on a 2-dimensional PCA space. Individual songs are drawn with markers representing the activity group, and color-coded with their activity. Example songs close to the centroid of points for each activity are reported. Calm songs, such as those for sleeping and relaxing, are mostly located in the leftmost side of the PCA space; intense songs, such as those for exercising, sex, and partying are on the right; and vibrant songs, such as those for breakfast, lunch, dinner, and driving, are in between the calm and intense songs

To characterize the three clusters, we compared their distributions on the different BMRI dimensions. Loudness and danceability were lowest in the calm group and highest in the intense group (Fig. 5 ). The results align with expectations: fast-paced activities (e.g., ‘exercising’, ‘running’) are best accompanied by songs that are more danceable compared to quieter solitary or social activities that require more focus (e.g., ‘studying’ or ‘dining’) or during time for relax. Figure 5 (left) shows the tempo (beats per minute) for the three groups. Surprisingly, the BPM was the highest for the calm group ( $\mu= 121.91$ , $\sigma= 24.62$ , $min = 61.56$ , $max=184.57$ ), followed by intense ( $\mu= 117.19$ , $\sigma= 21.72$ , $min = 68.18$ , $max = 184.57$ ) and vibrant ( $\mu= 116.31$ , $\sigma= 27.58$ , $min = 67.21$ , $max = 184.57$ ). We performed non-parametric ANOVA test, Kruskal-Wallis, for BPM, loudness, and danceability because our data could not assume the normality. A Kruskal Wallis test revealed a significant effect of group on BPM ( $\chi^{2}=7.55$ , $p = 0.02$ ), loudness ( $\chi^{2}=176.66$ , $p<0.001$ ) and danceability ( $\chi^{2}=87.52$ , $p<0.001$ ). Since the results of BPM do not align with expectations, we manually inspected outliers in the calm group whose BPM was greater than the mean plus one standard deviation. Twenty-four out of 28 songs were instrumental including classical songs and meditation songs. When the songs do not use steady metronomic time, it becomes harder to automatically detect the beats since the time is not kept by percussion. That is why the addition of features other than tempo is important.

Tempo (left), Loudness (middle), and danceability (right) of the songs across the three music archetypes, namely, calm , vibrant , and intense . Both loudness and danceability are the highest for intense group and are the lowest for calm group, and the vibrant is in-between the two. For tempo, measured as beats per minutes, was the highest for the calm group, followed by the intense and vibrant groups. That is because the songs in the calm group are instrumental, such as classical music and music for mediation, and their beats are harder to automatically detect. Means are shown as triangles and medians as solid lines. The box whiskers indicate range including outliers

We also looked at the most common musical keys of the songs for the three groups (Fig. 6 ). To best interpret the results, we linked the musical keys to feelings that they commonly provoke in people, as reported in the musical theory literature [ 32 , 33 ]. The most common musical key in the calm group was F Major, followed by G major, and A Major. F Major is associated with calm, complaisance and repose, G Major with rustic, moderately idyllic and lyrical, and A Major with contentment over its situation, and youthful cheerfulness. Based on such characteristics, it is not surprising that people would listen to songs with these keys to seek relaxation. In the vibrant group, the three most common musical keys were F Major, C Major, and G Major. The presence of C Major was the most distinctive aspect compared to the calm group. C major is a cheerful key and is often described as gaiety, mirth, victorious, and innocent [ 33 ] and it also conveys joy [ 34 ]. These characteristics fit quite well for monotonous activities when people can use a stimulus to raise their spirits, or in social activities such as dining, when music can bring joy and vibrancy to the table. Last, the most common musical keys for the intense group were A Major, A Minor, and F Major, and that meets expectation: people need contentment and cheerfulness while working out or partying. Although these general characteristics of musical keys give us a lens through which to interpret our results, we caution readers that such descriptions tend to be too specific for a key’s character, and there is a criticism over the belief in the uniqueness of character for each key, which was unanimous from late 17th till early 19th with music theorists [ 33 ]. Also, such characterization was based on classical music in early 17th–19th, which may not align perfectly with contemporary music.

Most common music keys for the songs across the three music archetypes. Top-3 musical keys for the calm group are F Major, G Major, and A Major; top-3 musical keys for the vibrant group are F Major, C Major, and G Major; top-3 musical keys for the intense group are A Major, A Minor, and F Major. This figure is normalized per group, and the distance represents the percentage of each key in the group

6 Classification

Clustering results show that the songs that accompany the 14 most common daily activities can be grouped into only three groups when it comes to the motivational properties of their sound. To build a recommender that picks the best song for an activity, we need to learn, for any given song, to which of these three groups it belongs to. To establish that, we run a classification task that aims at classifying a song into its correct group.

This is a three-class classification task that we approach with a combination of three ‘one vs. rest’ binary classifiers: given a song, we calculate the confidence that it falls into cluster $c_{i}$ or not, $\forall i \in[1,3]$ and we select the cluster with higher confidence. We accomplish that using a Random Forest classifier trained on: i) each individual feature, ii) all features, and iii) all features except Rhythm Histogram, Rhythm Patterns, and Pitch Bihistogram. We used 10-fold cross validation with 70-30 train-test split. To balance the training, in each fold, we randomly sampled the same number of positive and negative instances. The classifiers were optimized to maximize the accuracy, and we used a stratified random classifier that generated predictions by respecting the training set’s class distribution as the baseline.

The classification performance is shown in Table 3 . Overall, the features with the highest mean classification accuracy are two rhythm-related features: Rhythm Histogram (RH), and Rhythm Patterns (RP). Rhythm Histogram alone achieves 88.9% of accuracy for the calm group, 84.1% for the intense group, and 86.7% for the vibrant one. Rhythm Patterns alone achieves similar results between 84% and 88%. The third most predictive feature is a melody feature with Pitch Bihistogram achieving accuracy of 83% for the calm group, 81% for vibrant one, and 81.7% for intense one. Stimulative music features (i.e., loudness and tempo) was the fourth most predictive (78% to 83%).

For the misclassified songs per classifier, we also investigated the total number of songs in the testset for each classifier, the average number of misclassified songs, and the average percentage of misclassified songs per activity group (Table 4 ). For the calm classifier, there were 39.67% of vibrant songs were misclassified as calm, and 24.71% of intense songs were misclassified as calm. For the vibrant classifier, there were 14.11% of calm songs were misclassified as vibrant, and 51.44% intense songs were misclassified as vibrant. Lastly, for the intense classifier, 5.22% of calm songs were misclassified as intense, and 54.15% of vibrant songs were misclassified as intense. This result shows that it is more common for calm and intense classifiers incorrectly classify vibrant songs, possibly due to the fact that the vibrant songs are somewhat in between the motivational ranges, and some of the songs are more or less suitable for other activity groups as well.

Rhythm Histogram, Rhythm Patterns, and Pitch Bihistogram are very informative yet quite expensive to compute, as they take about 30 seconds to a minute to extract for each song on a computer with 2.5 GHz Intel Core i7 and 16 GB memory. However, a classifier that combines all the features with the exception of Rhythm Histogram, Rhythm Patterns, and Pitch Bihistogram still yields accuracies in the 83%–86% ballpark, which is comparable to the top results. To build our recommender and to test it in the wild we used this reduced, yet efficient model. In the next section, we described our preliminary user evaluation with these reduced classifiers.

7 Preliminary user evaluation

We have shown that it is possible to accurately predict which activity type a song would be relevant to. Here we take a step further by classifying each of the user’s song into 3 categories based on the songs the user has listened in the past, and by then asking the user to rate the quality of those recommendations.

7.1 Procedure and apparatus

We recruited participants through social media, mailing list, and word of mouth. Participants volunteered for their time and, upon accessing the website we set up for the experiment, they were asked to login with their Spotify account. In a pre-survey section, participants were asked to provide two pieces of information: basic demographic data (e.g., age and gender) and the frequency of listening to music while engaging in each of our three music archetypes. For the sake of clarity and exhaustiveness, we omit the cluster labels we arbitrarily picked and, instead, for each archetype, we listed the activities they include. We hypothesize that people who listen more often to music while performing a given activity can more reliably estimate the appropriateness of a song for that activity.

While the participants filled out the pre-survey, we gathered and processed their Spotify data. Specifically, we retrieved the last 50 songs played on each of the last 20 days. We chose 50 songs (which is approx. 4 hours) as a Nielsen report of 2017 showed that people spent 4.5 hours per day listening to music [ 35 ]. Footnote 2 We then randomly sampled 10 songs from this set, extracted their audio features, and used our pre-trained classifier to determine the likelihood of the song belonging to each of the three music archetypes. Footnote 3 We randomly selected a total of 6 songs such that each song has high confidence score (>0.5) for at least one of the three music archetypes.

Once the participants filled out the pre-study survey, they were directed to a sequence of six pages (one per selected song) that were identical in structure (Fig. 7 ). They could listen to a 30-second snippet of the song to answer a short questionnaire, which asked users to: i) rate how much they like the song on a scale from 1 (‘hate it’) to 5 (‘love it’); ii) and separately, assess how good the song is for the activities included in the three macro-groups, from 1 (‘very bad’) to 5 (‘very good’); and iii) specify if they have ever listened to the song while engaging in those activities.

An interface for participants to evaluate the recommended songs. A user can listen to a 30-second preview (left), rate how much they like the song (top right), rate how good the song is for three activity groups, and whether or not they listened to this song for each activity group in the past

7.2 Results

7.2.1 participants.

The 25 participants we recruited rated 150 songs on a 5-point scale. Among them, 18 were male (72%) and 7 were female (28%). Ages were distributed as follows: 18–24 years old (24%), 25–34 years old (60% ), 35–44 years old (8%), 45–54 years old (8%).

Figure 8 shows the frequency of listening to music while engaging in the three music archetypes. For calm category (sleeping and relaxing), 40% of participants listened to music more than 3 times a week, 12% of participants listened once a week, 12% of participants listened once a month, 12% of participants listened two to three times a month, 12% of participants listened once every couple of months, 8% of participants never listened, 4% of participants listened twice a week. For intense category such as exercising and running, 28% of participants listened to music more than 3 times a week, 20% of them never listened to music, 16% of them listened once a week, 16% of them listened two to three times a month, 12% of them listened twice a week, 4% of them listened once a month, and another 4% of them listened once every couple of months. For vibrant category such as dining, commuting and driving, 72% of participants listened more than 3 times a week, 12% of them listened twice a week, 8% of them never listened, 4% of them listened once a month, and another 4% of them listened once a week. Based on these results, we can conclude that activities in the vibrant category are more likely to be paired with music listening.

Participants’ frequency of listening to music for the three music archetypes. Twenty five participants participated in the study and rated how often they listen to music while engaged in the three music archetypes, namely calm (Blue), vibrant (Orange), and intense (Green)

7.2.2 Evaluation of recommended songs

To focus on people who were more likely to have vivid recollection of listening to music while engaged in an activity, we only considered the responses of those who listened to music for a given activity at least twice a week. This resulted in 65 songs rated for the calm category, 115 songs rated for the vibrant category, 49 songs rated for the intense category.

To evaluate how the confidence score of our classifier affects user responses, we looked at the three confidence score ranges (low: [0, 0.33), mid: [0.34, 0.66), high: [0.67, 1.00]) and their corresponding user responses (Fig. 9 ). For the calm category, the mean for the user responses was 2.5 ( $\sigma=1.61$ ) when the confidence score was in the low range, 2.92 ( $\sigma=1.44$ ) when the confidence score was in the mid range, and 3.5 ( $\sigma=1.22$ ) when the confidence score was in the high range. We conducted pair-wise comparisons, and the Mann-Whitney U test showed that there’s a marginally significant difference between low and mid ( $U=316$ , $p=0.112$ ), between low and high ( $U=37$ , $p=0.079$ ), and no significant difference between mid and high ( $U=91$ , $p=0.187$ ). For the intense category, the mean for the user responses was 3 ( $\sigma =1.41$ ) when the confidence score was in the mid range, and 3.86 ( $\sigma=1.24$ ) when the confidence score was in the high range. The Mann-Whitney U test showed that there’s a significant difference between mid and high ( $U=129$ , $p=0.017$ ). We did not include the low range in the significance testing because there was only one datapoint from a single user who rated 2. The results show that when our motivation-based classifiers were more confident about classification for the music archetype, the users also rated that the recommendation was good for the given music archetype.

User ratings for songs per three confidence score ranges for each activity group. Participants rated how good the recommended songs were for a given activity group. Answers were given on a 5-point Likert scale. The confidence score range is divided into low: [0,0.33), mid: [0.34, 0.66), and high: [0.67, 1.00]. The error bars indicate the standard error of the mean. Statistical analysis detected significant differences across three confidence score ranges for the calm category and the intense category, but did not detect any significant differences for the vibrant category

However, for the vibrant category, we did not see any significant difference of confidence score range on the user responses. The average user responses was 3.5 ( $\sigma=0.71$ ) when the confidence score was low, 3.61 ( $\sigma=1.32$ ) when the confidence score was in the mid range, and 3.56 ( $\sigma=1.11$ ) when the confidence score was in the high range. The absence of a significant difference in the last case might be due to the nature of the activities in the vibrant group, which are suitable to a wider variety of music types compared to activities with a specific focus such as relaxing or exercising. Our classifier is trained to find the ‘prototypical’ songs for, say, commuting or having breakfast, but because these activities tend to have more nuanced characteristics, even songs that are not a perfect suit for those activities might be perceived as equally fit.

8 Discussion and conclusion

8.1 implications.

Music has a strong motivational potential on people. Still, this potential is only partly understood in relation to the variety of activities that people engage in daily. With this paper, we contribute to advance this understanding by translating BMRI, an inventory from music psychology that lists music features related to motivational properties, into a module that extracts those properties directly from the audio signal. From the practical perspective, this tool—which we make publicly available to the community Footnote 4 —will provide practitioners with the means of studying these properties at scale. From the theoretical standpoint, the application of the tool to annotate songs from Spotify allowed us to discover that music does not need to be activity-specific to increase motivation in that activity. Rather, there are three types of emergent music archetypes that include multiple daily activities each. However, to fully characterize music that people listen for different activities, we urge readers to take all our clustering dimensions into account when interpreting the results since the expression or perception of music is dependent on, and a combination of, musical keys, progression of chords, tempo, dynamics, and rhythmic pattern.

8.2 Limitations and future work

In this work, as our main purpose is to understand and identify motivational songs for daily activities, we only used 14 common daily activities. An interesting extension would be to collect songs for other, rare activities or events beyond daily activities to explore which type of activities can be grouped together and what might be the characteristics of newly emerged activity groups.

Our preliminary user evaluation only focused on the songs that the users have listened in the past to avoid confounds related to personal music taste. We also recognize the importance of serendipity and novelty in recommendations [ 36 , 37 ]. In the future, we would like to introduce serendipitous recommendations [ 37 ] in a way that a recommended playlist has a mixture of songs that already meet user’s personal music taste and other new songs that they have never listened to but could still be suitable for the user’s current activity. For example, based on a user’s listening history, we may first acquire music content information such as preferred genres or artists, then based on such information we may find songs that are suitable for the user’s current activity and that the user has never listened before. By doing this, we can find songs that are both motivational for a given activity and that meet users’ personal tastes. On top of that, we may also improve our motivation-based classifiers by including other descriptors for the musical elements (e.g., including onset patterns and scale transforms as descriptors for rhythm, and 2D Fourier transform magnitudes and intervalgram as descriptors for melody [ 29 ]).

While our preliminary user evaluation mainly focused on how good the recommended songs were given an activity group, which served as first milestone towards evaluating motivation-based classifiers, future work should evaluate such recommender systems in a more realistic setting. For example, we may set up a study where we provide a user’s a playlist that is generated by a motivation-based recommender system, and ask the user to be engaged in an activity that the playlist was intended for, such as asking the user to go for a run or study for 30 minutes. Having more realistic settings like this will provide us with more accurate measures for the performance of such motivation-based recommender systems.

Another limitation of our preliminary user study is the relatively small number of datapoints, which limited our ability to run a significant correlation analysis between the user responses and our classifiers’ confidence scores. Future work should conduct a large-scale user study to provide strong evidence with a correlation analysis to prove the effectiveness of our classifiers.

As existing music psychology literature has investigated the correlation between personality traits and music preferences [ 38 ], in the future, we may also explore how personality traits are linked with people’s music listening habits with respect to different activities. As a first step towards this effort, we explored the correlation between the prevalence of 5 personality traits (the respondents of our user evaluation took a ten-item personality inventory [ 39 ]) and the frequency of listening to music while performing activities in the three music archetypes (Fig. 10 ). Respondents who were emotionally stable (low in Neuroticism) tended to listen to music while engaged in activities in the calm group (e.g., relaxing and sleeping), while those high in Extraversion tended to listen to music while engaged in activities in the intense group (e.g., partying and drinking). We speculate that emotionally stable people may tend to use music to regulate their emotions [ 38 ], while extroverts tend to engage more in social gatherings and parties. These early findings suggest that information on personality traits might be helpful at the beginning of the recommendation stage to offer tailored music recommendations, or to even nudge users into listening to music in situations they are not used to, making their music consumption more serendipitous.

Correlation between our respondents’ five personality traits and their frequency in listening to music while engaging in one of the three music archetypes

https://developer.spotify.com/documentation/web-api

It is possible for a participant who listened to a lot of songs for any given day, or depending on when a participant participated in the study, we may have sampled songs that they listened during specific activities. However, as our main goal is not to ensure the coverage of songs for varying activities but to evaluate the recommended songs for our three music archetypes, we believe this process will not affect our results.

We limited the selection to 10 songs to ensure that the results were promptly shown to the user. The feature extraction for a larger number of songs could take a few minutes, which was too long to retain volunteers.

http://social-dynamics.net/pepmusic

Abbreviations

Brunel Music Rating Inventory

beats per minutes

rhythm histogram

rhythm pattern

harmonic pitch class profile

Detrended Fluctuation Analysis

European Broadcast Union

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Acknowledgements

We thank all the participants who participated in the user study.

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The datasets generated and/or analysed during the current study are available on the project’s site http://social-dynamics.net/pepmusic .

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Kim, Y., Aiello, L.M. & Quercia, D. PepMusic: motivational qualities of songs for daily activities. EPJ Data Sci. 9 , 13 (2020). https://doi.org/10.1140/epjds/s13688-020-0221-9

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Music Essay

Essay on Music

Music is like a universal language of life. It is basically the sound that is brought together through the harmony of various instruments. Our life would have been totally empty and different without music. It is something that every human being enjoys. It is a very powerful thing. Music helps to destress, heal, and motivate.

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Music Essay for Students

“Without music, life will be a mistake” the statement of Friedrich Nietzsche, a German philosopher, simplified the importance of music in one’s life so easily. Music has a magical impact on humans. It's the best form of magic.

The origin of the word ‘music’ is the Greek word ‘mousike’ which means ‘art of muses’. Music is a form of art and artists decorate it. The music consists of lesser words with deeper meanings. Frequently people use music as a painkiller to escape from the pain of life. ‘Musical Notations’ is the leading form to write music. This provides a reference to an artist so he can share with others if necessary. Music is a mood freshener and accompanies us in our pocket devices, on televisions, movies, and the most effective in live concerts.

Different forms of music have different effects on human nature. Music is the greatest creation of mankind in the course of history. A combination of deem lights and calm music encourages the listener to eat less and enjoy the food more. Listening to music positively in a car influences one’s mood leads to safer behaviour and fewer road rages ultimately minimising accidental destructions.

If the students love the music, it helps them in recalling the information more significantly along with improvement in verbal intelligence. The studies have found that listening to favourite songs helps fibromyalgia patients to experience less chronic pain. Music has a direct effect on our hormonal levels. Listening to music decreases the level of the hormone cortisol in our body and counteracts the effect of chronic stress.

The heart-touching music is nothing but creativity with the purest and undiluted form. The combination of vocal or instrumental sounds in such a way that it produces beauty and expresses emotions. Anyone can make their day by enjoying music by listening or by composting or by playing. The global facts say parents intensively use music to soothe children even to interact.

Music touches the heart through the ears. It has divine power to act as an energy booster. Some music assists in motivation while some play the best role in sympathy. Music helps us to fight insomnia. Listening to classical or relaxing music, just before going to bed, improves one’s sleep.

Though music helps to counteract depression and loneliness, people underestimate the impact of music on the human mindset in the age of irony age. On the other side of the coin, there are some types of music that can result in deleterious effects on the human mind and body. Listening to music with high decibels can damage neurons. The effect on the brain subjected to continuous exposure to electronic amplification of rhythmic music is similar to that of drugs.

Genres of Music

While talking about a wide variety of music that ranges from ages belonging to different places, cultures, and types, the list of genres is endless. However, some of the major genres of music are stated as below:

Folk & Traditional Music

Traditional music holds an impression of the culture that it represents. It is usually illustrated and sung with folk music. Folk music is taught by one generation to another vocally through singing it and by listening to it. Various dance performances are in order to make it stay intact through ages. In India, the state of Rajasthan is well known for its Traditional-folk music with its dance. Several other regions are also popular.

Art music describes the characteristics of both classical and contemporary art forms. It is usually sung by just one person and demands a high level of attention from its listeners. It is quite well known in Europe.

Religious Music

The type of music that is affiliated to the worshipping of God by singing it, is known as Religious Music. Every religion has its own style and way of singing it. Christian music is one of the most famous religious music known all over the world.

Popular Music

As the name suggests, the type of music that is popular and accessible to everyone and everywhere is known as Popular Music. Such music is composed mostly by the entertainment industry for the purpose of monetary income. As compared to other types of music, Popular Music attracts a notable audience through different concerts or Live shows.

It has gained immense popularity over a period of time and varies from country to country and from culture to culture. One can listen to it on public platforms, digital platforms, television commercials, radio, and even at shopping centres.

Popular music can be subcategorized into numerous types such as Hip Hop Music, Rock Music, Polka Music Music, Jazz Music, Pop Music Latin Music, Electronic Music, Punk Music, and many more. Among different types of Popular Music, Hip Hop Music is vividly famous, especially among the youth population. The culture of Hip Hop music originally started in New York City and now has taken over its place everywhere. The culture of Hip Hop dance has also emerged because of the same. With passing time, a lot of changes are happening in the field of Music but it will never go out of style.

Music is a healer to all human emotions from sadness to depression. It is a cause of happiness. Music content has many genres to play. Emotional expressions have been regarded as the most important criteria for the aesthetic value of music. Sometimes, some crises of life are impossible to express in proper sentences and their music plays its best part. Log on to Vedantu to find exciting essays on other topics and learn how to frame one perfectly from experts.

FAQs on Music Essay

1. What Role Does Music Play in Our Life?

Music is a very important part of our life as it is a way to express our feelings as well as emotions. For some people, music is a way to escape from all the pain. It gives you relief and allows you to destress yourself. Music plays a crucial role in our life rather than just being a source of entertainment. More importantly, music is something that can be enjoyed by everyone irrespective of their caste, creed, age, or gender.

2. Why is Music So Powerful?

Music is a language of emotion in that it can represent different feelings of a soul without any boundaries or limitations. When people feel really low and think that no one understands them, they listen to music. It is a good weapon to imitate emotions and reduce them. Music is something that can be felt from within our soul. Music is connected with Nature. There are numerous incidents of various singers where singing had led towards the showering of rains.

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Get to know the topic. You can't start writing about music until you've familiarised yourself with the concept. Do research thoroughly. Understand the important points and jot them down. Then draw a structure and start writing an essay. A student needs to realise the importance of music and the belonging of its culture for a better understanding and ease of writing. Talking to different artists from this field may also help in writing the essay. Refer to this essay framed by the experts of Vedantu and compile on your own.

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In this modern era where everyone is busy living their hectic life, music plays an important role in soothing one’s mental health. Over a course of time, it has been scientifically proven that music acts as a therapy for a person suffering from depression or anxiety. Even the sound of waves in the ocean helps to heal a person mentally. Thus, psychologists suggest hearing calm and soothing to gain relief from worldly distress.

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Original research article, testing motivational theories in music education: the role of effort and gratitude.

1 Departamento de Ciencias de la Ocupación, Logopedia, Psicología Evolutiva y de la Educación, Universidad Católica de Valencia San Vicente Mártir, Valencia, Spain
2 Departamento de Didáctica de la Expresión Musical, Plástica y Corporal, Universidad de Valencia, Valencia, Spain
3 Departamento de Metodología, Psicología Básica y Psicología Social, Universidad Católica de Valencia San Vicente Mártir, Valencia, Spain

Acquiring musical skills requires sustained effort over long periods of time. This work aims to explore the variables involved in sustaining motivation in music students, including perceptions about one’s own skills, satisfaction with achievements, effort, the importance of music in one’s life, and perception of the sacrifice made. Two models were developed in which the variable of gratitude was included to integrate positive psychology into the motivational area of music education. The first predicts effort, while the second predicts gratitude. The models were tested using a sample of 84 music students. Both models were fitted using Bayesian analysis techniques to examine the relationship between variables and showed adequate goodness of fit. These models emphasize the role of cognition and motivation in music education and, more precisely, the relationship between effort and gratitude.

Introduction

Musical training has recently gained increasing interest in the field of human cognition, specifically regarding its positive effects on brain development. This study aims to explore the cognitive processes involved in music education. According to Cogdill (2015) , having a strong musical self-concept is a crucial component of whether students will have the motivation to persist with music. Musicians dedicate a large part of their lives to learning a diverse range of musical expertise, such as symbol comprehension, language rules, interpretation through singing or an instrument, and coordination of senses, both cognitive and physical; such extensive practice has a high associated cost. Nevertheless, those who consider music to be a fundamental part of their lives convert their musical facet into a lifestyle, profession, or passion with a high level of commitment. In many cases, the benefits of being a musician are not tangible, especially as remuneration is not always assured. However, musicians continue to invest extensive effort and time into their musical training. For this reason, cognitive processes are considered to be involved in the process of becoming a musician.

We are interested in investigating young students with different university degrees (teaching, social education, or psychology) whose scope of professional development is not exclusive to music. This would encompass those who would affirmatively answer the following questions: “Is being a musician part of your identity?”; “Do you consider yourself to be a musician?” This would allow for the fact that their main university degree may not be directly linked to music, meaning that they could be considered amateur musicians. This study focuses on the role of underlying cognitive processes, seeking to understand what variables affect musical behavior. To this end, this paper explores the cognitions of amateur musicians in terms of what they believe to have influenced their continued commitment to music. The study includes a series of cognitive variables related to global judgments on the maintenance of motivation in music students, such as perceptions of their own skills, satisfaction with achievements, effort, the importance of music in their life, and perception of the sacrifice they have made. To determine the range of variables to include in the empirical models, we drew fundamentally on: (1) the experiences of music students and their opinions on the elements that had influenced their lives in relation to musical training; and (2) a review the previous literature regarding the motivational elements underlying the processes of music education.

Music students’ opinions were obtained through a brainstorming task, in which we posed questions about what had led them to continue studying music. This procedure drew on prior studies of lay conceptions ( Lambert et al., 2009 ; Bernabé-Valero et al., 2013 ). The researchers then categorized the students’ responses according to their relevance to the literature.

Bandura Self-Efficacy

Some of the variables included in this investigation are related to Bandura’s classical theory of self-efficacy ( Bandura, 1977b ) – for example, musicians’ assessment of their abilities and of the effort they have devoted in their lives to musical activities; their opinions on the sacrifice music demands; and their satisfaction with the progress they have made in relation to music. This theory defines self-efficacy as “the conviction that one can successfully execute the required behavior to produce the outcomes” ( Bandura, 1977b , p. 79). In perceived self-efficacy, Bandura distinguishes between the effectiveness and expectations of outcome expectations: “An outcome expectancy is defined as a person’s estimate that a given behavior will lead to certain outcomes; an expectation is the conviction that one can successfully execute the required behavior to produce the outcomes” ( Bandura, 1977a , p. 193). Specifically, this approach suggests that individuals might cognitively assess their skills, particularly regarding the difficulty of the task. Several studies have emphasized the role of self-efficacy in music education ( McCormick and McPherson, 2003 ; Ozmentes, 2008 ; Catalán and Orejudo, 2013 ), which has come to be defined as “beliefs about the capacity of one to achieve musical objectives” ( Woody, 2004 , p. 12). A strong association has been found between self-efficacy and performance ( McPherson and McCormick, 2006 ), and between musical self-efficacy and self-esteem ( Ozmentes, 2014 ). This theory of self-efficacy has been integrated into motivational models such as that described by Jones (2009) : the MUSIC Model of Academic Motivation, which proposes a conceptual framework for five categories of teaching strategies: empowerment, usefulness, success, interest, and caring.

Theory of Attribution and Theory of Expectancy-Value

Other motivational elements included in our study are the variables of music’s importance in one’s life, the effort invested, perceived musical talent, and the sacrifice devoted to music. According to the theory of attribution ( Weiner, 1985 ), students’ attributions for or explanations of their past achievements are often important determinants of their choice, investment, and persistence in future activity. Some of this study’s previously found skill and effort to be the most common attributions given for success, while the most common attributions for failure were low capacity for learning and lack of effort. In Asmus (1986) study, 80% of music students attributed their successes and failures to internal reasons, and a large number of stable attributions for failure were reported. Austin and Vispoel (1998) also found that attributional beliefs, particularly those related to musical ability, were closely related to students’ musical self-concept and results in performance tests, and the magnitude of those relationships Such beliefs were generally higher when students reflected on past mistakes. Therefore, these authors recommend that music teachers increase their level of knowledge about students’ attributional beliefs (particularly the tendency to attribute failures to lack of ability and/or negative family influence), and encourage students to consider less stable and controllable factors (such as effort, persistence, and use of strategies and metacognition), which play an important role in determining achievement outcomes by promoting broader visions of musical development capacity ( Austin and Vispoel, 1998 ). The theory of expectancy-value also explains why many students pursue and persist in music, while others abandon their study ( O’Neill and McPherson, 2002 ). It posits that for students to be motivated to participate in an activity, they should value it and believe they can successfully master it in the future; expectancy is explained by the attributional variables and the value by the named variable of the “ importance that music has in the life of each person .”

Gratitude From the Positive Psychology

A novel variable included in this study is gratitude, measured through agreement with the statement: “I am grateful to have had the opportunity to study music.” The importance of the gratitude construct has increased in recent years, especially since the emergence of positive psychology. Although, to our knowledge, there has been no previous research linking gratitude and music, the framework of positive psychology has influenced the field of music education ( Croom, 2012 ).

In general psychology, a large body of research has focused on gratitude ( Emmons and McCullough, 2004 ; Watkins et al., 2004 ; Tsang, 2006 ; Froh et al., 2008 ; Wood, 2008 ; Bernabé-Valero, 2012 ), developing measuring instruments and models to deepen understanding of the concept. Gratitude has achieved great relevance because of its varying effects over time on psychological well-being ( Wood et al., 2010 ; Lamas et al., 2014 ), spiritual well-being ( Mills et al., 2015 ), prosocial behavior ( Goei and Boster, 2005 ; Bartlett and DeSteno, 2006 ; Tsang, 2006 ; McCullough et al., 2008 ; Mikulincer and Shaver, 2010 ), and the maintenance of affective attachment ( Algoe et al., 2008 ; Lambert and Fincham, 2011 ). However, few studies have researched gratitude within a specific context, and the predominant approach investigates gratitude at a dispositional level ( Emmons and McCullough, 2004 ; Watkins et al., 2004 ).

Gratitude can be understood as a predisposition to recognizing, valuing, and responding to the positive aspects of personal existence, experienced as gifts received ( Bernabé-Valero et al., 2014 ). The theory that underlies this definition considers the various agents toward whom it is experienced (both personal agents, including people with different degrees of relationship to the focal individual, and non-human agents, including luck, destiny, and God), as well as the object of gratitude (which may be pleasant experiences or those that generate suffering). This definition exhibits parallels with the neurocognitive approach espoused by Emmons and McNamara (2006) , integrating the results found regarding gratitude with the costly signaling theory (CST; Sosis, 2003 ) and from the latest neuroimaging techniques. According to these authors, the process of gratitude implies that the recipient of a benefit performs the following subprocesses: (1) recognition of receiving a gift; (2) calculation of the benefits/costs associated with the gift; (3) experience of an emotion, which starts with appreciation and becomes gratitude; (4) recall of the benefits and the benefactor, as well as the beginning of the gratitude emotion, which maintains a motivational state corresponding to the benefit received.

The variable we include in this study fits with these processes and this definition in assessing whether people feel grateful for having had the opportunity to study music. More innovatively, this work explores gratitude in a particular field, as part of a specific judgment about the opportunity to study music. That is, gratitude is investigated as a specific attribution, rather than at a dispositional level (as in most prior studies. The expectancy-value theory ( O’Neill and McPherson, 2002 ) argues that for students to be motivated to participate in an activity, they should value it and believe that they will ultimately successfully master it. The gratitude variable includes valuation of the object (the opportunity to study music, which many musicians perceive as part of their identity) and identification of the agents involved. These might be the closest and most explicit agents (such as family or educators), or the more indefinite aspects (such as the luck of having a music conservatory nearby or of passing the selection tests).

It should be noted that in the Spanish context of this study, musical education is a compulsory subject at school. However, the opportunity to continue receiving musical education after school depends on several factors, such as having: a conservatory of different levels that is proximate and accessible; financial resources to fund further training; time to attend classes; and an educational context favorable to such training. According to Fredrickson’s (1998) “broaden-and-build theory of positive emotions,” gratitude could play an important role in sustaining effort and musical development. She considers that positive emotions cause changes in cognitive activity, which can subsequently induce changes in behavior. Positive emotions also expand the possibilities of action and improve physical resources ( Emmons and McCullough, 2004 ; Watkins et al., 2004 ; Tsang, 2006 ; Froh et al., 2008 ; Wood, 2008 ). If this positive emotions increases, it will indirectly increase that of the action, through more responses that are creative and diverse. Social resources will also be increased, since these enable the creation of social relationships, cooperation, and friendship. More precisely, gratitude, along with other positive emotions intrinsic to music, might explain the motivational component operating in musicians. For many reasons, we consider that gratitude for the opportunity to develop this facet may play an important role in their musical development, and could enrich understanding of the psychological processes involved in musicians’ development.

On the other hand, some studies have linked gratitude with other theories that are also addressed in this study, such as students’ self-efficacy. For instance, Bird (2015) found relationships between gratitude, self-efficacy, and well-being in middle-school adolescents. Jackson et al. (2014) used a structural equation model to demonstrate that generalized self-efficacy, gratitude, and hope are indicators of personal resources. They also found subjective well-being to be a latent variable, measured by self-esteem and satisfaction with life. By contrast, Rey (2010) studied how gratitude and subjective well-being are related to self-efficacy and control of learning beliefs among college students. These investigations support the integration of gratitude into motivational theories.

From the ideas generated by the musicians and the above-described arguments from scientific literature, different variables were chosen as predictors of gratitude and effort in the models to be tested. We decided to include variables related to the motivational models previously included in music education (such as perceptions about own skills, satisfaction with achievements, effort, importance of music in life, and perception of sacrifices). It was considered that outcome expectations could be evaluated from the viewpoint that music requires extensive sacrifice. The concept of sacrifice, which encompasses renunciations of other desires and interests, the activities related to music, and the expectation of self-efficacy (effectiveness expectation), was evaluated by asking the subjects how they viewed their own capacity for music. With respect to expectancy-value theory, it was considered relevant to ask about subjects’ satisfaction with their musical achievements (related to expectancy) and the importance of music in the subjects’ lives (the value attributed to music). The dependent variables we evaluated were the current effort dedicated to musical activities and subjects’ gratitude, assessing the latter by asking whether subjects were grateful to have had the opportunity to study music. These arguments motivated our selection of six variables in the models to be empirically tested: effort, importance, sacrifice, skills, satisfaction, and gratitude. The inclusion of gratitude, which has not (to our knowledge) been included in previous theoretical models, is justified by the above arguments on the relevance of introducing positive psychology elements into music education research.

Another innovative aspect of this work is our Bayesian approach. Bayesian inference is a useful statistical tool developed inartificial intelligence models, designed to examine conceived probabilistic conditional relationships between nodes. A Bayesian network is defined as a probabilistic relationship between nodes. In mathematical terms, both total probabilities are conditioned (occurrence of A given B) following Bayes’ theorem: P (A | B) = P (A ∩ B)/P (B). This study employs this technique to examine the sensitivity and dependence between variables, such as the effort involved in musical training. According to several authors ( Nuzzo, 2014 ; Moret-Tatay et al., 2016 ), a complementary strategy to classical analysis might be the classical Bayesian approach: in particular, the p -values employed in hypothesis testing which is not used in Bayesian networks ( Nuzzo, 2014 ). However, according to Van de Schoot et al. (2017) , its popularity has grown relatively slow since 2010, as it might be considered to lack user-friendliness. Nonetheless, this analysis can be used to more precisely determine the state of a compilation of variables through observed measures, with several advantages in a multivariate analysis.

Materials and Methods

Participants and measures.

The study’s volunteer sample comprised 84 college musicians who had attained different levels of training (30.2% male, 69.8% female). The average age was 21.8 years (SD = 4.6), with an age range of 18–45 years. The participants were students of various university degrees (teaching, social education, and psychology) at two universities in Valencia (one public and one private). All participating students were amateur musicians (it was not their main career) and none had a degree in music. Regarding the training level attained in conservatory music studies, the distribution was as follows: 44.6% had completed study at elementary level; 39.7% at secondary level; and 10.8% at tertiary level. In other words, all participants were involved in different levels of music studies. All participants were volunteers and each participant signed the necessary informed consent documentation.

Different strategies were carried out: a qualitative and a quantitative approach. Firstly, we chose a series of variables associated with the previously developed Musical Profile Scale ( Bernabé-Valero et al., 2016 ). This scale was developed by three teachers interested in the psychology of music, positive psychology, and music education, who sought to explore the relationships between the different variables involved in maintaining motivation in music students. In this qualitative approach, music students participated in a brainstorming task in which they answered posed questions about what elements were important to their musical history and what had led them to continue studying music. The answers were collected and categorized according to their semantic proximity. The authors selected opinions that occurred more frequently and had prior theoretical support, thereby obtaining a set of 10 items suitable for testing ( Supplementary Appendix A ). This set of items was then reformulated, converting item to a question to build the Musical Profile Scale ( Bernabé-Valero et al., 2016 ), to which more specific questions regarding musical behavior were also added.

Secondly, we chose those variables most closely related to the theoretical models to be empirically tested. The sample was selected from two universities where the authors are based. The battery of questions was self-administered under the authors’ supervision during one of the classes, with permission from both the university and the presiding teacher.

The variables included in this study were taken from the Musical Profile Scale ( Bernabé-Valero et al., 2016 ) ( Supplementary Appendix B ). The battery of items presented to participants covered, among other matters, the level reached in regulated music studies, the hours devoted to studying music within their educational background, and their beliefs and attitudes toward music. Six items were chosen as variables for the model we tested.

Participants responded to the following items on a 7-point Likert scale, ranging from strongly disagree (1) to strongly agree (7). The six items were:

(i) Effort: “I put a lot of effort into activities related to music.”

(ii) Capacity: “I think I have a great capacity for music.”

(iii) Satisfaction: “I am pleased with the progress I have made in relation to music.”

(iv) Sacrifice: “I think that music has necessitated much sacrifice in my life.”

(v) Importance: “The importance of music in my life is… * (ranging from no importance to absolute importance in my life) * .”

(vi) Gratitude: “I am grateful to have had the opportunity to study music.”

Data Analysis

Our approach to data analysis focuses on using Bayesian networks. More precisely, after conducting a confirmatory factor analysis of the items employed, we first tested goodness of fit, and then tested the sensitivity of the variables.

Confirmatory factor analysis was performed using IBM SPSS 21 and AMOS 21 software. To confirm the model’s adequacy for a one factor solution, we used the absolute fit indices; the chi-square statistic χ 2 ( Joreskog et al., 1979 ; Saris and Stronkhorst, 1984 ); the comparative fit index (CFI); the normed fit index (NFI), also called delta 1; and the incremental fit index (IFI). For GFI, IFI and NFI, the values ranged between 0 and 1 and the reference value was 0.90 ( Bollen, 1989 ; Bentler, 1990 ). For parsimony-adjusted indices and the root mean square error of approximation (RMSEA), the smaller its value, the better the fit, with a reference value of 0.05 ( Steiger and Lind, 1980 ). Finally, a cluster analysis was employed (using K-Means Cluster) to try to identify structures within the data.

A descriptive model was constructed using Netica 4.2 (Norsys). We then developed a learning process to test the network. Once total and conditional probabilities in our sample were obtained, it was possible to make probabilistic inferences through Bayes’ theorem via the same software. We thereby developed our model through a tree augmented naïve (TAN) Bayes algorithm, which has previously exhibited excellent performance in its simplicity and inherent independence assumptions ( Friedman et al., 1997 ). Sensibility was measured through analysis of the receiver operating characteristic (ROC) curve. Moreover, the goodness of fit was tested via three different indexes: logarithmic loss, quadratic loss, and spherical compensation.

First, logarithmic loss takes values between zero and infinity; values closer to zero indicate the best goodness of fit. Quadratic loss takes values from zero to two; again, values closer to zero indicate the best goodness of fit. Finally, spherical compensation takes values from zero to one; in this case, values closer to one indicate a better fit ( López-Puga, 2012 ). Furthermore, each node was individually evaluated, in terms of sensitivity or percentage of information provided, variance of beliefs (their expected change squared), and mutual information (between nodes).

The Cronbach’s alpha value of 0.87 showed that the Musical Profile Scale has optimal internal consistency. All of the study variables were found to be positively related (see Table 1 ).

Table 1. Pearson coefficients for the variables under study (effort, importance, skills, satisfaction, gratitude, and sacrifice).

Differences between women and men were examined trough an independent samples t test. No statistically significant differences were found between these groups, although the importance variable was close ( p = 0.054). Bartlett’s test of sphericity was p < 0.001 with a chi-square value of 230.13 (df = 15), and the Kaiser–Meyer–Olkin sample index value was 0.86. As expected, a single factor was confirmed, with 50.58% variance explained and an optimal goodness of fit: χ 2 /df = 1.72; CFI = 0.97; NFI = 0.93; IFI = 0.97; RMSEA = 0.09. Next, a cluster analysis was performed to obtain binary data. This was divided into high and low scores, following the approach in previous literature ( Moret-Tatay et al., 2016 ). Two forecasting Bayesian models were constructed and evaluated, to test the effort as a target node. The first step involved creating a descriptive analysis of the data. This was necessary to establish the model’s adequacy and to examine the nodes’ sensitivity (see Table 2 for both models). In this sense, the model fit was assessed by three parameters, as described in section “Materials and Methods”: logarithmic loss, quadratic loss, and spherical compensation ( López Puga et al., 2007 ; López-Puga, 2012 ).

Table 2. Stipulated percentage of each node in the Bayesian model for the effort (model 1) and gratitude (model 2) models.

In the model to predict effort, the logarithmic loss, quadratic loss, and spherical compensation values were 0.39, 0.24, and 0.86, respectively. The area under the ROC had a value of 0.87, indicating high sensitivity ( Figure 1 ). Next, a model to predict gratitude was tested following the same procedure. For this model, the logarithmic loss, quadratic loss, and spherical compensation values were 0.24, 0.13, and 0.93, respectively. The area under the ROC curve had a value of 0.90, again indicating high sensitivity. The skills and effort nodes had the highest percentages of information for model II.

Figure 1. ROC (receiver operating characteristic) curve for the prediction of effort (Model 1 – left) and gratitude (Model 2 – right).

Figures 2 , 3 depict both the descriptive model obtained from the database (top) and a posterior probability distribution across the states of the true height node (bottom).

Figure 2. Top: The empirical model for predicting effort in musicians. Bottom: The prediction of high values in the model about effort in musicians.

Figure 3. Top: The empirical model for predicting gratitude in musicians. Bottom: The prediction of high values in the model about gratitude in musicians.

Discussion and Conclusion

This study aimed to examine the relationship between several variables involved in the maintenance of motivation in music students, including perceptions about one’s own skills, satisfaction with achievements, effort, the importance of music in one’s life, and the perception of sacrifices made. To these variables related to the music field we added the variable of gratitude, derived from positive psychology. Our main interest was to test models of multiple relationships in which we predicted both effort on activities related to music and gratitude (for the opportunity to study music).

Another goal was to examine the relationship between the variables in terms of probabilities. Thus, we used an alternative strategy of developing a Bayesian network to examine the relationships among the variables in probabilistic terms (via Bayes’ theorem). In turn, this analysis was divided into two parts: (1) developing the model, and (2) evaluating its sensitivity. The parameters obtained in the first part of the analysis indicated that the model had adequate fit. Regarding the variables’ sensitivity, the highest percentages obtained were for “sacrifice” and “gratitude” in relation to effort (see Figure 1 ).

On the one hand, our model includes variables related to both efficacy-expectation and outcome-expectation ( Bandura, 1977a ), since the variables that consider past achievements and the self-perception of musical abilities can support the expectation of personal self-efficacy. In addition, the sacrifice variable could operate as outcome expectations as it elicited strong opinion among subjects about the large amount of practice required to achieve a good musical performance. The results of this first model have practical implications for music teachers, who could initiate metacognitive processes in their students, with the objective of forming realistic perceptions of their own skills and of the sacrifice required, as well as feelings of satisfaction with their achievements and gratitude for the opportunity to study music.

On the other hand, this first empirical model of motivation justifies the inclusion of gratitude, since this variable was found to be among the most sensitive. This result is very promising because it allows the integration of existential attitudes as motivating elements: those individuals that regard the opportunity to study music as a gift, and therefore feel grateful, will be those that dedicate the most effort to music. This element is of great importance, since gratitude is a predominantly positive emotion ( Lambert et al., 2009 ), so its inclusion in the model supposes a greater positive emotional charge than a negative element – a quality that has sometimes been associated with the variables of effort and sacrifice. According to this model, educators wishing to promote effort in students could consider as a motivating factor for students their gratitude for the opportunity to study music, besides specific achievements. To achieve a state of motivation and satisfaction in students regarding aspects intrinsic to music, teachers could assess what each aspect brings to their lives. This reflection is especially important in the decision-making processes regarding commitment to music; thus, it would be important to emphasize not only the costs of musical activity but also the benefits.

In the second model, all the variables were found to predict gratitude for having been able to study music. However, the effort node was the most relevant for music students. Again, effort appears to have an important predictive relationship with gratitude. Effort is related to the attribution of value investigating the effect of perceptions of a task’s value (interest, usefulness, and importance) on students’ reported effort, Cole et al. (2008) found that the usefulness and importance variables significantly predicted test-taking effort and performance. This result is congruent with the results for our own model, in which the importance and satisfaction variables also fit adequately. Additionally, the skills node is relevant to gratitude: those who feel more satisfied with their abilities in music are likely also more grateful for the possibility for development that it offers, given the satisfaction assured by congruence between the task demands and the capacities put in place. Furthermore, our results seem to support previous literature, such as the models developed by Lehmann et al. (2007) that examine both intrinsic and extrinsic motivation, involving values about achieving success in a music activity, values about predicting rewarding experiences, values for the future, and evaluation of time spent or effort.

Considering everything discussed so far and the earlier findings of other authors ( Bamberger, 1979 ; Bernabé-Valero et al., 2016 ), it seems that both formal and untaught dimensions play a decisive role in musical progress. This study empirically tested two motivational models, incorporating classical variables from the musical field and a novel variable originating in positive psychology. We believe that this work shows the necessity to further integrate positive existential aspects into music education research, such as flourishing ( Croom, 2012 ), resilience ( Glowinski et al., 2016 ), and social bonds ( Freeman, 2000 ). As Van Der Schyff (2015) states, people may engage more deeply with musicality when they view it as a means to form richer and more compassionate relationships with their peers, communities, and the “natural” and cultural worlds they inhabit.

This work is limited by selecting the study’s sample through non-probability sampling, which might have caused distortions. In addition, the participants were amateur musicians who were studying a university degree other than music, so with the models need to be tested with professional musicians to ensure the findings are generalizable throughout the musical field. Additionally, the variables were determined inductively from the experiences of music students, and later elaborated by expert researchers. This may have introduced some bias: although the statistical analyses depicted optimal goodness of fit, they could not be generalized to the entire population of musicians. We propose that future studies should involve recruit professional musician participants through stratified and randomized sampling to assure greater generalizability of the results.

Nevertheless, we have been able to evaluate certain variables that, to our knowledge, seem underrepresented in the existing literature on musical training (such as satisfaction, sacrifice, and gratitude). It is very important for music education research to continue investigating areas that include multivariate models using various statistical methodologies (such as Bayesian networks, structural equation models, mediation models, and moderation) to enhance the robustness of findings. Reflection on these elements could be included in music teacher training programs, enabling the incorporation of these elements into their teaching and/or learning methodologies, thus favoring the purpose, projection, and meaning of the musical experience.

Ethics Statement

All participants completed a written informed consent and the research was approved by the ethical committee at the Universidad Católica de Valencia San Vicente Mártir: UCV2017-18-28 code.

Author Contributions

GB-V and JB-M conceived the presented idea. CM-T performed the computations and verified the analytical methods. All authors supervised the findings of this work, discussed the results, and contributed to the final manuscript.

GB-V, CM-T, and JB-M were supported by the Universidad Católica de Valencia San Vicente Mártir.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The reviewer RT declared a shared affiliation, though no other collaboration, with one of the authors JB-M to the handling Editor.

Acknowledgments

We thank the Universidad Católica de Valencia San Vicente Mártir for their financial support. We also thank the editor and reviewers for their indications, the participants involved, and Tom Irving and Reza Shah for their comments and help.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnbeh.2019.00172/full#supplementary-material

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Keywords : motivation, effort, gratitude, musicians, Bayesian, music education

Citation: Bernabé-Valero G, Blasco-Magraner JS and Moret-Tatay C (2019) Testing Motivational Theories in Music Education: The Role of Effort and Gratitude. Front. Behav. Neurosci. 13:172. doi: 10.3389/fnbeh.2019.00172

Received: 04 May 2018; Accepted: 12 July 2019; Published: 31 July 2019.

Reviewed by:

Copyright © 2019 Bernabé-Valero, Blasco-Magraner and Moret-Tatay. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Gloria Bernabé-Valero, [email protected] ; Carmen Moret-Tatay, [email protected]

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10 best motivational songs + pexels photo

The 10 best motivational songs to listen to while studying

Studies by scientists from the University of Birmingham have shown that music is an effective assistant in performing monotonous work. Whether it’s thoughtless checking of e-mail or filling out a spreadsheet, the presence of music helps to increase the speed of such tasks.

Very often, students lack the motivation to write works, and in such cases, you can contact the college essay writing service WriteMyEssayOnline and get help with a paper. If you want to fundamentally deal with the problem, then it is best to start by adding motivational music to your life. ln this article, we have gathered for you the best 10 inspirational songs for studying.

(1) Flying Lotus – Flotus (song)

Words are distracting. According to Cambridge Sound Management Studies , you can’t blame all noise for performance degradation. It is the words that distract us. Because a person, hearing a speech, inevitably switches from the current topic and begins to listen to the lyrics. Such is our social nature.

(2) Jon Hopkins – Lost in Thought (song)

We can be distracted by any spoken words, regardless of whether we hear them in an office noise or in a song playing with headphones. Have you ever noticed how sometimes you find yourself listening to the lyrics of a track instead of doing something important? This is exactly the case. Instrumental music will help to avoid sticking to texts. No words, no distractions.

(3) Tycho – See (song)

The effect of listening to music depends on its pace. Canadian researchers have found that subjects are better at taking IQ tests while listening to dynamic music, and Baroque music is a favorite here. Groups of researchers from the University and Baltimore Hospital, as well as the University of Philadelphia, reached the same conclusion. Baroque music really helps to work better.

(4) Handel – Arrival of the Queen of Sheba

(5) J.S. Bach – Toccata & Fugue in D Minor, BWV 565: Toccata

(6) Henry Purcell – Tell me, some pitying angel

Another study by scientists at the Malaysian College of Engineering found that the Estimation of effects of alpha music on EEG components by time and frequency domain analysis showed a marked reduction in stress and signs of physical relaxation when listening to music at a rate of around 60 beats per minute. In the musical vocabulary, the term “larghetto” roughly corresponds to this pace.

(7) What a Feeling – Irene Cara

The song became famous thanks to the movie “Flash Dance” in 1983. Irene Kara sings about how important it is to realize a dream step by step, believe in it, and never give up to fear. In addition, in this motivating song, one more meaning can be considered: if you are not afraid of difficulties and work on yourself, sooner or later there will be an opportunity to earn a living with your hobby.

(8) The Second Coming – Juelz Santana

Once this track was in the Nike Basketball promo video. This story is about team spirit and the struggle for victory. “If you fall, get up and try it again.” How can you despair when you hear these lines pronounced to the formidable melody of Hector Berlioz?

(9) Survival – Muse

The official song of the Summer Olympics in London talks about how it is to surpass an opponent in all respects and win. The choir that assists Matthew Bellamy is gradually replaced by an epic guitar part, and this creates the feeling that you yourself are preparing for the Olympic Games. The song inspires the fight for gold in any sport and beyond.

(10) Don’t Give Up – Peter Gabriel

This song is organized as a dialogue between Peter Gabriel, who gives up after another failure, and Kate Bush, who cheers him up. The inspirational function of this song is triggered when it feels as if life has reached an impasse. Is it possible to disobey Kate Bush, who from chorus to chorus repeats in her gentle voice: “Do not give up”? Unlikely.

The 10 best motivational songs

Ideal volume—medium volume. This conclusion was made by scientists at four universities at once: studies have revealed a positive effect of listening to music at a moderate volume on creative thinking. According to these studies, both moderate and loud music help abstract thinking, but excessive volume prevents the brain from processing information.

In conclusion

Motivation is the most important thing for studying. Music will help you to keep your focus and maintain high productivity. Only you need to choose it correctly. If it comes to complex, creative, intellectual work that requires the active participation of the brain, then random music will not help. Here you need a special playlist. We tried to select the best songs for you to increase motivation and efficiency and we hope they will help you.

Contact us on social media via Twitter , YouTube , Instagram , or Facebook , and let us know what’s going on. Also, check out our Dope Music Video Showcase and vote for the dopest music video. Expect to watch exciting videos showcasing music in popular genres such as hip-hop , R&B, soul, jazz, Pop, Rock, alternative, electronic, and more. Furthermore, don’t forget to subscribe to our newsletter , purchase our merchandise , and become a Patron of Bong Mines Entertainment .

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Motivational And Inspiring Music For Success Positive Feelings: Subliminal Music Of Success
Concentration music for writing essays and reports I concentration music for working fast
Motivational Music For Creativity and Studying
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Top 10 Best MOTIVATIONAL & INSPIRATIONAL Songs ✮ Motivational Music ✮
Motivational music for success in life

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Motivational Music for Work, Study and Concentration
Motivate yourself for any task at hand with this epic powerful motivation music. This is perfect for slow mornings, studying for exams, working out and even ...
Focus Music for Work and Studying, Background Music for ...
Unlock your creativity and productivity with specially designed focus music for writing. Our study music is perfect for concentration, helping you work more ...
Music for Writing: 32 Playlists to Maximize Focus
8. Soweto Beat/Township Jive. Soweto is a township in South Africa that's well known for music. This playlist features mbaqanga music, a style of South African music with Zulu roots that originated in the early 1960s. It's upbeat and rhythmic, so it's great for energetic bursts of writing.
11 Pieces of Inspiring Music for Writing
Song 2: Audiomachine. For some symphonic and electric scores to listen to while writing, you should try Audiomachine. They have a whole lot of albums, and many different moods of music. Their scores can be beautiful, eerie, light, or dark. Highly recommend you give them a listen on YouTube, Spotify, or your music service of choice.
MUSIC TO WRITE FASTER & BETTER ️
Whether you're writing for work, school, or just being creative... you'll enjoy this music to write faster and better. This 2-hour track will help you experi...
Maximize Your Writing Focus With These 45 Perfect Music Playlists
Pandora, Spotify, Soundcloud, Apple Music, and even good old YouTube. Some are subscription-based, some are free with a few ads, but all will get the job done. I've broken things down into genre as well, so browse around, click a link, block out the rest of the world, and get to work. Classical. The original focus music. Tolstoy, Austen, Dickens.
Top 30 Upbeat Inspirational Songs
Che'Nelle) Waving Flag (feat. Féfé) I Love It (I Don't Care 2022 re‐edit) (feat. Charli XCX) Price Tag (Sped Up) (feat. B.o.B) The easiest way to change how you're feeling is to listen to inspirational music. Listen to this top 30 playlist of inspirational music and you'll be feeling motivated to keep working towards your next goal.
10 Ideas For Inspiring Your Writing with Music
10 Ideas For Inspiring Your Writing with Music. by Ellen Buikema. "Music gives a soul to the universe, wings to the mind, flight to the imagination and life to everything.". - Plato. Music, the art of sound through the use of rhythm, harmonies, and melodies, is food for the soul—divine, effective, mathematical - the science of sound.
The Best Music for Focus & Productivity While Writing a Paper
3. Jazz music. Jazz music is an excellent choice for writers looking for something more upbeat and lively. The improvisational nature of jazz can stimulate imagination and break up the monotony of a long writing session. It is good music to listen to when you need to focus and build on your creativity.
30 Most Inspirational Songs of All Time
30 Inspirational Songs that Keep You Motivated for Life.
Motivational Songs to Get You Through Your Assignments
The only danger with this uncompromising track is that you end up memorising all the lyrics rather than the flash cards you have just made (speaking from experience again here!), but when walking into an exam or heading for a meeting with your tutor to discuss an assignment, there's nothing better for getting you walking with your shoulders ...
33 Motivational Songs To Get You Through Any Workday
33. Razzle Dazzle - Richard Gere. Memorable quote: "Give 'em an act with lots of flash in it and the reaction will be passionate". Every Small business owner must have this in their arsenal of tactics. Razzle Dazzle'em and you'll have your clients, and anyone else come to that, eating out of the palm of your hand.
Motivational and Inspiring Background Music Free Download
Royalty free Motivational and Inspiring Background Music Free Download mp3. A mix of cool, uplifting and inspiring motivational background music for speech, creativity, to keep going with your goals and success. Royalty free music for YouTube and social media, free to use even commercially. Cinematic.
Music: the best tool for motivation: [Essay Example], 474 words
Music is known to invoke a strong emotional response in our body. Putting it straight, scientists have found that listening to particularly happy or sad music impacts the way we perceive our surrounding. This very property of music can be exploited to pave the human mind and emotions. Motivation can be similarly derived from listening to music.
Motivational Music Download
1:32. motivational powerful. Epic Emotional_Long. Grand_Project. 4:20. epic background music. Get motivated with our free and royalty-free motivational music downloads! From inspiring background music to uplifting songs, we've got you covered. Download now!
Why is music good for the brain?
Music activates just about all of the brain. Music has been shown to activate some of the broadest and most diverse networks of the brain. Of course, music activates the auditory cortex in the temporal lobes close to your ears, but that's just the beginning. The parts of the brain involved in emotion are not only activated during emotional ...
The Influence of Music On Mood: Free Essay Example, 575 words
Pages: 1 (575 words) Views: 311. Grade: 4.8. Download. Music is a powerful and universal language that has the ability to evoke a wide range of emotions. Whether it's the joyful melody of a favorite song or the melancholic tune of a soulful ballad, music has a profound impact on our emotions and mood. In this essay, we will explore the ways in ...
Inspiration in Music: Free Persuasive Essay Samples and Examples
Reasons to Look for Inspiration in Music Essay Sample, Example. Inspiration is a phenomenon with many variables. It is difficult to tell when it will come, arduous to predict when it will leave, yet it is a soulful feast nonetheless. When in the realm of inspiration, ordinary objects can seem phenomenal and the slightest details can be observed ...
431 Music Essay Topics & Ideas
Easy Music Essay Topics. Evolution of Pop Music Genre in the 21st Century. Impact of Technology on Music Production. Influence of Classical Music on Modern Genres. Societal Relevance of Protest Songs in History. Examining the Relationship Between Music and Emotion. Significance of Traditional Music in Cultural Identity.
PepMusic: motivational qualities of songs for daily activities
Music can motivate many daily activities as it can regulate mood, increase productivity and sports performance, and raise spirits. However, we know little about how to recommend songs that are motivational for people given their contexts and activities. As a first step towards dealing with this issue, we adopt a theory-driven approach and operationalize the Brunel Music Rating Inventory (BMRI ...
Music Essay for Students in English
Music Essay for Students "Without music, life will be a mistake" the statement of Friedrich Nietzsche, a German philosopher, simplified the importance of music in one's life so easily. ... Some music assists in motivation while some play the best role in sympathy. Music helps us to fight insomnia. Listening to classical or relaxing music ...
Frontiers
Acquiring musical skills requires sustained effort over long periods of time. This work aims to explore the variables involved in sustaining motivation in music students, including perceptions about one's own skills, satisfaction with achievements, effort, the importance of music in one's life, and perception of the sacrifice made. Two models were developed in which the variable of ...
The 10 best motivational songs to listen to while studying
The 10 best motivational songs. Ideal volume—medium volume. This conclusion was made by scientists at four universities at once: studies have revealed a positive effect of listening to music at a moderate volume on creative thinking. According to these studies, both moderate and loud music help abstract thinking, but excessive volume prevents ...
The Accidental Tax Cutter in Chief
2. Hosted by Michael Barbaro. Featuring Jim Tankersley. Produced by Stella Tan and Mary Wilson. With Michael Simon Johnson. Edited by Lisa Chow. Original music by Dan Powell and Marion Lozano ...
Exclusive: Behind the plot to break Nvidia's grip on AI by targeting
The interest in unseating Nvidia through a potential weakness in software has ramped up in the last year, and startups aiming to poke holes in the company's leadership gobbled up just over $2 ...