An ABC of drumming: children’s narratives about beat, rhythm and groove in a primary classroom

This newly published study will interest several of you…

Mackinlay_2014_An ABC of drumming_Children’s narratives about beat, rhythm and groove in a primary classroom

In this paper, Elizabeth Mackinlay (School of Education, University of Queensland) uses a bricolage of arts-based research and writing practices to explore narratives by Grade 4 children about their experiences in a drumming circle called ‘Bam
Bam’ as represented in a text they created with me called An ABC of drumming. The
term ‘narrative’ is used here in a contemporary sense to simultaneously invoke a socially
and musically situated and constructed story (Chase, 2005 p. 657); as an ‘account to self
and others’ (Barrett & Stauffer, 2009, p. 7) about drumming in a particular place, with a
particular group of children during a particular set of events; and, to explore narratives
of drumming as the ‘shared relational work’ of myself as a drummer, teacher, researcher
and ‘story-teller/story-liver’ (Connelly & Clandinin, 1990, p. 12) alongside the children.
In synchronicity with the ABC of drumming produced by the children, the paper itself
is framed and written creatively around letters of the alphabet and variously includes
poetry and data or research poetry; ethnographic ‘thick descriptions’ (Geertz, 1973) of our
drumming circle; and, visual and textual expressions by the children. By doing so, her
aim is to move collectively from ‘narrative as a “story-presented” to narrative as a “form
of meaning-making”, indeed, a form of “mind-making”’ (Barrett & Stauffer, 2009, p. 10)
about the children’s experience of drumming and the drumming circle itself. The central
question underpinning this paper then is, what makes children’s experience in a drumming
circle meaningful, and how do they make sense of such meaning?

Moving to music: effects of heard and imagined musical cues on movement-related brain activity

Front Hum Neurosci 2014 Sep 26;8:774
Moving to music: effects of heard and imagined musical cues on movement-related brain activity

Schaefer RS1, Morcom AM2, Roberts N3, Overy K4,5
1 SAGE Center for the Study of the Mind, University of California, Santa Barbara, CA , USA; 2 School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK; 3 Clinical Research Imaging Centre (CRIC), Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, UK; 4 Institute for Music in Human and Social Development, Reid School of Music, Edinburgh College of Art, University of Edinburgh, Edinburgh, UK; 5 Don Wright Faculty of Music, Department of Music Education, University of Western Ontario, London, ON, Canada

Music is commonly used to facilitate or support movement, and increasingly used in movement rehabilitation. Additionally, there is some evidence to suggest that music imagery, which is reported to lead to brain signatures similar to music perception, may also assist movement. However, it is not yet known whether either imagined or musical cueing changes the way in which the motor system of the human brain is activated during simple movements. Here, functional magnetic resonance imaging was used to compare neural activity during wrist flexions performed to either heard or imagined music with self-pacing of the same movement without any cueing. Focusing specifically on the motor network of the brain, analyses were performed within a mask of BA4, BA6, the basal ganglia (putamen, caudate, and pallidum), the motor nuclei of the thalamus, and the whole cerebellum. Results revealed that moving to music compared with self-paced movement resulted in significantly increased activation in left cerebellum VI. Moving to imagined music led to significantly more activation in pre-supplementary motor area (pre-SMA) and right globus pallidus, relative to self-paced movement. When the music and imagery cueing conditions were contrasted directly, movements in the music condition showed significantly more activity in left hemisphere cerebellum VII and right hemisphere and vermis of cerebellum IX, while the imagery condition revealed more significant activity in pre-SMA. These results suggest that cueing movement with actual or imagined music impacts upon engagement of motor network regions during the movement, and suggest that heard and imagined cues can modulate movement in subtly different ways. These results may have implications for the applicability of auditory cueing in movement rehabilitation for different patient populations.

Upcoming Assignments, Tuesday & Thursday, October 28 & 30

Here is a brief summary of the upcoming assignments:

1. Individual Project STEP 3: Literature Review: Due Monday, October 27, 12:00 PM. You can find details here.

2. Statistics Workshop Preparation: Our statistics workshop with Sherlock Campbell is Tuesday, October 28, 11:35am-12:50pm at CSSSI (room TBA). In preparation for the workshop, review the handouts on statistics and the factsheet for the Spontaneous Grouping online experiment.

3. Group Project STEP 4: Experimental Design: The instructions for the next step, due Thursday, October 30 are here. NOTE: If you have not completed your requirement for STEP 3: Background Research, make sure to do this as soon as possible (the instructions for this step are here).


GROUP PROJECT – STEP 4: Experimental Design (Due Thursday, October 30)

Goal:  To operationalize your research question and build all the materials necessary for its implementation on the online platform. An as-complete-as-possible draft of your protocol is due on Thursday, October 30. The finalized plan and all materials will be due the following week.

Remember that In order to operationalize a research question, you need to come up with a theory from which you derive a set conjectures. (The theory and related conjectures should be informed by your background research.) You hypothesis is a formalize statement of one or two of these conjectures. The hypothesis is what you use as a guide to plan the experimental methods, including materials, task, and procedure. It must enable you to make a testable prediction, and thus must specify what will be measured. Ideally, it should also be followed by a scenario of the possible outcomes, and how each of these will be interpreted in relation to your question. The best experiments are often those whose findings are interesting no matter what the specific outcome is (e.g., see Levitin, 1999, “Experimental Design in Psychoacoustic Research”).

There are a few things to keep in mind that pertain to practical limitations:

1. Participants: Your population sample is likely to be small and not representative of the general population (a “convenient” rather than “random” sample). You should limit the number of variables and try to maximize the number of data points you will be collecting (e.g., using a repeated measures design, that is, a design where each condition is presented to all the participants). A convenient sample also means that you will not be able to generalize your findings to the entire population, but only to the population represented by your sample (thus, the importance of providing descriptive statistics of your sample along with the results).

2. Apparatus & Data Collection: This pilot study will be conducted online using Qualtrics. This software allows for several different formats for data collection: (1) multiple choice (single-forced or multiple responses); (2) rating scale (various formats are possible); and (3) free responses. It is possible to have more than one format, but be careful to not gather more data than you can handle. If you have only limited experience with Qualtrics, you should spend some time familiarizing yourself with it. There are various issues to consider when conducting experimental studies online, but an important one to think about from the start is low motivation (failing to complete the experiment). Thus, your experiment should not take too long to complete (25 minutes is probably the maximum time you can expect someone to spend on it) and you should make all efforts to not make it too tedious.

3. Performance Measures & Statistical Analysis: Be realistic and practical in your choice of measures and statistical methods. Most measures will require some form of processing, and unless you have very good programming skills, the road from data to measure could become very arduous. Remember that although inferential statistics have a lot of rhetorical power, descriptive statistics can also be very informative (e.g., see Windsor, 2004, “Data Collection, Experimental Design,” in Empirical Musicology).


1. Make a list of all the components of your experiment (this is a preview of the “methods” section). The final list should be detailed enough to serve as a recipe for building the components. All group members should review and edit the list as necessary by the deadline.

The list will include all necessary information pertaining to:

  • Task & procedure: what you will ask the participants to do and how the stimuli will be presented (ordering)
  • Stimuli: what are the source materials, where they can be found, and how they will be manipulated (i.e., independent variables), including all necessary tools (hardware, software, web tools, etc.); make sure to be in contact with Michael Lorello ( throughout this process!
  • Data collection & analysis: what kind of data will be collected, what will be measured and how, how the data will be analyzed (only descriptive statistics are required, but you may also use correlational and inferential statistics, if you know how. NOTE: We are scheduled for a statistics workshop on Tuesday, October 28 @ CSSSI; for additional reference, see Cozby (2011), “Understanding Research Results”.
  • Predicted outcome: What kind of results can you expect? Formulate how the different possible results would be interpreted in relation to your question.

2. Survey a few online experiments. How well did the design fit the experimental goal (may be presented only after the experiment is completed)? What may be some of the limitations of the methods use?

  • On the “Resources” page of this site, there are a few online experiments, some of which are still active.
  • You should still be able to access last semester’s group experiments on the MARL platform created by Mary Farbhood (NYU).

3. Build the experimental materials: Divide the “building” tasks between your group members. As you work on the materials, you should put samples up on the group site to be reviewed by your colleagues. We will use some of the class time on October 30 to review experimental materials and do troubleshooting; make sure to have some sample materials ready, including a few sample questions on Qualtrics.

Here is a sample list of the information that may be necessary (based on the first experiment on the MARL platform “Spontaneous grouping”):

  • Study title: you will need to take into account how the title might impact your participants responses (i.e., how much do you want your participants to know about the purpose of the experiment before they complete it?).
  • Study description: a concise, one sentence description that says what your study is about.
  • Background: one paragraph that explains the context of your study (you may or may not want to be too specific, again depending on whether you think this might impact you participants responses).
  • General instructions: a concise preview of what your participants will be doing, e.g., “You will be asked to listen to sound clips and indicate how the sounds are grouped (multiple choice response).” You may add any other special instructions about how you want your participants to go through the experiment, e.g., do you want your participants to try to do it without taking a break? If there is more than one block of trials, do you want them to take a break between them? Do you want to ask them to do the experiment in a quiet space? (NOTE: There is a standard piece of technical instructions already prepared that reads “Once you have started the experiment, please do not use the “Back” browser button or refresh the page. By doing so you will interrupt the experiment and it will result in technical problems.”)
  • Part Description (Part 1 of #): This can be the same as the instructions in the previous page or a more/less detailed version (if your study has more than one part, you will need to provide one for each).
  • Trial Instructions (Part #): specific instructions for participants’ task, including how they will respond, e.g., “[Above play button:] Click on the play button to hear the sound. After the sound has finished playing, select a response. Press the continue button to continue to the next trial. [Below play button and above response boxes and continue button:] “How many tones per group did you hear?” You should also provide the response format, e.g., multiple-choice questions: 1, 2, 3, 4; Yes/No; happy/sad/calming/exciting. (NOTE: If your study has more than one part you will need to give similar information for each part.)
  • End (of Part #): You may thank your participants and/or given them some more information about the purpose of your study, how to contact you if they want to see the results when the study is completed, etc. (If your study is in many parts, you may instruct them to take a break at this point or to continue on.)

NOTE: We will work on the background survey and post-experiment questionnaire together. You may want to draft some of the questions you would like to have included.


Project Outline

Does the number of levels of beats or pulses in a song enhance people’s perception of the groove? How does tempo affect this perception?

As for our experimental design, we plan to have 6 conditions, created by 2 variables

# of Pulse Levels: We plan to enlist a panel of musical experts to determine the number of salient pulse levels present in the songs we use in the experiment, and then will divide these songs into high and low categories based on this measurement.  Low (1-2 pulse levels), High (3-5 pulse levels)

Tempo: Slow (< 74 bpm), Medium (75 – 99 bpm), Fast (> 100 bpm)

Low # of Pulse Levels

High # of Pulse Levels

Slow Tempo

Low # + Slow Tempo

High # + Slow Tempo

Medium Tempo

Low # + Medium Tempo

High # + Medium Tempo

Fast Tempo

Low # + Fast Tempo

High # + Fast Tempo

We plan to randomly take songs (unchosen as of yet) from the list compiled by Janata et al., and use these in the experiment, and it is these that will be reviewed by the panel of experts

Subjects, after listening to the pieces, will be asked about the grooviness of the music, using the same scale as Janata et al., which was a 7 point scale with 1 = least groove and 7 = most groove.

The experiment will likely be administered by an online questionnaire with music inserted into it. Participants will respond for each song directly after it plays, and will be told to feel free to move along to the music. There will also be questions to address musical and cultural background of the subject, and whether they are familiar with the songs played.

We hypothesize that songs that are reported having more salient beat levels will be rated as groovier, and that the songs with slow tempos will also be rated as more groovy than those with faster tempos.

What’s coming up: Experimental design workshop with Michael Lorello

This coming Tuesday, Michael Lorello from the School of Music, will be visiting our class for your first consult on experimental design, focusing on the musical stimuli for your group experiments.

In preparation for the workshop, write a brief summary of your experimental design as it stands (draft), including hypothesis, operationalization (task & response-type, measures, stimuli, etc.). Ideally, this should read as a “factsheet” on your experiment, for Michael to refer to as he helps you with the music technology part of this project.

Announcements & Articles of Interest

Today in class, we discussed work-in-progress and literature reviews. Here are two articles that came up that might be of interest to some of you:

Phillips-Silver, J., (2009), “On the meaning of movement in music, development and the brain”

Trainor, L., (2007), “Do preferred beat rate and entrainment to the beat have a common origin in movement?”

It also came to my attention that some of you have midterm exams scheduled for next week and/or might benefit from extra time for completing the literature review for the individual projects. In response to this, I would like to officially extend the deadline for the literature review to Monday, October 27. Additional details are posted on the Individual Projects page.

Finally, while we dispensed with the official survey of the topic of “developmental and cross cultural issues”, I thought I should still post the articles I was planning to discuss here, some of which have already been mentionned in class( e.g., Hannon & colleagues’s 2012 study comparing Turkish and American listeners). At the very least, you will benefit from reading the abstracts and might find that one of these sources is a special relevance to something you are working on:

– Winkler, Gabor, Haden, Ladinig, Sziller, & Honing (2009), “Newborn infants detect the beat in music

– Zentner & Eerola (2010), “Rhythmic engagement with music in infancy

Trehub (2012), “Behavioral methods in infancy: Pitfalls of single measures”

Hannon & Trehub, (2005), “Tuning in to musical rhythms: Infants learn more readily than adults”

– Hannon, Soley & Ullal, (2012), “Familiarity overrides complexity in rhythm perception: A cross-cultural comparison of American and Turkish listeners”

Rammsayer & Altenmuller (2006), “Temporal information processing in musicians and nonmusicians”


Balch, W.R., & Lewis, B.S. (1996). Music-dependent memory: The roles of tempo change and mood mediation. Journal of Experimental Psychology: Learning, Memory, and Cognition. Vol.22(6), pp. 1354-1363.


Music-dependent memory was obtained in previous literature by changing from 1 musical piece to another. Here, the phenomenon was induced by changing only the tempo of the same musical selection. After being presented with a list of words, along with a piece of background music, listeners recalled more words when the selection was played at the same tempo than when it was played at a different tempo. However, no significant reduction in memory was produced by recall contexts with a changed timbre, a different musical selection, or no music (Experiments 1 and 2). Tempo was found to influence the arousal dimension of mood (Experiment 3), and recall was higher in a mood context consistent (as compared with inconsistent) with a given tempo (Experiment 4). The results support the mood-mediation hypothesis of music-dependent memory.

Balch & Lewis 1996

Juslin, P.N., & Västfjäll, D. (2008). Emotional responses to music: The need to consider underlying mechanisms. Behavioral and Brain Sciences, 31(5), pp. 559-­621.


Research indicates that people value music primarily because of the emotions it evokes. Yet, the notion of musical emotions remains controversial, and researchers have so far been unable to offer a satisfactory account of such emotions. We argue that the study of musical emotions has suffered from a neglect of underlying mechanisms. Specifically, researchers have studied musical emotions without regard to how they were evoked, or have assumed that the emotions must be based on the “default” mechanism for emotion induction, a cognitive appraisal. Here, we present a novel theoretical framework featuring six additional mechanisms through which music listening may induce emotions: (1) brain stem reflexes, (2) evaluative conditioning, (3) emotional contagion, (4) visual imagery, (5) episodic memory, and (6) musical expectancy. We propose that these mechanisms differ regarding such characteristics as their information focus, ontogenetic development, key brain regions, cultural impact, induction speed, degree of volitional influence, modularity, and dependence on musical structure. By synthesizing theory and findings from different domains, we are able to provide the first set of hypotheses that can help researchers to distinguish among the mechanisms. We show that failure to control for the underlying mechanism may lead to inconsistent or non-interpretable findings. Thus, we argue that the new framework may guide future research and help to resolve previous disagreements in the field. We conclude that music evokes emotions through mechanisms that are not unique to music, and that the study of musical emotions could benefit the emotion field as a whole by providing novel paradigms for emotion induction.