This series features the voices of educators and researchers who bring the MUSIC Model of Motivation to life in diverse classrooms and contexts. Through short interviews, they share how they apply and study the model to enhance student motivation and engagement around the world.

Interview with Dr. Renee Clark

— Associate Professor, University of Pittsburgh, Swanson School of Engineering, Department of Industrial Engineering

1. How did you find out about the MUSIC model, and why did you decide to use it for research?

I originally learned about the MUSIC Inventory approximately 10 years ago from a colleague. In several studies I have done in engineering education since then, the topic of student motivation has been of interest. I’ve used the MUSIC model to measure motivational climate each time. The MUSIC model is easy to use, and its questions are relevant and straightforward.

2. In what ways have you used the MUSIC model in your research, and in what context(s) (e.g., country, subject area, educational level of students)?

I have used the MUSIC model for research with undergraduate engineering students in the United States. I used it for a school-wide NSF-funded study in the fall 2020 to capture students’ perceptions of the motivational climate during the COVID pandemic. The instrument was taken by a large sample of undergraduate engineering students at our Swanson School of Engineering at the time. The results showed lower levels of MUSIC perceptions (as one may have suspected) during the period of remote instruction. Our results were compared to available prior results to show the degree of decreased MUSIC perceptions. This study was published in the International Journal of Engineering Education:
— Clark, R., Besterfield-Sacre, M., Dickerson, S., & Gau, D. (2023). Impact of COVID-19 on Engineering Students in the Middle Phases of the Pandemic: Academic Motivation, Valued College Experiences, and Stress. International Journal of Engineering Education, 39(1), 30-47.

I am currently using the MUSIC model in another NSF-funded study involving three US institutions with undergraduates from four engineering majors across five courses. We are using it to assess student motivation associated with the use of pre-class learning modules aimed at enhancing classroom preparation with pre-requisite content. Two delivery methods for this content are being compared – a learning management system versus an adaptive learning platform.

3. How has the MUSIC model helped you in your research?

I believe it has enabled us to publish quality research as well as secure NSF research grants, given its rigorous development and validation.

4. What challenges have you encountered when applying the MUSIC model and how have you addressed them?

No challenges come to mind. I have contacted Dr. Jones in the past with questions, and he has always been responsive. Thus, if a challenge were to occur, I believe there would be support for it.

5. How has the model influenced your thinking about student motivation or instructional design?

It has informed me that motivation is a multi-faceted, complex construct having several factors that play a role in students’ motivation. These are captured in the five dimensions of the MUSIC model. When providing or assessing instruction, I must (and do) keep in mind that these various facets must be accounted for when promoting a positive motivational climate.

6. What advice would you give to someone beginning to use the MUSIC model for research?

I recommend reviewing the User Guide that is available to learn how to analyze the collected data, including reporting results for each MUSIC component.

7. Is there anything else you would like to share about your experience in using the MUSIC model for research?

In my current research study, we are also using the SCCEI – Student Course Cognitive Engagement Instrument – to measure cognitive engagement during class alongside motivational climate. We are examining correlations between the various dimensions of the instruments. I think it’s interesting and informative to use validated instruments in combination.