Virtual Conference
July 26, 2021
July 26, 2021
July 19, 2022
Student
Diversity
2
10.18260/1-2--36950
https://peer.asee.org/36950
329
Cassie Wallwey is currently a Ph.D. candidate in Ohio State University's Department of Engineering Education. She is Graduate Teaching Associate for the Fundamentals of Engineering Honors program, and a Graduate Research Associate working in the RIME collaborative (https://u.osu.edu/rimetime) run by Dr. Rachel Kajfez. Her research interests include engineering student motivation and feedback in engineering classrooms. Before enrolling at Ohio State University, Cassie earned her B.S. (2017) and M.S. (2018) in Biomedical Engineering from Wright State University.
This student division poster will present the development and subsequent use of a course feedback classification tool whose purpose was to inform research around the impact of feedback on student motivation. Feedback is a tool used to inform learning and includes everything from informal conversations with students about assignments to final course grades. In multiple courses at various education levels feedback has been shown to impact student learning through deeper content understanding, improved retention, and more meaningful interactions with instructors [1]. When feedback is offered, instructors begin a dialog with students by pointing out misconceptions or misunderstandings. Many instructors hope that students will use feedback to correct their misunderstanding, as good feedback directs practice [2]. By employing good feedback practices in a course, students are better able to adjust and correct misconceptions, recognize their strengths and weaknesses, and set learning goals [3]. The purpose of this feedback classification tool is to help instructors or researchers identify what feedback practices are being used in a course, as well as further define those practices by identifying specific characteristics of the feedback. The classification tool lists a variety of assignments and activities that are used to improve or assess student learning. The classification tool first has users identify all assignments and activities that are used in their course and secondly, identify from those options those that students receive feedback on. For each of the assessments or assignments that have been identified as an opportunity that students have to receive feedback, further details regarding the feedback practices used for that assessment/assignment are identified by the user. These further details are organized based on four characteristics of feedback identified in literature: source, mode, occasion, and content [4]. This feedback classification tool was completed by instructors of engineering math courses and used in conjunction with another survey filled out by student research participants to complete the first phase of data collection for a dissertation research project. This project aims to explore the impacts of feedback on the motivation of students enrolled in engineering mathematics courses across multiple institutions. The complete study employs a mixed methods design, and this feedback classification tool and the student survey were used to inform the second phase of the research that uses qualitative interviews explain the results in further detail. Beyond the use of this feedback classification tool in this specific research context, it can also be used as a tool in courses across varying subjects and education levels to identify what feedback practices are being used and evaluate if those feedback practices align with recommendations from the literature that have shown to be pedagogically beneficial.
References [1] J. A. Hattie and H. Timperley, “The Power of Feedback,” Rev. Educ. Res., vol. 77, pp. 81–112, 2007. [2] S. A. Ambrose, M. W. Bridges, M. DiPietro, M. C. Lovett, and M. K. Norman, How Learning Works: Seven Research-Based Principles for Smart Teaching. John Wiley & Sons, 2010. [3] D. J. Nicol and D. Macfarlane-Dick, “Formative assessment and self-regulated learning: a model and seven principles of good feedback practice,” Stud. High. Educ., vol. 31, no. 2, pp. 199–218, 2006. [4] M. L. Rucker and S. Thomson, “Assessing student learning outcomes: An investigation of the relationship among feedback measures,” Coll. Stud. J., vol. 37, no. 3, pp. 400–404, 2003.
Wallwey, C. (2021, July), Development and Employment of a Course Feedback Classification Tool Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36950
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