Asee peer logo

Development and Employment of a Course Feedback Classification Tool

Download Paper |

Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Student Division Technical Session 2

Tagged Division

Student

Tagged Topic

Diversity

Page Count

2

DOI

10.18260/1-2--36950

Permanent URL

https://peer.asee.org/36950

Download Count

150

Request a correction

Paper Authors

biography

Cassie Wallwey The Ohio State University

visit author page

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.

visit author page

Download Paper |

Abstract

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

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2021 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015