Characteristics of Feedback that Influence Student Confidence and Performance during Mathematical Modeling

This study focuses on characteristics of written feedback that influence students’ performance and confidence in addressing the mathematical complexity embedded in a Model-Eliciting Activity (MEA). MEAs are authentic mathematical modeling problems that facilitate students’ iterative development of solutions in a realistic context. We analyzed 132 first-year engineering students’ confidence levels and mathematical model scores on aMEA(pre and post feedback), along with teaching assistant feedback given to the students. The findings show several examples of affective and cognitive feedback that students reported that they used to revise their models. Students’ performance and confidence in developing mathematical models can be increased when they are in an environment where they iteratively develop models based on effective feedback

Reflection Types and Students’ Viewing of Feedback in a First-Year Engineering Course Using Standards-Based Grading

Background: Feedback is one of the most powerful and essential tools for learning and assessment, particularly when it provides the information necessary to close an existing gap between actual and reference levels of performance. The literature on feedback has primarily focused on addressing strategies for providing effective feedback rather than aspects of students’ readiness to engage with feedback. Purpose/Hypothesis: This study investigated whether reflection, as a routine pedagogical intervention grounded in self-regulated learning theory, promotes the frequency with which students view feedback. Design/Method: A quasi-experimental design was employed to examine the relationship between the use of four different reflection types, as well as no reflection, and students’ feedback viewing behaviors in a first-year engineering course that used standards-based grading. Clickstream data were gathered through the learning management system to count the number of times students viewed feedback. The number of feedback views was compared by reflection type using descriptive statistics and a generalized linear model; weekly feedback viewing patterns were examined using time-descriptive graphs and the time-series cluster analysis. Results: Findings suggest reflection has the potential to increase the frequency of feedback views. Reflection not only had a positive and significant effect on the number of times students viewed feedback but also resulted in less variability between course sections and instructors when structured reflections made explicit references to feedback. Conclusions: Students need feedback to learn effectively, but many do not view feedback without formal prompting. The authors recommend instructors consistently administer reflections that include explicit pointers to feedback throughout the semester