East Lansing, Michigan
July 31, 2022
July 31, 2022
August 2, 2022
Diversity and Works In Progress
6
10.18260/1-2--42258
https://peer.asee.org/42258
332
Ahmed Ashraf Butt is a doctoral candidate in the school of engineering education at Purdue University with a multidisciplinary research focus that combines theory and practice in the area of learning science, Human-computer interaction (HCI), and engineering education. His primary research focuses on designing and developing educational technologies that can facilitate different aspects (e.g., engagement) of the students’ learning and provide an engaging experience. Further, he is interested in designing instructional interventions and exploring their relationship with different aspects of first-year engineering (FYE) students’ learning (e.g., motivation and learning strategies). Before Purdue University, he worked as a lecturer for two years at the University of Lahore, Pakistan. Additionally, he has been associated with the software industry in various capacities, from developer to consultant.
Saira Anwar is an Assistant Professor at Department of Multidisciplinary Engineering, Texas A &M University. Dr. Anwar has over 13 years of teaching experience, primarily in the disciplines of engineering education, computer science and software engineering. Her research focuses on studying the unique contribution of different instructional strategies on students' learning and motivation. Also, she is interested in designing interventions that help in understanding conceptually hard concepts in STEM courses. Dr. Anwar is the recipient of the 2020 outstanding researcher award by the School of Engineering Education, Purdue University. Also, she was the recipient of the "President of Pakistan Merit and Talent Scholarship" for her undergraduate studies.
Muhsin Menekse is an Associate Professor at Purdue University with a joint appointment in the School of Engineering Education and the Department of Curriculum and Instruction. Dr. Menekse's primary research focus is on exploring K-16 students' engagement and learning of engineering and science concepts by creating innovative instructional resources and conducting quasi-experimental research studies in and out of classroom environments. Dr. Menekse is the recipient of the 2014 William Elgin Wickenden Award by the American Society for Engineering Education. Dr. Menekse also received three Seed-for-Success Awards (in 2017, 2018, and 2019) from Purdue University's Excellence in Research Awards programs in recognition of obtaining three external grants of $1 million or more during each year. His research has been generously funded by grants from the Institute of Education Sciences (IES), Purdue Research Foundation (PRF), and National Science Foundation (NSF).
Reflection is an important skill and is a practical learning tool to engage students in learning tasks. In the context of first-year engineering (FYE) students, studies have emphasized the importance of the reflection activities as it facilitates the students’ learning process by engaging them with the learning contents, specifically with threshold and conceptually challenging concepts. Considering that the national average of male and female student population in the USA in FYE programs is disproportionate, students may experience varying impacts on their learning across gender. Consequently, this work in progress contributes to the literature by exploring the role of gender-based variations in the relationship between students’ self-reflection and academic performance in FYE students. Specifically, this study is guided by a research question: Do students’ self-reflections have a varying effect on the students’ academic performance between gender groups? We collected the data from 120 FYE students enrolled in a required FYE course at a large Midwestern University. We focused on a first-year programming course to evaluate the impact of reflection across gender groups and students’ performance for conceptually challenging concepts. We collected the data on gender, course reflection, and academic performance. In the data collection process, students self-reported their gender information. To collect students’ reflections, we used CourseMIRROR mobile application. This application prompted students to reflect on the interesting and confusing aspects of the lecture after the end of each lecture throughout the semester. We used the reflection specificity score (i.e., the quality of the reflection) to measure students’ ability to reflect, calculated by the application using NLP algorithms. Further, the instructional team provided the data on students’ performance through their exam scores. To inform our study, we will conduct multiple regression for each set of reflection questions (i.e., confusing and interesting aspects of lecture), where the dependent variable is the students’ exam score, and the independent variables are the average specificity score of students’ submitted reflections, and their gender. The draft paper will present the preliminary results across gender groups, implications, limitations, and future directions.
Butt, A. A., & Anwar, S., & Menekse, M. (2022, July), WIP: Investigating the relationship between FYE students’ reflections and academic performance across gender Paper presented at 2022 First-Year Engineering Experience, East Lansing, Michigan. 10.18260/1-2--42258
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