Year: 2024
Type: conference-paper
Abstract: This study investigates the effectiveness of WebTA, a MATLAB-based code critiquer, in enhancing programming education for first-year engineering students. WebTA aims to identify and provide feedback on antipatterns, promoting better coding practices. The research involved three classroom interventions at Michigan Technological University during the Spring and Fall semesters of 2023. In the Spring, WebTA was integrated into three MATLAB assignments in ENG1101, and student interactions were observed. Key areas of focus included student engagement, usage patterns, challenges, behavioral responses, and instructor interactions. Pre- and post-interviews with instructors were conducted to assess baseline knowledge and capture reflections on WebTA's impact. Thematic analysis of these interviews revealed varied abilities among instructors to identify antipatterns, diverse teaching approaches, and mixed feedback on WebTA's utility. Findings indicate that WebTA effectively reduces coding anxiety and instills good programming habits but also highlights the need for better integration with educational platforms and a balanced approach to feedback. Future research focuses on expanding WebTA's application across different programming courses and objectively measuring its impact on student and instructor perceptions. Addressing the identified challenges will enhance WebTA's usability and overall effectiveness, contributing to improved programming education outcomes.
DOI: 10.18260/1-2--48581
Authors: Mary Benjamin, Laura Albrant, Michelle Jarvie-Eggart, Jon Sticklen, Laura Brown, Leo Ureel
Institution: Michigan Technological University
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W4401834319