TY - GEN
T1 - AI-Tutoring in Software Engineering Education Experiences with Large Language Models in Programming Assessments
AU - Frankford, Eduard
AU - Sauerwein, Clemens
AU - Bassner, Patrick
AU - Krusche, Stephan
AU - Breu, Ruth
N1 - Publisher Copyright:
© 2024 Copyright held by the owner/author(s).
PY - 2024/4/14
Y1 - 2024/4/14
N2 - With the rapid advancement of artificial intelligence (AI) in various domains, the education sector is set for transformation. The potential of AI-driven tools in enhancing the learning experience, especially in programming, is immense. However, the scientific evaluation of Large Language Models (LLMs) used in Automated Programming Assessment Systems (APASs) as an AI-Tutor remains largely unexplored. Therefore, there is a need to understand how students interact with such AI-Tutors and to analyze their experiences. In this paper, we conducted an exploratory case study by integrating the GPT-3.5-Turbo model as an AI-Tutor within the APAS Artemis. Through a combination of empirical data collection and an exploratory survey, we identified different user types based on their interaction patterns with the AI-Tutor. Additionally, the findings highlight advantages, such as timely feedback and scalability. However, challenges like generic responses and students’ concerns about a learning progress inhibition when using the AI-Tutor were also evident. This research adds to the discourse on AI’s role in education.
AB - With the rapid advancement of artificial intelligence (AI) in various domains, the education sector is set for transformation. The potential of AI-driven tools in enhancing the learning experience, especially in programming, is immense. However, the scientific evaluation of Large Language Models (LLMs) used in Automated Programming Assessment Systems (APASs) as an AI-Tutor remains largely unexplored. Therefore, there is a need to understand how students interact with such AI-Tutors and to analyze their experiences. In this paper, we conducted an exploratory case study by integrating the GPT-3.5-Turbo model as an AI-Tutor within the APAS Artemis. Through a combination of empirical data collection and an exploratory survey, we identified different user types based on their interaction patterns with the AI-Tutor. Additionally, the findings highlight advantages, such as timely feedback and scalability. However, challenges like generic responses and students’ concerns about a learning progress inhibition when using the AI-Tutor were also evident. This research adds to the discourse on AI’s role in education.
KW - Artificial Intelligence
KW - Automated Programming Assessment Systems
KW - ChatBots
KW - ChatGPT
KW - OpenAI
KW - Programming Education
UR - http://www.scopus.com/inward/record.url?scp=85195462659&partnerID=8YFLogxK
U2 - 10.1145/3639474.3640061
DO - 10.1145/3639474.3640061
M3 - Conference contribution
AN - SCOPUS:85195462659
T3 - Proceedings - International Conference on Software Engineering
SP - 309
EP - 319
BT - Proceedings - 2024 ACM/IEEE 46th International Conference on Software Engineering
PB - IEEE Computer Society
T2 - 46th International Conference on Software Engineering: Software Engineering Education and Training, ICSE-SEET 2024
Y2 - 14 April 2024 through 20 April 2024
ER -