TY - GEN
T1 - Enhancing Student Motivation Through LLM-Powered Learning Environments
T2 - 19th European Conference on Technology Enhanced Learning, EC-TEL 2024
AU - Seßler, Kathrin
AU - Kepir, Ozan
AU - Kasneci, Enkelejda
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - The integration of ChatGPT and other large language models (LLMs) into educational environments has raised widespread discussions about the potential positive and negative effects. To understand the impact of LLMs on learning, it is crucial to consider various aspects of the learning process, including motivational factors, which play an important role in creating a positive learning experience. This study investigates the different motivational influences on the learning of university students in a traditional, static environment versus an LLM-supported learning platform. Our study includes 50 participants and focuses on their engagement in learning about a mathematical topic. The study demonstrates a statistically significant (p<0.001) increase in motivation among participants who use an LLM-powered platform for learning, compared to those who access a static website, with a large effect size (Cohen’s d=-1.387). This suggests that interactive, LLM-driven learning tools can substantially enhance learner motivation.
AB - The integration of ChatGPT and other large language models (LLMs) into educational environments has raised widespread discussions about the potential positive and negative effects. To understand the impact of LLMs on learning, it is crucial to consider various aspects of the learning process, including motivational factors, which play an important role in creating a positive learning experience. This study investigates the different motivational influences on the learning of university students in a traditional, static environment versus an LLM-supported learning platform. Our study includes 50 participants and focuses on their engagement in learning about a mathematical topic. The study demonstrates a statistically significant (p<0.001) increase in motivation among participants who use an LLM-powered platform for learning, compared to those who access a static website, with a large effect size (Cohen’s d=-1.387). This suggests that interactive, LLM-driven learning tools can substantially enhance learner motivation.
KW - Educational Technology
KW - Intrinsic motivation
KW - Large Language Models
KW - Learner Engagement
UR - http://www.scopus.com/inward/record.url?scp=85205306270&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-72312-4_21
DO - 10.1007/978-3-031-72312-4_21
M3 - Conference contribution
AN - SCOPUS:85205306270
SN - 9783031723117
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 156
EP - 162
BT - Technology Enhanced Learning for Inclusive and Equitable Quality Education - 19th European Conference on Technology Enhanced Learning, EC-TEL 2024, Proceedings
A2 - Ferreira Mello, Rafael
A2 - Rummel, Nikol
A2 - Jivet, Ioana
A2 - Pishtari, Gerti
A2 - Ruipérez Valiente, José A.
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 16 September 2024 through 20 September 2024
ER -