Learning analytics and psychophysiology : understanding the learning process in a STEM game
Abstract
This study focuses on the exploration of player experience in educational games and its potential impact on predicting learning outcomes. Specifically, the research aims to investigate the connection psychophysiology data, obtained through a summative study involving nine participants, and the results of a learning analytics model derived from a larger field test. The study incorporates eye tracking and electrodermal activity data to gain insights into the predictive power of this data. Through the analysis of player experience data, the study sheds light on the factors that contribute to effective educational game design. By examining the eye tracking and EDA data, the researchers explored the participants' engagement levels, attention patterns, and emotional arousal during gameplay. These findings revealed a connection between spikes of visual attention and EDA during interactions with character faces as well as in game cinematics. In conclusion, the outcomes of this study provide valuable insights for future educational game designers. By understanding the relationship between user experience indicators and learning analytics, designers can tailor game elements to enhance engagement, attention, and emotional arousal, ultimately leading to improved learning outcomes. The integration of eye tracking and EDA data in user experience studies adds a new dimension to the evaluation and design of educational games. The findings pave the way for future research in the field and highlight the importance of considering user experience as a crucial factor in educational game design and development.
Degree
Ph. D.