Learning behavior and achievement analysis of a digital game-based learning approach integrating mastery learning theory and different feedback models

• Published in: Interactive learning environments Vol. 25; no. 2; pp. 235 - 248
• Main Author: Yang, Kai-Hsiang
• Format: Journal Article
• Language: English
• Published: Abingdon Routledge 17.02.2017; Taylor & Francis Ltd
• Subjects: Educational Games; Electronic Learning; Elementary School Students; Feedback; Feedback (Response); feedback models; Foreign Countries; game-based learning; Grade 5; Instructional Design; Instructional Effectiveness; Interactive learning; learning achievement analysis; Learning behavior; Learning Theories; Mastery Learning; mastery learning theory; Pretests Posttests; Quasiexperimental Design; Questionnaires; Sequential Approach; Student Behavior; Students; Taiwan
• ISSN: 1049-4820; 1744-5191
• DOI: 10.1080/10494820.2017.1286099

It is widely accepted that the digital game-based learning approach has the advantage of stimulating students' learning motivation, but simply using digital games in the classroom does not guarantee satisfactory learning achievement, especially in the case of the absence of a teacher. Integrating appropriate learning strategies into a game can better enhance the learning performance. Therefore, in this study, a mastery theory-based digital game with different feedback models was developed to compare the differences in the learning behavior of students using the two feedback models. Lag sequential analysis was then applied to identify the sequential behaviors that are statistically proven to have impact. The results of the experiments and behavior analysis show that, with proper design of the game, students in both feedback methods can achieve the same learning performance as that in the conventional learning method with a teacher involved. Moreover, students in the Regular Feedback Group reviewed the learning material more times than those in the Corrective Feedback Group, which seemed to mitigate the drawbacks of the regular feedback. This result suggests that a proper game design will be able to achieve effective learning and is robust in terms of feedback models.