Based on Learning Motivation Model and Cognitive Load Theory to Explore the Effects of Formative Assessment on Learners' Academic Achievement in Mobile Game-Based Learning System

  • 黃 雯歆

Student thesis: Doctoral Thesis


Through the mobility of smart devices and interactive elements of games mobile game-based learning (MGBL) offers students for ubiquitous learning with game design features that may enhance motivation However due to the complexity of game elements it may have negative effects on students’ cognitive process and thus influence their learning performance Therefore this study will investigate how the game design quality impacts learning effectiveness based on learning motivation model and cognitive load theory In other words we will investigate the effects of motivational factors such as attention relevance confidence and satisfaction on learners’ extraneous and germane cognitive load This study used a survey research approach with system implementation to validate related hypotheses and theories Participants were categorized into two groups the experimental group learned with the MGBL system while the control group learned with the same MGBL system without formative assessment Data was collected from 130 students who experienced the system and completed questionnaires SPSS and SmartPLS were adopted to get a more detailed and extensive data The results reveal that game quality has a positive effect on motivational factors and satisfaction has a positive effect on cognitive load Both attention and confidence positively affect germane cognitive load Moreover confidence and germane cognitive load have positive effects on learning effectiveness This study validates the relationship among constructs based on theoretical framework of learning motivation model Therefore we can conclude that a well-designed MGBL can enhance students’ motivation confidence and learning effectiveness Based on above analysis suggestions for future MGBL studies will be elaborated in the paper
Date of Award2020
Original languageEnglish
SupervisorWei-Tsong Wang (Supervisor)

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