Predictors of active and inactive learners’ intention to use decision tree-based contextual mobile games for cultivating digital citizenship behaviour

Abstract

Recently, scholars have suggested artificial intelligence to enhance digital game-based learning by considering applications of the decision tree-based method. However, the technology acceptance model still needs to be determined to reveal findings from active and inactive students. With a validated questionnaire, the stepwise multiple regression technique was used to analyse the data collected from 434 samples in secondary school settings. It was found that active students thought an effective mobile game would include particular situations or tasks and the materials and methods influencing the adjustment of their behaviours. It is interesting to note that active students’ attitudes toward the decision tree-based contextual mobile gaming system are largely influenced by how easy they perceive the use of the system to be. Regarding the findings, this study discusses further implementation by properly developing and implementing the decision tree-based contextual mobile gaming approach to cultivate students’ digital citizenship competencies.