Predictive Model for Factors Influencing Students’ Continuance Usage Intention on a Gamified Formative Assessment Application

IF 0.8 Q3 EDUCATION & EDUCATIONAL RESEARCH
Rosfuzah Roslan, Ahmad Fauzi Mohd Ayub, Norliza Ghazali, Nurul Nadwa Zulkifli, Siti Noor Haslina Md Latip, Siti Syuhada Abu Hanifah
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引用次数: 0

Abstract

Formative assessments help students identify their strengths and weaknesses as well as the target areas that need work. Meanwhile, the success of gamification implementation in mobile learning (m-learning) applications has been proven by many research associated with technology acceptance. However, studies on the technology post-acceptance phase are scarce. Deploying gamification concepts in competency-based education and assessment method, aim to diversify the game dynamics usage in new and practical areas such as technical and vocational education. Therefore, this study focused on the development of a predictive model for a gamified m-learning application that extends the Expectation Confirmation Model (ECM) with perceived enjoyment. This study applied a correlational research design on the students of Technical and Vocational Education and Training (TVET) based diploma programmes in one of Malaysian public university. An online survey was conducted, and garnered 269 responses, which were used in the final analysis based on the Partial Least Square-Structural Equation Modelling (PLS-SEM). The findings showed that all the factors in the model, which are the confirmation of expectation, satisfaction, perceived usefulness and perceived enjoyment, appeared to be significantly influencing the students’ continuance usage intention towards the gamified m-learning application as well as jointly explained 64.6% (R2) of the changes. The addition of variable perceived enjoyment provided an increment of 2.7% compared to the R2 value of the original ECM model. Most importantly, the proposed extended ECM proved to be a reliable prediction model when the Q2 values for continuance use intention and perceived usefulness displayed strong predictive accuracy, having 0.368 (Q2) for both variables, while satisfaction showed moderate strength with the value of 0.305 (Q2). Therefore, the predictive model is reliable to be used to investigate future usage and effective designs of gamified m-learning products among the technical and vocational education students in other Higher Education Institution (HEI).
游戏化形成性评价应用中学生继续使用意愿影响因素预测模型
形成性评估帮助学生识别自己的优势和劣势,以及需要努力的目标领域。与此同时,许多与技术接受度相关的研究已经证明,在移动学习(m-learning)应用中实现游戏化的成功。然而,对技术验收后阶段的研究却很少。将游戏化概念应用于能力本位教育和评估方法中,旨在使游戏动力学在技术和职业教育等新的实用领域的应用多样化。因此,本研究的重点是开发一个游戏化移动学习应用程序的预测模型,该模型扩展了期望确认模型(ECM)的感知享受。本研究对马来西亚一所公立大学的技术与职业教育与培训(TVET)文凭课程的学生进行了相关研究设计。我们进行了一项在线调查,获得了269份回复,这些回复被用于基于偏最小二乘结构方程模型(PLS-SEM)的最终分析。研究结果表明,模型中的期望确认、满意度、感知有用性和感知享受都显著影响了学生对游戏化移动学习应用的继续使用意愿,并共同解释了64.6% (R2)的变化。与原始ECM模型的R2值相比,变量感知享受的增加提供了2.7%的增量。最重要的是,当持续使用意愿和感知有用性的Q2值显示出较强的预测准确性时,所提出的扩展ECM被证明是一个可靠的预测模型,两个变量的预测精度均为0.368 (Q2),而满意度的预测精度为0.305 (Q2)。因此,该预测模型可用于研究其他高等院校技职教育学生对游戏化移动学习产品的未来使用和有效设计。
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来源期刊
Journal of Technical Education and Training
Journal of Technical Education and Training EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
2.10
自引率
14.30%
发文量
12
期刊介绍: JTET will consider for publications original research articles, critical reviews as well as technical reports that can further our understanding of TVET issues and concerns
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