Students' Acceptance of Gamification in Higher Education

[[abstract]]Gamification provides a practical approach to improving learning processes, especially the learner's motivation. However, little research has been conducted on student intentions to use gamification in higher education. Therefore, this study explored the gamification in higher educational courses by collecting surveys and discusses the factors influencing the acceptance of gamification in higher education. Based on the PLS-SEM results, students should take initial game-based learning content to be more familiar with gamification; furthermore, they could have a positive experience so that they would increase their intention. Performance expectancy is the most important factors influencing a student to accept gamification. Other factors, such as effort expectancy, social influence, facilitating conditions, involvement, skill, and control, are also important factors. With the results of this study, the instructor designer could have substantial help in planning the course content and enhance its efficiency and effectiveness.[[notice]]補正完

Effect of Demographics on Use Intention of Gamified Systems

WOS: 000413325200001Gamification has become an influential term in diverse fields ranging from education to systems development and marketing. The recent intensifying emphasis is attributable to enabling technologies and successful practical applications used for changing attitudes and increasing engagement. However, relevant academic studies are not wide-spread and this study aims to address this vital research gap. This study is structured to understand the factors affecting intention to use gamified systems and test whether they are affected by gender or age. An online survey study was conducted on a web-based gamified system (EmpireAvenue.com) and following a detailed screening process, a total of 168 fully complete questionnaires were attained. The theoretical model employed was developed upon technology acceptance model (TAM) and modified to incorporate an intrinsic motivation element, namely the "perceived enjoyment" construct. According to the findings, age and gender moderate the relationships between usefulness, ease of use, perceived enjoyment and intention to use the gamified system

Artificial Neural Networks and other AI Applications for Business Management Decision Support

Artificial intelligence (AI) in general and artificial neural networks (ANN) in particular provide a tremendous amount of knowledge to improve managerial decision making. Additionally, these same ANN and AI techniques also serve as knowledge repositories and distribution schema for organizations that facilitate managerial leadership responsibilities. This article examines how various ANN and other AI applications may be adapted to facilitate managerial leadership, improve manager performance and in some cases perform management activities. Further research that classifies leadership styles and the desired qualities of leaders is reviewed