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Authors = Sylvester Arnab

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16 pages, 2213 KiB  
Article
Efficacy of the 4F Feedback Model: A Game-Based Assessment in University Education
by Sara de Freitas, Victoria Uren, Kristian Kiili, Manuel Ninaus, Panagiotis Petridis, Petros Lameras, Ian Dunwell, Sylvester Arnab, Stephen Jarvis and Kam Star
Information 2023, 14(2), 99; https://doi.org/10.3390/info14020099 - 6 Feb 2023
Cited by 6 | Viewed by 5434
Abstract
Feedback is a critical aspect of optimised learning design, but there are few, if any, feedback models that map different types of feedback and how they may assist students to increase performance and enhance their learning experience. This research paper outlines a feedback [...] Read more.
Feedback is a critical aspect of optimised learning design, but there are few, if any, feedback models that map different types of feedback and how they may assist students to increase performance and enhance their learning experience. This research paper outlines a feedback model as an extension of the four-dimensional framework which includes a consideration of the type, the content, the format, and the frequency of feedback, as well as the agent which delivers it. This model is based upon an understanding of learning in the context of designing learning experiences and utilises a game-based model of learning to understand the importance of motivation and autonomy in learners to enhance and accelerate learning. The framework is developed and reflected upon by analysing two cases: a medical triage case in which the timing and frequency of feedback proved critical, and a business simulation which illuminated the need for a range of types of feedback and to be aware of the possibility of different agents (instructor peer and game) that can deliver feedback. The extended model may help game and learning designers alike to discern different types of feedback, both in games and more generally, in more explicit and nuanced ways. Full article
(This article belongs to the Special Issue Artificial Intelligence and Games Science in Education)
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27 pages, 2242 KiB  
Review
Serious Gaming for Behaviour Change: A Systematic Review
by Ramy Hammady and Sylvester Arnab
Information 2022, 13(3), 142; https://doi.org/10.3390/info13030142 - 8 Mar 2022
Cited by 49 | Viewed by 16398
Abstract
Over the years, there has been a significant increase in the adoption of game-based interventions for behaviour change associated with many fields such as health, education, and psychology. This is due to the significance of the players’ intrinsic motivation that is naturally generated [...] Read more.
Over the years, there has been a significant increase in the adoption of game-based interventions for behaviour change associated with many fields such as health, education, and psychology. This is due to the significance of the players’ intrinsic motivation that is naturally generated to play games and the substantial impact they can have on players. Many review papers measure the effectiveness of the use of gaming on changing behaviours; however, these studies neglect the game features involved in the game design process, which have an impact of stimulating behaviour change. Therefore, this paper aimed to identify game design mechanics and features that are reported to commonly influence behaviour change during and/or after the interventions. This paper identified key theories of behaviour change that inform the game design process, providing insights that can be adopted by game designers for informing considerations on the use of game features for moderating behaviour in their own games. Full article
(This article belongs to the Section Review)
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38 pages, 3054 KiB  
Review
Power to the Teachers: An Exploratory Review on Artificial Intelligence in Education
by Petros Lameras and Sylvester Arnab
Information 2022, 13(1), 14; https://doi.org/10.3390/info13010014 - 29 Dec 2021
Cited by 141 | Viewed by 33724
Abstract
This exploratory review attempted to gather evidence from the literature by shedding light on the emerging phenomenon of conceptualising the impact of artificial intelligence in education. The review utilised the PRISMA framework to review the analysis and synthesis process encompassing the search, screening, [...] Read more.
This exploratory review attempted to gather evidence from the literature by shedding light on the emerging phenomenon of conceptualising the impact of artificial intelligence in education. The review utilised the PRISMA framework to review the analysis and synthesis process encompassing the search, screening, coding, and data analysis strategy of 141 items included in the corpus. Key findings extracted from the review incorporate a taxonomy of artificial intelligence applications with associated teaching and learning practice and a framework for helping teachers to develop and self-reflect on the skills and capabilities envisioned for employing artificial intelligence in education. Implications for ethical use and a set of propositions for enacting teaching and learning using artificial intelligence are demarcated. The findings of this review contribute to developing a better understanding of how artificial intelligence may enhance teachers’ roles as catalysts in designing, visualising, and orchestrating AI-enabled teaching and learning, and this will, in turn, help to proliferate AI-systems that render computational representations based on meaningful data-driven inferences of the pedagogy, domain, and learner models. Full article
(This article belongs to the Special Issue Artificial Intelligence and Games Science in Education)
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