AI-Induced guidance: Preserving the optimal Zone of Proximal Development

Ferguson, Chris; Broek, Egon L. van den; Oostendorp, Herre van

doi:10.1016/j.caeai.2022.100089

Cited by 5 publications

(2 citation statements)

References 59 publications

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“…Concurrent feedback is seen as one of the factors that foster immersion [32]. Yet, the combination of concentration and enjoyment that makes students forget about their environment or what is also referred to as 'flow' results from an optimal balance between skill and challenge [37].…”

Section: Discussionmentioning

confidence: 99%

A Virtual Reality Laboratory for Blended Learning Education: Design, Implementation and Evaluation

et al. 2023

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Launched during the pandemic, the EU-funded JANUS project aimed to ensure the continuity of student workshops at universities using a virtual reality (VR) robotics laboratory. With the return to normality, the project has been redesigned to capitalise on the positive outcomes of the experience. The VR lab provides safe and unrestricted access to the labs and experiments with the machines, reducing the consequences of student mistakes and improving the user experience by allowing the experiment to be repeated from different angles, some of which are impossible to access in the real lab. In addition, integration with an interactive learning platform called “ViLLE” allows for continuous assessment of the learning experience. Self-evaluation of the material taught and learned can be integrated with the execution of the exercises that pave the way for Kaizen. Two VR workshops for the blended learning of robotics were developed during the JANUS project. Their evaluation reported favourable responses from the students whose learning performance was indirectly measured.

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Section: Discussionmentioning

confidence: 99%

A Virtual Reality Laboratory for Blended Learning Education: Design, Implementation and Evaluation

et al. 2023

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“…ZPD is applied in various educational contexts, such as adaptive quiz question recommendations [19] and navigating optimized learning paths [20]. It reduces cognitive load and improves learning outcomes without affecting the learning experience [21]. ZPD is also utilized in specific fields like clinical education [22], participatory scenario planning [23], and divergent thinking [24].…”

Section: Related Workmentioning

confidence: 99%

An Adaptive Testcase Recommendation System to Engage Students in Learning: A Practice Study in Fundamental Programming Courses

Vu-Van¹,

Tran²,

Le³

et al. 2023

IJACSA

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This paper proposes a testcase recommendation system (TRS) to assist beginner-level learners in introductory programming courses with completing assignments on a learning management system (LMS). These learners often struggle to generate complex testcases and handle numerous code errors, leading to disengaging their attention from the study. The proposed TRS addresses this problem by applying the recommendation system using singular value decomposition (SVD) and the zone of proximal development (ZPD) to provide a small and appropriate set of testcases based on the learner's ability. We implement this TRS to the university-level Fundamental Programming courses for evaluation. The data analysis has demonstrated that TRS significantly increases student interactions with the system. Keywords-Testcases recommendation system (TRS); learning management system (LMS); zone of proximal development (ZPD); singular value decomposition (SVD)

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How should we change teaching and assessment in response to increasingly powerful generative Artificial Intelligence? Outcomes of the ChatGPT teacher survey

Bower,

Torrington,

Lai

et al. 2024

Educ Inf Technol

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There has been widespread media commentary about the potential impact of generative Artificial Intelligence (AI) such as ChatGPT on the Education field, but little examination at scale of how educators believe teaching and assessment should change as a result of generative AI. This mixed methods study examines the views of educators (n = 318) from a diverse range of teaching levels, experience levels, discipline areas, and regions about the impact of AI on teaching and assessment, the ways that they believe teaching and assessment should change, and the key motivations for changing their practices. The majority of teachers felt that generative AI would have a major or profound impact on teaching and assessment, though a sizeable minority felt it would have a little or no impact. Teaching level, experience, discipline area, region, and gender all significantly influenced perceived impact of generative AI on teaching and assessment. Higher levels of awareness of generative AI predicted higher perceived impact, pointing to the possibility of an ‘ignorance effect’. Thematic analysis revealed the specific curriculum, pedagogy, and assessment changes that teachers feel are needed as a result of generative AI, which centre around learning with AI, higher-order thinking, ethical values, a focus on learning processes and face-to-face relational learning. Teachers were most motivated to change their teaching and assessment practices to increase the performance expectancy of their students and themselves. We conclude by discussing the implications of these findings in a world with increasingly prevalent AI.

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AI-Induced guidance: Preserving the optimal Zone of Proximal Development

Cited by 5 publications

References 59 publications

A Virtual Reality Laboratory for Blended Learning Education: Design, Implementation and Evaluation

A Virtual Reality Laboratory for Blended Learning Education: Design, Implementation and Evaluation

An Adaptive Testcase Recommendation System to Engage Students in Learning: A Practice Study in Fundamental Programming Courses

How should we change teaching and assessment in response to increasingly powerful generative Artificial Intelligence? Outcomes of the ChatGPT teacher survey

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