Artificial intelligence and assistive technology: risks, rewards, challenges, and opportunities

Smith, Emma M.; Graham, David; Morgan, Cathal; MacLachlan, Malcolm

doi:10.1080/10400435.2023.2259247

Cited by 8 publications

(1 citation statement)

References 17 publications

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“…This gap highlights the pressing need for adaptive solutions that can personalize the learning experience and address individual learning preferences and abilities (Garcia, 2021). In response to this imperative, this paper proposes a novel approach to e-learning design, integrating artificial intelligence (AI) to create an adaptive learning system (Smith & Williams, 2023). By leveraging AI algorithms and drawing insights from pedagogical theories such as David Kolb's learning styles, the proposed system aims to revolutionize online education by offering tailored learning experiences (Taylor, 2022).…”

Section: Introductionmentioning

confidence: 99%

Crafting An AI-Powered Adaptive E-Learning Framework: Based on Kolb's Learning Style

Waladi,

Lamarti,

Khaldi

2024

Intl. J. Rel.

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In the contemporary educational realm, the convergence of pedagogical advancements with machine learning presents a profound opportunity for transformation. This in-depth exploration delves into the complexities of constructing an adaptive e-learning platform, seamlessly integrating Kolb's learning preferences with state-of-the-art machine learning techniques. At the core of this initiative lies the certification module, meticulously scrutinized to bolster its effectiveness in acknowledging student accomplishments. With a focus on personalized education driven by machine learning for error analysis, learner profiling, and content adaptation, this amalgamation reshapes the educational landscape, offering bespoke and dynamic learning journeys. By proposing an intelligent and dynamic adaptive learning system, this study addresses the constraints of passive and one-size-fits-all platforms, aiming to discern and furnish personalized learning environments tailored to the unique needs of individual learners within the hybrid teaching paradigm.

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Section: Introductionmentioning

confidence: 99%