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

Sección IA: Inteligencia artificial Bibliografía

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

Chris Ferguson
Egon L. van den Broek
Herre van Oostendorp
2022
Computers & Education: Artificial Intelligence
3
https://www.sciencedirect.com/science/a…
artículo
estudio experimental
estudio empírico
inteligencia artificial
andamiaje/scaffolding
juegos
cognición y procesamiento
teoría sociocultural
IA y aprendizaje
estudio empírico

Texto completo

Holding the promise of higher learning outcomes, discovery learning utilizes intrinsic motivation to provide an enjoyable self-directed learning experience. Unfortunately, this approach can also lead to a sub-optimal cognitive load, which hinders learning. To avoid this, players must be in the optimal Zone of Proximal Development (ZPD). A way of accomplishing this is to make use of Artificial Intelligence in a narrative-centered discovery game using adaptive guidance. Textual instructions were automatically adapted in real-time to ensure a personalized challenge for one group of learners, where a control group received static instructions. Compared to the control group, the learners with personalized instructions showed higher story and spatial learning, while having decreased cognitive load and a similar learning experience. So, instructions given to self-directed learners can be personalized in real-time, which not only reduces learners’ cognitive load but also leads to enhanced learning outcomes without affecting the learning experience.

Texto completo en abierto (CC BY-NC-ND 4.0).
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