| Title: |
AI-Induced guidance: Preserving the optimal Zone of Proximal Development |
| Authors: |
Ferguson, Chris; van den Broek, Egon L.; van Oostendorp, Herre; Multimedia; Sub Multimedia; Sub Human-Centered Computing; Sub General Interaction |
| Publication Year: |
2022 |
| Subject Terms: |
Artificial intelligence in education (AIEd); discovery learning; textual specificity; Zone of proximal development (ZPD); Personalization; Experience; Artificial Intelligence; Education; Human-Computer Interaction; Experimental and Cognitive Psychology; SDG 4 - Quality Education |
| Description: |
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. |
| Document Type: |
article in journal/newspaper |
| File Description: |
text/plain |
| Language: |
English |
| ISSN: |
2666-920X |
| Relation: |
https://dspace.library.uu.nl/handle/1874/432394 |
| Availability: |
https://dspace.library.uu.nl/handle/1874/432394 |
| Rights: |
info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.91F30 |
| Database: |
BASE |