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Discourse Analysis on Learning Theories and AI

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Intelligent Computing (SAI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1230))

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Abstract

The intent of the study was to identify the dialogue and discourse on how AI development includes and/or excludes pedagogical educational learning theories focused on the learner. Through identifying areas of intersection between AI development and learning theories, educational leaders can interface with developers and content experts to establish optimal teaching skills and strategies for the ethical ‘good’ of the learner. The review of the discourse in the literature revealed surprisingly limited intersections between AI and learning theories, with a tool-centric literature, coupled with efficiency evaluations and developmental narratives. The following three conceptual questions to engage in dialogue between AI developers and educational leaders surrounding AI and learning theories were proposed: (1) Who ultimately controls the curriculum? (2) Are cognitive theories primarily utilized in constructing AI algorithms? (3) What is encapsulated in AI’s hidden curriculum and how is bias/discrimination accounted for? The opportunity for educational leaders and theorists of learning to engage with AI developers and super-intelligence is necessary for the ‘good’ of what is developed artificially. If teachers are viewed as only content experts without acknowledgement of the multiple strategies they use to inspire and encourage students, then AI development may get teaching very wrong.

R. Brown—Educational Consultant.

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Correspondence to Rosemary Papa .

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Papa, R., Jackson, K.M., Brown, R., Jackson, D. (2020). Discourse Analysis on Learning Theories and AI. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2020. Advances in Intelligent Systems and Computing, vol 1230. Springer, Cham. https://doi.org/10.1007/978-3-030-52243-8_50

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