Literaturnachweis - Detailanzeige
Autor/inn/en | Aleven, Vincent; Mavrikis, Manolis; McLaren, Bruce; Nguyen, Huy A.; Olsen, Jennifer K.; Rummel, Nikol |
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Titel | Six instructional approaches supported in AIED systems. |
Quelle | Aus: DuBoulay, Benedict (Hrsg.); Mitrovic, Antonija (Hrsg.); Yacef, Kalina (Hrsg.): Handbook of artificial intelligence in education. Cheltenham u.a.: Edward Elgar Publishing (2023) S. 184-228
PDF als Volltext |
Reihe | Elgar handbooks in education |
Sprache | englisch |
Dokumenttyp | online; gedruckt; Sammelwerksbeitrag |
ISBN | 978-1-80037-540-6; 978-1-80037-541-3 |
DOI | 10.4337/9781800375413.00019 |
Schlagwörter | Bildung; Problemlösen; Künstliche Intelligenz; Spiel; Lernen; Beispiel; Lernen durch Lehren; Unterrichtsziel; Kollaboration; Unterstützung |
Abstract | This chapter reviews AIED implementations of six well-known instructional approaches, namely learning from problem-solving practice, learning from examples, exploratory learning, collaborative learning, game-based learning and learning-by-teaching. We explore the advantages of using AI in implementing these approaches. In our analysis, we take guidance from two complementary conceptual frameworks: first, the "S/vL framework" (Soller et al., 2005; VanLehn, 2016), which focuses on the level of assistance given to learners, and second, the "Adaptivity Grid" (Aleven et al., 2017), which distinguishes the ways this assistance can adapt to learners. Our review finds many variations of adaptive coaching within AIED systems. As well, many systems support multiple instructional goals. By providing assistance and adaptivity, AIED technologies help make feasible the use of the instructional approaches reviewed in this chapter in many educational settings. The great variability in adaptive coaching within AIED systems indicates a need for more conceptual work and a fine-grained taxonomy of coaching. (übernommen). |
Erfasst von | DIPF | Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main |
Update | 2025/2 |