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Lernpfade in adaptiven und künstlich-intelligenten Lernprogrammen. Eine kritische Analyse aus mediendidaktischer Sicht

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Künstliche Intelligenz in der Bildung

Zusammenfassung

Der Beitrag kontrastiert interaktive, adaptive sowie künstlich-intelligente (KI-)Lernprogramme, die sich in der Anlage ihrer Lernpfade unterscheiden. Adaptive und KI-basierte Anwendungen haben sich gegenüber einfacheren, interaktiven Anwendungen bislang in der Bildungspraxis nicht durchsetzen können. Anhand der Analyse von drei Beispielen wird gezeigt, dass sich adaptive Lernprogramme besonders für den angeleiteten Erwerb von Fertigkeiten eignen; KI-basierte Lösungen (mit »Learning Analytics«) erscheinen besonders interessant, wenn sich ein Expertisemodell nicht explizieren lässt, sondern durch Beobachtung erschlossen werden soll bzw. kann. Die Grenzen adaptiver Lernanwendungen (mit oder ohne KI) und die didaktischen Herausforderungen werden benannt, denen sich KI-basierte Lernanwendungen stellen müssen.

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Kerres, M., Buntins, K., Buchner, J., Drachsler, H., Zawacki-Richter, O. (2023). Lernpfade in adaptiven und künstlich-intelligenten Lernprogrammen. Eine kritische Analyse aus mediendidaktischer Sicht. In: de Witt, C., Gloerfeld, C., Wrede, S.E. (eds) Künstliche Intelligenz in der Bildung. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-40079-8_6

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