Abstract
Different types of learner models and their usefulness for tutoring have been discussed widely since the beginning of intelligent tutoring systems. In this paper we compare pragmatic and cognitive approaches of learner modeling. Pragmatic approaches consider relevant learner features for adaptive methods in learning environments and adapt different aspects of instruction to a restricted model representing these features. Cognitive approaches aim for a psychologically adequate modeling of human problem solving. We introduce the case-based learner model ELM as an example of a cognitive approach to learner modeling. The learning environments ELM-PE and ELM-ART use ELM for adaptional methods on conceptual, plan, and episodic levels and provide individual help and learning support. Especially in the case of integrated learning environments like ELM-ART which support a variety of learning activities, a combination of pragmatic and cognitive learner models is proposed to be a necessary and useful solution.
Zusammenfassung
Seit Beginn der Entwicklung tutorieller Systeme ist die Art der Modellierung von Lernenden in der Diskussion gewesen. In diesem Beitrag sollen pragmatische und kognitive Ansätze der Lernermodellierung diskutiert und kontrastiert werden. Während pragmatische Ansätze von einer Beschreibung des Zusammenhanges relevanter Eigenschaften von Lernenden und den Anpassungen eines adaptiven Lehr/Lernsystems ausgehen und die Information über Lernende auf einige für die Anpassungen relevante Dimensionen reduzieren, liegt die Betonung kognitiver Ansätze auf einer wissenspsychologisch adäquaten Modellierung der Fertigkeiten menschlicher Problemlöser. Als Beispiel für ein kognitives Lernermodell wird das fallbasierte Modell ELM vorgestellt. Die zwei Lehr/Lernsysteme ELM-PE und ELM-ART nutzen konzeptuelles Wissen, Planwissen und episodische Information des ELM-Modells zur individuellen Unterstützung von Lernaktivitäten. Besonders in integrierten Lehr/Lernumgebungen wie ELM-ART, in denen unterschiedlichste passive und aktive Lernprozesse unterstützt werden, wird eine Integration verschiedener Ansätze zur Lernermodellierung notwendig und nutzbringend.
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Diese Arbeit wurde gefördert durch ein Projekt der „Stiftung Rheinland-Pfalz für Innovation“ für den zweiten Autor.
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Specht, M., Weber, G. Kognitive Lernermodellierung. Kognit. Wiss. 6, 165–176 (1997). https://doi.org/10.1007/BF03354919
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DOI: https://doi.org/10.1007/BF03354919