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Improving Learner-Computer Interaction through Intelligent Learning Material Delivery Using Instructional Design Modeling

Department of Informatics and Computer Engineering, University of West Attica, 12243 Egaleo, Greece
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Academic Editor: Salim Lahmiri
Entropy 2021, 23(6), 668; https://doi.org/10.3390/e23060668
Received: 5 May 2021 / Revised: 21 May 2021 / Accepted: 25 May 2021 / Published: 26 May 2021
(This article belongs to the Special Issue Interactive Artificial Intelligence and Man-Machine Communication)
This paper describes an innovative and sophisticated approach for improving learner-computer interaction in the tutoring of Java programming through the delivery of adequate learning material to learners. To achieve this, an instructional theory and intelligent techniques are combined, namely the Component Display Theory along with content-based filtering and multiple-criteria decision analysis, with the intention of providing personalized learning material and thus, improving student interaction. Until now, the majority of the research efforts mainly focus on adapting the presentation of learning material based on students’ characteristics. As such, there is free space for researching issues like delivering the appropriate type of learning material, in order to maintain the pedagogical affordance of the educational software. The blending of instructional design theories and sophisticated techniques can offer a more personalized and adaptive learning experience to learners of computer programming. The paper presents a fully operating intelligent educational software. It merges pedagogical and technological approaches for sophisticated learning material delivery to students. Moreover, it was used by undergraduate university students to learn Java programming for a semester during the COVID-19 lockdown. The findings of the evaluation showed that the presented way for delivering the Java learning material surpassed other approaches incorporating merely instructional models or intelligent tools, in terms of satisfaction and knowledge acquisition. View Full-Text
Keywords: adaptive learning material delivery; Component Display Theory; content-based filtering; Intelligent Tutoring Systems; Multiple-Criteria Decision Analysis; online learning; Weighted Sum Model adaptive learning material delivery; Component Display Theory; content-based filtering; Intelligent Tutoring Systems; Multiple-Criteria Decision Analysis; online learning; Weighted Sum Model
MDPI and ACS Style

Troussas, C.; Krouska, A.; Sgouropoulou, C. Improving Learner-Computer Interaction through Intelligent Learning Material Delivery Using Instructional Design Modeling. Entropy 2021, 23, 668. https://doi.org/10.3390/e23060668

AMA Style

Troussas C, Krouska A, Sgouropoulou C. Improving Learner-Computer Interaction through Intelligent Learning Material Delivery Using Instructional Design Modeling. Entropy. 2021; 23(6):668. https://doi.org/10.3390/e23060668

Chicago/Turabian Style

Troussas, Christos, Akrivi Krouska, and Cleo Sgouropoulou. 2021. "Improving Learner-Computer Interaction through Intelligent Learning Material Delivery Using Instructional Design Modeling" Entropy 23, no. 6: 668. https://doi.org/10.3390/e23060668

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