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2024 | OriginalPaper | Chapter

3. AI-Driven and SOLO-Based Domain Knowledge Modeling in PARSAT AR Software

Authors : Christos Papakostas, Christos Troussas, Cleo Sgouropoulou

Published in: Special Topics in Artificial Intelligence and Augmented Reality

Publisher: Springer Nature Switzerland

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Abstract

This chapter of this book centers on the enrichment of the domain knowledge model through the incorporation of the Structure of Observed Learning Outcomes (SOLO) taxonomy. It investigates the correlation between the domain knowledge model and the SOLO taxonomy, offering practical instances of learning tasks aligned with each SOLO level. The “Overview” section introduces the chapter’s purpose, emphasizing the significance of aligning learning activities with SOLO-defined cognitive levels. The “Domain Model” section outlines the model’s objectives and relevance in spatial ability training, highlighting specific knowledge areas targeted in the mobile training system. In the “Domain Knowledge alongside SOLO Taxonomy” section, the integration of the SOLO taxonomy into the domain model is explored. This section underscores the importance of gradually developing students’ spatial ability through scaffolded learning experiences. The “Examples of Learning Activities of Each SOLO Level” section furnishes detailed examples of learning activities spanning from prestructural to extended abstract SOLO levels. These examples illustrate the practical application of the SOLO taxonomy within the domain knowledge model. The “Summary” section concludes by summarizing key points, highlighting the integration of the SOLO taxonomy as a scaffolding mechanism to enhance spatial ability training. This chapter serves as the foundation for subsequent chapters, which delve into the implementation and evaluation of the mobile training system.

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previous chapter Review of the Literature on AI-Enhanced Augmented Reality in Education

next chapter Fuzzy Logic for Modeling the Knowledge of Users in PARSAT AR Software

C. Papakostas, C. Troussas, A. Krouska, and C. Sgouropoulou, “On the development of a personalized augmented reality spatial ability training mobile application,” in Frontiers in Artificial Intelligence and Applications, IOS Press, 2021, pp. V–VI. https://doi.org/10.3233/FAIA210078.

C. Papakostas, C. Troussas, A. Krouska, and C. Sgouropoulou, “Exploration of Augmented Reality in Spatial Abilities Training: A Systematic Literature Review for the Last Decade,” Informatics in Education, vol. 20, no. 1, pp. 107–130, Mar. 2021, https://doi.org/10.15388/infedu.2021.06.

P. Strousopoulos, C. Papakostas, C. Troussas, A. Krouska, P. Mylonas, and C. Sgouropoulou, “SculptMate: Personalizing Cultural Heritage Experience Using Fuzzy Weights,” in Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, in UMAP ’23 Adjunct. New York, NY, USA: Association for Computing Machinery, 2023, pp. 397–407. https://doi.org/10.1145/3563359.3596667.

C. Troussas, C. Papakostas, A. Krouska, P. Mylonas, and C. Sgouropoulou, “Personalized Feedback Enhanced by Natural Language Processing in Intelligent Tutoring Systems,” in Augmented Intelligence and Intelligent Tutoring Systems, C. Frasson, P. Mylonas, and C. Troussas, Eds., Cham: Springer Nature Switzerland, 2023, pp. 667–677. https://doi.org/10.1007/978-3-031-32883-1_58.CrossRef

C. Papakostas, C. Troussas, A. Krouska, and C. Sgouropoulou, “Exploring Users’ Behavioral Intention to Adopt Mobile Augmented Reality in Education through an Extended Technology Acceptance Model,” Int J Hum Comput Interact, vol. 39, no. 6, pp. 1294–1302, 2023, https://doi.org/10.1080/10447318.2022.2062551.CrossRef

C. Papakostas, C. Troussas, A. Krouska, and C. Sgouropoulou, “Modeling the Knowledge of Users in an Augmented Reality-Based Learning Environment Using Fuzzy Logic,” in Lecture Notes in Networks and Systems, A. Krouska, C. Troussas, and J. Caro, Eds., Cham: Springer International Publishing, 2023, pp. 113–123. https://doi.org/10.1007/978-3-031-17601-2_12.CrossRef

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C. Troussas, A. Krouska, and C. Sgouropoulou, “Enriching Mobile Learning Software with Interactive Activities and Motivational Feedback for Advancing Users’ High-Level Cognitive Skills,” Computers, vol. 11, no. 2, 2022, https://doi.org/10.3390/computers11020018.

A. Krouska, C. Troussas, and C. Sgouropoulou, “Fuzzy Logic for Refining the Evaluation of Learners’ Performance in Online Engineering Education,” European Journal of Engineering Research and Science, vol. 4, pp. 50–56, Jun. 2019, https://doi.org/10.24018/ejers.2019.4.6.1369.

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A. Marougkas, C. Troussas, A. Krouska, and C. Sgouropoulou, “A Framework for Personalized Fully Immersive Virtual Reality Learning Environments with Gamified Design in Education,” 2021. https://doi.org/10.3233/FAIA210080.CrossRef

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C. Troussas, A. Krouska, and C. Sgouropoulou, “Dynamic Detection of Learning Modalities Using Fuzzy Logic in Students’ Interaction Activities,” in Intelligent Tutoring Systems, V. Kumar and C. Troussas, Eds., Cham: Springer International Publishing, 2020, pp. 205–213.CrossRef

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A. Krouska, C. Troussas, and C. Sgouropoulou, “A novel group recommender system for domain-independent decision support customizing a grouping genetic algorithm,” User Model User-adapt Interact, 2023, https://doi.org/10.1007/s11257-023-09360-3.

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C. Papakostas, C. Troussas, P. Douros, M. Poli, and C. Sgouropoulou, “CoMoPAR: A Comprehensive Conceptual Model for Designing Personalized Augmented Reality Systems in Education,” in Novel & Intelligent Digital Systems: Proceedings of the 3rd International Conference (NiDS 2023), K. Kabassi, P. Mylonas, and J. Caro, Eds., Cham: Springer Nature Switzerland, 2023, pp. 67–79.

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C. Papakostas, C. Troussas, A. Krouska, and C. Sgouropoulou, “Personalization of the Learning Path within an Augmented Reality Spatial Ability Training Application Based on Fuzzy Weights,” Sensors, vol. 22, no. 18, 2022, https://doi.org/10.3390/s22187059.

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M. Iakovidis, C. Papakostas, C. Troussas, and C. Sgouropoulou, “Empowering Responsible Digital Citizenship Through an Augmented Reality Educational Game,” in Novel & Intelligent Digital Systems: Proceedings of the 3rd International Conference (NiDS 2023), K. Kabassi, P. Mylonas, and J. Caro, Eds., Cham: Springer Nature Switzerland, 2023, pp. 31–39.

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P. Strousopoulos, C. Troussas, C. Papakostas, A. Krouska, and C. Sgouropoulou, “Revolutionizing Agricultural Education with Virtual Reality and Gamification: A Novel Approach for Enhancing Knowledge Transfer and Skill Acquisition,” in Novel & Intelligent Digital Systems: Proceedings of the 3rd International Conference (NiDS 2023), K. Kabassi, P. Mylonas, and J. Caro, Eds., Cham: Springer Nature Switzerland, 2023, pp. 67–80.

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C. Papakostas, C. Troussas, A. Krouska, and C. Sgouropoulou, “PARSAT: Fuzzy logic for adaptive spatial ability training in an augmented reality system,” Computer Science and Information Systems, vol. 20, no. 4, 2023, https://doi.org/10.2298/CSIS230130043P.

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Title: AI-Driven and SOLO-Based Domain Knowledge Modeling in PARSAT AR Software
Authors: Christos Papakostas
Christos Troussas
Cleo Sgouropoulou
Publisher: Springer Nature Switzerland
Book: Special Topics in Artificial Intelligence and Augmented Reality
Print ISBN: 978-3-031-52004-4

Electronic ISBN: 978-3-031-52005-1

Copyright Year: 2024
DOI: https://doi.org/10.1007/978-3-031-52005-1_3

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