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Volume 15
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Article

Delphi-Based Expert Evaluation of the XR2Learn Hybrid Instructional Design Framework for XR Education

by
Christoforos Karachristos
1,*,
Theodora Kouvara
1,
Vasilis Zafeiropoulos
1,*,
Theofanis Orphanoudakis
1,2,
Giorgos Anastasakis
1,
Alessandra Antonaci
3,
Ioannis Chatzigiannakis
4,
Maria Paola Conte
5,
Angelica Marsico
5,
Sindi Devole
5,
Silvia Giordano
6 and
Matteo Besenzoni
6
1
School of Science and Technology, Hellenic Open University, 26331 Patras, Greece
2
Department of Industrial Design and Production Engineering, University of West Attica, Egaleo, 12243 Athens, Greece
3
EADTU-European Association of Distance Teaching Universities, 6212 XN Maastricht, The Netherlands
4
Department of Computer, Control and Management Engineering, Sapienza University of Rome, 00185 Rome, Italy
5
EIT Manufacturing South S.r.l., 20121 Milano, Italy
6
Department of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, 6962 Viganello, Switzerland
*
Authors to whom correspondence should be addressed.
Computers 2026, 15(2), 131; https://doi.org/10.3390/computers15020131
Submission received: 1 December 2025 / Revised: 5 February 2026 / Accepted: 10 February 2026 / Published: 19 February 2026
(This article belongs to the Special Issue Extended or Mixed Reality (AR + VR): Technology and Applications (2nd Edition))
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Abstract

Extended Reality (XR) has reshaped how learning can be structured, yet its integration into formal curricula continues to lag behind its technological potential. Established instructional design models such as ADDIE and ASSURE provide stable planning structures, but were not developed to address the spatial, embodied and interactive characteristics of immersive environments. The XR2Learn framework was developed to bridge this gap by combining structured instructional planning with XR-specific pedagogical considerations. This study presents a multi-round Delphi-based expert evaluation of XR2Learn, involving twenty specialists in instructional design and XR-enhanced education. Experts assessed the framework across four dimensions: validity, clarity, usability and suitability. Qualitative feedback was thematically analyzed and subsequently quantified to establish consensus. The findings show strong agreement regarding the framework’s pedagogical grounding, logical structure and alignment with established instructional design practices. At the same time, experts identified limitations related to practical enactment, accessibility and the explicit integration of XR-specific learning constructs such as presence and social interaction. Overall, the results position XR2Learn as a framework at a transitional stage, moving from conceptual formulation toward practical instructional use. The study provides the first systematic expert validation of XR2Learn and outlines targeted directions for its refinement as a robust instructional design framework for XR-based education.
Keywords: instructional design framework; Delphi study; immersive learning; Extended Reality (XR); educational technology; pedagogical innovation instructional design framework; Delphi study; immersive learning; Extended Reality (XR); educational technology; pedagogical innovation

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MDPI and ACS Style

Karachristos, C.; Kouvara, T.; Zafeiropoulos, V.; Orphanoudakis, T.; Anastasakis, G.; Antonaci, A.; Chatzigiannakis, I.; Conte, M.P.; Marsico, A.; Devole, S.; et al. Delphi-Based Expert Evaluation of the XR2Learn Hybrid Instructional Design Framework for XR Education. Computers 2026, 15, 131. https://doi.org/10.3390/computers15020131

AMA Style

Karachristos C, Kouvara T, Zafeiropoulos V, Orphanoudakis T, Anastasakis G, Antonaci A, Chatzigiannakis I, Conte MP, Marsico A, Devole S, et al. Delphi-Based Expert Evaluation of the XR2Learn Hybrid Instructional Design Framework for XR Education. Computers. 2026; 15(2):131. https://doi.org/10.3390/computers15020131

Chicago/Turabian Style

Karachristos, Christoforos, Theodora Kouvara, Vasilis Zafeiropoulos, Theofanis Orphanoudakis, Giorgos Anastasakis, Alessandra Antonaci, Ioannis Chatzigiannakis, Maria Paola Conte, Angelica Marsico, Sindi Devole, and et al. 2026. "Delphi-Based Expert Evaluation of the XR2Learn Hybrid Instructional Design Framework for XR Education" Computers 15, no. 2: 131. https://doi.org/10.3390/computers15020131

APA Style

Karachristos, C., Kouvara, T., Zafeiropoulos, V., Orphanoudakis, T., Anastasakis, G., Antonaci, A., Chatzigiannakis, I., Conte, M. P., Marsico, A., Devole, S., Giordano, S., & Besenzoni, M. (2026). Delphi-Based Expert Evaluation of the XR2Learn Hybrid Instructional Design Framework for XR Education. Computers, 15(2), 131. https://doi.org/10.3390/computers15020131

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