Immersive Literary Learning Through Augmented Reality: Evaluating Cognitive Engagement Using a Rasch Measurement Approach

Authors

  • Onok Yayang Pamungkas Indonesian Language and Literature Education, Universitas Muhammadiyah Purwokerto, Indonesia Author
  • Achmad Fauzan Informatics Engineering, Universitas Muhammadiyah Purwokerto, Indonesia Author
  • Lahan Adi Purwanto Informatics Engineering, Universitas Muhammadiyah Purwokerto, Indonesia Author
  • Feisal Aziez English Language and Education, Universitas Muhammadiyah Purwokerto, Indonesia Author
  • Akhmad Fauzan English Language and Education, Universitas Muhammadiyah Purwokerto, Indonesia Author

DOI:

https://doi.org/10.65638/2978-8811.2026.02.03

Keywords:

Augmented reality learning, Literary psychology, Rasch model, Cognitive engagement, Measurement validity, Immersive education, Educational assessment

Abstract

This study examines the measurement quality and cognitive engagement of students in augmented reality–based literary psychology learning using a Rasch model framework. A total of 52 undergraduate students participated in the implementation of an Augmented Reality Psychology Sastra (ARPS) application, which integrates visual-interactive features with literary psychological concepts. Data were collected through a 24-item dichotomous quiz designed to capture multiple levels of cognitive processing, including conceptual understanding, character interpretation, and inferential reasoning. Rasch analysis revealed acceptable measurement properties, with person reliability of 0.78 and item reliability of 0.91, indicating consistent responses and stable item calibration. Item fit statistics showed that all items functioned within acceptable limits (0.88–1.22), supporting construct validity. However, the Wright Map indicated a targeting mismatch, with mean person ability exceeding item difficulty (+0.42 logits), suggesting that the instrument was relatively easy for most participants. Person fit analysis further confirmed response consistency, with only 5.8% misfit cases. These findings suggest that augmented reality enhances cognitive performance through immersive and multimodal learning experiences, while also highlighting the need for more complex items to improve measurement sensitivity at higher ability levels. The study contributes to the integration of immersive learning technologies and psychometric validation in literary education contexts.

References

Akçayır, M., & Akçayır, G. (2017). Advantages and challenges associated with augmented reality for education: A systematic review. Educational Research Review, 20, 1-11. https://doi.org/10.1016/j.edurev.2016.11.002

Bacca, J., Baldiris, S., Fabregat, R., Graf, S., & Kinshuk. (2014). Augmented reality trends in education: A systematic review of research and applications. Educational Technology & Society, 17(4), 133-149.

Boone, W. J. (2020). Rasch analysis for instrument development: Why, when, and how? CBE—Life Sciences Education, 19(4), es9.

Bond, T. G., & Fox, C. M. (2015). Applying the Rasch model: Fundamental measurement in the human sciences (3rd ed.). Routledge.

Brookhart, S. M. (2010). How to assess higher-order thinking skills in your classroom. ASCD.

Bruner, J. (1990). Acts of meaning. Harvard University Press.

Dunleavy, M., & Dede, C. (2014). Augmented reality teaching and learning. Journal of Science Education and Technology, 23, 735-748. https://doi.org/10.1007/978-1-4614-3185-5_59

Eagleton, T. (2008). Literary theory: An introduction. Blackwell.

Engelhard, G. (2013). Invariant measurement: Using Rasch models in the social, behavioral, and health sciences. Routledge. https://doi.org/10.4324/9780203073636

Garzón, J., Pavón, J., & Baldiris, S. (2019). Systematic review and meta-analysis of augmented reality in educational settings. Computers & Education, 128, 1-13.

Garzón, J., & Acevedo, J. (2021). Meta-analysis of the impact of augmented reality on students’ learning gains. Educational Research Review, 33, 100411.

Ibáñez, M. B., & Delgado-Kloos, C. (2018). Augmented reality for STEM learning: A systematic review. Computers & Education, 123, 109-123. https://doi.org/10.1016/j.compedu.2018.05.002

Kane, M. (2013). Validating the interpretations and uses of test scores. Journal of Educational Measurement, 50(1), 1-73. https://doi.org/10.1111/jedm.12000

Linacre, J. M. (1994). Sample size and item calibration stability. Rasch Measurement Transactions, 7(4), 328.

Linacre, J. M. (2002). What do infit and outfit mean-square values mean? Rasch Measurement Transactions, 16(2), 878.

Makransky, G., & Petersen, G. B. (2019). Immersive virtual reality and learning: A meta-analysis. Educational Psychology Review, 31(1), 1-40.

Makransky, G., Petersen, G. B., & Klingenberg, S. (2021). Can immersive virtual reality simulations facilitate learning? A meta-analysis. Computers & Education, 151, 103860.

Makransky, G., Borre-Gude, S., & Mayer, R. E. (2023). Immersive virtual reality and learning: A meta-analysis of immersion and cognitive load effects. Educational Psychology Review, 35(2), 1-27.

Mayer, R. E. (2009). Multimedia learning (2nd ed.). Cambridge University Press.

Mayer, R. E. (2014). Cognitive theory of multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 43-71). Cambridge University Press. https://doi.org/10.1017/CBO9781139547369.005

Messick, S. (1995). Validity of psychological assessment: Validation of inferences from persons’ responses. American Psychologist, 50(9), 741-749. https://doi.org/10.1037/0003-066X.50.9.741

Paivio, A. (1991). Dual coding theory: Retrospect and current status. Canadian Journal of Psychology, 45(3), 255-287. https://doi.org/10.1037/h0084295

Parong, J., Mayer, R. E., Fiorella, L., MacNamara, A., Homer, B. D., & Plass, J. L. (2021). Learning in immersive virtual reality: Effects of immersion on learning, cognitive load, and transfer. Journal of Educational Psychology, 113(4), 785-800.

Radu, I. (2014). Augmented reality in education: A meta-review and cross-media analysis. Personal and Ubiquitous Computing, 18, 1533-1543. https://doi.org/10.1007/s00779-013-0747-y

Radianti, J., Majchrzak, T. A., Fromm, J., & Wohlgenannt, I. (2020). A systematic review of immersive virtual reality applications for higher education. Computers & Education, 147, 103778. https://doi.org/10.1016/j.compedu.2019.103778

Rosenblatt, L. (1994). The reader, the text, the poem: The transactional theory of the literary work. Southern Illinois University Press.

Sweller, J. (2011). Cognitive load theory. Psychology of Learning and Motivation, 55, 37-76. https://doi.org/10.1016/B978-0-12-387691-1.00002-8

Tennant, A., & Conaghan, P. G. (2007). The Rasch measurement model in rheumatology. Arthritis Care & Research, 57(8), 1358-1362. https://doi.org/10.1002/art.23108

Wellek, R., & Warren, A. (1949). Theory of literature. Harcourt.

Wilson, M. (2005). Constructing measures: An item response modeling approach. Lawrence Erlbaum Associates.

Wright, B. D., & Masters, G. N. (1982). Rating scale analysis. MESA Press.

Downloads

Published

2026-04-15

Issue

Section

Articles