Networked learning behavior in Higher Education: a moderated mediation analysis of TPACK and AI readiness

Kriti Sarkar; Suman Bose

doi:10.22633/rpge.v30i00.21140

Authors

Kriti Sarkar University of Engineering & Management https://orcid.org/0009-0006-9360-1738
Suman Bose University of Engineering & Management https://orcid.org/0000-0003-1206-0820

DOI:

https://doi.org/10.22633/rpge.v30i00.21140

Keywords:

Networked learning, TPACK, AI readiness, Higher education, Digital infrastructure

Abstract

This study examines the structural relationships among artificial intelligence (AI) readiness, technological pedagogical content knowledge (TPACK), and networked learning behavior among faculty members at Indian public universities. Using a cross-sectional quantitative survey design, the study tests a moderated mediation model in which TPACK mediates the relationship between AI readiness and networked learning behavior, while institutional digital infrastructure moderates this indirect effect. Structural equation modeling was employed to assess the hypothesized relationships. The results show that AI readiness significantly increases TPACK, which, in turn, strongly predicts networked learning behavior. TPACK constitutes the main mechanism through which AI readiness influences collaborative online learning practices, and the indirect effect is significantly stronger in institutions with well-developed digital infrastructure. The study highlights the importance of integrating faculty AI readiness, pedagogical competence, and institutional digital support, with practical implications for faculty development programs and strategic investments in digital infrastructure in higher education settings.

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Author Biographies

Kriti Sarkar, University of Engineering & Management

University of Engineering & Management (UEM), Kolkata – West Bengal – India. Associate Professor. Department of Basic Sciences and Humanities.

Suman Bose, University of Engineering & Management

University of Engineering & Management (UEM), Kolkata – West Bengal – India. Researcher. Department of Management.

References

Ayanwale, M. A., Misu, E. E., & Molefi, R. R. (2022). Towards artificial intelligence readiness: Development and validation of an AI readiness scale for educators. Education and Information Technologies, 27(8), 11837–11860. https://doi.org/10.1007/s10639-022-11080-y

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.

Bates, A. W. (2015). Teaching in a digital age: Guidelines for designing teaching and learning. BC Open Textbooks.

Chai, C. S., Koh, J. H. L., & Tsai, C.-C. (2019). A review of the quantitative measures of technological pedagogical content knowledge (TPACK). In M. C. Herring, M. J. Koehler, & P. Mishra (Eds.), Handbook of technological pedagogical content knowledge for educators (2nd ed., pp. 87–106). Routledge.

Chen, X., Zou, D., Xie, H., & Wang, F. L. (2022). Past, present, and future of smart learning: A topic-based bibliometric analysis. International Journal of Educational Technology in Higher Education, 19(1), 2. https://doi.org/10.1186/s41239-021-00312-8

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312

Goodyear, P., Banks, S., Hodgson, V., & McConnell, D. (Eds.). (2004). Advances in research on networked learning. Kluwer Academic.

Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (3rd ed.). Guilford Press.

Hodgson, V., McConnell, D., & Dirckinck-Holmfeld, L. (2020). The theory, practice and pedagogy of networked learning. In L. Dirckinck-Holmfeld, V. Hodgson, & D. McConnell (Eds.), Exploring the theory, pedagogy and practice of networked learning (pp. 1–26). Springer.

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.

Kimmons, R., & Hall, C. (2016). Emerging technologies in the field: Today’s EdTech topics and trends. TechTrends, 60(5), 425–432.

Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–16). Association for Computing Machinery.

Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.

Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research, 42(1), 185–227.

Sánchez-Prieto, J. C., Cruz-Benito, J., Therón, R., & García-Peñalvo, F. J. (2023). Do you accept AI-based recommendations in technology-enhanced learning? The role of AI self-efficacy and the UTAUT2 model. International Journal of Human–Computer Studies, 169, 102934.

Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009). Technological pedagogical content knowledge (TPACK): The development and validation of an assessment instrument for preservice teachers. Journal of Research on Technology in Education, 42(2), 123–149.

Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14.

Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1), 3–10.

Trist, E. L. (1981). The evolution of socio-technical systems (Occasional Paper No. 2). Ontario Quality of Working Life Centre.

UNESCO. (2023). Global education monitoring report 2023: Technology in education—A tool on whose terms? UNESCO Publishing.

Valtonen, T., Sointu, E., Kukkonen, J., Mäkitalo, K., Hoang, N., Häkkinen, P., Järvelä, S., Näykki, P., Virtanen, A., Pöysä-Tarhonen, J., & Tondeur, J. (2021). TPACK updated to measure pre-service teachers’ twenty-first century skills. Australasian Journal of Educational Technology, 37(3), 1–18.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.

Zhao, Y., & Frank, K. A. (2003). Factors affecting technology uses in schools: An ecological perspective. American Educational Research Journal, 40(4), 807–840.