Work Engagement, Technology Adoption Propensity and Student Academic Performance: A Convergent Design

Academic performance is disconcerting. Using mixed method design, the significance and value of work engagement and technology adoption propensity of school heads on academic outcomes was explored. Data from 336 samples and 6 study participants were analyzed using multiple linear regression and thematic analysis respectively. It was found that while quantitative evidence only partially supports Expectancy-Value Theory by showing no direct effect of work engagement on academic performance, qualitative insights fully substantiate the theory by taking in the role of teachers and the learning environment; conversely, both strands converge in demonstrating that technology-driven leadership directly enhances academic performance. Exploring teacher and learning environment as mediators in school heads’ work engagement and technology adoption in shaping academic performance, and qualitative design may help evoke appropriate understanding on these elements are endorsed.

Work engagement, technology adoption propensity, student academic performance, convergent design

1. Acido, J. V., & Caballes, D. G. (2024). Assessing educational progress: A comparative analysis of PISA results (2018 vs. 2022) and HDI correlation in the Philippines. World Journal Of Advanced Research and Reviews. https://doi.org/10.30574/wjarr.2024.21.1.0020. [Google Scholar] [Crossref]

2. Al‐Hamdan, Z., & Bani Issa, H. (2022). The role of organizational support and self‐efficacy on work engagement among registered nurses in Jordan: A descriptive study. Journal of Nursing Management, 30(7), 2154-2164. https://doi.org/10.1111/jonm.13456 [Google Scholar] [Crossref]

3. AlAli, R., & Wardat, Y. (2024). Low PISA Performance Students: Factors, Perceptions, and Improvement Strategies. International Journal of Religion, 5(9), 334–348. https://doi.org/10.61707/nve8gj33. [Google Scholar] [Crossref]

4. Almeidai, F. (2018). Strategies to perform a mixed methods study. European Journal of Education Studies, Volume 5, Issue 1, 2018. doi: 10.5281/zenodo.1406214. [Google Scholar] [Crossref]

5. Asadpour, M., Bakhshi, M. H., Mirzapour, P., & Shahabi, M. (2025). The motivational role of teachers: A systematic review of key factors influencing students' academic motivation. European Journal of Psychology of Education, 40(4), 133. [Google Scholar] [Crossref]

6. Azam, Q. S., Siddiqui, M. Z., & Yosufzai, S. (2023). Financial technology adoption and organizational competitive performance: mediating role of employee engagement. Journal of Social Research Development. https://doi.org/10.53664/jsrd/04-04-2023-07-729-737. [Google Scholar] [Crossref]

7. Berényi, L., & Deutsch, N. (2023). Technology adoption among higher education students. Vezetéstudomány/Budapest Management Review, 54(11), 28-39. [Google Scholar] [Crossref]

8. Bernardo, A. B. I., Cordel, M. O., Calleja, M. O., Teves, J. M. M., Yap, S. A., & Chua, U. (2023). Profiling low-proficiency science students in the Philippines using machine learning. Humanities & Social Sciences Communications, 10(1). https://doi.org/10.1057/s41599-023-01705-y [Google Scholar] [Crossref]

9. Cabural, A. B. (2024). Beyond Benchmarking: A Diagnostic Inquiry into the Underlying Determinants of Low Performance in Philippine PISA Science. Journal of Tertiary Education and Learning, 2(3), 46–57. https://doi.org/10.54536/jtel.v2i3.3063. [Google Scholar] [Crossref]

10. Caglayan-Akay, E., & Oskonbaeva, Z. (2024). Investigating the factors affecting the PISA-based test performance of Asian students. Jurnal Ekonomi Pembangunan. https://doi.org/10.20885/ejem.vol16.iss1.art4. [Google Scholar] [Crossref]

11. Çali, M., Lazimi, L., & Ippoliti, B. M. L. (2024). Relationship between student engagement and academic performance. International Journal of Evaluation and Research in Education, 13(4), 2210-2217. [Google Scholar] [Crossref]

12. Çali, M., Lazimi, L., & Ippoliti, B. M. L. (2024). Relationship between student engagement and academic performance. International Journal of Evaluation and Research in Education, 13(4), 2210-2217. [Google Scholar] [Crossref]

13. Creswell, J. & Creswell, J.D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. 5th Edition. SAGE Publications, Inc, 20171127. [Google Scholar] [Crossref]

14. Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (Fifth edition). SAGE. [Google Scholar] [Crossref]

15. Creswell, J. W. (2012). Qualitative inquiry & research design: Choosing among five approaches (4th ed.). Thousand Oaks, CA: Sage [Google Scholar] [Crossref]

16. Creswell, J. W. (2014). Research design: qualitative, quantitative, and mixed methods approaches. 4th ed. Thousand Oaks, California: SAGE Publications. [Google Scholar] [Crossref]

17. Day, C. T. (2020). Expectancy Value Theory as a Tool to Explore Teacher Beliefs and Motivations in Elementary Mathematics Instruction. International Electronic Journal of Elementary Education, 13(2), 169-182. [Google Scholar] [Crossref]

18. Dirik, H. F., Seren Intepeler, S., & Hewison, A. (2024). A New Adaptation of the Authentic Leadership Questionnaire in Turkish: Evidence From Nursing. Nursing & Health Sciences, 26(4), e13178. https://doi.org/10.1111/nhs.13178. [Google Scholar] [Crossref]

19. Doyle, L., Brady, A. M., & Byrne, G. (2016). An overview of mixed methods research–revisited. Journal of research in nursing, 21(8), 623-635. [Google Scholar] [Crossref]

20. Embalsado, J. V. M., Balilu, B. C., Montoya, M. A. J. T., Tulabut, O. A. P., Mangalus, R. S., De Ala, C. L. M., Gonzales, A. B., & De Leon, J. R. (2023). Role of Work Engagement, Autonomy Support, Psychological Capital, and Economic Factors to Educator and Staff Well-being in the Philippines. Psychocentrum Review, 5(1), 1–18. https://doi.org/10.26539/pcr.511307. [Google Scholar] [Crossref]

21. Falguera, C. C. (2022). Relationship of Work Engagement with Nurse-work and Patient Outcomes among Nurses in Central Philippines. Acta Medica Philippina. https://doi.org/10.47895/amp.vi0.4426. [Google Scholar] [Crossref]

22. Farrokhi, F., & Mahmoudi-Hamidabad, A. (2012). Rethinking Convenience Sampling: Defining Quality Criteria. Theory and Practice in Language Studies, 2(4), 784–792. https://doi.org/10.4304/TPLS.2.4.784-792. [Google Scholar] [Crossref]

23. Fuentes, R. P., & LaBad, R. B. (2025). Impact of Digital Learning Tools on Student Engagement and Academic Achievement in Higher Education: A Systematic Review. Ennoia Advances in Social Science, Technology and Education, 1(02), 53-73. [Google Scholar] [Crossref]

24. Govindarajoo, M. V., Selvarajoo, N. D., & Ali, M. S. (2022). Factors Contributing to Poor Academic Achievement Among Low Performing Pupils: A Case Study. Asian Journal of University Education, 18(4), 981–997. https://doi.org/10.24191/ajue.v18i4.20008. [Google Scholar] [Crossref]

25. Guilford, J. P. (1961). Psychological measurement a hundred and twenty-five years later. Psychometrika, 26(1), 109-127. [Google Scholar] [Crossref]

26. Gutiérrez-de-Rozas, B., López-Martín, E., & Carpintero Molina, E. (2022, August). Defining the profile of students with low academic achievement: A cross-country analysis through PISA 2018 data. In Frontiers in Education (Vol. 7, p. 910039). Frontiers Media SA. [Google Scholar] [Crossref]

27. Gutiérrez-de-Rozas, B., Lopez-Martin, E., & Carpintero, E. (2022). Defining the profile of students with low academic achievement: A cross-country analysis through PISA 2018 data. Frontiers in Education, 7. https://doi.org/10.3389/feduc.2022.910039. [Google Scholar] [Crossref]

28. Hu, J., & Qian, S. (2025). Correlations and comparisons of teacher expectations achievement motivation academic achievement and creativity. Frontiers in Psychology, 16, 1516405. [Google Scholar] [Crossref]

29. Jabir, M. S., & Farooq, M. S. (2022). Development and Validation of Students’. [Google Scholar] [Crossref]

30. Jenaro, C., Flores, N., Orgaz, M. B., & Cruz, M. (2011). Vigour and dedication in nursing professionals: towards a better understanding of work engagement. Journal of advanced nursing, 67(4), 865-875. https://doi.org/10.1111/j.1365-2648.2010.05526.x [Google Scholar] [Crossref]

31. Johnston, O., Wildy, H., & Shand, J. (2021). ‘Believe in me, and I will too’: A study of how teachers’ expectations instilled confidence in Grade 10 students. Social Psychology of Education, 24(6), 1535-1556. [Google Scholar] [Crossref]

32. Karaca, M., Geraci, L., Kurpad, N., Lithander, M. P. G., & Balsis, S. (2023). Low-Performing Students Confidently Overpredict Their Grade Performance throughout the Semester. Journal of Intelligence, 11. https://doi.org/10.3390/jintelligence11100188. [Google Scholar] [Crossref]

33. Kennedy-Clark, S. (2013). Research by Design: Design-Based Research and the Higher Degree Research student. Journal of Learning Design, 6(2), 26-32. [Google Scholar] [Crossref]

34. Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information systems journal, 28(1), 227-261. [Google Scholar] [Crossref]

35. Kokkonos, A., Travlos, A., Antonopoulou, P., & Korre, M. P. (2025). Questionnaire for digital technologies and leadership practices: the validity and reliability study. Int J Eval & Res Educ, 14(1), 133-145. DOI: 10.11591/ijere.v14i1.29885. [Google Scholar] [Crossref]

36. Korstjens, I., & Moser, A. (2018). Series: Practical guidance to qualitative research. Part 4: Trustworthiness and publishing. European Journal of General Practice, 24(1), 120-124. [Google Scholar] [Crossref]

37. Kuzminykh, I., Ghita, B., & Xiao, H. (2021, August). The relationship between student engagement and academic performance in online education. In 2021 5th international conference on E-society, E-education and E-technology (pp. 97-101). [Google Scholar] [Crossref]

38. Lam, S. M., & Zhou, Y. (2021). SES-Achievement Gaps in East Asia: Evidence from PISA 2003–2018. Asia-Pacific Education Researcher, 1–20. https://doi.org/10.1007/S40299-021-00620-7. [Google Scholar] [Crossref]

39. Lee, S. W. (2022). Regression analysis for continuous independent variables in medical research: statistical standard and guideline of Life Cycle Committee. Life cycle, 2. [Google Scholar] [Crossref]

40. Lincoln, Y. S., & Guba, E. G. (1988). Criteria for Assessing Naturalistic Inquiries as Reports. [Google Scholar] [Crossref]

41. Loyola-Carrillo, P., Vega-Muñoz, A., Salazar-Sepúlveda, G., Gil-Marín, M., & Adsuar-Sala, J. (2025). Studying engagement in educational settings: A mapping review on high-impact academic engagement research. Frontiers in Psychology, 16, 1519509. [Google Scholar] [Crossref]

42. Lu, J. G., Nisbett, R. E., & Morris, M. W. (2022). The surprising underperformance of East Asians in US law and business schools: The liability of low assertiveness and the ameliorative potential of online classrooms. Proceedings of the National Academy of Sciences of the United States of America, 119(13). https://doi.org/10.1073/pnas.2118244119. [Google Scholar] [Crossref]

43. Medina-Jerez, W., Middleton, K. V., & Orihuela-Rabaza, W. (2011). USING THE DAST-C TO EXPLORE COLOMBIAN AND BOLIVIAN STUDENTS’IMAGES OF SCIENTISTS. International Journal of Science and Mathematics Education, 9, 657-690. [Google Scholar] [Crossref]

44. Mesurado, B., Cristina Richaud, M., & José Mateo, N. (2016). Engagement, flow, self-efficacy, and eustress of university students: A cross-national comparison between the Philippines and Argentina. The Journal of psychology, 150(3), 281-299. https://doi.org/10.1080/00223980.2015.1024595 [Google Scholar] [Crossref]

45. Mirza, I., & Jabeen, R. (2025). Impact of Teacher Expectations on Students’ Behaviour and their Academic Performance. Academy of Education and Social Sciences Review, 5(1), 15-25. [Google Scholar] [Crossref]

46. Mugizi, W., Dafiewhare, A. O., Manyange, M., & Zikanga, D. K. (2020). Talent development practices and work engagement of in-service teachers at a private university in Western Uganda. Journal of Educational Research and Reviews, 8(5), 57-66. [Google Scholar] [Crossref]

47. Nowell, B., & Albrecht, K. (2019). A reviewer’s guide to qualitative rigor. Journal of Public Administration Research and Theory, 29(2), 348-363. [Google Scholar] [Crossref]

48. Prananto, K., Cahyadi, S., Lubis, F. Y., & Hinduan, Z. R. (2025). Perceived teacher support and student engagement among higher education students–a systematic literature review. BMC psychology, 13(1), 112. [Google Scholar] [Crossref]

49. Ratchford, M., & Barnhart, M. (2012). Development and validation of the technology adoption propensity (TAP) index. Journal of Business Research, 65(8), 1209-1215. [Google Scholar] [Crossref]

50. Reference: [Google Scholar] [Crossref]

51. Sandoval-Hernández, A., Zhao, D., Chen, Z., & Eryılmaz, N. (2023). The Association Between Educational Systems and Reading Literacy Performance in PISA Across the Asia-Pacific Region and Countries (pp. 749–763). https://doi.org/10.1007/978-981-19-6887-7_26. [Google Scholar] [Crossref]

52. Shenton, A. K. (2004). Strategies for ensuring trustworthiness in qualitative research projects. Education for information, 22(2), 63-75 [Google Scholar] [Crossref]

53. Skinner, C. (2018). Issues and challenges in census taking. Annual Review of Statistics and Its Application, 5(1), 49-63. [Google Scholar] [Crossref]

54. Suescun, V. (2026). Understanding Leadership Dynamics in Relation to Employee Engagement in Contemporary Virtual Work Environments in Ireland (Doctoral dissertation, Dublin, National College of Ireland). [Google Scholar] [Crossref]

55. Sujan, M., Smith-Frazer, C., Malamateniou, C., Connor, J., Gardner, A., Unsworth, H., & Husain, H. (2023). Validation framework for the use of AI in healthcare: overview of the new British standard BS30440. BMJ health & care informatics, 30(1), e100749. [Google Scholar] [Crossref]

56. Sun, S., Hara, A., Johnstone, L., Hallmark, B., Watkins, J. C., Thomson, C. A., ... & Chilton, F. H. (2024). Optimal Pair Matching Combined with Machine Learning Predicts a Significant Reduction in Myocardial Infarction Risk in African Americans Following Omega-3 Fatty Acid Supplementation. Nutrients, 16(17), 2933. [Google Scholar] [Crossref]

57. Tang, J. J., & Fisher, P. A. (2012). High achieving students and their experience of the pursuit of academic excellence. In 2012 ISEP International Symposium (pp. 475-499). ISEP. [Google Scholar] [Crossref]

58. Torres, J. L. (2024). Uncovering Teachers’ Challenges in Teaching Qualitative Research: Basis for Innovation and Training. Journal of Interdisciplinary Perspectives, 2(6), 1-1. [Google Scholar] [Crossref]

59. van Herpen, S. G., Hilverda, F., & Vollmann, M. (2025). A longitudinal study on the impact of student-teacher and student-peer relationships on academic performance: the mediating effects of study effort and engagement. European Journal of Higher Education, 15(4), 599-618. [Google Scholar] [Crossref]

60. Westover, J. (2024). What’s Draining Your Workplace Energy and Joy? Identifying and Addressing Sources of Unhappiness to Boost Productivity and Morale. 14(2). https://doi.org/10.70175/hclreview.2020.14.2.3. [Google Scholar] [Crossref]

61. Wolf, S., & Brown, A. (2023). Teacher beliefs and student learning. Human Development, 67(1), 37-54. [Google Scholar] [Crossref]

62. Wollard, K. K. (2011). Quiet Desperation Another Perspective on Employee Engagement. Advances in Developing Human Resources, 13(4), 526–537. https://doi.org/10.1177/1523422311430942. [Google Scholar] [Crossref]

63. Wu, L., Wang, Z., Luo, W., Lee, W. S., & Gao, X. THE DUAL IMPACT OF DIGITAL LEARNING PLATFORMS AND STUDENT ENGAGEMENT ON ACADEMIC ACHIEVEMENT. [Google Scholar] [Crossref]

64. Yang, J. H., & Shim, D. C. (2023). Performance of Digital Transformation: Focusing on the Moderated Mediation Effect of Digital Leadership. Korean Public Administration Review, 57(2), 141–171. https://doi.org/10.18333/kpar.57.2.141. [Google Scholar] [Crossref]

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