Exploring Pre-Laboratory Engagement in Higher Education through a Validated Qualitative Approach

John C. Chavez; Sarah O. Namoco

doi:10.55927/ajae.v4i4.15282

Authors

John C. Chavez University of Science and Technology of Southern Philippines
Sarah O. Namoco University of Science and Technology of Southern Philippines

DOI:

https://doi.org/10.55927/ajae.v4i4.15282

Keywords:

Student Engagement, Pre-Lab Time, Idle Time, TVET, Higher Education

Abstract

This qualitative study explored how higher education TVET students and instructors engage during pre-laboratory idle time, a phase often overlooked in laboratory-based instruction. Guided by Engagement Theory and Self-Determination Theory, data were gathered through semi-structured interviews, non-participant observations, and institutional documents in two Philippine state universities. Interview protocols were pre-tested through cognitive interviews to ensure clarity, construct alignment, and contextual fit. Thematic analysis revealed four themes: proactive behavior and routine, instructor presence, emotional and motivational tensions, and environmental and institutional influences. Results show that idle time can foster readiness, self-regulation, and collaboration when supported by clear expectations, instructor visibility, and enabling environments. The study highlights the value of structuring idle time as a vital component of TVET pedagogy.

Downloads

Download data is not yet available.

References

Adeoye-Olatunde, O. A., & Olenik, N. L. (2021). Research and scholarly methods: Semi-structured interviews. JACCP Journal of the American College of Clinical Pharmacy, 4(10), 1358–1367.

Balza, J. S., Cusatis, R., McDonnell, S. M., Basir, M. A., & Flynn, K. E. (2022). Effective questionnaire design: How to use cognitive interviews to refine questionnaire items. Journal of Neonatal-Perinatal Medicine, 15(2), 345–349.

Braun, V., & Clarke, V. (2021). Thematic analysis: A practical guide [eBook version]. In SAGE.

Cagliero, L., Canale, L., & Farinetti, L. (2023). Data-driven analysis of student engagement in time-limited computer laboratories. Algorithms, 16(10), 464.

Cents-Boonstra, M., Lichtwarck-Aschoff, A., Denessen, E., Aelterman, N., & Haerens, L. (2021). Fostering student engagement with motivating teaching: An observation study of teacher and student behaviours. Research Papers in Education, 36(6), 754–779.

Chavez, J. C. (2025). Enhancing flipped classrooms with technology-enhanced assessments. International Journal of Educational Reform.

Comingking, J. A. R., Labos, M. C., Rebucas, E. M., & Caritativo, C. (2024). Regression analysis of communication gap in teaching-learning process among BTVTED students. Asian Journal of Education and Social Studies, 50(8), 393–410.

Costello, T., Logue, P., & Dunne, K. (2022). An evaluation of the effects of pre-laboratory activities on student engagement in a higher education computer engineering module. Education and Information Technologies, 14(2).

Deci, E. L., & Ryan, R. M. (2015). Self-determination theory. International Encyclopedia of the Social & Behavioral Sciences: Second Edition, 486–491.

Dunagan, L., & Larson, D. A. (2021). Alignment of competency-based learning and assessment to adaptive instructional systems. Lecture Notes in Computer Science, 12792, 537–549.

Eungoo, K., & Hwang, H.-J. (2021). Ethical conducts in qualitative research methodology: Participant observation and interview process. Journal of Research and Publication Ethics, 2(2), 5–10.

Fredricks, J. A. (2022). The measurement of student engagement: Methodological advances and comparison of new self-report instruments. In Handbook of Research on Student Engagement: Second Edition (pp. 597–616).

George-Williams, S. R., Blackburn, R. A. R., Wilkinson, S. M., & Williams, D. P. (2022). Prelaboratory technique-based simulations: Exploring student perceptions of their impact on in-class ability, preparedness, and emotional state. Journal of Chemical Education, 99(3), 1383–1391.

Gomes, S., Costa, L., Martinho, C., Dias, J., Xexéo, G., & Moura Santos, A. (2023). Modeling students’ behavioral engagement through different in-class behavior styles. International Journal of STEM Education, 10(1), 1–15.

Gómez-Ochoa de Alda, J. A., Marcos-Merino, J. M., Valares-Masa, C., & Esteban-Gallego, M. R. (2025). Anticipatory emotions and academic performance: The role of boredom in a preservice teachers’ lab experience. Heliyon, 11(1), e41142.

Hanaysha, J. R., Shriedeh, F. B., & In’airat, M. (2023). Impact of classroom environment, teacher competency, information and communication technology resources, and university facilities on student engagement and academic performance. International Journal of Information Management Data Insights, 3(2), 100188.

Imeraj, L., Antrop, I., Roeyers, H., Deboutte, D., Deschepper, E., Bal, S., & Sonuga-Barke, E. (2016). The impact of idle time in the classroom. Journal of Attention Disorders, 20(1), 71–81.

Kowitlawakul, Y., Tan, J. J. M., Suebnukarn, S., Nguyen, H. D., Poo, D. C. C., Chai, J., Wang, W., & Devi, K. (2022). Utilizing educational technology in enhancing undergraduate nursing students’ engagement and motivation: A scoping review. Journal of Professional Nursing, 42, 262–275.

Lai, H. M. (2021). Understanding what determines university students’ behavioral engagement in a group-based flipped learning context. Computers & Education, 173, 104290.

Lashley, M., & McCleery, R. (2020). Intensive laboratory experiences to safely retain experiential learning in the transition to online learning. Ecology and Evolution, 10(22), 12613.

Li, S., & Lajoie, S. P. (2022). Cognitive engagement in self-regulated learning: An integrative model. European Journal of Psychology of Education, 37(3), 833–852.

Liu, Y., Ma, S., & Chen, Y. (2024). The impacts of learning motivation, emotional engagement and psychological capital on academic performance in a blended learning university course. Frontiers in Psychology, 15, 1357936.

Lu, G., Xie, K., & Liu, Q. (2022). What influences student situational engagement in smart classrooms: Perception of the learning environment and students’ motivation. British Journal of Educational Technology, 53(6), 1665–1687.

Meadows, K. (2021). Cognitive interviewing methodologies. Clinical Nursing Research, 30(4), 375–379.

Naeem, M., Ozuem, W., Howell, K., & Ranfagni, S. (2023). A step-by-step process of thematic analysis to develop a conceptual model in qualitative research. International Journal of Qualitative Methods, 22.

Nguyen, T. D., Cannata, M., & Miller, J. (2018). Understanding student behavioral engagement: Importance of student interaction with peers and teachers. The Journal of Educational Research, 111(2), 163–174.

Nguyen-Viet, B., & Nguyen-Viet, B. (2025). The synergy of immersion and basic psychological needs satisfaction: Exploring gamification's impact on student engagement and learning outcomes. Acta Psychologica, 252, 104660.

Nordin, D. N., & Omar, M. K. (2024). Factors influencing TVET readiness among students at public secondary school: Exploring interest, motivation, and self-efficacy. Asian Journal of Vocational Education and Humanities, 5(1), 10–19.

Ramatsetse, B., & Zenda, R. (2024). Recognition of prior learning for promoting educator development and lifelong learning: The case of TVET colleges. In Lifelong Learning and Skills Development (pp. 87–116).

Rathnayaka, C. M., Ganapathi, J., Kickbusch, S., Dawes, L., & Brown, R. (2024). Preparative pre-laboratory online resources for effectively managing cognitive load of engineering students. European Journal of Engineering Education, 49(1), 113–138.

Ricci, L., Lanfranchi, J. B., Lemetayer, F., Rotonda, C., Guillemin, F., Coste, J., & Spitz, E. (2019). Qualitative methods used to generate questionnaire items: A systematic review. Qualitative Health Research, 29(1), 149–156.

Rivera, J., & Baptista, V. E. (2024). Investigating the policies, the resources and gaps in the competencies of Bachelor of Technical-Vocational Teacher Education (BTVTEd) prescribed by TESDA and K to 12 Basic Education Curriculum and a proposed curriculum revision for Bachelor of Technical-Vocational Teacher Education in the Philippines. Divine Word International Journal of Management and Humanities, 3(4), 1121–1136.

Rivera, J. P. R., Lorenzo, P. J. M., Generalao, I. N. A., & Balaoro, J. M. (2025). Examining the effects of technical vocational education and training (TVET) on employment outcomes in the Philippines. Discussion Papers.

Van den Beemt, A., Groothuijsen, S., Ozkan, L., & Hendrix, W. (2023). Remote labs in higher engineering education: Engaging students with active learning pedagogy. Journal of Computing in Higher Education, 35(2), 320–340.

Werang, B., & Radja Leba, S. M. (2022). Factors affecting student engagement in online teaching and learning: A qualitative case study. The Qualitative Report.

Willis, G. B. (2005). Cognitive interviewing.

Winter, M., Mordel, J., Mendzheritskaya, J., Biedermann, D., Ciordas-Hertel, G.-P., Hahnel, C., Bengs, D., Wolter, I., Goldhammer, F., Horz, H., & Drachsler, H. (2021). Behavioral trace data in an online learning environment as indicators of learning engagement in university students. PLoS ONE, 16(10), e0256430.

Zenouzagh, Z. M., Admiraal, W., & Saab, N. (2023). Learner autonomy, learner engagement and learner satisfaction in text-based and multimodal computer mediated writing environments. Education and Information Technologies, 28, 14283–14323.