Xiao-Feng Kenan KOK*, Ching Yee PUA, Shermain PUAH, Oran Zane DEVILLY, and Eric Chern-Pin CHUA
SIT Teaching and Learning Academy,
Singapore Institute of Technology (SIT)
Sub-Theme
Building Technological and Community Relationships
Keywords
Teaching behaviours, physical features of environment, student engagement, delivery methods of instruction, task value
Category
Paper Presentation
1 Introduction
Space plays a vital role in shaping learning experiences (Cox, 2018). Learning spaces—whether physical or virtual—are purposefully designed environments that support student interaction and knowledge construction (Christou et al., 2023). Given that the physical characteristics of these spaces can influence teaching practices and learning processes (Gislason, 2020; Tondeur et al., 2017), it is essential for institutions to understand their impact in order to make informed and strategic decisions about resource allocation (Sawers et al., 2016). Yet, research examining how students perceive physical learning environments and how these perceptions shape learning, motivation, and engagement remains limited (Adedokun et al., 2017). Specifically, several questions are still unresolved: (1) how the physical learning environment and task value affect student engagement (De Bruijin-Smolders & Prinsen, 2024; Edwards & Taasoobshirazi, 2022; Zepke et al., 2014); (2) how students’ perceptions of different face-to-face delivery methods influence their engagement (Hood et al., 2022), and (3) how specific spatial features or design elements shape instructors’ pedagogical adaptability and student engagement (Lee et al., 2023; Yu et al., 2020). To address these gaps, the present study examines the effects of physical features of the environment and task value on student engagement and whether these relationships are mediated by delivery methods of instruction and teaching behaviours across three types of learning spaces: lectorials, tutorial rooms, and applied and collaborative environment (ACE) rooms.
2 Methods
A cross-sectional survey research design was employed, drawing on a convenience sample of 293 undergraduate students enrolled in four modules conducted across the three learning spaces at a Singapore-based university. The survey contained sets of items adapted from five existing instruments measuring physical features of the environment, task value, student engagement, delivery methods of instruction, and teaching behaviours. Data was analysed using the Statistical Package for Social Sciences (SPSS) version 27.0 (IBM Corporation, 2020) to obtain the descriptive statistics and internal reliabilities of the scales, and Mplus 8.0 (Muthén & Muthén, 1998–2017) for exploratory factor analysis (EFA), multi-group invariance tests, confirmatory factor analysis (CFA), and structural equation modelling (SEM).
3 Results and Discussion
To examine the underlying factor structure of the data, a series of CFAs were conducted for task value, delivery methods of instruction, and teaching behaviours, while an EFA was performed for the instrument assessing the physical features of the environment. All analyses demonstrated good model fit. Following that, an SEM was performed to account for the shared variance amongst the factors, demonstrating an acceptable overall fit to the data: c2 = 2604.366, df = 1545, p < .001, RMSEA = .048, CFI = .916, TLI = .901, SRMR = .040. The SEM results indicated that (1) task value positively predicted teaching behaviours, (2) instructional interaction positively predicted learning experience and attitudes, (3) environmental comfort positively predicted learning experience and ease of use, and (4) learning experience and teaching behaviours positively predicted all facets of student engagement. Furthermore, learning experience positively mediated the relationship between task value and all facets of student engagement, and between environmental comfort and cognitive and emotional engagement. Interaction effects revealed that students with weaker foundational knowledge benefited more from lessons held in ACE rooms as compared to those using tutorial rooms or lectorials, in terms of cognitive and emotional engagement.
4 Implications and Conclusion
Our study offers valuable insights into the three learning spaces by examining how the physical environment features influence student engagement via teaching behaviours and instructional delivery methods. The results suggest that the learning experiences created in the physical environment are crucial for strengthening the relations between task value, environmental comfort, and student engagement. Educators could consider thoughtfully aligning instructional activities with the physical learning environment. For example, collaborative tasks or problem-based learning might be better facilitated in flexible, interactive spaces, while lecture or content heavy sessions may suit more traditional layouts.
References
Adedokun, O. A., Parker, L. C., Henke, J. N., & Burgess, W. D. (2017). Student perceptions of a 21st century learning space. Journal of Learning Spaces, 6(1), 1–13. https://libjournal.uncg.edu/jls/article/view/1339
Christou, E., Parmaxi, A., Nicolaou, A., & Pashia, E. (2023). Learning spaces in higher education: A systematic literature Review. In P. Zaphiris, & A. Ioannou (Eds.), Learning and collaboration technologies. HCII 2023. Lecture notes in computer science (Vol. 14041, pp. 431–446). Springer. https://doi.org/10.1007/978-3-031-34550-0_31
Cox, A. M. (2018). Space and embodiment in informal learning. Higher Education, 75(6), 1077–1090. https://doi.org/10.1007/s10734-017-0186-1
De Bruijn-Smolders, M., & Prinsen, F. R. (2024). Effective student engagement with blended learning: A systematic review. Heliyon, 10, Article e39439. https://doi.org/10.1016/j.heliyon.2024.e39439
Edwards, O. V., & Taasoobshirazi, G. (2022). Social presence and teacher involvement: The link with expectancy, task value, and engagement. The Internet and Higher Education, 55, Article 100869. https://doi.org/10.1016/j.iheduc.2022.100869
Gislason, N. (2020). Placing education: The school as architectural space. Paideusis, 16(3), 5–14. https://doi.org/10.7202/1072485ar
Hood, J., Chen, Y., Jacques, L., & Hebert, D. (2022). Perceptions of students and faculty on the various delivery methods of instruction. American Journal of Educational Research, 10(4), 245–252. https://doi.org/10.12691/education-10-4-13
IBM Corporation. (2020). IBM SPSS Statistics for Windows (Version 27.0) [Computer software]. IBM Corporation.
Lee, H. Y., Ramsay, C. M., & Robert, J. (2023). The effects of furnishings and technology on pedagogical agility and student engagement across flexible learning spaces. Journal of Learning Spaces, 12(1), 23–32. https://files.eric.ed.gov/fulltext/EJ1400782.pdf
Muthén, L. K. & Muthén, B. (1998–2017). Mplus User’s Guide. Muthén & Muthén.
Sawers, K. M., Wicks, D., Mvududu, N., Seeley, L., & Copeland, R. (2016). What drives student engagement: is it learning space, instructor behavior or teaching philosophy? Journal of Learning Spaces, 5(2), 26–38. https://libjournal.uncg.edu/jls/article/view/1247
Tondeur, J., Herman, F., De Buck, M., & Triquet, K. (2017). Classroom biographies: Teaching and learning in evolving material landscapes (c. 1960–2015). European Journal of Education, 52(3), 280–294. https://doi.org/10.1111/ejed.12228
Yu, J., Vermunt, J. D., & Burke, C. (2020). Students’ learning patterns and learning spaces in higher education: An empirical investigation in China. Higher Education Research & Development, 40(4), 868–883. https://doi.org/10.1080/07294360.2020.1775557
Zepke, N., Leach, L., & Butler, P. (2014). Student engagement: students’ and teachers’ perceptions. Higher Education Research & Development, 33(2), 386–398. https://doi.org/10.1080/07294360.2013.832160