Creativity and Critical Thinking as Mediators of Computational Thinking among Business Education Students
DOI:
https://doi.org/10.62794/ijober.v4i3.389Keywords:
Collaboration, Communication, Computational thinking, Creativity, Critical thinking, PLS-SEMAbstract
Computational thinking is no longer confined to computer science departments, yet we still know little about how the broader set of twenty-first-century skills feeds into its growth among business students. Here we test whether collaboration and communication shape computational thinking directly, and whether creativity and critical thinking carry part of that influence. A cross-sectional survey of 215 business education students at an Indonesian public university provided the data, with 21 reflective indicators capturing five constructs. The proposed model was estimated with partial least squares structural equation modelling and 5,000 bootstrap subsamples, and the measurement model held up well on reliability and validity checks. Both collaboration and communication predicted computational thinking directly; collaboration was a particularly strong driver of creativity, while communication mainly shaped critical thinking, and each of these in turn predicted computational thinking. The indirect paths running through creativity and critical thinking were both significant, pointing to complementary partial mediation, and together the model accounted for 62.4% of the variance in computational thinking. In practice, collaborative and communicative learning seems to matter most when it is deliberately channelled into creative output and critical scrutiny. Business curricula would therefore do well to build in team-based problem solving, structured reflection, and algorithmic solution design, rather than teaching the 4Cs and computational thinking as unrelated outcomes.
References
Anderson, N. D. (2016). A call for computational thinking in undergraduate psychology. Psychology Learning & Teaching, 15(3), 226–234. https://doi.org/10.1177/1475725716659252
Bakhru, S. A., & Mehta, R. P. (2020). Assignment and project activity based learning systems as an alternative to continuous internal assessment. Procedia Computer Science, 172, 397–405. https://doi.org/10.1016/j.procs.2020.05.073
Ceballos, H., Bogaart, T. V. D., van Ginkel, S., Spandaw, J., & Drijvers, P. (2026). How collaborative problem solving promotes higher-order thinking skills: A systematic review of design features and processes. Thinking Skills and Creativity, 59, Article 102001. https://doi.org/10.1016/j.tsc.2025.102001
Çoban, E., & Korkmaz, Ö. (2021). An alternative approach for measuring computational thinking: Performance-based platform. Thinking Skills and Creativity, 42, Article 100929. https://doi.org/10.1016/j.tsc.2021.100929
de Bruin, A. B., & van Merriënboer, J. J. (2017). Bridging cognitive load and self-regulated learning research: A complementary approach to contemporary issues in educational research. Learning and Instruction, 51, 1–9. https://doi.org/10.1016/j.learninstruc.2017.06.001
Diago, P. D., González-Calero, J. A., & Yáñez, D. F. (2022). Exploring the development of mental rotation and computational skills in elementary students through educational robotics. International Journal of Child-Computer Interaction, 32, Article 100388. https://doi.org/10.1016/j.ijcci.2021.100388
Durak, H. Y., & Saritepeci, M. (2018). Analysis of the relation between computational thinking skills and various variables with the structural equation model. Computers & Education, 116, 191–202. https://doi.org/10.1016/j.compedu.2017.09.004
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Ho, N. T. T., & Le, H. V. (2026). Embedding 21st-century competencies into higher education: Insights from Vietnamese lecturers’ perspectives and pedagogical strategies. Thinking Skills and Creativity, 59, Article 101990. https://doi.org/10.1016/j.tsc.2025.101990
Hwang, S., & Kim, H. K. (2022). Development and validation of the e-learning satisfaction scale (eLSS). Teaching and Learning in Nursing, 17(4), 403–409. https://doi.org/10.1016/j.teln.2022.02.004
Israel-Fishelson, R., & Hershkovitz, A. (2024). Cultivating creativity improves middle school students’ computational thinking skills. Interactive Learning Environments, 32(2), 431–446. https://doi.org/10.1080/10494820.2022.2088562
Korkmaz, Ö., Çakir, R., & Özden, M. Y. (2017). A validity and reliability study of the computational thinking scales (CTS). Computers in Human Behavior, 72, 558–569. https://doi.org/10.1016/j.chb.2017.01.005
Laisema, S., & Wannapiroon, P. (2014). Design of collaborative learning with creative problem-solving process learning activities in a ubiquitous learning environment to develop creative thinking skills. Procedia - Social and Behavioral Sciences, 116, 3921–3926. https://doi.org/10.1016/j.sbspro.2014.01.867
Lin, C.-J., Wang, W.-S., Lee, H.-Y., Li, P.-H., Huang, Y.-M., & Wu, T.-T. (2026). Guided reflection in collaborative problem-solving: Leveraging natural language processing and learning analytics. Journal of Research on Technology in Education. https://doi.org/10.1080/15391523.2025.2601873
Liu, J., Zhang, Y., Li, W., Wang, Q., Niu, P., & Zhang, X. (2026). Adaptive vs. planned metacognitive scaffolding for computational thinking: Evidence from generative AI-supported programming in elementary education. Computers & Education, 241, Article 105473. https://doi.org/10.1016/j.compedu.2025.105473
Martín-Núñez, J. L., Ar, A. Y., Fernández, R. P., Abbas, A., & Radovanović, D. (2023). Does intrinsic motivation mediate perceived artificial intelligence (AI) learning and computational thinking of students during the COVID-19 pandemic? Computers & Education: Artificial Intelligence, 4, Article 100128. https://doi.org/10.1016/j.caeai.2023.100128
Mengual-Andrés, S., Roig-Vila, R., & Mira, J. B. (2016). Delphi study for the design and validation of a questionnaire about digital competences in higher education. International Journal of Educational Technology in Higher Education, 13, Article 12. https://doi.org/10.1186/s41239-016-0009-y
Papert, S., & Harel, I. (1991). Situating constructionism. In I. Harel & S. Papert (Eds.), Constructionism: Research reports and essays (pp. 1–11). Ablex Publishing.
Parrado-Martínez, P., & Sánchez-Andújar, S. (2020). Development of competences in postgraduate studies of finance: A project-based learning (PBL) case study. International Review of Economics Education, 35, Article 100192. https://doi.org/10.1016/j.iree.2020.100192
Pérez-Escolar, M., Ordóñez-Olmedo, E., & Alcaide-Pulido, P. (2021). Fact-checking skills and project-based learning about infodemic and disinformation. Thinking Skills and Creativity, 41, Article 100887. https://doi.org/10.1016/j.tsc.2021.100887
Rapti, S., Sapounidis, T., Tselegkaridis, S., & Stamovlasis, D. (2026). Exploring communication, collaboration, critical thinking, and creativity in educational robotics curriculum. Education and Information Technologies, 31, 2539–2565. https://doi.org/10.1007/s10639-026-13895-4
Saad, A., & Zainudin, S. (2022). A review of project-based learning (PBL) and computational thinking (CT) in teaching and learning. Learning and Motivation, 78, Article 101802. https://doi.org/10.1016/j.lmot.2022.101802
Safahi, L., Mulyono, H., & Akbar, B. (2026). Scaffolding strategies for computational thinking in higher education science education: A systematic literature review. Journal of Educational and Social Research, 16(3), 417–450. https://doi.org/10.36941/jesr-2026-0340
Shin, Y., Jung, J., Choi, S., & Jung, B. (2025). The influence of scaffolding for computational thinking on cognitive load and problem-solving skills in collaborative programming. Education and Information Technologies, 30(1), 583–606. https://doi.org/10.1007/s10639-024-13104-0
Slof, B., Nijdam, D., & Janssen, J. (2016). Do interpersonal skills and interpersonal perceptions predict student learning in CSCL-environments? Computers & Education, 97, 49–60. https://doi.org/10.1016/j.compedu.2016.02.012
Snyder, C., Cohn, C., Fonteles, J. H., & Biswas, G. (2025). Using collaborative interactivity metrics to analyze students’ problem-solving behaviors during STEM+C computational modeling tasks. Learning and Individual Differences, 121, Article 102724. https://doi.org/10.1016/j.lindif.2025.102724
Sokhanvar, Z., Salehi, K., & Sokhanvar, F. (2021). Advantages of authentic assessment for improving the learning experience and employability skills of higher education students: A systematic literature review. Studies in Educational Evaluation, 70, Article 101030. https://doi.org/10.1016/j.stueduc.2021.101030
Sun, L., Hu, L., & Zhou, D. (2021). Improving 7th-graders’ computational thinking skills through unplugged programming activities: A study on the influence of multiple factors. Thinking Skills and Creativity, 42, Article 100926. https://doi.org/10.1016/j.tsc.2021.100926
Tang, T., Vezzani, V., & Eriksson, V. (2020). Developing critical thinking, collective creativity skills and problem solving through playful design jams. Thinking Skills and Creativity, 37, Article 100696. https://doi.org/10.1016/j.tsc.2020.100696
Tian, Q., & Zheng, X. (2025). The impact of artificial intelligence on students’ 4C skills: A meta-analysis. Educational Research Review, 49, Article 100728. https://doi.org/10.1016/j.edurev.2025.100728
van Laar, E., van Deursen, A. J. A. M., van Dijk, J. A. G. M., & de Haan, J. (2017). The relation between 21st-century skills and digital skills: A systematic literature review. Computers in Human Behavior, 72, 577–588. https://doi.org/10.1016/j.chb.2017.03.010
van Laar, E., van Deursen, A. J. A. M., van Dijk, J. A. G. M., & de Haan, J. (2019). Determinants of 21st-century digital skills: A large-scale survey among working professionals. Computers in Human Behavior, 100, 93–104. https://doi.org/10.1016/j.chb.2019.06.017
Wang, F., Huang, J., Zheng, X.-L., Wu, J.-Q., & Zhao, A.-P. (2025). STEM activities for boosting pupils’ computational thinking and reducing their cognitive load: Roles of argumentation scaffolding and mental rotation. Journal of Research on Technology in Education, 57(6), 1370–1389. https://doi.org/10.1080/15391523.2024.2398504
Wang, J., Yang, W., & Yeung, M. K. (2025). Cognitive foundations in the interplay between computational thinking and creativity: A scoping review. Thinking Skills and Creativity, 56, Article 101729. https://doi.org/10.1016/j.tsc.2024.101729
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://doi.org/10.1145/1118178.1118215
Yu, X., Soto-Varela, R., & Gutiérrez-García, M. Á. (2024). How to learn and teach a foreign language through computational thinking: Suggestions based on a systematic review. Thinking Skills and Creativity, 52, Article 101517. https://doi.org/10.1016/j.tsc.2024.101517
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Wening Patmi Rahayu, Dede Rusmana, Rachmad Hidayat, Lutfi Asnan Qodri
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
