Abstract

This study investigated the mediating role of students’ study time in the relationships between the availability of ICT (information and communication technology) resources, teacher competence, and academic performance in programming language courses. The researchers used a sample of 287 undergraduate students and employed structural equation modeling (SEM) to analyze the hypothesized mediating effects. The findings showed that both ICT resource availability and teacher competence had positive and significant indirect effects on academic performance, which were partially mediated by the amount of time students spent studying. Specifically, the indirect effect of ICT resource availability on academic performance through study time was 0.159 (p < 0.001), and the indirect effect of teacher competence on academic performance through study time was 0.195 (p < 0.001). These results suggest that while ICT resources and teacher competence directly contribute to improved academic performance in programming languages, they also indirectly influence performance by promoting increased study time among students. The mediating role of study time highlights the importance of creating an environment that supports and encourages students to engage in self-directed learning activities, in addition to providing adequate technological resources and competent teaching. The findings have important implications for educational practitioners and policymakers, as they emphasize the need to adopt a holistic approach to enhancing student learning outcomes in programming courses by understanding the complex interplay between various factors and their indirect effects.

References

Adekunle, S. E., & Adepoju, S. A. (2020). Collaborative Learning Strategy and Students’ Academic
Performance in Mathematics and Computer Programming. Handbook of Research on Using Global
Collective Intelligence and Creativity to Solve Wicked Problems, 175–192.
https://doi.org/10.4018/978-1-7998-2385-8.ch009
Basri, W. S., Alandejani, J. A., & Almadani, F. M. (2018). ICT Adoption Impact on Students’ Academic
Performance: Evidence from Saudi Universities. Education Research International, 2018.
https://doi.org/10.1155/2018/1240197
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/10.1177/002224378101800104
Gefen, D., & Straub, D. (2005). A Practical Guide To Factorial Validity Using PLS-Graph: Tutorial And
Annotated Example. Communications of the Association for Information Systems, 16(July).
https://doi.org/10.17705/1cais.01605
Genesee, F. (2005). Second-Language Learning in Bilingual Schools. Contemporary Psychology: A
Journal of Reviews, 32(5), 449–450. https://doi.org/10.1037/027134
Gursoy, D. (2016). Assessing novice programmers ’ performance in programming exams via computerbased test . Thesis, June.
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
Hamidu, H. (2022). RELATIONSHIP BETWEEN TEACHER PROFESSIONAL COMPETENCY AND
STUDENTS’ ACADEMIC ACHIEVEMENT IN ENGLISH LANGUAGE IN SENIOR
SECONDARY SCHOOLS, ADAMAWA STATE NIGERIAHalilu HamiduDepartment of General
Studies in Education, FCE Yolaalihamisu@gmail.comABSTRACTThis. African Journal of
Educational Management, Teaching and Entrepreneurship Studies, 2(2), 22–25.
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. https://doi.org/10.1016/j.jjimei.2023.100188
Hegde, V., Surendran, N., & Vaishnavi, M. (2023). Predicting Student Failure using Peer-based
Evaluation and Ratings. 2023 14th International Conference on Computing Communication and
Networking Technologies, ICCCNT 2023, 1–6.
https://doi.org/10.1109/ICCCNT56998.2023.10308388
Khan, Z., Athar, S., Mehmood, U., & Khan, W. A. (2023). The Effect of Peer Relation and Peer Pressure
on the Performance of University Students: A Quantitative Study. Pakistan Journal of Humanities
and Social Sciences, 11(3), 3577–3585. https://doi.org/10.52131/pjhss.2023.1103.0638
Knoke, D. (2004). Structural Equation Models. In K. B. T.-E. of S. M. Kempf-Leonard (Ed.),

Encyclopedia of Social Measurement, Three-Volume Set (Vol. 3, pp. V3-689-V3-695). Elsevier.
https://doi.org/10.1016/B0-12-369398-5/00392-3
Lin, P. T. T. S., Anutariya, C., & Utamachant, P. (2022). Understanding Relationships among Learning
Styles, Learning Activities and Academic Performance: From a Computer Programming Course
Perspective. 2022 19th International Joint Conference on Computer Science and Software
Engineering, JCSSE 2022, 1–6. https://doi.org/10.1109/JCSSE54890.2022.9836265
Llanos, J., Corresp, M., Bucheli, V., Calle, F. R., Llanos, J. M., Bucheli, V. A., & Restrepo-calle, F.
(2023). Computer Science Manuscript to be reviewed Early prediction of student performance in
CS1 programming courses Early prediction of student performance in CS1 programming courses.
PeerJ Computer Science.
Llorca, A., Richaud, M. C., & Malonda, E. (2017). Parenting, peer relationships, academic self-efficacy,
and academic achievement: Direct and mediating effects. Frontiers in Psychology, 8(DEC), 1–11.
https://doi.org/10.3389/fpsyg.2017.02120
Mbunge, E., Fashoto, S. G., & Olaomi, J. (2021). COVID-19 and Online Learning: Factors Influencing
Students’ Academic Performance in First-Year Computer Programming Courses in Higher
Education. SSRN Electronic Journal, 2, 163714. https://doi.org/10.2139/ssrn.3757988
Najera, C. L. L., & Osorno, R. I. M. (2023). Ict Indicators and Music Performance of Mapeh Students: the
Mediating Role of Teaching Competency. European Journal of Physical Education and Sport
Science, 9(2), 199–223. https://doi.org/10.46827/ejpe.v9i2.4831
Nonis, S. A., & Hudson, G. I. (2006). Academic Performance of College Students: Influence of Time
Spent Studying and Working. Journal of Education for Business, 81(3), 151–159.
https://doi.org/10.3200/JOEB.81.3.151-159
Ouahbi, I., Kaddari, F., Darhmaoui, H., Elachqar, A., & Lahmine, S. (2015). Learning Basic
Programming Concepts by Creating Games with Scratch Programming Environment. Procedia –
Social and Behavioral Sciences, 191, 1479–1482. https://doi.org/10.1016/j.sbspro.2015.04.224
Papageorgiou, E., & Callaghan, C. W. (2014). An exploratory perspective of student performance and
access to resources. Mediterranean Journal of Social Sciences, 5(23), 2234–2242.
https://doi.org/10.5901/mjss.2014.v5n23p2234
Qoiriah, A., Yamasari, Y., Asmunin, Nurhidayat, A. I., & Harimurti, R. (2021). Exploring Automatic
Assessment-Based Features for Clustering of Students’ Academic Performance. In A. Abraham, Y.
Ohsawa, N. Gandhi, M. A. Jabbar, A. Haqiq, S. McLoone, & B. Issac (Eds.), Advances in Intelligent
Systems and Computing: Vol. 1383 AISC (pp. 125–134). Springer International Publishing.
https://doi.org/10.1007/978-3-030-73689-7_13
Rashid, T., & Asghar, H. M. (2016). Technology use, self-directed learning, student engagement and
academic performance: Examining the interrelations. Computers in Human Behavior, 63, 604–612.
https://doi.org/10.1016/j.chb.2016.05.084
Sofowora, M. A., Obono, S. D. E., & Abayomi, A. (2022). The Influence of Mathematics on Students’
Performance in Computer Programming. In M. Ben Ahmed, A. A. Boudhir, İ. R. Karaș, V. Jain, &
S. Mellouli (Eds.), Lecture Notes in Networks and Systems (Vol. 393, pp. 745–755). Springer
International Publishing. https://doi.org/10.1007/978-3-030-94191-8_60
Sun, L., Frederick, C., Ding, L., & Rohmeyer, R. (2017). The application of second language acquisition
to programming language study. ASEE Annual Conference and Exposition, Conference
Proceedings, 2017-June. https://doi.org/10.18260/1-2–27424
Sunday, K., Ocheja, P., Hussain, S., Oyelere, S. S., Balogun, O. S., & Agbo, F. J. (2020). Analyzing
student performance in programming education using classification techniques. International
Journal of Emerging Technologies in Learning, 15(2), 127–144.
https://doi.org/10.3991/ijet.v15i02.11527
Talysheva, I., Pegova, K., & Khaliullina, L. (2021). The Use of Electronic Educational Resources of the
University as a Means of Increasing the Educational Motivation of Students. International Journal
of Emerging Technologies in Learning, 16(1), 289–304. https://doi.org/10.3991/IJET.V16I01.16799
Tomaszewski, W., Xiang, N., Huang, Y., Western, M., McCourt, B., & McCarthy, I. (2022). The Impact

of Effective Teaching Practices on Academic Achievement When Mediated by Student
Engagement: Evidence from Australian High Schools. Education Sciences, 12(5).
https://doi.org/10.3390/educsci12050358
Tunde, A. (2022). Educational Resources Availability and Utilization As Determinant of Students
Academic Performance in South West Nigeria. African Journal of Education and Practice, 8(5),
45–63. https://doi.org/10.47604/ajep.1636
Wang, Y., & Wang, Y. (2023). Exploring the relationship between educational ICT resources, student
engagement, and academic performance: A multilevel structural equation analysis based on PISA
2018 data. Studies in Educational Evaluation, 79(June), 101308.
https://doi.org/10.1016/j.stueduc.2023.101308
Youssef, A. Ben, Dahmani, M., & Ragni, L. (2022). ICT Use, Digital Skills and Students’ Academic
Performance: Exploring the Digital Divide. Information (Switzerland), 13(3), 1–19.
https://doi.org/10.3390/info13030129
Zhang, N. (2023). A Comparative Analysis of the Relationship Between ICT Resources and Students’
Reading Performance: Evidence from China, Japan and Singapore. Advances in Education,
Humanities and Social Science Research, 5(1), 469. https://doi.org/10.56028/aehssr.5.1.469.2023
Zhang, Y., Paquette, L., & Hu, X. (2024). Academic procrastination, incentivized and self-selected
spaced practice, and quiz performance in an online programming problem system: An intensive
longitudinal investigation. Computers and Education, 214, 105029.
https://doi.org/10.1016/j.compedu.2024.105029