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International Journal of Academic Research in Economics and Management Sciences

Open Access Journal

ISSN: 2226-3624

SCORE Overview: Programming and Computational Thinking in Vocational Landscape

Nurbaya Mohd Rosli, Mohd Effendi @ Ewan Mohd Matore, Hazrati Husnin, Siti Hannah Sabtu, Muhamad Firdaus Mohd Noh, Mohd Tarmizi Azerman, Hamzah Ishak, Nursohana Othman

http://dx.doi.org/10.6007/IJAREMS/v13-i4/22747

Open access

The increasing complexity of the digital economy underscores the need for vocational students in Malaysia to develop strong programming and computational thinking skills. To address this, it is essential to create effective screening tools that can accurately measure these competencies during the admissions process. This concept paper applies the SCORE Analysis Model, encompassing Strengths, Challenges, Options, Response, and Effectiveness. It represents as a strategic framework for developing and implementing such screening tests within vocational education. The paper begins by examining the strengths of current educational practices and assessment methodologies, particularly those grounded in psychometric principles. It then identifies the challenges associated with measuring programming and computational thinking skills, including the need for valid and reliable instruments, the integration of these assessments into existing curricula, and the variability in student preparedness. Drawing from these insights, the paper explores a range of strategic options to address these challenges, such as the development of adaptive testing methods, the use of digital platforms for assessment, and collaboration with industry partners to ensure relevance and rigor. The response section outlines a targeted strategy for the development and validation of the screening test, ensuring it leverages identified strengths while addressing the critical challenges. Finally, the effectiveness of this approach is evaluated through measurable outcomes, including the reliability and validity of the screening test, student performance metrics, and alignment with industry standards. The SCORE framework thus offers a comprehensive approach to the strategic development of educational measurements, providing a pathway to enhance the selection process for vocational education and better prepare students for the demands of the technology-driven workforce.

Espinosa, M. G. (2023). The skills of thinking and computational programming. Revista de Pedagogía Critica, 7(17), 6–11. https://doi.org/10.35429/jcp.2023.17.7.6.11
Berman, G., Goyal, N., & Madaio, M. (2024). A Scoping Study of Evaluation Practices for Responsible AI Tools: Steps Towards Effectiveness Evaluations. Conference on Human Factors in Computing Systems - Proceedings. https://doi.org/10.1145/3613904.3642398
Daniels, J., Bowers, L., Cook, M., Antonio, M., Foltz, A., Mccombs, C., Sound, J., & Vancuren, J. (2019). Improving Completion Rates for Underrepresented Populations. Inquiry: The Journal of the Virginia Community Colleges, 22(1), 22. https://commons.vccs.edu/inquiry/vol22/iss1/8
Dao, L. D., & Khanh, T. X. (2023). Effective project monitoring for ERP implementation success: A case study in a S&M company in Vietnam. Hong Bang International University Journal of Science, 4(June), 19–26. https://doi.org/10.59294/hiujs.vol.4.2023.382
Fatah, A., Oktapia, D., Hasibuan, I. T., & Khotima, N. (2024). Tantangan dan Strategi Merancang Program Pendidikan dan Pelatihan Berbasis Kompetensi. Cemara Journal, II(1), 69–75.
Ford, C. R., Ingalsbe, K., & Hanvey, A. (2024). Graduate program collaborations to identify and cultivate graduate enrollment best practices. New Directions for Higher Education, 2024(205), 59–74. https://doi.org/https://doi.org/10.1002/he.20502
Hassan, H. harbi, Alwan, Z. Y., & Berto, M. F. (2024). Examining the Impact of the Dimensions of Strategic Thinking on Outstanding Performance. The American Journal of Management and Economics Innovations, 6(2), 23–39. https://doi.org/10.37547/tajmei/volume06issue02-04
Jamaludin, R. B., Hamid, A. H. A., & Alias, B. S. (2023). Empowering Technical and Vocational Education and Training (TVET). International Journal of Academic Research in Business and Social Sciences, 13(12), 3072–3080. https://doi.org/10.6007/ijarbss/v13-i12/20159
Luesia, J. F., Benítez, I., Company-Córdoba, R., Gómez-Gómez, I., & Sánchez-Martín, M. (2023). Assessing the relevance of academic competencies in college admission tests from a higher-order thinking perspective: A systematic review. Thinking Skills and Creativity, 48, 101251. https://doi.org/https://doi.org/10.1016/j.tsc.2023.101251
Ma, H., Zeng, Y., Yang, S., Qin, C., Zhang, X., & Zhang, L. (2023). A novel computerized adaptive testing framework with decoupled learning selector. Complex and Intelligent Systems, 9(5), 5555–5566. https://doi.org/10.1007/s40747-023-01019-1
Makgamatha, M. M. (2022). Quality assurance processes of language assessment artefacts and the development of language teachers’ assessment competence. South African Journal of Childhood Education, 12(1), 1–11. https://doi.org/10.4102/sajce.v12i1.1151
Nong, S. A., & Osman, S. Z. (2024). Needs of 21St Century Artistic Skills for Students’ Career Readiness. International Journal of Modern Education, 6(20), 271–282. https://doi.org/10.35631/ijmoe.620021
Neal, M. (2023). SWOT, NOISE, SOAR, and SCORE, Tools for Strategy. https://medium.com/@marcneal/swot-noise-soar-and-score-tools-for-strategy-3b11a30031fd
Neal, M. (2024). SCORE, an Alternative to SWOT. https://medium.com/@marcneal/score-an-alternative-to-swot-64bcf5fc740a
Nieuwerburgh, C. van, & Green, A. (2022). Strengths-based interventions for students and staff. In Applied Positive School Psychology (p. 8). Routledge.
Proctor, C. (2023). Computational thinking. International Encyclopedia of Education(Fourth Edition), 88–95. https://doi.org/10.1016/B978-0-12-818630-5.13078-7
TADEU, P., & BR?GAS, C. (2022). Multiple Intelligence’s and Computational Thinking. Journal of Computer and Education Research, 10(19), 1–17. https://doi.org/10.18009/jcer.1027934
Davier, A. A. (2017). Computational Psychometrics in Support of Collaborative Educational Assessments. Journal of Educational Measurement, 54(1), 3–11. https://doi.org/10.1111/jedm.12129
Wing. (2014). Computational thinking benefits society. Social Issues in Computing New York: Academic Press 40th Anniversary Blog. http://socialissues.cs.toronto.edu/index.html%3Fp=279.html
Winkler, D. R. (1987). Screening Models and Education. In Economics of Education. Pergamon Books Ltd. https://doi.org/10.1016/b978-0-08-033379-3.50058-9
Young, R. R. (2022). Factors Affecting Formative Assessments: Basis for A Plan of Action For Its Effective Implementation. AIDE Interdisciplinary Research Journal, 3(November), 498–526. https://doi.org/10.56648/aide-irj.v3i1.83
Zhang, Q., & Neitzel, A. (2024). Choosing the Right Tool for the Job: Screening Tools for Systematic Reviews in Education. Journal of Research on Educational Effectiveness, 17(3), 513–539. https://doi.org/10.1080/19345747.2023.2209079

Rosli, N. M., Matore, M. E. @ E. M., Husnin, H., Sabtu, S. H., Noh, M. F. M., Azeman, M. T., Ishak, H., & Othman, N. (2024). SCORE Overview: Programming and Computational Thinking in Vocational Landscape. International Journal of Academic Research in Economics and Management Sciences, 13(4), 63–70.