Enhancing vocational school counseling program supervision through data-driven feedback

Jurnal Konseling dan Pendidikan October 24, 2024 Volume 12, Number 3 2 authors

Abstract

This study aims to explore the effectiveness of a data-driven structured feedback mechanism in the supervision of guidance and counseling (BK) programs in vocational high schools (SMK) in Central Java, Indonesia. Using a quasi-experimental design with pretest-posttest control group approach, the study involved 10 vocational high schools, with 5 schools each in the experimental and control groups. The experimental group comprised 5 supervisors and 10 counseling teachers, while the control group had the same number of participants. Results showed a significant improvement in supervisory effectiveness in the experimental group, with a mean difference of 1.25 (p < 0.001), compared to a minimal increase of 0.15 in the control group. The findings highlight the importance of integrating data in educational supervision and contribute to the development of more effective supervision models.

Authors

  1. Hanung Sudibyo

    Universitas Pancasakti Tegal

  2. Yovian Yustiko Prasetya

    Universitas Pancasakti Tegal,

Keywords

Structured feedbacksupervision of counseling programdata-drivenvocational schools.

References

  1. Asfaw, Z., Alemneh, D., & Jimma, W. (2023). Data-Driven Decision-Making and Its Impacts on Education Quality in Developing Countries: A Systematic Review. 2023 International Conference on Information and Communication Technology for Development for Africa, ICT4DA 2023, 198 – 203. https://doi.org/10.1109/ICT4DA59526.2023.10302228
  2. Awange, J. L. (2012). Environmental monitoring. Environmental Science and Engineering (Subseries: Environmental Science), 9783540882558, 1 – 12. https://doi.org/10.1007/978-3-540-88256-5_1
  3. Bastian, K. C., Fortner, C. K., Chapman, A., Flener, M. J., McIntyre, E., & Patriarca, L. A. (2016). Data sharing to drive the improvement of teacher preparation programs. Teachers College Record, 118(12), 1 – 29. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85007203538&partnerID=40&md5=ef210e0e437a7b0bb1589334ea7b3caf
  4. Davis, K. F., Loos, J. R., & Boland, M. G. (2021). Five Years and Moving Forward: A Successful Joint Academic-Practice Public Partnership to Improve the Health of Hawaii’s Schoolchildren. Journal of School Health, 91(7), 584 – 591. https://doi.org/10.1111/josh.13034
  5. Dunlap, K., & Piro, J. S. (2016). Diving into data: Developing the capacity for data literacy in teacher education. Cogent Education, 3(1). https://doi.org/10.1080/2331186X.2015.1132526
  6. Giroth, R. E., Lengkong, J., & Sumual, S. D. M. (2021). Performance of principal Baitani Kindergarten Eben Haezer Koha, Mandolang district, North Sulawesi – Indonesia. https://api.semanticscholar.org/CorpusID:235408681
  7. Herman, H., & Khalaf, O. I. (2023). Evidence from School Principals: Academic Supervision Decision-making on Improving Teacher Performance in Indonesia. Advances in Decision Sciences, 27(3). https://doi.org/10.47654/v27y2023i3p46-71
  8. Indadihayati, W., & Hariyanto, V. L. (2023). Tinjauan Literatur Tentang Penerapan Prinsip Total Quality Management Dalam Pendidikan Vokasi : Tantangan Dan Peluang. 7(1), 1–20. https://doi.org/10.33363/satya-sastraharing.v7i1.1029
  9. Kerr, K. A., Marsh, J. A., Ikemoto, G. S., Darilek, H., & Barney, H. (2006). Strategies to promote data use for instructional improvement: Actions, outcomes, and lessons from three urban districts. American Journal of Education, 112(4), 496 – 520. https://doi.org/10.1086/505057
  10. Luoma, P., Rauter, R., Penttinen, E., & Toppinen, A. (2023). The value of data for environmental sustainability as perceived by the customers of a tissue-paper supplier. Corporate Social Responsibility and Environmental Management, 30(6), 3110 – 3123. https://doi.org/10.1002/csr.2541
  11. Mhlanga, D. (2024). Driving Responsible Business and Sustainable Development: Leveraging Data and Metrics for Transformative Impact in the Global South. In Responsible Business and Sustainable Development: the Use of Data and Metrics in the Global South. https://doi.org/10.4324/9781032712246-10
  12. Prasetya, Y. Y., Setiawan, D., Aditama, M. H. R., & Selfiardy, S. (2024). The school counselor’s role in addressing ACEs: an intervention strategy. Journal of Public Health, 46(1), e201–e202. https://doi.org/10.1093/pubmed/fdad174
  13. Ronfeldt, M., & Campbell, S. L. (2016). Evaluating Teacher Preparation Using Graduates’ Observational Ratings. Educational Evaluation and Policy Analysis, 38(4), 603 – 625. https://doi.org/10.3102/0162373716649690
  14. Ryan, S. E., & Sladyk, K. (2024). Occupational Therapy Assistant Supervision. In Ryan’s Occupational Therapy Assistant: Principles, Practice Issues, and Techniques, Fifth Edition. https://doi.org/10.4324/9781003526346-47
  15. Schafer, C. M. (2024). Three ways big data can realize sustainability, digital transformation initiatives. Plant Engineering, 78(1), 22 – 23. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194913072&partnerID=40&md5=1af875f128056ddfc59e5ae139a1d552
  16. Schahczenski, C., & van Dyne, M. (2019). Easing the burden of program assessment: Web-based Tool Facilitates Measuring Student Outcomes for ABET Accreditation. Proceedings of the Annual Hawaii International Conference on System Sciences, 2019-January, 7624 – 7631. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081533578&partnerID=40&md5=0d552b62ad643243dfdd64fbf5825494
  17. Schildkamp, K., Poortman, C., Luyten, H., & Ebbeler, J. (2017). Factors promoting and hindering data-based decision making in schools. School Effectiveness and School Improvement, 28(2), 242 – 258. https://doi.org/10.1080/09243453.2016.1256901
  18. Shen, J., Cooley, V. E., Reeves, P., Burt, W. L., Ryan, L., Rainey, J. M., & Yuan, W. (2010). Using data for decision-making: Perspectives from 16 principals in Michigan, USA. International Review of Education, 56(4), 435 – 456. https://doi.org/10.1007/s11159-010-9172-x
  19. Verhaeghe, G., Schildkamp, K., Luyten, H., & Valcke, M. (2015). Diversity in school performance feedback systems. School Effectiveness and School Improvement, 26(4), 612 – 638. https://doi.org/10.1080/09243453.2015.1017506
  20. Weidlich, J., Fink, A., Jivet, I., Yau, J., Giorgashvili, T., Drachsler, H., & Frey, A. (2024). Emotional and motivational effects of automated and personalized formative feedback: The role of reference frames. Journal of Computer Assisted Learning. https://doi.org/10.1111/jcal.13024
  21. Xu, Z., Backes, B., & Goldhaber, D. (2023). The Impact of Transition Intervention in High School on Pathways Through College. Community College Review, 51(2), 216 – 245. https://doi.org/10.1177/00915521221145325