HIGH DENSITY CAPACITY BUILDING MODEL dalam LITERASI DATA SEKUNDER

Intan Mega Maharani, Dita Rosyita, Aulia Nurul Hikmah, Putra Astaman

Sari


Penguatan kompetensi berbasis pemanfaatan dataset sekunder menjadi kebutuhan penting dalam meningkatkan kesiapan riset mahasiswa. Namun, masih terdapat kesenjangan antara pemahaman konseptual metodologi dan kemampuan operasional dalam mengolah data riil. Kegiatan pengabdian ini bertujuan meningkatkan literasi analitik mahasiswa, memperkuat kemampuan eksplorasi dataset sekunder, serta mengevaluasi transformasi kesiapan penelitian melalui pelatihan intensif satu hari. Evaluasi menggunakan model Context–Input–Process–Product (CIPP) dengan partisipan 40 mahasiswa Agribisnis Universitas Pembangunan Nasional Veteran Jawa Timur yang dipilih secara purposif. Intervensi mengintegrasikan demonstrasi dataset dan praktik mandiri terbimbing. Kesiapan riset diukur secara multidimensi meliputi aspek kognitif, prosedural, dan afektif. Hasil menunjukkan peningkatan pemahaman konseptual dari 85% menjadi 100%, capaian keterampilan operasional berada pada kategori baik (mean 3,45/4), dan respons afektif sangat tinggi (mean 4,6/5). Temuan ini menunjukkan pelatihan singkat berbasis praktik efektif sebagai pemicu percepatan kesiapan penelitian mahasiswa. Meskipun terdapat potensi ceiling effect dan keterbatasan data agregat, model yang dikembangkan bersifat terstruktur dan berpotensi direplikasi pada konteks pendidikan tinggi.


Kata Kunci


Literasi analitik, research readiness, pelatihan intensif, evaluasi program

Teks Lengkap:

PDF

Referensi


Andrews, R., Higgins, S., Andrews, J., & Lalor, J. 2012. Classic grounded theory to analyse secondary data: Reality and reflections. The Grounded Theory Review, 11(1), 12–26.

Bandura, A. 1997. Self-efficacy: The exercise of control. W. H. Freeman.

Biggs, J., & Tang, C. 2011. Teaching for quality learning at university (4th ed.). Open University Press.

Burress, T. 2022. Data literacy and the undergraduate research process: A case study. The Journal of Academic Librarianship, 48(2), 102485. https://doi.org/10.1016/j.acalib.2021.102485

Echtenbruck, G., Fühles-Ubach, S., Naujoks, C., & Kaliva, A. 2025. Data literacy in higher education: A competence model for integrating data into academic research processes. Education and Information Technologies.

Ertl, B., Rutkowski, L., & Parry, M. 2020. Learning with large-scale assessment data: Potentials and challenges. Studies in Educational Evaluation, 66, 100887. https://doi.org/10.1016/j.stueduc.2020.100887

Gordon, S. 2004. Understanding students’ experiences with real data. Journal of Statistics Education, 12(1). https://doi.org/10.1080/10691898.2004.11910705

Hardini, A., & Dewi, R. 2025. Digital literacy and higher education transformation in Indonesia. Jurnal Pendidikan Indonesia, 14(1), 45–58.

Heeringa, S. G., West, B. T., & Berglund, P. A. 2017. Applied survey data analysis (2nd ed.). CRC Press. https://doi.org/10.1201/9781315153278

Hmelo-Silver, C. E., Duncan, R. G., & Chinn, C. A. 2007. Scaffolding and achievement in problem-based and inquiry learning. Educational Psychologist, 42(2), 99–107. https://doi.org/10.1080/00461520701263368

Hox, J. J., & Boeije, H. R. 2005. Data collection, primary versus secondary. In K. Kempf-Leonard (Ed.), Encyclopedia of Social Measurement (pp. 593–599). Elsevier. https://doi.org/10.1016/B0-12-369398-5/00041-4

Kolb, D. A. 1984. Experiential learning: Experience as the source of learning and development. Prentice Hall.

Martin, A. J., & Collie, R. J. 2022. Academic buoyancy and students’ academic outcomes: A review. Educational Psychology Review, 34, 2025–2054. https://doi.org/10.1007/s10648-021-09655-1

Neumann, D. L. 2013. Using real-life data when teaching statistics: Student perceptions of this strategy in an introductory statistics course. Statistics Education Research Journal, 12(2), 59–70.

OECD. 2021. OECD skills outlook 2021: Learning for life. OECD Publishing. https://doi.org/10.1787/0ae365b4-en

Parry, M., Rutkowski, L., & Ertl, B. 2021. Secondary data in education research: Opportunities and methodological considerations. Large-scale Assessments in Education, 9, 1–15. https://doi.org/10.1186/s40536-021-00107-3

Perkins, D. N., & Salomon, G. 1992. Transfer of learning. In International encyclopedia of education (2nd ed.). Pergamon Press.

Polit, D. F., & Beck, C. T. 2021. Nursing research: Generating and assessing evidence for nursing practice (11th ed.). Wolters Kluwer.

Rutkowski, L., Gonzalez, E., Joncas, M., & von Davier, M. 2010. International large-scale assessment data: Issues in secondary analysis and reporting. Educational Researcher, 39(2), 142–151. https://doi.org/10.3102/0013189X10363170

Smith, E. 2008. Using secondary data in educational research. Educational Research, 50(2), 183–195. https://doi.org/10.1080/00131880802082567

Stufflebeam, D. L. 2003. The CIPP model for evaluation. In T. Kellaghan & D. L. Stufflebeam (Eds.), International handbook of educational evaluation (pp. 31–62). Springer. https://doi.org/10.1007/978-94-010-0309-4_4

Walliman, N. 2021. Research methods: The basics (2nd ed.). Routledge. https://doi.org/10.4324/9781003145318

Wolff, A., Gooch, D., Cavero Montaner, J. J., Rashid, U., & Kortuem, G. 2016. Creating an understanding of data literacy for a data-driven society. Journal of Community Informatics, 12(3), 9–26. https://doi.org/10.15353/joci.v12i3.3275




DOI: https://doi.org/10.6131/sancaka.v2i1.206

DOI (PDF): https://doi.org/10.6131/sancaka.v2i1.206.g146

Refbacks

  • Saat ini tidak ada refbacks.


LEMBAGA PENELITIAN, PENGEMBANGAN, PEMBERDAYAAN POTENSI INDONESIA (LP4I)

Alamat Redaksi: Jl. Kemuliaan, Komp. BTP, Tamalanrea 90245,  Kota Makassar, Sulawesi Selatan

 This work is licensed under a Creative Commons Attribution 4.0 International License