IMPLEMENTING SCIENTIFIC PROJECT-BASED LEARNING IN COMPUTER PROGRAMMING COURSES: EVIDENCE ON QUALITY EDUCATION, LIFELONG LEARNING AND DECENT WORK SKILLS FROM KAZAKHSTAN
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Higher education is under pressure to translate programming instruction into demonstrable competence because technology employers recruit on evidence of applied problem-solving and teamwork rather than on course credits, and this gap between certification and capability constrains progress towards quality education, lifelong learning and decent work. This study investigates whether Scientific Project-Based Learning (SPBL), an instructional model that couples project work with systematic scientific inquiry, is associated with differentiated gains across four competence domains among undergraduate programming students: foundational programming skills, hands-on application of theory, problem-solving, and collaboration. The study employs cross-sectional survey data from 135 third-year and fourth-year students of the 6B061 Information and Communication Technologies in Education programme at M. Auezov South Kazakhstan University, Shymkent, Kazakhstan, all of whom completed a five-course programming sequence delivered through SPBL; perceptions were captured on a forced-choice four-point Likert instrument of eight statements and analysed using frequency distributions, item means, standard deviations, one-sample t-tests against the scale midpoint and Cohen's d. The results show that collaboration recorded the highest domain mean of 3.27 and problem solving 2.98, while hands-on application reached 2.73 and confidence in applying programming concepts recorded 2.39, the only item that did not differ significantly from the midpoint (t = -1.09, p = 0.278); effect sizes ranged from d = 1.13 to d = -0.09. The findings suggest that SPBL operates unevenly across competence domains, delivering large and consistent gains in collaborative and problem-solving capability while producing weak and heterogeneous gains in the transfer of theoretical knowledge into confident, independent coding practice.
JEL Classification Codes: A22, I21, I23, J24, O33.
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