programming education consistently faces challenges in bridging theory with practice and fostering students' cognitive competencies. This 12-year longitudinal study (2011-2023) investigates an innovative competenc...
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programming education consistently faces challenges in bridging theory with practice and fostering students' cognitive competencies. This 12-year longitudinal study (2011-2023) investigates an innovative competency-based teaching model in university C programming education that integrates six educational theories into a coherent framework with three dimensions (theoretical, practical, innovative), four integration mechanisms, and five combinatorial strategies. Using a mixed-methods approach with a quasi-experimental design, we studied 4,051 undergraduate students from a Chinese university. Results revealed significant enhancement in students' cognitive abilities, as measured by Raven's Standard Progressive Matrices (t (350) = 8.76, p < 0.001, d = 0.68), which strongly correlated with improved academic performance (r = 0.62), computational thinking (r = 0.71), and problem-solving skills (r = 0.67). The model creates multiple pathways for cognitive development through synergistic interactions between components, promoting collaboration and self-directed learning with effects extending beyond graduation. Multiple regression analysis identified three key predictors of cognitive enhancement: classroom engagement (beta = 0.35), project completion (beta = 0.28), and participation in innovation activities (beta = 0.22). This study provides robust empirical evidence for the long-term efficacy of a competency-based model in programming education, presenting a transformative approach to STEM education reform particularly relevant in rapidly evolving technological landscapes.
Instructional scaffolding is a well-researched, commonly-practiced educational technique whereby support is temporarily provided as an individual learns [1]. Grounded in constructivist teaching and learning theory, sc...
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ISBN:
(纸本)9781509059201
Instructional scaffolding is a well-researched, commonly-practiced educational technique whereby support is temporarily provided as an individual learns [1]. Grounded in constructivist teaching and learning theory, scaffolding historically referring to support provided by a teacher to a student. However, in the modern learning environment, instructors have access to a wide range of tools and techniques with which to help them scaffold learners [2]. This paper reports the findings of a design experiment comparing the employment of two instructional scaffolding strategies in reducing the impact of large laboratory class size on undergraduate students enrolled in an introductory computerprogramming course having a mandatory laboratory component. The design experiment compared the performance of students on programming procedural knowledge assessments as well as programming self-beliefs in two offerings of the course, each treated as a cohort, which differed in the instructional scaffolding strategy employed in the mandatory laboratory component. In one cohort, an undergraduate teaching assistant was used as a supplement to the laboratory instructor while students completed programming exercises in the laboratory component of the course. In the other cohort, a cooperative programming methodology known as pair programming was used as a supplement to the laboratory instructor while students completed programming exercises in the laboratory component of the course. Cohort composition, including school of study (e.g., Liberal Arts, Science, Technology, Engineering, Business, etc.), student classification (i.e., freshman, sophomore, junior, senior, or other), gender ratio, and amount of prior programming experience, was comparable. Course content, administrative processes and assessment mechanisms (formative and summative) remained constant. Each student completed a summative assessment of programming procedural knowledge at weeks 7, 12, and 16 of the semester. Open ended f
Educational curricula in data analysis are increasingly fundamental to statistics, data science, and a wide range of disciplines. The educational literature comparing coding syntaxes for instruction in data analysis r...
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Educational curricula in data analysis are increasingly fundamental to statistics, data science, and a wide range of disciplines. The educational literature comparing coding syntaxes for instruction in data analysis recommends utilizing a simple syntax for introductory coursework. However, there is limited prior work to assess the pedagogical elements of coding syntaxes. The study investigates the paradigms of the dplyr, ***, and DTwrappers packages for R programming from a pedagogical perspective. We enumerate the pedagogical elements of computerprogramming that are inherent to utilizing each package, including the functions, operators, general knowledge, and specialized knowledge. The merits of each package are also considered in concert with other pedagogical goals, such as computational efficiency and extensions to future coursework. The pedagogical considerations of this study can help instructors make informed choices about their curriculum and how best to teach their selected methods.
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