Development and Validation of Adaptable Rubrics for Programming Assessments: Measuring Computational Competencies

Advanced technological innovations and problem-solving across various domains demand proficient programming skills. Thus, developing and measuring computational competencies are critical in this modern digital era. Despite their significance, assessing these competencies is challenging, especially when catering to personalized learning needs. Several assessment methods are available, yet there is a lack of fast, adaptable and validated evaluation tools. This study addresses this gap by developing and validating adaptable rubrics for assessing computational competencies and fostering improved learning outcomes in the computer programming domain. The preliminary rubric was developed per the JAVA programming curricula, educational frameworks, and experts' opinions. A sample of 300 students studying the JAVA programming language were assessed via a multiple-response objective assessment based on the initial rubric. The rubric-based evaluation results were subjected to rigorous statistical analyses, including exploratory and confirmatory factor analyses, correlation, and regression analyses. The findings yielded a four-factor validated adapted rubric structure emphasizing the required computational competencies in the programming domain. Further, moderate associations between rubric scores and Java academic evaluations were revealed, highlighting the predictive validity of rubric-based objective assessments. This research work contributes to the refinement of rubric and assessment practices in programming education, offering insights into the role of adaptable rubrics in promoting student learning and suggesting pedagogical approaches. The findings of this study hold practical implications for educators, curriculum designers, and policymakers. The targeted interventions, adapting rubric-based assessment criteria, improving pedagogical strategies, and enriching curriculum design ensure that the learning experiences of programming learners are tailored to their individual needs and aspirations.

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Publication Details

Journal
Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformation
Published
2025-10-01
DOI
https://doi.org/10.16920/jeet/2025/v39i2/25149
Primary Topic
Teaching and Learning Programming
Type
article
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article

Development and Validation of Adaptable Rubrics for Programming Assessments: Measuring Computational Competencies

Priyanka Gupta, Deepti Mehrotra, Sunil Vadera
Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformation
Teaching and Learning Programming
article

Development and Validation of Adaptable Rubrics for Programming Assessments: Measuring Computational Competencies

Priyanka Gupta, Deepti Mehrotra, Sunil Vadera
article en

Abstract

Advanced technological innovations and problem-solving across various domains demand proficient programming skills. Thus, developing and measuring computational competencies are critical in this modern digital era. Despite their significance, assessing these competencies is challenging, especially when catering to personalized learning needs. Several assessment methods are available, yet there is a lack of fast, adaptable and validated evaluation tools. This study addresses this gap by developing and validating adaptable rubrics for assessing computational competencies and fostering improved learning outcomes in the computer programming domain. The preliminary rubric was developed per the JAVA programming curricula, educational frameworks, and experts' opinions. A sample of 300 students studying the JAVA programming language were assessed via a multiple-response objective assessment based on the initial rubric. The rubric-based evaluation results were subjected to rigorous statistical analyses, including exploratory and confirmatory factor analyses, correlation, and regression analyses. The findings yielded a four-factor validated adapted rubric structure emphasizing the required computational competencies in the programming domain. Further, moderate associations between rubric scores and Java academic evaluations were revealed, highlighting the predictive validity of rubric-based objective assessments. This research work contributes to the refinement of rubric and assessment practices in programming education, offering insights into the role of adaptable rubrics in promoting student learning and suggesting pedagogical approaches. The findings of this study hold practical implications for educators, curriculum designers, and policymakers. The targeted interventions, adapting rubric-based assessment criteria, improving pedagogical strategies, and enriching curriculum design ensure that the learning experiences of programming learners are tailored to their individual needs and aspirations.

Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformationVol. 39(2)
Openalex Percentile: Top 69%
Teaching and Learning Programming
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