An Assessment of Learning Content Model for Introductory Programming in Higher Education (original) (raw)

Academy of Sciences Malaysia, 2021

Abstract

Learning content plays an important role in introducing programming concepts to undergraduates. Nevertheless, among the key challenges in learning content adoption include the numerous undergraduates’ background characteristics. Learning content in introducing a programming language may take various forms depending on the level of mastery required. There is a need to identify how a particular form of learning content suits certain learners’ background characteristics. We propose the LEAP model, tracking the students’ Language proficiency in English (speaking, listening, reading, and writing), Educational background, Achievement in previous school examinations, and Programming experience. Furthermore, a programming learning asses sment (PLA) model is proposed with four dimensions: True/False Questions, Multiple Choice Questions (MCQ), Fill in the Blank, and Time taken to fulfill the given learning task. The results show that the percentage score of the PLA model correlates with the LEAP categorical data. This finding supports that learning content principles lead to benefits in the field of introductory programming in higher education. The models can be enhanced by adding more variables in assessing the learning content for any other programming languages

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