Scaffolding students’ learning of introductory programming in online higher education by personalised formative assessments

Abstract

This paper presents the results of a study to investigate the application of personalised assessment in supporting students’ learning of introductory programming. The participants of the study were university students majoring in information technology and data analytics. The students in the study were added to a Moodle course called Computer Programming in Python, where they were allowed to take a test implemented using personalised assessment and another test implemented using traditional assessment (i.e., timed, fixed length and randomised ordering) as many times as they intend. The tests consist of mixed types of questions ranging from single word answers, True-False to multiple choice questions with three, four or five possible answers with one correct answer. The questions for the test using personalised assessment are divided into three categories according to the level of difficulty (easy, medium and hard). Based on these three categories, students’ abilities were estimated as Beginner, Intermediate, Advanced and Expert and detailed personalised feedback were provided instantly highlighting the concepts and issues in their attempts and linking with the course contents and course objectives. The results of the study show that the personalised assessment significantly outperforms traditional assessment with respect to usability, effectiveness and immediate quality feedback.