Assessment and Feedback in Online Computer Science Education

Name of Author : Prof. Simeon Peter Olusola Gbeleyi

Abstract: This systematic review examines the effectiveness of online assessment and feedback tools in improving student learning outcomes in computer science (CS). Drawing on empirical studies, systematic reviews, and technical reports from 2012–2025, the paper synthesizes evidence on automated grading, formative feedback systems, peer assessment, learning analytics, and feedback literacy. Findings indicate that automated and analytics-driven feedback can improve timeliness and scalability of formative feedback, while peer and tutor feedback remain important for higher-order skill development. Effectiveness depends on alignment with learning objectives, feedback quality, timeliness, and students’ feedback literacy. The review concludes with practical recommendations for CS instructors and research priorities.

Keywords : Online assessment; automated feedback; learning analytics; computer science education; formative assessment

DOI :