ON THE ASSESSMENT OF STUDENTS’ SOFTWARE TESTING AND PROGRAMMING LANGUAGE SKILLS – CAMEROON CONTEXT: AN EXPERIMENTAL APPROACH
Despite decades of researches and technological advancements in software development, there is still a wide gap between good programmers, good software testers, software industry and the academic world.Higher institutions continue to rely on traditional teaching methods which fails to leverage recent technological improvements.The complexity of software systems has made traditional assessment methods inadequate to meets new programming demands.Over the last decades, the fastgrowing complexity of software systems has forced academic world to improve to a certain extent on teaching techniques in order to meet up with industrial demands.Nevertheless, there is still a wide gap as theory does not match practical.This paper presents a novel performance assessment method for assessing students' practical work not only in Software Testing courses but equally Programming Languages courses, by establishing an eye-tracking practical monitoring system in order to improve the rate of students' performance.We developed a novel assessment algorithm that used five performance criteria that were used in two Software testing and programming language courses for two consecutive semesters in 2023-2024 academic year in University of Yaound 1, Yaound, Cameroon.The assessment was done in two levels: Students-self assessment and Lecturer assessment of students' group practical using five features for assessment.After using this approach in two courses for two consecutive semesters, we observed significant improvements of students' learning outcome in various aspects.The results revealed that, the use of scoring elements with linguistics variables can also produce an evidence-based students' growth assessments direction showing whether a student is either improving or not in an iterative assessment.
Authors
- DJAM Xaveria Youh
- TAPAMO Kenfack Hyppolyte Michel
- Aminou Halidou
- Atsa Roger Etoundi
Publication Details
- Journal
- International Journal of Electronics Engineering and Applications
- Published
- 2025-03-01
- DOI
- https://doi.org/10.30696/ijeea.xiii.i.2025.21-41
- Primary Topic
- Artificial Intelligence in Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00