Toward Understanding Students' Learning Performance in an Object-Oriented Programming Course: The Perspective of Program Quality

This pilot study examines how students' performance has evolved in an Object-oriented (OO) programming course and contributes to the learning analytic framework for similar programming courses in university curriculum. First, we briefly introduce the research background, a novel OO teaching pra...

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Veröffentlicht in:IEEE access Jg. 8; S. 37505 - 37517
Hauptverfasser: Sun, Qing, Wu, Ji, Liu, Kaiqi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway IEEE 2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Colleges & universities
Correlation analysis
Curricula
Design analysis
Education
Empirical analysis
empirical assessment
Learning
Measurement
Object oriented programming
Object-oriented Metrics
Principal components analysis
Programming profession
Q factors
Software
Software testing
Source code
Students
Teachers
Teaching
Trend analysis
ISSN:2169-3536, 2169-3536
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Zusammenfassung:This pilot study examines how students' performance has evolved in an Object-oriented (OO) programming course and contributes to the learning analytic framework for similar programming courses in university curriculum. First, we briefly introduce the research background, a novel OO teaching practice with consecutive and iterative assignments consisting of programming and testing assignments. We propose a planned quantitative method for assessing students' gains in terms of programming performance and testing performance. Based on real data collected from students who engaged in our course, we use trend analysis to observe how students' performance has improved over the whole semester. By using correlation analysis, we obtain some interesting findings on how students' programming performance correlates with testing performance, which provides persuasive empirical evidence in integrating software testing practices into an Object-oriented programming curriculum. Then, we conduct an empirical study on how students' design competencies are represented by their program code quality changes over consecutive assignments by analyzing their submitted source code in the course system and the GitLab repository. Three different kinds of profiles are found in the students' program quality in the OO design level. The group analysis results reveal several significant differences in their programming performance and testing performance. Moreover, we conduct systematical explanations on how students' programming skill improvement can be attributed to their object-oriented design competency. By performing principal component analysis on software statistical data, a predictive OO metrics suite for both students' programming performance and their testing performance is proposed. The results show that these quality factors can serve as useful predictors of students' learning performance and can provide effective feedback to the instructors in the teaching practices.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2973470