A Data-Driven Approach to Compare the Syntactic Difficulty of Programming Languages

Educators who teach programming subjects are often wondering "which programming language should I teach first?" The debate behind this question has a long history and coming up with a definite answer to this question would be farfetched. Nonetheless, several efforts can be identified in th...

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Vydáno v:Journal of information systems education Ročník 34; číslo 1; s. 84 - 93
Hlavní autoři: Lokkila, Erno, Christopoulos, Athanasios, Laakso, Mikko-Jussi
Médium: Journal Article
Jazyk:angličtina
Vydáno: West Lafayette Journal of Information Systems Education 2023
EDSIG
Témata:
Academic achievement
Adaptive learning
Artificial intelligence
Coding
College students
Comparative Analysis
Computer programming
Computer science
Computer Science Education
Difficulty Level
Error Patterns
Errors
Higher education
Individualized Instruction
Information Science Education
Information systems
Introductory Courses
Java
Languages
Learning Analytics
Learning Management Systems
Object oriented programming
Pedagogy
Popularity
Probability
Programming Languages
Python
Questions
Students
Syntax
Teachers
Teaching
Textbooks
Transition probabilities
Trends
Undergraduate Students
Undergraduate study
United Kingdom
ISSN:1055-3096, 2574-3872
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Shrnutí:Educators who teach programming subjects are often wondering "which programming language should I teach first?" The debate behind this question has a long history and coming up with a definite answer to this question would be farfetched. Nonetheless, several efforts can be identified in the literature wherein pros and cons of mainstream programming languages are examined, analysed, and discussed in view of their potential to facilitate the didactics of programming concepts especially to novice programmers. In line with these efforts, we explore the latter question by comparing the syntactic difficulty of two modern, but fundamentally different, programming languages: Java and Python. To achieve this objective, we introduce a standalone and purely data-driven method which stores the code submissions and clusters the errors occurred under the aid of a custom transition probability matrix. For the evaluation of this model a total of 219,454 submissions, made by 715 first-year undergraduate students, in 259 unique programming exercises were gathered and analysed. The results indicate that Python is an easier-to-grasp programming language and is, therefore, highly recommended as the steppingnstone in introductory courses. Besides, the adoption of the described method enables educators to not only identify those students who struggle with coding (syntax-wise) but further paves the pathway for the adoption of personalised and adaptive learning practices.
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ISSN:1055-3096
2574-3872