Mining Hierarchies with Conviction: Constructing the CS1 Skill Hierarchy with Pairwise Comparisons over Skill Distributions
The skills taught in introductory programming courses are categorized into 1) \textit{explaining} the purpose of code, 2) the ability to arrange lines of code in correct \textit{sequence }, and 3) the ability to \textit{trace} through the execution of a program, and 4) the ability to \textit{write}...
Gespeichert in:
Hauptverfasser: | , , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The skills taught in introductory programming courses are categorized into 1)
\textit{explaining} the purpose of code, 2) the ability to arrange lines of
code in correct \textit{sequence }, and 3) the ability to \textit{trace}
through the execution of a program, and 4) the ability to \textit{write} code
from scratch. Knowing if a programming skill is a prerequisite to another would
benefit students, particularly those new to programming, by allowing them to
encounter new topics in the optimal skill sequence. In this study, we used the
conviction measure from association rule mining to perform pair-wise
comparisons of five skills: Write, Trace, Reverse trace, Sequence, and Explain
code. We used the data from four exams with more than 600 participants in each
exam from a public university in the United States, where students solved
programming assignments of different skills for several programming topics. Our
findings matched the previous finding that tracing is a prerequisite for
students to learn to write code. But, contradicting the previous claims, our
analysis showed that writing code is a prerequisite skill to explaining code
and that sequencing code is not a prerequisite to writing code. Our research
can help instructors by systematically arranging the skills students exercise
when encountering a new topic. The goal is to reduce the difficulties students
experience when learning that topic. |
---|---|
DOI: | 10.48550/arxiv.2410.12967 |