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Introductory programming courses aim to teach students to write code independently. However, transitioning from studying worked examples to generating their own code is often difficult and frustrating for students, especially those with lower CS self-efficacy in general. Therefore, we investigated the impact of using Parsons problems as a code-writing scaffold for students with varying levels of CS self-efficacy. Parsons problems are programming tasks where students arrange mixed-up code blocks in the correct order. We conducted a between-subjects study with undergraduate students (N=89) on a topic where students have limited code-writing expertise. Students were randomly assigned to one of two conditions. Students in one condition practiced writing code without any scaffolding, while students in the other condition were provided with scaffolding in the form of an equivalent Parsons problem. We found that, for students with low CS self-efficacy levels, those who received scaffolding achieved significantly higher practice performance and in-practice problem-solving efficiency compared to those without any scaffolding. Furthermore, when given Parsons problems as scaffolding during practice, students with lower CS selfefficacy were more likely to solve them. In addition, students with higher pre-practice knowledge on the topic were more likely to effectively use the Parsons scaffolding. This study provides evidence for the benefits of using Parsons problems to scaffold students’ write-code activities. It also has implications for optimizing the Parsons scaffolding experience for students, including providing personalized and adaptive Parsons problems based on the student’s current problem-solving status.
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The Impact of Connecting Worked Examples and Completion Problems for Introductory Programming Practice
Worked examples have consistently demonstrated their value in education, serving as the model solutions for solving specific problem types. Past studies indicate that combining worked examples with practice problems is more effective than providing either problems or examples in isolation. Despite these findings, the exploration of the effects of grouping worked examples and problems for programming practice is limited, especially in learning environments designed for practice. This paper compares two content organization approaches in a practice system. The first one is explicitly connecting worked examples and completion problems, allowing students to access them in smaller bundles. The other one is delivering the same set of activities separately but keeping an implicit connection by grouping them under a topic. We examined the effects of these two approaches on student engagement and performance in a semester-long classroom experiment conducted in a CS1 programming course. The results indicate that explicitly connecting worked examples and completion problems increased engagement with the completion problems and supported problem-solving performance by leading to higher success rates and persistence.
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- PAR ID:
- 10598698
- Publisher / Repository:
- European Conference on Technology Enhanced Learning, EC-TEL 2025
- Date Published:
- ISBN:
- 978-3-031-72314-8
- Page Range / eLocation ID:
- 3-18
- Subject(s) / Keyword(s):
- Worked examples computer science education CS1 Python programming open learner model classroom study
- Format(s):
- Medium: X
- Location:
- Krems, Austria
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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- The DOI is not currently available.
