An official website of the United States government
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.
more »
« less
Using Adaptive Parsons Problems to Scaffold Write-Code Problems
In this paper, we explore using Parsons problems to scaffold novice programmers who are struggling while solving write-code problems. Parsons problems, in which students put mixed-up code blocks in order, can be created quickly and already serve thousands of students while other types of programming support methods are expensive to develop or do not scale. We conducted two studies in which novices were given equivalent Parsons problems as optional scaffolding while solving write-code problems. We investigated when, why, and how students used the Parsons problems as well as their perceptions of the benefits and challenges. A think-aloud observational study with 11 undergraduate students showed that students utilized the Parsons problem before writing a solution to get ideas about where to start; during writing a solution when they were stuck; and after writing a solution to debug errors and look for better strategies. Semi-structured interviews with the same 11 undergraduate students provided evidence that using Parsons problems to scaffold write-code problems helped students to reduce the difficulty, reduce the problem completion time, learn problem-solving strategies, and refine their programming knowledge. However, some students found them less useful if the Parsons solution did not match their approach or if they did not understand the solution. We then conducted a between-subjects classroom study with 81 undergraduate students to investigate the effects on learning. We found that students who received Parsons problems as scaffolding during write-code problems spent significantly less time solving those problems. However, there was no significant learning gain in either condition from pretest to posttest. We also discuss the design implications of our findings.
more »
« less
- Award ID(s):
- 2143028
- PAR ID:
- 10432947
- Date Published:
- Journal Name:
- Proceedings of the 2022 ACM Conference on International Computing Education Research
- Volume:
- 1
- Page Range / eLocation ID:
- 15 to 26
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Novice programmers struggle with writing code from scratch. One possible way to help them is by using an equivalent Parsons problem on demand, where learners place mixed-up code blocks in the correct order. In a classroom study with 89 undergraduate students, we examined how using a Parsons problem as scaffolding impacts performance and problem-solving efficiency. Results showed that students in the Parsons as Help group achieved significantly higher practice performance and problem-solving efficiency than students who wrote code without help, while achieving the same level of posttest scores. These results improve the understanding of Parsons problems and contribute to the design of future coding practices.more » « less
-
Many students struggle with decomposition and planning despite the necessity of these skills in computing education. Hence, more tools are needed to scaffold these processes. In this paper, we present Jigsaw, a standalone visual planning tool to help students practice decomposition and planning before writing code. Jigsaw allows students to compose a solution to a new problem based on previously seen “patterns,” such as the accumulator pattern for summing values or the filter pattern for conditional input selection. Students can connect these patterns together to see how data flows between them and define a solution plan. Jigsaw’s goal is to scaffold students’ planning processes by presenting relevant patterns for a given problem. Using a within-subjects design, we evaluated Jigsaw by observing 17 undergraduate students as they planned for and implemented two programming assignments. The experimental task included Jigsaw, and the control task did not. This design aimed to understand how the tool impacted students’ planning and programming process. Subsequently, we conducted interviews with these students regarding their planning and programming experiences with and without Jigsaw. Many students explicitly mentioned they would employ Jigsaw for planning and appreciated the scaffolding it provided. Students also admired the Jigsaw’s novelty in visualizing programming problems. We conclude with our design takeaways and recommendations for future work.more » « less
-
Novice programmers need to write basic code as part of the learning process, but they often face difficulties. To assist struggling students, we recently implemented personalized Parsons problems, which are code puzzles where students arrange blocks of code to solve them, as pop-up scaffolding. Students found them to be more engaging and preferred them for learning, instead of simply receiving the correct answer, such as the response they might get from generative AI tools like ChatGPT. However, a drawback of using Parsons problems as scaffolding is that students may be able to put the code blocks in the correct order without fully understanding the rationale of the correct solution. As a result, the learning benefits of scaffolding are compromised. Can we improve the understanding of personalized Parsons scaffolding by providing textual code explanations? In this poster, we propose a design that incorporates multiple levels of textual explanations for the Parsons problems. This design will be used for future technical evaluations and classroom experiments. These experiments will explore the effectiveness of adding textual explanations to Parsons problems to improve instructional benefits.more » « less
-
Background and Context. The importance of CS to 21st-century life and work has made it important to find ways to integrate learning CS and programming into the regular school day. However, learning CS is difficult, so teachers integrating programming need effective strategies to scaffold the learning. In this study, we analyze students’ log data and apply a novel technique to compare Parsons Problems with from-scratch programming in a middle school science class. Objectives. Our research questions aimed to investigate whether, how, and when Parsons Problems improve learning efficiency for a programming exercise within science, utilizing log data analysis and an automated progress detector (SPD). Method. We conducted a study on 199 students in a 6th-grade science course, divided into two groups: one engaged with Parsons problems, and the other, a control group, worked on the same programming task without scaffolding. Then, we analyzed differences in performance and coding characteristics between the groups. We also adopted an innovative application of SPD to gain a better understanding of how and when Parsons problems helped students make more progress on the coding task, with an objective measure of final student grades. Findings. The experimental group, with scaffolding through Parsons Problems, achieved significantly higher grades, spent significantly less time programming, and toggled less between block category tabs. Interestingly, they ran their code more frequently compared to the control group. The SPD analysis revealed that the experimental group made significantly higher progress in all four quartiles of their coding time. Implications. Our findings suggest that Parsons problems can improve learning efficiency by enhancing novices’ learning experience without negatively impacting their performance or grades, which is especially important when programming is integrated into K12 courses.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3501385.3543977
