Scaffolding Code Writing with Parsons Problems: Understanding Efficacy Levels

The article discusses the effects of using Parsons problems to scaffold code writing for students with varying levels of computer science (CS) self-efficacy. The study aimed to investigate whether adding explanations to Parsons blocks or the finished solutions can improve students’ effective scaffolding rate, which is a measure of how well the scaffolding supports students in completing the coding task.
The researchers found that students with higher CS self-efficacy levels benefited more from using Parsons problems than those with lower self-efficacy levels. The study also revealed that adding explanations to the hints and solutions improved the relevance and understandability of the scaffolding, which in turn improved the students’ effective scaffolding rate.
The study used a mixed-methods approach, including surveys and interviews, to gather data on the students’ experiences with Parsons problems. The findings suggest that providing explanations for the hints and solutions can help students understand how to apply the concepts they have learned in class to real-world coding situations.
The article highlights the importance of tailoring scaffolding strategies to students’ individual needs and abilities, rather than using a one-size-fits-all approach. The researchers argue that by paying attention to these factors, educators can create a more supportive learning environment that helps students build their confidence and improve their coding skills.
In summary, the article demonstrates that adding explanations to Parsons problems can enhance the effectiveness of scaffolding in computer science education, particularly for students with lower self-efficacy levels. The findings suggest that tailoring scaffolding strategies to individual students’ needs and abilities is crucial for promoting their learning and success in coding tasks.