Distractors Make You Pay Attention: Investigating the Learning Outcomes of Including Distractor Blocks in Parsons Problems
\textbf{Background:} In CS1 courses, Parsons problems are a popular activity in which students are given blocks of code and asked to rearrange them into the correct order. Parsons problems often include incorrect blocks of code referred to as distractor blocks. Despite their widespread use, there have been few investigations into how distractor blocks impact student learning.
\textbf{Objectives:} Our goals are to understand (1) the impact that including distractor blocks in Parsons problems has on learning and (2) the causality underlying that learning, if any.
\textbf{Methods:} In this paper, we present the results of an explanatory sequential mixed methods study investigating the impact of distractor blocks on student learning. For the initial, quantitative stage, we use a randomized control trial to quantify the learning gains from practice with Parsons problems that include distractor blocks, as measured via post test taken immediately after the practice activity and a retention test taken a week later. This study is followed by think-aloud interviews with 10 students practicing using a mix of Parsons problems that do and do not contain distractors to understand differences in how students approach those problems.
\textbf{Findings:} Our findings show that students who practiced using Parsons problems that contained distractors performed 11 percentage points better on the immediate post-test (statistically significant) and 10 percentage points better on the retention test (marginally insignificant). The results of the think-aloud interviews indicate that grouping blocks of correct code with distractors causes students to more closely attend to the details of the code within those blocks.
\textbf{Implications:} The results of this study indicate that distractors are essential when Parsons problems are used in a formative context. When they are not included, students may be able to successfully place blocks of code without attending to details of the code. This in turn limits their ability to learn new concepts or reinforce existing knowledge from those code blocks.
Tue 13 AugDisplayed time zone: Brisbane change
16:20 - 17:00 | Interactive Learning ChallengesResearch Papers Chair(s): Carol Fletcher Texas Advanced Computing Center | ||
16:20 20mTalk | Probeable Problems for Beginner-level Programming-with-AI Contests Research Papers Mrigank Pawagi Indian Institute of Science, Bengaluru, Viraj Kumar Indian Institute of Science, India Pre-print | ||
16:40 20mTalk | Distractors Make You Pay Attention: Investigating the Learning Outcomes of Including Distractor Blocks in Parsons Problems Research Papers David Smith University of Illinois at Urbana-Champaign, Seth Poulsen University of Illinois at Urbana-Champaign, Chinny Emeka University of Illinois at Urbana-Champaign, Zihan Wu University of Michigan, Carl Haynes-Magyar Carnegie Mellon University, Craig Zilles University of Illinois at Urbana-Champaign |