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Multi-Institutional Multi-National Studies of Parsons Problems

Barbara Ericson, Janice L. Pearce, Susan H. Rodger, Andrew Csizmadia, Rita Garcia, Francisco J. Gutiérrez, Κωνσταντίνος Λιάσκος, Aadarsh Padiyath, Michael Scott, David H. Smith, Jayakrishnan Madathil Warriem, Angela Zavaleta Bernuy

202311 citationsDOI

Abstract

Students are often asked to learn programming by writing code from scratch. However, many novices struggle to write code and get frustrated when their code does not work. Parsons problems can reduce the difficulty of a coding problem by providing mixed-up blocks the learner rearranges into the correct order. These mixed-up blocks can include distractor blocks that are not needed in a correct solution. Distractor blocks can include common errors, which may help students learn to recognize and fix such errors. Evidence suggests students find Parsons problems engaging, useful for learning to program, and typically easier and faster to solve than writing code from scratch, but with equivalent learning gains. Most research on Parsons problems prior to this work has been conducted at a single institution. This work addresses the need for replication across multiple contexts.

Topics & Concepts

Computer scienceScratchCoding (social sciences)Code (set theory)InstitutionPair programmingProgramming languageMathematics educationPsychologySoftwareSociologySoftware developmentSet (abstract data type)Social scienceTeaching and Learning ProgrammingExperimental Learning in EngineeringOnline Learning and Analytics
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