Multi-Institutional Multi-National Studies of Parsons Problems

Ericson, Barbara J.; Pearce, Janice L.; Rodger, Susan H.; Csizmadia, Andrew; Garcia, Rita; Gutierrez, Francisco J.; GUTIERREZ-FERRER, FRANCISCO JAVIER; Liaskos, Konstantinos; Padiyath, Aadarsh; Scott, Michael James; Smith, David H.; Warriem, Jayakrishnan M.; Bernuy, Angela Zavaleta; ACM

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.

Más información

Título según WOS: Multi-Institutional Multi-National Studies of Parsons Problems
Título según SCOPUS: ID SCOPUS_ID:85182937766 Not found in local SCOPUS DB
Título de la Revista: Proceedings of the 2023 Working Group Reports on Innovation and Technology in Computer Science Education
Editorial: ACM Press
Fecha de publicación: 2023
Página de inicio: 57
Página final: 107
DOI:

10.1145/3623762.3633498

Notas: ISI, SCOPUS