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Title Multi-Institutional Multi-National Studies of Parsons Problems
Authors Barbara J. Ericson, Janice L. Pearce, Susan H. Rodger, Andrew Csizmadia, Rita Garcia, Francisco Gutierrez, Konstantinos Liaskos, Aadarsh Padiyath, Michael J. Scott, David H. Smith, Jayakrishnan Warriem, Angela Zavaleta Bernuy
Publication date 2023
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.
\n\n
A 2022 ITiCSE Parsons Problems Working Group conducted an extensive
literature review of Parsons problems,
designed several experimental studies for Parsons problems in Python, and
created `study-in-a-box' materials to help instructors run the experimental
studies, but the 2022 working group had only sufficient time to pilot two of
these studies.
\n\n
Our 2023 ITiCSE Parsons Problems Working Group reviewed these studies,
revised some of the studies, expanded both the programming and natural
languages used in some of the studies, created new studies, conducted
think-aloud observations on some of the studies, and ran both revised as
well as new experimental studies. The think-aloud observations and
experimental studies provide evidence for using Parsons problems to help
students learn common algorithms such as swap, and the usefulness of
distractors in helping students learn to recognize, fix, and avoid common
errors. In addition, our 2023 ITiCSE Parsons Problems Working Group reviewed
Parsons problem papers published after the 2022 literature review and
provided a literature review of multi-national (MIMN) studies conducted in
computer science education to better understand the motivations and
challenges in performing such MIMN studies.
\n\n
In summary, this article contributes an analysis of recent Parsons problem
research papers, an itemization of considerations for MIMN studies, the
results from our MIMN studies of Parsons problems, and a discussion of
recent and future directions for MIMN studies of Parsons problems and more
generally.
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Pages 57-107
Conference name ACM Conference on Innovation and Technology in Computer Science Education
Publisher ACM Press (New York, NY, USA)
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