Pencil Puzzles as a Context in Upper-level Core Computing Courses at Multiple Institutions

Context-based assignments have been shown as effective and popular for introductory-level computing courses. We study the use of one such context, pencil puzzles (puzzles typically found in newspapers), in upper-level core computing courses. These puzzles are designed to inspire computational thinking, making them a great choice for introductory-level computing assignments, but their fit for upper-level courses is less clear. We collaborated with several instructors of upper-level courses at four institutions, who delivered a pencil-puzzle-based assignment in their course and allowed us to survey their students about their experience. Overall, the students indicated positive perceptions of the assignments. The most varied answers related to implementation aspects of the assignments. To analyze correlations between students' sentiments and their demographic and experiential background, we used mixed-effects regression modeling to analyze this heterogeneous data set. The survey responses were characterized by two dimensions, one roughly corresponding to students' sentiment about the assignment and the other to their technical assessment of the assignment. For the first dimension, we found that the students' self-reported level of preparedness from earlier courses positively correlated with their enjoyment of and satisfaction with the pencil puzzle assignment. The second dimension was correlated with both the level of preparedness as well as the students' self-reported problem solving type: Clarifier, Implementor, Ideator, and Developer. Somewhat surprisingly, the analysis indicated Ideator as being the most positively correlated with the technical aspects of the assignment. Notably, the analysis did not indicate any correlation with students' race or gender in either dimension.

Authors

Institutions

Publication Details

Published
2025-02-18
DOI
https://doi.org/10.1145/3641555.3705225
Primary Topic
Teaching and Learning Programming
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pencil Puzzles as a Context in Upper-level Core Computing Courses at Multiple Institutions

Ivona Bezáková, Zack Butler, Angelina Brilliantova, Asya Vitko
Teaching and Learning Programming
article

Pencil Puzzles as a Context in Upper-level Core Computing Courses at Multiple Institutions

Ivona Bezáková, Zack Butler, Angelina Brilliantova, Asya Vitko
article en

Abstract

Context-based assignments have been shown as effective and popular for introductory-level computing courses. We study the use of one such context, pencil puzzles (puzzles typically found in newspapers), in upper-level core computing courses. These puzzles are designed to inspire computational thinking, making them a great choice for introductory-level computing assignments, but their fit for upper-level courses is less clear. We collaborated with several instructors of upper-level courses at four institutions, who delivered a pencil-puzzle-based assignment in their course and allowed us to survey their students about their experience. Overall, the students indicated positive perceptions of the assignments. The most varied answers related to implementation aspects of the assignments. To analyze correlations between students' sentiments and their demographic and experiential background, we used mixed-effects regression modeling to analyze this heterogeneous data set. The survey responses were characterized by two dimensions, one roughly corresponding to students' sentiment about the assignment and the other to their technical assessment of the assignment. For the first dimension, we found that the students' self-reported level of preparedness from earlier courses positively correlated with their enjoyment of and satisfaction with the pencil puzzle assignment. The second dimension was correlated with both the level of preparedness as well as the students' self-reported problem solving type: Clarifier, Implementor, Ideator, and Developer. Somewhat surprisingly, the analysis indicated Ideator as being the most positively correlated with the technical aspects of the assignment. Notably, the analysis did not indicate any correlation with students' race or gender in either dimension.

Rochester Institute of Technology (US)
Quality Education
Openalex Percentile: Top 98%
Teaching and Learning Programming
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.