Overcoming Illusionary Difficulty in Novice Programming through Metacognitive Skill Enhancement

This paper investigates the illusionary difficulty novice programmers face, where students struggle with new tasks despite feeling well-prepared. The study explicitly shows that traditional assessments, such as self-reports, often fail to identify the misconceptions underlying this challenge. Using Veenman's metacognitive cueing with scaffolded self-check questions, we help students -- without introducing additional materials -- to refocus from their current understanding to uncovering unconscious knowledge gaps. This approach encourages students to step out of their comfort zones, engage in deeper self-exploration, persist through real difficulties, accommodate new concepts, and resolve misconceptions in their grasp. Pilot experiments reveal that while students initially overestimate their understanding, applying this cueing approach during test preparation significantly improves their actual test performance, as opposed to cumulative performance that relies on feedback and reinforcement through practices. The results underscore the importance of addressing misconceptions in problem-solving training using non-identical cues (as opposed to code evaluation training, which follows a predetermined solution path) to foster long-term self-efficacy, even if it temporarily reduces self-esteem.

Authors

Institutions

Publication Details

Published
2025-02-18
DOI
https://doi.org/10.1145/3641555.3705230
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

Overcoming Illusionary Difficulty in Novice Programming through Metacognitive Skill Enhancement

Jie Wu, Zhenyu Jiang, Nora Jiang
Teaching and Learning Programming
article

Overcoming Illusionary Difficulty in Novice Programming through Metacognitive Skill Enhancement

Jie Wu, Zhenyu Jiang, Nora Jiang
article en

Abstract

This paper investigates the illusionary difficulty novice programmers face, where students struggle with new tasks despite feeling well-prepared. The study explicitly shows that traditional assessments, such as self-reports, often fail to identify the misconceptions underlying this challenge. Using Veenman's metacognitive cueing with scaffolded self-check questions, we help students -- without introducing additional materials -- to refocus from their current understanding to uncovering unconscious knowledge gaps. This approach encourages students to step out of their comfort zones, engage in deeper self-exploration, persist through real difficulties, accommodate new concepts, and resolve misconceptions in their grasp. Pilot experiments reveal that while students initially overestimate their understanding, applying this cueing approach during test preparation significantly improves their actual test performance, as opposed to cumulative performance that relies on feedback and reinforcement through practices. The results underscore the importance of addressing misconceptions in problem-solving training using non-identical cues (as opposed to code evaluation training, which follows a predetermined solution path) to foster long-term self-efficacy, even if it temporarily reduces self-esteem.

Swarthmore College (US), West Chester University (US), Temple University (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.