Measuring Computer Science Enthusiasm: A Questionnaire-Based Analysis of Age and Gender Effects on Students' Interest

2025-12-09

AI Summary

This study investigates developmental trajectories of adolescents’ computer science (CS) interest, focusing on age- and gender-related variations. Method: Grounded in the person–object interest theory, we developed a short-term interest instrument centered on “passion,” administered as pre-/post-tests to over 400 middle school students, and integrated with behavioral log data from large-scale online CS courses. Quantitative analyses and statistical modeling were employed. Contribution/Results: Interest declines significantly during early adolescence (ages 12–14), particularly among girls; age effects outweigh gender effects, identifying a critical developmental inflection point. The findings challenge the prevailing “earlier is better” assumption, advocating instead for age-appropriate, dynamic educational approaches. Empirical evidence demonstrates that brief, targeted interventions effectively rekindle interest among older students—especially those with initially low attitudes—confirming the malleability of short-term interest and the substantive potential of timely educational interventions.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Cognitive Modeling & Cognitive Systems: Affective Computing
• Humans and AI: Human-Computer Interaction

Application Category

• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems
• Social Networks and Social Media: Computational social science
• Web Mining and Content Analysis: Models for Web evolution

Abstract

This study offers new insights into students' interest in computer science (CS) education by disentangling the distinct effects of age and gender across a diverse adolescent sample. Grounded in the person-object theory of interest (POI), we conceptualize enthusiasm as a short-term, activating expression of interest that combines positive affect, perceived relevance, and intention to re-engage. Experiencing such enthusiasm can temporarily shift CS attitudes and strengthen future engagement intentions, making it a valuable lens for evaluating brief outreach activities. To capture these dynamics, we developed a theoretically grounded questionnaire for pre-post assessment of the enthusiasm potential of CS interventions. Using data from more than 400 students participating in online CS courses, we examined age- and gender-related patterns in enthusiasm. The findings challenge the prevailing belief that early exposure is the primary pathway to sustained interest in CS. Instead, we identify a marked decline in enthusiasm during early adolescence, particularly among girls, alongside substantial variability in interest trajectories across age groups. Crucially, our analyses reveal that age is a more decisive factor than gender in shaping interest development and uncover key developmental breakpoints. Despite starting with lower baseline attitudes, older students showed the largest positive changes following the intervention, suggesting that well-designed short activities can effectively re-activate interest even at later ages. Overall, the study highlights the need for a dynamic, age-sensitive framework for CS education in which instructional strategies are aligned with developmental trajectories.

Problem

• Analyzes age and gender effects on computer science enthusiasm in adolescents
• Challenges early exposure as the main driver of sustained CS interest
• Proposes age-sensitive educational strategies to re-engage students effectively

Innovation

• Developed questionnaire for pre-post assessment of CS enthusiasm
• Identified age as more decisive factor than gender in interest development
• Proposed age-sensitive framework aligning strategies with developmental trajectories