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

Kai Marquardt, Robert Hanak, Anne Koziolek, Lucia Happe

TL;DR

This study investigates how age and gender shape adolescents' enthusiasm for computer science (CS) in short interventions. It introduces a POI-based questionnaire to capture brief, intervention-triggered shifts in positive affect, perceived relevance, and re-engagement intent, validated with pre-post data from over 400 students aged 10–18 across diverse settings. The results show age—as opposed to gender—drives most of the variability in CS interest trajectories, with a notable early-adolescence dip especially among girls, but older students exhibit larger post-intervention improvements. The findings support the need for dynamic, age-sensitive CS education and provide a robust instrument for assessing the enthusiasm potential of CS interventions.

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.

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

TL;DR

This study investigates how age and gender shape adolescents' enthusiasm for computer science (CS) in short interventions. It introduces a POI-based questionnaire to capture brief, intervention-triggered shifts in positive affect, perceived relevance, and re-engagement intent, validated with pre-post data from over 400 students aged 10–18 across diverse settings. The results show age—as opposed to gender—drives most of the variability in CS interest trajectories, with a notable early-adolescence dip especially among girls, but older students exhibit larger post-intervention improvements. The findings support the need for dynamic, age-sensitive CS education and provide a robust instrument for assessing the enthusiasm potential of CS interventions.

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.

Paper Structure

This paper contains 5 sections, 3 figures, 7 tables.

Table of Contents

  1. Stage 1 & 2: Questionnaire Development
  2. Stage 3: Data Collection
  3. Stage 4: Analysis
  4. Ethical Compliance and Consent to Participate
  5. Final Questionnaire

Figures (3)

  • Figure 1: Schematical overview of research procedure.
  • Figure 2: Plots of mean values of girls' (red) and boys' (blue) responses in the pre-test (T1) to the self-efficacy item and summarized for items related to one of the three dimensions of interest. The colored area illustrates standard derivation.
  • Figure 3: Mean differences between pre-test and post-test with 95%-CI (y-axis) for items related to one of the three dimensions of interest as well as self-efficacy by age groups (AGs, x-axis).