TY - GEN
T1 - What Factors Influence Intrinsic Motivation and Test Anxiety Scores for Upper Second Level CS Students
AU - Nolan, Karen
AU - Quille, Keith
AU - Faherty, Roisin
AU - Nolan, Keith
AU - Farrell, Amanda O.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - Understanding how intrinsic motivation (IM) and test anxiety (TA) vary among students is critical for supporting self-regulated learning in constructivist Computer Science (CS) education; however, there is limited empirical evidence on how these factors differ across demographic, academic, and lifestyle contexts in Leaving Certificate Computer Science (LCCS). This study examines patterns of association between IM and TA, and a range of student-related factors, in an Irish upper-second-level CS context. Data were collected across 94 national outreach sessions (2020–2022), yielding 734 valid responses, with selected items drawn from the Motivated Strategies for Learning Questionnaire (MSLQ). Descriptive analysis showed high IM (M = 3.93, SD = 0.58) and moderate, variable TA (M = 3.33, SD = 0.89). Statistical analyses identified significant associations between IM and TA scores and factors including gender, prior CS experience, mathematics level and achievement, science subject choice, social media use, and teacher gender, with small-to-moderate effect sizes. Additional interaction analyses demonstrated that IM and TA vary across combinations of factors, particularly mathematics level, school gender, and science pathways, as well as lifestyle patterns involving gaming and social media. These findings suggest that IM and TA are associated with a range of intersecting demographic, academic, and lifestyle characteristics. However, as the analysis is correlational, the results indicate associations rather than cause-and-effect relationships. The results contribute to CS education research by highlighting patterns that may inform the design of targeted supports to sustain motivation and reduce anxiety in constructivist learning environments such as Leaving Certificate Computer Science.
AB - Understanding how intrinsic motivation (IM) and test anxiety (TA) vary among students is critical for supporting self-regulated learning in constructivist Computer Science (CS) education; however, there is limited empirical evidence on how these factors differ across demographic, academic, and lifestyle contexts in Leaving Certificate Computer Science (LCCS). This study examines patterns of association between IM and TA, and a range of student-related factors, in an Irish upper-second-level CS context. Data were collected across 94 national outreach sessions (2020–2022), yielding 734 valid responses, with selected items drawn from the Motivated Strategies for Learning Questionnaire (MSLQ). Descriptive analysis showed high IM (M = 3.93, SD = 0.58) and moderate, variable TA (M = 3.33, SD = 0.89). Statistical analyses identified significant associations between IM and TA scores and factors including gender, prior CS experience, mathematics level and achievement, science subject choice, social media use, and teacher gender, with small-to-moderate effect sizes. Additional interaction analyses demonstrated that IM and TA vary across combinations of factors, particularly mathematics level, school gender, and science pathways, as well as lifestyle patterns involving gaming and social media. These findings suggest that IM and TA are associated with a range of intersecting demographic, academic, and lifestyle characteristics. However, as the analysis is correlational, the results indicate associations rather than cause-and-effect relationships. The results contribute to CS education research by highlighting patterns that may inform the design of targeted supports to sustain motivation and reduce anxiety in constructivist learning environments such as Leaving Certificate Computer Science.
KW - Computer science education
KW - Constructivist learning
KW - Intrinsic motivation
KW - MSLQ
KW - Outreach
KW - Second-level education
KW - Self-regulated learning
KW - Student factors
KW - Test anxiety
UR - https://www.scopus.com/pages/publications/105051733530
U2 - 10.1007/978-3-032-31755-1_26
DO - 10.1007/978-3-032-31755-1_26
M3 - Conference contribution
AN - SCOPUS:105051733530
SN - 9783032317544
T3 - Lecture Notes in Networks and Systems
SP - 383
EP - 405
BT - Intelligent Computing - Proceedings of the 2026 Computing Conference
A2 - Arai, Kohei
A2 - Lorenz, Pascal
PB - Springer Science and Business Media Deutschland GmbH
T2 - 14th Computing Conference, CC 2026
Y2 - 9 July 2026 through 10 July 2026
ER -