Exploring domain-general and course-specific latent profiles of motivation in computer science

IF 9 1区心理学 Q1 PSYCHOLOGY, EDUCATIONAL

Learning and Individual Differences Pub Date : 2025-04-03 DOI:10.1016/j.lindif.2025.102686

Hye Rin Lee , Sanford R. Student , Teomara Rutherford , Rebecca J. Collie , Austin C. Bart

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引用次数: 0

Abstract

Although achievement motivation theories like the Situated Expectancy–Value Theory highlight domain-general and course-specific motivation, few studies have examined students' motivational beliefs at both levels. This study explores domain-general and course-specific motivational profiles in undergraduate computer science (CS) courses, focusing on expectancy for success, values, and belonging. Using latent profile analysis, we identified four domain-level profiles and five course-level profiles, with the profiles representing different combinations of positive motivation and cost. We examined how these profiles evolved during the semester, finding via latent transition analysis that domain-general motivations appear to be more stable over time. Additionally, gender differences in profile membership showed women and other non-men often in higher cost profiles compared to men, and there was more variability in mean grades across course profiles than across CS domain profiles. These findings enhance our understanding of how combinations of motivational beliefs can influence student engagement and performance.

Educational Relevance and Implications Statement

Our study explored the motivational profiles of undergraduate computer science (CS) students, revealing that these profiles vary by domain and course and change from the beginning to the end of the semester. We found that domain-general motivational beliefs, which encompass general attitudes toward the field of CS, remain more stable over time compared to course-specific motivational beliefs, which reflect specific attitudes toward individual CS courses. The stability of domain-general motivational beliefs suggest that foundational attitudes formed early could influence long-term engagement with CS, emphasizing the need for early interventions. We also found gender differences in motivational profiles; women and other non-men were more likely to be in high-cost profiles compared to men. The gender disparities in perceived costs highlight the necessity for tailored support that addresses the unique challenges faced by women and other non-men in the field. Additionally, course grades varied more by course-specific motivational beliefs than domain-general motivational beliefs, underscoring the importance of how students perceive their CS courses for their achievement. Educators can utilize this information to create more inclusive and effective educational environments that cater to the diverse needs of all students, ultimately improving retention and performance in CS programs.

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探索计算机科学中一般领域和特定课程动机的潜在特征

尽管成就动机理论（如情境期望价值理论）强调了领域一般动机和课程特定动机，但很少有研究在这两个层面上考察学生的动机信念。本研究探讨了本科计算机科学（CS）课程中一般领域和特定课程的动机概况，重点关注对成功、价值观和归属感的期望。利用潜在剖面分析，我们确定了4个领域层次的剖面和5个课程层次的剖面，这些剖面代表了积极动机和成本的不同组合。我们研究了这些概况在学期中是如何演变的，通过潜在的转变分析发现，随着时间的推移，领域一般动机似乎更加稳定。此外，性别差异表明，与男性相比，女性和其他非男性通常在更高的成本概况中，并且不同课程概况的平均成绩差异大于CS领域概况。这些发现增强了我们对动机信念组合如何影响学生参与和表现的理解。教育相关性和启示声明我们的研究探讨了计算机科学（CS）本科生的动机概况，揭示了这些概况因领域和课程而异，并且从学期开始到结束都有所变化。我们发现，与特定课程的动机信念相比，包含对计算机科学领域的一般态度的领域通用动机信念随着时间的推移保持更稳定，而特定课程的动机信念反映了对单个计算机科学课程的特定态度。领域一般动机信念的稳定性表明，早期形成的基本态度可能会影响CS的长期参与，这强调了早期干预的必要性。我们还发现了动机方面的性别差异；与男性相比，女性和其他非男性更有可能处于高成本状态。感知成本方面的性别差异突出表明，有必要提供有针对性的支助，解决妇女和其他非男子在实地面临的独特挑战。此外，课程成绩因课程特定的动机信念而异，而非领域一般的动机信念，这强调了学生如何看待他们的CS课程对他们的成就的重要性。教育工作者可以利用这些信息来创造更具包容性和更有效的教育环境，以满足所有学生的不同需求，最终提高计算机科学课程的保留率和表现。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Learning and Individual Differences PSYCHOLOGY, EDUCATIONAL-

CiteScore

6.60

自引率

2.80%

发文量

期刊介绍： Learning and Individual Differences is a research journal devoted to publishing articles of individual differences as they relate to learning within an educational context. The Journal focuses on original empirical studies of high theoretical and methodological rigor that that make a substantial scientific contribution. Learning and Individual Differences publishes original research. Manuscripts should be no longer than 7500 words of primary text (not including tables, figures, references).