Longitudinal Associations of Field-specific Ability Beliefs among Undergraduate Computer Science Students

• In Event: Investigating Field-Specific Ability Beliefs: How Do They Matter and for Whom?

Abstract

Objectives and Theoretical Framework
Computer science programs face a number of motivational and psychological challenges impacting both student success and retention within these fields (Cheryan et al., 2017; Stephenson et al., 2018). Field-specific ability beliefs (FABs), beliefs that an individual must be naturally brilliant to be highly successful in a given field, have shown initial promise in explaining these outcomes as they are highly endorsed in the fields of computer science compared to other fields (Leslie et al., 2015; Meyer et al., 2015). Prior research has provided evidence of the negative consequences of these beliefs on individual students such as reduced self-efficacy, belonging, and higher evaluative concerns (Deiglmayr et al., 2019; Jenifer et al., 2024; Limeri et al., 2023). However, the majority of the work connecting FABs to motivational and psychological outcomes in real-world classroom settings has been cross-sectional, limiting our understanding of the directionality of these associations and the potential for reciprocal relationships. As such, the current study sought to explore the longitudinal relationships between students’ own, as well as students’ perceptions of others’, FABs and their motivation, psychological experiences, and retention intentions.

Methods and Data
We surveyed 570 undergraduate students majoring in computer science in a required, first-semester computer science course (18.4% women, transgender, and nonbinary students, 22.3% underrepresented racial/ethnic minority students) at the beginning, middle, and end of the semester. We used random intercept cross-lagged panel models (Mund & Nestler, 2019) to examine temporal within-person relationships between the variables controlling for initial scale responses. We examined the relationship between FABs (both students’ own FABs and their perceptions of others’ FABs) and students’ motivation (interest, self-efficacy, identity, goal orientations), psychological experiences (anxiety, belonging, evaluative concerns), and retention intentions.

Results
Students’ own FABs had reciprocal relationships with self-efficacy, performance avoidance goals, belonging, and retention intentions in expected directions. Similarly, students’ own FABs predicted higher evaluative concerns. Students’ interest, identity, and anxiety predicted their own FABs in expected directions. Students’ perceptions of others’ FABs had a positive reciprocal relationship with anxiety. Students’ perceptions of others’ FABs also predicted self-efficacy, mastery approach goals, performance avoidance goals, and evaluative concerns in expected directions. Students’ belonging negatively predicted their perceptions of others’ FABs. See Table 1 for all cross-lagged regression effects.

Significance
Our study provides unique longitudinal classroom-based evidence as to how field-specific ability beliefs may be associated with motivation, psychological experiences, and retention intentions among computer science students. In addition to understanding one-way associations with various outcomes, we provide evidence suggesting that some of these relationships may be reciprocal in which field-specific ability beliefs not only predict maladaptive outcomes, but that some outcomes (e.g., lower belonging, lower self-efficacy, higher anxiety) may strengthen FABs or perceptions of FABs in others. This evidence not only helps build the case for the importance of intervening on these beliefs in computer science but may also help inform an understanding of the psychological process by which FABs impact students (Muradoglu et al., 2023) as these theoretical models continue to be developed.
 

Authors

• Nathaniel Woznicki, New York University

• Sophie Arnold, New York University

• Aashna Poddar, New York University

• Bethany Lassetter, New York University

• Natalie Hutchins, University of Virginia

• Kenneth Joseph, University at Buffalo - SUNY

• Chris Proctor, University at Buffalo - SUNY

• Andrei Cimpian, New York University