Implicit intelligence beliefs of computer science students: Exploring change across the semester

Abstract

This study investigated introductory computer science (CS1) students' implicit beliefs of intelligence. Referencing Dweck and Leggett's (1988) framework for implicit beliefs of intelligence, we examined how (1) students' implicit beliefs changed over the course of a semester, (2) these changes differed as a function of course enrollment and students' motivated self-regulated engagement profile, and (3) implicit beliefs predicted student learning based on standardized course grades and performance on a computational thinking knowledge test. For all students, there were significant increases in entity beliefs and significant decreases in incremental beliefs across the semester. However, examination of effect sizes suggests that significant findings for change across time were driven by changes in specific subpopulations of students. Moreover, results showed that students endorsed incremental belief more strongly than entity belief at both the beginning and end of the semester. Furthermore, the magnitude of changes differed based on students' motivated self-regulated engagement profiles. Additionally, students' achievement outcomes were weakly predicted by their implicit beliefs of intelligence. Finally, results showed that the relationship between changes in implicit intelligence beliefs and student achievement varied across different CS1 courses. Theoretical implications for implicit intelligence beliefs and recommendations for STEM educators are discussed.

A Growth Mind-Set Intervention Improves Interest but Not Academic Performance in the Field of Computer Science

“…Although in the current work students report relatively strong growth mindset to start, this may not be the case at STEM-focused universities and we do see their growth mindsets decline from pretest to posttest. This is similar to recent work on implicit theories of intelligence that found theories become more entity-oriented across the semester in a sample of introductory computer science students (Flanigan, Peteranetz, Shell, & Soh, 2017). In summary, future work seeking to increase the interest and continuation of students in STEM might benefit from transforming not only individual students’ mindsets but also shifting learning environments to growth-oriented ones.…”

Implicit theories of intelligence in STEM education: perspectives through the lens of technology education students

“…While the importance of educators understanding student's implicit theories about intelligence concerning entity and incremental beliefs is acknowledged (Flanigan et al 2017), it is also of paramount importance for educators to understand what students perceive to be intelligent behaviour. A misalignment between student and teacher expectations has the potential to elicit many negative educational implications and therefore the knowledge of student beliefs can support the development of mutual understandings.…”

“…Specifically within Science, Technology, Engineering and Mathematics (STEM) disciplines, Dai and Cromley (2014) elucidate the importance of students' developing and maintaining incremental beliefs towards their abilities. Critically, the adaptive nature of these implicit beliefs has been illuminated (Flanigan et al 2017;Shively and Ryan 2013) identifying the capacity for pragmatic attempts to positively affect educational change.…”

Knowledge or Abilities? How Undergraduates Define Intelligence

“…Some studies using the mindset scale with college students have reported some validity evidence, such as indicators of the measure's internal structure (e.g., Cronbach's alpha, omega-total, and factor analyses) and test-retest reliability (Burkley et al, 2010(Burkley et al, , 2017Dai and Cromley, 2014;Scott and Ghinea, 2014;Smiley et al, 2016;Flanigan et al, 2017). An important component of validity that has yet to be assessed with the mindset scale is response process validity, which means that respondents engage in a common set of cognitive processes when responding to the items (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 2014; Bandalos, 2018).…”