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Two studies investigated change in computer science (CS) students' implicit intelligence beliefs. Across both studies, we found that the strength of incremental and entity beliefs changed across time. In Study 1, we found that incremental beliefs decreased and entity beliefs increased across the semester. Change in implicit intelligence beliefs was similar for students taking introductory and upper-division courses. In Study 2, growth curve analysis revealed a small linear change in incremental beliefs across time but no change in entity beliefs--these trends were similar for students enrolled in introductory and upper-division CS courses. Across both studies, change in implicit intelligence beliefs was not associated with academic achievement in CS. Findings provide preliminary evidence that shifts in implicit intelligence beliefs occur as students progress through the CS curriculum. Finally, findings support that mindset interventions may be more effective if delivered at the beginning of the semester before shifts in beliefs occur.

Contribution: This article presents a synthesis of the findings and implications from the IC2Think program of research in undergraduate computer science (CS) courses examining student motivation and self-regulated learning (SRL). These studies illuminate both the difficulty and potential for motivating CS students, as well as the uniqueness of CS as a context for studying undergraduate motivation. Background: Computing disciplines are increasingly important in preparing the future workforce. It is imperative that CS educators understand how to motivate students and enhance student outcomes. Synthesizing findings across multiple studies allows for the emergence of new insights into student motivation and SRL. Research Questions: Which aspects of students' motivation and SRL are predictive of achievement and retention in CS and how can findings inform CS education? Methodology: The primary methodology is a comprehensive review of seven years of research on undergraduate CS education. Studies use a variety of analysis techniques, examine a range of constructs, and include multiple introductory and advanced CS courses. Studies of relationships between variables and change over time were conducted. Findings: The present synthesis of studies on motivation and SRL highlights the complex, counter-intuitive, and positive aspects of student motivation in CS.

Contribution: This paper provides evidence that computational creativity exercises (CCEs) can increase engineering students' learning in introductory computer science (CS1) courses. Its main contribution is its more rigorous treatment/control group research design that allows testing for causal influences of CCEs on student learning and performance. Background: Computer science (CS) courses are critical foundational courses for engineering students. CCEs that merge computational and creative thinking have been shown to increase achievement and learning of engineering and nonengineering students in CS1 courses, but previous research has used quasi- and non-experimental designs. Intended Outcomes: CCEs are intended to improve students' learning of CS1 content and problem-solving ability by fostering computational creativity. Application Design: CCEs can improve student learning and can be used to supplement other evidence-based instructional practices. Findings: Propensity score matching was used to create equivalent treatment and control groups; results show that students in the CCE implementation section had higher scores on a CS knowledge test than students in the control section, but not higher self-efficacy for their CS knowledge. Focus group and open-ended survey questions indicated that students had mixed reactions to the CCEs, with about half the students seeing them as improving their learning, understanding, and ability to apply CS in their engineering field. Responses also reinforced the importance of fully incorporating CCEs in courses and aligning them with course topics.

Computational thinking and creative thinking are valuable tools both within and outside of computer science (CS). The goal of the project discussed here is to increase students' achievement in CS courses through a series of computational creativity exercises (CCEs). In this paper, the framework of CCEs is described, and the results of two separate studies on their impact on student achievement are presented. Students in introductory CS courses completed CCEs as part of those courses. Students in Study 1 came from a variety of programs, and students in Study 2 were engineering majors. A profiling approach was used to test whether the impact of the CCEs could be accounted for by differences in students' motivated and self-regulated engagement. Overall, CCEs had positive impacts on students' grades and knowledge test scores, and although there were differences in achievement across the profiles, the impact of the CCEs was generally consistent across profiles. The CCEs appear to be a promising way to increase student achievement in introductory CS courses. Implications and directions for future research are discussed.

This research investigated the relationships among undergraduate computer science students’ computer-science-related career aspirations, perceived instrumentality (PI) for computer science courses, and achievement in those courses. Specifically, the two studies examined (a) change in PI and career aspirations during a single semester, (b) the relationship between change in career aspirations and change in PI, and (c) the influence of career aspirations, PI, and change in career aspirations and PI on achievement in computer science courses. Findings from both studies revealed that students experienced a decrease in endogenous PI and career aspirations and an increase in exogenous PI during the semester. Study 1 showed that non-computer science majors experienced greater shifts in PI and career aspirations than computer science majors. Study 2 showed that the change in PI happened in parallel and was curvilinear, with more change happening in the first half of the semester than the second half. Both studies also showed that computer-science-related career aspirations were associated with PI, and that aspirations and PI had a stronger relationship with scores on a computer science knowledge test than with course grades. Implications and directions for future research are discussed. [ABSTRACT FROM AUTHOR]