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Contribution: This paper argues for a shift in how students’ team project experiences are assessed. Findings from this paper suggest that it is not enough to consider student-reported data in assessing team dynamics; hidden gendered behavior may be impacting students in ways that students do not realize or report. Background: Although the number of women in engineering is rising, difficulties still exist for female students in electrical engineering and computer science, particularly in team projects. Male and female students may have very different project experiences, due to differing levels of confidence/self-efficacy, difficult team dynamics, or inequitable task division. Research Questions: This paper aimed to elucidate what differences exist in the project experience between male and female students, considering self-reported measures (engineering confidence/self-efficacy, time spent on task, and team satisfaction) and observational study. Methodology: Students completed pre/post-project surveys, weekly logs, and post-project interviews to report and discuss their engineering confidence/self-efficacy, project task selection, and team satisfaction. This paper reports a case study of one student team, observed by a researcher throughout the project course. Findings: While student-reported data implied a lack of gender division (male and female students had the same levels of confidence, completed the same project tasks, and were similarly satisfied with their teams), the observational study implied that the student-reported data may not be telling the whole story. Given the difficult team dynamics observed in the student team (but not reported by students), findings suggest that difficult gender dynamics may go unrecognized by students. [ABSTRACT FROM AUTHOR]

Contribution: This paper employs the automatic scoring of short essays as a novel way to determine pre-service teachers’ knowledge of and attitudes toward computational thinking (CT) from their written reflections. Implications about designing CT courses for pre-service teachers are discussed. Background: CT is an essential 21st-century competency that supports the development of problem-solving skills. Inspired by computing science problem-solving practices, CT should transcend disciplines, but few universities or colleges include CT courses or CT content in their core courses. It is also difficult to know what pre-service teachers think about CT and their role in promoting it. Research Questions: Do pre-service teachers’ coding reflections reveal any important information about their knowledge of, skills in, and attitudes toward CT? Methodology: Traditional qualitative techniques based on human raters are impractical in analyzing hundreds of essays. Topic modeling, an unsupervised machine learning modeling technique, was employed to extract topical features from participants’ reflections. In one section of an undergraduate Introduction to Educational Technology course offered at a large university in Western Canada, n = 139 pre-service teachers wrote a short reflection on their experience following a 20 h Accelerated Intro to Computer Science Code.org course. Topics were identified by analyzing contextual trends in participants’ written reflections. Findings: Results showed that pre-service teachers’ reflections included CT concepts, practices, and perspectives. Specifically, participants connected the coding activity to prior knowledge and experiences. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Contribution: Active classroom programmer (ACP) is a software tool that places minimal pressure on resources, and is shown to help improve student learning while also encouraging a high degree of engagement both during and outside of programming lectures. Background: Programming is difficult for students, largely due to the myriad of ever-advancing concepts. As students gradually become stronger programmers, both within a course and within their degree, they are constantly presented with new and challenging programming concepts regardless of their expertise. While laboratory sessions provide an excellent opportunity for students to independently practice, this does not help them in the programming process where expert scaffolding is desired. Intended outcomes: ACP is intended to engage students with active programming exercises and develop an inductive approach to learning, focusing on developing problem-solving skills. Application design: Students need guidance in the programming strategy rather than the syntax and peculiarities of the particular programming language. ACP allows students to program alongside instructors as new concepts are introduced. Findings: Experience from two concept-rich programming courses at different levels is presented, demonstrating students engaged with ACP both inside and outside lectures to deepen their understanding of the programming concepts. [ABSTRACT FROM AUTHOR]