Hackathons bring developers, artists and designers together around a shared challenge: ideate, plan and create an application in a highly constrained time frame. A way to socialize, solve problems, and strengthen soft and hard skills, hackathons have grown tremendously in popularity in the last half decade. Despite this growth, it has been noted that females do not participate in hackathons with the same frequency as males. Some theorize that the hackathon culture is intimidating, does not appeal to women, or that it acts to amplify pre-existing cultural biases in computing. In this paper we introduce an alternative format for hackathons to address these issues. Think Global Hack Local (TGHL) is a non-competitive, communitybased hackathon that connects non-profit organizations with student developers. Students donate a weekend to solve problems that these organizations otherwise lack the resources to solve. To date, there have been two TGHL hackathons, and we have observed many interesting divergences within the culture of TGHL in comparison to other hackathons. Response has been positive, and nearly all of them indicate that they would do it again. By adopting some of these ideas, we believe that hackathons can become an environment that is more inclusive and fun for all.
The variables that researchers measure and how they measure them are central in any area of research. Which research questions can be asked and how they are answered depends on measurement. This paper describes a systematic review of the literature in computing education research to summarize the commonly used variables and measurements in 197 papers and to compare them to best practices in measurement for human-subjects research. Characteristics of the literature that are examined in the review include variables measured (including learner characteristics), measurements used, and type of data analysis. The review illuminates common practices related to each of these characteristics and their interactions with other characteristics. The paper lists standardized measurements that were used in the literature and highlights commonly used variables for which no standardized measures exist. To conclude, this review compares common practice in computing education to best practices in human-subjects research to make recommendations for increasing rigor.
A lack of diversity in the computing field has now existed for several decades, and while female participation in computing remains low, outreach programs attempting to address the situation are now quite numerous. To begin to understand whether or not these past activities have had long-term impact, we conducted a systematic literature review. Upon discovering that longitudinal studies were lacking, we investigated whether undergraduate students believed that their participation in computing activities prior to college contributed to their decision to major in a computing field. From the 770 participants in the study, we discovered that approximately 20% of males and 24% of females who were required to participate in computing activities chose a computing or related major, but that males perceived that the activity had a greater affect on their decision (20%) than females (6.9%). Females who participated in an outreach activity were more likely to major in computing. Female respondents who did not major in computing in college were less likely than those females who did to indicate that a majority of students participating in pre-college computing activities were boys and that they were a welcome part of the groups participating in the activities. Results also showed that female participants who do not ultimately major in computing have a much stronger negative perception of the outreach activities than male participants who also chose a non-computing major. Although many computing outreach activities are designed to diversify computing, it may be the case that overall boys receive these activities more favorably than girls, although requiring participation yields approximately the same net positive impact.
Background: Programming a computer is an increasingly valuable skill, but dropout and failure rates in introductory programming courses are regularly as high as 50%. Like many fields, programming requires students to learn complex problem-solving procedures from instructors who tend to have tacit knowledge about low-level procedures that they have automatized. The subgoal learning framework has been used in programming and other fields to breakdown procedural problem solving into smaller pieces that novices can grasp more easily, but it has only been used in shortterm interventions. In this study, the subgoal learning framework was implemented throughout a semester-long introductory programming course to explore its longitudinal effects. Of 265 students in multiple sections of the course, half received subgoal-oriented instruction while the other half received typical instruction. Results: Learning subgoals consistently improved performance on quizzes, which were formative and given within a week of learning a new procedure, but not on exams, which were summative. While exam performance was not statistically better, the subgoal group had lower variance in exam scores and fewer students dropped or failed the course than in the control group. To better understand the learning process, we examined students' responses to open-ended questions that asked them to explain the problem-solving process. Furthermore, we explored characteristics of learners to determine how subgoal learning affected students at risk of dropout or failure. Conclusions: Students in an introductory programming course performed better on initial assessments when they received instructions that used our intervention, subgoal labels. Though the students did not perform better than the control group on exams on average, they were less likely to get failing grades or to drop the course. Overall, subgoal labels seemed especially effective for students who might otherwise struggle to pass or complete the course.
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