Gender, achievement, and persistence in an undergraduate computer science program

This study investigated whether student academic achievement in college computer science programs in Taiwan could be predicted by factors reported to be effective in U.S. studies. Subjects were 940 college students enrolled in five universities offering computer science programs. A correlation study was conducted and prediction models were established. The predictive powers of college entrance examination (CEE) scores in relation to subsequent college performance appeared to be limited. Overall high school achievement and math course averages were identified as effective performance predictors. The close relationship between performance in introductory computer science courses and performance in complete computer science programs was validated. Significant linear prediction models with limited predictive powers were generated for overall performance but not for introductory computer science course performance. Model predictive powers were significantly improved when performance in introductory computer science courses was included in the models. No significant gender differences were found for CEE performance. However, female subjects outperformed male counterparts in course performance at both the high school and college levels.

In a previous study, we investigated a framework for teaching abstraction in computer science (CS) in the context of an introductory CS course for 7th-grade students. The framework was found effective for developing CS abstraction skills. In this paper, we describe a study that investigated teaching abstraction in CS to 7th-grade students through the perspective of gender. Specifically, we compared the CS abstraction abilities of boys and girls taking the introductory CS course in 7th grade (using the Scratch environment). We also examined the difference in the effect of the teaching strategy on CS abstraction abilities between boys and girls. Our findings show a significant advantage of girls over boys regarding several aspects of CS abstraction. We also found that the framework for teaching CS abstraction, which was already established in our previous study as effective in the context of an introductory course for 7th-grade students, has an enhanced effect in this context when it comes to girls. This enhancement was manifested by a better overall performance by the girls, when comparing boys and girls that took an introductory CS course in which this framework was used. It was also manifested by the girls' deeper and more reliable perception of CS. We conjecture that this framework has the potential to affect girls' self-efficacy, and as a result to create a positive effect by encouraging and motivating girls to pursue CS education beyond this introductory course. That is, this framework has the potential to contribute to solving the issue of underrepresentation of females at the different stages of CS education, or in other words, to widening the CS pipeline for females.

The pipeline of three introductory computer science courses at our university have low pass rates. As part of our efforts to improve the pass rates in these courses, we examine the students' mathematics preparation and their progress from one course to the next. We find that the minority of students who enter the university with good mathematics preparation are likely to succeed in our introductory computer science courses. For the majority of students, we suggest a series of interventions throughout the pipeline. Prior to taking Computer Science 1, students could gain more experience with problem solving during the Introduction to Computer Science and Introduction to Computer Engineering courses. We suggest adding precalculus as a prerequisite for Computer Science 2. For students who do not earn an A in Computer Science 2, we plan to examine whether taking a class in a second programming language before taking Computer Science 3 will improve performance in Computer Science 3. Our goal is to improve student learning and retention through these efforts, combined with continual innovation in the classroom.

The number of computer science (CS) courses has been dramatically expanding in U.S. high schools (HS). In comparison with well-established courses in mathematics and science, little is known about how the decisions made by HS CS teachers regarding how and what to teach impact student performance later in introductory college CS courses. Drawing on a large sample of 2,871 introductory college CS students at 115 U.S. institutions who had taken a CS course in HS, we examined the topic coverage and prevailing instructional methods in the HS course and investigated how these experiences influenced student performance in college CS. Controlling for differences in student background, we find two predictors of higher grades in college CS: greater frequency of coding-related activities in HS (programming, debugging, studying algorithms) and lower frequency of “non-coding” computer use (e.g., data analysis, computer security). Interaction models revealed a more complex story. Coding-related activity more heavily benefited students who did not have coding help available at home. In the 28% of college CS courses in which instructors employed innovative pedagogies, students with higher ACT or SAT mathematics scores had a greater advantage than in traditionally taught courses. Finally, in the innovative college courses, students whose HS CS exams had typically included testing on vocabulary did worse than students whose exams had not included such tests.

Many colleges and universities offer an introductory computer science course based on a specific programming language. The Department of Computer Science at the University of Kansas has recently reorganized its introductory computer science course to include such topics as algorithms, top-down algorithmic design, elementary programming techniques, and introduction to time-sharing. Besides the discussion of this transition, the paper discusses a questionaire that was developed and utilized during this transition. It is hoped that others will benefit from our experiences.

Background Despite ongoing calls for prioritizing K-12 computer science (CS) education, an enduring gender gap exists. Objective We explored one high school CS program where female participation was consistently higher than state averages to better understand how the program was developed. Method Using a case study method, data were collected over three-months through interviews, observations, course documents, student reflections, and researcher reflections. Constant comparative analysis was employed to analyze data throughout and following data generation. Findings Recruitment and teacher support were key practices. Recruitment practices included letter writing campaigns and recruiting from introductory CS courses. Teacher support came from counselors, administrators, and other teachers. While the CS program was consistently more gender-inclusive, the focus when building the program had been on supporting all students, not only female students. Implications Recruitment should be active and purposeful, but using academic indicators for targeted recruitment campaigns can limit student exposure. Teachers need support for broadening participation, particularly from counselors and administrators, who must also be aware of what CS is and their role in these efforts. Opportunities for coteaching within CS programs can be beneficial for growth. Overall, broadening participation must be a holistic effort, supported by school-wide stakeholders, not only CS teachers.

This study examined the relationship between high school computer experience and university achievement in introductory computer science. Achievement was analyzed in terms of both the amount of high school computer science instruction and the degree of emphasis on structured programming in high school. A sample of 117 students in an introductory computer science course was pretested and all subsequent course examination scores were monitored. Neither amount of computer science nor emphasis on structured programming in high school had any measurable effect on university examination achievement. Students with less high school experience were more likely to withdraw from the university course.

It is common knowledge that enrollments in computer science have plummeted and educators are challenged to find ways to engage and promote success and retention of students while maintaining standards in introductory computer science courses. This study focuses on the implementation of a collaborative, modified peer-led team learning (PLTL) instructional approach in a large sized introductory computer science course. The site is a major southeastern university in the United States where all students are required to take one of three introductory computer science classes. The course version selected for this study specifically targets computer science majors and the study spans three years of data, and involves 591 students. Students who experienced the student-centered instruction and worked in small groups facilitated by a peer leader (treatment) in years 2006-07 and 2007-08 were compared with students who experienced a traditional recitation lecture section (control) in 2005-06. The content and the course owner was the same for all three years. Quantitative data analysis show marked and statistically significant improvements in student performance, for both male and female students. These findings suggest that using undergraduate leaders to implement a peer-led team learning model can be as effective in promoting achievement and retention in computer science education as it has shown to be in math and science classes over the past several years.

article A comparison of Ada and Pascal in an introductory computer science course Share on Authors: Jeanne L. Murtagh Software Professional Development Program, Air Force Institute of Technology, Wright-Patterson AFB, OH Software Professional Development Program, Air Force Institute of Technology, Wright-Patterson AFB, OHView Profile , John A. Hamilton D/Electrical Engineering & Computer Science, United States Military Academy, West Point, NY D/Electrical Engineering & Computer Science, United States Military Academy, West Point, NYView Profile Authors Info & Claims ACM SIGAda Ada LettersVolume XVIIIIssue 6Nov./Dec. 1998 pp 75–80https://doi.org/10.1145/301687.289535Online:01 November 1998Publication History 1citation275DownloadsMetricsTotal Citations1Total Downloads275Last 12 Months7Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

ABSTRACTBackground and Context: The relationship between novices’ first programming language and their future achievement has drawn increasing interest owing to recent efforts to expand K–12 computing education. This article contributes to this topic by analyzing data from a retrospective study of more than 10,000 undergraduates enrolled in introductory computer science courses at 118 U.S. institutions of higher education.Objective: We explored the relationship between students’ first programming languages and both their final grades in an introductory computer science course and their attitudes about programming.Method: Multiple matching techniques compared those whose first language was graphical (e.g., Scratch), textual (e.g., Java), or absent prior to college.Findings: Having any prior programming experience had positive effects on both attitudes about programming and grades in introductory computer science courses. Importantly, students whose first language was graphical had higher grades than did students whose first language was textual, when the languages were introduced in or before early adolescent years.Implications: Learning any computer language is better than learning none. If programming is to be taught to students before early adolescence, it is advised to start with a graphical language. Future work should investigate the transition between different types of programming languages.

As part of an ongoing initiative to continually revise and improve its introductory computer science courses, the Electrical Engineering and Computer Science Department at the United States Military Academy has added the use of LEGO Mindstorm robots as part of the active-learning environment used to teach Information Technology (IT) and programming basics. It is critical for the Army and the Nation that its future leaders understand and are capable of taking advantage of IT. All cadets at the United States Military Academy at West Point are required to take a course on IT and problem solving using computer programming. This course is an important first, and sometimes only, opportunity to expose undergraduate students to technology and concepts that will be a part of their daily lives and future careers. The LEGO Mindstorm robots are used in the introductory computer science course to teach fundamental, computer programming concepts and introduce the concepts of autonomous vehicles, embedded computer systems and computer simulation. The positive short-term impact on the students taking the course has been substantial and while the long-term impact has yet to be measured, it also has the potential to be substantial. Members of the faculty at West Point developed a computer simulation of the robot environment as well as a Java programming language translator for the LEGO programmable brick, called the RCX. These two tools are combined into a unique programming and teaching environment that we named Jago. Jago enables the robots and robot simulator to be used to teach fundamental programming concepts visually, which some students can more easily grasp and all are clearly excited to use. Based on these results we have incorporated Jago into the core IT course taught at West Point.

Students in today's introductory Computer Science courses are often already experienced with sophisticated collaborative technologies and social computing systems. Among these popular systems are the online community building and information sharing sites that have become an intrinsic part of a new cyber-culture that continues to emerge. The involvement of students in collaborative technologies can be responsible in some cases for why certain students are inspired to pursue careers in computing disciplines. Yet very few CS 1 and CS 2 textbooks contain content related to collaborative software systems, presumably because of the extreme complexity involved in developing software that communicates with other software over a network. While social computing activities are very popular, the fact that it is not very prevalent in CS 1 and CS 2 course material can discourage students who have particular interest in that area of computing. In this paper, I present a system that I have developed that offers a simple way to incorporate class work and projects that involve collaborative networking and social computing paradigms at the level of introductory Computer Science courses.

Aim/Purpose: The purpose of this study is to identify how Advanced level Mathematics and Mathematics course units offered at university level do impact on the academic performance of theoretical Computer Science course units. Background: In Sri Lankan state universities, students have been enrolled only from the Physical Science stream to do a degree program in Computer Science. In addition to that, universities have been offering some course units in Mathematics to provide the required mathematical maturity to Computer Science undergraduates. Despite of this it is observed that the failure rates in fundamental theoretical Computer Science course units are much higher than other course units offered in the general degree program every year. Methodology : Academic records comprised of all 459 undergraduates from three consecutive batches admitted to the degree program in Computer Science from a university were considered for this study. Contribution: This study helps academics in identifying suitable curricula for Mathematics course units to improve students’ performance in theoretical Computer Science courses. Findings: Advanced level Mathematics does not have any significant effect on the academic performance of theoretical Computer Science course units. Even though all Mathematics course units offered were significantly correlated with academic performance of every theoretical Computer Science course unit, only the Discrete Mathematics course unit highly impacted on the academic performance of all three theoretical Computer Science course units. Further this study indicates that the academic performance of female undergraduates is better than males in all theoretical Computer Science and Mathematics course units. Future Research: Identifying other critical success factors contributing to the students’ academic performance of the theoretical Computer Science through empirical studies

This study was conducted to determine factors that promote success in an introductory college computer science course and to determine what, if any, differences appear between genders on those factors. The model included math background, attribution for success/failure, self-efficacy, encouragement, comfort level in the course, work style preference, previous programming experience, previous non-programming computer experience, and gender as possible predictive factors for success in the computer science course. Subjects included 105 students enrolled in an introductory computer science course. The study revealed three predictive factors in the following order of importance: comfort level (with a positive influence), math background (with a positive influence), and attribution to luck (with a negative influence). No significant gender differences were found in these three factors. The study also revealed that both a formal class in programming (which had a positive correlation) and game playing (which had a negative correlation) were predictive of success. The study revealed a significant gender difference in game playing with males reporting more experience with playing games on the computer than females reported.

Most computer science programs at various universities offer courses in problem solving which are generally taken by the student in the first year. The student learns problem solving methodology which includes problem definition, analysis, design, and documentation. Although a student is graded/evaluated in each course, it may not reflect the student’s success potential in a real work environment. What is lacking is standards for various components of problem solving methodology.