Math proficiency

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

At the University of Tennessee at Martin (UTM), freshman computer science majors were being successful in their first quarter in computer science, but many majors were not completing the year sequence (Programming Concepts and Problem Solving I, II, and III). This study describes a freshman studies program that helps increase student retention in the first computer science course.Two populations were used in this study. The first population (Group A) consisted of 25 freshman computer science majors (16 men and 9 women) enrolled Fall Quarter 85 in freshman orientation General Studies GS1000 for one quarter hour credit. The second population (Group B) consisted of 17 freshman computer science majors (12 men and 5 women) enrolled the Fall Quarter 86 in freshman orientation General Studies GS1001 for two quarter hours credit. Both groups were placed in the first course in computer science using the cutting scores ACT English > 17 or 0.78 (ACT English) + 0.49 (UTM Math Placement) > 33. Both Groups A and B had an average ACT English score of 20 and an average UTM Math Placement score of 55. Each quarter during the freshman year, the computer science major enrolls in calculus (4 hrs.), Programming Concepts and Problem Solving (3 hrs.), a laboratory science (4 hrs.), English (3 hrs.), and a humanities course (3 hrs.).Group A was offered a freshman orientation program that involved a pass/fail one quarter hour credit GS1000 which met one hour each day during freshman studies week. Each section consisted of twenty-five heterogeneously grouped students. The course content was review of study skills. Group B was offered a freshman orientation program that involved a pass/fail two quarter hour credit GS1001 which met one hour each day during freshman studies week, plus one hour each week during the first quarter. Each section consisted of only students of a particular major (computer science) and was taught by a faculty member of that department. The topics of this course consisted of a review of study skills, discussions of student problems, special academic speakers, field trips to professional sites, cultural events, meetings with deans and department heads, and a follow-up on study skills. In the meeting before the final exam week, the faculty member dealt specifically with suggestions on preparing for finals.Groups A and B were enrolled in the same first computer science sequence (Programming Concepts and Problem Solving I, II, and III) their freshman year. Both groups had the same instructors, text (Introduction to Computing and Computer Science with Pascal by H. Walker), and course syllabus for this sequence. Both groups carried the same academic course load their freshman year. However, in Group A only 20% (5 out of 25) of the students completed the first computer science sequence with a grade of C or better, while in Group B 41% (7 out of 17) completed the same sequence with a grade of C or better. Student retention is achieved through the students' integration into the academic and social systems of the college by two factors: (1) faculty-student interaction and (2) peer-group interaction. Although the population of this study was small, I believe GS1001 provides one way of increasing student retention in computer science.

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.

Teaching formal methods in software construction has often been a concern of several computer science educators. In our opinion, the origin of most of the difficulties in learning formal methods in computer science and software engineering does not lie in computer science courses but in the mathematical background of the students. Moreover, there are numerous obstacles to learning basic concepts noted by both computer science and mathematics educators. To change this situation it is necessary to integrate the work of mathematics and computer science educators. That is, the main focus should be the creation of new educational approachs nourished by two components: a theoretical one (formally introducing discrete mathematics concepts) and an experimental one (implementing those concepts in a suitable programming language). In this paper, using examples from a discrete mathematics course for high school teachers, we describe the main characteristics of our approach.

There has been much debate in the past few years about the appropriate mathematics requirements for an undergraduate computer science major. The discussion has focused primarily on two issues: (1) the underlying mathematical content of computer science courses and (2) the content of mathematics courses which would serve as appropriate cognate requirements for computer science major programs. While this discussion has been helpful, it has been too narrowly focused--it has not started from an understanding of the relationship between the disciplines of mathematics and computer science, but rather has sought to identify mathematical prerequisites that computer science majors need in order to take existing computer science courses. This paper is a small step in seeking to apply an understanding of the relationship between the disciplines of mathematics and computer science to the undergraduate computer science curriculum.

The promise of computer-assisted instruction (CAI) was recognized long ago, but CAI is not widely used in college-level science and engineering curricula. Standup lectures remain the method of choice for delivering classroom instruction. In this paper, we describe an educational software package called ALECS (A Learning Environment for Computer Science). ALECS has been used in a first-semester computer science course to dramatically reduce the time devoted to standup lectures, which gives the instructor more time for tutoring. ALECS provides assistance in three areas: instruction, feedback and student tracking. We describe each of these areas and the changes ALECS enables in the structure of our courses and in the classroom.

We feel that for a long time introductory computer science courses have degenerated into courses more appropriately titled “Introduction to the Programming Language X” where X has historically been FORTRAN or BASIC and more recently PL/I or APL. In this paper we propose an introductory course which first, and foremost, teaches problem-solving methodology with the final stage of it being translation of an algorithm into a well-structured program. And, second, it achieves this in conjunction with an introduction to the major areas of computer science.

Working under the Curriculum Committee of the Education Board of the ACM, the committee has developed a detailed analysis of the requirements of the first course in computer science as described in the current ACM curriculum guidelines. The report includes the material which should be included in such a course and also recommendations for effective presentation of the material. Discussion of the computer laboratory and implications of increased exposure to programming experiences by incoming students is included.

This paper explores the potential of virtual education options to fulfill policies designed to broaden participation in computer science (CS) education. Virtual education platforms inherently offer access to a wider range of students than traditional brick-and-mortar schools. Access does not preclude the various socio-economic challenges to engaging these platforms, but this format could be used to mitigate barriers to reaching groups of students that have historically been marginalized in CS courses. In 2019, Georgia passed legislation that requires all middle and high schools to offer CS courses by 2025. The legislation also allowed for virtual courses to satisfy the requirement. While the legislation is intent on broadening participation in CS education, it specifically incorporates a virtual option, making it novel among similar legislative actions across the country. In this context, we examine whether virtual CS courses increase access for marginalized student populations. As such, we explore (1) to what extent do the disparities in CS education found in brick-and-mortar classrooms also appear in virtual settings and (2) to what extent is there an association between modality and rurality on CS course enrollment. Using district enrollment data from 2012 to 2019 for CS courses in Georgia, we calculated the percentage of students in marginalized groups that enrolled in physical courses across the state compared to the percentage enrolled in statewide virtual courses to illuminate existing disparities in enrollment. We conducted this analysis at the district level to highlight variability in representative disparity and the underlying structural differences that might contribute to these disparities. Our analysis provides insight that incorporates the different levels of representative disparity districts have overall. As an early adopter of virtual CS education, the Georgia model provides valuable information for states interested in policies to broaden participation in CS courses.

This study investigated the relationships between computer science (CS) course effectiveness and academic performance in a Guangdong Province private school through an integrated environmental and social psychology framework, examining collaborative learning environment and technology environment perception as mediating mechanisms. A quantitative cross-sectional design surveyed several hundred Grade 4 international high school students enrolled in computer science courses at Guangdong Country Garden School during the 2024-2025 academic year. Results revealed that all five CS course effectiveness dimensions—hands-on experiences, real-world applications, collaborative learning, problem-solving abilities, and technology landscape readiness—demonstrated strong positive correlations with academic performance (r=.790-.879, p<.01), with problem-solving abilities emerging as the strongest predictor (β=.342). Mediation analysis using Hayes' PROCESS macro with bootstrapping procedures confirmed that collaborative learning environment (14.7%-23.7% mediation) and technology environment perception (14.7%-23.9% mediation) functioned as significant partial mediators, with real-world applications showing strongest social-psychological mediation and hands-on experiences exhibiting strongest environmental mediation. Hierarchical regression demonstrated that environmental and social-psychological factors contributed unique variance beyond course effectiveness dimensions (ΔR²=.043, p<.001). Findings provide empirical support for person-environment fit theories and social cognitive frameworks, highlighting the importance of optimizing both technological infrastructure and interpersonal climate for CS education effectiveness in private school contexts.

The adoption of innovative online teaching tools in Computer Science (CS) courses provides opportunities for data-informed instruction as a regular teaching practice in CS classrooms. In this paper, we present a design study for an interactive visual analytics dashboard, called UserFlow, that supports feedback collection from teaching documents and assists instructors in interpreting feedback and acting on it in a timely manner. The design study is conducted with eight domain experts comprising of four teaching instructors, two learning analytics (LA) experts and two instructional designers. UserFlow offers a set of novel visualization designs for presenting the four interleaving aspects of document engagement (i.e., annotations, document traversal path, reading/focus time and student information). We evaluated UserFlow in an undergraduate computer science course with over 700 students. Our results demonstrate the usefulness and need for such a tool for CS educators to inform teaching approaches and courseware improvement.

This research shows an audience of fellow computer science teachers that there is benefit in testing college student's scientific reasoning skills and that the students increase their logical thinking skills in computer science classes when they are presented with real world problems, engaged in group activities, and given hands-on experiments.Students' scientific reasoning skills from several different computer science courses are analyzed and tested before and after taking the computer science course to measure their improvement in logical thinking. The higher order thinking skills test results are compared, and the overall class and individual student improvement between the classes that use different teaching strategies are analyzed. Also, the test results are compared with students' ability to perform adequately in a computer science course. This information is valuable to advisors when placing students in computer science courses.In the assessments of students' entering knowledge and evaluations of students' thinking improvement, the students' individual higher order thinking skills as well as their overall level of cognitive development are analyzed. Through the analysis of their individual skills and level of thinking, one can expand conclusions about the students' and teacher's performance over time.

The purpose of this study was to justify of the formation technique of representation of modeling methodology at computer science lessons. The necessity of studying computer modeling is that the current trends of strengthening of general education and worldview functions of computer science define the necessity of additional research of the problems relating to study of computer modeling bases within the basic course of computer science. Such necessity is caused by that “Mathematics and Computer Science” education range is a backbone line of the course. Consideration of modeling issues within computer science course is the basis of cogitative operations development called in pedagogies as methods of mental actions or intellectual abilities. But at schools and in pedagogical higher education institutions of Republic of Kazakhstan this section of computer science course is not considered properly. The issues related to a formation technique of basic concepts of modeling, and also usage of applied software environments for development and research of models except an Excel editor are not developed. Practically there are no techniques creating a broad view on concept of model, there is no methodically acceptable models’ typology. The research results indicate that when disclosing the material on themes about modeling stages the process is should be considered as cyclic, there is need of interpretation of models’ relevance concept, “undelivered”, “vital” tasks are should be considered, which fully reflect intersubject links.

This paper describes our experiences using Active Learning in four first-year computer science and industrial engineering courses at the School of Engineering of the Universidad Católica de la Santísima Concepción, Chile. This work corresponds to the implementation stage of the curriculum reform using a CDIO-based approach currently underway at the School of Engineering. Before this reform, students had only one introductory course to their field of study, meeting one hour a week. After the reform, computer science students take an Introduction to Computer Science course and a Programming Laboratory. Similarly, the industrial engineering program now includes an Introduction to Industrial Engineering and an Engineering Communication course. These courses have been designed using CDIO standards 1, 4 and 8 as guidelines and have been formulated to include active learning in its many forms such as project-based learning, problem-based learning, case studies, small group discussions, oral presentations and reflective memos. The redesign impact was assessed via anonymous student surveys and reflective memos. Our results show improved student understanding of their professional endeavour and increased student motivation for their engineering programs. Student surveys registered high degrees of satisfaction with active learning techniques, working in teams, and receiving immediate feedback from instructors and peers.

Recent work in Peer Led Team Learning (PLTL) has resulted in development of strategies and exercises for implementation of PLTL in the first course in Computer Science as well as two higher-level u...