A discrete structures course for a small college

It is generally accepted that a course in discrete structures such as Course B3 in Curriculum 68 recommendations [1] is an important part of a Computer Science program. In many institutions a Discrete Structures course is offered in the Computer Science Department although it overlaps courses in the Mathematics Department [2,3,4]. In smaller schools the size of the student body and staff limitations make such a solution impractical. At Augusta College we have met the objective of early exposure to discrete mathematics with applications in computer science by offering a two-hour computer science course as a co-requisite to a three-hour mathematics course. While this approach is a compromise it does appear to have some merit.

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

Discrete Structures texts are notorious for their lack of examples from computer science. One response to this problem is to teach the Discrete Structures course as a course in pure mathematics. However the end result is computer science students completing the course without understanding the reason it is required. A second response to the problem is to give the course a computer science flavor by requiring the writing of programs illustrating the mathematical ideas introduced. This approach still does not address the real issue of why the course is required. A third response, the one advocated by this paper, is to supplement the text with examples and exercises showing how the mathematical concepts are actually applied in various areas of computer science. This paper examines some appropriate computer science examples and exercises and discusses the author's experiences when incorporating them into the Discrete Structures course at S.U.N.Y. at Plattsburgh.

Supporting computer science and computer application courses requires spending many resources on specialized software. Courses, such as database concepts and applications, depend upon hands-on experience with software to help students understand important principles. Both the university computer labs and students need to install software for homework assignments. Problems include software availability, cost, installation, platform compatibility, and configuration. While academic licensing provides software to students at significantly lower prices, the price may still be too high for some students. Installation and configuration on client/student side may also be a problem. Further, IT departments face the challenge of installing, upgrading and patching the software in student labs.

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.

This chapter describes four interdisciplinary fields originated and defined by Ashu M. G. Solo in 2011 called political engineering, public policy engineering, computational politics, and computational public policy. Political engineering is the application of engineering, computer science, mathematics, or natural science to solving problems in politics. Computational politics is the application of computer science or mathematics to solving problems in politics. Political engineering and computational politics include, but are not limited to, principles and methods for political decision-making, analysis, modeling, optimization, forecasting, simulation, and expression. Public policy engineering is the application of engineering, computer science, mathematics, or natural science to solving problems in public policy. Computational public policy is the application of computer science or mathematics to solving problems in public policy. Public policy engineering and computational public policy include, but are not limited to, principles and methods for public policy formulation, decision-making, analysis, modeling, optimization, forecasting, and simulation. The chapter describes the scope of research and development in these fields, provides examples of research and development in these fields, and provides possible university curricula for academic programs in these fields.

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 purpose of the study is to assess the application of Computer science in the fractional distillation of petroleum. The study sought to: Determine the merit of using Computer science in fractional distillation of petroleum. Evaluate the cost effectiveness to the application of Computer science in fractional distillation of petroleum to the welfare of citizens. Determine if Computer science can help in controlling the natural effects of fractional distillation of petroleum on the environment. Computer science has gained wider application in so many areas of human endeavor ranging from the homes to more scientific and industrial applications, hence its application of Computer science in fractional distillation of petroleum cannot be overemphasized. Irrespective of the benefits of the application of Computer science in fractional distillation of petroleum as a whole, it has become pertinent to ask how effective and efficient its application of Computer science in fractional distillation of petroleum has been. This research work tries to investigate how effective the application of Computer science in fractional distillation of petroleum. The project exertion covered statement of the problem, purpose of the study, research questions/hypotheses were formulated to enable the researcher find out facts about the study, highlighted in division one. Subdivision two was based on the literature review of this study. The study covers the research methodology which guided the study, the next stage was based on the presentation of data and its’ analysis as well as the discussion of findings. The final stage of the research was concerned with the conclusion as well as recommendations and suggestions for further studies

This paper describes an introductory course in discrete structures for the undergraduate computer science student that has evolved at the University of Saskatchewan, Saskatoon. The philosophy of such a course and certain problems encountered in preparing and teaching it are discussed.

The Computing Curricula 2001 (CC 2001) computer science volume [1] is the first professional society curriculum model for computer science to include elements of discrete mathematics as part of the core of computer science. In the roughly eight years between the release of that curriculum and SIGCSE 2010, computer science education in general has evolved in many ways, and the CC 2001 recommendations have played an influential role in that evolution. This panel reviews developments in integrating discrete mathematics into the computer science curriculum since CC 2001, how those developments have been influenced by the centrality of discrete math in the CC 2001 core, and how the role of math in computer science curricula may continue to develop in the future. The panel will address both the influence CC 2001’s discrete math recommendation has had on curricular changes to computer science courses, and what changes have taken place in the discrete math courses themselves. The panel format will consist of… ˜ A 5 minute introduction by the moderator ˜ 10 minute presentations by each panelist, each describing a specific development with which that panelist has been involved, discussing its relationship to CC 2001, and outlining what it bodes for the future ˜ 30 minutes for discussion between the audience and panel. Suggested topics for discussion include (in addition, of course, to anything that the audience wishes to introduce) the role of mathematics in computer science, whether math’s actual place in computer science curricula has changed since the publication of CC 2001, and if so how. A questionnaire handed out to audience members as they enter the panel session will help them start thinking about these issues.

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.

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.

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.

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.