Game-Based Learning in an Introduction to Mathematics of Computer Science Course: A Case Study

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 Proceedings paper was revised and published in the 2018 issue of the journal Issues in Informing Science and Information Technology, Volume 15] ABSTRACT Mathematics is fundamental to the study of Computer Science. In Sri Lankan state universities, students have been enrolled only from the Physical Science stream with minimum ‘C’ grade in Mathematics in the advanced level examination to do a degree program in Computer Science. In addition to that universities have been offering some course units in Mathematics covering basis in Discrete Mathematics, Calculus, and Algebra to provide the required mathematical maturity to Computer Science under-graduates. Despite of this it is observed that the failure rate in fundamental theoretical Computer Science course units are much higher than other course units offered in the general degree program every year. 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 and to make appropriate recommendations based on our findings. Academic records comprised of 459 undergraduates from three consecutive batches admitted to the degree program in Computer Science from a university was considered for this study. Results indicated that 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 in the first and second year of studies were significantly correlated with academic performance of every theoretical Computer Science course unit, only the Discrete Mathematics course unit highly impact-ed 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.

This descriptive study is underpinned by, and anchored on, the Transfer of Learning Theory (TLT); and it sought to determine the association between students’ attainments in Mathematics at West African Senior School Certificate Examination (WASSCE) and their undergraduate Mathematics courses. In addition, it sought to establish the correlation between students’ performance in undergraduate Mathematics courses and that of Computer Science and Engineering (CSE) courses. 872 undergraduate students were sampled from three public universities in Ghana using stratified random sampling technique; and data analysis was performed with ANOVA and descriptive statistics. The results revealed a moderate correlation among the students’ attainments in Mathematics at WASSCE, in undergraduate Math courses, and in undergraduate CSE courses. Also, it showed a significant difference in the mean performances of male and female students in all the 3 performance variables/datasets, with the females outperforming the males. Furthermore, this study proffered policy and strategy recommendations for university administrators and academic deans.

This thesis presents an analysis of a range of social, psychological and motivational factors which accounted for the inequitable representation of females in Computer Science (CS) courses in both the Australian (AU) and Taiwanese (TW) educational contexts. It draws on the literature on educational and vocational achievement related choices and decision-making to identify the key factors and how they influence males and females in making educational choices in their respective educational contexts. A mixed methods approach was chosen, using surveys for gathering the general characteristics of the undergraduates studying CS and non Computer Science (NCS) courses by educational context during the first phase (Phase 1), then interviews to examine in more detail the reasons for individuals’ course participation in the second phase (Phase 2). Results of surveys (Phase 1: AU=106, TW=52) and interviews (Phase 2: AU=7, TW=10) were analysed and presented by gender, group membership (CS and NCS) and educational context. This research offers a cross-national insight into the reasons behind females’ participation and non-participation in CS courses in two different educational contexts, which is not captured in the existing literature. The study found that an interest—enjoyment value attached to IT and/or CS encouraged Australian students to pursue CS courses. In contrast, Taiwanese students’ high self-efficacy beliefs in mathematics and programming skills encouraged their choice of CS courses. However, Taiwanese students’ course selection was dependent on the attainment value they attached to attending particular institutions, whether or not in CS. Stereotypical notions about CS related courses and careers were found to have discouraged both Australian and Taiwanese NCS females from enrolling in CS courses. This thesis concludes that although the trend of inequitable female representation in tertiary CS courses exists internationally, including in Australia and Taiwan, the factors accounting for the gender imbalance in CS vary across countries. Therefore, the strategies to address the issue of gender inequity should also reflect these differences across countries. Recommendations for the Australian context call for schools to re-consider the nature of the tasks provided in IT classrooms. As for the Taiwanese context, building female confidence in general IT learning through pre-tertiary and on-going programs, as well as instituting positive discrimination for females in CS course enrolment in Taiwanese universities, may increase the likelihood of Taiwanese females studying CS courses. Females in both contexts should be provided with broader and more accurate information regarding CS courses and careers rather than being left ill-informed with stereotypical perceptions of CS and thus choosing NCS courses. An understanding of the motivational and discouraging factors in females’ participation in CS courses in both the Australian and Taiwanese contexts provides a starting point for tackling the gender imbalance in the CS field in both contexts.

In the traditional teaching mode, students passively receive knowledge, which does not fully stimulate their enthusiasm and innovation. With the development of the Internet, blended teaching mode comes into being and has become one of the main ways of teaching reform. We introduce the blended teaching mode firstly. And then, we take the undergraduate discrete mathematics course, which is one of the most important courses of computer science, as an example, analyze its characteristics and the shortcomings of the current teaching mode. The application of blended teaching mode is imperative. Finally, we explore the application and design of the blended teaching mode based on flipped class on the undergraduate discrete mathematics course.

Scientific Visualization (SciVis) has evolved past the point where one undergraduate course can cover all of the necessary topics. So the question becomes "how do we teach SciVis to this generation of students?" Some examples of current courses are: A graduate Computer Science (CS) course that prepares the next generation of SciVis researchers. An undergraduate CS course that prepares the future software architects/developers of packages such as vtk, vis5D and AVS. A class that teaches students how to do SciVis with existing software packages and how to deal with the lack of interoperability between those packages (via either a CS service course or a supercomputing center training course). An inter-disciplinary course designed to prepare computer scientists to work with the "real" scientists (via either a CS or Computational Science course). In this panel, we will discuss these types of courses and the advantages and disadvantages of each. We will also talk about some issues that you have probably encountered at your university: How do we keep the graphics/vis-oriented students from going to industry? How does SciVis fit in with evolving Computational Science programs? Is SciVis destined to be a service course at most universities? How do we deal with the diverse backgrounds of students that need SciVis?

Many introductory computer science (CS) courses are intended to address the increased demand for computer literacy and the development of cross‐cutting concepts and practices of computational thinking (CT). Colleges and universities offer introductory CS courses every semester toward this end. The issue is centered on how to support CT learning in a large introductory CS course. To do it, an introductory CS course was designed to enrich CT by embedding short episodes of assessments to facilitate learning (AfL) and to support students’ self‐regulated learning (SRL). This chapter begins by articulating the intricacies of the underlying processes of SRL, principles of AfL, and computational thinking practices in CS. Using the undergraduate introductory CS course referred to above, key practices of SRL and AfL will be illustrated to demonstrate how student learning of CS programming is structured with various online and offline supports. The chapter then concludes by appraising aspects of this CS course with practical suggestions for supporting student SRL and their learning of CS programming.

Background: Software engineering are courses comprising various project types, including simple assignments completed in supervised settings and more complex tasks undertaken independently by students, without the oversight of a constant teacher or lab assistant. The imperative need arises for a comprehensive assessment framework to validate the fulfillment of learning objectives and facilitate the measurement of student outcomes, particularly in computer science and software engineering. This leads to the delineation of an appropriate assessment structure and pattern. Objective: This study aimed to acquire the expertise required for assessing student performance in computer science and software engineering courses. Methods: A comprehensive literature review spanning from 2012 to October 2021 was conducted, resulting in the identification of 20 papers addressing the assessment framework in software engineering and computer science courses. Specific inclusion and exclusion criteria were meticulously applied in two rounds of assessment to identify the most pertinent studies for this investigation. Results: The results showed multiple methods for assessing software engineering and computer science courses, including the Assessment Matrix, Automatic Assessment, CDIO, Cooperative Thinking, formative and summative assessment, Game, Generative Learning Robot, NIMSAD, SECAT, Self-assessment and Peer-assessment, SonarQube Tools, WRENCH, and SEP-CyLE. Conclusion: The evaluation framework for software engineering and computer science courses required further refinement, ultimately leading to the selection of the most suitable technique, known as learning framework. Keywords: Computer science course, Software engineering course, Student assessment, Systematic literature review

Nowadays, many universities have adopted Virtual Learning Environments for delivering and distributing educational resources. In the context of Computer Science (CS) courses, the use of these environments addresses several issues ranging from the application of instructional strategies to the selection of the most adequate learning platform. In this work, we propose an instructional approach to drive CS courses through virtual learning environments. The concept of driving a CS course adds a pedagogical value to the classical approach delivering educational resources. This pedagogical value is supported by applying instructional methods based on pedagogical patterns to design specific components of CS courses. The use of these pedagogical patterns helps to guide the deployment of Virtual Learning Environments (VLE) in CS courses enabling a connection between the course requirements and the VLE features. We have evaluated the proposed approach using an example of VLE called Poliformat. The evaluation focuses on the platform role as the road to drive Operating System courses during the 2005-06, 2006-07 and 2007-08 academic years. The evaluation results have contributed to a better understanding of how virtual learning environments can be used in CS courses and they confirm the benefits of applying instructional based approaches.

Nowadays, many universities have adopted Virtual Learning Environments for delivering and distributing educational resources. In the context of Computer Science (CS) courses, the use of these environments addresses several issues ranging from the application of instructional strategies to the selection of the most adequate learning platform. In this work, we propose an instructional approach to drive CS courses through virtual learning environments. The concept of driving a CS course adds a pedagogical value to the classical approach delivering educational resources. This pedagogical value is supported by applying instructional methods based on pedagogical patterns to design specific components of CS courses. The use of these pedagogical patterns helps to guide the deployment of Virtual Learning Environments (VLE) in CS courses enabling a connection between the course requirements and the VLE features. We have evaluated the proposed approach using an example of VLE called Poliformat. The evaluation focuses on the platform role as the road to drive Operating System courses during the 2005-06, 2006-07 and 2007-08 academic years. The evaluation results have contributed to a better understanding of how virtual learning environments can be used in CS courses and they confirm the benefits of applying instructional based approaches.

Assessment methods play an important role in evaluating students’ understanding of course content and in supporting effective learning. In the Software Quality Assurance (SQA) course, the syllabus primarily comprises theoretical concepts covering a broad range of topics, including quality models, testing strategies, standards, and process improvement techniques. Traditionally, essay-type questions have been used as the primary method of assessment. However, this approach was found to evaluate only limited portions of the syllabus, as students often concentrated on selected topics based on anticipated examination questions. As a result, students’ overall understanding of the complete course content was not adequately assessed, despite their exposure to all chapters of the syllabus. To address this limitation, the existing essay-based assessment format was restructured into a multiple-choice question (MCQ)-based approach. The redesigned MCQs were systematically developed to cover nearly all sections of each chapter, thereby enabling broader representation of course content within a single assessment. This approach facilitated the evaluation of students’ factual knowledge, conceptual understanding, and basic application of key principles across the entire curriculum. The adoption of MCQ-based assessments was also intended to promote consistent engagement with all topics rather than selective learning. An analysis of student feedback and assessment outcomes indicates that the MCQ-based approach enhanced comprehensive syllabus coverage, improved objectivity through standardized grading, and increased consistency in evaluation. Furthermore, students reported increased motivation to study the entire course content due to the broader scope of assessment. Nevertheless, it was acknowledged that MCQs alone may be limited in assessing higher-order cognitive skills, such as critical thinking, synthesis, and in-depth analysis. Therefore, the continued use of MCQs is proposed to ensure comprehensive content coverage while effectively assessing students’ understanding of key concepts. This approach supports efficient and consistent evaluation of learning outcomes in theory-intensive courses such as Software Quality Assurance.

In this paper, we present the findings of the effectiveness of the following two techniques that were incorporated in multiple Computer Science courses taught in multiple institutions: in-class active learning activities and video-recorded lectures. Active learning or hands-on activities have been identified as one of the most useful methods to increase students' engagement for practical Computer Science courses such as programming courses. We present our records of application of such active learning activities used in theory/mathematics-oriented Computer Science courses and discuss its effectiveness by comparing the students' performance on the same topics before and after the use of such activities as well as students' written comments in the course evaluation surveys. In addition, we will discuss the effectiveness of the lecture videos recorded during class and made available on the desire2learn and moodle pages. The students' overall performance will be compared before and after the lecture video posting and students' written comments on the course evaluation survey will be quoted to confirm the helpfulness of the recorded videos in the students' improved understanding.

The Digital Education For All project (DEFA) is a joint collaboration of five universities to open first-year computer science courses online and for free to audiences outside of universities. Additionally, students who complete enough courses through the project can apply for a study right at any of the participating universities. Completing university courses as a method of applying for a study right measures students' motivation over a long period of time, and gives the students a clear idea of the content they will encounter during their studies, whereas a traditional entrance exam measures competence only at a single point in time. While high school grades, another typical intake mechanism besides entrance exams, measure generic study skills, course-based intake mechanisms may help with student retention, as students express and gain interest in the field while completing the required courses. This study is a preliminary examination of the student intake of the DEFA project in the University of Helsinki, one of the participating universities, and a comparison of how the students accepted through the project perform in studies compared to students accepted through other intake mechanisms. Students wishing to apply for a study right through this intake are expected to complete one regular study year's worth of first-year computer science and mathematics courses in approximately one calendar year.

Success in an introductory college computer science (CS) course encourages students to major and pursue careers in computer science and many other STEM fields, whereas weak performance is often a powerful deterrent. This article examines the role of high school course taking (AP, regular, or none) in mathematics and in CS as predictors of later success in college introductory computer science courses, measured by students’ final grades. Using a sample of 9,418 students from a stratified random sample of 118 U.S. colleges and universities, we found that the observed advantage of taking AP calculus over taking AP CS, seen in an uncontrolled model, was largely confounded by students’ background characteristics. After applying multinomial propensity score weighting, we estimated that the effects of taking AP calculus and AP CS on college CS grades were similar. Interestingly, enrollment in both AP calculus and AP CS did not have any additional positive effect, suggesting that both AP calculus and AP CS strengthened similar skills that are important for long-term CS achievement. Taking regular CS did not have a significant effect; taking regular calculus had a positive effect, about half the size of taking AP calculus or AP CS. Thus, the study showed that simply exposing students to any kind of CS course before college does not appear to be sufficient for improving college CS performance; and that advanced CS and advanced calculus in high school may substitute for each other in the preparation of college CS.

BackgroundThe motivational climate within a course has been shown to be an important predictor of students’ engagement and course ratings. Because little is known about how students’ perceptions of the motivational climate in a computer science (CS) course vary by sex, race/ethnicity, and academic major, we investigated these questions: (1) To what extent do students’ achievement and perceptions of motivational climate, cost, ease, and effort vary by sex, race/ethnicity, or major? and (2) To what extent do the relationships between students’ achievement and perceptions of motivational climate, cost, and effort vary by sex, race/ethnicity, and major? Participants were enrolled in a large CS course at a large public university in the southeastern U.S. A survey was administered to 981 students in the course over three years. Path analyses and one-way MANOVAs and ANOVAs were conducted to examine differences between groups.ResultsStudents’ perceptions of empowerment, usefulness, interest, and caring were similar across sexes and races/ethnicities. However, women and Asian students reported lower success expectancies. Students in the same academic major as the course topic (i.e., CS) generally reported higher perceptions of the motivational climate than students who did not major or minor in the course topic. Final grades in the course did not vary by sex or race/ethnicity, except that the White and Asian students obtained higher grades than the Black students. Across sex, race/ethnicity, and major, students’ perceptions of the motivational climate were positively related to effort, which was positively related to achievement.ConclusionsOne implication is that females, Asian students, and non-CS students may need more support, or different types of support, to help them believe that they can succeed in computer science courses. On average, these students were less confident in their abilities to succeed in the course and were more likely to report that they did not have the time needed to do well in the course. A second implication for instructors is that it may be possible to increase students’ effort and achievement by increasing students’ perceptions of the five key constructs in the MUSIC Model of Motivation: eMpowerment, Usefulness, Success, Interest, and Caring.