The 2022 undergraduate database course in computer science

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.

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

Identifying at-risk students as soon as possible is a challenge in educational institutions. Decreasing the time lag between identification and real at-risk state may significantly reduce the risk of failure or disengage. In small courses, their identification is relatively easy, but it is impractical on larger ones. Current Learning Management Systems store a large amount of data that could help to generate predictive models to early identification of students in online and blended learning. The contribution of this paper is twofold: First, a new adaptive predictive model is presented based only on students’ grades specifically trained for each course. A deep analysis is performed in the whole institution to evaluate its performance accuracy. Second, an early warning system is developed, focusing on dashboards visualization for stakeholders (i.e., students and teachers) and an early feedback prediction system to intervene in the case of at-risk identification. The early warning system has been evaluated in a case study on a first-year undergraduate course in computer science. We show the accuracy of the correct identification of at-risk students, the students’ appraisal, and the most common factors that lead to at-risk level.

The training of a professional in the area of computing involves understanding the process of building software. In the Computer Science course curricular guidelines, this training is a requirement for graduating from the course. For the construction of the Pedagogical Project of the Course (PPC), the In-stitutions observe reference documents for the development of the project according to the local/regional specificity. Dealing with computing courses, the National Curricular Guidelines (DCN) for Computing courses, the training references of the Brazil-ian Computing Society (SBC) and the Guide to the Software Engineering Body of Knowledge (SWEBOK), are key elements to support the construction of the PPC. In Computer Science courses, software engineering is presented as a central element in technological training for students. Software engineering defines stages for the construction of quality software, which begins with the requirements conception, analysis, design and ends with the construction of the solution. The scope of this article will deal with the software design area, which is responsible for defining an implementable structure for a software product, which meets the specified requirements, that is, makes the communication interface between the requirements and the construction of the software. In the specialized literature, the area of Software Design (SD) is presented as important and emerging topics in the training of Computing professionals. Emerging topics for teaching Software Engineering aligned with teaching Software Design were identified, such as: UX Design Practices, Current Interface Prototyping Tools and Design Patterns. One of the challenges for the area of Software Engineering is the high heterogeneity of solutions, leading to hybrid systems, with multi-paradigms, and this heterogeneity reflects on how the professional designs the solution, what is directly associated with training in Software Design. The justification for the development of this article is given by the need to understand how the curricula of Computer Science courses are contemplating the Software Design stage and the alignment of contents to the SWEBOK guide. Given this context, the objective of this work is to identify the panorama of Software Design teaching in the Computer Science course in Higher Education Institutions in Brazil. To this end, an analysis of the disciplines of the courses selected for the research was carried out, in order to identify which SubTopics defined in the SWEBOK for the Software Design knowledge area are present in the subjects. It was observed the diversity of subjects that deal with aspects of Software Design and the dispersion of these contents throughout the student's academic path, with the highest concentration in the 2nd and 3rd year of the course. In addition, contents related to Software Design Quality are little explored in CS courses. The study enables the discussion on teaching software design in the computer science course, seeking to address the gaps identified in this study, with the objective of making improvements in Project Pedagogical of the courses from the perspective of teaching software design.

This report presents an experiment using a cross-over assignment between an upper-level writing course and a first-year seminar, both required undergraduate computer science courses at a large research university. Logistical challenges and lessons learned are described. Inspired by increased attention to ethics within the computer science academic community and technical communication scholarship connecting power, ethics, and user-centered technology, this writing activity asks students to evaluate and explain a user's risk after a breach or exploit. I argue that the rhetorical concepts of audience and nomos are effective vehicles for engaging students toward a more user-focused ethical awareness within a computer science context. In his recent Call to Action, Wolf (Vice Chair of ACM's Committee on Professional Ethics) echoes this need to complicate an understanding of users with an ethical focus, quoting Updated Code Imperative 3.4: The needs of people---including users ... should always be a central concern in professional computing [1].

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 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.

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.

While blogs are an established communication channel on the World Wide Web, their use in technology-enhanced education has only recently been gaining popularity. In educational settings, blogs can be used to facilitate the creation of a community of learners, to support students in exploratory learning, reflection of learning activities, and by instructors to follow learning progress and collaborative activities. In this chapter, we present the application of blogs in an undergraduate computer science course on software architectures and web technologies. We provide quantitative and qualitative analyses of blogging behavior and learning outcome data, and provide reflections along with some recommendations on using this Web 2.0 tool in higher education settings.

According to the literature, Computer Science courses are highly technical but are lacking in soft skills that enable students to develop not only the technical skills but also professional skills such as collaboration, communication within and across cultures, teamwork and knowledge of diverse cultures. In this paper we report on the design and execution of a prototype framework for using active learning to build soft skills and diversity awareness into a service learning component for a database management course. In this course students were given an opportunity to work with a regional Native American organization to create a database solution for a maple syrup operation that needed greater coordination for marketing, distributing and delivering their product across ancestral homelands disrupted by colonialism. Our aim was to test the prototype framework to see if it increased student learning over the traditional final exam and brought greater self-awareness, recognition and respect concerning cultural difference. Students reported that they learned more about the technical aspects of database creation from doing the service learning project than from preparing for the final exam; they also reported greater awareness of cultural diversity. This paper lays out the design of our service learning pedagogy, the test results, and the model we propose for other computer science technical courses.

This tutorial is concerned with a method of organizing undergraduate computer science courses, in which the students collaborate in small groups. Effectively this breaks up a large class into a number of independent small groups and changes the role of the teacher from a director to a 'consultant.' The teacher has to provide a series of discussion papers for the groups, each including a problem to be solved. The group is expected to investigate the topic, produce an exact specification of the problem, provide an algorithm to solve the problem, an implementation of the algorithm, and documentation including a discussion of implications and generalizations. This form of peer instruction has improved performance of both the better and the poorer students, and plagiarism is no longer a problem. (Students who do not do their share of the work are liable to be excluded by their group.) They also investigate topics with much greater thoroughness and appear to obtain a deeper understanding. The group experience is valuable training for working on projects in industry. The tutorial will outline how to organize such a course and will discuss case studies.

We are developing instructional tools that will help students and instructors use discussion boards more effectively, with an emphasis on automatically assessing discussion activities and promoting student discussion participation and learning. In this paper, we present a discussion scaffolding tool that exploits natural language processing and information retrieval techniques. The PedaBot tool is designed to aid student knowledge acquisition, promote reflection about course topics and encourage student participation in discussions. It dynamically processes student discussions and presents related discussions and document from a knowledge base of past discussions and course materials. This paper describes the system and presents a comparative analysis of the information retrieval techniques used to respond to free-form student discussions, including a combination of topic profiling, term frequency-inverse document frequency, and latent semantic analysis. Responses are presented as annotated links that students can follow and rate for usefulness. The tool has been integrated into a live discussion board and has been used by an undergraduate computer science course for three semesters. We report current studies of PedaBot from its usages based on student viewings, student ratings, and a small survey. Initial results indicate that there is a high level of student interest in the feature and that its responses are moderately relevant to student discussions. We are exploring more opportunities to exposing the tool to students.

KLYDE is a software workbench that helps students study issues related to the design, implementation, and empirical analysis of algorithms. Using the system's graphical user interface students can design and conduct experiments to study the efficiency of a variety of algorithms and their underlying implementations. The data generated by these experiments can be studied directly, or imported into speadsheet and presented graphically. This paper gives an overview of the KLYDE system and illustrates how the system can be used in a variety of undergraduate computer science courses.

Problem posing refers to the generation of a new problem or a question, by a learner of a given topic. It has been shown to be an effective strategy for learning of complex material in domains such as mathematics. In this study we have defined Problem Posing Exercises (PPE) as a problem posing based instructional strategy to scaffold the learning of complex material and problem solving in a first year undergraduate computer science course (CS1). We implemented PPE in a large CS1 course of 450 students and found that PPE has positive effects on students' learning and engagement. We also examined the differences in effect of PPE for novice and advanced learners and found that PPE has more evident effects on novices than advanced learners.

BOARD # 70: Instructor Practices for Supporting Neurodivergent Students in Undergraduate Computer Science Courses: Neurodivergent Faculty and Student Perspectives