Computer Science Courses Research Articles

Teaching Data Science with Literate Programming Tools

This paper presents a case study on using Emacs and Org-mode for literate programming in undergraduate computer and data science courses. Over three academic terms, the author mandated these tools across courses in R, Python, C++, SQL, and more. The onboarding relied on simplified Emacs tutorials and starter configurations. Students gained proficiency after undertaking initial practice. Live coding sessions demonstrated the flexible instruction enabled by literate notebooks. Assignments and projects required documentation alongside functional code. Student feedback showed enthusiasm for learning a versatile IDE, despite some frustration with the learning curve. Skilled students highlighted efficiency gains in a unified environment. However, the uneven adoption of documentation practices pointed to a need for better incorporation into grading. Additionally, some students found Emacs unintuitive, desiring more accessible options. This highlights a need to match tools to skill levels, potentially starting novices with graphical IDEs before introducing Emacs. The key takeaways are as follows: literate programming aids comprehension but requires rigorous onboarding and reinforcement, and Emacs excels for advanced workflows but has a steep initial curve. With proper support, these tools show promise for data science education.

Implementation of blended learning approach in teaching introductory computer science course

Information communication and technology has great impact on modern education architecture of 21st century. This research intends to analyze the effectiveness of blended learning considering its basic principles and factors. Also, this study is focused on determining core problems of blended learning thus highlighting its design approach. A descriptive and inferential statistical analysis has been conducted on the data that reveal that the majority of students prefer blended learning system regardless their major, gender and any other factors if they have good infrastructure and effective electronic platform. It is recommended that for effective implementation of blended system there should be opportunities of face to face as well as online synchronous, and non-synchronous communication between students and teachers.

Engineering Students’ Experiences of Assessment in Introductory Computer Science Courses

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Contribution:</i> This study evaluates the generalizability of previously identified perceptions among engineering students of assessments in introductory programming (CS1). The students’ perceptions of their instructors’ and teaching assistants’ (TAs) roles in these assessments are also studied, and differences based on prior programming experience, gender, and course explored. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>Background:</i> Basic programming skills are desirable also for students who are not majoring in computer science (CS). Students’ experience of assessments has not been fully explored. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>Research Questions:</i> 1) How do engineering students experience the assessment (lab assignments, midterm exam, and project) in their CS1 courses? 2) What are the students’ perceptions of the TAs and instructors in relation to these assessment situations? 3) What significant differences can be found based on students’ prior experience in programming, gender, and course? <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>Methodology:</i> Previously identified themes from an interview study worked as a framework for the formulation of 25 statements used in a survey among 137 students in six CS1 courses (second part of a mixed-method study). Descriptive statistics, Mann–Whitney U Test, and Kruskal–Wallis tests with Bonferroni corrections, were used to analyze the data. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <i>Findings:</i> Laboratory assignments were experienced as an opportunity to learn while the exams were viewed as predictable. The projects were perceived as authentic, although varying in difficulty, and as a huge leap from the lab assignments. Students perceived the instructors to put their touch on the course but viewed their TAs as carrying out the assessments, and experienced variations between TAs. Female students experienced these variations to a larger extent and perceived received feedback as less useful.

Implementation of blended learning approach in teaching introductory computer science course

Information communication and technology has great impact on modern education architecture of 21st century. This research intends to analyze the effectiveness of blended learning considering its basic principles and factors. Also, this study is focused on determining core problems of blended learning thus highlighting its design approach. A descriptive and inferential statistical analysis has been conducted on the data that reveal that the majority of students prefer blended learning system regardless their major, gender and any other factors if they have good infrastructure and effective electronic platform. It is recommended that for effective implementation of blended system there should be opportunities of face to face as well as online synchronous, and non-synchronous communication between students and teachers.

Quizzing Students about their Writing: Implications for Deterring and Detecting Contract Cheating, and Promoting Academic Integrity and Greater Engagement

Contract cheating is a significant concern in the higher education sector, and a multi-faceted approach focusing on student learning and growth, in addition to deterring and detection cheating, is necessary to address the issue. One way to support student learning is by encouraging active engagement in learning activities and assessments. To this end, we explored the utility Auth+ by Sikanai, an authorship verification platform that auto-generates six multiple-choice questions based on students’ writing submissions and generates scores based on responses to the questions. Auth+ is designed to encourage students to engage in the learning process and to facilitate the detection of potential contract cheating. Auth+ was implemented in a third-year computer science course, and 24 students shared their perceptions of its value for teaching and learning. Only 25% of students agreed that Auth+ would be useful in their studies but 62.5% agreed it would deter contract cheating. We also found an association between Auth+ scores and individual differences in working memory (τB = .391). Our findings suggest that, with further technology development, authorship verification platforms may be useful for promoting academic integrity and deeper engagement in learning at scale. Training educators to interpret the results and use them as part of a multi-faceted strategy for promoting academic integrity and reduce academic misconduct is important.

“Regular” CS × Inclusive Design = Smarter Students and Greater Diversity

What if “regular” Computer Science (CS) faculty each taught elements of inclusive design in “regular” CS courses across an undergraduate curriculum? Would it affect the CS program's climate and inclusiveness to diverse students? Would it improve retention? Would students learn less CS? Would they actually learn any inclusive design? To answer these questions, we conducted a year-long Action Research investigation, in which 13 CS faculty integrated elements of inclusive design into 44 CS/IT offerings across a 4-year curriculum. The 613 affected students’ educational work products, grades, and/or climate questionnaire responses revealed significant improvements in students’ course outcomes (higher course grades and fewer course fails/incompletes/withdrawals), especially for marginalized groups; revealed that most students did learn and apply inclusive design concepts to their CS activities; and revealed that inclusion and teamwork in the courses significantly improved. These results suggest a new pathway for significantly improving students’ retention, their knowledge and usage of inclusive design, and their experiences across CS education—for marginalized groups and for all students.

How are websites used during development and what are the implications for the coding process?

Websites are frequently used to support the development process. This paper investigates how websites are used when writing code and programmers’ perceptions of the potential impact of this on their behaviour and the quality of the resulting software. We interviewed 18 programmers (13 students enrolled in undergraduate computer science courses, and 5 experienced professionals), and analysed the data thematically. The findings were used to develop a survey, which was distributed to 276 programmers (251 students, 25 experienced professionals). The results indicate that use of websites, especially Stack Overflow, is viewed as an essential part of programming by both students completing coursework and professionals developing code in industry.We also found that developers have experience of encountering a diverse set of problematic code snippets online, that copying code from websites without checking its quality or understanding how it worked is common, and that using online resources in this way had a potentially counter-productive effect on learning. Based on these findings, we make a number of recommendations, including better consideration of online code reuse in taught programmes, co-development and code-reuse practices in professional settings, and software licensing training for professional developers.Editor’s note: Open Science material was validated by the Journal of Systems and Software Open Science Board.

Empirical Evaluation of a Differentiated Assessment of Data Structures: The Role of Prerequisite Skills

There can be many reasons why students fail to answer correctly to summative tests in advanced computer science courses: often the cause is a lack of prerequisites or misconceptions about topics presented in previous courses. One of the ITiCSE 2020 working groups investigated the possibility of designing assessments suitable for differentiating between fragilities in prerequisites (in particular, knowledge and skills related to introductory programming courses) and advanced topics. This paper reports on an empirical evaluation of an instrument focusing on data structures, among those proposed by the ITiCSE working group. The evaluation aimed at understanding what fragile knowledge and skills the instrument is actually able to detect and to what extent it is able to differentiate them. Our results support that the instrument is able to distinguish between some specific fragilities (e.g., value vs. reference semantics), but not all of those claimed in the original report. In addition, our findings highlight the role of relevant skills at a level between prerequisite and advanced skills, such as program comprehension and reasoning about constraints. We also suggest ways to improve the questions in the instrument, both by improving the distractors of the multiple choice questions, and by slightly changing the content or phrasing of the questions. We argue that these improvements will increase the effectiveness of the instrument in assessing prerequisites as a whole, but also to pinpoint specific fragilities.

An evaluation of game-based computer science course designs: The example of minecraftedu

An evaluation of game-based computer science course designs: The example of minecraftedu

Constructive Combinatorics in Elementary School Mathematics

The paper describes in detail a class of educational problems from an elementary school course of mathematics and computer science. This course has been implemented over the past decades by a team led by Academician of the RAS A.L. Semenov. In the problems, it is necessary to find, build, or list all objects that satisfy a certain system of conditions. The student conducts these activities in a visual world of basic objects of discrete mathematics and computer science: strings (finite sequences of symbols), bags (multisets), tables, trees, and statements containing quantifiers. The connections of these problems with problems in computational combinatorics (counting the number of options), with search problems in the theory of computational complexity, with “big ideas,” and general cognitive strategies for their formation in education are considered. The content of education in our approach is more adequate to the context of the modern world.

A systematic review of the literature on methods and technologies for teaching parallel and distributed computing in universities

There is a growing demand for software developers who have experience writing parallel programs rather than just "parallelizing" sequential systems as computer hardware gets more and more parallel. In order to develop the skills of future software engineers, it is crucial to teach pupils parallelism in elementary computer science courses. We searched the Scopus database for articles on "teaching parallel and distributed computing" and "parallel programming," published in English between 2008 and 2019. 26 papers were included in the study after quality review. As a result, a lab course using the C++ programming language and MPI library serves as the primary teaching tool for parallel and distributed computing.

Base Algorithm and Open Data of Auditing the e-Learning Digital Accessibility

Enhancement the methodology for assessing the digital accessibility of e-learning is an important condition for improving the quality of modern educational services. In order to develop a basic algorithm for auditing digital accessibility, the expert data from 173 e-learning resources (56 Massive Open Online Courses (MOOCs) in mathematics, 65 MOOCs in computer science and programming, 22 intra-university online courses in mathematics, computer science and programming, 30 MOOCs in cardiopulmonary resuscitation) were systematized and analyzed. The paper considers: methods and process of collecting expert data, the content of data sets, the procedure for empirical analysis of the results of testing the e-learning content accessibility. The structure of the proposed algorithm of auditing the digital accessibility includes the following stages: preparation for examination; automatic and expert testing of digital accessibility and generation of data sets; data analysis; formulating a final conclusion and recommendations for improving digital accessibility. Further use of the basic algorithm and data sets of audits can be useful for the development of accessible education, the training of e-learning specialists, and the strengthening of regulatory and control mechanisms in the field of education.&#x0D;

Relationship Between Implicit Intelligence Beliefs and Maladaptive Self-Regulation of Learning

Objectives . Although prior research has uncovered shifts in computer science (CS) students’ implicit beliefs about the nature of their intelligence across time, little research has investigated the factors contributing to these changes. To address this gap, two studies were conducted in which the relationship between ineffective self-regulation of learning experiences and CS students’ implicit intelligence beliefs at different times during the semester was assessed. Participants . Participants for Studies 1 (n = 536) and 2 (n = 222) were undergraduate students enrolled in introductory- and upper-level CS courses at a large, public, Midwestern university. Race-ethnicity information was not collected due to IRB concerns about possible secondary identification of participants from underrepresented groups. Study Method . Participants completed a condensed version of the Implicit Theories of Intelligence Scale [ 16 , 54 ] and the Lack of Regulation Scale from the Student Perceptions of Classroom Knowledge Building scale [ 51 , 53 ] at the beginning (Studies 1 and 2), middle (Study 2), and end (Studies 1 and 2) of semester-long undergraduate CS courses. Survey responses were analyzed using path analyses to investigate how students’ lack of regulation experiences throughout the semester predicted their implicit intelligence beliefs at the beginning (Study 2) and end (Studies 1 and 2) of the semester. Findings . Results from Study 1 indicate that undergraduate CS students come to more strongly believe that their intelligence is a fixed, unchanging entity from the beginning until the end of the semester. Moreover, participants’ responses to the lack of regulation scale were predictive of their implicit intelligence beliefs at the end of the semester. Results from Study 2 indicate that ineffective self-regulation experiences early in the semester enhance CS students’ belief in the unchanging nature of intelligence (i.e., during the first half of the semester). Taken altogether, these findings provide evidence that self-regulation experiences influence students’ beliefs about the malleability of intelligence. Conclusions . Findings align with Bandura's [ 4 ] contention that students’ behaviors and experiences influence their values and beliefs. Students who experienced poor self-regulated learning came to view intelligence as more of a fixed, unalterable entity than their more successfully self-regulated peers. Findings suggest that CS instructors can positively affect student motivation and engagement by embedding self-regulated learning strategy instruction into their courses and helping CS students adopt an incremental-oriented (e.g., growth-oriented) belief system about their intellectual abilities.

Context matters: Secondary science teachers' integration of process‐based, unplugged computational thinking into science curriculum

AbstractThere is growing recognition in the education community that the problem‐solving practices that comprise computational thinking (CT) are a fundamental component of both life and work in the twenty‐first century. Historically, opportunities to learn CT have been confined to computer science (CS) and elective courses that lack racial, ethnic, and gender diversity. To combat this inequity, a number of scholars have proposed integrating CT practices into core curriculum——especially science, technology, engineering, and math curriculum. Successfully achieving the goal of integrated CT, however, depends on frameworks to guide integration, professional development for teachers, exemplars of successful integrations, and identifications of the barriers teachers encounter. Research pertaining to each of these areas is in its infancy. This study addresses these needs through a collective case study of 10 secondary science teachers' implementations of a novel, process‐based, unplugged approach to CT/science integration and the factors that supported or hindered their CT/science integration efforts. The results of this work reveal that: (1) an unplugged and process‐based approach to CT/science integration shows promise as a vehicle for infusing CT into diverse science classrooms; (2) educators' teaching context exerts a strong influence on their CT‐integration efforts and persistence; and (3) special attention is needed to support teachers in their CT/science integrations including algorithm creation. This study also demonstrates the utility of the Fraillon et al.'s CT framework as a guide for CT/science integration efforts and sheds light on the unique affordances of unplugged strategies for implementing CT‐integrated science curricula.

Generating Interest in Foundational Computer Science in High Schools: A Northwest Florida Case Study

Computer Science drives innovation and discovery, and Computer Science classes in High Schools, particularly AP Computer Science Principles, have also been linked to better performance in other High School courses, but a Code.org report shows that the state of Florida, particularly the Northwest Florida region, is far behind the rest of the nation in offering Computer Science classes at the High School level. This paper discusses strategies that are can be implemented to improve High School Computer Science offerings in like-regions that have lower Computer Science offerings. The paper also discusses the challenges that come up in addressing this issue and presents potential avenues for addressing these challenges. One major challenge that is addressed is creating the culture of inclusive computing by getting more women and under-represented groups interested in taking Computer Science courses. Though this is a Northwest Florida case study, most of the strategies discussed in this paper would be applicable to any other part of the country with low Computer Science offerings with a similar socio-economic background.

Interactions between self‐regulated learning and assessment for learning in an undergraduate introductory computer science course

AbstractMany 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.

Increasing Women's Participation in CS at Large Public Universities: Issues and Insights

Despite rapidly growing interest in Computer Science (CS), CS has the second lowest participation rate for women of all science and engineering degrees, according to a recent report by the US National Science Board [16]. The reasons for women's underrepresentation and their experiences may differ from university to university. Universities are very different in terms of types of students, student profiles, students' socio-economic status, race, number of students, admission requirements, and resources. For example, some universities can create gender balance in introductory courses through selective admission. However, typically, admission practices in large public universities are not able to achieve gender balance for CS majors. As a result, there are lower percentages of women in the CS major in large public universities than in selective schools. In addition, large public universities tend to have a larger number of CS students when compared to private universities. To understand women students' experiences and struggles in computer science at a large public university in the United States and to find ways to intervene in favor of gender equity in computer science, we conducted in-depth interviews with women students in introductory programming courses. In this article, we present women students' experiences, struggles, expectations and offer potential interventions based on the findings to encourage women to consider CS as their major and stay in the CS major. Our interview data shows there is a persistent effect of lack of prior programming experience and gender bias that leads to a negative experience for women students in introductory CS courses. This article presents the challenges faced by women in CS and provides their recommendations for attracting and retaining women students in CS at large public universities.

Can Automated Feedback Improve Teachers’ Uptake of Student Ideas? Evidence From a Randomized Controlled Trial in a Large-Scale Online Course

Providing consistent, individualized feedback to teachers is essential for improving instruction but can be prohibitively resource-intensive in most educational contexts. We develop M-Powering Teachers, an automated tool based on natural language processing to give teachers feedback on their uptake of student contributions, a high-leverage dialogic teaching practice that makes students feel heard. We conduct a randomized controlled trial in an online computer science course (N = 1,136 instructors), to evaluate the effectiveness of our tool. We find that M-Powering Teachers improves instructors’ uptake of student contributions by 13% and present suggestive evidence that it also improves students’ satisfaction with the course and assignment completion. These results demonstrate the promise of M-Powering Teachers to complement existing efforts in teachers’ professional development.

CONSTRUCTIVE COMBINATORICS IN PRIMARY SCHOOL MATHEMATICS

The paper is describing the class of educational problems from the course of mathematics and computer science for elementary school. This course has been implemented over the past decades by a team led by A.L. Semenov. In the problems it is required to find, build, list all objects that satisfy a certain system of conditions. The student conducts these activities in the visual world of the basic objects of discrete mathematics and computer science: strings (finite sequences of symbols), bags (multisets), tables, trees, and statements containing quantifiers. The connections of these problems with problems of computational combinatorics (“counting the number of options”), search problems of the theory of computational complexity, with “big ideas”, general cognitive strategies in their formation are considered. The content of education in our approach is more adequate to the context of the modern world.

A Gender-Based Comparison of the Effects of Face-to-Face and Online Learning on Student Performance in Introductory Computer Science Courses

Introductory computer science courses help students, regardless of their majors, keep up with the rapid pace of change in the workplace. However, such courses are commonly perceived as being difficult. Although many studies have discussed the importance of online introductory computer science courses, there is a dearth of studies investigating the effectiveness of this delivery mode when the same assessment tools are used as in the traditional delivery mode. Moreover, it is unclear how students of different genders perform in both online and traditional face-to-face introductory computer science course sections when they receive the same instructional content. The purpose of this study is to expand the existing literature by examining the academic achievement of students in an introductory computer science course through the evaluation of grades obtained from online and traditional face-to-face course sections. Additionally, the study aims to explore any gender-based variations between the two delivery modes. The sample size included 589 first-year students in an introductory computer science course at a public university in Saudi Arabia. The participants were selected randomly from different sections. The results confirm the findings of previous studies suggesting that there are no gender-based differences in students’ performance in introductory computer science. Additionally, this study makes a valuable contribution to the existing body of literature by demonstrating that students who receive introductory computer science instruction through online delivery mode achieve significantly higher performance than students who receive the same instruction through traditional face-to-dace delivery mode. Moreover, this study found that both female and male students who receive introductory computer science instruction through online delivery mode perform significantly better than male students who receive instruction through traditional face-to-face delivery mode, indicating that online learning may be a more effective mode of delivery for students of both genders.