Computer Science Education Research Articles

Increasing the Level of Cognitive Activity of Students of the Secondary Vocational Education System in Computer Science Classes Based on a Collective Learning Method

Purpose. The purpose of the article is to substantiate the application of a collective method of teaching in computer science classes in the system of secondary vocational education, contributing to an increase in the level of cognitive activity of students.Research methodology. The idea of the study is related to the implementation of collective learning methods in computer science classes to increase the level of cognitive activity of students. The use of collective learning methods in computer science classes is considered from three positions: organizational, methodological and diagnostic. The organizational aspect includes the conditions for the formation of student groups and scenarios of their interaction in the learning process. The methodological aspect is related to the selection and preparation of special educational and methodological support, including teaching methods. The diagnostic aspect provides an assessment of the effectiveness of learning the educational material, the level of cognitive activity and the state of the psychological atmosphere in the classroom. The measurement of the level of cognitive activity is carried out with the help of a simplified three-dimensional diagnostic method by O. Markelova. The observation of changes in the psychological atmosphere in the classroom is carried out by the method of pedagogical observation.Results. Based on the adaptation of the principles and advantages of collective learning methods (according to V. Dyachenko) to the tasks of the secondary vocational education system, the conditions for the formation of student groups and scenarios of their interaction in the process of teaching computer science were outlined. A training cycle has been proposed for the implementation of a collective method of teaching in computer science classes and a collection of digital educational resources has been compiled. Diagnostic tools have been adapted to identify the level of cognitive activity in computer science classes. The diagnosis of the level of cognitive activity and the effectiveness of learning material in computer science classes was carried out, as well as the psychological atmosphere in computer science classes was analyzed.Conclusions. The use of collective teaching methods in computer science classes in the secondary vocational education system helps to increase the level of cognitive activity of students and, as a result, provides a comfortable psychological atmosphere in the classroom and increases the effectiveness of learning material.

Artificial Intelligence Curriculum Development for Intelligent System Experts in University

Artificial intelligence (AI) has emerged as a pivotal technology for enhancing national and industrial competitiveness in the digital transformation era. Consequently, the cultivation of specialized talent in AI has garnered significant attention. This study analyzed AI-related department curricula at major universities worldwide, identifying critical courses for each academic semester. The data we collected included course titles, syllabi, and learning objectives, which were refined and analyzed afterward. Furthermore, we comparatively examined university AI education programs based on the content of Computer Science Curricula 2023, a widely recognized framework for computer science education. The insights gleaned from our analysis revealed that AI curricula are built upon a foundation of computer science, emphasizing the importance of a deep understanding of various related domains within the field of computer science. Based on these findings, we proposed a curriculum for AI departments, considering the need for a comprehensive understanding of computer science alongside specialized AI courses. This study aims to provide foundational data for advancing AI education and guide educational program improvements. Ultimately, it aspires to contribute to developing specialized professionals in the AI field, thereby bolstering national and industrial competitiveness in the rapidly evolving digital landscape.

Exploring the Efficacy of Machine Learning Tools for Analyzing Student Performance in Computer Science Applications

This research study examines how ML techniques can assess computer science student performance. The study compares current and past performance metrics, identifies salient performance assessment features, and outlines strategies for sustaining or enhancing student achievement in the context of the COVID-19 pandemic, which has shifted the paradigm toward online learning. Context: With the rise of digital learning platforms and the changing educational environment, ML approaches are being used to get useful insights from massive student data sets. The COVID-19 pandemic has highlighted the need for improved virtual student learning monitoring and support methods. Objective: The purpose of this study is to determine if ML methods can accurately assess student computer science proficiency. Compare students' current performance measures to their prior records to identify COVID-19-related changes. To choose relevant characteristics for performance evaluation using ML algorithms and statistics. Methods: The research uses a mixed-methods approach, combining quantitative academic record analysis with qualitative student survey and interview data. Results: show substantial relationships between performance metrics and external influences, including remote learning. ML models identify academic performance factors, enabling targeted interventions and instructional improvements. Conclusion: Integrating ML technologies can improve computer science instruction and student achievement. Data-driven insights help instructors change teaching tactics, identify at-risk pupils, and create a dynamic learning environment that promotes academic success. ML techniques may help educational institutions negotiate distant learning and achieve inclusive, equitable, and successful results.

EXPLORING MULTI-REPRESENTATION LEARNING APPROACH IN MATHEMATICS ELEMENTARY SCHOOL STUDENTS

The purpose of this study was to analyze the effectiveness of the multi-representation learning approach in improving the understanding of mathematical concepts for elementary school students. The inclusion criteria in this review include studies that clearly apply a multi-representation approach in primary school settings and have relevant data to evaluate. Studies that do not provide adequate data or do not meet the inclusion criteria are excluded. Sources of information used to identify these studies include various academic databases such as ERIC, Springer, Elsevier, Ebschoohost, Taylor &; Francis, the ACM Technical Symposium on Computer Science Education and MDPI publishers. The last search was conducted last month before the writing of this abstract. Methods of evaluating bias risk in included studies include methodological quality assessment, data quality control, and evaluation of the accuracy of the statistical analysis used. The main findings of the study are presented through thematic and narrative analysis, with a total of 75 scientific studies included in this review. The characteristics of relevant studies will be discussed further in the analysis which includes research content, study design, type of participants, learning domain, and year of publication. The findings show that with various forms of representation students can improve their understanding of mathematics from informal to formal levels, in addition to the fact that multi-representation learning can deepen students' understanding of complex mathematical concepts.

ICT TRENDS IN EDUCATION: A BIBLIOMETRICS STUDY OF THE PAST TWENTY YEARS OF STUDIES

Technology is a major component in education. Therefore, it must be investigated in order to gather knowledge for additional study. 185 articles were assessed using the PRISMA approach in conjunction with VOS-Viewer via Scopus data collecting. Analysing the quantity of articles, nations, citations, journals, and research partnerships on digital assessment in education is how evaluation is done. Knowledge map analysis is another way to investigate co-occurrence mapping. According to the research findings, the number of articles published rises annually, with the UK having the highest number of published publications. The research with the most citations is "Affordances of ICT in science learning: Implications for an integrated pedagogy," the journal with the most publications is "International Journal of Science Education," and the most well-liked partnership is the work done in Germany and the United Kingdom. The author with the most citations is "Webb M.E." Additionally, cluster analysis indicates that there are five primary categories—computer science education, education, science education, teaching, and science learning—that are most closely related to one another. Teaching, education, and computer science education are hot subjects right now.

ICT TRENDS IN EDUCATION: A BIBLIOMETRICS STUDY OF THE PAST TWENTY YEARS OF STUDIES

Technology is a major component in education. Therefore, it must be investigated in order to gather knowledge for additional study. 185 articles were assessed using the PRISMA approach in conjunction with VOS-Viewer via Scopus data collection. Analyzing the quantity of articles, countries, citations, journals, and research partnerships on ICT in education is how evaluation is done. Knowledge map analysis is another way to investigate co-occurrence mapping. According to the research findings, the number of articles published rises annually, with the UK having the highest number of published publications. The research with the most citations is "Affordances of ICT in Science Learning: Implications for an Integrated Pedagogy," the journal with the most publications is "International Journal of Science Education," and the most well-liked partnership is the work done in Germany and the United Kingdom. The author with the most citations is "Webb M.E." Additionally, cluster analysis indicates that there are five primary categories—computer science education, education, science education, teaching, and science learning—that are most closely related to one another. Teaching, education, and computer science education are hot subjects right now.

Assessing the Impact of Mobile Applications on Student Engagement in ICT and Computer Science Education

This study investigates the impact of mobile applications on student engagement in the realms of Information and Communication Technology (ICT) and Computer Science Education. As the integration of mobile applications in educational settings becomes increasingly prevalent, understanding their influence on student engagement is crucial for optimizing learning experiences. The study employs assess the effectiveness of selected mobile applications aligned with the curriculum. Data analysis focuses on measuring and evaluating student engagement levels. The results reveal shedding light on the implications for enhancing ICT and computer science education. This research contributes to the existing literature by addressing gaps and providing insights into the practical use of mobile applications in educational settings.

The impact of virtual learning environment on future teachers’ professional competence in lifelong learning

The study aimed to empirically test the impact of a virtual learning environment on the professional competence of future computer science teachers in lifelong learning by conducting a survey and comparing the professional competence of bachelor and master students, as well as their opinions on the impact of the virtual learning environment on future teachers’ professional competence in lifelong learning. The surveying methods were cognitive, motivational, activity-based, and value-based. A survey of students found that a virtual learning environment has the most significant impact on the activity component of professional competence, and most students are motivated to use virtual learning environments to improve their professional competence. The survey of teaching staff revealed a positive attitude towards professional development through virtual learning environments, the prevalence among students of high and sufficient levels of professional competence and digital literacy. The obtained results can be used to adjust the virtual educational process of future teachers’ professional training in the system of Ukrainian HEIs.

Generative AI and CS Education

Increasing knowledge sharing between industry and academia.

What does the phrase “diverse students” mean? An exploration of CS teachers’ ideas of race, culture, and community in their classrooms

ABSTRACT Background and Context Recent research suggests that there is work to be done in overcoming color-evasive ideologies in Computer Science (CS) education. In particular, we have limited insight into how to support white teachers in using Culturally Responsive Computing (CRC) approaches. This paper addresses this gap in the literature by analyzing interviews with white high school CS teachers through the lens of hegemonic whiteness. Objective We ask two questions 1) What are the gaps between these teachers’ views on culture, community, and responsiveness, and how CRC envisions the interplay of these three elements? 2) How can we use teachers’ understandings to reconceptualize presenting CRC to them in a manner that may best benefit their students? Method We use semi-structured interviews of nine teachers until data saturation. We use in-vivo and values coding in the first round and code-weaving in the second round to come up with emergent themes. Findings Our findings show that these teachers did one or more of the following: 1) had dynamic but content-agnostic views about culture in the classroom; 2) focused on community connections with academia, industry, and/or parents; 3) framed the challenges of implementing CRC through a deficit lens; and 4) valued students’ individuality, but were essentialist about student culture. Implications We have implications for practitioners, e.g. to have professional developments that allow teachers to name and challenge white supremacy in CS. We also have implications for researchers, e.g. to investigate ways in which white students and teachers can benefit from anti-racist CS education.

Enacting algorithms: Evolution of the algorythmics storytelling

Visual storytelling, particularly through dance choreographies as showcased in previous AlgoRythmics performances, has been effective in communicating relatively straightforward algorithms in an engaging and memorable way. Nevertheless, when addressing complex algorithmic concepts, an approach with greater expressiveness and flexibility becomes necessary. Consequently, this study introduces stage performances as an innovative solution, using cinematic representation to successfully convey and communicate these intricate concepts and processes. To evaluate the effectiveness of this approach, a short film was designed, produced, and showcased to a second-semester CS2 university course audience studying programming techniques. Following an opening scene that establishes the context, the subsequent three acts vividly depict ad hoc, greedy, and dynamic programming solutions in response to the posed programming challenge. After the screening, a questionnaire was administered, built on four key constructs of the Technology Acceptance Model, as well as other potential facilitating factors. The study reveals 100% positive perceptions of educational benefits, with the vast majority of students expressing agreement regarding the utility, enjoyment, engagement, creativity, filmic quality, and cognitive benefits of short films. Additionally, a remarkable 96% reported the intent to utilize this approach. Our subsequent Structural Equation Modeling analysis discovered that students whose learning styles were in sync with this approach demonstrated a robust correlation between their perception of the method’s value, their enjoyment of the process, and their overall attitude towards this pedagogical method. This study confirms the potential of visual storytelling through short films as an effective tool for delivering programming education. The findings provide valuable insights for computer science educators seeking to engage learners and convey complex information in an attractive and effective way.

In search of artificial intelligence (AI) literacy in teacher education: A scoping review

Artificial intelligence (AI) literacy has recently emerged on the educational agenda raising expectations on teachers’ and teacher educators’ professional knowledge. This scoping review examines how the scientific literature conceptualises AI literacy in relation to teachers’ different forms of professional knowledge relevant for Teacher Education (TE). The search strategy included papers and proceedings from 2000 to 2023 related to AI literacy and TE as well as the intersection of AI and teaching. Thirty-four papers were included in the analysis. The Aristotelian concepts episteme (theoretical-scientific knowledge), techne (practical-productive knowledge), and phronesis (professional judgement) were used as a lens to capture implicit and explicit dimensions of teachers’ professional knowledge. Results indicate that AI literacy is a globally emerging research topic in education but almost absent in the context of TE. The literature covers many different topics and draws on different methodological approaches. Computer science and exploratory teaching approaches influence the type of epistemic, practical, and ethical knowledge. Currently, teachers’ professional knowledge is not broadly addressed or captured in the research. Questions of ethics are predominantly addressed as a matter of understanding technical configurations of data-driven AI technologies. Teachers’ practical knowledge tends to translate into the adoption of digital resources for teaching about AI or the integration of AI EdTech into teaching. By identifying several research gaps, particularly concerning teachers' practical and ethical knowledge, this paper adds to a more comprehensive understanding of AI literacy in teaching and can contribute to a more well-informed AI literacy education in TE as well as laying the ground for future research related to teachers’ professional knowledge.

Project-based teaching of computer science in inclusive education using digital technologies

Relevance. The relevance of the research is due to the rapid development of information technologies and the digital environment, which requires constant updating of educational methodologies and their adaptation for inclusive educational practices. Purpose. This article aims to research and develop a methodology that would contribute to the effective implementation of project-based learning using digital technologies in inclusive education in the field of computer science. Methodology. The leading method of researching this problem was system analysis. The following methods of scientific cognition were also applied: logical analysis, comparison, synthesis, deduction, and classification. Results. The study reveals the indicators of inclusive education, including student involvement, accessibility, indicators of student achievement, and professional competence of teachers. It also highlights barriers and discrimination, funding, and cooperation. The concept of project-based learning, its functions, and aspects are disclosed. The relationship between project-based learning and inclusive education and the prospects for its application in inclusive education are explored. Four types of approaches in project-based learning that can be applied in teaching computer science are presented. Additionally, a methodology to improve the teaching of computer science is developed. Conclusions. The study considered in detail the main principles, methodologies, and practices that affect the effectiveness and accessibility of inclusive education for diverse groups of students. It justified the prospects of project-based learning methodology as part of an effective strategy for inclusive education. The materials from the study can be used to improve curricula for inclusive classes, providing more effective teaching of computer science through the use of digital technologies. Keywords: educational methodology; personalization; special educational needs; active participation; educational plans; computer literacy

Use of open collaborative learning system and a methodology for measuring its effectiveness

Relevance. This study is devoted to the problem of using open co-education in the training of computer science teachers in universities of the Republic of Kazakhstan. The problems covered are relevant in the context of the development of the education system, and the rethinking and updating of existing teaching methods used in education, especially in the field of training teachers in the field of information technology. Purpose. The purpose of this study is to determine the effectiveness of the use of open collaborative training of teachers in information technology to increase teachers� awareness of such teaching methods. Methodology. In the current study, an experiment based on the evaluation of three parameters was used for two groups of students � one of the groups of students was taught according to the conventional form of education, the second group of students used the form of open co-education, which is considered in this study. Results. As a result of the introduction of this technique, an increase in attendance was obtained: in the experimental group, the average number of classes attended was 42.875, compared with 39.02 in the control group (Eta-squared value 0.0093) and with 40.3 in the experimental group itself before the introduction of the technique (Eta-squared value 0.0093). Exam results: the experimental group had an average score of 4.33, compared with 3.58 in the control group (Eta-squared value 0.0035) and 3.8 in the experimental group itself, compared with the period when the group was trained in the conventional way (Eta-squared value 0.0033). Similarly, a decrease in the dropout rate was noted � from 8.33% and 5.56% to 0%, respectively. Conclusions. In other words, there is an improvement in all indicators as a result of the introduction of open collaborative learning. Thus, it is possible to recommend this methodology for educators who teach future teachers in the field of information technology. Keywords: computer science; academic achievements; learning models; trends in education; collaboration

Advancing Equity and Access: Addressing the Side Effects of Broadening Participation in Computer Science K–12 Education

Over the past 20 years, there has been a concentrated effort on expanding K–12 pathways, experiences, and access in computer science education (CSEd). Computer science (CS) is a multifaceted discipline within education, and the current emphasis in education policy has focused on how to expand access for K–12 students in CSEd that will lead to increased innovation and bring new participants into the United States labor economy. Industry partners have advocated for policies and incentives to increase pathways to CS opportunities. This chapter interrogates the side effects of CSEd and offers a framework for considering how side effects impact CS teaching and learning. We highlight the barriers that exist within CS and CSEd and how broadening participation in computing efforts could address longstanding equity and disparity issues.

Computer science and engineering students’ self-directed learning strategies and satisfaction with online learning

There is an increasing need for computer science and engineering (CSE) online education. This study examined CSE online learners’ perceptions of self-directed learning (SDL) readiness, strategies, and satisfaction. The researchers surveyed 225 students and conducted semi-structured interviews with 15 online CSE students. The quantitative survey data and the qualitative interview data were analyzed using descriptive statistics and thematic analysis, respectively. The findings were as follows: (1) Both extrinsic motivation strategies (e.g., future career development, building a learning routine) and intrinsic motivation strategies (e.g., interest in learning) were utilized; (2) Diverse metacognition strategies (e.g., assignments, quizzes, and tests, discussing with peers, tracking progress, staying in touch with professors and teaching assistants) and cognitive strategies (e.g., watching recorded lectures, taking notes, reading books, seeking out information) were used to monitor learning; (3) Time-management (e.g., priority, checklist, fixed schedule, time-block for study) and resource management strategies (e.g., focused on lectures, textbook reading) were leveraged; (4) Specific designs or instruction promoted students’ SDL skills, such as access to documented learning materials, reminders sent from instructors, availability of the instructor, group interaction, and flexibility, and (5) Student satisfaction depended on the design of the course. The advantages and disadvantages of online learning were identified. The findings indicated that the instruction strategies and online course design are critical for CSE students’ SDL.

Improving Computer Science Curriculum and Teaching in the New Information Age

Improving Computer Science Curriculum and Teaching in the New Information Age

MODELING COMPETENCIES FOR FUTURE COMPUTER SCIENCE TEACHERS

This article explores the improvement of modeling skills among future computer science teachers. The current methods of forming these skills are analyzed, and the need for their improvement is justified. The research methods and the results of the experiment on the introduction of a new model of modeling training are described. The article concludes with conclusions and suggestions for further improving the training of future computer science teachers in the field of modeling.

Applying Q-methodology to investigate computer science teachers’ preferences about students’ skills and knowledge for obtaining a degree

Students’ dropout of Computer Science (CS) education is a crucial issue. This study aims to investigate one of the aspects which can help to retain our students. It is vital to examine CS education on the challenge of competence transition within the BSc curriculum from faculty perspectives. Teachers’ expectations about students’ skills and knowledge are important to understand because they influence learning outcomes and teaching methodologies. Acquiring hard skills and professional skills has outstanding significance in preparing students for their future careers. This study uses Q-methodology to identify the different viewpoints on the skills necessary to obtain a CS degree. Teachers from CS bachelor’s programmes at a large European university participated in the study and shared their opinions. The participants were asked to rank the statements along a spectrum of “the most important skill” to “unimportant skill” (containing hard skills as well as soft skills). Factor analysis revealed five factors that are key components to obtaining a degree in CS: 1. analytical and technical skills, 2. teamwork and self-study experience, 3. group programming experience, 4. communication and problem-solving skills, 5. mathematical foundations and process modelling ability. This exploratory study applied a new research instrument and approach to incorporate teachers’ perspectives into research and practice. These findings could help administrators develop new curricula in order to increase students’ retention. We confirmed the need for acquiring professional skills and highlighted the need for designing new programmes which can improve students’ soft skills to prepare them for work in the IT field.

Visualizing Algorithms in the Field of Education: A Comprehensive Review

Abstract: Visualization of algorithms can enhance computer science education by offering a beneficial method for comprehending intricate concepts within engineering courses. An electronic learning tool has been created to cover various algorithms, including sorting algorithms, prime numbers, recursive sorting algorithms, and the N Queen problem. Employing animation as a means of conveying information, the tool enables users to select data ordering and algorithms. Users can either initiate automatic animation or progress through the steps at their own pace. Additionally, the pathfinding algorithm permits usersto modify the starting and ending nodes. This e-learning tool serves as both a standalone application and a complementary resource for in-person training, providing a visual representation of the execution stages of algorithmic rules.