Computer Science Education Research Articles

Coding as another language: an early childhood programming curriculum in Argentina

ABSTRACT Background and context Early childhood computer science (CS) education is a high-priority focus worldwide, but early childhood CS tools are primarily developed and researched within the United States and Europe. As an example, the Coding as Another Language ScratchJr (CAL-ScratchJr) curriculum is used in multiple countries but was developed and evaluated in the United States. Objectives This paper describes the implementation and evaluation of an adapted CAL-ScratchJr curriculum in Mendoza and Corrientes, Argentina. Method We used mixed methods and a cluster-randomized control trial to evaluate curriculum success, measured by validated assessments and teacher interviews. Findings The curriculum significantly improved student coding knowledge and computational thinking. Teachers saw the curriculum as successful across multiple domains. Implications These findings reinforce that the success of CS education programs should be evaluated not only with internationally validated assessments but also by local understandings of success..

Using artificial intelligence tools for automating the assessment of future computer science teachers' work

This paper examines the problem of automated testing of modified programming tasks for future computer science teachers. It is recommended that GitHub Copilot be used to generate tests based on the code. This approach makes it possible to solve the following tasks: reducing the time and effort required for manual checking of programming tasks completed by students; promoting better assimilation of the material of the relevant disciplines by students; promoting the development and improvement of students' skills in algorithmisation and programming; compliance by students with academic integrity; effective use of GitHub Copilot to generate baseline tests to test modified programming assignments completed by students; ensuring the flexibility and scalability of the approach to the development of various training courses in programming; development of students' software product testing skills. In the process of research, we found the following disadvantages of using the GitHub Copilot system for generating basic tests: GitHub Copilot does not always generate perfect code or tests; for complex tasks, GitHub Copilot may require additional correction of the generated code. Therefore, it is important to check and refine the generated tests carefully, if necessary. Therefore, at the moment, we recommend using GitHub Copilot as a template generator for writing tests. The proposed approach is a promising solution for facilitating the verification of modified programming tasks and increasing the effectiveness of the education process of future informatics teachers. The conducted research opens up new prospects for effective improvement of the verification of modified tasks performed by students and the generation of tests for verification. In particular, the integration of the proposed system based on GitHub Copilot with learning management systems (LMS) and automated task verification systems. Another area of research could be exploring the possibilities of using other tools for generating tests instead of GitHub Copilot or combining them in order to obtain better results.

Comments on School Education in Mathematics and Computer Science

This work aims to improve problem-solving skills even for students and adults, who are not so interested in mathematics. This requires simple algorithms. The efficiency of these is not the focus of this work, as we assume that computers will continue to take over this computational work. We concentrate on important, flexible operations that are as universal as possible. In doing so, we rely on the object of the structured table. A structured table can represent a number of any type, but also texts and structured collections of text and numbers. This means that the focus is no longer only on individual data operations such as addition, multiplication, sine, root, etc., but also on mass data operations such as selecting (choosing), sorting, aggregating, restructuring, joining (merging tables), etc. The work clearly shows that these operations can also be used to develop new, simpler solutions for the problems now being dealt with at school. Simpler, more universal algorithms that can be programmed by anyone should be taught at school. The work on the data model o++o was strongly motivated by the Relational data model with its language SQL and the language CONVERT, which tried to extend the flat table model to hierarchical data structures.

CodeContrast: A Contrastive Learning Approach for Generating Coherent Programming Exercises

Generating high-quality programming exercises with well-aligned problem descriptions, test cases, and code solutions is crucial for computer science education. However, current methods often lack coherence among these components, reducing their educational value. We present CodeContrast, a novel generative model that uses contrastive learning to map programming problems, test cases, and solutions into a shared feature space. By minimizing the distance between matched components and maximizing it for non-matched ones, CodeContrast learns the intricate relationships necessary to generate coherent programming exercises. Our model architecture includes three encoder networks for problem descriptions, test cases, and solutions. During training, CodeContrast processes positive triplets (matching problem, test case, solution) and negative triplets (non-matching combinations) and uses a contrastive loss to position positive triplets close in the feature space while separating negative ones. Comprehensive evaluations of CodeContrast—through automatic metrics, expert ratings, and student studies—demonstrate its effectiveness. Results show high code correctness (92.3% of test cases passed), strong problem–solution alignment (BLEU score up to 0.826), and robust test case coverage (85.7% statement coverage). Expert feedback and student performance further support the pedagogical value of these generated exercises, with students performing comparably to those using manually curated content. CodeContrast advances the automated generation of high-quality programming exercises, capturing relationships among programming components to enhance educational content and improve the learning experience for students and instructors.

Comprehensive evaluation of humanistic qualities and mental health of computer science teachers based on biomechanical algorithms

Comprehensive evaluation of humanistic qualities and mental health of computer science teachers based on biomechanical algorithms

Automated Generation of Multiple-Choice Questions for Computer Science Education Using Conditional Generative Adversarial Networks

Automated Generation of Multiple-Choice Questions for Computer Science Education Using Conditional Generative Adversarial Networks

Understanding ChatGPT: Impact Analysis and Path Forward for Teaching Computer Science and Engineering

Understanding ChatGPT: Impact Analysis and Path Forward for Teaching Computer Science and Engineering

Personalized games for computer science education in higher education: the effect of personalization feature on students’ engagement and flow state

Personalized games for computer science education in higher education: the effect of personalization feature on students’ engagement and flow state

Pedagogical guidance of the process of forming information technological competence of future computer science teachers: a practical aspect

The article reveals the current problem of organizing pedagogical guidance in the process of forming information technology competence of future computer science teachers in a practical aspect:It is noted that technological training in the conditions of the modern information and educational space of higher education` pedagogical institutions is implemented by performing a significant part of educational activities using communication technologies.In the article it is presupposed that mandatory presence of initial information and technological literacy of students, is manifested not only in their mastery of the skills and abilities in using their activities of a set oftechnical means and devices, but also in the ability to understand when this information is needed, find it how to evaluate and use it effectively.Therefore it is necessary to improve the ways of forming and developing information technology competence of specialists as a necessary component of their general professional competence. It is a value guideline of modern higher pedagogical education; the practical component of the process of forming information technology competence of future computer science teachers. It is revealed in the context of the activities of the studio of pedagogical excellence to improve the methodological and technological literacy of higher education teachers, which provided for work in two directions: «Modern Educational Technologies» and «Fundamentals of Computer Telecommunications». It is concluded that the use of information and communication technologies in the educational and information environment of a pedagogical institution of higher education and the optimal management of this process made it possible to provide students with additional theoretical and methodological material on electronic media in the disciplines of basic training in the field of informatization of education, which made it possible to repeat the educational material of the studied problems and use it in a new context.

TRAINING OF COMPUTER SCIENCE TEACHERS FOR THE FORMATION OF CYBERSECURITY SKILLS IN STUDENTS: ACTUALIZATION OF PROBLEMS AND THEIR POSSIBLE SOLUTIONS

The article presents an analysis of the problem of preparing computer science teachers for the formation of cybersecurity skills in students. The generalization of the available scientific results gives an idea of the general trends and problems in this field: the need for constant updating of the curriculum in computer science and cybersecurity is emphasized to keep pace with the development of technologies and standards; emphasizes the need to combine practical skills with fundamental knowledge in cybersecurity education; stresses the importance of pedagogical and methodological knowledge along with subject knowledge in the training of computer science teachers; mastering innovative digital strategies for teaching and learning computer science; a mixed way of teaching courses (face-to-face, hybrid or online) and a variety of teaching methods; development of methodological competence of computer science teachers through different approaches to such development (special courses, internship programs, mentoring, joint lesson planning and reflective practice, etc.). Based on the results of the analysis, recommendations were formulated for the modernization of teacher training programs for the formation of students' cybersecurity skills: integration of content modules on cybersecurity into courses on methods of teaching computer science; development and implementation of specialized cybersecurity courses in educational and professional teacher training programs; use of digital tools and simulation technologies; promoting the continuous professional development of teachers in the field of cybersecurity; promoting cooperation and knowledge exchange with cybersecurity practitioners; bringing computer science teacher training curricula in line with international standards in the field of cybersecurity. We consider further research to be promising in studying the content of educational programs for training computer science teachers and analyzing the effectiveness of various teaching methods for developing cybersecurity skills in future computer science teachers.

INTEGRATING BLENDED LEARNING IN PROGRAMMING COURSE: A COMPREHENSIVE SYSTEMATIC REVIEW

This systematic review examines the integration of blended learning in programming courses, addressing the increasing diversity of student backgrounds and the consequent challenges in teaching programming effectively. The study synthesizes findings from recent research to identify effective strategies and best practice outcomes associated with blended learning approaches in this context. A comprehensive methodology was employed, involving the selection and analysis of relevant articles from databases such as Scopus and Web of Science, focusing on studies published between 2020 and 2024. The study was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) framework. The database found (n=30) final primary data was analysed. Numerical results from the chosen literature reveal three main themes: (1) Effectiveness of Blended Learning in K-12 Education, (2) Best Practice of Blended Learning in Higher Education and Professional Development, and (3) Students’ Understanding on Blended Learning in Programming and Computer Science Education. This review concludes that integrating blended learning in programming courses not only addresses diverse learning needs but also fosters improved academic outcomes and student engagement. Future research should continue to explore innovative blended learning strategies and their long-term impacts on programming education.

USING CLOUD TECHNOLOGIES TO OPTIMIZE THE EDUCATIONAL PROCESS AT SCHOOL

The article is devoted to the study of the use of cloud technologies in the educational process of schools, focusing on innovative approaches such as the «Flipped classroom» model. Cloud technologies provide ample opportunitiesfor students and teachers to work together, providing access to educational materials at anytime from anywhere, which contributes to the development of cognitiveindependence of students. The article discusses the types of cloud technologies, their advantages, including cost-effectiveness, accessibility and convenience, as well asdidactically the features of their use. Special attention is paid to the technology of mixed learning in the form of an «Flipped classroom «. Its advantages in comparisonwith the traditional approach are shown, including the activation of cognitive activity of students, increasing the level of their involvement, the development of critical thinking and cooperation skills. The experiment demonstrates the advantages of this technology in teaching computer science, including increasing the interest of schoolchildren in educational material and improving the quality of mastering the topic. The hypothesis of the study is that the use of cloud technologies in combination with the «Flipped classroom» model contributes to increasing the cognitive activity of students, developing their independence and improving the assimilation of educational material. The conclusions confirm the effectiveness of the proposed methodology, which is reflected in the increase in student engagement and quality indicators of their learning. It is concluded that the introduction of cloud technologies in school education contributes to the creation of a personalized and accessible educational process, stimulating the use of modern digital tools to improve the quality of education. The expediency of the adaptive application of the technology of the « Flipped classroom» in educational practice is substantiated.

Using STEM Education and Machine Learning to Prepare Future Computer Science Teachers

The process of training future computer science teachers using the links of STEM education and machine learning as a field of artificial intelligence is considered. It is known that STEM education is being introduced and implemented in the education sector of the republic, and the concept of machine learning is being considered within the framework of technical specialties, its wide application in the training of future computer science teachers is not paid attention. The importance of teaching future computer science teachers to use machine learning algorithms in teaching STEM fields is noted. The rapid development of artificial intelligence, including machine learning, shows the need to introduce new subjects into the educational program for future computer science teachers, since computer science teachers are required to acquire new knowledge, skills in working with data and machine learning algorithms to apply them in future professional activities. The purpose of the proposed work is to introduce machine learning into the educational process of training computer science teachers, as well as using machine learning algorithms and methods in teaching STEM areas, to improve the content of education for training future computer science teachers.

A Thematic Literature Review of Decolonization and Abolitionist Approaches in Computing Education

This scoping review explores the role of critical and culturally responsive pedagogy in addressing the significant gap in computer science (CS) education. Despite ongoing efforts to increase diversity, many groups, including women, remain underrepresented in CS. The research draws on Paulo Freire's foundational ideas on critical pedagogy, advocating for a dynamic and ethical approach to teaching that fosters critical thinking and community involvement. The review also examines various interventions in literature which incorporate critical, decolonial, and abolitionist pedagogies in CS education. Addressing both the technical and social dimensions of computing, educators can equip students with the tools needed to challenge and transform existing power structures, contributing to a more just and equitable society.

Диверсифицированные подходы и стратегии формирования инженерного мышления у студентов педагогических вузов

The relevance of this research lies in the need to train highly qualified specialists with engineering thinking. These specialists are crucial for developing the country’s scientific and technical potential. The training of such specialists with a broad and flexible mindset starts from school, where the teacher plays a fundamental role. Objective: the goal of this study is to identify effective methods, approaches, and practices that can be used to develop engineering thinking in future teachers of physics and computer science and application of these methods and practices in the training of graduates from pedagogical universities. Hypothesis: the study hypothesizes that if the educational process in pedagogical universities is based on diverse approaches and strategies, it will contribute to the development of engineering thinking in students. Methods (tools): the research used various methods and tools to address the issue including theoretical research and analysis of publications in scientific journals on the subject of engineering thinking formation, synthesis and methods of logical generalizations, the questionnaire aimed at studying the readiness of future teachers to develop engineering thinking of students (by O. R. Schaefer, T. N. Lebedeva, S. V. Kraineva, and G. S. Kochetkova). Results: by assessing the potential for developing engineering thinking in the training of future teachers, we have described the experience of the Faculty of Mathematics, Physics, and Computer Science at the South Ural State Humanitarian and Pedagogical University in developing this type of thinking. The survey has shown to what extent intending teachers of physics and computer science are prepared to develop engineering thinking in their students. Main conclusions: using the technological tools available in subject laboratories of techno-parks, models of engineering research, and practice-oriented tasks allows intending teachers of physics and computer science to work more effectively with information that contains engineering solutions. This, in turn, helps them achieve the desired outcomes in developing engineering thinking. Practical Significance: The experience of developing engineering thinking in educational institutions can be applied in teacher training. The results of this research can be used to plan and optimize the system of professional development and retraining for teachers.

Variable Teaching of Artificial Intelligence and Data Analysis Basics in Computer Science General Education Course: Integrative Approach and Key Components of Methodology

The paper prepared in the context of mainstreaming artificial intelligence (AI) school teaching describes a model of AI and data analysis variant teaching of schoolchildren in computer science class and its components based on the integrative approach. The main aim of this study is to provide scientific and teaching community with the results of a methodological research that was carried out in Institute of Mathematics and Computer Science (Moscow Pedagogical State University) to develop methodological support for teaching schoolchildren topics related to AI technologies in both basic and secondary general education organizations and basic or advanced computer science classes. The paper summarizes current experience in AI and data analysis school teaching, with an integrative approach being the main methodological approach to designing a course for schoolchildren. The paper proposes the structure and the components of a methodology of variant teaching of AI and data analysis that considers project and extracurricular activities possibilities and the requirements of the Federal State Educational Standard of Basic General Education and the Federal State Educational Standard of Secondary General Education. The paper concludes that the model that is designed in accordance with the requirements of Federal State Educational Standard and which is in a sense an “ideal” model for teaching schoolchildren AI and data analysis basics can be interpreted by educational organizations, for example, to design various learning trajectories that meet the personal needs of schoolchildren, the technical and methodological capabilities of an educational organization, and the personal character of students. Moreover, the paper emphasizes that this model for variant teaching AI and data analysis basics centered on an integrative approach is already supported with practical educational learning materials for schoolchildren (Basic General Education and Secondary General Education level) and can be used by computer science teachers in their classroom, extracurricular, and project-research activities, as well as in preparing high school students for AI and data analysis Olympiads.

Social engineering as a component of professional competence in information security of future computer science teachers

The article considers the actual problem of information security - social engineering. The authors investigate what social engineering is and its main methods, including phishing, vishing, baiting, and pretexting, and analyze the educational programs of the speciality "014.09 Secondary Education (Informatics)" regarding the availability of relevant competencies. The article analyzes data on the components of professional competencies in information security and social engineering of the leading educational institutions of the USA, the EU, and Ukrainian higher education institutions; based on the analyzed data provided in general, the relationship between training in cyber security and social engineering. The authors also explore the role of future computer science teachers in protecting students from the threats of social engineering. They note that a critical factor in this protection is teaching students to recognize and eliminate social engineering threats and how to protect their sensitive information.

Improving CS Performance by Developing Spatial Skills

A dive into the research linking development of spatial skills with improved outcomes at all levels of CS education.

Computational Thinking in Undergraduate Pre-Service Special Education Programs

In the 21st century, an increased emphasis on integrating computational literacy within classrooms occurred (Bouck & Yadav, 2020). This learning representation aims to equip preservice special education teachers (PSSETs) with tools to deliver inclusive computational thinking (CT) and computer science (CS) instruction, fostering an understanding of CT/CS concepts and promotes integration across content areas. This technology-rich learning representation employs robots, interactive whiteboards, and a blend of unplugged and plugged CT activities to demonstrate how CT can be integrated into a PK-12 classroom. This learning representation concludes with an assessment tasking PSSETs to create an activity integrating CT. This approach prepares PSSETs to provide equitable and accessible CT/CS education, aligning with current educational priorities.

Robotic Badges for Girl Scouts

This three-day computer science (CS) robotics coding exploration targets three Girl Scouts (n.d.) Brownie (2nd/3rd grades) badges. For each badge, a 60-minute session follows the 5E instructional model, which incorporates various robots to provide learners with diverse coding experiences. Throughout the coding exploration, learners engaged with real-life robot applications and used different robots to complete coding challenges. This learning exploration concluded by having learners complete at least one robot coding challenge per session, tailored to their capability, and utilize their expressive language skills to describe and explain their designed artifacts, algorithms, and block-based codes. This coding exploration can be extended to support broader elementary-level CS instruction.