Computer Science Education Research Articles

Teachers' and students' perceptions of AI-generated concept explanations: Implications for integrating generative AI in computer science education

The educational application of Generative AI (GAI) has garnered significant interest, sparking discussions about the pedagogical value of GAI-generated content. This study investigates the perceived effectiveness of concept explanations produced by GAI compared to those created by human teachers, focusing on programming concepts of sequence, selection, and iteration. The research also explores teachers' and students' ability to discern the source of these explanations. Participants included 11 teachers and 70 sixth-grade students who were presented with concept explanations created or generated by teachers and ChatGPT. They were asked to evaluate the helpfulness of the explanations and identify their source. Results indicated that teachers found GAI-generated explanations more helpful for sequence and selection concepts, while preferring teacher-created explanations for iteration (χ2(2, N = 11) = 10.062, p = .007, ω = .595). In contrast, students showed varying abilities to distinguish between AI-generated and teacher-created explanations across concepts, with significant differences observed (χ2(2, N = 70) = 22.127, p < .001, ω = .399). Notably, students demonstrated difficulty in identifying the source of explanations for the iteration concept (χ2(1, N = 70) = 8.45, p = .004, φ = .348). Qualitative analysis of open-ended responses revealed that teachers and students employed similar criteria for evaluating explanations but differed in their ability to discern the source. Teachers focused on pedagogical effectiveness, while students prioritized relatability and clarity. The findings highlight the importance of considering both teachers' and students' perspectives when integrating GAI into computer science education. The study proposes strategies for designing GAI-based explanations that cater to learners' needs and emphasizes the necessity of explicit AI literacy instruction. Limitations and future research directions are discussed, underlining the need for larger-scale studies and experimental designs that assess the impact of GAI on actual learning outcomes.

Enhancing Class 6 Computer Education with Flash-Based Multimedia at Bukit Islamiah

This research focuses on developing practical and efficient media for computer systems material aimed at grade 6 students. Employing the ADDIE model, the study progresses through analysis, design, development, and implementation stages to craft a flash-based interactive multimedia. A small-scale trial involving 5 students indicates promising results, with validation scores from media and material experts at 87% and 78%, respectively. Moreover, the average student response stands at 87.2%, affirming the suitability of the developed multimedia for learning purposes. This research underscores the potential of interactive multimedia in enhancing educational experiences, particularly in computer science education for young learners. Highlights : Implementation of ADDIE model ensures systematic development. Flash-based multimedia yields high validation scores from experts. Student response supports suitability for educational use. Keywords: Interactive multimedia, Grade 6 education, Computer systems, ADDIE model, Learning efficiency

UNDERSTANDING THE CHALLENGES OF TEACHING COMPUTER SCIENCE SUBJECTS FROM SCHOOL TEACHERS’ PERSPECTIVE

The implementation of Computer Science (CS) in Malaysian secondary schools aims to develop digital proficiency among youths. Despite this, Kedah state has seen fluctuating enrolment in CS elective subjects for the Sijil Pelajaran Malaysia (SPM) exam between 2018 and 2021, which contrasts with the increasing popularity of CS programs in higher education and the rising demand for CS skills.Addressing the challenges teachers face in delivering CS subjects is crucial, including issues like inadequate training, limited resources, language barriers, and diverse student backgrounds. This study uses a quantitative approach with self-developed questionnaires distributed among experienced CS teachers in Kedah to identify these challenges and propose solutions. Findings reveal a mix of experienced and less experienced teachers, mostly with medium-level proficiency. The study highlights difficulties in teaching Form 4 and Form 5 content and suggests improvements through professional development, collaboration, hands-on experiences, and updated resources to enhance teaching effectiveness and better align secondary education with higher education and job market needs.

Reconstruction of Transformative CS Topics in Education: A Model Proposal for Artificial Intelligence

From an educational perspective, artificial intelligence (AI) poses new challenges for computer science education due to its unique nature. In addition to its highly complex content and strong social relevance, the topic has further characteristics that distinguish it from typical computer science topics. Although there are many learning materials on AI, there is a lack of systematic approaches that take a holistic view of AI from an educational perspective and analyze the unique features of the topic in more detail. We develop a model that analyzes the actors and layers of educational processes regarding AI and outlines their relationships. The subsequent comparison with the Model of Educational Reconstruction for Computer Science Education permits conclusions for its practical consequences. Furthermore, a process model for introducing topics like AI into the classroom is proposed.

Exploring the impact of psychosocial learning environments and instructional modalities on academic achievement in blended computer science education

Exploring the impact of psychosocial learning environments and instructional modalities on academic achievement in blended computer science education

Is being clever enough? Young people’s construction of the ideal student in computer science education

ABSTRACT Popular discourses of computing and computer science can often frame the sector and the people within it as highly intelligent yet socially challenged, contributing to stereotypes that can potentially exclude those perceived to lack these skills or characteristics. For young people, such stereotypes can influence their educational and career aspirations, especially if there are discrepancies between their own identity and perceptions of what is desirable for computer science students. Drawing on open-ended questionnaire data from 3235 young people in England (aged 11–16), we collected 9442 keywords that students used to describe their “ideal student” in computer science education. An understanding of these perceptions allows us to recognise the prevailing stereotypes that may be shaping young people’s views and aspirations. In this paper, we employ an innovative large-scale descriptive analysis of the most common words that students use to describe the ideal computer science student, including its differences, if any, by students’ demographic background (e.g. gender, ethnicity, free school meal) and responses to the questionnaire (e.g. aspirations to be a computer scientist). We tentatively identified eight clusters of popular ideal student characteristics, namely being Smart & Clever; Knowledgeable & Interested; Determined & Hardworking; Kind & Helpful; Creative; Independent; Confident; and Collaborative. By examining how students imagine the ideal student in computer science, we gain better understanding of their educational aspirations and choice of study and provide educators with valuable insights to potentially challenge and reshape these perceptions. These insights can inform educational interventions to foster a more inclusive computing education.

Improving the training on creating a distance learning platform in higher education: evaluating their results

The COVID-19 pandemic has had a profound impact on the world, and one of the many changes it has brought about is the shift to distance learning in Kazakhstan’s universities. However, both teachers and students were ill-prepared for this sudden change. In some remote villages, lack of internet access meant that students had no access to online classes at all. To address this issue, universities had to rent foreign platforms, but these platforms had inadequate information security measures in place. To address these challenges, it is necessary to create a robust and secure independent platform for distance learning. This platform will be particularly important for training teachers of “Informatics” in the context of distance learning. This article presents methods and schemes for creating a distance learning platform specifically for training computer science teachers. The introduction of the “Education-Online Platform” discipline at the university has yielded promising results. As a result, a distance learning platform has been created, and this new discipline has been introduced and tested in the educational program of a particular university in the training of future specialists.

On the relationship between Mathematics- and Computer Science Education

On the relationship between Mathematics- and Computer Science Education

TRAINING FUTURE COMPUTER SCIENCE TEACHERS TO USE ARTIFICIALINTELLIGENCE TECHNOLOGIES IN THE EDUCATIONAL PROCESS

The article discusses the training of future computer science teachers to use artificial intelligence (AI) technologies in education. The authors highlight the relevance of this issue in light of the rapid spread of AI technologies in various spheres of life and the need to develop students’ digital competencies related to the use of artificial intelligence. The study aims to identify the essential competencies that future computer science teachers need to effectively use AI in education. It also analyzes the existing problems and challenges in this area, studies the prospects for the use of AI in education, develops recommendations for improving relevant training programs, and overcoming barriers to the implementation of AI technologies. The study identified three main groups of competencies for future computer science teachers in the field of AI: technical, pedagogical, ethical and legal. Technical competencies include knowledge of AI technology principles, algorithms, and software. Pedagogical competencies relate to the ability to adapt teaching materials and methods to the capabilities of AI and to develop appropriate tasks and projects. Ethical and legal competencies involve comprehending the risks and challenges associated with AI usage, as well as being aware of the ethical principles and legal norms in this field. The article analyzes technical, pedagogical, ethical, and legal problems related to introducing AI technologies into computer science teacher training and education. It also explores the potential benefits of AI in education, such as personalized and adaptive learning, improved teaching and assessment effectiveness, and the development of critical thinking and creativity in students. The authors suggest methods to enhance computer science teacher training programs, such as incorporating specialized AI courses, providing practical training, and involving industry experts. They also stress the significance of considering the most effective international practices in this field. To summarize, the article highlights the pressing need to modernize the computer science teacher training system in Ukraine. This is necessary to develop the competencies required for the effective use of AI technologies in the educational process. Such modernization will contribute to the development of students’ digital literacy and ensure the competitiveness of the Ukrainian educational system in the context of digital transformation.

РОЗВИТОК КРИТИЧНОГО МИСЛЕННЯ МАЙБУТНІХ ВЧИТЕЛІВ ІНФОРМАТИКИ ТА МАТЕМАТИКИ З ВИКОРИСТАННЯМ ЗАСОБІВ ШТУЧНОГО ІНТЕЛЕКТУ

The article examines the problems of developing critical thinking of future teachers of computer science and mathematics using artificial intelligence tools. The experience of domestic and foreign researchers regarding the use of artificial intelligence in education for the development of critical thinking, in particular, the United States of America, the Republic of Poland, and the Republic of Slovenia, was analyzed. The necessary components of critical thinking are defined: the use of logical thinking to analyze problems, make decisions and solve problems; obtaining, interpreting and using knowledge/facts/data in the process of solving problems; demonstration (manifestations) of creativity and non-standard thinking. In order to investigate the specifics of the application of critical thinking skills by future teachers of computer science and mathematics when working with artificial intelligence systems, a survey was conducted. The "Klochko Questionnaire: Peculiarities of using critical thinking skills by future teachers of computer science and mathematics when working with artificial intelligence systems" was created. The possibilities of using artificial intelligence tools in education have been clarified, in particular: analysis of educational data, creation of educational content, professional development, adaptive learning, and others.The results of the study showed that 92.2% of respondents use or plan to use artificial intelligence tools in the educational process. The vast majority of students studying to become computer science and mathematics teachers actively use artificial intelligence to solve various problems, applying critical thinking and developing their critical thinking skills. The development of critical thinking skills of future computer science and mathematics teachers is a necessary condition for their academic success, personal and professional development, competitiveness, preparation for future challenges, solving new problems, teaching students to think critically. The implementation of artificial intelligence tools for the development of critical thinking in future teachers may have certain risks, such as excessive trust in artificial intelligence and the reduction of the role of one's own experience, intuition, etc. It is important to note that the field of using artificial intelligence technologies in education is just beginning to develop and needs additional research, however, it has great potential for the development of critical thinking of future teachers.

РЕАЛІЗАЦІЯ ДИФЕРЕНЦІЙОВАНОГО ПІДХОДУ ПРИ НАВЧАННІПРОГРАМУВАННЮ МОВОЮ PYTHON ЗДОБУВАЧІВЗАГАЛЬНОЇ СЕРЕДНЬОЇ ОСВІТИ

Students choose their future path starting from school. The learner can determine their abilities when they genuinely understand their potential and prospects in a specific subject or direction. A differentiated approach helps explore the limits of knowledge and encourages its expansion. The paper discusses the implementation of a differentiated approach in teaching computer science, particularly in programming. Tasks are proposed to students, emphasizing the method of solving. Each learner chooses the method that suits them best. Evaluation criteria are provided in advance, helping students identify the aspects of the task to focus on. An example task demonstrating the implementation of a differentiated approach involves calculating the recommended body weight for a woman and a man using the Broca's Formula. Depending on the complexity chosen by the student, this task can be solved using a linear structure, applying branching, or developing a widget. Widgets allow students to demonstrate the use of libraries and functions in the Python programming language. Various solutions in Python and recommendations for the placement of such tasks in the study of a specific topic are also provided. During the defense, all students become acquainted with different task implementations, allowing each student to understand various execution methods and choose a more challenging one next time. The presented example can be extended to other topics, in the study of other programming languages or programming environments. Prospects for further research include developing a system of multi-level programming tasks for the purpose of implementing differentiated learning

Data-related concepts for artificial intelligence education in K-12

Due to advances in Artificial Intelligence (AI), computer science education has rapidly started to include topics related to AI along K-12 education. Although this development is timely and important, it is also concerning because the elaboration of the AI field for K-12 is still ongoing. Current efforts may significantly underestimate the role of data, the fundamental component of an AI system. If the goal is to enable students to understand how AI systems work, knowledge of key concepts related to data processing is a prerequisite, as data collection, preparation, and engineering are closely linked to the functionality of AI systems. To advance the field, the following research provides a comprehensive collection of key data-related concepts relevant to K-12 computer science education. These concepts were identified through a theoretical review of the AI field, aligned through a review of AI curricula for school education, evaluated through interviews with domain experts and teachers, and structured hierarchically according to the data lifecycle. Computer science educators can use the elaborated structure as a conceptual guide for designing learning arrangements that aim to enable students to understand how AI systems are created and function.

Meta Analisis Implementasi Computational Thinking untuk Meningkatkan Hasil Belajar Ipas di Sekolah Dasar

This study aims to analyze relevant research in implementing the computational thinking approach to improve learning outcomes in Integrated Science (IPAS) at the Elementary School level. The study adopts a meta-analysis approach with data collection conducted through searching Google Scholar or Google Scholar and Mendeley using the keywords computational thinking, learning outcomes, and science education in elementary schools. The search yielded a total of 7 articles that utilized the computational thinking approach in teaching science at the elementary school level, employing qualitative research methods. The findings of the study indicate that the implementation of computational thinking in IPAS instruction at the Elementary School level can provide significant benefits in developing critical thinking skills, problem-solving abilities, teamwork, learning interest, and students' digital readiness. Therefore, it can be concluded that the positive implementation of computational thinking contributes to improved learning outcomes and skill development in students. The results of this research are expected to serve as recommendations and a foundation for enhancing students' learning outcomes through the application of computational thinking in the teaching and learning process. Keywords: Computational Thinking, Learning Outcomes, Science, Elementary School

The Impact of AI on Computer Science Education

Understanding why “working hard and struggling is … an important way of learning.”

Fostering Equity in Computer Science Education: Principles from a Feminist Standpoint Conceptual Framework

Fostering Equity in Computer Science Education: Principles from a Feminist Standpoint Conceptual Framework

Using the gaming chatbot to develop algorithmic and logical thinking skills

The use of special computer games in classes increases student engagement and maintains their interest in learning, including learning computer science. Due to the logical and rational nature of solving programming problems, logic games and puzzle games that develop cognitive abilities, logical and algorithmic thinking are well suited for teaching computer science. Considering the popularity of Wordle puzzle game and the fact that word games are very effective for developing cognitive abilities, a gaming chatbot with puzzle tasks organized according to Wordle principles was developed for learning computer science and programming. The aim of the article is to investigate the effect of the developed gaming chatbot on students’ algorithmic and logical thinking.The study involved 3rd year undergraduate students of the educational program “Information Systems and Technologies”, Faculty of Information Technologies, Moscow Polytechnic University. The students used the gaming chatbot outside of class for 10 days and completed surveys before and after use. The analysis of the students’ surveys showed the impact of this gaming chatbot on the activation of memory, attention and to a greater extent logical thinking of the students, as well as on assessing students’ perception of the complexity of programming, their own knowledge of programming languages and logical thinking skills.The results of the study expand current ideas regarding the use of gaming chatbots and Wordle-type puzzle tasks in teaching computer science and programming. The presented gaming chatbot will help to increase students’ interest in classes, students’ involvement in the learning process, and ensure the development of their cognitive abilities.The conclusions of the article may be of practical interest to informatics and programming teachers. They contribute to the development of the direction of building gaming chatbots, as well as the use of word puzzles for teaching computer science.

Using an online platform in a didactic learning model that stimulates critical thinking skills of future informatics teachers

Critical thinking is a key competency for future computer science teachers, who must be prepared not only for the rapid technological and informational development of the economy and society but also for the actively evolving process of digitalization in education. The aim of the research presented in the article is to develop methods and tools for enhancing critical thinking skills among future informatics teachers. To this end, the author has created an online platform that provides students with access to a variety of educational resources, including lectures, laboratory work, and interactive tasks. By integrating constructivist, cognitive, and sociocultural approaches to learning, this model promotes deep understanding and analysis of information by students. The platform is physically hosted on the server of Termez State University, built using the Python programming language with the Django framework, and is already being used by second-year students majoring in “Mathematics and Informatics”, studying under the discipline “Informatics and Digital Technologies”.The online platform offers the necessary functionality for organizing independent study sessions and self-monitoring, allowing students to track their progress and develop the ability to critically evaluate information. The educational platform is a key component of the didactic model for developing critical thinking skills in future informatics teachers, the architecture of which is detailed in the article.The results of the study presented in the article can be utilized in the educational practices of higher educational institutions (and even schools) seeking to update and optimize their training processes in the context of digitalization.

California 4-H Computer Science Education Pathway

California 4-H Computer Science Education Pathway

An unplugged remix of culturally responsive computing for early childhood education

AbstractDespite a growing movement towards expanding computer science education in PreK‐12, gaps in computing opportunities along lines of race, ethnicity, class, and gender have widened. Emergent theories and practices related to culturally responsive computing show promise in addressing this gap; however, little is known about engaging Black, Latinx, and Indigenous preschoolers in computer science. In this paper, we utilized qualitative content analyses to explore how an early childhood computer science curriculum created opportunities for young Black and Latinx preschoolers to develop computational thinking skills while engaging in culturally responsive computing. Overwhelmingly, we found the curriculum, co‐developed with educators and caregivers, emphasized unplugged tools and coding activities to support computational thinking. These unplugged opportunities positioned children as innovators with technology and technosocial change agents, in developmentally‐appropriate, play‐based ways. Findings demonstrate a need to emphasize the value of unplugged tools and coding activities in order to support computational thinking and align the goals of culturally responsive computing with the unique needs of young children. We discuss implications for a theory of culturally responsive computing specifically for early childhood education.

Strategies for Computer Science Education in University

The study investigated the Strategies for Computer Science Education Programme at Kogi State University, Anyigba. The purpose of the study was specifically targeting the types of computer facilities, their importance in computer education, factors militating against effective use for teaching and learning and strategies to be adopted for effective teaching and learning. Four research questions and four hypotheses guided the study. A descriptive survey design was adopted for the study. 100 computer students were purposively sampled for the study. Computer Education Checklist (CEC) and Strategies for Computer Education Questionnaire (SCEQ) were used as data collection tools. Percentage, mean and standard deviation were used to analyze the data collected. Analysis revealed that (1) the types of computer facilities available for computer education are laptops, printers, computer laboratories, desktops, monitors, CPU and Diskettes, CDs and flash (2) the benefits of computer education are that computer education programme enhances efficiency in teaching and learning, makes instruction in the class to be lively, and enhances individualization of learning among others, (3) several factors militate against computer education programmes in the study area are lack of skills, cost of the facilities, weak infrastructure, lack of relevant software, limited access to the internet and others and (5) strategies to handle the challenges above are that computer training for teachers, procurement of hardware facilities, curriculum development, and software development, maintenance of computer systems, adequate funding, and increase in government allocation to computer studies and provision of internet facilities should be used.