Analysis of AI Ethical Competence to Computational Thinking

The rapid advancement of Artificial Intelligence (AI) technology has brought about significant positive changes across society. However, it has also introduced challenges like privacy breaches, data bias, and spreading fake news. In response, several countries, including South Korea, have provided ethical guidelines and policies for AI. Yet, these measures often fall short of keeping pace with the speed and diversity of AI development. To address these issues, this study developed a comprehensive approach by integrating ethical considerations into AI education, covering the entire AI technology development and application process. It involved analyzing previous research on AI and AI ethics education and creating a draft of an integrated AI education program focused on problem-solving based on computational thinking and ethical practicality. The draft was refined and supplemented through two rounds of expert Delphi surveys, ultimately leading to an “Integrated AI Education Program.” This proposed program emphasizes that the knowledge content of AI technology and ethical considerations should not be treated separately but addressed together. It aims to enhance moral and social capacities alongside the experience of thinking like a computer scientist when solving real-life problems. Through this, the program supports the ultimate goal of AI education: to foster computational thinking while providing an educational experience that considers both technology and ethics. This study is expected to advance the discussion on integrating AI ethics into AI education curricula and contribute to developing socially responsible AI developers and users.

Computational thinking skill is an important skill individuals should acquire to meet the requirements of the digital age. The aim of the study is to predict the computational thinking skills of middle school students through ANFIS approach, which is an adaptive neural network-based fuzzy logic. Students' computational thinking skill scores were predicted by creating a model based on grade level and academic achievement variables. Grade level and academic achievement served as the model's input variables, and computational thinking skill scores served as the model's output variable. Data were collected using personal information form and computational thinking scale. A comparison was made between students' real and artificial computational thinking skill scores using statistical methods. In the study, a strong and favorable association between the artificial scores produced using the ANFIS technique and the actual scores was discovered. Furthermore, there was no statistically significant difference between the real and artificial scores for computational thinking skills. These results indicate that the ANFIS approach is a suitable alternative analysis method for predicting students' computational thinking skills. The study provides a good example in the field of education where artificial intelligence can be used to predict students' educational characteristics.

<span lang="EN-US">Based on the study, computational thinking skills are influenced by science, technology, engineering and mathematics (STEM) skills, and there is a relationship between computational thinking skills and 21st-century skills. However, studies related to STEM attitudes, computational thinking and their impact on 21st-century skills are still very few and limited. The purpose of our study was to examine the impact of STEM attitudes and computational thinking on 21st-century. This research uses a quantitative approach. The participants of this study were students of a vocational school in Bantul Regency, Yogyakarta, Indonesia (N=290). Research data in STEM attitude, computational thinking, and 21st-century skills using a questionnaire. The data were analyzed using structural equation modeling techniques using the Smart PLS application. The results of the study obtained several findings, including: the model proposed in this study was valid; STEM attitude has a positive and significant effect on computational thinking; and computational thinking has a positive and significant effect on 21-st century skills. It can be argued that when STEM attitudes and computational thinking are more positive, 21-st century skills will improve. These findings have implications that curriculum development and STEM learning practices have to develop students’ computational thinking skills and 21st-century skills, especially in vocational schools.</span>

This research aims to examine the effect of Mind Games activities on problem-solving skills and computational thinking skills of 5th grade students. Sequential explanatory design, one of the mixed research methods, was used in the research. The research was carried out in a quasi-experimental design pretest-posttest without a control group with 17 5th grade students in a secondary school in Adıyaman. The research was carried out with an experimental period of 6 weeks. Before the experimental study, the problem-solving skills and computational thinking skills scales were applied to the students as a pre-test. Kapsul game activity was performed in the first week of the experimental study. ABC Baglama activity was held during the week. Sudoku activity was held in the 3rd week. In the 4th week, Three Stone game activities were held. Kendoku game activity was held in the 5th week. In the 6th week, Kakuro game activity was held. Statistical values in the study were calculated using the SPSS program. To collect quantitative data, a pre-test of problem-solving skills and computational thinking skills was applied to the students before the experimental process. After the experimental process, problem-solving skills and computational thinking skills scales were applied as a posttest. The applied pre-test and post-test results were analyzed with the paired sample t-test. Additionally, to collect qualitative data to strengthen the research, an interview form was applied to obtain the opinions of the students about the experimental process. In line with the findings obtained because of the experimental study, it can be said that the mind game activities have a positive effect on the students' computational thinking and problem-solving skills, and the lesson turns into more fun.

Two studies were conducted to examine the use of grounded embodied pedagogy, construction of Imaginary Worlds (Study 1), and context of instructional materials (Study 2) for developing learners' Computational Thinking (CT) Skills and Concept knowledge during the construction of digital artifacts using Scratch, a block-based programming language. Utilizing a conceptual framework for grounded embodied pedagogy called Instructional Embodiment, learners physically enacted (Direct Embodiment) and mentally simulated (Imagined Embodiment) the actions and events as presented within pre-defined Scripts. Instructional Embodiment utilizes action, perception, and environment to create a dynamic, interactive teaching & learning scenario that builds upon previous research in embodied teaching and learning. The two studies described herein examined the effects of Instructional Embodiment, Imaginary World Construction, and Context on the development of specific Computational Thinking Concepts and Skills. In particular, certain CT Concepts, such as Conditionals, Variables, Thread Synchronization, Collision Detection, & Events, and CT Skills, such as abstraction and pattern recognition, were identified and measured within the learners' individual digital artifacts. Presence and/or frequency of these Concepts and Skills were used to determine the extent of Computational Thinking development. In Study 1, fifty-six sixth- and seventh-grade students participated in a fifteen-session curricular program during the academic school day. This study examined the type of instruction and continuity of Imaginary World Construction on the development of certain CT Skills and Concepts used in a visual novel created in Scratch. Main effects were found for learners who physically embodied the pre-defined instructional materials: embodying the pre-defined Scripts led to the learners using significantly more ‘speech’ Blocks in their projects and more Absolute Positioning Blocks for ‘motion’ than those who did not physically embody the same Scripts. Significant main effects were also found for continuity of Imaginary World Construction: learners who were instructed to continue the premise of the first digital artifact (Instructional Artifact) implemented significantly more computational structures in their second digital artifact (Unique Artifact) than those who were instructed to create a Unique Artifact with a premise of their own design. In Study 2, seventy-eight sixth- and seventh-grade students participated in a seventeen-session curricular program during the academic school day. This study examined the type of instruction and context of instructional materials on the development of CT Skills and Concepts during the construction of a video game using Scratch. Similar to Study 1, findings suggest that physically embodying the actions presented within the pre-defined instructional materials leads to greater implementation of many of these same structures during individual artifact construction. The study also showed that as the pre-defined Scripts become more complex (e.g. single-threaded to multi-threaded), the effect of physical embodiment on the development of CT Skills and complex CT Concept structures becomes less pronounced. Findings from this study also suggest that Context has a significant effect on identifying & implementing the CT Skill pattern recognition: learning CT Concepts from an Unfamiliar Context had a significant positive effect on the implementation of both Broadcast/Receive couplings and Conditional Logic & Operator patterns. In sum, the findings suggest that the type of instruction, the continuity of the Imaginary World being constructed, and the context of the instructional materials all play a significant role in the learners' ability to develop certain Computational Thinking Skills and Concept knowledge. The findings also suggest that a physically embodied approach to teaching abstract concepts that is grounded in an unfamiliar context is the most effective way to integrate a grounded embodied approach to pedagogy within a formal instructional setting.

This research aims to create a tool for assessing students' computational thinking (CT) skills in relation to biology concepts. The study followed a research and development approach, utilizing a modified 4D design model, with the dissemination phase excluded. Various data collection techniques were employed, including observations, literature reviews, documentation, surveys, interviews, and tests. The findings showed that the developed instrument was valid, having been evaluated by three experts. The material expert rated it at 95%, the assessment and evaluation expert at 88%, and the linguist at 90%. In terms of readability, the instrument scored 75%, indicating a "good" rating. The overall validity of the instrument was found to be 0.70, placing it in the high validity range, while its reliability score was 0.82, reflecting a very high level of dependability. The assessment of students' computational thinking skills in biology revealed that 25% of students scored in the low range, 28% in the medium range, and 57% in the high range. From these findings, it can be concluded that the CT test tool is both valid and appropriate for evaluating students' computational thinking skills.

Objective: The study aimed to identify the attitudes of music skills teachers in Oman towards the use of artificial intelligence (AI) in teaching and to understand the challenges they face in integrating AI into their teaching methods. Theoretical Framework: The proliferation of modern learning resources and technological advancements, especially the emergence of artificial intelligence, have significantly impacted educational institutions. Oman is striving to align its education system with the digital transformation outlined in Oman Vision 2040, which emphasizes high-quality education, the integration of technology, innovation, entrepreneurship, and skill-building. Method: This study adopted a descriptive analytical method, analyzing a questionnaire completed by music skills teachers in Oman regarding their opinions on AI in teaching. The survey focused on three main axes: knowledge of AI, its use in teaching music skills, and the challenges faced by teachers in integrating AI into their practice. Results and Discussion: The results indicated that music skills teachers in Oman have a positive attitude towards the use of artificial intelligence in teaching. Regarding knowledge of AI, the statement "I strive to develop my knowledge about artificial intelligence and its applications in various fields" received the highest mean score of 4.14 with a standard deviation of 0.808, showing a strong commitment to learning about AI. In terms of using AI in teaching music skills, the statement "I intend to use artificial intelligence technologies in the future" ranked highest with a mean score of 4.24 and a standard deviation of 0.761, reflecting a positive intention to integrate AI into their future teaching practices. However, when it came to challenges, the statement "Lack of specialized training in artificial intelligence for music skills teachers" emerged as the most significant barrier, with the highest mean of 4.26 and a standard deviation of 0.782, pointing to the lack of adequate training as the primary obstacle in AI adoption for teaching music skills. Conclusion: The study concludes that music skills teachers in Oman generally have positive attitudes toward the use of AI in teaching. However, the main challenge identified was the lack of specialized training for teachers, which hinders the effective implementation of AI in music education. Research Implications: This research highlights the need for better training and resources for teachers to effectively incorporate AI in their teaching practices. It also emphasizes the importance of curriculum updates to align with AI advancements. Originality/Value: This study provides valuable insights into the perspectives of music skills teachers in Oman on the integration of AI in teaching, contributing to the growing body of research on AI in education in the Middle East. Contributions: The study contributes to the understanding of the role of AI in music education, specifically in Oman, and identifies key barriers that must be addressed for effective integration.

Artificial intelligence (AI) has been integrated into various fields, accelerating innovation in existing ones. Consequently, AI has been employed in education to drive changes such as learning analytics and personalized learning. Recently, the development of generative AI has further transformed the educational landscape. Given the increasing use of generative AI in education, this study was conducted to explore its educational applications. We developed an educational program incorporating generative AI based on design thinking principles for high school students. To verify its effectiveness, high school students in Korea were selected as research subjects and divided into an experimental group (n=53) and a control group (n=42). A test tool aligned with the 2022 revised curriculum in Korea measured computational thinking skills. The study results showed that the group receiving AI convergence education using generative AI significantly improved their computational thinking. The improvement in computational thinking was also significant compared to the control group, providing strong evidence of the benefits of AI in education. This study confirmed that AI convergence education, utilizing generative AI grounded in design thinking, effectively develops computational thinking skills in high school students. The findings of this research highlight the potential educational value of integrating generative AI into both AI design thinking and convergence education. The study provides reassurance that generative AI can be a powerful tool in enhancing student learning experience and outcomes, paving the way for future educational innovations.

This research aims to critically examine the ethical integration of artificial intelligence (AI) in education through the perspective of maqāṣid al-sharīʿah, emphasizing the alignment between technological innovation and Islamic moral principles. The methods used are a systematic literature review and thematic content analysis against peer-reviewed publications for the period 2015–2025, which discuss the application of AI in primary, secondary, and higher education. The study identified dominant ethical issues, such as data privacy, algorithmic bias, accountability, human agency, and moral development, which were then mapped to Islamic ethical goals, including ʿadl (justice), amānah (belief), karāmah al-insān (human dignity), and ḥifẓ al-ʿaql (protection of reason). The results of the analysis show that the adoption of AI in education often emphasizes efficiency, personalization, and predictive analytics, but has the potential to reduce learners' autonomy and ethical reasoning. The mapping of maqāṣid al-sharīʿah shows a strong normative conformity, so that Islamic principles can be a moral foundation as well as a practical guide for AI governance. The research contribution is theoretical by bridging the literature on AI ethics and Islamic educational philosophy, as well as practical by offering an integrative framework for AI policymakers, educators, and developers. The integration of maqāṣid al-sharīʿah in AI governance ensures justice, trust, inclusivity, and the development of the whole human being (insān kāmil).

The integration of Artificial Intelligence (AI) in non-formal, informal and formal education is an emerging area with great potential to transform the world. However, the capacity of educators, youth workers and teachers to capitalise on this potential remains limited due to a lack of well-defined frameworks for AI integration in practices. The scope of this study is to explore the needs, challenges, and perspectives of youth work professionals regarding AI integration.The research methodology employed mixt research methods. The literature review was followed by four semi-structured focus groups involving 72 youth workers and professionals with diverse backgrounds, nationalities and experience levels. A common guideline was used to ensure consistency, including facilitator instructions, discussion prompts, and reporting templates. The data collected during the focus groups were analysed using a Computer-Assisted Qualitative Data Analysis Software (CAQDAS), ATLAS.ti software dedicated to qualitative research. The authors conducted qualitative analysis, through coding, identification of main categories, thematic map for visualization of results, and interpretation of findings to uncover patterns and deeper insights. The results revealed a generally positive attitude toward AI tools and an awareness of their potential benefits in youth work, particularly in content creation. However, participants reported significant challenges regarding the use of AI for administrative tasks efficiency, for personalised learning, ethical concerns, and difficulty in interpretation of data. Cross-country similarities emerged, suggesting a shared need for capacity building and continuous training, while differences highlighted the influence of national contexts and digital infrastructure.This study provides a foundational understanding of the competence needs of youth workers in relation to AI adoption. The findings are relevant for course designers wishing to offer targeted training for youth workers. Future research is also needed into policy-level support mechanisms that can enhance AI literacy and ethical integration across the sector.

This study attempts to enhance high school learners' computational thinking and mathematical resilience skills. This study employs quantitative approaches with a quasi-experimental research design, and the type of research is Non-Equivalent Group Design. The tools used in this study were computational thinking skills tests and mathematical resilience questionnaires. From the results of the survey conducted, it is known that: 1) the Project Learning model accompanied by GeoGebra significantly improves computational thinking skills, and Project-Based Learning model has moderate improvement; 2) computational thinking skills of high school students who were taught through Project-Based Learning model aided by GeoGebra improved significantly compared to those taught with the Project-Based Learning model; 3) Project-Based Learning model aided by GeoGebra has a positive effect on the mathematical resilience of high school students, but only to a moderate extent.

Problem-based learning integrated with Digital Argumentation (PBL-DA) is a learning strategy for optimizing innovative learning in the digital era. This research aimed to investigate whether the application of PBL-DA can foster the Computational Thinking (CT) and Higher Order Thinking Skills (HOTs). A quasi-experimental design measured three aspects: skill (decomposition, algorithm design, evaluation), attitude (confidence, communication, flexibility), and approach (tinkering, creating, collaborating). The students' HOTs were measured through eight aspects: critical thinking, argumentation, problem-solving, problem-identifying, understanding concepts, analysing, making decisions, and creative thinking. The students' CT and HOTs scores of control and experimental classes were analyzed using Hotelling’s T² test and Tukey’s post hoc test. The Hotelling’s T² test revealed a significant difference between the experimental and control classes for both CT and HOTs (T² = 0.340, p < 0.001 for CT; T² = 0.718, p < 0.001 for HOTs). Tukey’s test further showed that PBL-DA significantly impacted the CT skill and attitude aspects (p < 0.01), while the approach aspect was not significant (p > 0.05). For HOTs, critical thinking, argumentation, problem-identifying and analyzing were significantly improved (p < 0.01), but problem-solving, understanding concepts, making decisions, and creative thinking showed no significant improvement (p > 0.05). Pearson’s correlation analysis indicated a strong positive correlation (r = 0.651, p < 0.001) between students' CT and HOTs skills. These findings provide evidence of the effectiveness of the PBL-DA model in improving students' CT and HOTs, demonstrating its potential for fostering critical and higher-order thinking skills in the digital era.

In recognition of the integration of Information and Communications Technology (ICTs) along with Artificial Intelligence (AI) into education, several educational organizations have recommended cultivating 21st-century digital skills as part of every educational curriculum. The computational thinking skill, which is at the core of 21st-century digital skills, has gained research in several fields, such as physics and psychology (Barkela et al., 2024). However, applied linguistics and computer-assisted language learning (CALL) have overlooked this crucial skill, which might stem from the lack of language teachers’ computational thinking competency. For this reason, in the present study the researchers developed a new theoretical framework, and it’s corresponding scale specifically designed for applied linguistics and CALL, namely the Language Teachers’ Computational Thinking Competency in Computer Assisted Language Learning (LTCCTCALL). Using deductive and inductive methods, the researchers developed the items, followed by a validation process that used the Rasch-Andrich rating scale model (RSM) to assess the scale’s item difficulty and validity using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). LTCCTCALL was validated with five factor structures that included 15 items in the Iranian EFL context, involving 273 Iranian in-service language teachers. Based on this result, the study introduced a new theoretical framework and its scale to the fields of CALL, applied linguistics, and the Common European Framework of Reference for Languages (CEFR) to lead the community’s continued growth and to prevent the community from falling behind other fields that incorporate computational thinking skills into our classrooms to have problem-solving approaches with CALL, AI, and chatbots in language class.

Computational thinking is a new concept that is hardly known by most ordinary Malaysians. On a positive note, in 2017, the Ministry of Education of Malaysia implemented a new curriculum by introducing two new secondary school subjects, namely Fundamental of Computer Science and Computer Science. These subjects contain five components of computational thinking called ‘techniques, which are taught to Form 1 and Form 4 students, respectively. Likewise, the Department of Teachers Education of Malaysia also introduced six components of computational thinking in its training programs. In contrast, there is a lack of attention to such a concept given to tertiary education. A preliminary survey was conducted in early 2019, which involved 50 students majoring in 21 educational programs. The findings showed 92% of the respondents had no knowledge regarding the computational thinking skill, signifying an urgent need to determine relevant components that characterize such a skill needed in educational programs, which according to Wing (2006) has numerous components. In this study, the researchers aimed to identify relevant components that characterize the computational thinking skill required for students in learning educational programs. An extensive review of documents published in leading online databases, such as IEEEXplore, Science Direct, and Web of Science, was carried out that yielded 116 articles. Further analysis reduced this number to 29 articles that were related to the characterization of the computational thinking skill with 66 components. Among these components, algorithm, abstraction, and decomposition were the top three components with the highest frequency of being cited in the selected articles, registering percentage points of 9.78%, 7.41%, and 5.35%, respectively. As such, the design and development of new instructional approaches for the teaching of educational programs should emphasize three components to help students develop strong computational thinking skills.

The graphics calculator (GC) is a hand-held technology. With it, students visualize and understand concepts in mathematics and science better. It also allows them to make real-world connections, binding together advanced graphing functionality and conceptual science, technology, engineering, arts and mathematics (STEAM). As they gain a deeper understanding of abstract concepts, they acquire creative and critical thinking and problem- solving skills they need to reach greater academic successes. In learning, GC plays several roles in increasing students’ computational thinking and procedural skills. Despite being a learning tool that satisfies science and mathematics curriculum needs, the calculator often has been used as an add-on to traditional teaching methodology rather than central and in more integrated ways. This study looks into the potential of developing computational thinking skills using GC technology. The data of the study was obtained from secondary sources through a systematic review method. The study showed that GC seems to be effective tools to practice STEAM education as well as to develop students’ computational thinking through analysing and decompose real problem as well as engaging in the abstraction process and developing an algorithm using coding. The findings provides justifications on the impact of GC in developing computational thinking skills thereby maximizing the pedagogical benefits to students.