The contemporary age has been marked by a significant paradigm shift towards digital transformation. In the context of the rapid advancements in digital technology, society is confronted with novel possibilities, which is accompanied by substantial ch...
The contemporary age has been marked by a significant paradigm shift towards digital transformation. In the context of the rapid advancements in digital technology, society is confronted with novel possibilities, which is accompanied by substantial changes in the educational sector. The Korean Ministry of Education has adopted digital education as its core policy, and education utilizing artificial intelligence, big data, and learning analytics is becoming more widespread. The government has distributed digitized textbooks to elementary, middle, and high schools nationwide. These applications include "Smart Mathematics Exploration Team" and "AI PengTalk." In the private sector, generative AI-based educational technology markets, including "ChatGPT," "Teachable Machine," and "Grammarly," are experiencing significant growth and being introduced into educational settings. Moreover, the 2022 revised curriculum 2022 includes artificial intelligence as an official subject. Additionally, the notion of "AI integrated education," which integrates artificial intelligence with subjectmatter education, is garnering increasing attention. Consequently, AI is precipitating substantial transformations in the content, methodologies, and direction of education. Education is thus undergoing a gradual evolution toward a novel paradigm of "AI-based education."
However, the integration of AI in educational settings presents both novel opportunities and significant challenges. As artificial intelligence (AI) technology continues to advance, concerns regarding social anxiety are escalating. For instance, AI errors can yield inaccurate feedback, and personal information leaks can result in violations of student privacy. This phenomenon can lead to a wide range of detrimental consequences, including physical and emotional distress, as well as the escalation of social issues. Consequently, in the context of education, the implementation of AI must be approached with caution, ensuring the preservation of the dignity of students, teachers, parents, and other stakeholders, as well as the upholding of public values. An approach that prioritizes efficiency and effectiveness without considering ethical implications can potentially compromise the fundamental principles of education. The utilization of AI should not be regarded as a mere declaration; rather, it should be acknowledged as a tangible issue that has the potential to jeopardize human dignity and the social responsibility of education.
Teachers play a critical role in the integration of AI into education, as they are responsible for designing and implementing lessons. Consequently, the training of educators is imperative for the responsible utilization of AI. However, the prevailing professional development programs for educators predominantly emphasize the practical application of AI tools, offering only limited attention to the ethical considerations surrounding these technologies. Consequently, it is imperative to implement comprehensive AI ethics training to empower educators to identify ethical issues, engage in critical reflection, and respond appropriately. The objective of this study is twofold: first, to develop educational principles and models for enhancing teachers' AI ethics competencies, and second, to empirically verify the validity and effectiveness of these models. To this end, the model research approach was employed. This approach is considered to be among the design and development research methodologies suitable for generating practical knowledge by linking theory and practice in the field of educational technology.
The study was conducted in three primary stages. First, a systematic literature review and interviews with current teachers were conducted to derive the theoretical foundations for educational principles and models, and to analyze educational needs. A review of existing AI ethics education goals, content, and methods was conducted, and individual interviews were carried out with eight in-service teachers, followed by thematic analysis. Secondly, based on the analysis results, initial educational principles and models were developed, and internal validity was ensured through repeated reviews by nine experts in educational technology, ethics, and AI. Thirdly, the developed model was utilized to design educational workshops, which were subsequently conducted with a total of 27 teachers. The effects and reactions to the educational intervention were assessed through the administration of AI ethics competency tests, the analysis of reflection journals, satisfaction surveys, focus group interviews (FGI), and observational studies. In light of these findings, we have subsequently formulated principles and models for teacher education that are designed to enhance AI ethics competencies.
As a result of the study, four educational principles were derived: 1) ethical motivation principle, 2) cooperative interaction principle, 3) AI utilization principle, and 4) teacher-centered contextualization principle. First, 1) the ethical motivation principle consists of ① utilizing actual cases to encourage teachers to accept AI ethics as their own issue, ② cultivating a solution-oriented attitude toward AI ethics issues among teachers, ③ stimulate teachers' ethical imagination by encouraging them to reflect on the sustainability of AI technology, ④ present ethical challenges and provide teachers with the experience of solving them on their own, and ⑤ internalize ethical problem-solving procedures through reflective activities. This principle aims to help teachers recognize AI ethics as a personal and practical issue and to foster active participation and internal motivation based on ethical responsibility.
Second, the principle of collaborative interaction consists of two specific principles: ① Encourage teachers to interact with others through collaborative tasks to accept others' perspectives and clarify their own perspectives, and ② Provide teachers with experiences to establish the basis for their ethical decisions through dilemma discussions. This principle aims to deepen and expand teachers' ethical judgments through diverse perspectives.
Third, 3) The principle of AI utilization consists of three specific principles: ① Guide teachers who lack a basic understanding of AI to understand how AI works through AI experience activities; ② Consider the characteristics of teachers (e.g., school level, digital familiarity, community characteristics, age, etc.) when selecting AI tools for learning content; ③ Verify teachers' understanding of AI when conducting AI practice activities, and adjust the difficulty of assignments and lessons accordingly. This principle is designed to enable teachers to directly experience technical principles and develop concrete solutions to actual ethical problems.
Fourth, 4) The principle of teacher-centered contextualization consists of three specific principles: ① Construct cases using familiar content that reflects the occupational nature of teachers; ② Present realistic dilemma situations that are relevant to the school context to promote teacher engagement; ③ Introduce teachers to the goals and content of AI ethics education for their students to motivate learning. This principle aims to increase engagement and improve practical skills by providing examples that reflect actual educational settings.
Reflecting these four principles, the final AI ethics education model for teachers consists of three stages: “Understanding AI Ethics Traits and Necessity,” “Analyzing AI Ethics Issues in Education,” and “Evaluating AI Ethics Issues in Education,” as well as basic knowledge areas of “AI Ethics Principles” and “AI Technology.” At the core of the education model lies an ethics dilemma case bank, which enables customized instruction, developing cognitive, critical, and creative ethical competencies gradually.
The first stage, entitled "Understanding AI Ethics Traits and Necessity," aims to facilitate a comprehensive understanding of the fundamental concepts and the indispensability of AI ethics principles. This stage offers a comprehensive overview of relevant ethical issues in AI, drawing from authentic educational scenarios to assist educators in recognizing ethical concerns as personal issues and fostering a comprehensive understanding of the underlying rationales for ethical reasoning. The subsequent stage, entitled "Analyzing AI Ethics Issues in Education," employs authentic case studies to methodically examine and critically evaluate ethical concerns. This stage provides personalized, customized dilemma cases and analyzes them from various perspectives. The objective of this analysis is to help teachers accept the perspectives of others and refine their own judgment criteria. Ultimately, this process clarifies their ethical judgment process. The third stage, entitled "Evaluating AI Ethics Issues in Education," aims to derive creative and practical ethical solutions. In this stage, participants establish priorities for various ethical values and establish practical plans that can be applied to actual educational situations. Through this process, teachers can connect ethical thinking to actual behavior and narrow the gap between ethical judgment and practice.
In order to enhance the ethical competencies of AI, the section entitled "Understanding AI Ethical Principles" presents fundamental ethical principles, including transparency, fairness, and accountability, in a conceptual manner. This clarifies the differences between laws, norms, guidelines, and ethical principles, and helps teachers design their own practical strategies through the meaning of ethical principles and actual application cases. The “Understanding AI Technology” area is divided into three sub-areas: “AI Concepts and Characteristics,” “AI Principles and Applications,” and “AI Utilization and Evaluation.” It consists of exploring the basic concepts and types of technology, exploring the actual operating principles, and finally utilizing and evaluating AI. These two areas of basic knowledge form the foundation for teachers' ability to use AI technology ethically.
Education model-based programs have been shown to result in increased teacher satisfaction and enhanced ethical competence. According to the results of a recent satisfaction survey, the average satisfaction score among teachers was 4.85, which is considered to be very high. Focus group interviews also reported improvements in critical thinking skills through ethical discussions and exchanges of diverse perspectives. Statistical analysis revealed a significant increase in AI ethical competency scores from 3.37 before the education to 4.30 after the education. Furthermore, reflection data analysis indicated changes in awareness of ethical practices in AI utilization as well as specific action plans. This finding underscores the efficacy of the educational model in fostering teachers' ethical knowledge, critical thinking skills, and ethical problem-solving abilities, thereby suggesting its potential for applicability across diverse educational settings.
In conclusion, this study developed educational principles and models to strengthen teachers' AI ethics competencies and verified their effectiveness through actual application. The results of this study were discussed in the context of the importance of social cooperation for ethical practice in AI-utilized education. The study also examined the effectiveness of dilemma discussion methods and case-based learning as educational strategies. Additionally, it explored the significance of reflection as an intervention strategy in adult education. Additionally, the potential for the expansion of the model to include teacher training and student education in the future was presented. The significance of this study lies in its establishment of a practical foundation for the shift from technology-centered education to ethics-centered education.
Educational technology has the responsibility to design the parameters of a new educational paradigm in the midst of the transitional period brought about by the digital transformation. Educational technology, as a field rooted in the tradition of technology-based education, should propose directions for the cultivation of specific expertise, along with the content and methods, within the new technological environment. This study presents a human-centered educational paradigm through AI ethics, reflecting on the essence of education from such a perspective. This study anticipates continued discussions toward "ethical AI-utilizing education," in which the inherent values of education and innovation can coexist harmoniously.