Analysis of AI Ethical Competence to Computational Thinking

Jinah Bae - Jeju National University, 102 Jejudaehak ro, Jeju 63243, Republic of Korea
Junghun Lee - Jeju National University, 102 Jejudaehak ro, Jeju 63243, Republic of Korea
Jungwon Cho - Jeju National University, 102 Jejudaehak ro, Jeju 63243, Republic of Korea


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DOI: http://dx.doi.org/10.30630/joiv.6.2-2.1126

Abstract


Artificial Intelligence (AI) is a driving force leading the intelligent information society. Major advanced countries have established AI into key policy projects and made continuous efforts to nurture and develop future talents through AI education. Unlike conventional software, AI can infer results through training with data, and if there is a data bias, it may cause social and ethical problems. These problems incur extensive damage to society, so ethical consideration is essential in terms of effectiveness and efficiency in implementing AI. Computational thinking aims to perform effective and efficient problem-solving to address real-life problems using computing technology such as AI. Therefore, ethical considerations in AI education can be regarded as an important element of computational thinking. This study aims to analyze the relationship between computational thinking and AI ethical competence from problem-solving using AI. To this end, evaluations and analyses of computational thinking and AI ethical competence were performed based on the evaluation results of the education program with the integration of AI and AI ethics. The analysis demonstrated that the group with relatively high computational thinking skills also showed high AI ethical competence. The findings of this study are expected to facilitate research on nurturing computational thinking through AI-integrated education with sufficient consideration of AI ethics. To increase the effectiveness of the AI-integrated education program, it is necessary to develop a mid-to-long-term education program to systematically examine the process-focused evaluation by systematizing observational and portfolio assessments.

Keywords


AI education; AI ethics education; computational thinking; AI integrated education model; AI ethical competence.

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References


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