The Impact of Artificial Intelligence on Education: Opportunities and Challenges - Sri Rahayu (Universitas Majalengka, 2023)
The integration of Artificial Intelligence (AI) in education, particularly in learning assessments, presents a notable paradigm shift, promising advancements in learning methodologies. Numerous studies advocate for AI's potential to enhance students' quality by refining evaluations and furnishing precise, measurable feedback. It stands out in mitigating errors, enhancing evaluation accuracy, identifying individual needs, and fostering more effective teaching. Traditional educational approaches, fraught with subjective human judgment and limited forms of assessment like written or oral tests, often fail to capture individual abilities comprehensively. AI's implementation demonstrates the ability to reduce bias, enhance efficiency, and provide tailored assessments, addressing these limitations. Methodologically, this article employs a literature review to synthesize various perspectives on AI's impact on education. It explores AI's potential benefits such as objectivity, efficiency, consistency, analytical capabilities, developmental programs, personalization, flexibility, and anti-cheating measures. Furthermore, it delves into challenges, notably AI's validity, high costs, technological dependency, data security, and the potential influence of behavioral changes on assessment outcomes. The results reveal multifaceted advantages of AI technology, including objectivity in assessments devoid of human bias, efficiency in time and cost, consistent evaluations, enhanced analytical skills, assessment program development, flexibility, and fraud mitigation. However, challenges exist, ranging from ensuring AI's validity and reliability, addressing technological dependency and cost hurdles, securing data, to mitigating biased discrimination. In conclusion, while AI presents a plethora of advantages, its integration into education demands meticulous consideration of associated challenges. The technology's efficacy and reliability, coupled with the cost and security aspects, necessitate thorough scrutiny and rigorous testing before implementation.