Authors:
Andi Asrifan (Universitas Negeri Makassar, Indonesia), Rismawati Sudirman (Universitas Muhammadiyah Palopo, Indonesia), Rusdiana Junaid (Universitas Cokroaminoto Palopo, Indonesia), and Juvrianto Chrissunday Jakob (Politeknik Negeri Ambon, Indonesia)
Abstract
This chapter examines the revolutionary impact of Artificial Intelligence (AI) on educational evaluation, highlighting how AI tools can enhance, rather than supplant, teacher ability. In response to the changing requirements of 21st-century education, AI provides avenues for individualized learning, immediate feedback, and effective performance monitoring. Grounded in cognitive and constructivist learning theories, the book delineates various AI-driven assessment models, encompassing rule-based grading and adaptive analytics. It emphasizes the pedagogical, ethical, and technical aspects of AI integration by utilizing empirical research and practical case studies. The debate emphasizes promoting a human-centered approach that maintains teacher autonomy, guarantees equity, and fosters inclusivity. The book advocates for a collaborative future where instructors and AI synergistically enhance assessment processes and student results.
Chapter Description:
Enhancing assessment with artificial intelligence (AI) means using technology to support teachers in evaluating student learning more effectively. AI does not replace teachers, but helps them work more efficiently and make better decisions. By combining AI tools with teacher expertise, assessment can become more accurate, fair, and supportive of student development.
One important strategy is using AI to assist with grading routine tasks. For example, AI can quickly check multiple-choice tests, short answers, or basic language exercises. This saves teachers time, allowing them to focus more on giving meaningful feedback and supporting students who need extra help.
AI can also help teachers understand student learning patterns. By analyzing student responses and performance over time, AI can identify strengths, weaknesses, and common mistakes. This information helps teachers adjust their teaching strategies and design assessments that better match students’ needs.
Another way AI complements teacher expertise is through personalized feedback. AI systems can provide instant feedback on assignments, such as writing or quizzes, based on clear criteria. Teachers can then review this feedback, add their professional judgment, and give more personal and encouraging guidance to students.
AI can also support fairness and consistency in assessment. By using the same standards for all students, AI can reduce bias in scoring. However, teachers still play a key role in interpreting results, understanding student context, and ensuring that assessments remain ethical and meaningful.
In conclusion, enhancing assessment with AI is about partnership, not replacement. When AI is used as a supportive tool, it helps teachers save time, understand students better, and improve the quality of assessment. Teacher expertise remains essential to guide, interpret, and humanize the assessment process.
