Attitudes Toward the Use of AI in Student Assessment

Several studies have been conducted across various academic disciplines to explore the use and effectiveness of generative AI. Scholars have found significant support for AI-based tools in higher education, leading to their integration to enhance student learning outcomes. However, there has been limited exploration of how AI-based tools can be utilized to assess student performance and offer feedback. This study aims to fill this gap by utilizing behavioral approaches to investigate public perceptions regarding using AI-based tools to assess student performance and provide feedback. Additionally, it will assess public perceptions of AI's potential to mitigate human bias in student assessment, a promising aspect of AI in education. The study also aims to understand preferences for human and/or AI-based tools in training learners on specific topics such as leadership, empathy, and human connection. The study aims to understand the essential attributes of AI-based assessment and performance evaluation approaches among college students. With the increasing integration of AI-based tools in various aspects of modern society, there is an urgent need to understand how these tools may influence how learners in higher education perceive their utility in assessing performance and providing personalized feedback. Our research aims to contribute to the ongoing exploration of generative AI, particularly in the area of student assessment and feedback generation, which has not been extensively examined in academic discourse.