Work

Perceptions of AI-Driven Frameworks for English Composition Assessment Strategies: A Comparison of Professional and Student Researchers

Year: 2025

Type: article

Abstract: In an effort to explore the integration of Artificial Intelligence (AI) in higher education, this project focused on the evaluation of perceptions of AI-related assessment strategies between student researchers and professional researchers. With English composition as a focal point, the AI-driven framework consisted of the policy, guidelines, and rubric that were analyzed through perceptions related to cognition, attitude, and behavior. Through the creation of the Perceptions of AI-Generated Assessments Model, researchers compared and contrasted the insights from these groups and identified trends that served as new approaches to innovation in higher education assessment. Overall, this research project revealed that student researchers were more optimistic yet sensitive toward benefits for their peers, whereas professional researchers were more critical and deeper analyzers related to AI’s impact on learning and its benefit to student researchers.

Source: Intersection A Journal at the Intersection of Assessment and Learning

DOI: 10.61669/001c.131922

Authors: Amy J. Heston, Ling Qian, Tatiana Tolson, Madeline M. Heston

Institutions: Walsh University, University of Akron

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

OpenAlex ID: W4408184530

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