Assessment Types, Strategies, and Feedback in Online Higher Education Courses in the Age of Artificial Intelligence

Perspectives of Instructional Designers

Dados Bibliográficos

ID12815503
AutoresFlorence Martins (0000-0002-6055-5636, North Carolina State University), Stella Kim (0000-0002-0562-1071, University of North Carolina at Charlotte), Doris U Bolliger (0000-0001-8104-6243, Texas Tech University), Jennifer DeLarm (North Carolina State University)
Ano2025
Volume69
Fascículo6
Páginas1330-1346
Data de publicação2025-07-22
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoTechTrends (JOURNAL)
Identificadores do periódicoISSN: 8756-3894 • E-ISSN: 1559-7075
EditoraSpringer Science+Business Media (PUBLISHER • DE)
DOI10.1007/s11528-025-01115-8
OpenAlexW4412552779
IdiomaEN
Citações recebidas3
Referências citadas36

This study used a survey methodology to examine instructional designer perceptions on assessment types, assessment strategies, instructor feedback, and the influence of artificial intelligence (AI) in online assessments. An online survey with 46 questions was developed and administered to instructional designers at higher education institutions. Instructional designers from multiple universities were invited to participate in the study, with one hundred and three individuals completing the survey. Results indicated that instructional designers rated case study analysis, followed by electronic portfolio, design project and multimedia project as most effective assessment types. Least effective assessment types were non-proctored exams, proctored exams, and asynchronous participation. A grading rubric was rated as the most effective assessment strategy, and ungraded assignments and automated graded assignments were perceived to be least effective. AI was recognized to be effective for creating rubrics for assessments, generating automated quizzes, and providing feedback. To address academic integrity challenges with use of AI, participants recommended administering assessments that measure higher-order thinking, incorporating authentic assessments, and utilizing synchronous sessions

Computer-Assisted Instruction · Educational technology · Higher education · Instructional design · Mathematics education · Multimedia · Political science · Computer Science · Online Learning and Analytics · Psychology · Artificial Intelligence