The Impact of Generative AI on Syllabus Design and Learning
Saved in:
| Title: | The Impact of Generative AI on Syllabus Design and Learning |
|---|---|
| Language: | English |
| Authors: | Hyoseok Kim (ORCID |
| Source: | Journal of Marketing Education. 2026 48(1):20-41. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 22 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Artificial Intelligence, Educational Quality, Technology Uses in Education, Course Descriptions, Marketing, Business Education, Student Attitudes, Material Development, Authors, Disclosure, Undergraduate Students, Foreign Countries, Conventional Instruction |
| Geographic Terms: | North America |
| DOI: | 10.1177/02734753241299024 |
| ISSN: | 0273-4753 1552-6550 |
| Abstract: | This research examines the impact of generative artificial intelligence (AI) on the perception of educational content quality, specifically by comparing AI-generated and human-generated course syllabi in marketing education. Results from four studies indicate a general preference for AI-generated syllabi, attributed to their greater perceived objectivity. This preference is more pronounced in conventional courses but diminishes in unconventional ones, suggesting that the unique aspects of these courses may reduce the advantages of generative AI. In addition, disclosing the AI authorship of syllabi significantly affects their perceived quality negatively, underscoring the impact of transparency on the acceptance of AI-generated educational materials. These findings highlight the potential of generative AI in educational content creation and its limitations in certain contexts. They offer valuable insights for enhancing educational practices and shaping policy decisions to enrich student experiences in the era of AI integration. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1499495 |
| Database: | ERIC |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
