Assessment of Learner Engagement and Expert Evaluations of AI-Generated versus Human-Created Interactive Content in an Online Course
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| Title: | Assessment of Learner Engagement and Expert Evaluations of AI-Generated versus Human-Created Interactive Content in an Online Course |
|---|---|
| Language: | English |
| Authors: | Hamza Aydemir, Seyda Kir |
| Source: | International Review of Research in Open and Distributed Learning. 2025 26(4):1-23. |
| Availability: | Athabasca University Press. 1200, 10011-109 Street, Edmonton, AB T5J 3S8, Canada. Tel: 780-497-3412; Fax: 780-421-3298; e-mail: irrodl@athabascau.ca; Web site: http://www.irrodl.org |
| Peer Reviewed: | Y |
| Page Count: | 23 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Learner Engagement, Online Courses, Artificial Intelligence, Evaluation Methods, Instructional Materials, Educational Quality, Instructional Material Evaluation, Foreign Countries, Universities, Programming, Computer Science Education, Distance Education, Technology Uses in Education, Opinions, Expertise |
| Geographic Terms: | Turkey |
| ISSN: | 1492-3831 |
| Abstract: | Generative artificial intelligence (GenAI) has introduced a novel aspect to educational methodologies and sparked fresh dialogues regarding the creation and evaluation of instructional resources. This project seeks to investigate the impact of GenAI on the development and assessment of online course materials and learners' engagement with these materials in the online learning environment. The study analyzed GenAI-generated multiple-choice questions, fill-in-the-blank exercises, and true-false activities during 3 weeks of a 14-week online course. Subject matter experts assessed these documents in regards to content, relevance, and clarity. Data was collected through an online form with open-ended questions. The interactions of learners with the GenAI-created learning activities were analyzed using log records of the learning management system and compared to the content provided by the course instructor regarding interaction levels. The study's conclusions elucidate the capability of GenAI technologies to produce course-specific content and their efficacy in education. We stress that human specialists' critical evaluations play a crucial part in improving the pedagogical validity of GenAI-powered learning materials. Further research into topics including the ethical dimension, the effect on academic achievement, and student motivation is recommended. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1492278 |
| Database: | ERIC |
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| Header | DbId: eric DbLabel: ERIC An: EJ1492278 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Assessment of Learner Engagement and Expert Evaluations of AI-Generated versus Human-Created Interactive Content in an Online Course – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hamza+Aydemir%22">Hamza Aydemir</searchLink><br /><searchLink fieldCode="AR" term="%22Seyda+Kir%22">Seyda Kir</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22International+Review+of+Research+in+Open+and+Distributed+Learning%22"><i>International Review of Research in Open and Distributed Learning</i></searchLink>. 2025 26(4):1-23. – Name: Avail Label: Availability Group: Avail Data: Athabasca University Press. 1200, 10011-109 Street, Edmonton, AB T5J 3S8, Canada. Tel: 780-497-3412; Fax: 780-421-3298; e-mail: irrodl@athabascau.ca; Web site: http://www.irrodl.org – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 23 – Name: DatePubCY Label: Publication Date Group: Date Data: 2025 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research – Name: Audience Label: Education Level Group: Audnce Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink> – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Learner+Engagement%22">Learner Engagement</searchLink><br /><searchLink fieldCode="DE" term="%22Online+Courses%22">Online Courses</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+Methods%22">Evaluation Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Materials%22">Instructional Materials</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Quality%22">Educational Quality</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Material+Evaluation%22">Instructional Material Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Universities%22">Universities</searchLink><br /><searchLink fieldCode="DE" term="%22Programming%22">Programming</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Science+Education%22">Computer Science Education</searchLink><br /><searchLink fieldCode="DE" term="%22Distance+Education%22">Distance Education</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Opinions%22">Opinions</searchLink><br /><searchLink fieldCode="DE" term="%22Expertise%22">Expertise</searchLink> – Name: Subject Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Turkey%22">Turkey</searchLink> – Name: ISSN Label: ISSN Group: ISSN Data: 1492-3831 – Name: Abstract Label: Abstract Group: Ab Data: Generative artificial intelligence (GenAI) has introduced a novel aspect to educational methodologies and sparked fresh dialogues regarding the creation and evaluation of instructional resources. This project seeks to investigate the impact of GenAI on the development and assessment of online course materials and learners' engagement with these materials in the online learning environment. The study analyzed GenAI-generated multiple-choice questions, fill-in-the-blank exercises, and true-false activities during 3 weeks of a 14-week online course. Subject matter experts assessed these documents in regards to content, relevance, and clarity. Data was collected through an online form with open-ended questions. The interactions of learners with the GenAI-created learning activities were analyzed using log records of the learning management system and compared to the content provided by the course instructor regarding interaction levels. The study's conclusions elucidate the capability of GenAI technologies to produce course-specific content and their efficacy in education. We stress that human specialists' critical evaluations play a crucial part in improving the pedagogical validity of GenAI-powered learning materials. Further research into topics including the ethical dimension, the effect on academic achievement, and student motivation is recommended. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2026 – Name: AN Label: Accession Number Group: ID Data: EJ1492278 |
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| RecordInfo | BibRecord: BibEntity: Languages: – Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 1 Subjects: – SubjectFull: Learner Engagement Type: general – SubjectFull: Online Courses Type: general – SubjectFull: Artificial Intelligence Type: general – SubjectFull: Evaluation Methods Type: general – SubjectFull: Instructional Materials Type: general – SubjectFull: Educational Quality Type: general – SubjectFull: Instructional Material Evaluation Type: general – SubjectFull: Foreign Countries Type: general – SubjectFull: Universities Type: general – SubjectFull: Programming Type: general – SubjectFull: Computer Science Education Type: general – SubjectFull: Distance Education Type: general – SubjectFull: Technology Uses in Education Type: general – SubjectFull: Opinions Type: general – SubjectFull: Expertise Type: general – SubjectFull: Turkey Type: general Titles: – TitleFull: Assessment of Learner Engagement and Expert Evaluations of AI-Generated versus Human-Created Interactive Content in an Online Course Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hamza Aydemir – PersonEntity: Name: NameFull: Seyda Kir IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2025 Identifiers: – Type: issn-electronic Value: 1492-3831 Numbering: – Type: volume Value: 26 – Type: issue Value: 4 Titles: – TitleFull: International Review of Research in Open and Distributed Learning Type: main |
| ResultId | 1 |
