Exploring Students' Perspectives on Generative AI-Assisted Academic Writing
Saved in:
| Title: | Exploring Students' Perspectives on Generative AI-Assisted Academic Writing |
|---|---|
| Language: | English |
| Authors: | Jinhee Kim, Seongryeong Yu, Rita Detrick, Na Li (ORCID |
| Source: | Education and Information Technologies. 2025 30(1):1265-1300. |
| Availability: | Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ |
| Peer Reviewed: | Y |
| Page Count: | 36 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research Tests/Questionnaires |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Student Attitudes, Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Academic Language, Writing (Composition), Writing Processes, College Students, Foreign Countries, Intelligent Tutoring Systems, Instructional Design, Writing Instruction |
| Geographic Terms: | China |
| DOI: | 10.1007/s10639-024-12878-7 |
| ISSN: | 1360-2357 1573-7608 |
| Abstract: | The rapid development of generative artificial intelligence (GenAI), including large language models (LLM), has merged to support students in their academic writing process. Keeping pace with the technical and educational landscape requires careful consideration of the opportunities and challenges that GenAI-assisted systems create within education. This serves as a useful and necessary starting point for fully leveraging its potential for learning and teaching. Hence, it is crucial to gather insights from diverse perspectives and use cases from actual users, particularly the unique voices and needs of student-users. Therefore, this study explored and examined students' perceptions and experiences about GenAI-assisted academic writing by conducting in-depth interviews with 20 Chinese students in higher education after completing academic writing tasks using a ChatGPT4-embedded writing system developed by the research team. The study found that students expected AI to serve multiple roles, including multi-tasking writing assistant, virtual tutor, and digital peer to support multifaceted writing processes and performance. Students perceived that GenAI-assisted writing could benefit them in three areas including the writing process, performance, and their affective domain. Meanwhile, they also identified AI-related, student-related, and task-related challenges that were experienced during the GenAI-assisted writing activity. These findings contribute to a more nuanced understanding of GenAI's impact on academic writing that is inclusive of student perspectives, offering implications for educational AI design and instructional design. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1457897 |
| Database: | ERIC |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: eric DbLabel: ERIC An: EJ1457897 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Exploring Students' Perspectives on Generative AI-Assisted Academic Writing – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jinhee+Kim%22">Jinhee Kim</searchLink><br /><searchLink fieldCode="AR" term="%22Seongryeong+Yu%22">Seongryeong Yu</searchLink><br /><searchLink fieldCode="AR" term="%22Rita+Detrick%22">Rita Detrick</searchLink><br /><searchLink fieldCode="AR" term="%22Na+Li%22">Na Li</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0003-2395-3499">0000-0003-2395-3499</externalLink>) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Education+and+Information+Technologies%22"><i>Education and Information Technologies</i></searchLink>. 2025 30(1):1265-1300. – Name: Avail Label: Availability Group: Avail Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 36 – Name: DatePubCY Label: Publication Date Group: Date Data: 2025 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research<br />Tests/Questionnaires – 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="%22Student+Attitudes%22">Student Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+Language+Processing%22">Natural Language Processing</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Language%22">Academic Language</searchLink><br /><searchLink fieldCode="DE" term="%22Writing+%28Composition%29%22">Writing (Composition)</searchLink><br /><searchLink fieldCode="DE" term="%22Writing+Processes%22">Writing Processes</searchLink><br /><searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Intelligent+Tutoring+Systems%22">Intelligent Tutoring Systems</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Design%22">Instructional Design</searchLink><br /><searchLink fieldCode="DE" term="%22Writing+Instruction%22">Writing Instruction</searchLink> – Name: Subject Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink> – Name: DOI Label: DOI Group: ID Data: 10.1007/s10639-024-12878-7 – Name: ISSN Label: ISSN Group: ISSN Data: 1360-2357<br />1573-7608 – Name: Abstract Label: Abstract Group: Ab Data: The rapid development of generative artificial intelligence (GenAI), including large language models (LLM), has merged to support students in their academic writing process. Keeping pace with the technical and educational landscape requires careful consideration of the opportunities and challenges that GenAI-assisted systems create within education. This serves as a useful and necessary starting point for fully leveraging its potential for learning and teaching. Hence, it is crucial to gather insights from diverse perspectives and use cases from actual users, particularly the unique voices and needs of student-users. Therefore, this study explored and examined students' perceptions and experiences about GenAI-assisted academic writing by conducting in-depth interviews with 20 Chinese students in higher education after completing academic writing tasks using a ChatGPT4-embedded writing system developed by the research team. The study found that students expected AI to serve multiple roles, including multi-tasking writing assistant, virtual tutor, and digital peer to support multifaceted writing processes and performance. Students perceived that GenAI-assisted writing could benefit them in three areas including the writing process, performance, and their affective domain. Meanwhile, they also identified AI-related, student-related, and task-related challenges that were experienced during the GenAI-assisted writing activity. These findings contribute to a more nuanced understanding of GenAI's impact on academic writing that is inclusive of student perspectives, offering implications for educational AI design and instructional design. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2025 – Name: AN Label: Accession Number Group: ID Data: EJ1457897 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1457897 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10639-024-12878-7 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 36 StartPage: 1265 Subjects: – SubjectFull: Student Attitudes Type: general – SubjectFull: Artificial Intelligence Type: general – SubjectFull: Technology Uses in Education Type: general – SubjectFull: Natural Language Processing Type: general – SubjectFull: Academic Language Type: general – SubjectFull: Writing (Composition) Type: general – SubjectFull: Writing Processes Type: general – SubjectFull: College Students Type: general – SubjectFull: Foreign Countries Type: general – SubjectFull: Intelligent Tutoring Systems Type: general – SubjectFull: Instructional Design Type: general – SubjectFull: Writing Instruction Type: general – SubjectFull: China Type: general Titles: – TitleFull: Exploring Students' Perspectives on Generative AI-Assisted Academic Writing Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jinhee Kim – PersonEntity: Name: NameFull: Seongryeong Yu – PersonEntity: Name: NameFull: Rita Detrick – PersonEntity: Name: NameFull: Na Li IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 1360-2357 – Type: issn-electronic Value: 1573-7608 Numbering: – Type: volume Value: 30 – Type: issue Value: 1 Titles: – TitleFull: Education and Information Technologies Type: main |
| ResultId | 1 |