When Tutors Simultaneously Instruct Students from the Primary, Middle, and High School Levels in Online One-on-One Tutoring: Investigating the Interaction Dynamics Using AI, ENA, and LSA Methods.
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| Title: | When Tutors Simultaneously Instruct Students from the Primary, Middle, and High School Levels in Online One-on-One Tutoring: Investigating the Interaction Dynamics Using AI, ENA, and LSA Methods. |
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| Authors: | Wang, Deliang1 (AUTHOR) wdeliang@connect.hku.hk, Gao, Lei2 (AUTHOR) shirleygao@link.cuhk.edu.hk, Shan, Dapeng3 (AUTHOR) dpshan@cs.hku.hk, Chen, Gaowei1 (AUTHOR) gwchen@hku.hk, Zhang, Chenwei1 (AUTHOR) chwzhang@hku.hk, Kao, Ben3 (AUTHOR) kao@cs.hku.hk |
| Source: | Journal of Science Education & Technology. Oct2025, Vol. 34 Issue 5, p1128-1142. 15p. |
| Subject Terms: | *Tutors & tutoring, *Artificial intelligence, *Student engagement, *Educational attainment, *Interpersonal relations, Dialogics |
| Abstract: | Online one-on-one tutoring serves as a personalized approach to supplement classroom instruction. However, with the growing tutoring market, a single tutor often handles inquiries from students across primary, middle, and high school levels. Consequently, the extent of tutors' interactions with students of varying grades and their use of tutoring strategies to enhance student learning remains unclear. To address this gap, we collected and analyzed 1500 tutoring dialogues from amateur mathematics tutors concurrently instructing students from primary, middle, and high school levels. These dialogues were annotated using a coding scheme and a well-trained powerful artificial intelligence (AI) model. The interaction dynamics were subsequently examined using epistemic network analysis and lag sequential analysis, yielding findings on the occurrences, co-occurrences, and sequential patterns of dialogic strategies. First, the results reveal that tutors frequently engaged in off-topic behaviors and direct instruction, regardless of students' educational level. Second, tutors' constructive questions and knowledge sharing and instruction were more associated with greater constructive expressions from students at higher educational levels, while primary students primarily demonstrated simple acknowledgment. Third, tutors exhibited limited sequential patterns of dialogic strategies when tutoring primary and middle school students, mainly focusing on question-asking behaviors and evaluation and feedback. In contrast, tutors displayed diverse patterns across various categories of dialogic strategies when instructing high school students, emphasizing the facilitation of students' reasoning and metacognition. These findings underscore the importance of training tutors to develop dialogic skills and adopt tailored pedagogical approaches for different educational levels, ensuring effective and efficient online one-on-one mathematics tutoring. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Science Education & Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 189590664 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: When Tutors Simultaneously Instruct Students from the Primary, Middle, and High School Levels in Online One-on-One Tutoring: Investigating the Interaction Dynamics Using AI, ENA, and LSA Methods. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wang%2C+Deliang%22">Wang, Deliang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wdeliang@connect.hku.hk</i><br /><searchLink fieldCode="AR" term="%22Gao%2C+Lei%22">Gao, Lei</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> shirleygao@link.cuhk.edu.hk</i><br /><searchLink fieldCode="AR" term="%22Shan%2C+Dapeng%22">Shan, Dapeng</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> dpshan@cs.hku.hk</i><br /><searchLink fieldCode="AR" term="%22Chen%2C+Gaowei%22">Chen, Gaowei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> gwchen@hku.hk</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Chenwei%22">Zhang, Chenwei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> chwzhang@hku.hk</i><br /><searchLink fieldCode="AR" term="%22Kao%2C+Ben%22">Kao, Ben</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> kao@cs.hku.hk</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Science+Education+%26+Technology%22">Journal of Science Education & Technology</searchLink>. Oct2025, Vol. 34 Issue 5, p1128-1142. 15p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Tutors+%26+tutoring%22">Tutors & tutoring</searchLink><br />*<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Student+engagement%22">Student engagement</searchLink><br />*<searchLink fieldCode="DE" term="%22Educational+attainment%22">Educational attainment</searchLink><br />*<searchLink fieldCode="DE" term="%22Interpersonal+relations%22">Interpersonal relations</searchLink><br /><searchLink fieldCode="DE" term="%22Dialogics%22">Dialogics</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Online one-on-one tutoring serves as a personalized approach to supplement classroom instruction. However, with the growing tutoring market, a single tutor often handles inquiries from students across primary, middle, and high school levels. Consequently, the extent of tutors' interactions with students of varying grades and their use of tutoring strategies to enhance student learning remains unclear. To address this gap, we collected and analyzed 1500 tutoring dialogues from amateur mathematics tutors concurrently instructing students from primary, middle, and high school levels. These dialogues were annotated using a coding scheme and a well-trained powerful artificial intelligence (AI) model. The interaction dynamics were subsequently examined using epistemic network analysis and lag sequential analysis, yielding findings on the occurrences, co-occurrences, and sequential patterns of dialogic strategies. First, the results reveal that tutors frequently engaged in off-topic behaviors and direct instruction, regardless of students' educational level. Second, tutors' constructive questions and knowledge sharing and instruction were more associated with greater constructive expressions from students at higher educational levels, while primary students primarily demonstrated simple acknowledgment. Third, tutors exhibited limited sequential patterns of dialogic strategies when tutoring primary and middle school students, mainly focusing on question-asking behaviors and evaluation and feedback. In contrast, tutors displayed diverse patterns across various categories of dialogic strategies when instructing high school students, emphasizing the facilitation of students' reasoning and metacognition. These findings underscore the importance of training tutors to develop dialogic skills and adopt tailored pedagogical approaches for different educational levels, ensuring effective and efficient online one-on-one mathematics tutoring. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Science Education & Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=189590664 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10956-024-10154-4 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 1128 Subjects: – SubjectFull: Tutors & tutoring Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Student engagement Type: general – SubjectFull: Educational attainment Type: general – SubjectFull: Interpersonal relations Type: general – SubjectFull: Dialogics Type: general Titles: – TitleFull: When Tutors Simultaneously Instruct Students from the Primary, Middle, and High School Levels in Online One-on-One Tutoring: Investigating the Interaction Dynamics Using AI, ENA, and LSA Methods. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang, Deliang – PersonEntity: Name: NameFull: Gao, Lei – PersonEntity: Name: NameFull: Shan, Dapeng – PersonEntity: Name: NameFull: Chen, Gaowei – PersonEntity: Name: NameFull: Zhang, Chenwei – PersonEntity: Name: NameFull: Kao, Ben IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 10590145 Numbering: – Type: volume Value: 34 – Type: issue Value: 5 Titles: – TitleFull: Journal of Science Education & Technology Type: main |
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