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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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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.

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Data Availability

The data and materials that support the findings of this study are available from the first author, Deliang Wang, upon reasonable request.

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Authors and Affiliations

  1. Faculty of Education, The University of Hong Kong, Hong Kong, China

    Deliang Wang, Gaowei Chen & Chenwei Zhang

  2. Faculty of Education, The Chinese University of Hong Kong, Hong Kong, China

    Lei Gao

  3. Faculty of Engineering, The University of Hong Kong, Hong Kong, China

    Dapeng Shan & Ben Kao

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  1. Deliang Wang
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Deliang Wang and Lei Gao: conceptualization, methodology, investigation, formal analysis, writing—original draft, writing—reviewing and editing; Dapeng Shan, Gaowei Chen, Chenwei Zhang, and Ben Kao: methodology, reviewing and editing.

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Correspondence to Lei Gao.

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Wang, D., Gao, L., Shan, D. et al. 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. J Sci Educ Technol (2024). https://doi.org/10.1007/s10956-024-10154-4

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