Preservice teachers' teaching internship affects professional identity: self-efficacy and learning engagement as mediators
Open accessAbstract
Preservice teachers’ professional identity is a critical factor in their motivation, effectiveness, and retention. Teaching internship can promote the transformation of professional identity and self-efficacy of preservice teachers. The internship environment also enhances students’ increasing level of learning engagement. Although much research has shown strong relationship between preservice teachers’ teaching internship and professional identity, less is known about how self-efficacy and learning engagement mediated those variables. The purpose of this study is to investigate the roles that self-efficacy and learning engagement play in the relationship between preservice teachers’ professional identities and their teaching internship experiences. The study involved 309 preservice teachers in total, and the variables were measured using questionnaires. For the data analysis, we used structural equation modeling. The study’s findings are as follows. (a) Teaching internship, professional identity, self-efficacy, and learning engagement were all significantly correlated with one another. (b) Both self-efficacy and learning engagement partially mediated the relationship between teaching internship and professional identity in a parallel manner. (c) Self-efficacy and learning engagement also sequentially mediated the relationship between teaching internship and professional identity.
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Cai et al. (2022) found that teachers' PI is positively associated with their self-efficacy, which in turn is related to teaching practices.
“For instance, Cai et al. (2022) found that teachers’ PI is positively associated with their self-efficacy, which in turn is related to teaching practices.”
From AI teaching innovation behavior among college teachers: a structural equation modeling analysis based on the AI-TPACK framework, teaching self-efficacy, professional identity, and AI literacy (2026) · cites this paper as Cai et al., 2022
The Findings (Mediation model; page not available) report a significant positive path from self-efficacy to professional identity among preservice teachers. But the Discussion (Self-efficacy and learning engagement as mediators; page not available) says a cited study found no significant correlation between self-efficacy and science teaching practices in preservice elementary teachers. Cai et al. did not establish the claimed link to teaching practices. (LLM, conf=0.88)
Experimental — accuracy not yet measuredIn prior work, teachers' self-efficacy is positively associated with professional identity.
“This result aligns with Cai et al. (2022), who found that teachers’ self-efficacy is positively associated with PI.”
From AI teaching innovation behavior among college teachers: a structural equation modeling analysis based on the AI-TPACK framework, teaching self-efficacy, professional identity, and AI literacy (2026) · cites this paper as Cai et al. (2022)
The Findings (Descriptive statistics and correlations; page unavailable) report a positive correlation between self-efficacy and professional identity (r = 0.659, p < 0.01). The finding is for preservice teachers, so the citation does not establish the association for teachers generally. (LLM, conf=0.82)
Experimental — accuracy not yet measuredTeachers with strong PI tend to devote more effort to exploring teaching methods and view teaching challenges as growth opportunities, which is associated with enhanced TSE.
“Teachers with a strong PI tend to devote more effort to exploring teaching methods (behavioral engagement) and view teaching challenges as growth opportunities through positive attribution (cognitive regulation), which is associated with enhanced TSE (Cai et al., 2022).”
From AI teaching innovation behavior among college teachers: a structural equation modeling analysis based on the AI-TPACK framework, teaching self-efficacy, professional identity, and AI literacy (2026) · cites this paper as Cai et al., 2022
The Introduction (page unavailable) says professional identity predicts dedication to professional preparation, and the Findings’ mediation model (page unavailable) reports an association between self-efficacy and professional identity. But the model treats self-efficacy as contributing to professional identity, not the reverse. The copy does not establish that teachers with stronger professional identity explore teaching methods or positively reframe challenges, or that those behaviors enhance teaching self-efficacy. (LLM, conf=0.86)
Experimental — accuracy not yet measured
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“This result aligns with Cai et al. (2022), who found that teachers’ self-efficacy is positively associated with PI.”
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Digital literacy and teaching innovation in physical education teachers: a moderated mediation modelPreprint
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- Authors
- Cai, Z., Zhu, J., & Tian, S.
- Affiliations
- Wenzhou University (CN)
- Corresponding author
- Tian, Saiqi
- Venue
- Frontiers in Psychology
- Publisher
- Frontiers Media SA
- Published
- 2022-11-30
- Volume
- 13
- Pages
- 1070763-1070763
- ISSN
- 1664-1078 (ISSN-L)
- PMC
- PMC9748549
- OpenAlex
- W4310995047
- Cited by
- 57
- References
- 69
- Citations by year
- 2026: 31 · 2025: 19 · 2024: 4 · 2023: 3
- FWCI
- 14.02
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Psychology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Education › Teacher Education and Leadership Studies
- Social Sciences › Education › Teacher Professional Development and Motivation
- Social Sciences › Education › Teacher Education and Assessments
- Keywords
- pre-service teachers, teaching internship, professional identity, self-efficacy, student engagement, mediation, teacher professional development
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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