Pub Date : 2025-08-25DOI: 10.1177/00224871251364263
Vicki S. Collet, Savannah Gragg, Amanda Leggett
Teaching residencies offer opportunities for sustained support within schools as a liminal space for novice teachers, and school-based mentor teachers significantly impact residency outcomes. Mentoring improves when mentors have clear expectations for their role and support for meeting those expectations. This mixed-method case study investigates the effects of a model for mentor training, its impact on residents’ learning, and the perceptions of mentors and residents regarding support provided. Quantitative findings showed a statistically significant difference in growth for residents whose mentors were trained in the Gradual Increase of Responsibility mentoring model compared with those who were not. Qualitative analysis offers support for differentiated use of the mentoring moves of modeling, recommending, questioning, affirming, and praising (with this sequence expressing de-escalating levels of support). Findings suggest that when mentoring varies based on residents’ differing and changing skill levels, teaching improves. Centering dialogue in mentor/resident interactions supports change and growth.
{"title":"Making Moves: Use of the Gradual Increase of Responsibility Model for Mentoring Student Teachers in Residency","authors":"Vicki S. Collet, Savannah Gragg, Amanda Leggett","doi":"10.1177/00224871251364263","DOIUrl":"https://doi.org/10.1177/00224871251364263","url":null,"abstract":"Teaching residencies offer opportunities for sustained support within schools as a liminal space for novice teachers, and school-based mentor teachers significantly impact residency outcomes. Mentoring improves when mentors have clear expectations for their role and support for meeting those expectations. This mixed-method case study investigates the effects of a model for mentor training, its impact on residents’ learning, and the perceptions of mentors and residents regarding support provided. Quantitative findings showed a statistically significant difference in growth for residents whose mentors were trained in the Gradual Increase of Responsibility mentoring model compared with those who were not. Qualitative analysis offers support for differentiated use of the mentoring moves of modeling, recommending, questioning, affirming, and praising (with this sequence expressing de-escalating levels of support). Findings suggest that when mentoring varies based on residents’ differing and changing skill levels, teaching improves. Centering dialogue in mentor/resident interactions supports change and growth.","PeriodicalId":17162,"journal":{"name":"Journal of Teacher Education","volume":"33 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144905778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-11DOI: 10.1177/00224871251366349
Jacqueline E. King, Chen-Su Chen
{"title":"Preview of Two New AACTE Publications","authors":"Jacqueline E. King, Chen-Su Chen","doi":"10.1177/00224871251366349","DOIUrl":"https://doi.org/10.1177/00224871251366349","url":null,"abstract":"","PeriodicalId":17162,"journal":{"name":"Journal of Teacher Education","volume":"52 1","pages":"333-336"},"PeriodicalIF":3.9,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144898154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-10DOI: 10.1177/00224871251350680
Larissa Aust, Jeanne-Celine Linker, Luise Eichholz, Jana Schiffer, Marcus Nührenbörger, Christoph Selter, Elmar Souvignier
Only limited evidence exists on how to best make the effective yet broad concept of formative assessment (FA) accessible to teachers. Thus, this study investigated the effects of two differently structured FA approaches (curriculum-embedded assessment [CE] vs. planned-for-interaction assessment [PI]) on implementation outcomes over time. A total of N = 118 mathematics teachers participated in a six-session professional development program offered over one school year and implemented one of the two approaches in their classrooms. Implementation success was assessed via teachers’ self-reports. Hierarchical linear models for repeated measurement revealed higher ratings for CE for the initial phase of implementation. Over time, differences between the approaches decreased for feasibility and cooperation, but remained quite constant in terms of acceptability, fidelity and perceived learning outcome. The approaches did not significantly differ regarding sustainability. Thus, for implementing FA, it seems worthwhile to provide teachers with clear guidelines and an explicit structure.
{"title":"Implementing Formative Assessment Into School Practice: A Matter of Structuring the Intervention?","authors":"Larissa Aust, Jeanne-Celine Linker, Luise Eichholz, Jana Schiffer, Marcus Nührenbörger, Christoph Selter, Elmar Souvignier","doi":"10.1177/00224871251350680","DOIUrl":"https://doi.org/10.1177/00224871251350680","url":null,"abstract":"Only limited evidence exists on how to best make the effective yet broad concept of formative assessment (FA) accessible to teachers. Thus, this study investigated the effects of two differently structured FA approaches (curriculum-embedded assessment [CE] vs. planned-for-interaction assessment [PI]) on implementation outcomes over time. A total of <jats:italic>N</jats:italic> = 118 mathematics teachers participated in a six-session professional development program offered over one school year and implemented one of the two approaches in their classrooms. Implementation success was assessed via teachers’ self-reports. Hierarchical linear models for repeated measurement revealed higher ratings for CE for the initial phase of implementation. Over time, differences between the approaches decreased for feasibility and cooperation, but remained quite constant in terms of acceptability, fidelity and perceived learning outcome. The approaches did not significantly differ regarding sustainability. Thus, for implementing FA, it seems worthwhile to provide teachers with clear guidelines and an explicit structure.","PeriodicalId":17162,"journal":{"name":"Journal of Teacher Education","volume":"69 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144594495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-19DOI: 10.1177/00224871251344913
Luecha Ladachart, Ladapa Ladachart
This research examines changes in orientations to teaching science among 37 preservice biology teachers, who primarily intend to work in secondary education, during a 5-year program of science teacher education in Thailand. Data were collected twice, in the first and fourth years of the program, using the same Pedagogy of Science Teaching Test, in which participants quantitatively chose their preferred approaches to instruction, while qualitatively providing the reasons for choosing these instructional approaches in a written format. Quantitative data were analyzed using inferential statistics, whereas qualitative data were analyzed using content analysis. The results indicate that participants’ orientations toward inquiry-based instruction improved, primarily due to their understanding of the nature of students’ learning. This result supports the idea that conceptions relating to students’ learning are critical in shaping orientations toward teaching science. Experiences that reinforced inquiry-based orientations to teaching science are discussed based on follow-up interviews with the five participants with the highest improvements.
{"title":"“It Changed Continuously, and I Don’t Know When”: Thai Preservice Biology Teachers’ Orientations to Teaching Science","authors":"Luecha Ladachart, Ladapa Ladachart","doi":"10.1177/00224871251344913","DOIUrl":"https://doi.org/10.1177/00224871251344913","url":null,"abstract":"This research examines changes in orientations to teaching science among 37 preservice biology teachers, who primarily intend to work in secondary education, during a 5-year program of science teacher education in Thailand. Data were collected twice, in the first and fourth years of the program, using the same Pedagogy of Science Teaching Test, in which participants quantitatively chose their preferred approaches to instruction, while qualitatively providing the reasons for choosing these instructional approaches in a written format. Quantitative data were analyzed using inferential statistics, whereas qualitative data were analyzed using content analysis. The results indicate that participants’ orientations toward inquiry-based instruction improved, primarily due to their understanding of the nature of students’ learning. This result supports the idea that conceptions relating to students’ learning are critical in shaping orientations toward teaching science. Experiences that reinforced inquiry-based orientations to teaching science are discussed based on follow-up interviews with the five participants with the highest improvements.","PeriodicalId":17162,"journal":{"name":"Journal of Teacher Education","volume":"36 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144328813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-27DOI: 10.1177/00224871251336875
Kennedy Kam Ho Chan, Jianyun She, Jan van Driel, Xiang Hu
Although teacher noticing is regarded as a critical component of teacher expertise that matters for student learning, empirical evidence verifying the relationship between teacher noticing and student learning outcomes is scare. Using a relatively large-scale sample involving 189 middle school biology teachers from 156 schools and their students ( n = 7,086), this quantitative study investigated the association between teachers’ level of noticing, measured by a standardized video-based instrument, and student achievement. An analysis utilizing two-level hierarchical linear modeling revealed a significant and positive association between teachers’ level of noticing and student learning outcomes. Specifically, the proportion of variance explained was 0.383. Our study offers robust and timely evidence that verifies the core assumption underpinning teacher noticing research as well as professional development efforts focusing on teacher noticing. Implications for teacher noticing research and teacher professional development are discussed.
{"title":"Does Teacher Noticing Matter for Students’ Science Content Learning Outcomes? Evidence From a Large-Scale Empirical Study","authors":"Kennedy Kam Ho Chan, Jianyun She, Jan van Driel, Xiang Hu","doi":"10.1177/00224871251336875","DOIUrl":"https://doi.org/10.1177/00224871251336875","url":null,"abstract":"Although teacher noticing is regarded as a critical component of teacher expertise that matters for student learning, empirical evidence verifying the relationship between teacher noticing and student learning outcomes is scare. Using a relatively large-scale sample involving 189 middle school biology teachers from 156 schools and their students ( <jats:italic>n</jats:italic> = 7,086), this quantitative study investigated the association between teachers’ level of noticing, measured by a standardized video-based instrument, and student achievement. An analysis utilizing two-level hierarchical linear modeling revealed a significant and positive association between teachers’ level of noticing and student learning outcomes. Specifically, the proportion of variance explained was 0.383. Our study offers robust and timely evidence that verifies the core assumption underpinning teacher noticing research as well as professional development efforts focusing on teacher noticing. Implications for teacher noticing research and teacher professional development are discussed.","PeriodicalId":17162,"journal":{"name":"Journal of Teacher Education","volume":"5 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144153937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-24DOI: 10.1177/00224871251324713
Punya Mishra, Jon Margerum-Leys, Guy Trainin, Valerie Hill-Jackson, Laurie Bobley, Peña L. Bedesem, John A. Williams, Cheryl J. Craig
{"title":"Teacher Education in the Age of Generative Artificial Intelligence: Introducing the Special Issue","authors":"Punya Mishra, Jon Margerum-Leys, Guy Trainin, Valerie Hill-Jackson, Laurie Bobley, Peña L. Bedesem, John A. Williams, Cheryl J. Craig","doi":"10.1177/00224871251324713","DOIUrl":"https://doi.org/10.1177/00224871251324713","url":null,"abstract":"","PeriodicalId":17162,"journal":{"name":"Journal of Teacher Education","volume":"6 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143867019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-30DOI: 10.1177/00224871251325079
Eunhye Flavin, Sunghwan Hwang, Melita Morales
Generative artificial intelligence (AI)-powered conversation agents such as ChatGPT are increasingly being used in teacher education. Although ChatGPT can provide ample resources for lesson planning, little attention has been paid to how teacher candidates construct prompts and evaluate AI-generated outputs in real time to develop lesson plans. Taking up Bisconti et al.’s conceptualization of generative AI as a social agent in a sociotechnical system, this article investigates how knowledge construction is dynamic and negotiated through interaction when using ChatGPT to develop lesson plans. We applied conversation analysis through Heritage’s gradient model of epistemic stance––which captures moment-to-moment expressions of social relationships––to analyze how teacher candidates position their knowledge in relation to that acquired from ChatGPT, as managed through their prompts and questions. Our findings aim to offer insights to help teacher educators develop scaffolds for teacher candidates to critically curate content from AI-powered agents and identify areas needing further instructional support.
{"title":"“Let’s Ask the Robot!”: Epistemic Stance Between Teacher Candidates Toward AI in Mathematics Lesson Planning","authors":"Eunhye Flavin, Sunghwan Hwang, Melita Morales","doi":"10.1177/00224871251325079","DOIUrl":"https://doi.org/10.1177/00224871251325079","url":null,"abstract":"Generative artificial intelligence (AI)-powered conversation agents such as ChatGPT are increasingly being used in teacher education. Although ChatGPT can provide ample resources for lesson planning, little attention has been paid to how teacher candidates construct prompts and evaluate AI-generated outputs in real time to develop lesson plans. Taking up Bisconti et al.’s conceptualization of generative AI as a social agent in a sociotechnical system, this article investigates how knowledge construction is dynamic and negotiated through interaction when using ChatGPT to develop lesson plans. We applied conversation analysis through Heritage’s gradient model of epistemic stance––which captures moment-to-moment expressions of social relationships––to analyze how teacher candidates position their knowledge in relation to that acquired from ChatGPT, as managed through their prompts and questions. Our findings aim to offer insights to help teacher educators develop scaffolds for teacher candidates to critically curate content from AI-powered agents and identify areas needing further instructional support.","PeriodicalId":17162,"journal":{"name":"Journal of Teacher Education","volume":"28 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143736536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-30DOI: 10.1177/00224871251325065
Stefanie Panke
The autoethnographic study investigates the transformative impact of generative AI on educational research, instructional design, and teaching practices over a 5-month period (May–October 2024). By integrating AI tools into every phase of the research process, the study examines AI’s role as both a research partner and a subject of inquiry. Field notes, queries, and AI-generated outputs were systematically collected, creating a corpus for analysis. Grounded in activity theory, this research offers a reflective narrative on the evolving work routines of instructional designers and educators, emphasizing the orchestration of technology rather than prescriptive best practices. The study contributes to educational technology research by documenting the use of AI at a specific point in time, providing a foundation for future inquiry into the practical implications of AI in education.
{"title":"How Can (A)I Research This? An Autoethnographic Exploration of Generative AI in Research, Teaching and Instructional Design","authors":"Stefanie Panke","doi":"10.1177/00224871251325065","DOIUrl":"https://doi.org/10.1177/00224871251325065","url":null,"abstract":"The autoethnographic study investigates the transformative impact of generative AI on educational research, instructional design, and teaching practices over a 5-month period (May–October 2024). By integrating AI tools into every phase of the research process, the study examines AI’s role as both a research partner and a subject of inquiry. Field notes, queries, and AI-generated outputs were systematically collected, creating a corpus for analysis. Grounded in activity theory, this research offers a reflective narrative on the evolving work routines of instructional designers and educators, emphasizing the orchestration of technology rather than prescriptive best practices. The study contributes to educational technology research by documenting the use of AI at a specific point in time, providing a foundation for future inquiry into the practical implications of AI in education.","PeriodicalId":17162,"journal":{"name":"Journal of Teacher Education","volume":"50 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143736531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-24DOI: 10.1177/00224871251325073
Melissa Warr, Marie K. Heath
In this article, we explore the concept of a “hidden curriculum” within generative AI, specifically Large Language Models (LLMs), and its intersection with the hidden curriculum in education. We highlight how AI, trained on biased human data, can perpetuate societal inequities and discriminatory practices despite appearing objective. We present a technology audit that examines how LLMs score and provide feedback on student writing samples paired with student descriptions. Findings reveal that LLMs exhibit implicit biases, such as assigning lower scores when students are said to attend an “inner-city school” or prefer rap music. In addition, the feedback text given to passages said to be written by Black and Hispanic students displayed higher levels of clout or authority, mirroring and legitimizing power dynamics of schooling. We conclude by discussing implications of these findings for teacher education, policy, and research, emphasizing the need to address AI’s hidden curriculum to avoid perpetuating educational inequality.
{"title":"Uncovering the Hidden Curriculum in Generative AI: A Reflective Technology Audit for Teacher Educators","authors":"Melissa Warr, Marie K. Heath","doi":"10.1177/00224871251325073","DOIUrl":"https://doi.org/10.1177/00224871251325073","url":null,"abstract":"In this article, we explore the concept of a “hidden curriculum” within generative AI, specifically Large Language Models (LLMs), and its intersection with the hidden curriculum in education. We highlight how AI, trained on biased human data, can perpetuate societal inequities and discriminatory practices despite appearing objective. We present a technology audit that examines how LLMs score and provide feedback on student writing samples paired with student descriptions. Findings reveal that LLMs exhibit implicit biases, such as assigning lower scores when students are said to attend an “inner-city school” or prefer rap music. In addition, the feedback text given to passages said to be written by Black and Hispanic students displayed higher levels of clout or authority, mirroring and legitimizing power dynamics of schooling. We conclude by discussing implications of these findings for teacher education, policy, and research, emphasizing the need to address AI’s hidden curriculum to avoid perpetuating educational inequality.","PeriodicalId":17162,"journal":{"name":"Journal of Teacher Education","volume":"8 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-19DOI: 10.1177/00224871251325109
Ling Zhang, Zijun Yao, Arya Hadizadeh Moghaddam
Educator preparation, personalized learning (PL) implementation, and applications of Generative AI converge as three interrelated systems that, when carefully designed, can help achieve the long-sought goal of providing inclusive education for all learners. However, realizing this potential comes with challenges resulting from theoretical complexities and technological constraints. This article provides a theoretical analysis of the complex interconnectedness among these systems guided by the Cultural-Historical Activity Theory (CHAT). Building on the analysis, we introduce CoPL, a multi-agent system consisting of multiple agents with distinct functions that facilitate the complex PL design and engage pre-service teachers (PSTs) in dynamic conversations while prompting them to reflect on the inclusivity of agent-generated instructional suggestions. We describe the affordances and limitations of the system as a professional learning tool for PSTs to develop competencies for designing inclusive PL to meet diverse learning needs of all learners. Finally, we discuss future research on refining CoPL and its practical applications.
{"title":"Designing GenAI Tools for Personalized Learning Implementation: Theoretical Analysis and Prototype of a Multi-Agent System","authors":"Ling Zhang, Zijun Yao, Arya Hadizadeh Moghaddam","doi":"10.1177/00224871251325109","DOIUrl":"https://doi.org/10.1177/00224871251325109","url":null,"abstract":"Educator preparation, personalized learning (PL) implementation, and applications of Generative AI converge as three interrelated systems that, when carefully designed, can help achieve the long-sought goal of providing inclusive education for all learners. However, realizing this potential comes with challenges resulting from theoretical complexities and technological constraints. This article provides a theoretical analysis of the complex interconnectedness among these systems guided by the Cultural-Historical Activity Theory (CHAT). Building on the analysis, we introduce CoPL, a multi-agent system consisting of multiple agents with distinct functions that facilitate the complex PL design and engage pre-service teachers (PSTs) in dynamic conversations while prompting them to reflect on the inclusivity of agent-generated instructional suggestions. We describe the affordances and limitations of the system as a professional learning tool for PSTs to develop competencies for designing inclusive PL to meet diverse learning needs of all learners. Finally, we discuss future research on refining CoPL and its practical applications.","PeriodicalId":17162,"journal":{"name":"Journal of Teacher Education","volume":"34 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143661355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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