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The paper provides analysis of the use of instructional coaching (IC) as a prevalent trend supporting new teachers in the English system and aims to inform ongoing policy development and implementation. The qualitative study examines mentors' conceptualisations and enactment of the role of instructional coach and the readiness of mentors to assume mentors' key stakeholder roles in the professional education of early career teachers (ECTs).

Semi-structured interviews with 37 mentors explored mentors' understandings and experiences of becoming instructional coaches as part of a pilot support initiative to support ECTs in England. Two rounds of interviews were conducted to generate data related to the first six months of mentoring on the programmes. Thematic analysis identified seven semantic themes which describe manifest content found within the data and identify mentors' perceptions of their role and practice as instructional coaches. Three latent themes were developed from mentors' accounts which indicate challenges in becoming an instructional coach in this context.

Concern to apply IC “correctly” according to the programme models was a strong feature amongst both novice and experienced mentors. A key finding is the lack of explicit knowledge of professional learning pedagogies amongst mentors and insecure understanding of how new teachers learn. Assuming the role of instructional coach presented both benefits of having a “model” to follow and disadvantages in fostering limited and over-prescribed concepts and practices related to the learning of new teachers.

The study investigated mentors during the first six months of a pilot programme and the paper reports on analysis of one type of data. The research results may lack generalisability, and a longitudinal study is necessary to further explore the validity of the findings.

Sustained, high-quality professional learning for mentors is crucial to mentors' role as instructional coaches to enable mentors to develop deep, critical understanding of how IC might support new teachers and how to exercise professional judgement in working with “models”. Judicious use of time and resource is needed to enable mentors to fulfil the potential of national mentoring programmes.

The study is timely in its examination of mentors that assume the role of instructional coach as one response to national policy development that makes support for ECTs mandatory. Such strategies have wide international relevance where the retention of new teachers is a policy priority.

This paper seeks to illustrate how interventionist education reforms shape dis/trust-building processes and their impact on teacher professionalism in vocational education and training (VET) across national contexts. Using trust as the object of analysis, we discuss the affective mechanisms of becoming a professional in a standards-based neoliberal environment.

Through an analysis of VET teacher narratives in England and Austria, the paper draws attention to the ways in which policy instrumentalism has created a culture of distrust in VET. Drawing upon foundational work on system trust developed by Niklas Luhmann, we illustrate how conditions for trust sit at symbolic thresholds, which set the conditions for professional recognition within VET.

Our analysis revealed that attempts to standardise VET strategy are fuelled by the need for existential security and predictability, leading to tensions in the cultivation of system trust. Conditions for professional recognition across both contexts were based on practices of documentation and subordination, narrowly defining modes of legitimate self-expression in organisations. This constitutes a crisis of trust in VET teacher professionalism, which undermines pedagogical autonomy and integrity.

We seek to highlight the impact that reduced trust in the governance of VET can have on issues associated with teacher motivation, well-being and retention. The consideration of trust is therefore essential both for policy design and implementation in VET organisations.

The application of trust theory offers a distinctive lens through which to understand the impact of accountability, performativity and governance processes upon teacher subjectivity within VET across national contexts.

This study aims to explore whether Chat Generative Pre-training Transformer (ChatGPT) can produce quantitative data sets for researchers who could behave unethically through data fabrication.

A two-stage case study related to the field of tourism was conducted, and ChatGPT (v.3.5.) was asked to respond to the first questionnaire on behalf of 400 participants and the second on behalf of 800 participants. The artificial intelligence (AI)-generated data sets’ quality was statistically tested via descriptive statistics, correlation analysis, exploratory factor analysis, confirmatory factor analysis and Harman's single-factor test.

The results revealed that ChatGPT could respond to the questionnaires as the number of participants at the desired sample size level and could present the generated data sets in a table format ready for analysis. It was also observed that ChatGPT's responses were systematical, and it created a statistically ideal data set. However, it was noted that the data produced high correlations among the observed variables, the measurement model did not achieve sufficient goodness of fit and the issue of common method bias emerged. The conclusion reached is that ChatGPT does not or cannot yet generate data of suitable quality for advanced-level statistical analyses.

This study shows that ChatGPT can provide quantitative data to researchers attempting to fabricate data sets unethically. Therefore, it offers a new and significant argument to the ongoing debates about the unethical use of ChatGPT. Besides, a quantitative data set generated by AI was statistically examined for the first time in this study. The results proved that the data produced by ChatGPT is problematic in certain aspects, shedding light on several points that journal editors should consider during the editorial processes.

本研究旨在探讨ChatGPT是否能够为那些可能通过数据伪造行为不道德的研究人员生成定量数据集。

本研究进行了与旅游领域相关的两阶段案例研究, 并要求ChatGPT（v.3.5.）代表400名参与者回答第一个问卷, 以及代表800名参与者回答第二个问卷。通过描述统计、相关分析、探索性因子分析、验证性因子分析和哈曼的单因素测试对人工智能生成的数据集的质量进行了统计测试。

结果显示, ChatGPT能够按照所需的样本大小水平回答问卷, 并以表格格式呈现生成的数据集, 以便进行分析。还观察到ChatGPT的回答是系统性的, 并且它创建了一个在统计上理想的数据集。然而, 本研究注意到所产生的数据在观察变量之间存在较高的相关性, 测量模型未能达到足够的拟合度, 并出现了共同方法偏差的问题。本研究得出的结论是, ChatGPT目前不能生成适用于高级统计分析的数据, 或者说不适合这样做。

本研究表明, ChatGPT可以为试图不道德地伪造数据集的研究人员提供定量数据。因此, 它为关于ChatGPT不道德使用的持续争论提供了一个新而重要的论点。此外, 在本研究中首次对由人工智能生成的定量数据集进行了统计检验。结果表明, ChatGPT生成的数据在某些方面存在问题, 为期刊编辑在编辑过程中考虑的几个要点提供了启示。

ChatGPT, an artificial intelligence (AI)-powered chatbot, has gained substantial attention in the academic world for its potential to transform the education industry. While ChatGPT offers numerous benefits, concerns have also been raised regarding its impact on the quality of education. This study aims to bridge the gap in research by exploring teachers' perspectives on the adoption of ChatGPT, with a focus on identifying factors that motivate and inhibit them to adopt ChatGPT for educational purposes.

This research has employed a interpretative phenomenological analysis (IPA) qualitative approach. Through in-depth interviews among the teachers, data will be collected to identify the motivating and inhibiting factors that impact teachers' willingness to adopt ChatGPT. The data was collected from 34 teachers working across 10 branches of the University of Technology and Applied Sciences (UTAS) in Oman.

The analysis revealed four themes under motivating factors that encourage teachers to adopt ChatGPT for their educational purpose. These include Theme 1: Exploration of innovative education technologies, Theme 2: Personalization teaching and learning, Theme 3: Time-saving and Theme 4: Professional development. On the other hand, inhibiting factors includes five themes which includes Theme 1: Reliability and accuracy concerns, Theme 2: Reduced human interaction, Theme 3: Privacy and data security, Theme 4: lack of institutional support and Theme 5: Overreliance on ChatGPT.

This study contributes to the understanding of teachers' perspectives on the adoption of ChatGPT in education. By understanding teachers' perspectives, policymakers can design appropriate policies and service providers can customize their offerings to meet teachers' requirements. The study's findings will be valuable for higher education institutions (HEIs) in formulating policies to ensure the appropriate and effective utilization of ChatGPT. The study will provide suggestions to ChatGPT service providers, enabling them to focus on motivating factors and address inhibiting factors, thereby facilitating the seamless adoption of ChatGPT among teachers.

In comparison to previous studies, this study goes beyond merely discussing the possible benefits and limitations of ChatGPT in education. This research significantly contributes to the understanding of ChatGPT adoption among teachers by identifying specific motivating and inhibiting factors that influence teachers to adopt ChatGPT for educational purposes. The research enables to gain important new insights that were not previously found, giving a fresh dimension to the existing literature.