READ ME File For 'Generative AI tools and teachers’ research-informed practice' Dataset DOI: 10.5258/SOTON/D3185 Date that the file was created: August, 2024 ------------------- GENERAL INFORMATION ------------------- ReadMe Author: Stephen Sowa, University of Southampton Date of data collection: June-August 2024 Information about geographic location of data collection: n/a (secondary data collected online) Related projects: n/a -------------------------- SHARING/ACCESS INFORMATION -------------------------- Licenses/restrictions placed on the data, or limitations of reuse: no restrictions placed on the data Recommended citation for the data: Sowa, S., Brown, C., Choi, T-H., and Newman, R. (2024) Generative AI tools and teachers’ research-informed practice. https://doi.org/10.5258/SOTON/D3185 Links to other publicly accessible locations of the data: n/a Links/relationships to ancillary or related data sets: n/a -------------------- DATA & FILE OVERVIEW -------------------- This dataset contains: a protocol for the systematic review; lists of included and excluded studies; inter-rater reliability calculations; data extraction documents; coding documents; and quality appraisal documents. File list: Systematic review protocol - Word document detailing the protocol used for the systematic review. Study Screening - Excel file showing the abstract and full-text screening of the studies using Covidence. Grey Literature Full-Text Screening - Word document detailing the full-text screening of grey literature. Inter-Rater Reliability - Excel file showing the data used to calculate inter-rater reliability scores. Data Extraction - Word document summarising the included the studies and associated evidence/data extracts. Coding - Word document detailing the coding process as part of a thematic analysis of the review evidence. Quality Assessment - 19 Word documents detailing the results from the quality assessment process using the Mixed Methods Appraisal Tool (MMAT). Relationship between files, if important for context: Documents are part of a systemic review of literature on teachers’ uses of generative AI tools to find and incorporate research evidence into their practice. Additional related data collected that was not included in the current data package: n/a If data was derived from another source, list source: Prakasha et al. (2024) - User experiences of ChatGPT among engineering students, teachers, and working professionals in India Ulla et al. (2023) - 'To generate or stop generating response': Exploring EFL teachers' perspectives on ChatGPT in English language teaching in Thailand Galindo-Domínguez et al. (2023) – An analysis of the use of artificial intelligence in education in Spain: The in-service teacher’s perspective Govindarajan & Christuraj (2023) - Opportunities and challenges of using ChatGPT in the ELT scenario of Utas, Nizwa, Oman Gustilo et al. (2024) - Algorithmically-driven writing and academic integrity: exploring educators' practices, perceptions, and policies in AI era Moorhouse & Kohnke (2024) - The effects of generative AI on initial language teacher education: The perceptions of teacher educators Bhaskar & Rana (2024) - The ChatGPT dilemma: unravelling teachers’ perspectives on inhibiting and motivating factors for adoption of ChatGPT Uribe et al. (2024) - Artificial intelligence chatbots and large language models in dental education: Worldwide survey of educators ElSayary (2023) - An investigation of teachers' perceptions of using ChatGPT as a supporting tool for teaching and learning Kartal (2024) - The influence of ChatGPT on thinking skills and creativity of EFL student teachers: a narrative inquiry Chiu (2023) - The impact of Generative AI (GenAI) on practices, policies, and research direction in education: a case of ChatGPT and Midjourney Alammari (2024) - Evaluating generative AI integration in Saudi Arabian education: a mixed-methods study Hasanein & Sobaih (2023) - Drivers and Consequences of ChatGPT Use in Higher Education: Key Stakeholder Perspectives Davis and Lee (2023) - Prompt: ChatGPT, Create My Course, Please! Derakhshan & Ghiasvand (2024) - Is ChatGPT an evil or an angel for second language education and research? A phenomenographic study of research-active EFL teachers' perceptions Tapan-Brout?n (2024) - Exploring Mathematics Teacher Candidates' Instrumentation Process of Generative Artificial Intelligence for Developing Lesson Plans Department for Education, UK Government (2024) - Generative AI in education: Educator and expert views Al-Mughairi, H., & Bhaskar, P. (2024). Exploring the factors affecting the adoption AI techniques in higher education: insights from teachers' perspectives on ChatGPT Nguyen Thi Thu (2023) - EFL Teachers’ Perspectives toward the Use of ChatGPT in Writing Classes: A Case Study at Van Lang University If there are there multiple versions of the dataset, list the file updated, when and why update was made: n/a -------------------------- METHODOLOGICAL INFORMATION -------------------------- Description of methods used for generation of data: a thematic analysis was used to analyse data collected from a systematic review of literature. Describe any quality-assurance procedures performed on the data: Used the Mixed Methods Appraisal Tool (MMAT) to assess the quality of the studies and data. People involved with sample collection, processing, analysis and/or submission: Stephen Sowa, Chris Brown, Tae-Hee Choi, and Rachele Newman.