While Artificial Intelligence is becoming prevalent in every field of work (Müller & Bostrom, 2016), Artificial Intelligence in Education (AIED) has only really gained visibility and practical application in the educational context over the past few years (Renz, Krishnaraja, & Gronau, 2020). The adoption and advancement of AI in education has been slower than other fields (Holmes, 2019; Luckin, Holmes, Griffiths, & Pearson, 2016). However, it is known that new digital technologies will only be integrated if teachers perceive them to be useful in learning (Scherer, Siddiq, & Tondeur, 2019). To potentially improve adoption of AI tools, it is important to include teachers in the process of development to ensure they are relevant in teaching and learning.

As AI comes into education more rapidly, it is important that teachers are involved in the process of developing tools and applications, so they are useful and meaningful in practice and learning. Teachers’ participation in the adoption and development of AI are subjects that are rarely discussed (Williamson & Eynon, 2020). Therefore, the current research addresses the first part of this question: What is teachers’ participation in AI development? Digital technologies are only integrated in learning and practice if teachers feel it has a positive effect on learning and helps them to achieve instructional goals they consider essential (Howard, Curwood, & McGraw, 2018). Perceived usefulness is key for technology adoption (Teo, 2015). However, if teachers and educators are not involved in the process of developing AI, it may limit the relevance of new AI tools in teaching and learning. Understanding teachers’ participation in this process is a first step to understanding the potential of AI adoption in teacher practice.

To explore teachers’ involvement in the process of developing tools and applications, it is necessary to analyse research in the field to assess our understanding and practice in this area. To address this question, the current study has identified 88 articles related to teachers’ participation in the process of developing AIED tools and applications. Using explicit inclusion and exclusion criteria, 23 empirical articles were retained for the research. However, it is intended to continue the selection and revision of more recent publications to understand what role educators have played in the current AI integration to the pedagogical practices. It is noticeable the small sample of articles which may be due to the lack of study and engagement of researchers with this topic.

The conclusions reveal that AIED tools have been developed as a replacement of teacher in more procedural tasks such as administrative labour (e.g. Cutumisu, Blair, Chin, & Schwartz, 2017), which might not attend the real necessities of an educator in the classroom. Teachers have limited experience and are not the main agents who decide for adoptions or the ones responsible for the validation of AIED tools tested in the classroom (e.g. Young Oh, Song, & Hong, 2020). Teachers’ limited experience might also affect their perceptions of a technology that is often seen as a threatening type (Stone et al., 2016). Reviewing the literature in this area helps to define our current understanding of teachers’ participation in developing AIED tools and applications for the educational context and their possible perceptions of the technology which can inform how work in this area can be improved in the future.

To identify relevant articles on teachers’ participation in AI development, Scopus, Web of Science and ERIC were searched. A date range was also considered in the initial search. AIED has changed rapidly (Langran & Ph, 2020) and a recent search seemed to be appropriate for this review. The articles and conference papers from 2017 to 2020 were initially identified. The initial criteria for the research included peer-reviewed articles in English published in peer-reviewed journals rated as Q1 and Q2 in SJR. The search was conducted in July 2020. The keywords used in all three database searches were “Artificial intelligence” OR “Computational intelligence” OR ai OR AIED OR “intelligent systems” Education OR pedagogy OR teaching OR learning “Primary education” OR “Secondary education” OR “Elementary education” OR “Middle school” OR “Elementary school” OR K-12 Application OR implementation. ERIC database presented 25 paperwork, Web Science showed a total of 16 and Scopus retrieved 47 papers that would pass to the second part of the selection. Initial screening of 88 articles led to a full-text screening of 25 articles, however, 2 articles could not be retrieved through the library order scheme. Duplicates were then removed from the corpus. The abstract of each paper was carefully analysed to ensure the document would fit be suitable to possibly answer the research questions developed for this review. Questions about how teachers are involved in the process of AIED tools development and adoptions in the classrooms; and who are the main agents involved in the AIED adoptions in schools were used as guide for the research and review. A final total of 23 papers were identified and key findings summarised. To extract the data, the articles were uploaded into Mendeley software and coded. The coding process included article information such as year of publication, journal name, authorship), literature used (relevant bodies of literature to this research), observations and arguments (existing evidence in the literature related to the educator’s participation in the process), educational setting (primary, middle or high school), study design (empirical or descriptive study) and AIED tool used (application, methods, and evidence of teachers’ involvement). The limitations of the search include research published in other languages rather than English and book chapters and grey literature what was not indexed in the chosen databases. Future steps include new searches that can improve the results, change the findings or be included in the conclusions.

Initial findings show that teachers are rarely involved in the development of AIED tools and even more difficult it is to find teachers involved in the process of adoption of such tools in the classroom. If there is an urgent demand of AIED tools to be adopted in the classrooms (Macgilchrist, Allert, & Bruch, 2020; Zawacki-Richter, Marín, Bond, & Gouverneur, 2019), it is crucial to include teachers in the process of AIED tools development to ensure they are relevant to the educators’ practice. AI’s growth in the field of education is expected to be 47.5% by the end of 2021 (Cortez, 2018). Teachers are responsible for what is taught in the classroom and know the needs of their students. Once teachers are not considered in the development of the tools, or do not perceive them as useful, or once their needs are not addressed by the new tools presented, there is a high chance that new tools will not be adopted. Teachers’ views on and perceptions of AI and its uses should be included in the development process. As highlighted by Williamson (2020), there should be more dialogue between across the “different academic communities focused on AIED”. The review suggests there is a need for research considering the relationship between teachers and AI. The uncertainties that this new technology brings demands future research in the field. This study intends to continue the search for valuable papers that can disclose the role that educators play in the AIED development and adoption scenario.

Cutumisu, M., Blair, K. P., Chin, D. B., & Schwartz, D. L. (2017). Assessing Whether Students Seek Constructive Criticism: The Design of an Automated Feedback System for a Graphic Design Task. International Journal of Artificial Intelligence in Education, 27(3), 419–447. https://doi.org/10.1007/s40593-016-0137-5 Holmes, W. (2019). Artificial Intelligence in Education (1st ed.). Boston: The Center for Curriculum Redesign. Retrieved from http://bit.ly/AIED-BOOK Howard, S., Curwood, J., & McGraw, K. (2018). Leaders Fostering Teachers’ Learning Environments for Technology Integration. In Second Handbook of Information Technology in Primary and Secondary Education (pp. 1–19). Charlottesville, USA: Springer, Cham. https://doi.org/https://doi.org/10.1007/978-3-319-71054-9_35 Luckin, R., Holmes, W., Griffiths, M., & Pearson, L. B. F. (2016). Intelligence Unleashed. An argument for AI in Education. Pearson. Retrieved from http://oro.open.ac.uk/50104/1/Luckin et al. - 2016 - Intelligence Unleashed. Renz, A., Krishnaraja, S., & Gronau, E. (2020). Demystification of Artificial Intelligence in Education – How much AI is really in the Educational Technology? International Journal of Learning Analytics and Artificial Intelligence for Education (IJAI), 2(1), 14. https://doi.org/10.3991/ijai.v2i1.12675 Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers and Education, 128(0317), 13–35. https://doi.org/10.1016/j.compedu.2018.09.009 Stone, P., Brooks, R., Brynjolfsson, E., Calo, R., Etzioni, O., Hager, G., … Teller., A. (2016). Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, 52. Teo, T. (2015). Comparing pre-service and in-service teachers’ acceptance of technology: Assessment of measurement invariance and latent mean differences. Computers and Education, 83, 22–31. https://doi.org/10.1016/j.compedu.2014.11.015 Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology. Routledge. https://doi.org/10.1080/17439884.2020.1798995 Young Oh, E., Song, D., & Hong, H. (2020). Interactive Computing Technology in Anti-Bullying Education: The Effects of Conversation-Bot’s Role on K-12 Students’ Attitude Change toward Bullying Problems. Journal of Educational Computing Research, 58(1), 200–219. https://doi.org.10.1177/0735633119839177