Artificial Intelligence in K-12 Education: eliciting and reflecting on Swedish teachers' understanding of AI and its implications for teaching & learning

Abstract

Uncovering patterns and trends in vast, ever-increasing quantities of data has been enabled by different machine learning methods and techniques used in Artificial Intelligence (AI) systems. Permeating many aspects of our lives and influencing our choices, development in this field continues to advance and increasingly impacts us as individuals and our society. The risks and unintended effects such as bias from input data or algorithm design have recently stirred discourse about how to inform and teach AI in K-12 education. As AI is a new topic not only for pupils in K-12 but also for teachers, new skill sets are required that enable critical engagement with AI. AI literacy is trying to close the gap between research and practical knowledge transfer of AI-related skills. Teachers' AI-related technological, pedagogical and content knowledge (TPACK) are important factors for AI literacy. However, as teachers' perspectives, beliefs and views impact both the interpretation and operationalisation of curriculum. this study explores teachers' and teacher educators' understanding and preconceptions of AI to inform teacher education and professional development. To gain a comprehensive understanding of teachers’ conceptualisations regarding AI an anonymous questionnaire together with focus group discussions were employed. The qualitative content analysis underpinned by the theoretical framework Intelligent TPACK reveals that teachers' AI-related content knowledge is generally gained through incidental learning and often results in pre- and misconceptions of AI. Our analysis also revealed several potential challenges for teachers in achieving core constructs of Intelligent TPACK, examples of such challenges are vague and unclear guidelines in both policy and curriculum, a lack of understanding of AI and its limitations, as well as emotional responses related to participants' preconceptions. These insights are important to consider in designing teacher education and professional development related to AI literacy.

Teachers’ AI-TPACK: Exploring the Relationship between Knowledge Elements

“…The main objective of this research is to integrate AI technologies to form the teacher's AI-TPACK framework and evaluate the knowledge elements described within the teacher's AI-TPACK framework. When developing and validating this tool, recommendations from recent publications [25,98] and analyzed data from various perspectives were considered.…”

Activity Theory-based Ecosystem for Artificial Intelligence in Education (AIED)

“…However, TPACK seems unclear in terms of its relationship to educational policy and the overall curriculum (O'Dea & O'Dea, 2023). In addition, it lacks consideration towards the social and emotional contexts of both teachers and students (Velander et al, 2023). Therefore, there is somewhat a need to develop a more over encompassing theoretical framework for AIED.…”

“…There are, however, some challenges associated with the use of TPACK as an overarching model. A common problem regarding the implementation of TPACK at the institutional level is the lack of consideration given to teachers' perspectives, beliefs, and how their views affect both the interpretation and operationalization of the course curriculum (Velander et al, 2023).…”

The influence of sociodemographic factors on students' attitudes toward AI-generated video content creation

“…Thus, the impact of AI-generated video creation on sociodemographics presents a compelling area for research, with several notable research gaps that merit investigation. While AI has the potential to support content creation and amplify diverse voices, there is a notable scarcity of studies that delve into how AI-driven video production technologies specifically affect marginalized or underrepresented sociodemographic groups (Kuhn et al, 2023;Velander et al, 2023). Understanding whether AI-powered platforms facilitate greater inclusivity and representation or, conversely, exacerbate existing disparities in sociodemographics is a critical research gap.…”

“…Both AI and ML technologies have played a pivotal role in the creation of highly convincing synthetic videos. One prominent application is video content creation, which leverages NLP to superimpose one person's face onto another's in multimedia footage, giving the illusion of realistic impersonation (Velander et al, 2023). Furthermore, AI has enabled the emergence of virtual influencers, entirely computer-generated characters that engage with audiences on social media platforms and in advertising campaigns.…”