Den accelererande utvecklingen inom artificiell intelligens (AI) berör alla och har utan tvekan redan en betydande inverkan på hur utbildningspraktiker utvecklas och förändras globalt (Holmes & Tuomi 2022). Vikten av att lära sig förstå AI ur olika perspektiv lyfts fram av bland annat Europarådet (2019a) som rekommenderar alla medlemsstater att göra satsningar för att stärka medborgarnas AI-kunnande (Europarådet 2019b, rekommendation 10). I olika länders nationella strategier angående AI-kunnande har behovet i första hand fokuserat på tekniska färdigheter eller kompetenser för ett framtida arbetsliv (Penagos, Kassir & Vosloo 2020). Samtidigt har redan mängder av AI-lösningar, såsom chatbottar, rekommendationssystem och ansiktsigenkänning, blivit en del av vår vardag. AI bör därför ses som ett nutida – inte ett framtida – fenomen, och följaktligen är kunskap om olika aspekter av AI redan en viktig del av skolans innehåll och därmed centralt både för lärarstudenter och verksamma lärare (UNESCO 2021).

 Att AI är en aktuell utbildningsfråga handlar dock inte enbart om teknologiska framsteg, utan speglar också skiftande ideologier, politiska ambitioner och ekonomiska intressen (Linderoth, m. fl. 2024). Införande av AI i utbildning medför därför en diskussion där traditionella metoder utmanas i mötet med teknisk innovation och potentiell förändring av utbildning, samtidigt som gängse syn på kunskap och lärande ifrågasätts (Selwyn 2022).

I detta kapitel diskuterar vi behovet av att de verksamma i utbildningssystemet utvecklar a) förståelse för AI ur ett tekniskt perspektiv, b) förmåga att kritiskt granska och medvetet kunna välja när det är lämpligt att integrera AI i olika undervisningssammanhang och c) kompetens att använda AI utifrån ett professionellt pedagogiskt förhållningssätt. Vi inleder med att förklara vad AI är. Därefter belyses automatisering och förstärkning för att tydliggöra två huvudsakliga sätt som AI kan tänkas bidra i utbildning. Vidare beskrivs några av drivkrafterna bakom introduktionen av AI i utbildning och skola och de behov av problematisering som uppstår. Därefter diskuteras behovet av AI-litteracitet, något som kan ses som en grundkompetens alla behöver för att kunna fatta ansvarsfulla och medvetna beslut i ett samhälle där AI får allt större betydelse. Kapitlet avslutas genom att peka på vad detta specifikt kan innebära för lärare och deras arbete. 

Den ökade användningen av AI-teknologier i samhället ställer höga krav på utbildningssektorn att förbereda framtida generationer för att verka i ett sådant samhälle (Linderoth et al., 2024). Nyckelpersoner i denna utveckling är lärare. Lärare behöver kunskap om vad dessa teknologier kan användas till och också när de bör och inte bör användas i undervisning. Den här kritiska och medvetna blicken för AI-verktygens möjligheter och risker behöver introduceras redan under lärarutbildningen, vilket också ställer krav på lärarutbildares AI-litteracitet (Sperling et al., 2024).

Det här projektet har tagit sin utgångspunkt i det högaktuella utvecklingsbehovet att införa AI-litteracitet och AI-didaktik i lärarutbildningen. I såväl projektet som i den här rapporten menar vi i första hand generativ AI, när vi inte explicit uttrycker något annat. Generativ AI definieras som ett slutanvändarverktyg vars tekniska implementering innefattar en generativ modell som baseras på ’deep learning’ (Lee et al., 2025). Typiska exempel på generativ AI är Microsofts Copilot, Open AI’s ChatGPT och Googles Gemini.

AI-litteracitet definieras i rapporten som kunskap om AI (t.ex. språkmodeller och hur dessa fungerar), kunskap om användning av AI (t.ex. promptning, alltså hur man ställer frågor), och socioetisk kompetens, (t.ex. hur AI kan användas på ett ansvarsfullt och etiskt sätt i olika sammanhang) (Long & Magerko, 2020). AI-didaktik handlar om hur och när AI kan användas som ett verktyg för och i undervisning. Frågor om på vilket sätt AI-användande hjälper eller stjälper utveckling av kunskaper och förmågor hos den lärande aktualiseras.

Projektets mål har varit att utveckla designkriterier för hur AI-litteracitet och AI-didaktik kan implementeras i lärarutbildningens kurser, vilket också får implikationer för andra delar av högskolesektorn. Därigenom syftar projektet till att öka lärarutbildares förmåga att förbereda och rusta lärarutbildningens studenter för framtidens arbetsmarknad och skola. Det betyder konkret att vi i projektet, i Linköpings universitets lärarprogram, dels implementerat ett forskningsbaserat innehåll, dels utprövat undervisningsmodeller i inriktningarna förskoleklass och årskurs 1—3, samt årskurs 4—6.

International large-scale assessment studies play a significant role in educational reforms. The aim of this article is to explore the constructions of the meaning and significance of reading literacy in relation to presentations of Swedish results in 2021 PIRLS. While the National Agency for Education focuses on the positive aspects of the results, the government presented them as indicative of a ‘reading crisis.’ Furthermore, whereas the National Agency attributes the main problem in Swedish education to segregation, the government emphasises digitalisation, migration, and insufficient time allocated for reading to explain decline in reading literacy. We relate this official discourse to findings from our research project conducted in two Year 4 classes in Sweden, where we explored reading as a bodily activity. This article contributes to the critical study of international large-scale assessment studies and to reading literacy research.

In the 'Star Wars' universe, the Force is a powerful energy that can be harnessed for good or evil. Similarly, artificial intelligence (AI) in education is often depicted as a transformative power capable of revolutionizing teaching and learning. This paper explores possible futures in education in relation to generative AI and predictive AI, using informed speculation to offer insights into the future. As our visions for tomorrow's technology are being defined today, it is important to invite teachers to define the technology we should strive for. This paper presents two co-design workshops involving seven secondary-school teachers with diverse experiences and understandings of AI. Analysis of the workshop recordings informed three narrative episodes that center on lesson-planning in the future, the technical divide, and assessment agency. Education fiction is used as a mode for deep reflection on the results, staging scenarios and exploring the implications of AI in education. The results suggest that while teachers fear changes to their profession, they also offer constructive ideas for AI's potential use. This informed speculation helps to elaborate on challenges and possibilities AI poses for teachers, providing important insights into how to harness AI effectively in teaching while avoiding techno-solutionism by broadening future perspectives.

National and international policy documents emphasize the need for AI-related competencies “for all”, but there is little clarity on what these competencies should include, and determining what non-experts need to know remains a challenge. AI literacy has become a widely discussed topic in this context, often referring to a set of skills that empower individuals to critically evaluate AI, communicate and collaborate effectively with AI systems, and utilize AI as a tool across diverse contexts, including online environments, homes, schools, and workplaces. However, what AI literacy looks like in practice depends on factors such as age, level of education, and individual background. In this article, we frame AI literacy based on a qualitative analysis of the views of 33 international experts from various disciplines on what AI literacy in K-12 education should encompass. This analysis builds on existing AI literacy frameworks, with a focus on understanding and critically evaluating AI’s role in daily life, recognizing and using AI, and designing AI solutions for everyday problems. The findings show that experts emphasize a wide range of knowledge, skills, and attitudes, highlighting the importance of multiple perspectives when exploring this emerging field.

AI literacy in school education is booming within the scientific discourse of AI in education. How AI literacy is currently being framed serves diverse educational, political, and commercial purposes influencing how we imagine postdigital classrooms today and in the future. More importantly, how AI literacy emerges in primary education notably impacts how children understand AI and their own agency in a society where AI is ubiquitous. This study reviews how scientific literature conceptualises AI literacy, focusing on middle school students. An AI-adapted literacy framework (GeST) is used in the analysis to distinguish three perspectives of AI literacy (Generic, Situated, and Transformative). Forty-four papers from 2016–2024 were included in the final descriptive and qualitative analysis, showing an exponential growth in scientific papers. While still vaguely defined and poorly theorised, AI literacy materialises into different AI curricula and technology-supported teaching activities. The GeST analysis indicates that AI literacy is primarily viewed as a set of measurable skills related to generalisable theoretical knowledge that is expected to make children more competitive in a globalised and technologised world. Although some papers consider empowering students with specific competencies to challenge the AI development, critical considerations of AI in education is less visible. The paper highlights the necessity to steer the conceptualisation of AI literacy to put a stronger emphasis on critical orientations that enable students as well as teachers to examine claims about AI, and pose ethical questions to its adoption and use in classrooms and beyond.

Amid discourses that portray young people’s changing relationships to text as jeopardizing democratic society and warranting urgent interventions, this paper maps primary students’ conceptions of reading through three cartographies—simple, complex, and potentializing— using survey responses, logbooks, and co-creation sessions with 10–11-year-olds. Drawing on two Swedish Research Council–funded projects (“The Heart of Reading” and “How Hot Is the Book-Bot?”), it reveals how a simple, abstract cartography reinforces normative binaries of readers as either enthralled or disengaged. The complex cartography, grounded in students’ concrete experiences, uncovers the spatial, temporal, bodily, and emotional dimensions shaping classroom reading. Potentializing cartographies capture students’ curiosities, affirmations, problematizations, and individual variations in bodily and spatial preferences, showcasing diverse ways reading might unfold. Employing an interdisciplinary, post-qualitative cartographic approach, the study problematises and pluralises the concept of reading, moving beyond narrow literacy discourses and the perceived “reading crisis”. It argues that leveraging students’ openness to develop embodied, self-directed reading practices can enrich primary reading instruction. Ultimately, this work emphasizes the transformative power of questioning and reimagining conventional definitions of reading.

Education and teacher practices are increasingly entangled with anticipations of how Artificial Intelligence (AI) will change education. Implications for teacher education are not wholly understood. This study explores anticipations of AI in K–12 education and teachers’ pedagogical practices, and contributes to an understanding of the anticipated impacts of AI on teacher education. Interviews were conducted with experts in computer science and teacher education. Findings identify different ways AI is anticipated to influence teachers’ professional agency and judgement. The paper discusses implications for the implementation and organisation of AI in teacher education, emphasising the inclusion of educational sciences in the development of Artificial Intelligence in Education (AIED).

The motivation to read among children in Nordic countries has seen a noticeable decline in recent years. This study explores the design of social robots for stimulating interest in reading among fourth-grade students (age 10–11). We used a combination of conceptual design methods to engage teachers and students from four classes in two Swedish schools in co-creation workshops. Ideas on functions, qualities, and robot designs were generated, and based on this a set of ten distinct design concepts were created: the Facilitator, the Librarian, the Coach, the Buddy, the Assistant, the Narrator, the Creator, the Apprentice, the Portable, and the Gamer. The strengths and weaknesses of different designs were evaluated, resulting in a final design named ‘The BookBot,’ aiming to inspire and engage students in book reading through discussions of book content, character portrayal, and personalised book recommendations.

This paper provides a critical examination of the domain of artificial intelligence (AI) in education, with a focus on the expectations and practical implications accompanying its integration into teaching. The expectations have been propelled by two interconnected concepts: (1) the potential for AI to automate pedagogical processes, replacing teachers in certain scenarios; and (2) the notion that teachers’ insights can be augmented through AI-based analysis. Drawing on two ethnographic studies in Swedish primary and secondary schools, this paper explores the enactments of pupils, teachers and two AI-based educational technologies. The aim is to demonstrate how automation and augmentation can emerge in teachers’ practice. Utilizing inspiration from a relational epistemological problematisation of socio-technical phenomena, the paper demonstrates how rather than automation and augmentation, AI in education is an act of symmation in which automation and augmentation is co-produced by the technology and teachers’ different hidden work, in this paper conceptualised as adaptations, experimentations, compensations and confirmations. The paper suggests that the study of symmation in relation to the teaching profession can be productive in further exploring the yet limited understanding of AI in educational practice.