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This paper investigates the potential aspects of visual literacy that might appear when visual analytics and students interact in social science secondary classrooms. Interacting with visual technology likely demands new forms of literacy as various dimensions of complexity emerge in such learning activities where reading imposes order and relevance on what is displayed. However, only a few studies have evaluated how these visual processes emerge. Applying a socio-material semiotic approach, this paper examines the interactions between teachers, students and a visual analytics application, clarifying what strengthens or weakens the socio-material relations at work in emerging visual literacy. Methodologically, a designbased research approach is chosen. Notably, it is the early stages of the designed-based research cycle that are applied. Interventions were designed and conducted in five classes in three secondary schools in Sweden (97 students). The visual analytics application introduced was Statistics eXplorer. For each class, two to three lessons were video recorded to capture how the students interacted with the application. The socio-material analyses show that the interactions between the visual analytics and the students were both strengthened and weakened by different social as well as material forces. The actions were directed by visual properties such as movement, highlighting, and color, properties that often resulted in quick vision or locked vision. This paper argues that there needs to be a close didactic alignment and deeper knowledge of how visual interfaces attract students' attention and how students' visual literacy emerges in that relationship.

In these times, described as an ´post-truth´ era where we are faced with information overload, it is a challenge to help students find relevant information, support their knowledge building and engage them in thinking critically about information and knowledge from different perspectives. This study investigates how a visual analytics interface (with a dynalinked view of an interactive map together with interactive graphs) and students interact to solve tasks in secondary schools' social-science classrooms. Teachers are probably better able to support their students if they know more about the translations and the patterns that emerge when students try to engage in interactive graph reading. We have distinguished three patterns that emerge in the interactions. These patterns, decoding, manoeuvering and incorporation of prior knowledge, is supportive in elucidating the students' visual and analytical reasoning processes. Insights about those reasoning processes is important since earlier research has highlighted the centrality of considering the problems of the complexity of interactive graph reading and thus dealing with issues concerning students' abilities to read and interpret such graphs, when presented as part of interactive information visualization technology.

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. [ABSTRACT FROM AUTHOR]