By Rasmus Leth Jørnø, Susanne Dau og Stig Toke Gissel
AI technology has made great strides in recent years and has (perhaps) the potential to revolutionize the way we teach and learn. As so often before when new technology meets the education sector, the debate about AI’s importance to education has divided the waters. The use of AI in education can potentially personalize learning, increase student motivation and engagement, and help teachers and educators effectively evaluate student progress. Conversely, critical voices paint a picture of an education system with a greater degree of social isolation. The fear of a dehumanization of work areas that were previously the domain of humans, as well as a non-democratic and otherwise disproportionately large power for various tech giants, is also significant.Read full preface
From a teaching aids perspective, the three editors of this themed issue will argue that, as a starting point, we must always try to understand the new technologies and their potential effects on teaching and learning before passing judgment on the technologies. We write this knowing that we cannot predict how, for example, a new technology such as AI will change the ways in which we teach and learn – and the ways in which we view and problematize teaching, evaluation and learning processes at all.
We can perceive technology as culture in the process of creating itself. The French philosopher of technology Gilbert Simondon (1924-1984) describes technology as the human capacity to be self-determined. We (re-)create our own environment at the same time that in the process we reorganize ourselves in such a way that organism and environment change the complex problems we face. Technology should therefore not be seen as a neutral means, medium, artefact or tool, where only our intentions determine their meaning. The technology value is for better or worse, borne by our standing capacity to assess and translate them into action, materials, networks and infrastructure. And what we do is not always the same as what we want or think we are doing. These days, it is AI that is creating a stir in the education sector and challenging our understandings of didactics, learning, evaluation and teaching aids. In this edition of Learning Tech, we present four articles under the theme of AI in didactics and education.
In the theme issue’s first article, Use of AI-powered technologies in upper secondary language learning, Bundgaard and Møller present the results of a survey of high school students’ use of and attitudes towards AI-based machine translation in foreign language teaching. AI-supported language technologies in particular are an example of AI being widespread and has gradually been in play in the world of education for a while, at least as far as students are concerned. But that teachers may have failed to relate sufficiently to the technology.
In the article Between the Clicks – Student learning paths when interacting with an adaptive learning resource in 4th grade mathematics, Gissel and Jørnø examine fourth grade students’ interaction with an adaptive learning resource for mathematics teaching. The purpose of the article is to achieve a deeper understanding of the interaction between a student and an AI-based learning tool through screen recordings of the students’ behavior in relation to the professional challenges the learning tool presents the students. The article thus provides insight into how the adaptive learning tool handles students who act differently and come with different prerequisites, while at the same time drawing a picture of how the students react to being in the hands of the adaptive machine, Rhapsode.
In the theme issue’s third article, Scaffolding teaching – between learning objective and assessment when using AI chatbots, Jensen, Gade and Dau examine ethical and pedagogical perspectives on the use of ChatGPT through a case study. The article examines students’ perspectives on how teachers can scaffold their use of ChatGPT in relation to the work with learning outcomes and the teachers’ evaluation practices. The study is based on focus group interviews with students on higher education. On the basis of the empirical data, a conceptual framework for the use of generative AI is derived, which teachers in higher education can use to scaffold the students’ learning. The conceptual framework addresses cognitive, pedagogical and teaching perspectives on activities and evaluation in relation to the use of ChatGPT in teaching and learning processes.
In the theme issue’s fourth article Measuring fluent reading with eye movements in school, Klerke and Engmose present a study in which eye-tracking technology is used to measure students’ reading in an attempt to translate data into reading insights. With the technology, breakdowns in students’ reading fluency can be captured to find correlations between eye movements and reading/spelling test scores and focus words. The study is based on data from 68 students from five fourth grades. The intention is to translate such goals into practical relevance, for example teaching evaluation.
The fifth and final article of the theme issue Danish high school students’ multimodal use in physical and digital learning spaces by Nielsen and Jensen is based on observation studies four high school courses. In the article, there is a focus on the students’ professional reading, and four different types of digital students are identified, each of whom uses digital teaching aids in different ways. The four identified digital student types are characterized in the article as: Digital passengers, digital dreamers, digital soloists and digital social creators. On the basis of the article’s findings, recommendations are derived for design principles in relation to the development of digital teaching aids. The article also contributes perspectives on how student behavior can strengthen the communities in the transformed learning spaces and how students’ multimodal gaze can support expertise. The article is off topic.