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Digitalisering och AI förändrar i grunden hur elever söker, tolkar och använder naturvetenskaplig information. Denna avhandling undersöker hur gymnasieelever resonerar kring digitala förmågor och vilka strategier de faktiskt använder när de arbetar med naturvetenskapligt innehåll i digitala miljöer. Studien utgår från en postdigital förståelse av undervisning, där analoga och digitala resurser ses som sammanvävdadelar av samma didaktiska praktik. Genom denna lins analyseras hur uppgifter, digitala resurser, ämnesspråk och undervisningens ramar tillsammans skapar villkoren för elevernas meningsskapande.

Avhandlingen består av fyra delstudier som kombinerar intervjuer, elevresonemang och analyser av autentiska sökprocesser. Teoretiskt förenar studien perspektiv från digital litteracitet, naturvetenskapernas didaktik och den framväxande forskningen om AI-litteracitet. Centralt i avhandlingen är utvecklingen av begreppet digital mångsidighet – ett samlingsbegrepp som beskriver digital kompetens i undervisningssituationer som ett situationsbundet, relationellt och ämnesspecifik digital handlingsförmåga.

Digital mångsidighet fungerar som motpol till generella policydefinitioner av digital kompetens och förankrar digitala förmågor i undervisningens innehåll, syfte och praktiker. Studien genererar tre analytiska bidrag:

DVOS-modellen (Digital Versatility in Online Searching) konkretiserar fyra delförmågor – ämneskompetens, källitteracitet, informationskompetens och sökkompetens – och visar hur dessa aktiveras samtidigt när elever söker naturvetenskaplig information online. Modellen visar att digital kompetens inte är en uppsättning isolerade färdigheter, utan en koordination av språk, strategi och ämnesförståelse.

AD-ramverket (Aktivitetsdomäner) synliggör digitalt meningsskapande som process – elevernas växlingar mellan tolkning, begreppsanvändning, sökning och utvärdering. Ramverket visar att elevernas sökande ofta är snabbt, fragmenterat och starkt påverkat av uppgiftens utformning. Analysen tydliggör att källkritik ofta kommer för sent i processen, vilket gör att stegen före granskningen riskerar att förbises i undervisningen.

DVAI-modellen (Digital Versatility in AI) utvecklas i mötet med

generativa AI-verktyg. När söklogik ersätts av svar–först–logik förändras villkoren för lärande radikalt: elever bedömer inte bara innehåll utan även hur “trovärdigt” något låter. DVAI visar hur ämneskompetens, språklig rimlighet, teknisk förståelse och etisk bedömning samverkar i AI-stödda interaktioner – och hur elever använder vetenskapliga begrepp som verktyg för att pröva, förhandla och omformulera AI-genererade svar.

Tillsammans visar modellerna att digital kompetens i naturvetenskapliga klassrum bäst förstås som en postdigital och epistemisk praktik. Resultaten pekar på att undervisning behöver rikta större uppmärksamhet mot de tidiga stegen i elevernas digitala arbete – hur de formulerar frågor, tolkar uppgifter och orienterar sig i ämnesspråket – eftersom dessa steg avgör vilken kunskap som överhuvudtaget blir synlig.

Avhandlingen bidrar därmed med empiriskt grundade modeller som kan stödja lärare i att planera, analysera och utveckla undervisning i en tid där digitalisering och generativ AI snabbt förändrar skolans villkor. Genom modellerna DVOS, DVAI och ramverket AD erbjuds ett didaktiskt språk för att beskriva och förstå digitalt meningsskapande som både dynamiskt och undervisningsbart.

Accelerating digitalization actualizes the importance of secondary science education in developing students’ digital abilities, such as retrieving and appraising scientific information online. However, there is little research and policy guidance on the purposes and challenges of teaching digital abilities in science classrooms. This article reports on a mixed-methods study that explored how upper secondary school students in Sweden reasoned about their digital abilities when searching for scientific information online. The results reveal three key themes: the role of scientific terminology in improving search accuracy, as students noted how precise terms yielded more credible results; the need for deliberate search strategies, including using questions or keywords depending on the context; and, the impact of selective exposure, as students became aware of how personalized results could reinforce existing beliefs and limit perspective diversity. Based on these insights, we introduce the concept of ‘digital versatility’ and outline a model, Digital Versatility in Online Searching (DVOS), that integrates essential digital abilities (source literacy, information abilities, and search abilities) with scientific subject knowledge. The DVOS model provides guidance for teachers in instructional planning and offers a basis for future research on digital abilities in science education.

Secondary schools need to develop students’ digital competence. In Sweden this requirement is included in governing documents for school subjects such as civic and history. However, the governing documents for science education in Sweden lack these requirements. This study aims to explore students’ reasoning about digital information retrieval in biology education. The research question is: How do secondary school students’ reason about filter bubbles and their use of search engines when searching for scientific knowledge online? The study employs mixed methods, including (1) a questionnaire with open-ended and multiple-choice questions, (2) written reflections (3) focus group discussions. Altogether 68 students participated in the data collection. The data collection methods were informed by Ribble's framework for digital citizenship  and guided the abductive thematic data analysis. Theme 1: search results and science concepts. Students’ responses indicate a belief that search results are primarily influenced by the keywords used and the search history. Students argued that more serious, credible, and precise search results can be obtained if one uses correctly spelled keywords, appropriate science concepts and synonyms. Theme 2: filter bubbles and information overload. Students demonstrated a low level of awareness about how filter bubbles can influence search results and what consequences this may have for social life; rather than problematizing filter bubbles. These preliminary results indicate that the participating students demonstrate insufficient digital competence and under-developed online search practices when searching for biology-related knowledge online. More research is needed on how science teachers can help students develop the skills and attitudes they need to engage critically and constructively with the ever-increasing amount of science-related information online.       

This paper intends to describe a new pedagogical approach to teach science subjects and the practical implementation of the method in regular lessons in schools in Europe.

The Analogous Comparison and Transfer Method (ACAT) was developed in School Education and focuses on the age of 16 to 18 years old students. The method uses analogous comparisons by taking examples or situations from everyday life and in consequence the logical or analogous transfer to the scientific problem. The method uses the development of imaginations or “pictures in the head” to develop a view of the analogy; this picture is transferred as a problem-solving idea to the concrete scientific problem. Multimedia material like animations are used to provide a higher level of imagination and to develop the understanding for the discussed problem. The method was developed for the subject physics, mathematics, chemistry, biology and computer science and was tested in a case study in physics at high school level in Austria.

The second text in praxis is currently done in the frame of the Erasmus+ Project (2018-1-ES01-KA201-050186 Cooperation for innovation and the exchange of good practices) named Technology Enhanced Science Teaching (TEST). In the frame of the project, 15 different teaching units for science subjects have been developed, implemented and tested in current teaching.

The learning units were created with different tools on a multimedia and interactive basis. They are available as web-based material that always uses the ACAT method. The ongoing Covid-19 pandemic resulted in additional experiences, which are also reported in this paper.

The first experiences with the learning units were positive and showed additional added value in addition to the advantages of the ACAT method. The learning units can be used in the framework of distance learning as part of "home schooling" (practiced as part of the Covid-19 crisis). The material is also suitable for pre-class use in the context of flipped learning (following the ideas of Jon Bergmann). The case study in Austria also showed that female learners have an advantage in learning complex scientific contexts through this method.

The learning units will be tested in schools in Spain, Austria, Ireland and Sweden, and the results will show the extent to which the ACAT method and the new multimedia-based approach to teaching in science teaching make learners more successful.

Abstract: Digital information searching is a central part of secondary school students’ academic work, yet it is often treated as a set of general technical skills rather than as a subject-specific and strategic ability. This study examines how students describe digital abilities—subject competence, source literacy, information competence, and search competence—in relation to science content and different phases of online search processes. Two research questions are addressed: how students articulate digital abilities, and how these abilities interact across the phases of the search process.

The study was conducted with 27 upper secondary students. Data were collected through logbooks, questionnaires, and pod discussions, and analysed using four activity domains (interpretation, planning, navigation, evaluation) and three knowledge forms (conceptual, procedural, and metacognitive). Findings show that students’ articulation of their digital abilities varied in complexity—from general use of subject terms to strategic adaptation and metacognitive reflection.

Multiple abilities were often activated concurrently, particularly when navigating and evaluating information. The study refines the DVOS (Digital Versatility in Online Searching) model by integrating knowledge forms as an analytical lens, thereby clarifying how digital versatility takes shape in practice. It also contributes new frameworks for understanding and supporting digital versatility in science education.

Denna studie undersöker hur gymnasieelever resonerar kring användningen av generativ AI, särskilt ChatGPT, i samband med digital informationssökning inom naturvetenskap. Syftet är att analysera hur olika aspekter av digitalt kunnande kommer till uttryck i elevernas resonemang. Studien utgår från modellen Digital Versatility in Online Searching (DVOS) och prövar dess relevans i en AI-baserad kontext där informationssökning sker genom dialog snarare än genom traditionella sökmotorer.

Empirin består av klassrumsnära data insamlade 2023 och 2024 genom videodokumenterade elevdiskussioner, enkäter, loggböcker, podcastsamtal och fokusgrupper. Analysen, inspirerad av DVOS-modellens fyra delförmågor – ämneskompetens, källiteracitet, informationskompetens och sökkompetens – fokuserar på hur elevernas resonemang varierar från begreppslig orientering till metakognitiv reflektion. Eleverna beskriver att de använder ChatGPT både som snabb informationskälla och som stöd för att pröva begrepp och resonemang, men deras förhållningssätt till generativ AI spänner från instrumentellt till reflekterande. Många beskrev att de bedömde AI-svar utifrån språkets trovärdighet snarare än ämnesmässig logik, samtidigt som flera uttryckte medvetenhet om teknikens funktion, begränsningar och det egna ansvaret i användningen. Resultaten tyder på att digitalt kunnande i AI-miljöer tar form som en växling mellan språk, teknik och ämnesförståelse, vilket motiverar en anpassning av DVOS till en AI-kontext. Modellen Digital Versatility in AI (DVAI) presenteras som begreppslig modell för att resonera kring hur elever utvecklar ämneskompetens, källkritisk vaksamhet, tekniklogik och dialogisk sökförmåga i mötet med generativ AI.

Digital search strategies are essential for science learning in today’s digital age, but knowledge about students’ search strategies, especially in relation to scientific content, is limited. This study examines how upper-secondary students incorporate scientific content into their search processes. Video recordings of students’ online searches and peer-to-peer discussions during two tasks of varying complexity were analyzed using Legitimation Code Theory (LCT) and semantic analysis. The findings, based on a semantic analysis of students’ reflections, confirmed three previously identified search strategies - linear, one-shot, and random search - while revealing three additional ones: targeted refinement, text-to-image searches, and piecewise searching. These strategies illustrate how students engage with scientific content in different phases of digital search processes. The results indicate that strategies involving conceptual abstraction and iterative refinement were associated with stronger semantic shifts. By adapting LCT to analyze students’ meaning-making the study contributes to a novel framework for exploring how digital search practices intersect with scientific understanding.