Models are at the core of scientific reasoning and science education. They are especially crucial in scientific and educational contexts where the primary objects of study are unobservables. While empirical science education researchers apply philosophical arguments in their discussions of models and modeling, we in turn look at exemplary empirical studies through the lense of philosophy of science. The studied cases tend to identify modeling with representation, while simultaneously approaching models as tools. We argue that such a dual approach is inconsistent, and suggest considering models as epistemic artifacts instead. The artifactual approach offers many epistemic benefits. The access to unobservable target systems becomes less mysterious when models are not approached as more or less accurate representations, but rather as tools constructed to answer theoretical and empirical questions. Such a question-oriented approach contributes to a more consistent theoretical understanding of modeling and interpretation of the results of empirical research.

Zusammenfassung: Schulbücher sind wichtige Medien im Unterrichtsalltagu nd beeinflussen sowohl dieP lanung vonU nterrichta ls auch denU mgangm it Fachwissen durchL ehrkräfte. DerM odellbegriff isti nd iesen Medien allgegenwärtig unddie Arts einerV erwendungi nçsterreichischenChemieschulbüchernwurde in der vorliegenden Untersuchung mitM ethodend es NaturalL anguage Processing erfasst. Es konntenT extähnlichkeiten und-unterschiede quantifiziertund anschließend qualitativ gedeutet werden.Als Fazitwirddie Modellnutzunginden untersuchten Büchernals eindimensionalbewertet, da kaum einexpliziterBezug zu systematischem, naturwissenschaftlichemA rbeitene rkennbar ist, sondernv or allemd er Abbildungscharakter vonM odellen im Vordergrundsteht. Stichworte: ModelleinSchulbüchern•Erkenntnistheorie•NaturalLanguageProcessingDo models depict particles? AnalyzingA ustrianc hemistry school textbooksv ia naturall anguage processing

The lack of time available for staying up to date with the literature is a common issue for scholars and practitioners in many disciplines. A recent challenge issued on Twitter with the goal to read 100 papers in 100 days attracted the attention of several members of the chemistry education research community. In this paper, we report the outcomes of this reading challenge, including insights into the group composition, its reading preferences, and challenges participants face. We also provide an overview of the themes covered in the group’s readings obtained via natural language processing of the abstracts of the papers read by the group. Common themes in the papers were generally centered around students, learning, and chemistry, with an emphasis on research validity and the role of technology in chemistry instruction. Differences between individual participants’ reading choices and those of the group as a whole are visualized using semantic network plots.