Apps have become a significant part of contemporary social life in a very short period of time, with the dominant app distribution stores having debuted only in 2008. During that period, apps have become mundane software, and it is precisely because of this mundaneness that they are now situated in nearly each aspect and facet of contemporary society, including education. Educational apps are a distinctive category in app stores, tailored to all levels of the educational field (from kindergarten to higher education; from formal to non- and informal learning), and comprising over hundreds of thousands of apps with many different forms of projected usage (Zosh et al. 2017). Apps both extend (i.e., give additional functionalities to) and transcend (i.e., are operating outside) the regular educational system (Cherner, Dix, and Lee 2014). In both cases, their specialized nature generally implies that the type of learning that is envisaged is highly specific and focused on delineated and predetermined aspects or subjects (Godwin-Jones 2011).

At the same time, the proliferation and sheer abundance of educational apps has given rise to several concerns. Many apps are unclear, unreflexive or untested as far as their educational design and underlying didactic philosophies is concerned, leading Hirsh-Pasek et al. (2015:3) to the conclusion that the educational app industry in practice amounts to ‘a vast, unplanned experiment’ on its – often very young – user base. Next to this didactic indistinctiveness, concerns have equally been raised in view of app developers’ tendencies to surreptitiously collect and mine user data for commercial purposes, thereby turning private data into the circulating currency par excellence within the educational app industry (Herold 2016). Furthermore, it has equally been argued that apps tend to reduce education and learning to its most traditional, salient and visible components such as the test, the quiz or the lecture, thus offering environments that are largely built on technological affordances rather than on educational rationales (Salomon 2016).

Despite these important general concerns, sociologies of education have not yet often been directed towards an up-close study of educational apps. Curiously, whereas recent years have seen a general upsurge of critical sociological studies that seek to analyze (and counter) the instrumentation, instrumentalism and rhetoric reigning in the broad field of educational technology (Eynon 2018), these studies have largely sidestepped the specific field of educational apps. Whilst some arguments about the educational relevance of app analysis have already been made, and whilst educational apps have already been the subject of some critical scrutiny (e.g. Williamson 2017), critical studies of educational apps are still few and far between. Moreover, most of the sociologically inspired studies tend to focus on how these apps are positioned within wider discursive and policy networks, rather than on the operations that are performed in the app itself. It is the aim of this paper to develop a critical approach to the study of educational apps, and to do so by developing a heuristic framework that can be deployed to scrutinize such apps. In order to do so, we will analyze three apps that all target an adult user base and that reflect the huge variety in types of educational apps: a learning to code app (e.g. Grasshopper), a language learning app (e.g. Duolingo) and a more general learning app (e.g. edX).

The specific approach of this paper is a multi-situated app study (Dieter et al. 2018) and is more particularly grounded in Science and Technology Studies (STS). One of the central characteristics of STS is the adoption of a relational ontology, which does not prioritize social or material dimensions in researching a setting (such as an educational app). Instead of focusing exclusively on social and/or material dimensions, STS places analytical focus on the relations between actors, and contends that it are precisely these relations that are constitutive in the shaping of sociality, materiality and/or technicality (Decuypere and Simons 2016; Fenwick and Edwards 2010). That is to say, the point of departure is that practices are never pregiven – rather, they are shaped in and through the relations that are formed between different actors. Practices, thus, do not exist prior to their operations: they are realized or enacted in the course of their effectuation (Woolgar and Lezaun 2013). As such, STS operates as sensitizing device that allows to focus on the relational features of apps – in particular how the relational interplay between technologies and individuals shapes and makes different sorts of users, forms of learning, conceptions about education, and so on (Decuypere 2019).

In order to disentangle the socio-technical operations performed by apps, we foreground and will analyze each app according to four dimensions. First, the ecologies of apps will be scrutinized, that is, their situatedness within larger wholes (e.g. websites, similar apps in stores) and what this relational embeddedness and infrastructural positioning tells us about how apps are inscribed and positioned within distinct thematic, discursive, and algorithmically-tailored and curated fields. Next to ecologies are the technologies that are operational in app practices, such as algorithmic and platform technologies. Whereas these technologies are increasingly argued to be dispersed, not directly amenable to scrutiny, and opaque from the point of view of their technical details or their underlying operations, STS focuses not so much on what algorithms and platforms are as on what they do (Bucher 2018). As such, the attention is not so much on the technical intricacies of an app’s architecture, but rather on the effects that this platform architecture generates and, thus, on how it makes different versions of reality (Bucher 2018:56). A third dimension consists of the subjectivities that are being shaped in relation to these ecologies and technologies. Apps do not function in a vacuum: they have particular sorts of projected users in mind and, hence, always have a specific understanding about ideal learners or students. These ideal users are not only assumed, they are equally actively being created: technological environments actively configure or script particular kind of users (Woolgar 1990). A fourth and last dimension is that educational apps always install a particular learning regime: a particular understanding about what learning is and about the specific forms of learning that are considered to be worthwhile (Decuypere 2019; Williamson 2017).

Bucher, Taina. 2018. If...Then: Algorithmic Power and Politics. Oxford University Press. Cherner, T, J Dix, and C Lee. 2014. “Cleaning up That Mess: A Framework for Classifying Educational Apps.” Contemporary Issues in Technology and Teacher Education 14 (2): 158–93. Decuypere, Mathias. 2019. STS in/as education: Where do we stand and what is there (still) to gain? Some outlines for a future research agenda. Discourse: Studies in the Cultural Politics of Education. Decuypere, Mathias, and Maarten Simons. 2016. "Relational thinking in education: Topology, sociomaterial studies and figures". Pedagogy Culture & Society 24 (3): 371-386. Dieter, Michael, Carolin Gerlitz, Anne Helmond, Nathaniel Tkacz, Fernando Van Der Vlist, and Esther Weltevrede. 2018. “Store, Interface, Package, Connection : Methods and Propositions for Multi-Situated App Studies.” CRC Media of Cooperation Working Paper Series. Eynon, Rebecca. 2018. “Into the Mainstream : Where next for Critical Ed Tech Research ?” Learning, Media and Technology 43 (3): 217–18. doi:10.1080/17439884.2018.1506976. Fenwick, Tara, and Richard Edwards. 2010. Acor-Network Theory in Education. London: Routledge. Godwin-Jones, R. 2011. “Emerging Technologies: Mobile Apps for Language Learning.” Language Learning & Technology 15 (2): 2–11. doi:ISSN 1094-3501. Herold, Benjamin. 2016. “Google Acknowledges Data Mining Student Users Outside Apps for Education.” https://blogs.edweek.org/edweek/DigitalEducation/2016/02/google_acknowledges_data_mining_GAFE_users.html. Hirsh-Pasek, Kathy, Jennifer M. Zosh, Roberta Michnick Golinkoff, James H. Gray, Michael B. Robb, and Jordy Kaufman. 2015. “Putting Education in ‘Educational’ Apps: Lessons From the Science of Learning.” Psychological Science in the Public Interest 16 (1): 3–34. doi:10.1177/1529100615569721. Salomon, Gavriel. 2016. “It’s Not Just the Tool but the Educational Rationale That Counts.” In Educational Technology and Polycontextual Bridging, edited by E Elstad, 149–61. Rotterdam: Sense Publishers. Williamson, Ben. 2017. 2017. “Decoding ClassDojo: Psycho-Policy, Social-Emotional Learning and Persuasive Educational Technologies.” Learning, Media and Technology 42 (4): 440–53. doi:10.1080/17439884.2017.1278020 Woolgar, Steve, and Javier Lezaun. 2013. “The Wrong Bin Bag: A Turn to Ontology in Science and Technology Studies?” Social Studies of Science 43 (3): 321–40. doi:10.1177/0306312713488820. Zosh, Jennifer M., Sarah R. Lytle, Roberta Michnick Golinkoff, and Kathy Hirsh-Pasek. 2017. “Putting the Education Back in Educational Apps: How Content and Context Interact to Promote Learning.” In Media Exposure during Infancy and Early Childhood, edited by R. Barr and D.N. Linebarger, 259–82. Springer. doi:10.1561/2200000016.