Digital education governance:Data visualization, predictive analytics, and ‘real-time’ policy instruments

Educational institutions and governing practices are increasingly augmented with digital database technologies that function as new kinds of policy instruments. This article surveys and maps the landscape of digital policy instrumentation in education and provides two detailed case studies of new digital data systems. The Learning Curve is a massive online data bank, produced by Pearson Education, which deploys highly sophisticated digital interactive data visualizations to construct knowledge about education systems. The second case considers ‘learning analytics’ platforms that enable the tracking and predicting of students’ performances through their digital data traces. These digital policy instruments are evidence of how digital database instruments and infrastructures are now at the centre of efforts to know, govern and manage education both nationally and globally. The governing of education, augmented by techniques of digital education governance, is being distributed and displaced to new digitized ‘centres of calculation’, such as Pearson and Knewton, with the technical expertise to calculate and visualize the data, plus the predictive analytics capacities to anticipate and pre-empt educational futures. As part of a data-driven style of governing, these emerging digital policy instruments prefigure the emergence of ‘real-time’ and ‘future-tense’ techniques of digital education governance

Evoluzione del gene Hdh nei primati

Il gene Hdh si origina senza la tripletta CAG in Dictyostelium discoideum (Dd), circa 800 milioni di anni fa, prima della divergenza dei protostomi-deuterostomi (Zuccato et al., Physiol Rev 2010). La tripletta CAG compare in seguito ed ? esclusiva della branca dei deuterostomi (Tartari et al., Mol Biol Evol 2008). Due ripetizioni CAGs si trovano nel gene Hdh del riccio di mare (Strongylocentrotus purpuratus, Sp), la prima specie ad avere un sistema nervoso primitivo, e due ripetizioni si trovano anche nell\u27anfiosso (Branchiostoma floridae, Bf), che presenta un rudimentale tubo nervoso e un primo tentativo di cefalizzazione. Quattro ripetizioni CAG si riscontrano nei pesci pi? evoluti, negli anfibi e negli uccelli. Il numero di triplette CAG aumenta ulteriormente nei mammiferi e raggiunge la lunghezza massima nella nostra specie (Tartari et al., Mol Biol Evol 2008). In Homo sapiens il gene Hdh si trova sul braccio corto del cromosoma 4 e presenta la sequenza trinucleotidica ripetuta da 11 a 35 volte. Un recente studio su 278 individui normali ha rivelato che chi ha pi? CAG nel range sano ha pi? materia grigia (Muhlau et al., PlosOne 2012), indicazione del fatto che il numero di CAG potrebbe influire sulla normale struttura del cervello. Infatti, un numero di triplette CAG superiore a 35 causa la Corea di Huntington, una malattia neurodegenerativa che insorge tanto pi? precocemente quanto maggiore ? il numero delle ripetizioni CAG. Al fine di verificare se il progressivo incremento del numero di ripetizioni CAG nel gene Hdh durante l\u27evoluzione avesse un possibile ruolo nelle funzioni cognitive emergenti del cervello dei mammiferi, abbiamo analizzato il gene Hdh in diverse specie di primati non umani per analizzare la variabilit? interspecifica e intraspecifica. I risultati sperimentali e le ricostruzioni filogenetiche sostengono che il numero di ripetizioni CAG aumenta nel corso dell\u27evoluzione dei deuterostomi e sembra essere correlato con l\u27aspetto e/o l\u27evoluzione dei sistemi nervosi progressivamente pi? complessi

Digital methodologies of education governance:Pearson plc and the remediation of methods

This article analyses the rise of software systems in education governance, focusing on digital methods in the collection, calculation and circulation of educational data. It examines how software-mediated methods intervene in the ways educational institutions and actors are seen, known and acted upon through an analysis of the methodological complex of Pearson Education’s Learning Curve data-bank and its Center for Digital Data, Analytics and Adaptive Learning. This calls for critical attention to the ‘social life’ of its methods in terms of their historical, technical and methodological provenance; their affordances to generate data for circulation within the institutional circuitry of Pearson and to its wider social networks; their capacity to configure research users’ interpretations; and their generativity to produce the knowledge to influence education policy decisions and pedagogic practices. The purpose of the article is to critically survey the digital methods being mobilized by Pearson to generate educational data, and to examine how its methodological complex acts to produce a new data-based knowledge infrastructure for education. The consequence of this shift to data-based forms of digital education governance by Pearson is a challenge to the legitimacy of the social sciences in the theorization and understanding of learning, and its displacement to the authority of the data sciences

Educating the smart city:Schooling smart citizens through computational urbanism

Coupled with the ‘smart city’, the idea of the ‘smart school’ is emerging in imaginings of the future of education. Various commercial, governmental and civil society organizations now envisage education as a highly coded, software-mediated and data-driven social institution. Such spaces are to be governed through computational processes written in computer code and tracked through big data. In an original analysis of developments from commercial, governmental and civil society sectors, the article examines two interrelated dimensions of an emerging smart schools imaginary: (1) the constant flows of digital data that smart schools depend on and the mobilization of analytics that enable student data to be used to anticipate and shape their behaviours; and (2) the ways that young people are educated to become ‘computational operatives’ who must ‘learn to code’ in order to become ‘smart citizens’ in the governance of the smart city. These developments constitute an emerging educational space fabricated from intersecting standards, technologies, discourses and social actors, all infused with the aspirations of technical experts to govern the city at a distance through both monitoring young people as ‘data objects’ and schooling them as active ‘computational citizens’ with the responsibility to compute the future of the city