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

Williamson, Ben

doi:10.1080/02680939.2015.1035758

Cited by 345 publications

(261 citation statements)

References 33 publications

(17 reference statements)

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“…This further involves a predictive element, where trajectories of individual students can be created and calculated for future performance of both the system and the learner. Educational policy has increasingly focused on these types of knowledge sources (Edwards 2014;Williamson 2016): Learning analytics constitutes an emerging form of policy instrumentation in educational governance privileging techniques of prediction and preemption. Such 'big data' practices are distinct from the large-scale datasets used in contemporary Policy Sci (2017) 50:367-382 377 techniques of government (such as international assessments).…”

Section: Substantive Policy Instrumentsmentioning

confidence: 99%

Big data for policymaking: fad or fasttrack?

2017

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The buzz surrounding big data has taken shape in various theoretical and practical forms when it comes to policymaking. The paper combines current research streams with long-standing discussions on government and technology in public policy and public administration, such as e-government and evidence-based policymaking. The goal is to answer the question whether big data is a fleeting trend or has long-lasting effects on policymaking. Three larger themes in the literature are identified: First, the role that institutional capacity has within government to utilize big data analytics; second, government use of big data analytics in the context of digital public services; and finally, the way that big data information enters the policy cycle, focusing on substantive and procedural policy instruments. Examples from the education, crisis management, environmental and healthcare domain highlight the opportunities and challenges for each of these themes. Exploring the various aspects of big data and policymaking shows that big data is here to stay, but that its utilization by government will take time due to institutional barriers and capacity bottlenecks.

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Section: Substantive Policy Instrumentsmentioning

confidence: 99%

Big data for policymaking: fad or fasttrack?

2017

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“…In English and European contexts, Lawn (2013) refers to the «rise of data» in education systems to try to capture the nature of these enumerative technologies of control that enable particular kinds of collection, visualisation and use of data. Williamson (2016) also refers to how numbers and associated forms of computational data provided through schooling systems and associated bodies provide important visual representations of practice, constituting the forms of educational governance processes that arise, including through various forms of profiles, summaries and comparisons of performance.…”

Section: An Infrastructure Of Accountabilitymentioning

confidence: 99%

“…This was an active undertaking in which teachers were asked to consider the nature of their students' results as a whole, and to identify lower performing students whom they believed could improve, and attain a passing grade for the year. This involved scrutiny of individual teachers' summaries of student data (LoA data, PMs, PAT results and NAPLAN) in their «class profile»: This monitoring, through the visualisation of data (Williamson, 2016) via the class profiles, was also evident in the way teachers compared results across different data sets, drawing upon more standardized and teacher judgment measures to bolster arguments about coherence between the different data sets:…”

Section: Monitoring Learning Through Class Profilesmentioning

confidence: 99%

“…Significantly, such data were construed as providing important evidence under broader conditions in which teachers' judgment is increasingly under scrutiny. Even as the Inquiry Cycles were explicitly designed to effect enhanced teacher judgment, and involved much discussion about the specific aspects of students' work that needed to be attended to, and interrogation of curriculum to improve teachers' understandings to improve their teaching, the visualisation of enumerative data (Williamson, 2016) and the subsequent focus upon this data within the discussions, also reflects how such judgement alone was considered insufficient, and needed to be complemented by the gravitas that attends numeric representations of student learning; rival «measures» (Porter, 1995) to these numbers were at a distinct disadvantage during these discussions.…”

Section: Managing Learning: «Shifting» and Engaging Lower Performimentioning

confidence: 99%

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Measuring, monitoring, and managing for productive learning? Australian insights into the enumeration of education

Hardy

2017

RASE

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This article reveals how ongoing teacher learning in schools is heavily influenced by the increased measurement of student learning outcomes. It draws upon a broad range of literature on the practice of education, measuring learning, and its effects on ongoing teachers' learning at the school site. The paper analyses the meeting transcripts of an ongoing, long-term teacher learning initiative in a school in northern Queensland, Australia, and indicates how processes of measurement influenced such learning. Teachers' learning is revealed as heavily influenced by processes of «measuring [student] learning», the subsequent «monitoring» of student learning through students' data profiles, and 'managing' the learning of lower performing students. The article cautions that while these resultant teacher learning practices may be beneficial for students' learning, this is a contested point, and requiring much more careful analysis of the effects of the measurement of education on such practices. KeywordsQuantification of learning; testing, standardized testing, standardized learning, teacher learning, teacher professional development. ResumenEste artículo muestra cómo la formación continua de los maestros en las escuelas está muy influida por el incremento de la medición de los resultados del aprendizaje de los estudiantes. Se basa en un amplio repertorio de literatura sobre la práctica educativa, la medición del aprendizaje y sus efectos sobre la formación continua de los docentes en la escuela. El texto analiza las transcripciones de una serie de reuniones en el marco de una iniciativa de formación continua a largo plazo de docentes en una escuela en el norte de Queensland, Australia, e indica cómo los procesos de medición influyeron en esa formación. Se constata que la formación de los maestros está muy influida por los procesos de «medición del aprendizaje de los estudiantes», el seguimiento posterior del aprendizaje estudiantil través de sus perfiles de datos y la «gestión» del aprendizaje de los estudiantes de bajo rendimiento. El artículo advierte que, aunque estas prácticas resultantes de la formación del profesorado pueden ser beneficiosas para el aprendizaje del estudiantado, esta es una cuestión a debate, y requiere un análisis mucho más cuidadoso de los efectos que la medición de la educación ejerce sobre tales prácticas. Palabras claveCuantificación del aprendizaje; pruebas; pruebas estandarizadas; aprendizaje estandarizado; formación del maestro; desarrollo profesional docente.

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“…Podemos classificar a Big Data como: (I) como marcada pela enormidade, ou seja, constituída de terabytes ou petabytes de dados; (II) por sua alta velocidade, onde os dados são criados quase que em tempo real; (III) por sua diversidade; (IV) por seu exaustivo alcance, que se esforça para capturar não só minucias individuais mais sim populações e ou sistemas inteiros; (V) flexível, mantendo características de extensividade e escalabilidade. Em outras palavras, grandes quantidades de dados não são designados apenas pelo volume (KITCHIN, 2014;WILLIAMSON, 2016;MORAES, 2016a).…”

Section: Uma Erupção De Dadosunclassified

Do #ForaDilma ao #ForaTemer – as duas faces antagônicas de Jano

Moraes¹,

Santos²

2016

RevistaPautaGeral

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ResumoO Twitter é uma rede de mensagens curtas, criada em 2006, que permite aos seus usuários escrever mensagens de 140 caracteres. Estudos recentes apontam que esta ferramenta vem sendo utilizada como um instrumento de mobilização política. Neste ponto, o objetivo deste trabalho é aferir de que forma o Twitter está sendo utilizado como uma ferramenta de mobilização contra os governos Dilma Rousseff (PT) e Michel Temer (PMDB). Utiliza-se a ferramenta Hashtagify para a coleta de dados no período de 12 de maio até 7 de julho de 2016, o que permitiu estudar o padrão de distribuição das hashtags. Dois resultados merecem destaque: (I) as contas de Twitter "anti Dilma" são formadas, sobretudo por meios de comunicação de massa; (II) Somados, os seguidores das contas anti Dilma representam seis vezes mais que os seguidores das contas anti Temer. Palavras-chave: Impeachment. Opinião Pública. Twitter. AbstractThe Twitter is a network of short messages, created in 2006, that lets its users writes messages of 140 characters. Recent studies indicate that this tool has been used as an instrument of political mobilization. At this point, the aim of this work is to assess how Twitter is being used as a tool to mobilize against Governments Dilma Rousseff (PT) and Michel Temer (PMDB). The Hashtagify tool for the collection of data for the period 12 May to 7 July 2016, which allowed study the distribution pattern of hashtags. Two results worth mentioning: (I) the Twitter

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

Cited by 345 publications

References 33 publications

Big data for policymaking: fad or fasttrack?

Big data for policymaking: fad or fasttrack?

Measuring, monitoring, and managing for productive learning? Australian insights into the enumeration of education

Do #ForaDilma ao #ForaTemer – as duas faces antagônicas de Jano

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