scholarly journals Commentary on Neil Selwyn’s LAK18 Keynote Address

2019 ◽  
Vol 6 (3) ◽  
Author(s):  
Paul Prinsloo
Keyword(s):  
Learning Analytics ◽  
Data Science ◽  
Keynote Address ◽  
Research Focus ◽  
Critical Data ◽  
Royal Household

In his keynote, Neil Selwyn not only acknowledged his role as ‘outsider’ to the field of learning analytics, but also intentionally assumed the role of “idiot”. In my commentary I assume that Selwyn’s embrace of being an idiot was more than just self-deprecating humour or a disclaimer aimed to prepare the audience for his provocations. In a Medieval carnival, the clown, fool or community idiot was crowned king, and for the duration of the carnival, could make fun of the royal household, blaspheme and provoke, all licenced by his or her role at that moment in time. Selwyn acknowledged that his own position was and continue to be informed by Critical Data Studies (CDS), an emerging research focus and discourse aimed at troubling much of current accepted and unquestioned assumptions and practices in the broader context of data science. I reflect and comment on Selwyn’s keynote by firstly mapping some of the key tenets of CDS, before addressing some aspects of the keynote and two aspect of his “learning analytics wish-list” namely “giving students control” and “seeing ethics in terms of power, not in terms of protection."

scholarly journals Critical Data Studies, Abstraction & Learning Analytics

2019 ◽  
Vol 6 (3) ◽  
Author(s):  
Simon Buckingham Shum
Keyword(s):  
Social Science ◽  
Learning Analytics ◽  
Teaching And Learning ◽  
Special Section ◽  
Keynote Address ◽  
Critical Data

This editorial introduces a special section of the Journal of Learning Analytics, for which Neil Selwyn’s keynote address to LAK ’18 has been written up as an article, “What’s the problem with learning analytics?” His claims and arguments are engaged in commentaries from Alfred Essa, Rebecca Ferguson, Paul Prinsloo, and Carolyn Rosé, who provide diverse perspectives on Selwyn’s proposals and arguments, from applause to refutation. Reflecting on the debate, I note some of the tensions to be resolved for learning analytics and social science critiques to engage productively, observing that central to the debate is how we understand the role of abstraction in the analysis of data about teaching and learning, and hence the opportunities and risks this entails.  

scholarly journals Critical Care, Critical Data

2019 ◽  
Vol 10 ◽  
pp. 117959721985656 ◽  
Author(s):  
Christopher V Cosgriff ◽  
Leo Anthony Celi ◽  
David J Stone
Keyword(s):  
Artificial Intelligence ◽  
Critical Care ◽  
Clinical Data ◽  
Continuous Monitoring ◽  
Data Science ◽  
Clinical Decision ◽  
Critical Care Medicine ◽  
Data Driven ◽  
Critical Data

As big data, machine learning, and artificial intelligence continue to penetrate into and transform many facets of our lives, we are witnessing the emergence of these powerful technologies within health care. The use and growth of these technologies has been contingent on the availability of reliable and usable data, a particularly robust resource in critical care medicine where continuous monitoring forms a key component of the infrastructure of care. The response to this opportunity has included the development of open databases for research and other purposes; the development of a collaborative form of clinical data science intended to fully leverage these data resources, and the creation of data-driven applications for purposes such as clinical decision support. Most recently, data levels have reached the thresholds required for the development of robust artificial intelligence features for clinical purposes. The systematic capture and analysis of clinical data in both individuals and populations allows us to begin to move toward precision medicine in the intensive care unit (ICU). In this perspective review, we examine the fundamental role of data as we present the current progress that has been made toward an artificial intelligence (AI)-supported, data-driven precision critical care medicine.

The role of machine learning analytics and metrics in retailing research

2020 ◽  
Author(s):  
Xin (Shane) Wang ◽  
Jun Hyun (Joseph) Ryoo ◽  
Neil Bendle ◽  
Praveen K. Kopalle
Keyword(s):  
Machine Learning ◽  
Learning Analytics

The central role of data repositories and data models in Data Science and Advanced Analytics

2021 ◽  
Author(s):  
Ladjel Bellatreche ◽  
Carlos Ordonez ◽  
Dominique Méry ◽  
Matteo Golfarelli ◽  
El Hassan Abdelwahed
Keyword(s):  
Data Science ◽  
Data Models ◽  
Data Repositories ◽  
Advanced Analytics

TIME SERIES MODELLING OF EPIDEMICS: LEADING INDICATORS, CONTROL GROUPS AND POLICY ASSESSMENT

2021 ◽  
Vol 257 ◽  
pp. 83-100
Author(s):  
Andrew Harvey
Keyword(s):  
Time Series ◽  
Data Science ◽  
Leading Indicators ◽  
Control Groups ◽  
Balanced Growth ◽  
Time Series Modelling ◽  
Key Variables ◽  
The Uk ◽  
The Relationship

This article shows how new time series models can be used to track the progress of an epidemic, forecast key variables and evaluate the effects of policies. The univariate framework of Harvey and Kattuman (2020, Harvard Data Science Review, Special Issue 1—COVID-19, https://hdsr.mitpress.mit.edu/pub/ozgjx0yn) is extended to model the relationship between two or more series and the role of common trends is discussed. Data on daily deaths from COVID-19 in Italy and the UK provides an example of leading indicators when there is a balanced growth. When growth is not balanced, the model can be extended by including a non-stationary component in one of the series. The viability of this model is investigated by examining the relationship between new cases and deaths in the Florida second wave of summer 2020. The balanced growth framework is then used as the basis for policy evaluation by showing how some variables can serve as control groups for a target variable. This approach is used to investigate the consequences of Sweden’s soft lockdown coronavirus policy in the spring of 2020.

scholarly journals A DIDÁTICA NA ATUALIDADE: UMA PESQUISA SOBRE OS ASSUNTOS ABORDADOS NO GT04 DA ANPED

2018 ◽  
Vol 15 (Especial 2) ◽  
pp. 27-32
Author(s):  
Daniele dos Santos Martins Vieira ◽  
Renata Portela Rinaldi
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Data Collection ◽  
Working Group ◽  
The Political ◽  
Pedagogical Practice ◽  
Research Focus ◽  
Research In Education ◽  
Object Of Study

The didactics is configured as a broad field of investigation and has as object of study the teaching process. It encompasses several actions on pedagogical practice, but also involves the conception of education that the teacher possesses, since to human and integral formation it is necessary to consider the political, social, cultural and economic scenario in which the subjects are inserted. In the light of the above, the objective of this article is to analyze from the productions in the field, specifically the Working Group on Didactics (GT04) of the National Association of Postgraduate and Research in Education (ANPED), which reveal about the role of didactics in teacher training. It is based on the qualitative research, of the bibliographic type; the data collection took place in the ANPED database between 2007-2017 and data analysis was performed from a descriptiveanalytical perspective. The results reveal mainly the research focus in the researched area.

scholarly journals Keynote Address for Western Journal Day

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Jerry P. White ◽  
Susan Wingert
Keyword(s):  
Open Access ◽  
Keynote Address ◽  
Western Journal ◽  
Indigenous Policy ◽  
Open Access Journals

Today, I want to look at three interconnected things. The first is the importance of open access and what it really means. The second is the role of Scholarship@Western in supporting our open access journals from the perspective of the International Indigenous Policy Journal (IIPJ). Lastly, we want to talk about some of the actions that we have taken to enhance our journal’s readership and rankings.

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