Critical Data Studies, Abstraction &amp; Learning Analytics

Shum, Simon Buckingham

doi:10.18608/jla.2019.63.2

Cited by 16 publications

(12 citation statements)

References 22 publications

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“…Two other Dimensions (Second and Third) embraced relatively critical perspectives with respect to the existing forms of data usage, which can be connected with emerging literature on the ethical and power issues relating to the form in which data are collected and manipulated in the techno-structure [29][30][31][32]. The fourth dimension, which could be linked to the research strand just mentioned, was placed in a separate area due to its specific nature relating data usage in education [56,57]. In this sense, some authors advocate for smart data usage in higher education, taking the form of learning analytics and its impact on students' self-regulation, drop-out prevention, personalization of learning, and informing learning design [41,54].…”

Section: Discussionmentioning

confidence: 99%

“…This topic has followed a similar pattern of concern, with the attention put on academics' ability to handle students' digital data. Nevertheless, while the issue of data literacy to deal with learning analytics has been raised by some authors, [41,54] a comprehensive training over learning analytics and their implications for teachers and learners' data ethics seem to be far from the mainstream [55][56][57].…”

Section: Is Data Literacy a Catalyst Of Social Justice?mentioning

confidence: 99%

“…The latter refers to conceptual categories that emerged along the inductive process of classification and transverse elements, particularly regarding the educational approach to data literacy. [58]; the Special Issue "Data & Agency" [34]; "Algorithmic affordances for productive resistance" [56] and the project "Big Data from the South" https://stefaniamilan.net/content/big-data-south Where: Global…”

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confidence: 99%

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Is Data Literacy a Catalyst of Social Justice? A Response from Nine Data Literacy Initiatives in Higher Education

Raffaghelli

2020

Education Sciences

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Is education and more specifically, data literacy initiatives in Higher Education, an appropriate instrument to promote social justice in a context of datafication? Education is (and has been) at the center of the debate over the achievement of social justice as a desirable quality of the human society. However, which type of educational interventions should be promoted to deal with a complex, multi-layered, emergent problem, such is the case of datafication in society? Since the problem is heavily entrenched with a shifting socio-economic model (the so called “surveillance capitalism”) and the technological infrastructures connected to it, educational approaches could be diversified and even contradictory in their purpose of heralding the skills to live in a datafied society. This paper explores nine initiatives in Higher Education aimed at developing the literacies to deal with data in society. Their efforts are concentrated in promoting freedom of choice, awareness, and agency. Though their original intention is not promoting social justice, the analysis is carried out on the theoretical basis provided by Martha Nussbaum on social justice. The initiatives span educational activities with open data as open educational resources, to more formal data literacy activities such as educational engagement with students’ data and students’ personal and educational data. There emerges a still fragmented panorama in responding to the need of promoting social justice in a context of datafication. Given this fragmentation, the article provides a conceptual scheme to address further pedagogical reflection and practice with the aim of supporting social justice against datafication.

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Section: Discussionmentioning

confidence: 99%

Section: Is Data Literacy a Catalyst Of Social Justice?mentioning

confidence: 99%

mentioning

confidence: 99%

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Is Data Literacy a Catalyst of Social Justice? A Response from Nine Data Literacy Initiatives in Higher Education

Raffaghelli

2020

Education Sciences

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“…The special section contains a robust dialogue between Selwyn and four experts in the field of learning analytics (Carolyn Rosé, Al Essa, Paul Prinsloo, and Rebecca Ferguson) about the "dark side" of learning analytics. The key points and tensions raised are summarized in the guest editorial for the section (Buckingham Shum, 2019), which also points to the nature of our field as a design science, and the concomitant responsibility to "think in terms of the ripples that [our] inventions create at multiple levels of the sociotechnical infrastructure that constitutes 'education'" (p. 8).…”

Section: Equity Justice and Inclusion In Educationmentioning

confidence: 99%

Learning Analytics Impact: Critical Conversations on Relevance and Social Responsibility

Ochôa¹,

Knight²,

Wise³

2020

JLA

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Our 2019 editorial opened a dialogue about what is needed to foster an impactful field of learning analytics (Knight, Wise, & Ochoa, 2019). As we head toward the close of a tumultuous year that has raised profound questions about the structure and processes of formal education and its role in society, this conversation is more relevant than ever. That editorial, and a recent online community event, focused on one component of the impact: standards for scientific rigour and the criteria by which knowledge claims in an interdisciplinary, multi-methodology field should be judged. These initial conversations revealed important commonalities across statistical, computational, and qualitative approaches in terms of a need for greater explanation and justification of choices in using appropriate data, models, or other methodological approaches, as well as the many micro-decisions made in applying specific methodologies to specific studies. The conversations also emphasize the need to perform different checks (for overfitting, for bias, for replicability, for the contextual bounds of applicability, for disconfirming cases) and the importance of learning analytics research being relevant by situating itself within a set of educational values, making tighter connections to theory, and considering its practical mobilization to affect learning. These ideas will serve as the starting point for a series of detailed follow-up conversations across the community, with the goal of generating updated standards and guidance for JLA articles.

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“…-Selwyn, 2020, p. 4 In 2019, this journal published a dialogue and scholarly reflection about a necessary and unresolved question: "What's the problem with learning analytics?" (Buckingham Shum, 2019). The JLA dialogue featured learning analytics (LA) scholars who commented on Selwyn's (2019) keynote address to the 2018 International Conference on Learning Analytics & Knowledge in which he asked a series of critical questions, including these: "What are the 'ideologies' and 'politics' of learning analytics technologies?…”

Section: Introductionmentioning

confidence: 99%

Learning Analytics and the Abolitionist Imagination

Swauger¹,

Kalir²

2023

Learning Analytics

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This article advances an abolitionist reframing of learning analytics (LA) that explores the benefits of productive disorientation, considers potential harms and care made possible by LA, and suggests the abolitionist imagination as an important educational practice. By applying abolitionist concepts to LA, we propose it may be feasible to open new critiques and social futures that build toward equity-oriented LA design and implementation. We introduce speculative methods to advance three vignettes imagining how LA could be weaponized against students or transformed into a justice-directed learning tool. Our speculative methods aim to destabilize where power in LA has been routinely located and contested, thereby opening new lines of inquiry about more equitable educational prospects. Our concluding discussion addresses how speculative design and fiction are complementary methods to the abolitionist imagination and can be pragmatic tools to help build a world with fairer, more equitable, and responsible LA technologies.

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Critical Data Studies, Abstraction & Learning Analytics

Cited by 16 publications

References 22 publications

Is Data Literacy a Catalyst of Social Justice? A Response from Nine Data Literacy Initiatives in Higher Education

Is Data Literacy a Catalyst of Social Justice? A Response from Nine Data Literacy Initiatives in Higher Education

Learning Analytics Impact: Critical Conversations on Relevance and Social Responsibility

Learning Analytics and the Abolitionist Imagination

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