The connected university: connectedness learning across a lifetime

Kitto, Kirsty; Cutrupi, Julieanne; Philips, Mark R.; Gardiner, Gabrielle; Ghodrati, Moein; Shum, Simon Buckingham

doi:10.4337/9781788972611.00023

Cited by 2 publications

(3 citation statements)

References 13 publications

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“…The focus of virtue ethics on the practical reason of virtuous actors, in contrast to consequences or rules, provides a useful additional conceptual lens for LA, which may be shared and developed through practical edge cases. As people increasingly enter into ever more porous relationships with the education sector (Kitto, O'Hara, et al , ) a virtues based approach helps us to shift focus towards practical action and reason in navigating decisions around how to support student learning.…”

Section: Discussionmentioning

confidence: 99%

“…The need to link data and profile people is often challenged by privacy advocates (Zuboff, ), but this argument fails to appreciate the value for users that sometimes comes with these approaches. For example, to evolve adaptive learning from its current largely product ‐based methodology to a practice based one (Feldstein & Hill, ) we would need to join datasets from multiple places and spaces (Kitto, O'Hara, et al , ). Indeed, joining such datasets opens up a number of possibilities for developing models of lifelong personalised learning that put the data subject in control of their learning data (Kay, ; Kay & Kummerfield, in press).…”

Section: Three Case Studies In Applying Aidamentioning

confidence: 99%

“…Artificial intelligence and data analytics (AIDA) is increasingly entering education: Standardised tests, such as the Programme for International Student Assessment: (PISA—http://www.oecd.org/pisa) evaluate student performance around the world (Sellar, Thompson & Rutkowski, ); academics are appointed and promoted based upon satisfaction scores sourced from students (Kitto, Williams, & Alderman, ); machine learning predicts which students might be at risk of failure based upon various datasets (Gašević, Dawson, Rogers, & Gasevic, ); text analysis can give students real time feedback on their writing (Gibson et al , ; Shibani, Knight, Buckingham Shum, & Ryan, ); intelligent tutoring and adaptive learning systems are leveraged to personalise content delivery (Feldstein & Hill, ); and companies and consortia such as Google, Burning Glass, Salesforce, IMS Global and ADL are marketing data, standards and suites of new tools to institutions (Kitto, O'Hara, et al , ).…”

Section: Introductionmentioning

confidence: 99%

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Practical ethics for building learning analytics

Kitto¹,

Knight²

2019

Brit J Educational Tech

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Artificial intelligence and data analysis (AIDA) are increasingly entering the field of education. Within this context, the subfield of learning analytics (LA) has, since its inception, had a strong emphasis upon ethics, with numerous checklists and frameworks proposed to ensure that student privacy is respected and potential harms avoided. Here, we draw attention to some of the assumptions that underlie previous work in ethics for LA, which we frame as three tensions. These assumptions have the potential of leading to both the overcautious underuse of AIDA as administrators seek to avoid risk, or the unbridled misuse of AIDA as practitioners fail to adhere to frameworks that provide them with little guidance upon the problems that they face in building LA for institutional adoption. We use three edge cases to draw attention to these tensions, highlighting places where existing ethical frameworks fail to inform those building LA solutions. We propose a pilot open database that lists edge cases faced by LA system builders as a method for guiding ethicists working in the field towards places where support is needed to inform their practice. This would provide a middle space where technical builders of systems could more deeply interface with those concerned with policy, law and ethics and so work towards building LA that encourages human flourishing across a lifetime of learning. What is already known about this topic Applied ethics has a number of well‐established theoretical groundings that we can use to frame the actions of ethical agents, including, deontology, consequentialism and virtue ethics. Learning analytics has developed a number of checklists, frameworks and evaluation methodologies for supporting trusted and ethical development, but these are often not adhered to by practitioners. Laws like the General Data Protection Regulation (GDPR) apply to fields like education, but the complexity of this field can make them difficult to apply. What this paper adds Evidence of tensions and gaps in existing ethical frameworks and checklists to support the ethical development and implementation of learning analytics. A set of three edge cases that demonstrate places where existing work on the ethics of AI in education has failed to provide guidance. A “practical ethics” conceptualisation that draws on virtue ethics to support practitioners in building learning analytics systems. Implications for practice and/or policy Those using AIDA in education should collect and share example edge cases to support development of practical ethics in the field. A multiplicity of ethical approaches are likely to be useful in understanding how to develop and implement learning analytics ethically in practical contexts.

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Section: Discussionmentioning

confidence: 99%

Section: Three Case Studies In Applying Aidamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Practical ethics for building learning analytics

Kitto¹,

Knight²

2019

Brit J Educational Tech

Self Cite

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Institutional enabling strategies

Bridgstock¹,

Tippett²

2019

Higher Education and the Future of Graduate Employability

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University structures and processes often militate against the promotion of connectedness learning. From the outside, they are often seen as walled gardens, restricting the flow of people and information between themselves and the outside world, while on the inside, the often-used metaphor is a series of siloes, where staff, programs, and organisational areas in different academic and functional areas all work in parallel to each other with relatively little interaction. If we are to support students to develop connections and use these to work and live productively and meaningfully, then it follows that universities themselves should also be well connected. This chapter explores the range of approaches that universities can use to overcome the institutional barriers to connectedness. Seven enabling institutional strategies are outlined which can be used to create, grow and maintain inter-and intrainstitutional connectedness. The chapter then introduces three empirical studies which explore how these enabling strategies are being integrated within and across different higher education institutions, and the impact they have had toward enhancing graduates' connectedness capabilities.

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The connected university: connectedness learning across a lifetime

Cited by 2 publications

References 13 publications

Practical ethics for building learning analytics

Practical ethics for building learning analytics

Institutional enabling strategies

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