Building the Learning Analytics Curriculum: Should we Teach (a Code of) Ethics?

This brief chapter explores the feasibility of teaching (a code of) ethics against a background which examines our views around data scientists, data analysis, data and, in particular, student data. It touches upon different approaches to ethics and asks whether teaching ethics would make any difference

Stemming the flow: improving retention for distance learning students

Though concern about student attrition and failure is not a new phenomenon, higher education institutions (HEIs) have struggled to significantly reduce the revolving door syndrome. Open distance learning higher education is particularly susceptible to high student attrition. Despite a great deal of research into the student journey and factors impacting on likely success, we are not necessarily closer to understanding and being able to mitigate against student attrition. Learning analytics as emerging discipline and practice promises to help penetrate the fog… This case study describes work undertaken at the Open University in the UK to investigate how a learning analytics approach allows the University to provide timely and appropriate student support in a cost-effective manner. It includes a summary of the establishment of curriculum-based student support teams and a framework which defines more standardised student support informed by both student data and an enhanced knowledge of the curriculum. The primary aim of student support teams is to proactively support students through their study journey and to optimise their chances of reaching their declared study goals. Higher education institutions (HEIs) are making increasing use of learning analytics to support delivery of timely and relevant student support. The Open University in the UK, like other HEIs, knows a great deal about its students before they start to study and is able to track student behaviours once study has begun. Until recently, the university has not taken full advantage of the additional insight offered by such information. This paper describes the framework of support interventions established for all student support teams and describes the learning analytics approach used to support that framework

In the eye of the storm: preliminary evidence on the use of online learning diaries

The surprising lack of pressure and speed in the centre of the vortex of a storm are in stark contrast to the force and destruction often experienced at its periphery. Many spectators watching a developing storm will be caught between fear and a desire to escape. The metaphor of a storm has been applied here to the emotions experienced by many students enrolling in online learning courses. Not only do the requirements of studying online collide with personal and professional commitments, the experience of learning online (often in groups) results in many students feeling displaced, scared or out of control. Learning diaries, especially in an online environment, present students with an opportunity to reach the centre of the vortex, though this may not be as quiet and safe as we may have presumed. This paper reports on students’ reflections in their learning diaries as a prescriptive part of the Professional Certificate in Management offered by the Open University. The research focused on the unstructured learning diary entries of 12 students from one tutor group over an 18 day period of a short compulsory online course. This phenomenographic study used grounded theory as methodology to analyse and describe students’ use of their learning diaries. The research found ample evidence that online learning diaries provide students with a safe space to reflect on the vortex around them. Without a quiet and reflective centre, students may be overwhelmed by the wider forces impacting on them. Students’ postings provided rich descriptions of the vortex of studying online and the function of having a centre to which to withdraw. There is, however, also evidence that posting reflections in learning diaries can itself be a dislocating and uncomfortable experience for some learners, while others question its usefulness. The work provides practical and useful information for managers of online learning experiences, instructional designers and curriculum developer

Ethical considerations in using student data in an era of ‘big data’

Learning with technology enables the collection of data on students at a level unprecedented in face-to-face tuition and paper-based academic administration. Universities see the advantage in tracking students’ engagement and progress, particularly when it comes to putting interventions in place for at-risk students. Our use of these data should be legal, ethical and seen as fair use by students. At no time should it cross the boundaries into the realm of ‘creepy’, a word used by Gartner analyst Frank Buytendijk in several of his presentations at the Gartner ITExpo in Cape Town in September 2014.Universities South Afric

Ethics and Learning Analytics: Charting the (Un)Charted

As the field of learning analytics matures, and discourses surrounding the scope, definition, challenges, and opportunities of learning analytics become more nuanced, there is benefit both in reviewing how far we have come in considering associated ethical issues and in looking ahead. This chapter provides an overview of how our own thinking has developed and maps our journey against broader developments in the field. Against a backdrop of technological advances and increasing concerns around pervasive surveillance and the role and unintended consequences of algorithms, the development of research in learning analytics as an ethical and moral practice provides a rich picture of fears and realities. More importantly, we begin to see ethics and privacy as crucial enablers within learning analytics. The chapter briefly locates ethics in learning analytics in the broader context of the forces shaping higher education and the roles of data and evidence before tracking our personal research journey, highlighting current work in the field, and concluding by mapping future issues for consideration

The Complexities of Developing a Personal Code of Ethics for Learning Analytics Practitioners: Implications for Institutions and the Field

In this paper we explore the potential role, value and utility of a personal code of ethics (COE) for learning analytics practitioners, and in particular we consider whether such a COE might usefully mediate individual actions and choices in relation to a more abstract institutional COE. While several institutional COEs now exist, little attention has been paid to detailing the ethical responsibilities of individual practitioners. To investigate the problems associated with developing and implementing a personal COE, we drafted an LA Practitioner COE based on other professional codes, and invited feedback from a range of learning analytics stakeholders and practitioners: ethicists, students, researchers and technology executives. Three main themes emerged from their reflections: 1. A need to balance real world demands with abstract principles, 2. The limits to individual accountability within the learning analytics space, and 3. The continuing value of debate around an aspirational code of ethics within the field of learning analytics

Student privacy self-management: implications for learning analytics

Optimizing the harvesting and analysis of student data promises to clear the fog surrounding the key drivers of student success and retention, and provide potential for improved student success. At the same time, concerns are increasingly voiced around the extent to which individuals are routinely and progressively tracked as they engage online. The Internet, the very thing that promised to open up possibilities and to break down communication barriers, now threatens to narrow it again through the panopticon of mass surveillance. Within higher education, our assumptions and understanding of issues surrounding student attitudes to privacy are influenced both by the apparent ease with which the public appear to share the detail of their lives and our paternalistic institutional cultures. As such, it can be easy to allow our enthusiasm for the possibilities offered by learning analytics to outweigh consideration of issues of privacy. This paper explores issues around consent and the seemingly simple choice to allow students to opt-in or opt-out of having their data tracked. We consider how 3 providers of massive open online courses (MOOCs) inform users of how their data is used, and discuss how higher education institutions can work toward an approach which engages and more fully informs students of the implications of learning analytics on their personal data

An elephant in the learning analytics room: the obligation to act

As higher education increasingly moves to online and digital learning spaces, we have access not only to greater volumes of student data, but also to increasingly fine-grained and nuanced data. A significant body of research and existing practice are used to convince key stakeholders within higher education of the potential of the collection, analysis and use of student data to positively impact on student experiences in these environments. Much of the recent focus in learning analytics is around predictive modeling and uses of artificial intelligence to both identify learners at risk, and to personalize interventions to increase the chance of success. In this paper we explore the moral and legal basis for the obligation to act on our analyses of student data. The obligation to act entails not only the protection of student privacy and the ethical collection, analysis and use of student data, but also, the effective allocation of resources to ensure appropriate and effective interventions to increase effective teaching and learning. The obligation to act is, however tempered by a number of factors, including inter and intra-departmental operational fragmentation and the constraints imposed by changing funding regimes. Increasingly higher education institutions allocate resources in areas that promise the greatest return. Choosing (not) to respond to the needs of specific student populations then raises questions regarding the scope and nature of the moral and legal obligation to act. There is also evidence that students who are at risk of failing often do not respond to institutional interventions to assist them. In this paper we build and expand on recent research by, for example, the LACE and EP4LA workshops to conceptually map the obligation to act which flows from both higher education's mandate to ensure effective and appropriate teaching and learning and its fiduciary duty to provide an ethical and enabling environment for students to achieve success. We examine how the collection and analysis of student data links to both the availability of resources and the will to act and also to the obligation to act. Further, we examine how that obligation unfolds in two open distance education providers from the perspective of a key set of stakeholders - those in immediate contact with students and their learning journeys - the tutors or adjunct faculty

The use and application of learning theory in learning analytics: a scoping review

Since its inception in 2011, Learning Analytics has matured and expanded in terms of reach (e.g., primary and K-12 education) and in having access to a greater variety, volume and velocity of data (e.g. collecting and analyzing multimodal data). Its roots in multiple disciplines yield a range and richness of theoretical influences resulting in an inherent theoretical pluralism. Such multi-and interdisciplinary origins and influences raise questions around which learning theories inform learning analytics research, and the implications for the field should a particular theory dominate. In establishing the theoretical influences in learning analytics, this scoping review focused on the Learning Analytics and Knowledge Conference (LAK) Proceedings (2011–2020) and the Journal of Learning Analytics (JLA) (2014–2020) as data sources. While learning analytics research is published across a range of scholarly journals, at the time of this study, a significant part of research into learning analytics had been published under the auspices of the Society of Learning Analytics (SoLAR), in the proceedings of the annual LAK conference and the field’s official journal, and as such, provides particular insight into its theoretical underpinnings. The analysis found evidence of a range of theoretical influences. While some learning theories have waned since 2011, others, such as Self-Regulated Learning (SRL), are in the ascendency. We discuss the implications of the use of learning theory in learning analytics research and conclude that this theoretical pluralism is something to be treasured and protected.publishedVersio