A Framework to Support Interdisciplinary Engagement with Learning Analytics

Learning analytics (LA) is an emerging area that has had extensive development in higher education in recent years, focused both on the learning process of students within subjects and on monitoring their trajectories in training programmes. However, most of the developments remain in the pilot phase without reaching institutional adoption. This paper reports the results of a systematic review of the literature carried out with the aim of identifying the factors that influence the adoption of LA, as well as the existing strategies that facilitate such adoption in higher education institutions. The results show that factors for LA adoption are situated in multiple dimensions, including stakeholders at different levels, institutional and pedagogical processes, technical limitations and ethical considerations. This work contributes with a consolidated list of 14 critical factors to be considered to effectively adopt LA tools, addressing planning, strong leadership, collaboration and prioritizing senior management commitment, goal setting, cross‐organizational design, educational process redesign, system integration and legacy system linkage. On the other hand, a variety of frameworks, models and approaches are distinguished in the literature to help the adoption of LA, however, none of them cover all the factors involved in such adoption. Therefore, we provide a compilation of strategies that have been used in the literature to reduce the gaps associated with the different factors described. Practitioner notesWhat is already known about this topic LA is a field of research that has had a lot of interest and a wide variety of tools have been developed. Still, it is criticized that they originate more from data availability than from the needs of students, teachers and decision makers. LA tools are mostly evaluated on their usability aspects and to a lesser extent on their usefulness to impact learning processes. The adoption processes of LA in higher education are oriented to specific aspects such as the relevance of the visualizations in the different contexts of application, but they do not address extensively other important aspects involved in such adoption. What this paper adds This article seeks to synthesize what has been investigated in the literature regarding the factors that affect the adoption of LA by higher education institutions. Describe the 14 critical factors identified from the literature to address adoption of multiple dimensions that include stakeholders at different levels, institutional contexts and ethical considerations. A compilation of strategies that have been used in the literature to reduce the gaps associated with the different factors are described, and the aspects or dimensions that are not addressed are highlighted. Implications for practice and/or policy The synthesis of LA adoption factors and the approach strategies present in the literature allow practitioners to focus their efforts on the key aspects to consider in their LA adoption processes. Future work could shift from a pure design perspective to strengthen an engineering perspective in the adoption practices. From the point of view of the policies associated with the adoption of LA in higher education institutions, it is concluded that it is necessary to approach the process from a comprehensive perspective considering all the dimensions involved.

Section: Results and Findingsmentioning

confidence: 99%

Adoption of learning analytics in higher education institutions: A systematic literature review

Márquez,

Henríquez,

Chevreux

et al. 2023

“…Although there is much to rejoice at the prospect of institutions (HEIs) pursuing datadriven decision-making to improve the experience of students, faculty and staff, this has not been an easy transition because often HEIs lack the capability to analyse and interpret those data (Davenport et al, 2001). Technology integration is now well underway and research is now guiding HEIs to use data analytics to understand student learning (Ward & Wolf-Wendel, 2017) and improve it (Blackmon & Moore, 2020). It is also steering them strategically, to inform individual and institutional decision-making (Duran, 2022); and ethically to prevent misuses, ensuring, for instance, that student privacy is protected (see, Webber & Zheng, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Technology integration is now well underway and research is now guiding HEIs to use data analytics to understand student learning (Ward & Wolf‐Wendel, 2017) and improve it (Blackmon & Moore, 2020). It is also steering them strategically, to inform individual and institutional decision‐making (Duran, 2022); and ethically to prevent misuses, ensuring, for instance, that student privacy is protected ( see , Webber & Zheng, 2020).…”

Section: Introductionmentioning

confidence: 99%

Technology integration in higher education and student privacy beyond learning environments—A comparison of the UK and US perspective

Giuffrida,

Hall

2023

Technology integration in higher education (HE) has brought immense innovation. While research is investigating the benefits of leveraging, through learning analytics, the data created by the greater presence of technology in HE, it is also analysing the privacy implications of vast universes of data now at the fingertips of HE administrators. This paper argues that student privacy challenges linked to technology integration occur not only within but also beyond learning environments, namely at the enterprise level. By analysing the UK and US legal frameworks surrounding how HE institutions respond to parents demanding disclosure of their adult children's personal data in the event of mental health crises, this paper offers an example of real and complex privacy issues, often overlooked by interdisciplinary inquiry, that exist in the ‘interstitial space’ between HE technology and privacy law. The purpose of conducting a comparative analysis was to demonstrate that countries with different privacy regimes are similarly ill‐equipped to address certain student privacy issues at the HE enterprise level, leaving HEIs exposed to potential litigation/regulatory risks. The contribution of this work is to invite greater interdisciplinary awareness of, and inquiry into, student privacy beyond learning environments.

“…Therefore, the purpose of this special issue is to bring the matter of student privacy with technology integration in higher education to the forefront, with the added goal of offering balanced, interdisciplinary perspectives on student privacy-balance in the variety and types of technologies discussed, balance in the conversations about facilitating positive aspects of technology integration while mitigating or alleviating the harmful aspects and balance in the efforts to understand the interstitial areas that can often exist in technology integration as it relates to privacy.There is also an urgency regarding student privacy with technology integration in higher education. Increasingly, researchers are drawing more and more attention to the need for greater student privacy guidelines in learning analytics (Blackmon & Moore, 2020;Ifenthaler & Tracey, 2016), big data (Reidenberg & Schaub, 2018) and technology integration broadly (Blackmon, 2022). The need for more robustly addressing student privacy is further heightened by the growing monetization of student data through colleges' and universities' often unclear partnerships with educational technology companies (Komljenovic, 2022).…”

mentioning

confidence: 99%

“…There is also an urgency regarding student privacy with technology integration in higher education. Increasingly, researchers are drawing more and more attention to the need for greater student privacy guidelines in learning analytics (Blackmon & Moore, 2020; Ifenthaler & Tracey, 2016), big data (Reidenberg & Schaub, 2018) and technology integration broadly (Blackmon, 2022). The need for more robustly addressing student privacy is further heightened by the growing monetization of student data through colleges' and universities' often unclear partnerships with educational technology companies (Komljenovic, 2022).…”

mentioning

confidence: 99%

Balancing student privacy and technology integration in higher education: Engagement, encroachment and interstitial spaces

Blackmon,

Major

2023

Self Cite

The matter of student privacy in higher education technology integration is an incredibly important one. However, the emphasis on student privacy can sometimes get lost in the zeal to integrate new technology, be eclipsed by the assumption that because some students are less stringent regarding privacy that all of them are or should be, get overlooked because of assumptions that other policies already cover student privacy, be relegated to one area of technology integration at the expense of a more holistic focus and everything in between. Therefore, the purpose of this special issue is to bring the matter of student privacy with technology integration in higher education to the forefront, with the added goal of offering balanced, interdisciplinary perspectives on student privacy-balance in the variety and types of technologies discussed, balance in the conversations about facilitating positive aspects of technology integration while mitigating or alleviating the harmful aspects and balance in the efforts to understand the interstitial areas that can often exist in technology integration as it relates to privacy.There is also an urgency regarding student privacy with technology integration in higher education. Increasingly, researchers are drawing more and more attention to the need for greater student privacy guidelines in learning analytics (Blackmon & Moore, 2020;Ifenthaler & Tracey, 2016), big data (Reidenberg & Schaub, 2018) and technology integration broadly (Blackmon, 2022). The need for more robustly addressing student privacy is further heightened by the growing monetization of student data through colleges' and universities' often unclear partnerships with educational technology companies (Komljenovic, 2022). Additionally, policies that are intended to address the matters of student privacy are not always thorough enough to grapple with the complex and rapidly changing nature of the relationships between higher education institutions and educational technology companies (Paris et al., 2021). Even outside of higher education, there are growing concerns about data breaches in areas such as generative artificial intelligence (A.I.) (Kim, 2023), technology that is already being integrated into college and university classrooms and across campuses.Prioritizing the balance of student privacy with technology integration in higher education is of utmost significance. The effort of this issue is not an attempt at consensus, as the authors may hold various, even disparate opinions on how to address student privacy with technology integration. However, the special issue is unified in its emphasis on the critical importance of student privacy in technology integration and offers considerations, data, perspectives and strategies that can be helpful in prioritizing student privacy for technology integration in higher education. Furthermore, the work of student privacy necessarily involves different disciplines-such as education, law and technology-and our special issue is designed with that in mind.