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Blended learning is the new buzzword in higher education. International trends in open and distance learning proclaim that the use of blended learning is essential for any distance education institution that wishes to remain relevant in an increasingly contested market. Blended learning refers to the use of a variety of technologies, pedagogies, contexts and delivery modes (such as online learning) to create a strategic mix that will increase student success. Online learning environments form a crucial part of any blended learning strategy. In the South African context, access to such online environments is a controversial issue. This article reports on a study which attempted to determine how many of the students registered for Accounting at second year level at the University of South Africa (UNISA) would benefit from a blended learning approach.

The sustainability of higher education institutions is affected various things, particularly by student satisfaction and the financial stability of the institution. An analysis of student attrition and retention plays a vital role in assessing the sustainability of a higher education institution. Using suitable analysis techniques to do success profiling of prospective and current students is crucial for students and institutions alike. Success/risk estimation is essential for any higher education institution (HEI), because determining such factors can assist higher education institutions in fulfilling their obligation to provide support, guidance and interventions for their prospective and existing students. Strategic decisions in this regard, by both students and institutions, should be based on valid and reliable profiles. The validation of established profiles increases the accuracy of existing profiles and increases the efficiency of institutional strategic planning. This article reports on the validation of a success profile for first year Accounting students established by the authors of this article in an earlier study in an open and distance learning (ODL) environment at the University of South Africa.

The purpose of this study is to address the generalised lack of guidance on ethical treatment of corporate (e.g. non-research) data in higher education institutions, by focusing on the case of the University of Queensland (Brisbane, Australia). No actionable framework is currently available in the country to govern the ethical usage of corporate data. As such, this research takes a stakeholder-centred approach to data ethics; the lived experience of the stakeholders involved coupled with a theory-based ethical framework allowed the authors build to build a framework to guide ethical data practice.

Adopting a revised canonical action research approach focused on intervention on the context, the authors conducted a review of the literature on ethical usage of data in higher education institutions; administered one survey to university students (n = 168); and facilitated three workshops with professional staff (two) and students (one).

Collected data highlighted how, among other themes, the role and ethical importance of transparency was the dominant claim among all stakeholder groups. Findings helped the authors develop an Enhanced Enterprise Data Ethics Framework (EEDEF) emphasising transparency and stakeholder-centricity.

Legislation is the driver to regulate the use of corporate data in higher education; however, this can be problematic because legislation is retrospective, lacks normativity and offers scarce directions for cases that do not exactly follow within the legislative mandate. In light of these regulatory limitations, the authors’ EEDEF offers operators guidance on how to ethically manage corporate data in the higher education environment.

This study fills gaps in praxis and theory; that is the lack of literature and guiding ethical frameworks to inform data practice in higher education. This research fosters a more ethical data management by virtue of genuine and authentic engagement with stakeholders and emphasises the importance of strategic decision-making and maturity of data culture in the higher education sector.

That life is inundated with constant push–pull between contradictory demands is indisputable. Different traditions and worldviews inform individuals’ approaches to dealing with the ensuing paradoxes. However, the literature has focused on Western and Eastern philosophies and traditions, while disregarding others such as the Afrocentric. In this chapter, the authors explore Ubuntu, an Afrocentric tradition, as an alternative philosophical underpinning that can inform the nature of paradoxes. Doing so enriches the understanding, problematizing and managing of paradoxes. Central to Ubuntu is otherness: the emphasis on the need of the other that implies focusing on the other; in doing so, the polarities of diverse needs are accommodated, striving for an ultimate goal of harmony. Moreover, the authors elaborate on the hybrid space where collapsing the East–West and the West and non-west dualism allow engagement with a multiplicity of worldviews. In so doing, the authors expand paradox theorizing beyond the orthodoxy of East and West antinomies and challenge the basic assumption in paradox management by asking the question: what if we start from others’ demands?

The purpose of this paper is to take a student-centred perspective to understanding the range of ways that students respond to receiving information about their learning behaviours presented on a dashboard. It identifies four principles to inform the design of dashboards which support learner agency and empowerment, features which Prinsloo and Slade (2016) suggest are central to ethical adoption of learning analytics.

The study involved semi-structured interviews with 24 final-year undergraduates to explore the students’ response to receiving dashboards that showed the students’ achievement and other learning behaviours.

The paper identifies four principles that should be used when designing and adopting learner dashboards to support student agency and empowerment.

The study was based on a small sample of undergraduate students from the final year from one academic school. The data are based on students’ self-reporting.

The paper suggests that these four principles are guiding tenets for the design and implementation of learner dashboards in higher education. The four principles are: designs that are customisable by students; foregrounds students sense making; enables students to identify actionable insights; and dashboards are embedded into educational processes.

The paper’s originality is that it illuminates student-centred principles of learner dashboard design and adoption.

The purpose of this paper is to explore and establish the contours of trust in learning analytics and to establish steps that institutions might take to address the “trust deficit” in learning analytics.

“Trust” has always been part and parcel of learning analytics research and practice, but concerns around privacy, bias, the increasing reach of learning analytics, the “black box” of artificial intelligence and the commercialization of teaching and learning suggest that we should not take stakeholder trust for granted. While there have been attempts to explore and map students’ and staff perceptions of trust, there is no agreement on the contours of trust. Thirty-one experts in learning analytics research participated in a qualitative Delphi study.

This study achieved agreement on a working definition of trust in learning analytics, and on factors that impact on trusting data, trusting institutional understandings of student success and the design and implementation of learning analytics. In addition, it identifies those factors that might increase levels of trust in learning analytics for students, faculty and broader.

The study is based on expert opinions as such there is a limitation of how much it is of a true consensus.

Trust cannot be assumed is taken for granted. This study is original because it establishes a number of concerns around the trustworthiness of learning analytics in respect of how data and student learning journeys are understood, and how institutions can address the “trust deficit” in learning analytics.

The purpose of this paper is to reveal how instructors discuss student data and information privacy in their syllabi.

The authors collected a mixture of publicly accessible and privately disclosed syllabi from 8,302 library and information science (LIS) courses to extract privacy language. Using privacy concepts from the literature and emergent themes, the authors analyzed the corpus.

Most syllabi did not mention privacy (98 percent). Privacy tended to be mentioned in the context of digital tools, course communication, policies and assignments.

The transferability of the findings is limited because they address only one field and professional discipline, LIS, and address syllabi for only online and hybrid courses.

The findings suggest a need for professional development for instructors related to student data privacy. The discussion provides recommendations for creating educational experiences that support syllabi development and constructive norming opportunities.

Instructors may be making assumptions about the degree of privacy literacy among their students or not value student privacy. Each raises significant concerns if privacy is instrumental to intellectual freedom and processes critical to the educational experience.

In an age of educational data mining and analytics, this is one of the first studies to consider if and how instructors are addressing student data privacy in their courses, and the study initiates an important conversation for reflecting on privacy values and practices.

The concept of student behaviour provides a tool for describing and understanding the underlying mechanisms between academic success as a dependent variable and individual determinants of students and the institutional context of study as independent variables. Defined as the micro-level characteristics that encompass students' actual behaviour and transitions within higher education, student behaviour influences the outcomes of academic performance, learning outcomes, the duration of studies, completion rates and future career paths. Student behaviour therefore serves as an intermediary construct between inputs and student outcomes. This chapter provides a comprehensive heuristic framework of student behaviour, drawing on insights from a range of disciplinary theoretical perspectives, including education, psychology, sociology, economics and political science. The conceptual model outlines the central role of student behaviour within the student life cycle and its implications for higher education research. In doing so, the chapter offers a conceptual panorama that encompasses both the factors that explain student behaviour and the phenomena that student behaviour itself influences, including its relationship to the concept of student engagement. The framework is not limited to conceptual delineation but invites further theoretical development.

Almost every detail of our lives – where we go, what we do, and with whom – is captured as digital data. Technological advancements in cloud computing, artificial intelligence, and data analytics offer the education sector new ways not only to improve policy and processes but also to personalize learning and teaching practice. However, these changes raise fundamental questions around who owns the data, how it might be used, and the consequences of use. The application of Big Data in education can be directed toward a wide range of stakeholders, such as educators, students, policy-makers, institutions, or researchers. It may also have different objectives, such as monitoring, student support, prediction, assessment, feedback, and personalization. This chapter presents the nuances and recent research trends spurred by technological advancements that have influenced the education sector and highlights the need to look beyond the technical boundaries using a socio-semiotic lens. With the explosion of available information and digital technologies pervading cultural, social, political as well as economic spaces, being a lifelong learner is pivotal for success. However, technology on its own is not sufficient to drive this change. For technology to be successful, it should complement individual learning cultures and education systems. This chapter is broadly divided into two main sections. In the first section, we contemplate a vision for the future, which is deemed possible based on ongoing digital and computing advancements. The second section elaborates the technological, pedagogical, cultural, and political requirements to attain that vision.

It has been demonstrated that AI-powered, data-driven tools’ usage is not universal, but deeply linked to socio-cultural contexts. The purpose of this paper is to display the need of adopting situated lenses, relating to specific personal and professional learning about data protection and privacy.

The authors introduce the results of a case study based on a large educational intervention at a fully online university. The views of the participants from degrees representing different knowledge areas and contexts of technology adoption (work, education and leisure) were explored after engaging in the analysis of the terms and conditions of use about privacy and data usage. After consultation, 27 course instructors (CIs) integrated the activity and worked with 823 students (702 of whom were complete and correct for analytical purposes).

The results of this study indicated that the intervention increased privacy-conscious online behaviour among most participants. Results were more contradictory when looking at the tools’ daily usage, with overall positive considerations around the tools being mostly needed or “indispensable”.

Though appliable only to the authors’ case study and not generalisable, the authors’ results show both the complexity of privacy views and the presence of forms of renunciation in the trade-off between data protection and the need of using a specific software into a personal and professional context.

This study provides an example of teaching and learning activities that supports the development of data literacy, with a focus on data privacy. Therefore, beyond the research findings, any educator can build over the authors’ proposal to produce materials and interventions aimed at developing awareness on data privacy issues.

Developing awareness, understanding and skills relating to data privacy is crucial to live in a society where digital technologies are used in any area of our personal and professional life. Well-informed citizens will be able to obscure, resist or claim for their rights whenever a violation of their privacy takes place. Also, they will be able to support (through adoption) better quality apps and platforms, instead of passively accepting what is evident or easy to use.

The authors specifically spot how students and educators, as part of a specific learning and cultural ecosystem, need tailored opportunities to keep on reflecting on their degrees of freedom and their possibilities to act regarding evolving data systems and their alternatives.