Unintended Consequences of E-Learning: Reflections on the Digital Transformation of Learning in Higher Education

The use of digital technologies in Higher Education has grown dramatically dur-ing the COVID-19 pandemic with many courses moved to online teaching, a trend which is likely to continue post-pandemic. However, the rise of such E-Learning is likely to have a number of unintended consequences for students, teachers, higher education institutions, employers and society more generally (Webb et al. 2021) . These have important implications for regional and local labour markets, skills development and observatories. E-Learning can generate innovative approaches to learning and can enhance ef-ficiently and convenience, particularly for those wishing to work or study re-motely or ‘at a distance’. Some students favour the use of digital technologies and enjoy having on-demand access to lecture content and other materials, par-ticularly for revision and assessment. However, there are a number of associat-ed issues that can lead to unintended consequences for those involved and for wider society. After the introduction, this chapter starts with a brief description of digitalisa-tion in Higher Education to offer context for the digital transformation of univer-sity learning. Section 3 considers who might be particularly affected by barriers around the move to large-scale E-Learning in terms of digital access and the dig-ital divide. This is followed by exploration of three key issues around the unin-tended consequences related to the rapid uptake of digitised teaching and learning due to the COVID-19 pandemic. These issues are: (1) the impact of E-Learning on assessment, particularly where and how learning is delivered due to remote learning and assessment; (2) the use of learning analytics, and how da-ta is gathered and used particularly with the growing use of learning analytics which can undermine privacy and increase the surveillance of people’s activi-ties?; (3) the implications of machine learning/Artificial Intelligence (AI) in learn-ing and teaching, and what ways students are supported by digitalisation through the increased use of Machine Learning/Artificial Intelligence (AI) assis-tants for students? Finally, conclusions are presented