Artificial Intelligence and the Transformation of Digital Education: Robotics, Student Skills, and Learning Analytics

Introduction

Artificial Intelligence (AI) is emerging in almost all sectors of industry, including finance, retail, manufacturing and farming to name a few, and will likely become much more visible to the average employee within the next 5-10 years (this being 2020) as developments grow. Education is one sector where AI could and likely will have a massive impact as it encompasses a lot of administration of large groups of people and tasks, such things as grading of assessments and uploading of results; creating schedules for classes; creating teams and analyzing skills for student projects; creating and teaching learning resources and trying to determine students’ academic progress, to name a few key areas of likely impact. Thus, an important focus and aim of this chapter will be looking at how AI is going to transform the education sector and how that will be managed effectively by exploring three key important elements. This chapter provides insights and discoveries which have come from three multi-award-winning academic experts with findings from a number of digital education and AI research projects, published research papers in AI, secondary data from literature reviews, personal future insights and observations in the sector, which will address three main research questions:

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  what opportunities will robots with AI create for educators and students?

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  what benefits can AI bring to the table when it comes to student professional skills and team allocation for assessments? And

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  what can we learn from student data to better understand students and make predictions about their progress.

Background

Education has been a mainstay for most cultures around the globe and is seen as a progressive ladder for human society because it aims at ensuring cultural heritage and social development Wang et al. (2018). The state of education some might say has been relatively the same across the past 20 years from a technological sense, however in terms of educational theories and methodologies these are always being pushed to the forefront, such approaches like flipped learning and active learning have had a resurgence of late. Educational goals are shifting away from preparation for the workforce in terms of a rigid body of knowledge and on to giving students access to tools and skills which allow them to become experts and on-the-job learners (Common Core & NGSS as cited in Roll & Wylie, 2016) where technological skills like digital literacy and a comprehension of AI will be paramount. While technology moves at a rapid pace and it has embedded itself into education, it has not kept up with the rate of speed in other industries. Major transformations have been with the advent of innovative learning management systems like OnTrack (Cain, 2020) and online learning through avenues like MOOCs delivered on platforms like FutureLearn (Nelson, 2020). These digital resources and trends have come about as the result of high-speed internet and mobile technology strategies (Roll & Wylie, 2016) becoming highly accessible globally, specifically where nearly 50% of the world is online (Hern, 2018).

Advanced technology is a rapidly changing venture and has worked its way into almost every field, including the education sector, usually due to educators being unhappy with the first generation of digital learning environments and looking for alternatives (Cope, Kalantzis, & Searsmith, 2020). So educational technologists tend to look to see what advances there are in technology and see how that can be integrated with education, and when we look for the next significant digital transformation that is bound for the education space, we can look no further than that of new generation AI tools and systems, as they have been introduced and used in nearly all other industries and trades in some shape, form or another (Wang et al., 2018).