Opportunities and Challenges of Adopting Artificial Intelligence for Learning and Teaching in Higher Education

Introduction

Over the past two decades the term artificial intelligence (AI) has received an increased interest in academia and practice. Although the foundations for AI from assembly and procedural language, object-oriented computer programming, data mining, and machine learning have been laid several decades ago, some uncertainty regarding consequences of the full adoption of AI to the society and economy remains. Recent breakthroughs towards natural language processing (NLP), computer vision, image recognition, text-to-speech and speech-to-text have further accentuated the capabilities of AI.

AI adoption can result in significant social and economic benefits since computers can quickly analyse and learn from vast amounts of data at higher accuracy and speed. Furthermore, AI can improve efficiency in nearly all sectors of human endeavour, ranging from transportation, healthcare, industrial manufacturing, and financial sectors. In each of these sectors, research into the integration of AI to processes is on the increase to infuse methods for efficient and cost effective data-driven decision-making (Collins et al., 2018; Poonia et al., 2018; Wang et al., 2018). According to a report by Gov.UK, AI adoption could add an additional £630bn to the UK economy by 2035 (Hall and Pesenti, 2019). To this end, there is a shortage of AI experts in the UK, therefore teaching of AI in HEIs via industry-funded master’s degrees and research in AI at leading UK universities should be increased (Hall and Pesenti, 2019).

AI is currently progressing an already has positive impacts on services within higher education. For instance, many universities already partner with IBM to provide cloud-based access to the emergent AI platform – IBM’s supercomputer Watson – to automate simple, repetitive, and typically administrative tasks, such as attendance reminder, classifying feedback, and student support. Even though only the basic service is provided, it provides an illustration of the impact of AI on teaching and learning in higher education. From the foregoing, it is imminent to increase the adoption of AI for educational purposes, in order to equip students or learners with relevant skills that can fill skill gaps in domains. Furthermore, answers to the following questions can make clearer the hurdles that need to be overcome to adopt AI for higher education teaching and learning.

• i.

  How can AI be integrated to the teaching curriculum?

• ii.

  Can AI be used to assess and provide feedback to students automatically?

• iii.

  What impact will AI have to classroom size?

• iv.

  What are the ethical implications of integrating AI for HEI teaching / learning?

Addressing these questions will lead to better understanding and provide a discussion that can benefit higher education regulatory bodies that can improve the visibility of AI in the society and economy.