Paper Title
THE POTENTIAL OF SPATIAL COMPUTING AND NATURAL LANGAUGE PROCESSING INCORPORATION IN HIGHER EDUCATION: A HUMAN RESOURCE-BOT CASE

Abstract
Abstract - The higher education systems of today will not be applicable to the demands and requirements of tomorrow. This highlights the importance to keep on adapting and improving the higher education sector to meet the demands of consumers and the changing environment. One of the most prominent changes we currently face is the era of the fourth industrial revolution and the incorporation of new technologies in our higher education systems. This study aimed to contribute to this growing area of research by exploring the potential of combining Natural Language Processing (NLP) tasks through Large Language Models (LLM) via sentiment analysis with spatial computing in higher education through a review of literature. Additionally, this paper aimed to contribute novel information on the design and building of a ‘smart-HR-bot’ (NexAR) as one potential use-case for combining these technologies. This web-based HR-bot offers many unique characteristics such as being accessible via any mobile device and a customizable avatar of which its data can be tailored for a wide array of use cases. The HR-bot has been developed by the co-author and is showcased in this paper as one solution to incorporate these technologies in the higher education classroom to enhance learning and meet the challenges of the rapidly changing environment. As a case study, NexAR simulates a human resource scenario where the student can interact with the bot according to a predetermined data set within specific parameters. The bot aims to enhance the teaching and learning experience, increased inclusivity, efficient teaching and assessment, innovative pedagogical approaches and flexible learning environments. The bot is showcased in this paper, the next step will be testing it in the higher education setting. Keywords - Spatial Computing, Augmented Reality, Artificial Intelligence, Higher Education, Natural Language Processing.