Estimated reading time: 3 minutes, 30 seconds
In case you missed my last post, I am blogging an unpublished paper as a series in parts over several days. You can read that post to understand the story and the reason behind this. Comments on each post welcome. This is the first post, and it will have the abstract and references. I added something between brackets in the abstract.
Abstract
The potential uses of Artificial Intelligence and particularly Machine Learning in education has been gaining traction in media. We often hear the perspectives of the designers, often computer scientists or corporations, and more recently, we hear groups working towards a more ethical AI, often at large research institutions like MIT, Harvard and Stanford. But how do educators use AI and how do they perceive other potential uses? There is a gap in the literature that tackles educators’ experiences on the ground, to see whether AI indeed solves problems or creates opportunities for enhancing teaching and learning. This article will focus on three applications of machine learning in higher education: plagiarism-detection systems such as Turnitin.com, automated grading, and teacher bots, and two others, speech recognition and automated translation. Faculty/academic developers at two African universities (in Egypt and South Africa) were interviewed about their actual experiences with Turnitin.com, its benefits, costs and challenges, from both a pedagogical and logistical perspective. They were also asked about their attitudes and perceptions towards the potential of teacher bots, automated grading, speech recognition and automated translation, and what it means for the future of the teaching profession. They were also asked explicitly about ethical issues in AI and how this influences their perception of the future of AI in education.
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That’s it for now – wanna suggest more references? Leave them in the comments?
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