The Use of Artificial Intelligence In Higher Education
Lasse Rouhainen, the author of Artificial Intelligence: 101 Things You Must Know Today About Our Future and an international expert on artificial intelligence, disruptive technologies, and digital marketing wrote recently in Harvard Business Review about his views on how AI could be used in higher education.
In his opinion both the opportunities and challenges that the introduction of artificial intelligence could bring to higher education “are significant.” As he notes, the higher education today in general faces a wide range of challenges – from “disengaged students, high dropout rates, and the ineffectiveness of a traditional “one-size-fits-all” approach to education.”
Rouhainen sees the possibility to overcome these challenges with the correct use of big data analytics and AI, which would create “personalized learning experiences,” that would then overcome some of these challenges. This personalized learning experience would create “a completely unique educational approach,” which in turn offers the possibility of increasing student’s motivation and possibly lower the drop out rate. On the other hand, professors would have the ability to better understand the learning process of each of their students, making the teaching process much more effective.
As the author explains, “AI learning systems would be helping students to reach their full potential, quite possibly preventing them from dropping out by identifying problems early enough to allow the appropriate corrective measures to be taken.” To achieve that, though, and to make an AI-based learning system to work properly, “big data would be needed in order to train it.” Rouhainen adds the caveat that “data would need to be used ethically, and students would need to be informed about how their personal data might be shared and used by AI algorithms.”
Such ‘ethical use’ could be in the form of “ MyData.org, an international non-profit whose mission is to promote human-centered control and privacy of personal data.” The basis on which MyData.org operates is “to give users more control over which personal data they choose to share with AI systems.”
A successful AI testing was noted at The University of Murcia in Spain when an AI-enabled chatbot to answer students’ questions about the campus and areas of study. The results were quite surprising to school administrators – the chatbot was able able to answer more than 38,708 questions, answering correctly more than 91% of the time. As was also noted, this chatbot was “able to provide immediate answers to students outside of regular office hours, but university officials also found that the chatbot increased student motivation.” At the same time, there were no changes in the structure of the staff.
Similar advances were registered at several other universities that tested chatbots in handling repetitive tasks that otherwise need to be handled by either a professor or a member of faculty staff. One such task is answered student FAQ’s frequently asked questions. Staffordshire University in the UK and Georgia Tech in the U.S. have rolled out chatbots that offer 24/7 answers to students’ most frequently asked questions.
Rouhainen also mentions the use of AI in reducing stress among students and improving their motivation. This could be achieved with the use of chatbots and virtual assistants that would take a student’s mental well-being. As an example, he mentions Woebot, an AI-enabled chatbot designed to help users learn about their emotions with “intelligent mood tracking.”
One of the problems the author sees is the fact that students need to understand that“over time, more repetitive and routine tasks will be automated and performed by artificial intelligence, automation, and robots.” He stresses that right now, “many universities around the world are failing to teach students about the kinds of skills that will and will not be needed in their future careers.”
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