Artificial Intelligence (AI) technologies such as computer vision and Machine Learning (ML) are providing new ways to revolutionize learning and skills training at universities. From doctorate degrees in Machine Learning (ML) to bots that aid the work of teachers, there’s accelerating intrerest at the college level in A.I. and ML.
Research firm TechNavio projects that the AI, market in education will grow by a compound annual growth rate (CAGR) of close to 48% from 2018 to 2022 (the study also noted the role of chatbots in enhancing learning—hopefully that technology pans out better for education than it did for most of buisness world.
Ethics of Artificial Intelligence (AI)…
One area in which AI, intersects with student learning is in ethics. Some studies are already exploring the ethical issues of replacing teachers with bots. However, although bots can enhance education, they can’t replace teachers, according to Bernhardt L. Trout, professor of chemical engineering and director of Society, Engineering and Ethics at the Massachusetts Institute of Technology.
Trout argues that AI, can enrich the learning of students as they master skills, languages and basic math, but it can’t help students learn creativity or critical thinking. “Bots will not be able to decide for us what is good, although they might be able to help us learn better the issues around the decision of what is good,” he said. “Bots are limited in making certain choices about education in ways that human beings are not limited, so this is where we get into the more ethical issues.
Machine Learning(ML) and Educational Data Mining(DM)…
Zachary Pardos, assistant professor in the Graduate School of Education and the School of Information for the University of California at Berkeley, has been developing a system that uses ML to help students choose a course curriculum based on past student enrollment histories. His research uses 10 years of UC Berkeley student enrollment records.
One goal of the initiative is to use ML to get an idea of what every course entails, and to focus on sets of employable skills rather than single-course curriculums. In theory, this ML-powered data mining could help students choose the best courses to meet their goals, making their educational pathway that much more efficient.
Machine learning can also provide data on how students are mastering skills. Pardos has studied AI systems that provide insight on how much additional training students require in a particular skill. “Essentially, the AI is saying: ‘Does the student need to be given more practice, yes or no?’” Pardos said.
Meanwhile, UC Berkeley is among the universities using an assessment and learning system called Aleks, which stands for Assessment and Learning in Knowledge Spaces. Aleks helps teachers determine whether a student has mastered certain skills. The university uses the ML algorithms to develop a personalized curriculum for students in an area such as math, chemistry or accounting. Based on the results of the AI assessment, students might switch their degrees from an area like sociology to data science.