Higher education is in a unique position to adopt AI. Many innovations and research breakthroughs in the field will occur on university campuses. One thing you may notice however is that a lot of incredible research happening on the campuses of our public intuitions is failing to be commercialized by our universities. This will be discussed later in the module. For now let’s start with applications of AI in higher education and highlight companies in those areas.
The AI Grad Student
AI has already begun replacing the tasks that TA’s normally do including grading and answering questions.
The Classroom TA
Ashok Goel was teaching an online computer science course with over 400 students. He couldn’t do it alone so he hired Jill Watson to be one of us teaching assistants. Jill answered students’ routine questions about due dates and the course information. Jill wasn’t an ordinary TA, she was a machine! The AI was so convincing that students had no idea that Jill wasn’t human until the end of the course.
The Research Assistant
Ashok Goel’s next hire was Vera also known as Virtual Ecological Research Assistant. VERA is a Georgia Tech project to build AI that can create interactive models of ecological phenomena. AI promises advancements in research in a variety of fields. AI is capable of handling and manipulating data in ways that have never been possible before.
The Grader
AI can be used to grade essays. There have been trials already happening in China, although some argue the technology is not quite ready yet.
Academic honesty and integrity can be improved with AI that detects plagiarism in assignments. An example of a company working in this area is Grammaly. Grammaly uses AI to help students write better including checking for unintentional plagiarism.
Erik Anderson from Cornell created an AI program that could determine what steps or errors students made when answering questions incorrectly
The AI Registrar
Enrollment and Admissions
Artificial intelligence has the potential to automate admissions, enrollment, and retention of students. This technology is already being used by HR departments in large companies to sort through incoming job applicants and streamline the hiring process. This same technology adapts well to education.
Besides the efficiency benefits, there is the hope that A.I. could lead to fairer admissions. There is the belief that by removing humans from some of these processes it could prevent unconscious human bias. This has been criticized however because ultimately the algorithms used in A.I. are created by humans. This means that bias could be coded-in.
Student Retention
The University of Oklahoma partnered with IBM to reduce dropout rates and increase student retention. Typically schools would use structured data like GPA and SAT scores to determine risk of student dropout. Advanced analytics and AI were used to analyse unstructured data not possible before such as student application essays. This unstructured data was scrutinized for tone, personality insights, and choice of language. This was additional data allowed the university to spot retention risks early and provide appropriate services.
Case Study: Applyboard and International Student Market
Applyboard Waterloo based startup uses A.I. to match international students with the right school and program. It has partnered with post-secondary schools across Canada and the United States. A.I. is used to review applicant profiles to recommend the best match for students. The company’s A.I. algorithms analyse complex data sets that include school historical admission data, tuition costs, programs, location, student financial situation, academic records, interests, and more.
The Smart Campus
Thanks to the Internet of Things we live in a world where everything can become wireless sources of data. AI excels with data. This could lead to automated smart campus with classrooms that take attendance and invigilate tests. There are even possibilities outside of the classroom in areas like parking, building maintenance, and safety.
Focus Questions
- What concerns are there regarding the use of A.I. in enrollment, admissions, and retention? What can be done to alleviate potential problems? How could these problems be openings for new startups?
- How might the culture of post-secondary institutions present challenges and opportunities?
