How AI and Data Could Personalize Higher Education

Executive Summary

Artificial intelligence (AI) is rapidly transforming and improving the ways that industries like healthcare, banking, energy, and retail operate. However, there is one industry in particular that offers incredible potential for the application of AI technologies: education. Today’s colleges and universities face a wide range of challenges, including disengaged students, high dropout rates, and the ineffectiveness of a traditional “one-size-fits-all” approach to education.  But when big data analytics and artificial intelligence are used correctly and ethically, personalized learning experiences can be created, which may in turn help to resolve some of these challenges.

Artificial intelligence (AI) is rapidly transforming and improving the ways that industries like healthcare, banking, energy, and retail operate. However, there is one industry in particular that offers incredible potential for the application of AI technologies: education. The opportunities — and challenges — that the introduction of artificial intelligence could bring to higher education are significant.

Personalized learning as a cornerstone

Today’s colleges and universities face a wide range of challenges, including disengaged students, high dropout rates, and the ineffectiveness of a traditional “one-size-fits-all” approach to education. But when big data analytics and artificial intelligence are used correctly, personalized learning experiences can be created, which may in turn help to resolve some of these challenges.

With a personalized learning experience, every student would enjoy a completely unique educational approach that’s fully tailored to his or her individual abilities and needs. This could directly increase students’ motivation and reduce their likelihood of dropping out. It could also offer professors a better understanding of each student’s learning process, which could enable them to teach more effectively. Here’s what this might look like: AI-based learning systems would be able to give professors useful information about their students’ learning styles, abilities, and progress, and provide suggestions for how to customize their teaching methods to students’ individual needs. For example, some students might be experiencing learning difficulties or challenges that require extra attention or tutoring to keep up. Others might be advancing so rapidly that they are not being intellectually challenged and would benefit from additional study materials or assignments. In both of these hypothetical scenarios, 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.

For this type of AI-based learning system to work properly, big data would be needed in order to train it. As discussed later in this article, 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.

Personal data will be a key ingredient

In theory, the application of AI and personalized learning sounds like an ideal solution to some of the most common educational issues. However, the technology still has a long way for to go before it can fully meet its potential.

The primary ingredient of personalized learning is a large amount of student data. My own personal experience in lecturing at universities around the world has shown me that today’s students are more protective of the privacy of their data than previous generations, most likely due to the security breaches and data scandals they’ve already been exposed to.  However, if student data could be collected and processed in a way that was ethical, secure, and transparent, it would allow AI to be used to effectively improve just about every area of study.

Insight Center

One promising initiative in this direction comes from MyData.org, an international non-profit whose mission is to promote human-centered control and privacy of personal data. MyData.org, which has become a global movement, aims to give users more control over which personal data they choose to share with AI systems.

Chatbots can provide personalized help and guidance

Recently, The University of Murcia in Spain began testing an AI-enabled chatbot to answer students’ questions about the campus and areas of study. As this chatbot was rolled out, the school’s administrators were surprised to discover that it was able to answer more than 38,708 questions, answering correctly more than 91% of the time. Not only was this chatbot able to provide immediate answers to students outside of regular office hours, but university officials also found that the chatbot increased student motivation. All of these benefits were achieved without the need to change the structure of the staff.

One additional benefit of having chatbots at universities to answer students’ questions is the large volume of big data that would be obtained regarding students’ concerns and areas of interest. This data could be analyzed to help enable universities to create innovative new services and programs to further improve students’ educational experiences.

Several other universities have also started to test the application of chatbots for repetitive tasks that would normally require a professor or faculty member to perform — such as providing answers to students’ 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.

These tests have confirmed that many repetitive tasks and routines could benefit from the assistance of AI-enabled systems, offering teachers more time to focus on educating their students or to engage in research pursuits.

To reduce students’ stress and improve their motivation to study, universities should also consider introducing chatbots and virtual assistants that can help them manage their mental well-being. One example of such a tool is Woebot, an AI-enabled chatbot designed to help users learn about their emotions with “intelligent mood tracking.”  At a time when many university health systems are stretched to capacity, and students experience dangerously long wait times for on-campus mental health counseling, chatbots could provide some immediate relief. Of course, introducing such a chatbot is not without its own inherent risks. Universities would need to exercise extreme caution in protecting students’ personal data and would need some level of human oversight to monitor the advice that chatbots are giving students.

Important challenges that lie ahead

As universities begin to apply AI to various operations, they will likely find that there are still a number of challenges to be resolved. Perhaps the most crucial point to address is the way in which educational institutions can best prepare students for the new technology-based world and the many disruptive technologies that will change the way people work.

It is essential that students understand that over time, more repetitive and routine tasks will be automated and performed by artificial intelligence, automation, and robots. However, there will always be roles requiring creative skills, cognitive skills, and emotional intelligence skills. 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.

As artificial intelligence is applied to education, the best results will come from combining the strengths of AI and human abilities. There will never be a time when humans aren’t necessary for the tasks related to education. For example, teachers will always play a crucial role in our society, as we must never underestimate the value of human interaction and critical thinking in the field of education.

Even though algorithms can be helpful in guiding decisions, not all educational activities should be run by robots and algorithms. The assistance provided by AI algorithms should instead be leveraged to support the creation of optimal learning environments. For example, AI-based learning systems would be excellent tools for teaching rule-based subjects like foreign languages and math. AI systems could significantly enhance the learning process by providing greater precision and more accurate feedback, and would also allow students to take the time to repeat study exercises as many times as necessary. However, a teacher would still be needed to help explain whatever students don’t understand, like the nuances and exceptions to rules of languages, or how to apply mathematical formulas to solve problems. The professor’s role would be to guide, support, and mentor students, helping them to understand what they’ve learned, why it’s important, and how it can be applied in the real world.

A final major challenge in the implementation of AI technologies is the oversight of data usage. There are difficult and important decisions that will need to be made on every level of society about data ownership, as well as the best ways to use data transparently and ethically.

Although AI offers many exciting developments, especially for improving education around the world, we are still in the early stages of its use. More experimentation and research is necessary for AI tools to be successfully implemented throughout higher education institutions.

Personally, I’d encourage more university leaders and administrators to become proactive in initiating pilot programs to test the use of AI in various ways, while critically considering the results and the ethical obligations that must be met along the way. Also, students should learn about how algorithms use data to make decisions, and their input into the design and development of AI systems should be invited and encouraged. Above all, students should remain informed about the ways in which their data is being used.