Massive Open Online Courses
Massive Open Online Courses (MOOCs) made education accessible to anyone with internet access. As reported by Class Central, in 2018, there were 101 million learners enrolled in MOOCs, with the top platforms being: Coursera with 37 million learners, edX with 18 million, XuetangX with 14 million, Udacity with 10 million, and FutureLearn with 8.7 million. More than 900 universities in the world offer MOOCs courses, including higher education degrees. However, MOOCs are struggling with one major problem: extremely low retention. In 2015, one report on MOOC completion rate stated that only 12.6% of learners completed their courses. But in March 2019, Financial Times reported that a study by MIT found that online courses had a 96% dropout rate over five years. To save the situation, e-learning platforms are using learners’ data to help them go on with their education.
For example, edX tracks user engagement – how frequently learners watch videos and submit assignments. When they see data indicating that someone will drop out, they give them a little push to go forward by sending updates and reminders to complete tasks. Nina Huntemann, senior director of academics and research at edX, says that engagement is 30% higher when students have been nudged. What’s more, edX figured out that if learners are struggling with a course, the material may not be worded clearly enough or the videos may be too long. The university partners working with edX later use that data to produce course iterations.
What are the AI solutions enhancing e-learning platforms?
Coursera is currently the most popular e-learning platform, and one that emphasizes the importance of AI in their educational offer. There are university and professional courses in AI for business, digital strategy, machine learning, deep learning, and many more AI-related topics. It was co-founded by Andrew Ng, a well-known AI and ML researcher, professor at Stanford University, who also co-founded Google Brain and deeplearning.ai.
So Coursera will teach you about AI, but how does it use AI solutions in practice? Though it’s difficult to find details on the exact solutions they use, even looking at your profile, you can figure out that they have a decent recommendation system in place. To get course recommendations, you can solve a short test where you specify the area of your interest and answer a few questions. After you’ve done that, you’re shown the result, and courses are recommended based on your current level of knowledge. Additionally, the platform keeps track of your on-site activity (enrollment in courses, what courses you displayed) to suggest related courses that you may be interested in. It works similar to the recommendation systems in Netflix or Amazon – where we are served with the recommendations of movies or products, but in this case, the recommendations we get are about courses in the area we’re interested in.
AI can also provide assistance to students on a daily basis. Have you heard of Jill Watson? The last name may give it away, and yes, “she” is related to the Watson of IBM. Jill Watson is a graduate-level artificially intelligent teacher assistant (TA). Jill helps students of the Knowledge-Based Artificial Intelligence course at Georgia Tech. Jill was implemented on IBM’s Watson platform and first used in the spring 2016 semester.
When Georgia Tech introduced Jill into their course, they run a little experiment: they didn’t tell the students which TA is AI and which one is human. They had 2 “Jills” named Stacy and Ian working alongside 13 human TAs. In an article from January 2017, they describe this experiment and their observations on the virtual TAs activity. At the end of the semester, students were polled about who was human and which TA was AI. A little over 50% of them guessed that Stacy was AI and 16% named Ian as non-human. About 10% of the students thought that 2 of the human teacher assistants weren’t real.