Recently Dr. Robert Murphy of the RAND Corporation, a presenter in Alelo’s Webinar Series on the Future of AI in Education and Training, was interviewed by Education Week. In the interview Bob revisited some of the points that we discussed in the Alelo webinar, and went on to talk about the potential impact of COVID-19 on the adoption of AI-based tools in K-12 education. The impact of COVID-19 on the adoption of AI is also of great interest at Alelo, so here are some additional comments and elaborations on the points that Bob discussed, based upon our observations of the needs of teachers and students during this time.
In the Education Week interview Dr. Murphy said: “I do believe the current COVID-19 distance learning situation will bring renewed attention to the need for online instructional systems that support adaptive instruction and provide automated feedback and support to students when teachers and parents cannot be present.” Now that teaching is mainly taking place through videoconferencing, this point has become critical. Teachers find that teaching via videoconference is time-consuming, and it is more difficult to track student progress. Therefore, as a practical necessity, students are going to have to do more work on their own using online tools.
This raises an issue of accountability. Teachers we work with want to know how much time students are spending using Alelo tools, how well the students are performing, and how they are improving over time. This enables teachers to hold students accountable for their work outside of class.
Dr. Murphy discussed whether teachers, parents, and students will trust AI to make the best recommendations. This is another kind of accountability issue. Our teachers express an interest in seeing the student data that underlie Alelo system decisions. This enables them to form their own conclusions about student progress, and gives teachers confidence that the system is making the right decisions.
Dr. Murphy mentions three potential barriers to adoption of advanced AI solutions: (1) lack of appropriate data sets to train AI, (2) funding for development, and (3) data-privacy issues. In my view these issues are readily solvable and need not constitute barriers. Alelo follows international data protection and privacy standards. We constantly collect and archive learner data, and curate them to make sure that we are appropriate for training the machine learning algorithms. New funding vehicles such as crowdfunding make funds more broadly available.
Looking ahead, after the COVID-19 pandemic is over, we do not anticipate that teaching will revert to the way it was done before. Teachers and students are becoming accustomed to online instruction, and they will come to expect AI-based learning tools as well.