Getting Schooled by Artificial Intelligence: How to use AI to improve classroom learning
Artificial intelligence is everywhere
At Georgia Tech University, Professor Ashok Goel brought on a Teaching Assistant (TA) named Jill Watson to handle the large number of forum posts1 in his computer science course. The students liked her so much that they recommended her for a teaching award.2 But Jill wasn’t actually a human: she was completely fabricated via Artificial Intelligence (AI) - the students had no idea until Dr. Goel’s reveal at the end of the semester.
Why is AI used in education?
Educational AI currently manifests as online humanoid chatbots, working either independently or in conjunction with instructors. These chatbots, like Jill Watson, will become more popular over time.3
In the United States and abroad, teachers are often underpaid and overworked, and their capacity for productivity is hindered by their high load of responsibilities.2 But AI can help: in one study, researchers found that with AI, instructors were able to perform administrative functions more accurately and effectively - and it improved students’ quality of learning.3
Algorithmic systems are growing in education through use of microblogging sites, academic social media platforms, and mobile applications. Instructors from kindergarten through high school are increasingly using scholarly social media sites,4 which places the teaching responsibilities onto intelligent algorithmic systems.5
The benefits of AI in the classroom
The use of AI in educational settings provides 3 key benefits for teachers and students. AI can:
- Support a mixed-abilities classroom6,7
- Reduce the pressure placed on teachers and gives them more time to support students6,7
- Create a more personalized learning experience for students8
References
- Meet Jill Watson: Georgia Tech’s first AI teaching assistant. (2016, November 10). Georgia Tech Professional Education. https://pe.gatech.edu/blog/meet-jill-watson-georgia-techs-first-ai-teaching-assistant
- Chace, C. (2020, October 29). The Impact of Artificial Intelligence on Education. Forbes. https://www.forbes.com/sites/calumchace/2020/10/29/the-impact-of-artificial-intelligence-on-education/
- Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
- Greenhow, C., Galvin, S. M., Brandon, D. L., & Askari, E. (2020). A Decade of Research on K–12 Teaching and Teacher Learning with Social Media: Insights on the State of the Field. Teachers College Record, 122(6), 1–72. https://doi.org/10.1177/016146812012200602
- Cheney-Lippold, J. (2017). We Are Data: Algorithms and the Making of Our Digital Selves. In We Are Data. New York University Press. https://doi.org/10.18574/nyu/9781479888702.001.0001
- Hrastinski, S., Olofsson, A. D., Arkenback, C., Ekström, S., Ericsson, E., Fransson, G., Jaldemark, J., Ryberg, T., Öberg, L.-M., Fuentes, A., Gustafsson, U., Humble, N., Mozelius, P., Sundgren, M., & Utterberg, M. (2019). Critical Imaginaries and Reflections on Artificial Intelligence and Robots in Postdigital K-12 Education. Postdigital Science and Education, 1(2), 427–445. https://doi.org/10.1007/s42438-019-00046-x
- Roll, I., & Wylie, R. (2016). Evolution and Revolution in Artificial Intelligence in Education. International Journal of Artificial Intelligence in Education, 26(2), 582–599. https://doi.org/10.1007/s40593-016-0110-3
- Hubert, K. (2021, March 30). The Benefits of AI in Education. Capacity. https://capacity.com/the-benefits-of-ai-in-education/
- Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020). Application and theory gaps during the rise of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002
- Fahimirad, M., & Shakib Kotamjani, S. (2018). A Review on Application of Artificial Intelligence in Teaching and Learning in Educational Contexts. International Journal of Learning and Development, 8. https://doi.org/10.5296/ijld.v8i4.14057
- Peterson, R. (2013, November 12). Why Do Students Drop Out of MOOCs? By Rachelle Peterson | NAS. https://www.nas.org/blogs/article/why_do_students_drop_out_of_moocs
- Chen, K.-C., & Jang, S.-J. (2010). Motivation in online learning: Testing a model of self-determination theory. Computers in Human Behavior, 26(4), 741–752. https://doi.org/10.1016/j.chb.2010.01.011
- What Is Self-Efficacy? (2022, April 28). WebMD. https://www.webmd.com/balance/what-is-self-efficacy
- Garrison, D. R., Anderson, T., & Archer, W. (1999). Critical Inquiry in a Text-Based Environment: Computer Conferencing in Higher Education. The Internet and Higher Education, 2(2), 87–105. https://doi.org/10.1016/S1096-7516(00)00016-6
- Jensen, S. A. (2011). In-Class Versus Online Video Lectures: Similar Learning Outcomes, but a Preference for In-Class. Teaching of Psychology, 38(4), 298–302. https://doi.org/10.1177/0098628311421336
- Ivanov, B. (2020, November 30). The Role of Artificial Intelligence in E-learning. Medium. https://becominghuman.ai/the-role-of-artificial-intelligence-in-e-learning-41ac88ee3e8d
- How Is AI Being Used in E-Learning in 2020? (2020, July 24). LearnDash.https://www.learndash.com/how-is-ai-being-used-in-e-learning-in-2020/
About the Authors
Lindsey Turk
Lindsey Turk is a Summer Content Associate at The Decision Lab. She holds a Master of Professional Studies in Applied Economics and Management from Cornell University and a Bachelor of Arts in Psychology from Boston University. Over the last few years, she’s gained experience in customer service, consulting, research, and communications in various industries. Before The Decision Lab, Lindsey served as a consultant to the US Department of State, working with its international HIV initiative, PEPFAR. Through Cornell, she also worked with a health food company in Kenya to improve access to clean foods and cites this opportunity as what cemented her interest in using behavioral science for good.
Dan Pilat
Dan is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. Dan has a background in organizational decision making, with a BComm in Decision & Information Systems from McGill University. He has worked on enterprise-level behavioral architecture at TD Securities and BMO Capital Markets, where he advised management on the implementation of systems processing billions of dollars per week. Driven by an appetite for the latest in technology, Dan created a course on business intelligence and lectured at McGill University, and has applied behavioral science to topics such as augmented and virtual reality.
About us
We are the leading applied research & innovation consultancy
Our insights are leveraged by the most ambitious organizations
“
I was blown away with their application and translation of behavioral science into practice. They took a very complex ecosystem and created a series of interventions using an innovative mix of the latest research and creative client co-creation. I was so impressed at the final product they created, which was hugely comprehensive despite the large scope of the client being of the world's most far-reaching and best known consumer brands. I'm excited to see what we can create together in the future.
Heather McKee
BEHAVIORAL SCIENTIST
GLOBAL COFFEEHOUSE CHAIN PROJECT
OUR CLIENT SUCCESS
$0M
Annual Revenue Increase
By launching a behavioral science practice at the core of the organization, we helped one of the largest insurers in North America realize $30M increase in annual revenue.
0%
Increase in Monthly Users
By redesigning North America's first national digital platform for mental health, we achieved a 52% lift in monthly users and an 83% improvement on clinical assessment.
0%
Reduction In Design Time
By designing a new process and getting buy-in from the C-Suite team, we helped one of the largest smartphone manufacturers in the world reduce software design time by 75%.
0%
Reduction in Client Drop-Off
By implementing targeted nudges based on proactive interventions, we reduced drop-off rates for 450,000 clients belonging to USA's oldest debt consolidation organizations by 46%
