Artificial Intelligence is a “high potential” trend in the 2020 Innovating Pedagogy Report (read the report summary). The first post in this series provided a background of artificial intelligence in education. This post will outline three goals of artificial intelligence and explore one application for artificial intelligence, the animated pedagogical agent.
Three Goals of Artificial Intelligence in Education
Artificial intelligence has developed a symbiotic relationship to the learning process that fulfills three main goals: to replicate human behavior, to model human behavior, and to augment human behavior. In replicating human behavior, artificial intelligence endeavors to replace human activity/cognition in an educational context. In modeling human behavior, artificial intelligence seeks to imitate or mimic the processes of human cognition in an effort to model effective behavior. Finally, in augmenting human behavior, artificial intelligence partners with learners for knowledge acquisition (Sklar & Richards, 2010).
History of Animated Pedagogical Agents
Animated pedagogical agents, appearing in classrooms to personalize the learning process, are one of the most common applications of AI in education. Agents form a social-interaction bridge, paring down often overwhelming content to the individual needs of the learner (Veletsianos & Russell, 2014).
Animated pedagogical agents credit their birth to Carbonell’s 1970 Socratic intelligent tutoring computer system. Though the beginning generations of tutors were abstracted, text-based systems, as technological advances came in rapid succession, tutors incarnated into agents with a distinctly human personae, capable of portraying both social skills and intelligence on a wide variety of topics (Veletsianos, 2010).
Theoretical and Social Foundations of Pedagogical Agents
Learning is a social process and activities that require engaging with others in environments with high social interactivity promote knowledge acquisition (Kim & Baylor, 2006). Though animated pedagogical agents are not “human” in the literal sense, agents benefit from the computer as social actor paradigm. A human face coupled with a natural tendency for human subjects to anthropomorphize computers as social tools, paves the way for interpersonal communication with an animated pedagogical agent. If designed appropriately, learners easily socialize with agents, even making them on equal terms with the instructor (Veletsianos & Russell, 2014).
Roles of Animated Pedagogical Agents
Animated pedagogical agents can assume a wide variety of roles in the learning process. Agents can be text-based or natural language-based engaging in a conversation with the learner complete with a facial expression and non-verbal cues. As the technology behind traditional animation has grown increasingly realistic, so too have animated pedagogical agents grown in their capability to connect with students not only on a knowledge level, but also an empathetic one (Kim & Baylor, 2006). Indeed, because agents are non-judgmental, many students feel more comfortable asking them questions and being vulnerable in the learning process.
This sense of empathy can also increase student engagement and motivation in class. A well-designed agent who gives appropriate encouragement can cause a student to believe more strongly in their skills, increasing the chance of successfully accomplishing a skill. In turn, students who successfully “teach” an animated agent a new skill are shown to be much more confident in their own learning (Bodenheimer et al., 2009).
Animated pedagogical agents can also function as peers to students. Cooperative learning in a peer-to-peer mediated environment has been shown to have a positive impact on student learning (Craig, Driscoll & Gholson, 2004). If the animated agent is designed to look and speak like the students, then the agent can be easily enfolded into the social mix of the class. In a distance education environment, where learners are geographically remote, animated pedagogical agents could decrease transactional distance and increase social presence.
In conclusion, by humanizing the communication methods between learners and computers, animated pedagogical agents are one way AI is impacting education, creating a unique learning environment.
What potential do you see for artificial intelligence in general for education or animated pedagogical agents in particular? Would you (or do you currently) partner with any pedagogical agents in course teaching or design? Please share your experiences or ideas in the comments below!
Sklar, E. & Richards, D. (2010). Agent-based systems for human learners. The Knowledge
Engineering Review, 25(2), 111-35. doi 10.1017/S0269888910000044
Kim, Y., & Baylor, A. L. (2006). A social-cognitive framework for pedagogical agents as
learning companions. Educational Technology Research and Development, 54(6), 569-596. doi: 10.1007/s11423-006-0637-3
Veletsianos, G. & Russell, G. (2014). Pedagogical Agents. In Spector, M., Merrill, D., Elen, J., &
Bishop, MJ (Eds.), Handbook of Research on Educational Communications and Technology, 4th Edition (pp. 759-769). Springer Academic.
Veletsianos, G. (2010). Contextually relevant pedagogical agents: Visual appearance,
stereotypes, and first impressions and their impact on learning. Computers & Education, 55(2), 576-585. doi: 10.1016/j.compedu.2010.02.019
Bodenheimer, B. B., Williams, B. B., Kramer, M. R., Viswanath, K. K., Balachandran, R. R.,
Belynne, K. K., & Biswas, G. G. (2009). Construction and evaluation of animated teachable agents. Educational Technology And Society, 12(3), 191-205. Retrieved from: http://www.ifets.info/others/download_pdf.php?j_id=44&a_id=967
Craig, S. D., Driscoll, D. M., & Gholson, B. (2004). Constructing knowledge from dialog in an
intelligent tutoring system: Interactive learning, vicarious learning, and pedagogical agents. Journal of Educational Multimedia and Hypermedia, 13(2), 163-183. Retrieved from http://0-search.proquest.com.aupac.lib.athabascau.ca/docview/205853786/141C863A0E0723B43D5/6?accountid=8408