Keynote Lectures

Learning Environments with Conversational Agents
Art Graesser, University of Memphis, United States, United States

Implementing Learning Analytics
Barbara Wasson, University of Bergen, Norway, Norway

Intelligent Mentoring: Linking Learning Analytics and Interactive Nudges to Support Life-wide Learning
Vania Dimitrova, School of Computing, University of Leeds, United Kingdom, United Kingdom

Abstract
Computer agents can participate in conversations with students, help them learn, and assess their progress in acquiring knowledge and skills. The design of an agent (e.g., talking head, chatbot, avatar) requires a research team with expertise in artificial intelligence, computational linguistics, psychology, discourse processes, and data mining in addition to education.  This presentation describes some learning environments with computer agents that target different adult populations.  These systems implement the eight learning affordances in the digital age that were identified in the 2018 edition of How People Learn of the National Academy of Sciences, Engineering, and Medicine: interactivity, adaptivity, feedback, choice, nonlinear access, linked representations, open-ended learner input, and communication with others. Some systems have three-party conversations, called trialogues, where two agents (such as a tutor and a peer) interact with the adult. The adult populations have ranged from struggling adult readers who need to improve their comprehension skills to advance their careers (AutoTutor-ARC) to high ability sailors in the Navy learn electronics (ElectronixTutor).  This presentation addresses a fundamental question: When does it make sense (or NOT) to include conversational agents in a learning environment?  

Abstract
Implementing Learning Analytics in Education
After 12 years Learning Analytics and Knowledge is a thriving research field, but still has to make a major impact on education. Why is it so hard to implement learning analytics in education?  Through reflections on research to practice, and examples  from my own experience in Norway I will address the complex challenges (e.g., law, ethics, technological, cultural, and pedagogical) that are met when scaling up the use of learning analytics in education. 

Abstract
In the past decades, the successful and deployable solutions of intelligent learning environments have predominantly been in formal education, usually school or university settings. Socio-economic and technological developments show the need to broaden the educational scope to address soft (transferable) skills and to include life-wide learning in real contexts and everyday life experiences. I will argue that this calls for a change in the way we design intelligent learning environments, shifting from tutoring to coaching and mentoring. Digital transformation of education enables the capturing of digital traces which can be analysed to understand the learners, their behaviour, and the overall learning process. Hence, learning analytics approaches can provide ‘sensors’ about aspects of the learners and the learning context. This can then indicate situations in which we can provide nudges to foster behaviour change and facilitate learning. I will illustrate this in several domains and will further research directions.