Description: Intelligent systems (e.g., Intelligent Tutoring Systems) have been developed and empirically evaluated to support human learning in a variety of domains (e.g., STEM). Recent advancement in AI technologies has allowed such systems to become even more effective through, for instance, adaptive tutoring (e.g., adaptive problem selection, and affect detection). In this block seminar, we will review key papers on intelligent systems that support human learning and discuss future opportunities for further enhancing such systems. We will also pretend to be secondary-school learners and use some of the established intelligent systems to get hands-on experiences. The seminar is open to both master’s and bachelor’s students. The seminar doesn’t require any prerequisite knowledge and is therefore open to students with any background, but knowledge or experience in one or more of these fields will help: cognitive science, learning sciences, and Human-Computer Interaction. This seminar is open to students in all departments/faculties across UdS campus. Active participation in class discussions and activities is expected and encouraged. I rather want to design learning experiences in this seminar with students – your active participation is the key to the success of the seminar! SIC Seminar page

Learning objectives: By completing this seminar, you will be able to discuss the benefits and limitations of various intelligent systems designed for supporting human learning. You will also be able to generate new research and development ideas for the future of intelligent learning systems.

Lecturer:  Tomohiro Nagashima (nagashima[at]cs.uni-saarland.de), Man “Echo” Su (mansu[at]cs.uni-saarland.de)

The number of students:  12 maximum

Location:  TBD (in-person attendance required; however, if remote participation is desired due to special reasons, please consult in advance)

Time: block seminar in March; we will meet on March 1, 4, 6, 8, 11, 13, and 15th. All 11:00-13:00 except for 13th (14:00-16:00).

Credit points: 7CP

Application/Enrollment: If you are in the CS department, please use the seminar portal to send your application with a motivation statement (by October 24, 2023). If you are in other departments (e.g., EduTech), please email Tomo and Echo a brief motivational statement on why you are interested in this seminar by October 22, 2023

Grading:

• 20% daily reading posts (summary and your thoughts on papers we read)
• 30% discussion lead (present 10min summary of the paper, once for every student)
• 40% final report (2000-3000 words on the future of intelligent learning systems)
• 10% contributions to discussion during the class

Tentative List of Topics:

• Day 1: Introduction, History of intelligent learning systems 
• Day 2: Cognitive principles in designing intelligent systems for supporting learning
• Day 3: Efficacy studies of intelligent tutoring systems
• Day 4: Hands-on exercise or learning analytics/data mining with intelligent systems
• Day 5: Supporting affect, motivation, and engagement with intelligent systems
• Day 6: Self-regulated learning with intelligent systems (guest lecture: Daryn Dever from the University of Central Florida)
• Day 7:  Participatory design for learning technology