Advanced Research in Intelligent Systems (ARIES)
The ARIES lab is dedicated to the fusion of computing technology and education. They aim to develop intelligent education systems that can customize themselves to the interests and abilities of individual learner, as well as developing tools that enable human educators to engage with their students using technology.
Notable Research Accomplishments
The ARIES Laboratory is a well known centre for work on intelligent learning environments, especially in international research communities such as Artificial Intelligence in Education (AIED), Intelligent Tutoring Systems (ITS), User Modeling, Adaptivity, and Personalization (UMAP), Educational Data Mining (EDM), and Learning Analytics and Knowledge (LAK). ARIES faculty members serve on program committees of key international conferences in these areas, are members of the editorial boards of the major journals in the areas, and have been instrumental in helping to develop the communities themselves through service to international societies. Former students and research assistants are now prominent in the software industry or are employed at other universities, and at various places around the world.
Current Research Projects
- The development of a system to help learners discuss cases as they learn how to deal with professional ethics issues
- Investigating patterns in keystroke level data captured as learners interact with online reading material as they answer questions at various levels of Bloom's taxonomy
- Building a reciprocal recommender system in the lifelong learning context of graduate students seeking help, and testing the system in a simulated version of a graduate school
- Gamifying online learning to help build social connections for online learners and to better motivate them
- Investigating through simulation the best techniques for recommending learning objects in the ecological approach architecture
- Enhancing peoples' visits to museums through recommender system techniques
- Using learning analytics to find useful patterns in educational data
- Dr. Gordon McCalla (Professor Emeritus)
- Dr. Julita Vassileva
- Dr. Ralph Deters