Learning Technology

fist bump with human hand and robotic hand

We conduct research in artificial intelligence (particularly natural language processing and machine learning) and in human-computer interaction. Our researchers build learning technologies and analyze educational data from such technologies, e.g., intelligent tutoring systems, computer-supported collaborative learning systems, automated writing evaluation systems, and robotic learning environments. In addition, we implement principles of learning and teaching to understand when and why educational technology is effective and rectify it when it isn't.

Additionally, we study the use of mobile applications in large STEM lectures to monitor and enhance student reflection, in medical settings to provide paramedic students with access to practice when not in the field, and in classrooms to support the teaching of statistics.

Our research has created Web-based writing environments that use computational linguistics to score student essays and to provide formative feedback to guide essay revision. We have also used computational linguistics to create analytics to improve the teaching of collaborative argumentation, and to succinctly summarize legal cases for lay users.

We investigate the use of social robots to support collaborative learning and study how the relationship between learners and robots influences knowledge acquisition and use. We are part of the emerging discipline of data mining, the use of educational datasets to better understand students and settings in which they learn.

Related Research Areas:
Motivation & Engagement Reasoning, Decision Making, & Argumentation
Related Research Interests:
Artifical Intelligence Automated Writing Evaluation Computer-supported Collaboration Intelligent Tutoring Systems Natural Language Processing Robotic Learning Environments

Researchers Associated with this Area