AutoTutor [PI: Art Graesser]
AutoTutor is an intelligent tutoring system that helps students learn about computer literacy or physics by holding a conversation in natural language. AutoTutor appears as an animated agent that acts as a dialog partner with the learners. The animated agent delivers AutoTutor's dialog moves with synthesized speech, intonation, facial expressions, and gestures.
AutoCommunicator [PI: Art Graesser and Xiangen Hu]
This project is developing a question answering system that allows faculty, students, and the public to learn about technology transfer and the relevant research projects at the University of Memphis. The system will be one of the Web faculties for the FedEx Institute of Technology site. The user accesses relevant information to their queries by asking a question in natural language and engaging in a brief dialogue with AutoCommunicator until an answer is found. An animated conversational agent is available to guide the dialog.
Coh-Metrix is a system for computing computational cohesion and coherence metrics for written and spoken texts, using advanced methods that are widely used in computational linguistics. Coh-Metrix allows readers, writers, educators, and researchers to instantly gauge the difficulty of written text for the target audience.
Deep Tutor [PI: Vasile Rus]
The researchers are developing an innovative intelligent tutoring system that is intended to improve student outcomes in science relative to current state-of-the art tutoring systems. DeepTutor’s hallmark features are deep natural language and discourse processing, advanced tutoring strategies targeting frequent illusions in tutoring, and advanced instructional strategies in the form of learning progressions.
Guru [PI: Andrew Olney]
Guru models the strategies and dialogue of expert human tutors and is a logical progression from AutoTutor, which models novice human tutors. The Guru expert tutor, by using expert human tutor strategies, actions, and dialogue, should promote larger learning gains than previous novice computer tutors. Guru could have a big impact on Memphis City Schools because it is designed to improve educational outcomes on the Tennessee Gateway Science Test, which high school students must pass to receive a diploma.
iDrive [PI: Barry Gholson]
This project implements vicarious learning strategies wherein learners observe virtual tutoring sessions with conversational agents and multimedia learning environments. The agents ask and answer deep-level questions that facilitate constructive learning in labs and classroom instruction. Exposure to deep-level reasoning questions improves the number and quality of questions asked that are critical to establish interactive knowledge construction. Dialogs with deep-level reasoning questions and also interactive AutoTutor tutoring sessions improved learning over equivalent content presented at a monolog for middle- and high-school aged students.
iMAP (Intelligent MapTask Agent) project investigates multimodal
communication in humans and agents, focusing on linguistic modalities
(prosody and dialog structure) that reflect major communicative events,
and nonlinguistic modalities (eye gaze, facial expressions, and
iSTART (Interactive Strategy Trainer for Active Reading and Thinking) is an automated strategy trainer designed to help students become better readers via multi-media technologies. Pedagogical agents provide students with interactive and adaptive training to use active reading strategies.
Languages Across Cultures [PI: James Pennebaker]
This project investigates the language and discourse patterns of English and Arabic texts using computerized text analysis tools. Specifically, the researchers are interested in analyzing discourse patterns in various corpora such as newspapers, speeches, and conversations to elucidate the leadership style, personality, and social status of leaders. In addition to English and Arabic, analyses will be performed on Korean, Chinese, and other languages. We will use computational tools that automatically analyze texts on hundreds of measures of language and text cohesion (using Coh-Metrix), including word characteristics, syntax complexity, lexical diversity, readability, connectives, latent semantic analysis, co-referential cohesion, mental model dimensions, and genre.
MetaTutor [PI: Roger Azevedo]
is a new multi-agent, hypermedia-based intelligent tutoring system that
is designed to improve the effectiveness of animated pedagogical agents
(APAs) as external regulatory agents in the learning of the circulatory
system. A mixed-initiative intelligent tutoring system similar to
AutoTutor simulates the discourse patterns and pedagogical strategies
of human tutors. The underlying assumption of MetaTutor is that
students should regulate key cognitive, metacognitive, motivational,
social, and affective processes to learn complex science topics. The
design of MetaTutor is based on extensive research by Azevedo and
colleagues showing that adaptive human scaffolding that addresses both
the content of the domain and the processes of self-regulated learning
enhances students' learning of challenging science topics with
project investigates the impact of a Web tutor on helping college
students' identify true versus false bodies of knowledge while
exploring Web pages to research the causes of the eruption of Mt. St.
Helens. The Web tutor (called SEEK, an acronym for Source, Evidence,
Explanation, and Knowledge) was designed to improve a critical stance
through several facilities in a computer environment: spoken hints on a
mock Google search page, on-line ratings on the reliability of
particular Web sites, and a structured note-taking facility that
prompted them to reflect on the quality of particular Web sites.
A computer model of human question understanding (called QUEST) helps survey designers identify problems with questions on a Web-based tool called QUAID (Question Understanding Aid). QUAID is a software tool that assists survey methodologists, social scientists, and designers of questionnaires in improving the wording, syntax, and semantics of questions. QUAID is being used by six government agencies.
Sandia Labs [PI: Sidney D'Mello]
Working in collaboration with researchers at Sandia National Laboratories and the University of Notre Dame, UM researchers will identify skills that may differentially affect performance of individual humans in cognitive tasks relevant to flying airplanes and communicating with team members. The project will either identify or develop measures to quantify individual ability with respect to each identified skill. A battery of tests will be administered to experimental test participants to assess their relative abilities to predict task performance.
Writing Pal [PI: Danielle McNamara]
This project develops a new automated intelligent tutoring system that provides interactive and adaptive strategy training that encourages students to use independent writing techniques. The W-Pal will be evaluated with high school students and English teachers from urban and suburban schools in Memphis. The goal is to provide a tool that provides writing strategy instruction via automated technologies, which offer tutoring that mimics human one-on-one tutoring. The W-Pal allows teachers to provide adaptive one-on-one tutoring, not to a few students in the classroom, but to all of the students in the classroom. As such, this research will significantly impact the educational community by providing an automated instructional writing tool that can potentially benefit students across the nation.