AutoTutor: a tutor with dialogue in natural language.
Arthur C. Graesser,Shulan Lu,G. T. Jackson,Heather H. Mitchell,Mathew Ventura,Andrew Olney,Max M. Louwerse +6 more
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TLDR
The design was inspired by explanation-based constructivist theories of learning, intelligent tutoring systems that adaptively respond to student knowledge, and empirical research on dialogue patterns in tutorial discourse.Abstract:
AutoTutor is a learning environment that tutors students by holding a conversation in natural language. AutoTutor has been developed for Newtonian qualitative physics and computer literacy. Its design was inspired by explanation-based constructivist theories of learning, intelligent tutoring systems that adaptively respond to student knowledge, and empirical research on dialogue patterns in tutorial discourse. AutoTutor presents challenging problems (formulated as questions) from a curriculum script and then engages in mixed initiative dialogue that guides the student in building an answer. It provides the student with positive, neutral, or negative feedback on the student’s typed responses, pumps the student for more information, prompts the student to fill in missing words, gives hints, fills in missing information with assertions, identifies and corrects erroneous ideas, answers the student’s questions, and summarizes answers. AutoTutor has produced learning gains of approximately .70 sigma for deep levels of comprehension.read more
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Journal ArticleDOI
The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems
TL;DR: It was found that the effect size of human tutoring was much lower than previously thought, and the effect sizes of intelligent tutoring systems were nearly as effective as human tutors.
Health literacy interventions and outcomes: an updated systematic review.
Nancy D. Berkman,Stacey L. Sheridan,Katrina E Donahue,David J Halpern,Anthony J. Viera,Karen Crotty,Audrey Holland,Michelle Brasure,Kathleen N. Lohr,Elizabeth Harden,Elizabeth Tant,Ina Wallace,Meera Viswanathan +12 more
TL;DR: Differences in health literacy level were consistently associated with increased hospitalizations, greater emergency care use, lower use of mammography, lower receipt of influenza vaccine, poorer ability to demonstrate taking medications appropriately, poorer able to interpret labels and health messages, and, among seniors, poorer overall health status and higher mortality.
Journal ArticleDOI
Better to be frustrated than bored: The incidence, persistence, and impact of learners' cognitive-affective states during interactions with three different computer-based learning environments
TL;DR: Findings suggest that significant effort should be put into detecting and responding to boredom and confusion, with a particular emphasis on developing pedagogical interventions to disrupt the ''vicious cycles'' which occur when a student becomes bored and remains bored for long periods of time.
References
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Journal ArticleDOI
A Sign That Education is Maturing: Taxonomy of Educational Objectives, the Classification of Educational Goals, Handbook I: Cognitive Domain
TL;DR: Using Bloom's Taxonomy to Write Effective Learning Objectives: The Abcds of Writing Learning ObjectIVES: A Basic Guide.
Book
Foundations of Statistical Natural Language Processing
TL;DR: This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear and provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations.
Journal ArticleDOI
A Solution to Plato's Problem: The Latent Semantic Analysis Theory of Acquisition, Induction, and Representation of Knowledge.
TL;DR: A new general theory of acquired similarity and knowledge representation, latent semantic analysis (LSA), is presented and used to successfully simulate such learning and several other psycholinguistic phenomena.
Book
Affective Computing
TL;DR: Key issues in affective computing, " computing that relates to, arises from, or influences emotions", are presented and new applications are presented for computer-assisted learning, perceptual information retrieval, arts and entertainment, and human health and interaction.