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Journal ArticleDOI

AutoTutor: an intelligent tutoring system with mixed-initiative dialogue

01 Nov 2005-IEEE Transactions on Education (IEEE)-Vol. 48, Iss: 4, pp 612-618
TL;DR: Grounded in constructivist learning theories and tutoring research, AutoTutor achieves learning gains of approximately 0.8 sigma (nearly one letter grade), depending on the learning measure and comparison condition.
Abstract: AutoTutor simulates a human tutor by holding a conversation with the learner in natural language. The dialogue is augmented by an animated conversational agent and three-dimensional (3-D) interactive simulations in order to enhance the learner's engagement and the depth of the learning. Grounded in constructivist learning theories and tutoring research, AutoTutor achieves learning gains of approximately 0.8 sigma (nearly one letter grade), depending on the learning measure and comparison condition. The computational architecture of the system uses the .NET framework and has simplified deployment for classroom trials.
Citations
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Journal ArticleDOI
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.
Abstract: We study the incidence (rate of occurrence), persistence (rate of reoccurrence immediately after occurrence), and impact (effect on behavior) of students' cognitive-affective states during their use of three different computer-based learning environments. Students' cognitive-affective states are studied using different populations (Philippines, USA), different methods (quantitative field observation, self-report), and different types of learning environments (dialogue tutor, problem-solving game, and problem-solving-based Intelligent Tutoring System). By varying the studies along these multiple factors, we can have greater confidence that findings which generalize across studies are robust. The incidence, persistence, and impact of boredom, frustration, confusion, engaged concentration, delight, and surprise were compared. We found that boredom was very persistent across learning environments and was associated with poorer learning and problem behaviors, such as gaming the system. Despite prior hypothesis to the contrary, frustration was less persistent, less associated with poorer learning, and did not appear to be an antecedent to gaming the system. Confusion and engaged concentration were the most common states within all three learning environments. Experiences of delight and surprise were rare. These 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.

765 citations


Cites background from "AutoTutor: an intelligent tutoring ..."

  • ...Confusion was the second most common state across environments, thereby substantiating the significant role of confusion (also referred to as perplexity) in complex learning (Craig et al., 2004; Festinger, 1957; Graesser et al., 2005; Guhe, Gray, Schoelles, & Ji, 2004)....

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  • ...AutoTutor is a fully automated computer tutor that simulates human tutors and holds conversations with students in natural language (Graesser et al., 2001, 2005)....

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Journal ArticleDOI
TL;DR: The authors proposed a model to explain the dynamics of affective states that emerge during deep learning activities, which predicts that learners in a state of engagement/flow will experience cognitive disequilibrium and confusion when they face contradictions, incongruities, anomalies, obstacles to goals, and other impasses.

600 citations

Journal ArticleDOI
TL;DR: In this paper, confusion was experimentally induced via a contradictory-information manipulation involving the animated agents expressing incorrect and/or contradictory opinions and asking the human learners to decide which opinion had more scientific merit.

549 citations

MonographDOI
31 Mar 2014
TL;DR: Automated Evaluation of Text and Discourse with Coh-Metrix describes this computational tool, as well as the wide range of language and discourse measures it provides, and empowers anyone with an interest in text to pursue a wide array of previously unanswerable research questions.
Abstract: Coh-Metrix is among the broadest and most sophisticated automated textual assessment tools available today. Automated Evaluation of Text and Discourse with Coh-Metrix describes this computational tool, as well as the wide range of language and discourse measures it provides. Section I of the book focuses on the theoretical perspectives that led to the development of Coh-Metrix, its measures, and empirical work that has been conducted using this approach. Section II shifts to the practical arena, describing how to use Coh-Metrix and how to analyze, interpret, and describe results. Coh-Metrix opens the door to a new paradigm of research that coordinates studies of language, corpus analysis, computational linguistics, education, and cognitive science. This tool empowers anyone with an interest in text to pursue a wide array of previously unanswerable research questions.

445 citations

Journal ArticleDOI
TL;DR: In this paper, a computer-based lesson on the topic of immunization was used as multimedia learning material, and participants were randomly assigned to four conditions created by two factors related to learners' emotion: external mood induction and emotional design induction (positive vs. neutral emotions).
Abstract: Can multimedia learning environments be designed to foster positive emotions that will improve learning and related affective outcomes? College students (N 118) were randomly assigned to 4 conditions created by 2 factors related to learners’ emotion: external mood induction (positive vs. neutral emotions) and emotional design induction (positive vs. neutral emotions). A computer-based lesson on the topic of immunization was used as multimedia learning material. Results indicate that applying emotional design principles to learning materials can induce positive emotions and that positive emotions in multimedia-based learning facilitate cognitive processes and learning. Controlling for the germane load of the materials, the internal induction of positive emotions through design of the materials increased comprehension and transfer, whereas the external induction of positive emotions through mood induction enhanced transfer but not comprehension. Positive emotions induced through mood induction significantly increased the amount of learners’ reported mental effort, whereas positive emotional design reduced the perceived difficulty of the learning task. Positive emotions increased motivation, satisfaction, and perception toward the materials. Mediation analyses suggest that the effect of positive emotions induced externally was mediated by both motivation and mental effort but found no mediators for emotion induced via emotional design, suggesting that positive emotional design has a more direct impact on learning than externally induced emotions. The study suggests that emotions should be considered an important factor in the design of multimedia learning materials.

423 citations

References
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Book
01 Jan 1997
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.
Abstract: Computers are beginning to acquire the ability to express and recognize affect, and may soon be given the ability to " have emotions. " The essential role of emotion in both human cognition and perception, as demonstrated by recent neurological studies, indicates that affective computers should not only provide better performance in assisting humans, but also might enhance computers' abilities to make decisions. This paper presents and discusses key issues in " affective computing, " computing that relates to, arises from, or influences emotions. Models are suggested for computer recognition of human emotion, and new applications are presented for computer-assisted learning, perceptual information retrieval, arts and entertainment, and human health and interaction. Affective computing, coupled with new wear-able computers, will also provide the ability to gather new data necessary for advances in emotion and cog-nition theory. Nothing in life is to be feared. It is only to be understood. – Marie Curie Emotions have a stigma in science; they are believed to be inherently non-scientific. Scientific principles are derived from rational thought, logical arguments, testable hypotheses, and repeatable experiments. There is room alongside science for " non-interfering " emotions such as those involved in curiosity, frustration, and the pleasure of discovery. In fact, much scientific research has been prompted by fear. Nonetheless, the role of emotions is marginalized at best. Why bring " emotion " or " affect " into any of the deliberate tools of science? Moreover, shouldn't it be completely avoided when considering properties to design into computers? After all, computers control significant parts of our lives – the phone system, the stock market, nuclear power plants, jet landings, and more. Who wants a computer to be able to " feel angry " at them? To feel contempt for any living thing? In this essay I will submit for discussion a set of ideas on what I call " affective computing, " computing that relates to, arises from, or influences emotions. This will need some further clarification which I shall attempt below. I should say up front that I am not proposing the pursuit of computerized cingulotomies 1 or even into the business of building " emotional computers ". 1 The making of small wounds in the ridge of the limbic system known as the cingulate gyrus, a surgical procedure to aid severely depressed patients. Nor will I propose answers to the difficult and intriguing questions , " …

5,700 citations

Journal ArticleDOI
TL;DR: The adequacy of LSA's reflection of human knowledge has been established in a variety of ways, for example, its scores overlap those of humans on standard vocabulary and subject matter tests; it mimics human word sorting and category judgments; it simulates word‐word and passage‐word lexical priming data.
Abstract: Latent Semantic Analysis (LSA) is a theory and method for extracting and representing the contextual‐usage meaning of words by statistical computations applied to a large corpus of text (Landauer & Dumais, 1997). The underlying idea is that the aggregate of all the word contexts in which a given word does and does not appear provides a set of mutual constraints that largely determines the similarity of meaning of words and sets of words to each other. The adequacy of LSA's reflection of human knowledge has been established in a variety of ways. For example, its scores overlap those of humans on standard vocabulary and subject matter tests; it mimics human word sorting and category judgments; it simulates word‐word and passage‐word lexical priming data; and, as reported in 3 following articles in this issue, it accurately estimates passage coherence, learnability of passages by individual students, and the quality and quantity of knowledge contained in an essay.

4,391 citations


"AutoTutor: an intelligent tutoring ..." refers background in this paper

  • ...LSA is a high-dimensional statistical technique that measures the conceptual similarity of any two pieces of text [9], [10]....

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Journal ArticleDOI
26 Apr 1985-Science
TL;DR: Computer tutors based on a set of pedagogical principles derived from the ACT theory of cognition have been developed for teaching students to do proofs in geometry and to write computer programs in the language LISP.
Abstract: Cognitive psychology, artificial intelligence, and computer technology have advanced to the point where it is feasible to build computer systems that are as effective as intelligent human tutors Computer tutors based on a set of pedagogical principles derived from the ACT theory of cognition have been developed for teaching students to do proofs in geometry and to write computer programs in the language LISP

3,092 citations

Journal ArticleDOI
TL;DR: The 10-year history of tutor development based on the advanced computer tutoring (ACT) theory is reviewed, finding that a new system for developing and deploying tutors is being built to achieve the National Council of Teachers of Mathematics (NCTM) standards for high-school mathematics in an urban setting.
Abstract: This paper review the 10-year history of tutor development based on the ACT theory (Anderson, 1983,1993). We developed production system models in ACT ofhow students solved problems in LISP, geometry, and algebra. Computer tutors were developed around these cognitive models. Construction ofthese tutors was guided by a set of eight principles loosely based on the ACT theory. Early evaluations of these tutors usually but not always showed significant achievement gains. Best-case evaluations showed that students could achieve at least the same level of proficiency as conventional instruction in one third the time. Empirical studies showed that students were learning skills in production-rule units and that the best tutorial interaction style was one in which the tutor provides immediate feedback, consisting of short and directed error messages. The tutors appear to work better if they present themselves to students as nonhuman tools to assist learning rather than as emulations of human tutors. Students working with these tutors display transfer to other environments to the degree that they can map the tutor environment into the test environment. These experiences have coalesced into a new system for developing and deploying tutors. This system involves first selecting a problem-solving interface, then constructing a curriculum under the guidance of a domain expert, then designing a cognitive model for solving problems in that environment, then building instruction around the productions in that model, and finally deploying the tutor in the classroom. New tutors are being built in this system to achieve the NCTM standards for high school mathematics in an urban setting. (http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA312246)

1,826 citations


"AutoTutor: an intelligent tutoring ..." refers background in this paper

  • ...Second, there are intelligent tutoring systems that adaptively respond to the learner’s actions [3]–[6]....

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