Part I. Experimental Studies: 2. Experiment in psychology 3. Experiments on perceiving III Experiments on imaging 4-8. Experiments on remembering: (a) The method of description (b) The method of repeated reproduction (c) The method of picture writing (d) The method of serial reproduction (e) The method of serial reproduction picture material 9. Perceiving, recognizing, remembering 10. A theory of remembering 11. Images and their functions 12. Meaning Part II. Remembering as a Study in Social Psychology: 13. Social psychology 14. Social psychology and the matter of recall 15. Social psychology and the manner of recall 16. Conventionalism 17. The notion of a collective unconscious 18. The basis of social recall 19. A summary and some conclusions.

Remembering. A Study in Experimental and Social Psychology, Cambridge (University Press) 1964.

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The Development and Psychometric Properties of LIWC2015

which is used to describe a third component of thinking processes, particularly preverbal, and it denotes the concept that the world is activated by some generalized "energy" that links together causally all objects and events ; it is presumably revealed by a person's lack of curiosity about causal connections, as though they were self-evident. Aside from the rather frequent use of such key words, having strong connotations for this reviewer far away from what the author is aiming to denote, the book is written in a lucid and stimulating style that makes reading it an invigorating intellectual exercise. It is a book that is likely to have somewhat limited attraction to the full-time clinician, especially one treating adult patients. And child psychiatrists and psychologists, if reasonably well read, will most likely be familiar with the majority of references from which this author has synthesized his material. On the other hand, the scholarly and refreshing con¬ ceptual approaches of the author will appeal to psychologists, philosophers, linguists, and psychiatrists with a research bent and anyone else who wants to be provoked to do some thinking on the problems of language, language development, and the psychology of cognition. Louis A. GOTTSCHALK, M.D. Plans and the Structure of Behavior. By George A Miller, Eugene gALANTER, and Karl H. Pribram. Price, $5.00. Pp. 226. Henry Holt & Co., Inc., New York 17, 1960. This is an important book for psychiatrists and behavioral scientists, since it presents a clear, concise study of the application of cybernetics, information and computer theory to the problem of analyzing behavior. The authors have been actively engaged in behavioral research in different areas\p=m-\Millerin information and communication, Galanter in experimental psychology, and Pribram in neurophysiology. The book resulted from a series of discussions which they engaged in during a year they spent together at the Center for Advanced Study in the Behavioral Sciences, Palo Alto, Calif. Their original intent was to write a diary, as it were, of the development of their ideas and, fortunately, enough of this remains to make the book clear, easy to read, and interesting. It is also fortunate, however, that in the final writing a variety of studies comparing the "behavior" of computing machines with human "cognitive behavior" have been reviewed and summarized. The result is one of the best presentations of the present status of the brain-computer problem. The authors, however, do not discuss certain aspects of this problem, such as the difference between the brain and its vast number of parallel channels, but few operations, and the modern high-speed computer with its few channels and vast numbers of operations. This omission is consistent with their interest, since it would introduce the question of mechanisms rather than the problem of the structure of behavior as it is observed in everyday life in the clinic and in experiments on learning, conditioning, etc. Similarly, they do not discuss the qualitative differences between mechanisms of memory in the computer and those in the brain. In the former, a "memory"\p=m-\ i.e., stored information\p=m-\isidentified, metaphorically speaking, by an address, whereas no such mechanism is known in the brain (personal communication, Dr. Julian Bigelow). With few exceptions, however, the data, concepts, and theories presented are handled with elegant precision, as illustrated by the discussion of Sherrington's concepts of the "Reflex" and the "Synapse," Kurt Lewin's ideas of "tension states," and the numerous references to the work of Newell, Shaw, and Simon on computers and logic. There are, nevertheless, areas with

https://link.springer.com/content/pdf/10.1057%2Fjors.1968.86.pdf

Plans and the Structure of Behavior

This article is a review of experiments comparing the effectiveness of human tutoring, computer tutoring, and no tutoring. “No tutoring” refers to instruction that teaches the same content without tutoring. The computer tutoring systems were divided by their granularity of the user interface interaction into answer-based, step-based, and substep-based tutoring systems. Most intelligent tutoring systems have step-based or substep-based granularities of interaction, whereas most other tutoring systems (often called CAI, CBT, or CAL systems) have answer-based user interfaces. It is widely believed as the granularity of tutoring decreases, the effectiveness increases. In particular, when compared to No tutoring, the effect sizes of answer-based tutoring systems, intelligent tutoring systems, and adult human tutors are believed to be d = 0.3, 1.0, and 2.0 respectively. This review did not confirm these beliefs. Instead, it found that the effect size of human tutoring was much lower: d = 0.79. Moreover, the eff...

The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems

Thank you very much for reading working with emotional intelligence. As you may know, people have search hundreds times for their favorite novels like this working with emotional intelligence, but end up in infectious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they are facing with some infectious bugs inside their desktop computer. working with emotional intelligence is available in our digital library an online access to it is set as public so you can get it instantly. Our digital library hosts in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the working with emotional intelligence is universally compatible with any devices to read.

Working With Emotional Intelligence

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.

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AutoTutor: a tutor with dialogue in natural language.

The PREG model of question asking assumes that questions emerge when there is cognitive disequilibrium, as in the case of contradictions, obstacles, and anomalies. Participants read illustrated texts about everyday devices (e.g., a cylinder lock) and then were placed in cognitive disequilibrium through a breakdown scenario (e.g.,the key turns but the bolt does not move). The participants asked questions when given the breakdown scenario, and an eyetracker recorded their fixations. As was predicted, deep comprehenders asked better questions and fixated on device components that explained the malfunction. The eye fixations were examined before, during, and after the participants’ questions in order to trace the occurrence and timing of convergence on faults, causal reasoning, and other cognitive processes.

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Question asking and eye tracking during cognitive disequilibrium: comprehending illustrated texts on devices when the devices break down.

SUMMARY In human-computer interaction people often interpret the interaction with the computer as interactions with humans. The social agency theory suggests that social cues like the face and voice of the agent motivate this interpretation. In two off-line experiments in which comprehension scores and liking ratings were collected, we found that participants preferred natural agents with natural voices, as predicted by the social-cue hypothesis. Although female agents with male voices formed an exception, this was explained by a stereotype effect. These findings support the social-cue hypothesis and the social agency theory that human characteristics are applied in the perception of computational animated conversational agents. Copyright # 2005 John Wiley & Sons, Ltd.

Social Cues in Animated Conversational Agents

SUMMARY Conversational agents are becoming more widespread in computer technologies but there has been little research in how humans interact with them. Two eye tracking studies investigated how humans distribute eye gaze towards conversational agents in complex tutoring systems. In Study 1, participants interacted with the single-agent tutoring system AutoTutor. Fixation times showed that the agent received most attention throughout the interaction, even when display size was statistically controlled. In Study 2, participants interacted with iSTART. Fixations were on the relevant agents when these agents spoke. Both studies provided evidence that humans regard animated conversational agents as conversational partners in the communication process. Copyright# 2008 John Wiley & Sons, Ltd. Embodied conversational agents (ECAs) are animated characters that emulate human behaviour and communication. There has been a boom of these agents in computer environments that vary from conventional web systems to advanced virtual worlds. A fundamental question arises as to how humans interpret these agents. Are these ECAs distracting artefacts or human-like conversational partners? Answers to these questions require an in-depth analysis of the humans’ perceptions, attention and interactions with the agents. The present studies were designed to address these questions. Some studies have suggested that users interact with ECAs as they would with humans (Reeves & Nass, 1996), presumably because these computer-generated characters demonstrate many of the same multi-modal properties as do humans in face-to-face conversation (Cassell, Sullivan, Prevost, & Churchill, 2000). Studies in cognitive psychology, social psychology, artificial intelligence and education have investigated the effects of ECAs on user impressions, comprehension and learning gains (Atkinson, 2002; Baylor & Ryu, 2003; Graesser, Moreno, Marineau, Adcock, Olney, & Person, 2003). Some studies have shown that there are conditions in which users interacting with ECAs displayed on a computer monitor benefit from these interfaces more than from interfaces

Shulan Lu

Papers

AutoTutor: a tutor with dialogue in natural language.

Question asking and eye tracking during cognitive disequilibrium: comprehending illustrated texts on devices when the devices break down.

Social Cues in Animated Conversational Agents

Embodied conversational agents as conversational partners

An Empirical and Computational Investigation of Perceiving and Remembering Event Temporal Relations