scholarly journals IMPROVING LEARNING DESIGN AND EDUCATION OUTCOMES THROUGH COGNITIVE PSYCHOLOGY: THE EFFECTS OF CONTROL OPPORTUNITIES ON INFORMATION PROCESSING AND MENTAL FATIGUE

2022 ◽  
Author(s):  
Michalis Varkas
2004 ◽  
Vol 34 (7) ◽  
pp. 1151-1155 ◽  
Author(s):  
EILEEN JOYCE ◽  
VYV HUDDY

Cognitive psychology became an important discipline in schizophrenia research when information processing deficits were implicated as the basis from which psychotic symptoms emerged (Broen & Storms, 1967; Hemsley, 1977; Frith, 1979). The study of cognition as an independent construct began in earnest when the detection of brain morphological abnormalities on computed tomography (CT) in patients with schizophrenia (Johnstone et al. 1976; Weinberger et al. 1979) prompted the search for behavioural correlates. It became apparent that impairments typical of damage to frontal or medial temporal lobes could be seen in patients with schizophrenia, irrespective of symptom type or severity (Goldberg et al. 1988; McKenna et al. 1990). Since then a number of findings have been replicated sufficiently to make certain conclusions about the nature and extent of cognitive dysfunction in this disorder.


2002 ◽  
Vol 6 (2) ◽  
pp. 153-165 ◽  
Author(s):  
Diego Fernandez-Duque ◽  
Mark L. Johnson

Scientific concepts are defined by metaphors. These metaphors determine what attention is and what count as adequate explanations of the phenomenon. The authors analyze these metaphors within 3 types of attention theories: (a) “cause” theories, in which attention is presumed to modulate information processing (e.g., attention as a spotlight; attention as a limited resource); (b) “effect” theories, in which attention is considered to be a by-product of information processing (e.g., the competition metaphor); and (c) hybrid theories that combine cause and effect aspects (e.g., biased-competition models). The present analysis reveals the crucial role of metaphors in cognitive psychology, neuroscience, and the efforts of scientists to find a resolution to the classic problem of cause versus effect interpretations.


2021 ◽  
Vol 11 (6) ◽  
pp. 661-667
Author(s):  
Wensheng Deng

The author of the thesis has focused on the mistranslations pointed out in a thesis, entitled with A Study of Howard Goldblatt’s “Mistranslation”, specifically on “seven sisters”. The paper has discussed and defended it from four dimensions. First, semantically speaking, it is spiritual similarity instead of formal one to the original, for it has conveyed the connotative and associative meanings hidden in the original. Second, based on cognitive translation studies, it has embodied the cognitive experience as what the original has done. Third, from cognitive psychology, it is the best representation which language central nerve stimulates the translator to select and match with the original in information processing and communication. Finally, functionally speaking, it is more equivalent to the original than other translations. Therefore, the author holds that “seven sisters” translated by Howard Goldblatt is no mistranslation of “六(liù)个(gè)姐(jiě)姐(jiě)”.


1989 ◽  
Vol 28 (04) ◽  
pp. 324-326
Author(s):  
S. Walsh

Abstract:An information processing model is used to describe the learning process. The implications of some of these cognitive concepts are examined in the context of computer-assisted instruction.


Author(s):  
Zhongxia Chen ◽  
Xiting Wang ◽  
Xing Xie ◽  
Tong Wu ◽  
Guoqing Bu ◽  
...  

Despite widespread adoption, recommender systems remain mostly black boxes. Recently, providing explanations about why items are recommended has attracted increasing attention due to its capability to enhance user trust and satisfaction. In this paper, we propose a co-attentive multi-task learning model for explainable recommendation. Our model improves both prediction accuracy and explainability of recommendation by fully exploiting the correlations between the recommendation task and the explanation task. In particular, we design an encoder-selector-decoder architecture inspired by human's information-processing model in cognitive psychology. We also propose a hierarchical co-attentive selector to effectively model the cross knowledge transferred for both tasks. Our model not only enhances prediction accuracy of the recommendation task, but also generates linguistic explanations that are fluent, useful, and highly personalized. Experiments on three public datasets demonstrate the effectiveness of our model.


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