Rule and attribute identification in children's attainment of disjunctive and conjunctive concepts.

1969 ◽  
Vol 80 (3, Pt.1) ◽  
pp. 498-504 ◽  
Author(s):  
Francis J. Di Vesta ◽  
Richard T. Walls
Keyword(s):  
Attribute Identification ◽  
Conjunctive Concepts

INDIVIDUAL DIFFERENCES AMONG REPRESSORS AND SENSITIZERS IN CONCEPTUAL SKILLS

1973 ◽  
Vol 1 (2) ◽  
pp. 144-152
Author(s):  
William H. Bergouist ◽  
John T. Lloyd ◽  
Sandra L. Johansson
Keyword(s):  
Individual Differences ◽  
Cognitive Flexibility ◽  
Concept Acquisition ◽  
Conceptual Skills ◽  
Disjunctive Concepts ◽  
Conjunctive Concepts ◽  
Better Than

Sensitizers were hypothesized to perform significantly better than repressors on eleven concept acquisition tasks. Differences between repression-sensitization (R-S) groups (n = 48), as measured by the Byrne R-S scale, were found to be significant on several of these tasks. As compared with repressors, sensitizers more rapidly acquired: (a) A disjunctive nonverbal concept, when a set for conjunctive concepts had to be broken (p < 0.05); and (b) Two verbal concepts (p < 0.05). Medium scoring subjects performed significantly better than repressors in acquiring: (a) Nonverbal disjunctive concepts (p < 0.05); and (b) Verbal concepts (p < 0.05). R-S results are discussed with reference to conceptual skills and “cognitive flexibility”.

scholarly journals TallyQA: Answering Complex Counting Questions

2019 ◽  
Vol 33 ◽  
pp. 8076-8084 ◽  
Author(s):  
Manoj Acharya ◽  
Kushal Kafle ◽  
Christopher Kanan
Keyword(s):  
High Resolution ◽  
Object Detection ◽  
Question Answering ◽  
Visual Question Answering ◽  
Attribute Identification ◽  
High Resolution Imagery

Most counting questions in visual question answering (VQA) datasets are simple and require no more than object detection. Here, we study algorithms for complex counting questions that involve relationships between objects, attribute identification, reasoning, and more. To do this, we created TallyQA, the world’s largest dataset for open-ended counting. We propose a new algorithm for counting that uses relation networks with region proposals. Our method lets relation networks be efficiently used with high-resolution imagery. It yields stateof-the-art results compared to baseline and recent systems on both TallyQA and the HowMany-QA benchmark.

Frequency analysis of attribute identification.

1976 ◽  
Vol 105 (3) ◽  
pp. 294-312 ◽  
Author(s):  
L. E. Bourne ◽  
B. R. Ekstrand ◽  
W. R. Lovallo ◽  
R. T. Kellogg ◽  
C. C. Hiew ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Attribute Identification

Inhibiting Effects of Attempts to Verbalize on Attainment and Use of Complex Conjunctive Concepts

1968 ◽  
Vol 22 (3) ◽  
pp. 785-793 ◽  
Author(s):  
Joseph G. Phelan
Keyword(s):  
College Students ◽  
Sorting Task ◽  
Card Sorting ◽  
Errorless Trial ◽  
Sat Scores ◽  
Card Sorting Task ◽  
Conjunctive Concepts

For 90 college students, matched for SAT scores, there was differentiation of ability to identify correctly complex conjunctive concepts in a card-sorting task, as demonstrated by ability to learn the concepts to an errorless trial and to apply the newly formed concepts to other materials. Some Ss were able to learn the concepts to an errorless trial and to apply each concept to new sorts but were then unable to verbalize correctly those rules they had just employed. The same Ss who had previously learned an equivalent principle for sorting in one situation, then having tried unsuccessfully to verbalize the concept which they had just employed, were unable to apply the same principle in a new, equivalent situation.

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