Children's Use of Observed Behavioral Frequency versus Behavioral Covariation in Ascribing Dispositions to Others

1984 ◽  
Vol 55 (6) ◽  
pp. 2094 ◽  
Author(s):  
Tamara J. Ferguson ◽  
Tjeert Olthof ◽  
Annemieke Luiten ◽  
Brendan Gail Rule
Keyword(s):  
Behavioral Frequency

scholarly journals A behavioral frequency discrimination paradigm for use in adult primates

1991 ◽  
Vol 23 (3) ◽  
pp. 357-369 ◽  
Author(s):  
Gregg H. Recanzone ◽  
William M. Jenkins ◽  
Gary T. Hradek ◽  
Michael M. Merzenich
Keyword(s):  
Frequency Discrimination ◽  
Behavioral Frequency

The Implementation of Modeling Technique on Social Skills of People With Mental Psychotic Disability

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Cep Yoga Firmansyah ◽  
Dorang Luhpuri ◽  
Rosyikin Sukanda
Keyword(s):  
Social Skills ◽  
Study Data ◽  
Face Validity ◽  
Mental Condition ◽  
Single Subject ◽  
Mental Disabilities ◽  
Persons With Disabilities ◽  
Behavioral Frequency ◽  
And Behavior ◽  
Behavioral Improvement

Social skills are not the capacity that can be easily mastered by persons with mental disabilities; they endeavor to master and/-or regain control of these capacities. Having 2 persons with mental disabilities as case studies, the objective of this study is to improve social skills of those persons with disabilities in more stable mental condition. This research uses a quantitative approach with a single subject experimental research design utilizing multiple baseline cross subject model; two persons with mental disabilities having similar characteristics and behavior became respondents of the study. Data analysis has been conducted by means of graph making, descriptive statistics, and visual inspection. Furthermore, the research uses face validity for its test validation and inter-rater reliability (kappa coefficient) in the reliability test. The study shows that 4 (four) aspects of social skills of the two respondents has been increasing since the intervention started. The behavioral improvement can be seen in the aspects of their communication, people-to-people interaction, ways to cooperate, and motivation for doing daily activities. The post-intervention’s (A2) measurement indicated that there was a decrease of behavioral frequency even though the number is still above the prior-intervention phase (A1). The decline was allegedly triggered by changes of activities of the two respondents.

scholarly journals Integration of Behavioral Frequency and Intention Information in Young Children's Trait Attributions

2012 ◽  
Vol 22 (1) ◽  
pp. 38-57 ◽  
Author(s):  
Janet J. Boseovski ◽  
Korinne Chiu ◽  
Stuart Marcovitch
Keyword(s):  
Behavioral Frequency

scholarly journals Differences In Consumers’ Attitude Towards Online Shops Based On Product Types And Consumer Characteristics And Their Influence On Repurchase Interests

2021 ◽  
Vol 21 (1) ◽  
pp. 78
Author(s):  
Ike Janita Dewi ◽  
Odilia Larasati Hertaswari
Keyword(s):  
Rapid Development ◽  
Behavioral Characteristics ◽  
Repurchase Intentions ◽  
Marketing Environment ◽  
Computer Mediated ◽  
Behavioral Frequency ◽  
Gender And Age ◽  
The Difference ◽  
New Research ◽  
Online Shops

The research responds to the new realities in marketing environment following the rapid development of internet and information technology. In accordance with Yadav and Pavlou’s (2014) new research directions in computer-mediated environments, this research examines the relevance of market segmentation in online distribution strategies. Specifically, this research aims at analyzing: (1) the difference in consumers’ attitudes towards online shops based on consumers’ demographic and behavioral characteristics, (2) the difference in consumers’ attitudes towards online shops depending on product type sold by the online shops, and (3) influence of attitude towards online shops on repurchase intentions. Data were collected using online and offline questionnaire to 200 respondents. Data analysis techniques include Analysis of Variance, multiple comparison, and simple linear regression. Results of the research show that demographic (gender and age) and behavioral (frequency of purchase) segmentation variables can generally explain differences in consumers’ attitude towards online shops. Differences in consumers’ attitudes are also shown in the cases of different product types (gadgets versus fashion) sold in the online shops. Lastly, consumers’ attitudes positively affect repurchase intention. Keywords— attitude; computer-mediated consumer behavior

Behavioral Frequency Judgments: An Accessibility-Diagnosticity Framework

1995 ◽  
Vol 22 (2) ◽  
pp. 212 ◽  
Author(s):  
Geeta Menon ◽  
Priya Raghubir ◽  
Norbert Schwarz
Keyword(s):  
Frequency Judgments ◽  
Behavioral Frequency
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