Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 2 |
Since 2006 (last 20 years) | 3 |
Descriptor
Accuracy | 3 |
Bayesian Statistics | 3 |
Experiments | 3 |
College Students | 2 |
Task Analysis | 2 |
Associative Learning | 1 |
Change | 1 |
Classification | 1 |
Cognitive Processes | 1 |
Computer Networks | 1 |
Computer Security | 1 |
More ▼ |
Author
Ashby, F. Gregory | 1 |
Cowan, Nelson | 1 |
Hardman, Kyle O. | 1 |
Koc, Levent | 1 |
Logie, Robert H. | 1 |
Rhodes, Stephen | 1 |
Vucovich, Lauren E. | 1 |
Publication Type
Journal Articles | 2 |
Reports - Research | 2 |
Dissertations/Theses -… | 1 |
Education Level
Higher Education | 2 |
Postsecondary Education | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Rhodes, Stephen; Cowan, Nelson; Hardman, Kyle O.; Logie, Robert H. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
Provided stimuli are highly distinct, the detection of changes between two briefly separated arrays appears to be achieved by an all-or-none process where either the relevant information is in working memory or observers guess. This observation suggests that it is possible to estimate the average number of items an observer was able to retain…
Descriptors: Cognitive Processes, Short Term Memory, Recall (Psychology), Change
Ashby, F. Gregory; Vucovich, Lauren E. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how…
Descriptors: Feedback (Response), Classification, Learning Processes, Associative Learning
Koc, Levent – ProQuest LLC, 2013
With increasing Internet connectivity and traffic volume, recent intrusion incidents have reemphasized the importance of network intrusion detection systems for combating increasingly sophisticated network attacks. Techniques such as pattern recognition and the data mining of network events are often used by intrusion detection systems to classify…
Descriptors: Bayesian Statistics, Computer Security, Computer Networks, Data Collection