Catherine L Williams
Biographic Data
| ID | 4435041 |
|---|---|
| NAME | Catherine L Williams |
| GIVEN NAMES | Catherine L |
| FAMILY NAME | Williams |
| SIGNATURE | WILLIAMS C L |
| AFFILIATIONS | West Virginia University |
| ORCID | 0000-0002-4265-2467 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 1 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
A Comparison of Extinction Procedures for Responding Maintained by Random-Cycle Avoidance Schedules
Instruction consisting of a rule and set of examples and nonexamples reliably teaches concepts
Conceptual learning is discrimination between new examples and nonexamples and generalization to new examples. Conceptual learning can be demonstrated after practice with differential reinforcement of the correct response and is influenced by procedural variables during practice. However, less research has been done identifying an ideal structure for instruction (rules), which is likely a typical teaching format for learners with more advanced ve…
Using must‐have and can‐have features to improve conceptual learning
Concepts can be taught by presenting examples and nonexamples and giving the learner feedback on whether they accurately identify the examples, but it is not clear how to select examples and nonexamples. Specifically, the degree to which examples and nonexamples should differ is unknown. Six experiments were conducted to compare conceptual learning for four stimulus sets (three sets of arbitrary stimuli and one set of biological stimuli) across u…
Time-Out During Alternative Reinforcement Does Not Reduce Resurgence
ABA and ABC Renewal during Ongoing Omission Training
Using must‐have and can‐have features to improve conceptual learning
Concepts can be taught by presenting examples and nonexamples and giving the learner feedback on whether they accurately identify the examples, but it is not clear how to select examples and nonexamples. Specifically, the degree to which examples and nonexamples should differ is unknown. Six experiments were conducted to compare conceptual learning for four stimulus sets (three sets of arbitrary stimuli and one set of biological stimuli) across u…
Time-Out During Alternative Reinforcement Does Not Reduce Resurgence
ABA and ABC Renewal during Ongoing Omission Training
Instruction consisting of a rule and set of examples and nonexamples reliably teaches concepts
Conceptual learning is discrimination between new examples and nonexamples and generalization to new examples. Conceptual learning can be demonstrated after practice with differential reinforcement of the correct response and is influenced by procedural variables during practice. However, less research has been done identifying an ideal structure for instruction (rules), which is likely a typical teaching format for learners with more advanced ve…
Using must‐have and can‐have features to improve conceptual learning
Concepts can be taught by presenting examples and nonexamples and giving the learner feedback on whether they accurately identify the examples, but it is not clear how to select examples and nonexamples. Specifically, the degree to which examples and nonexamples should differ is unknown. Six experiments were conducted to compare conceptual learning for four stimulus sets (three sets of arbitrary stimuli and one set of biological stimuli) across u…
A Comparison of Extinction Procedures for Responding Maintained by Random-Cycle Avoidance Schedules
Behavioral and Psychological Studies (3 works) · Computer Science (3 works) · Psychology (3 works) · Artificial Intelligence (2 works) · Artificial Intelligence (2 works) · Autism Spectrum Disorder Research (2 works) · Cognitive psychology (2 works) · Concept learning (2 works) · Set (abstract data type) (2 works) · Advanced Text Analysis Techniques (1 work)