Theoretical and Applied Implications of Precisely Measuring Learning Rates

By Christopher H. Skinner. 2008

99 citations recorded by the source corpus.

Subfields: Developmental and Educational Psychology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/a00e8579dfb504fa2576c50e18168f30dc0f1741

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Developmental and Educational Psychology

1. M. Burns
2. Christopher H. Skinner
3. Brian C. Poncy
4. G. Lukito
5. Gary J. Duhon
6. Robin S. Codding
7. Scuddy F. Fontenelle
8. Benjamin G. Solomon

In Statistics and Probability

1. M. Burns
2. Brian C. Poncy
3. G. Lukito
4. Gary J. Duhon
5. Robin S. Codding
6. Scuddy F. Fontenelle
7. Christopher H. Skinner
8. Benjamin G. Solomon

Citations in the corpus

• Meta–Analysis of Mathematic Basic–Fact Fluency Interventions: A Component Analysis (2011, background): “Treatment dose is a critical variable when considering limited school resources (e.g., time, personnel), leading some researchers to suggest that decisions regarding which treatments are implemented should be made according to learning rates (Skinner, 2008).”
• An Analysis of Learning Rate and Curricular Scope: Caution When Choosing Academic Interventions Based on Aggregated Outcomes (2015, background): “One variable that is not always controlled in comparative effectiveness studies is cumulative instructional time (CIT), or the amount of time students spend with each intervention (Bramlett, Cates, Savina, & Lauinger, 2010; Skinner, 2008; Yaw et al., 2014).”
• Using Detect, Practice, and Repair (DPR) to Differentiate and Individualize Math Fact Instruction in a Class-Wide Setting (2013, background): “In addition, insufficient practice on difficult problems for the student may result from time spent on already mastered problems (Skinner 2008).”