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Measures of learning speed (i.e., the amount of learning/cumulative time learner spends engaged in an intervention) are rarely included in research designed to evaluate and compare academic interventions. We build a case that includes analyses of learning speed metrics in academic intervention research can provide more useful information for prevention and remediation efforts, deter researchers from drawing misleading data‐based conclusions, and promote scientific parsimony. Research is reviewed where the same learning data is analyzed across different metrics (i.e., same amount of learning, different measurement scales) including learning per event, learning speed, and growth. Patterns are analyzed and examples are provided that demonstrate how altering metrics can influence relative effectiveness conclusions and applied recommendations when researchers compare two or more interventions, conduct component analysis or optimization studies, and apply meta‐analytic techniques. Opportunity costs for learners, educators, and learning scientists that may be caused by failure to measure learning speed are identified and analyzed. Our review and analyses support the conclusion that, in most instances, researchers can better inform prevention and remediation efforts by including precise measures of learning speed as dependent variables when they evaluate and compare interventions designed to enhance academic skills. Limitations and challenges associated with measuring learning speed are described and directions for future research are provided. Practitioner Points: Researchers who evaluate and compare academic interventions often measure learning, but rarely measure learning speed.Almost all academic deficits are not caused by failure to learn, but by not learning as rapidly as expected.When evaluating and comparing academic interventions, including measures of learning speed may allow for the identification and application of interventions that are superior for preventing and remedying academic deficits. [ABSTRACT FROM AUTHOR]

Teachers focused on prevention of academic problems should apply procedures that enhance learning speed, or learning as a function of the time that the learner spends engaged in the intervention(s). Although few researchers evaluate or compare academic interventions using precise measures of learning speed, several strategies for modifying interventions or instructional procedures have been developed that may enhance learning speed. Teachers who apply strategies that increase learning speed may allow students who receive remedial and special education services to incur fewer opportunity costs associated with time reallocation strategies and allow them to return to typical school activities earlier. More importantly, applying interventions that cause more rapid learning may prevent learning deficits, which may be the best way to minimize opportunity costs and enhance student success. [ABSTRACT FROM AUTHOR]

Through innovation in research and self-correction, it is inevitable that some practices will be replaced or be discredited for one reason or another. De-implementation of discredited and low-value practices is a necessary step for school psychologists' maintenance of evidence-based practices and to reduce unnecessary costs and risk. However, efforts to clarify de-implementation frameworks and strategies are ongoing. The scope of this paper follows McKay et al. in considering the potential for de-implementation strategies to be informed by applied behavior analysis and operant learning theory. We conceptualize low-value practice as sets of behaviors evoked by their context and maintained by their consequences, and thus de-implementation as behavior reduction. We discuss the need for future research given this perspective. [ABSTRACT FROM AUTHOR]

Brief experimental analysis (BEA) is a well-researched approach to conducting problem analysis, where potential interventions are pilot tested using a single-subject alternating treatment design. However, its brevity may lead to a high frequency of decision-making errors, particularly in situations where one tested condition is rarely optimal for students (i.e., the base rate). The current study explored the accuracy of a specific variant of BEA, skill versus performance deficit analysis (SPA), across different variations of the basic BEA design, score difference thresholds, and reading and math curriculum-based measurements (CBMs). Findings indicate that the ABAB design provides a reasonable control of such error rates when using reading CBM, whereas subtraction CBM required the use of an ABABAB design. Such error rates could not be controlled, regardless of design, when using multiplication CBM. Implications for best practice in the use of BEA are discussed. [ABSTRACT FROM AUTHOR]

Math proficiency is related to math calculation fluency. Explicit timing provides repeated practice for math fluency. It is enhanced through goal setting, graphic feedback, and rewards. Self-selected goals have potential to increase performance for math fluency. This study compared the effect of goal lines, and researcher goals versus self-selected goals. The authors compared three groups: (a) researcher-selected goals only, (b) researcher-selected goals with goal lines, and (c) self-selected goals with goal lines. First-grade students completed subtraction probes and colored in a bar graph with their performance. When participants met or exceeded their goals, participants received rewards twice per week. Results indicated that the researcher-selected goals with goal lines procedures with explicit timing had the greatest effect on subtraction fluency for first-grade students. The researcher-selected goals with goal lines and self-selected goals with goal lines groups outperformed the researcher-selected goals-only group. [ABSTRACT FROM PUBLISHER]

Observational bias can significantly affect results attained through observation. This study focused on 122 preservice teacher educators who conducted a structured observation, using momentary time sampling procedures with 10-second intervals, to measure student on-task and off-task behaviors. The experimental variable altered was the exceptionality label of the observed student to determine if the label would have a biasing effect. Labels used were oppositional defiant disorder, attention deficit hyperactivity disorder, and gifted/talented. Results suggest that an exceptionality label (i.e., oppositional defiant disorder) significantly affects observed behavior. Practical implications of the study are discussed. [ABSTRACT FROM AUTHOR]

Programming common stimuli is a strategy for generalizing behavior across settings (Stokes & Baer, 1977). The present study programmed common stimuli (i.e., goal statement and use of a pictorial icon) to generalize the effects of a reinforcement-based intervention for students identified as either developmentally delayed or emotionally disturbed. Results supported the effectiveness of the strategy in producing generalized responding from training to the generalization setting. The importance of methodological rigor in future research exploring generalization and the need to compare generalization strategies are discussed. [ABSTRACT FROM AUTHOR]