BEHAVIORAL RESEARCH & TEACHING > Articles by: BRT_Admin
    
      
Author Archive: BRT_Admin
    
    
      
        
        
          
Anderson, D., Alonzo, J., & Tindal, G. (2010). easyCBM mathematics criterion related validity evidence: Washington state test (Technical Report No. 1010). Eugene, OR: Behavioral Research and Teaching, University of Oregon. TechRpt_1010
           
         
            
        
        
          
Ketterlin-Geller, L. R., Jung, E., Geller, J., & Yovanoff, P. (2008). Project DIVIDE instrument development (Technical Report No. 0810). Eugene, OR: Behavioral Research and Teaching, University of Oregon. TechRpt_0810
           
         
            
        
        
          
Wray, K. A., Alonzo, J., Tindal, G. (2014). Internal consistency of the easyCBM CCSS math measures grades K-8 (Technical Report No. 1405). Eugene, OR: Behavioral Research and Teaching, University of Oregon. This technical report documents findings from a study of the internal consistency and split‐half reliability of the easyCBM© CCSS Math measures, grades K-8.     TechRpt_1405
           
         
            
        
        
          
Alonzo, J., Park, B. J., & Tindal, G. (2013). An examination of the internal structures of the easyCBM CCSS reading measures (Technical Report No. 1304). Eugene, OR: Behavioral Research and Teaching, University of Oregon. This technical report presents the results of a confirmatory factor analysis of the internal structures of the easyCBM® CCSS reading assessments. These assessments, which include item prompts based onRead to Perform a Task, Informational Text, and Short Literary Text include a series of item prompts followed…
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Anderson, D., Alonzo, J., & Tindal, G. (2010). easyCBM mathematics criterion related validity evidence: Oregon state test (Technical Report No. 1011). Eugene, OR: Behavioral Research and Teaching, University of Oregon. TechRpt_1011
           
         
            
        
        
          
Wray, K. A., Alonzo, J., Tindal, G. (2014). Internal consistency of the easyCBM vocabulary measures grades 2-8 (Technical Report No. 1406). Eugene, OR: Behavioral Research and Teaching, University of Oregon. This technical report documents findings from a study of the internal consistency and split‐half reliability of the easyCBM© Vocabulary measures, grades 2-8.     TechRpt_1406
           
         
            
        
        
          
Alonzo, J., Park, B. J., Tindal, G. (2013). An examination of the internal structures of the gr. K-5 easyCBM CCSS reading measures: A construct validity study (Technical Report No. 1305). Eugene, OR: Behavioral Research and Teaching, University of Oregon. This technical report presents the results of a construct validity study in which we used confirmatory factor analysis to study the ways in which the different easyCBM® reading measures relate to one another. These assessments, which include item prompts based on…
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Anderson, D., Patarapichayatham, C., Nese, J. F. T. (2013). Basic concepts of structural equation modeling (Technical Report No. 1306). Eugene, OR: Behavioral Research and Teaching, University of Oregon. In this paper we introduce the basic concepts of structural equation modeling (SEM) for consumers of research. The purpose is to help provide readers a basis from which articles employing SEM can evaluated; but not necessarily to teach readers how to conduct an analysis.     TechRpt_1306
           
         
            
        
        
          
Sáez. L., Lai, C. F., Tindal, G. (2013). Learning progressions: Tools for assessment and instruction for all learners (Technical Report No. 1307). Eugene, OR: Behavioral Research and Teaching, University of Oregon. Conceptually, learning progressions hold promise for improving assessment and instruction by precisely outlining what students know and don’t know at particular stages of knowledge and skill development. Based upon a synthesis of the literature, a rationale for the use of learning progressions maps to clarify how learning progresses in English…
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Anderson, D. (2013). Hierarchical Linear Modeling (HLM): An introduction to key concepts within cross-sectional and growth modeling frameworks (Technical Report No. 1308). Eugene, OR: Behavioral Research and Teaching, University of Oregon. This manuscript provides an overview of hierarchical linear modeling (HLM), as part of a series of papers covering topics relevant to consumers of educational research. HLMis tremendously flexible, allowing researchers to specify relations across multiple “levels” of the educational system (e.g., students, classrooms, schools, etc.).  TechRpt_1308