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Intervention 2019, Vol. 44(2) 95–103  \n© Hammill Institute on Disabilities 2018 Article reuse guidelines: [sagepub.com/journals-permissions](sagepub.com/journals-permissions)[ ](sagepub.com/journals-permissions)[DOI: 10.1177/1534508418811593](DOI: 10.1177/1534508418811593)[ ](DOI: 10.1177/1534508418811593)[aei.sagepub.com](aei.sagepub.com)  \nTodd A. Glover, PhD 1, Linda A. Reddy, PhD 1, Alexander Kurz, PhD2,  \nand Stephen N. Elliott, PhD2  \nAbstract  \nThis article presents theoretical and empirical support for a data-driven instructional coaching approach and emerging evidence for the contributions of an online platform in operationalizing, assessing, and facilitating the implementation of key coaching actions for both research and practice. The contributions of an online platform in guiding the implementation and investigation of key coaching actions (i.e., modeling, facilitation of practice, and feedback) throughout a five-phase coaching sequence are presented. The article outlines initial research to demonstrate the utility of the online platform for advancing an understanding of how coaching actions predict teacher and student outcomes. This research suggests that there are predictive relationships between coaching actions and the fidelity of implementation of teacher interventions, reductionsin instructional gaps, and student achievement. The implications of this work for advancing coaching practices and future empirical investigations are described.  \nKeywords  \ninterventions, professional development, progress monitoring  \nFederal initiatives based on advances in educational science have emphasized the need to support teachers’ use of assessment data to inform the implementation of researchbased practices for improving student learning and behavior (e.g., Every Student Succeeds Act, 2015; Individuals with Disabilities Education Act, 2004) . Such initiatives have identified school-based, job-embedded coaching as a crucial mechanism for advancing educators’ application of data-driven decision making and implementation of research-based practices. However, despite the emerging popularity of coaching in schools, the empirical basis for coaching approaches and supports is limited, with few tools available for operationalizing, assessing, and facilitating a structured coaching process (e.g., Denton & Hasbrouck, 2009) .  \nAlthough nearly four decades have passed since Joyce and Showers (1981) defined coaching as a collaborative relationship “characterized by an observation and feedback cycle. . . for the purpose of integrating mastered skills and strategies into a curriculum, a set of instructional goals, a time span, and a personal teaching style”(p. 170), there is no consensus today on core components for coaching. As Denton and Hasbrouck (2009) and Kurz, Reddy, and Glover (2017) have noted, the operationalization of coaching has varied widely, as defined by various coaching foci (e.g., technical support, problem solving),  \nactions (e.g., observation, goal-setting, collaborative planning, modeling, practice, feedback), and desired outcomes (e.g., enhanced performance, environmental change, promotion of autonomy). Reflecting on research from a recent special journal issue on consultation and coaching, Erchul (2015) has recognized the importance of full operationalization and measurement of coaching as an independent variable with clearly defined components and the need to prioritize measurement of student outcomes rather than only teacher practices following coaching. Similarly, Kraft, Blazer, and Hogan (2018), in discussing the implications of a recent meta-analysis of school-based coaching, have highlighted the critical need for research evaluating specific coaching features, rather than only the efficacy of coaching programs as a whole.  \nAlthough a recent meta-analysis of 60 randomized controlled studies ","cbCaieLOJ5TqL15J","https://ap.wps.com/l/cbCaieLOJ5TqL15J","pdf",448498,"English","# Abstract\n## Data-driven coaching model and online platform\n## Operationalization, assessment, and five-phase coaching sequence\n## Predictive relationships and intervention outcomes\n## Research implications and future investigations","[{\"question\":\"What is the main purpose of the online platform discussed in the article?\",\"answer\":\"The platform provides structure and guidance to operationalize, facilitate, and measure key coaching components within a data-driven instructional coaching model.\"},{\"question\":\"Which coaching actions are emphasized in the five-phase coaching sequence?\",\"answer\":\"The article highlights modeling, facilitation of practice, and feedback as core actions supported by the platform across the coaching sequence.\"},{\"question\":\"What relationships does the research suggest between coaching actions and outcomes?\",\"answer\":\"Coaching actions are reported to predict fidelity of teacher intervention implementation, reductions in instructional gaps, and student achievement.\"}]","Use of an Online Platform to Facilitate and Investigate Data-Driven Instructional Coaching - Assessment for Effective Intervention 2019, Vol. 44(2) | PDF",1792074959,23]