Data Driven Dialogue
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Data-Driven Dialogue
In the second edition of Data-Driven Dialogue: A Facilitator's Guide to Collaborative Inquiry, authors Bruce Wellman and Laura Lipton provide strategies that transform school culture through data-driven inquiry. By applying a three-phase model and a host of process tools to facilitate collaborative data analysis, K-12 school and district leaders can develop high-performing teams, promote effective problem solving, and orchestrate decisions that stay made. K-12 school leaders will: Develop facilitative skills in orchestrating data-driven dialogue Access the Collaborative Learning Cycle, an inquiry-driven model for structuring data-driven planning and problem solving Learn how to create visually vibrant data displays Explore tools for teams, along with information on application, variation, and extension Utilize an appendix that includes a glossary of technical terms, a rubric for group assessment and goal setting, additional strategy descriptions, examples of survey questions, and planning designs for meetings Contents: Preface Introduction Chapter 1: Change Is the Context--Why We Talk Chapter 2: Facilitative Patterns--Crafting the Container Chapter 3: A Model for Collaborative Inquiry Chapter 4: Getting Smart About Data Chapter 5: Tools for Teams Chapter 6: Leading System--Structures and Capacities for Continuous School Improvement Appendix References and Resources Index
Data-Driven Methods for Adaptive Spoken Dialogue Systems
Author: Oliver Lemon
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-10-20
Data driven methods have long been used in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) synthesis and have more recently been introduced for dialogue management, spoken language understanding, and Natural Language Generation. Machine learning is now present “end-to-end” in Spoken Dialogue Systems (SDS). However, these techniques require data collection and annotation campaigns, which can be time-consuming and expensive, as well as dataset expansion by simulation. In this book, we provide an overview of the current state of the field and of recent advances, with a specific focus on adaptivity.
The Data Coach's Guide to Improving Learning for All Students
Use data as an effective tool for school change and improvement! This resource helps data team facilitators move schools away from unproductive data practices and toward examining data for systematic and continuous improvement in instruction and learning. The book, which includes a CD-ROM with slides and reproducibles, illustrates how the authors' model has proven successful in: Narrowing achievement gaps in all content areas and grade levels Achieving strong, continuous gains in local and state assessments in mathematics, science, and reading Initiating powerful conversations about race/ethnicity, class, educational status, gender, and language differences Developing a vision for a high-performing, data-informed school culture