Got Data? Now What? draws from our work with professional learning communities, data teams, and grade-level, department, and administrative meetings. This book shares the lessons we’ve learned and presents practical, time-efficient methods for effectively completing tasks while developing productive collaborative relationships.
This book is based on the following five assumptions about group leadership.
1. Assessment and feedback drive group growth: Group development is an active ongoing process, not a result.
2. Group development and task accomplishment intertwine: Groups need purposeful structures and practical tools to learn with and from their data and one another.
3. When groups change the way they talk, they change the way they work: Thoughtful, systematic data-driven exploration of the results of instructional practice produces learning gains for both students and teachers.
4. Comfort with discomfort is necessary for collaborative learning: Willingness to navigate the emotional challenges of work with data is a key factor for group success.
5. Patterns become habits, habits become norms, and norms shape behavior: The real goal is to positively influence the culture of the organization. High-performing groups are vehicles for producing high-performing cultures, not an end in themselves.
We present a three-phase learning cycle—the collaborative learning cycle—which is a framework for using data to energize collaborative practices that improve student learning. Each chapter offers concepts, tools, tips, exercises, and a data story that illuminates the central focus. Each chapter also offers an Exercise Your Learning section with opportunities for application of the information in the chapter and an Extend Your Learning section with additional resources for further exploration. Visit go.solution-tree.com/teams to download the reproducibles and access the links in this book.
Chapter 1 presents the traits of high-performing data cultures and ways to purposefully develop and sustain learner-centered practices in schools. We offer an inventory for turning these standards of excellence into data for feedback and self-correction to produce ongoing improvements in group performance. The data story illustrates an elementary group applying data about its processes and interactions to refine and improve collaborative skills.
Chapter 2 presents a three-phase, inquiry-driven model for guiding productive group work with data—the collaborative learning cycle. Examples of purpose, process, potential, and pitfalls elaborate each phase of the model. We offer applications and tips for success, and we emphasize the importance of structuring group work and the liabilities that occur when scaffolds and skills are missing. The data story illustrates the collaborative learning cycle in action as a middle school team works with data from a benchmark expository writing assessment.
Chapter 3 presents ways to frame issues for investigation. These fundamental choices direct a group’s attention and data pursuits. We describe how expert groups use structured inquiry to identify gaps and successes and to clarify root causes before generating solutions. The data story illustrates a high school language arts team grappling with student performance gaps in reading comprehension of informational texts.
Chapter 4 presents fundamental definitions and descriptions of data types and uses with tips and cautions for choosing and using effective data displays. We offer approaches for data gathering including data that are presently available or archival and data that might need to be collected via constructed tools such as surveys or interviews. The data story illustrates an elementary math coach helping a vertical team consider possible causes for gaps in student problem-solving skills and identify formative assessment data to explore the issue.
Chapter 5 presents the group-member knowledge, skills, and dispositions that drive high performance. We describe stages of group development including predictable challenges, developmental indicators, and requirements for transitioning from one stage to the next. The data story illustrates a middle school team working with a group-development inventory to assess its growth as a team.
Chapter 6 presents distinctions between three essential modes of discourse in data-based conversations: (1) dialogue, (2) discussion, and (3) decision making. We describe common constraints to productive discourse and identify problematic and productive elements in six decision-making methods. The data story illustrates a middle school team applying effective discourse patterns within the collaborative learning cycle to improve a new behavior management program.
Chapter 7 presents approaches for turning decisions into productive plans for action driven by clear and measurable goals. We offer ten tips for avoiding common planning problems and addressing barriers to effectiveness. The data story illustrates a high school science team moving from making a decision to crafting an action plan for improving student inquiry skills across the science curriculum.
The Road to Learning
School improvement is not easy and quick. Data-driven change requires the commitment and perseverance of individual practitioners sustained by the focused efforts of the whole school community. Collaborative inquiry requires the vulnerability to learn in public, be patient with process, and suspend self-interest to serve a larger purpose. Groups that embrace these challenges, invest energy in their own development, and put data in the center of their conversations produce significant learning gains for themselves and their students.
School improvement is not easy and quick. Data-driven change requires the commitment and perseverance of individual practitioners sustained by the focused efforts of the whole school community.
We invite you to use this book as one vehicle on your road to learning. To accelerate your progress, use the exercises in each chapter individually or as a group study. Exploring the web resources will open further avenues for investigation. While at times the road ahead might be steep or bumpy, we believe the journey will both exhilarate and surprise you.
CHAPTER ONE
Developing Cultures of Collaborative Inquiry
In a rapidly changing world, the role of teaching and teachers has remained highly stable. Images from novels, old photographs, and movies portray instructors at the front and center of the classroom, delivering lessons to sometimes docile, sometimes unruly groups of students. When the backstage life of teachers is depicted, we see staffrooms filled with banter, gossip, and complaint. In these settings, social interaction with other adults is a way station offering respite from the arduous work of enlightening young minds.
Outdated expectations and structures cannot meet the learning needs of today’s students. Data bounce off these entrenched cultures of individualism, cultures that maintain isolated pockets of both excellence and mediocrity in the same organization with no mechanisms for sharing and transferring success (Newman, King, & Rigdon, 1997). A cohesive approach to school improvement requires new ways of thinking about and structuring teachers’ work. The emerging models of professional engagement rally all resources to produce greater cumulative effects on student achievement.
Some teachers still perceive working with colleagues outside the classroom as shifting away from their real work with students. However, in this changing climate, collaborative interaction is, in fact, as much a part of teachers’ work as is their time in the classroom with students.
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