Data Driven Decision Making
Through this course, teachers will learn the importance of using data to plan appropriate instructional experiences for their students and to identify and analyze the measures of data to understand student learning needs. Participants are guided to develop the practice of gathering and analyzing data in a systematic and continuous manner. As part of this workshop, participants will review data-driven decision-making theory regarding multiple measures of data and they will analyze intersections of the data to answer questions about student achievement and how to improve student learning. Participants will learn to use tools to gather and analyze formative data to identify trends and gaps in learning. As a final product in this workshop participants will create an action plan to guide instructional change in their own classrooms and to lead to the improvement of student learning and achievement.
This is an introductory workshop for administrators, teachers, curriculum specialists, professional development specialists, or other school personnel. Participants are expected to have regular access to computers. In addition, participants should be proficient with using email, browsing the Internet, and navigating to computer files. Additionally, participants will need access to Microsoft Excel software.
This workshop will enable participants to:
understand the importance of using data to guide instructional planning,
become familiar with multiple measures of data,
analyze intersections of data to identify learning gaps as well as the root causes for the gaps,
use tools to identify, collect, and analyze data measures and intersections,
use curriculum-based assessments to monitor student progress,
use results of data analysis to make decisions about appropriate instructional strategies to differentiate instruction and address, students' individual learning needs, and
create an action plan for instructional improvement in their own classrooms.
Assessment and Course Requirements
This workshop is divided into six one-week sessions, each of which includes readings, an activity, and an online discussion among workshop participants. The time for completing each session is estimated to be five to six hours.
Participants will complete a Pareto Analysis Template, a Questioning the Data Template and a Classroom Teacher Academic Template as part of their course activities. As a final product, participants will complete an Action Plan Template to guide instructional change in response to data analysis with a goal of improving student achievement and learning.
As a final product, participants will develop an action plan to guide instructional change in response to data analysis to improve student achievement and learning
Participants will be evaluated on the frequency and quality of their discussion board participation. Participants are required to post a minimum of two substantial postings each session, including one that begins a new thread and one that responds to an existing thread. Postings that begin new threads will be reviewed based on their relevance, demonstrated understanding of course concepts, examples cited, and overall quality. Postings that respond to other participants will be evaluated on relevance, degree to which they extend the discussion, and tone.
Session One: Becoming a Data-driven Teacher
Data provides feedback and information about the total school program. Data-driven teachers use the results of a variety of data measures to make key decisions about their instructional programs. In this session, participants will read articles that describe how the use of data and careful analysis of data can make a difference to them and their students. In the activity section, they will view a video of a principal who describes how teachers in her school believe their use of data is important to student learning, and they will complete a Pareto Analysis to identify specific areas for improvement and to set SMART Goals. In the discussion for this session, participants will share ideas with their colleagues about the way they currently use data in their classrooms.
Session Two: Identifying and Using Multiple Measures of Data
In this session, participants will be introduced to other measures of data as identified by Dr. Victoria Bernhardt in her work on data-driven decision making. They will read descriptions of the four domains of data she identifies and discover how data in the other domains can help them understand more about students and their learning needs. In the activities, participants will view an interview with 8th grade teacher Jan Martin about what she learns from demographic data about her students. They will learn to use the Classroom Teacher Academic Template, a Microsoft Excel template, to gather data, including demographic and achievement data, and to track student progress. In addition, participants will complete a self-assessment to discover how much they've learned about multiple measures of data. In the discussion, they will share what they've learned about student data using the filters on the Classroom Academic Template.
Session Three: Using Data to Monitor Progress
In addition to annual school assessments, regular classroom curriculum-based assessments are an important part of the data picture. In this session, participants will learn the importance of curriculum based measurement to monitor the progress of their students, and they will learn how they can use these regular probes for progress monitoring. You will plan important regular assessments or probes and analyze the results and trends using the Classroom Teacher Academic Template. In the discussion, you and your colleagues will share ideas about using curriculum-based measurement and progress monitoring.
Session Four: Analyzing and Planning Around Data Intersections
In this session, participants will view intersections of data at two, three and four levels to help them predict the steps to take to address the learning needs of all students. In the activities section, participants will view a handout that illustrates the intersections of data, work with data on a diagram of their own, and begin to ask questions in order to gain insights about the data. In addition, they will complete a Questioning the Data Template in preparation for the development of their Action Plan.
Session Five: Using Data to Make Instructional Decisions
Now that participants have completed a Pareto analysis, created a SMART goal, and identified gaps in students' learning, they will next take a look at instructional interventions they can use in their classroom to help students improve their learning.. Participants will have the option of viewing a video of either a third grade math teacher or an 8th grade English language arts teacher who share ideas about data and classroom instruction. Then participants will review instructional strategies included in their School Improvement Plans and take a closer look at research-based instructional strategies. Participants will also complete an additional section of the Action Plan, and, in the discussion, share ideas with their colleagues about differentiating instruction.
Session Six: Putting Data into Action
In this session, participants will use the Classroom Academic Template to analyze scores they have tracked so far on weekly curriculum-based probes and look for students who need are not performing as expected. They will share ideas with their school teams or online colleagues to determine new strategies or interventions to reach these students. Participants will reflect on the work they have done in the course and prepare an Action Plan for their own classrooms to help their students reach the SMART goal they identified for their students. In the final discussion, participants and their colleagues will share ideas from their Action Plans.