Continuous Improvement: Improving Performance and Personalization through Powerful Data

January 16, 2017 by

dataThis is the twenty-fifth article in the series Implementing Competency Education in K-12 Systems: Insights from Local Leaders.

Timely, relevant data plays an important role in the transition to student-centered learning. In the process of the transition to competency education, school leadership, educators, and students will want, or even demand, an integrated information system to take advantage of the increased data on student learning. The drive toward improved student performance will increase the demand for data to guide greater personalization. Teachers who recognize the value of tracking student progress based on standards will not be content with the modifications allowed in most traditional student information systems or learning management platforms organized around semesters and courses. They will want to be able to monitor, support, and credential learning on standards regardless of if students are working below or beyond their grade levels. This requires organizing standards in a learning continuum beyond the course structure and displaying data in a way that gives a picture of the student profile—an entire student’s body of work and mastery, not just grading assignments and assessments within a course.

An integrated learning system to support competency-based environments starts with student profiles and standards-based learning continuums. Indicators of a student’s progress on each standard across content areas are key. Many vendors are offering standards-based or competency-based grading, but don’t provide the student-centered approach to managing progress along a learning continuum in all the significant domains. The student information systems that support traditional time-based schools are organized by courses or classes— not students—thus it is very difficult to generate a picture of how students are advancing across disciplines and over the years.

In early stages of the transition, most districts collect data on how students are progressing within the academic disciplines. As the competency-based system is further implemented, tracking of data on student learning often expands to include habits of learning, the type of learning experiences to ensure students are having adequate opportunities to apply learning in real-world settings or projects, and a broader set of domains. Bob Crumley, Superintendent of Chugach School District, explains, “It’s important to send a message that the state testing indicators aren’t the end all, even if that’s the focus of state legislators. It sends a powerful message when the state only tests reading, writing, and math but not social studies or employability skills. As a district, we had to put into place a system that created a meaningful and balanced way to talk about student progress and our effectiveness in all areas. We believe all content areas are equally important. We dedicate staff development and resources on all ten content areas. We monitor progress and celebrate growth in all ten areas.”

While stitching and patching together systems that require teachers to enter information into two systems can serve as a stop gap fix in the short run, this is absolutely unsustainable in the long run. New options for next generation learning platforms that are taking into consideration the needs of competency-based schools are beginning to emerge. Some districts are creating customized systems in partnership with vendors. Schools purchasing new products or working with small vendors may be frustrated with inadequate product support, and creating customized systems will raise issues of its own. It is best if a district takes the time, as Fulton County Schools is doing, to develop an enterprise architecture to guide decision making. The process of designing a full enterprise architecture requires districts to clarify—and, if need be, redefine—the core functions of district and school operations and the data needed to support it. The bottom line is that districts will make decisions based on local considerations and the urgency of their need to create transparency for teachers and students to track progress and help focus instructional support to ensure students are continuing to advance.

In addition to developing integrated management systems, districts will need to nurture the culture and capacity for data-driven learning. The student data for personalizing learning with a culture of continuous improvement can be deeply empowering to all the members of a school community. Students and parents can monitor progress in close to real-time. Teachers can more easily personalize education for students’ needs, monitor progress, and see where they need to improve their skills. Principals can identify early on when there are students struggling in a number of disciplines or transitioning from steady progress to a slower rate of learning.

Integrated information management systems and blended learning can power personalized models and help bring them to scale. Data-driven instruction will require that teachers expand their skills. As reported by iNACOL, teachers will need to build their technical skills, competencies, and capacity to use data, including the ability to:

  • Use qualitative and quantitative data to understand individual skills, gaps, strengths, weaknesses, interests, and aspirations of each student, and use that information to personalize learning experiences;
  • Use data from multiple sources to inform and adjust individual student instruction and groupings; and
  • Create ways to move ownership and analysis of data to students to promote independent learning. Continually evaluate technologies, tools, and instructional strategies to ensure their effectiveness.

As districts and schools begin the process of designing information systems, it is important to keep the decisions about operations and data-driven instruction in balance with the availability and capacity of the technology. For example, as teachers build their capacity to manage flexible personalized learning environments, they will be generating data on student learning through direct observation, formative assessments, and in dialogue with students. It is important to consider in advance how much assessment data teachers are going to need to track, analyze, and adjust for instruction in relation to student progress—and then look at the degree of ease in digitally managing this information. Districts have learned to stay focused on the most important items to track so teachers can concentrate on providing responsive instructional support.

In developing an integrated learning system, districts will also want to consider how it enhances student ownership of how, when, where, and what they are learning. In making design choices about the information systems, districts have an expanded understanding of end users and are thinking about how students, parents, teachers, PLCs or departments, principals, and district staff can use data to enhance learning and increase the agility of the system. For example, dashboards can be created that facilitate the use of data from different stakeholder perspectives, thereby empowering teachers and students and helping to inform conversations about instruction and daily operations.

As districts continue to deepen their implementation of competency education, it is anticipated that a deeper understanding of the system requirements and capabilities for a comprehensive integrated learning system will be developed. Such a system provides the platform for a school’s learning environment by enabling the management, delivery, and tracking of student-centered learning, and includes robust reporting and analytics capabilities. An effective and well-designed information system is an important tool for educators to input and analyze data about their students; to curate instructional materials; to track student mastery; to support students in documenting their work and progress toward mastery; and to communicate with students and their families about their progress. An integrated learning information system could also provide data to school and district staff on the use of instructional materials and their impact on student performance.

LESSONS LEARNED AND LEADERSHIP OPPORTUNITIES

When writing requests for proposals (RFPs) for an information management system, start with describing the desired functionality (the ability of the system to accomplish a goal) rather than a list of features (tools or features). An RFP that is a long shopping list of features can cause difficulty in implementation later on. When using functionality, district and school leaders will need to describe use cases that can help them think through how single or multiple products will help meet their goals. This is particularly important for competency-based districts, as there are new functions being developed such as monitoring the level of the depth of knowledge students are demonstrating.

Districts will want to begin to build their analytical capacity to better support principals in designing and using management and exception reports as well as rethinking performance metrics for the system, such as doing cost-benefit analyses. How much learning is happening per unit of time? What strategies are working to address the needs of students not yet proficient? What are the most effective approaches? What is the most cost-effective use of resources?

Be careful of expecting a one-solution approach and, alternatively, cobbling together systems that don’t integrate well. Begin with an enterprise architecture approach. New platforms and technology tools are emerging that will better help meet district need expectations for data and information management, as well as content and learning management.

For more information, explore this whole blog series:

Blog #1 Introducing Implementing Competency Education in K–12 Systems: Insights from Local Leaders

Blog #2 What Is Competency Education?

Blog #3 Investing in Shared Leadership

Blog #4 Constructing a Shared Journey of Inquiry, Shared Vision, and Shared Ownership

Blog #5 Engaging the Community

Blog #6 Creating the Shared Purpose

Blog #7 Investing in Student Agency

Blog #8 Clarifying the Overall Pedagogical Approach

Blog #9 Configuring the Instruction and Assessment Model

Blog #10 Constructing a Common Language of Learning

Blog #11 Creating a Common Language of Learning: A Continuum of Learning

Blog #12 Creating a Common Language of Learning: Rubrics and Calibration

Blog #13 Creating a Common Language of Learning: Habits of Learning

Blog #14 Policies for Personalization: Student Agency

Blog #15 Policies for Personalization: Levels, Pace, and Progress

Blog #16 Empowering Teachers

Blog #17 Preparing for Leadership Lifts

Blog #18 Rollout Strategies

Blog #19 Preparing Teachers for Personalized Classrooms

Blog #20 Leveling and Parent Conversations

Blog #21 Making Mid-Course Corrections and Refinements

Blog #22 Refining the Instructional Model and Enhancing the Instructional Cycle

Blog #23 Three Ways Districts Stumble in Implementation

Blog #24 Continuous Improvement and Innovation

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