In this course, participants will learn data literacy and inquiry methods necessary for effective data utilization within a K12 school setting. They will demonstrate knowledge and skills through a series of interactive simulations that address a variety of data utilization purposes, such as identifying strengths and weaknesses for a group of students, monitoring progress toward an end-of-year goal for an individual student, and differentiating instruction.

The course includes 13 modules. Modules 1-4 address foundational knowledge essential for effective data utilization. Modules 5-13 are hands-on scenarios representing specific data use purposes in education. Statewide Longitudinal Data System (SLDS) data use standards have been identified and goals have been established for each part of each module, with the exception of a couple parts in introductory portions of Module 1.

Course content is structured a bit like a funnel. The broad and foundational modules at the beginning flow into more narrow and specific modules as participants progress through the curriculum. In module 1, participants will be introduced to common data types in educational settings, such as demographic, student learning, perception, school process, and behavior data. Assessment, evaluation, and research as methods of disciplined inquiry that require the use of data are briefly covered; most, perhaps all, data use purposes in educational settings could be classified as one or more of these inquiry methods. In module 2, the focus narrows into an overview of knowledge, skills, and professional behaviors as standards required to be an effective data user for assessment, evaluation, or research purposes; key standards are operationalized using the A+ Inquiry framework to synthesize the standards. In module 3, the focus narrows into specific school initiatives that require data utilization for various assessment and evaluation purposes; questions guiding data use processes aligned with these initiatives are also highlighted. In module 4, the focus narrows further into the use of student learning data by creating an assessment calendar representing different types of student learning data for various formative and summative purposes. Each remaining module represents a narrowed focus on the application of A+ Inquiry to navigate a specific data use scenario identified in the assessment calendar.

Learning Goals
  • Improve educator competence in using data
  • Improve educator actions with data
  • Improve educator attitudes toward data
SLDS Data Use Standards
  • B.3.D Prioritization: Prioritizes time to analyze and use data
  • K.1.A Question Formation: Knows which questions can be answered with data and how to identify the nature and extent of the data needed to answer questions
  • K.1.C Types of Data: Knows that data come in two main forms— QUANTITATIVE and QUALITATIVE—and that, within these forms, there are other categories
  • K.1.D Types of Measures: Knows various types and purposes of ASSESSMENTS and other MEASURES
  • K.1.E Data Metric: Knows that MEASURES can be broken down into data metrics, which are calculated for ANALYSIS and monitored for changes
  • K.1.F Data Sources: Knows different types of data sources and the benefits and limitations of using each
  • K.2.C Data Collection: Knows that DATA COLLECTION can be performed using different methods and at different points in time
  • K.2.D Data Context: Knows the circumstances and purposes for which data are collected
  • K.3.B Data Limitations: Knows that data have limitations and that these limitations affect the interpretation and usefulness of data
  • S.1.A Goals and Questions: Identifies BASELINE measure(s) and poses questions that can be answered with data
  • S.1.B Alignment: Aligns question(s), type of data needed, and measurement tools (e.g., ASSESSMENTS, surveys, etc.) with goals and objectives
  • S.1.D Data Meaning: Identifies different types of data and can explain specific DATA DEFINITIONS and how data are collected and formatted
  • S.2.A Data Discovery and Data Acquisition: Identifies and locates appropriate data sources and can access the data from various sources (e.g., classroom, school, district, state sources) for DATA ACQUISITION
  • S.2.B Critical Evaluation: Knows how to perform CRITICAL EVALUATION on data sources for reputability, quality (including validity and reliability), relevancy, and ability to address the identified need
  • S.3.A Facilitation: Collects data in ways that ensure VALID, RELIABLE data and that minimize BIAS
  • S.3.B Technology: Uses appropriate technologies to collect, access, and store data
  • S.3.C Multiple Measures: Uses MULTIPLE MEASURES (e.g., FORMATIVE, SUMMATIVE, GROWTH MEASURES, etc.), appropriately
  • S.4.C Aligned Analysis: Using appropriate technologies, conducts ANALYSIS suitable for the type of data collected, the VARIABLES identified, and the questions or hypotheses posed
  • S.5.C Patterns: Identifies patterns, TRENDS, and gaps in data and suggests reasons for their occurrence
  • S.6.B Explanation: Explains different data representations and distinguishing features (e.g., histograms, bar charts, contingency tables)
  • S.6.C Multiple Audiences: Communicates effectively about data, interprets FINDINGS, and explains progress toward goals to a variety of constituent groups (e.g., students, families, and colleagues)
  • S.7.A Strategies: Identifies appropriate strategies grounded in evidence to address the needs and goals identified during data ANALYSIS