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Use the + symbol at the top of the column to post your question(s) for Section 4.

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Use the + symbol at the top of the column to post your question(s) for Section 4.

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Use the + symbol at the top of the column to post your question(s) for Section 3.

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Use the + symbol at the top of the column to post your question(s) for Section 3.

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Use the + symbol at the top of the column to post your question(s) for Section 2.

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Use the + symbol at the top of the column to post your question(s) for Section 2.

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Use the + symbol at the top of the column to post your question(s) for Section 1.

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Use the + symbol at the top of the column to post your question(s) for Section 1.

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Upcoming and On-Demand Training Opportunities

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Upcoming and On-Demand Training Opportunities

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For more information on upcoming training opportunities, including additional sessions in the 2023 Data Leadership Training Series, please visit www.caaspp.org/training/training-opportunities.

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Training workshops for administration of the CAASPP computer-based summative and interim assessments and the Digital Library.

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Please post technical issues or questions here. 

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Please post technical issues or questions here. 

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https://www.cde.ca.gov/ta/tg/ai/caregionalranmap.asp

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The County Office of Education (COE) RAN members represent a sub-committee of the Curriculum and Instruction Steering Committee (CISC) of the County Superintendents Association . The purpose of RAN is to develop a knowledge and understanding about California's assessment and accountability systems by facilitating communication between the California Department of Education (CDE) and COEs, which represent the schools, districts, and county offices in their region.

The decision about whom to appoint as an official COE RAN member is a regional decision, not determined by the CDE. For more information about RAN, contact your regional representative listed below.

Many regions have created local assessment networks that support assessment coordinators in their work. These networks allow coordinators a place to connect with other local coordinators, receive updates, discuss what is new in the assessment landscape, or share best practices. For more information about local assessment networks, see the list below of networks who have submitted their information to the CDE. If you have a local assessment network you would like added to this web page, please contact Deborah Baumgartner at dbaumgartner@cde.ca.gov.

Regional Contact Information

Region

Counties

Regional Assessment Network (RAN)
Contacts

2

Butte, Glenn, Lassen, Modoc, Plumas, Shasta, Siskiyou, Tehama, Trinity

3

Alpine, Colusa, El Dorado, Nevada,
Placer, Sacramento, Sierra, Sutter, Yolo, Yuba

4

Alameda, Contra Costa, Marin, Napa,
San Francisco, San Mateo, Solano

5

Monterey, San Benito, Santa Clara, Santa Cruz

6

Amador, Calaveras, San Joaquin, Stanislaus, Tuolumne

7

Fresno, Kings, Madera, Mariposa, Merced, Tulare

8

San Luis Obispo, Santa Barbara, Ventura, Kern

9

Imperial, Orange, San Diego

10

San Bernardino, Inyo, Riverside, Mono

Local Network Information

Region 1

Information coming soon.

Region 2

No local network. Information is shared at monthly superintendent meetings and county curriculummeetings.

Region 3

Capital Region Assessment Network (CRAN)
Meets last Friday of every month

To be added to the mailing list, contact Rachel Ibach by email at ribach@scoe.net

Region 4

Region 5

Region 6

Region 7

Fresno Assessment Network
Meets four to five times per year, usually right after RAN

To be added to the mailing list, contact Joe Valero by email at jvalero@fcoe.org

Region 8

State/Federal and Assessment Network
Meets quarterly
To be added to the mailing list, visit Kern County Superintentent of Schools Event Calendar

Region 9

Region 10

San Bernardino County Assessment Network (SBCAN)
Meets monthly
To be added to the mailing list, visit San Bernadino County Assessment Accountability Network Calendar (PDF)

Riverside County Assessment Network (RCAN)
Meets approximately every other month
To be added to the mailing list, visit Riverside County Office of Education Events Calendar

Region 11

Wednesdays at 1 p.m. for CAASPP & ELPAC Coordinators
Meets each Wednesday from 1 to 2 p.m. from February 1 to May 31, 2023
To be added to the mailing list, contact the assessments office by email at assessment@lacoe.edu

Questions: Assessment Development and Administration Division | 916-319-0803

Last Reviewed: Wednesday, March 22, 2023

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The County Office of Education (COE) RAN members represent a sub-committee of the Curriculum and Instruction Steering Committee (CISC) of the County Superintendents Association . The purpose of RAN is to develop a knowledge and understanding about California's assessment and accountability systems by facilitating communication between the California Department of Education (CDE) and COEs, which represent the schools, districts, and county offices in their region.

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You should have received an email with a link to access the meeting materials. You may also access the materials at https://www.caaspp-elpac.org/s/docs/Data-Leadership-Training-Series-Session-2-Materials-2025.zip

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You will receive an email with an evaluation survey and verification of attendance for each of the sessions you attend. If you do not receive the email by the end of the day tomorrow, email CalTrainings@WestEd.org for assistance.

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Thank you for attending this session. Please share your feedback with us by completing this evaluation form.

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2024-25 Data Leadership Training Series Evaluation Survey

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2024-25 Data Leadership Training Series Evaluation Survey.

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Educators often begin improving their schools by asking two questions: "What data should we be analyzing to help our school improve?" and "What data besides the state's standardized test results can we use?"

If you have asked these questions, the good news is that your school probably already has an abundance of powerful data on the effectiveness of all parts of the school-and much of this information does not come from standardized tests. The bad news is that if you are not using these data, your school or district probably has not yet organized the data for easy access and analysis.

What kinds of data are important for continuous school improvement, and how can you best organize the data for easy access and analysis?

Four Kinds of Data

You can answer almost any question about the effectiveness of a school by gathering, intersecting, and analyzing four kinds of data.

Demographic data describe the students, the school's staff, the school, and the surrounding community (see fig. 1). This information delineates the context in which the school operates and is crucial for understanding all other data. By dis-aggregating information by demographics (for example, by gender or ethnicity), you can understand what impact the education system is having on different groups of students.

Figure 1. Data You Can Use to Analyze Demographics

Numbers of teachers, administrators, paraprofessionals, and support staff

Years of experience (total number of years and by grade level)

Professional development opportunities

Extracurricular activity involvement/committees

Student learning data include a variety of measurements-norm-referenced tests, criterion-referenced tests, standards assessments, teacher-assigned grades, and authentic assessments-that show the impact of your education system on your students.

Perceptions data-gathered through questionnaires, interviews, and observations-help you understand what students, parents, teachers, and the community think about the learning environment. People act according to what they believe about different topics, so if you want to change a group's perceptions, you have to know about their beliefs. Student perceptions, for example, can tell you what motivates students to learn, and staff perceptions can indicate what kind of change is possible and necessary within the school.

School processes data include the school's programs, instructional strategies, assessment strategies, and classroom practices. Keeping track of these processes through careful documentation helps you build a continuum of learning for all students.

Data Snapshots

How many students are enrolled in your school this year? (demographic)

How did students at your school score on the state test? (student learning)

What are parent, student, and staff perceptions of the learning environment? (perceptions)

What special programs are operating in your school this year? (school processes)

How has enrollment in the school changed? (demographic)

Have student scores on standardized tests changed during the past several years? (student learning)

How have parent, student, and teacher perceptions of the learning environment changed? (perceptions)

What programs have operated in the school during the past five years? (school processes)

Do students who attend school every day get better grades? (demographic/student learning)

Do students with positive attitudes toward school do better academically, as measured by teacher-assigned grades? (perceptions/student learning)

Did students enrolled in interactive math programs this year perform better on standardized achievement tests than those who took traditional math courses? (student learning/school processes)

What strategies do 3rd grade teachers use to teach students with native languages different from their own? (demographic/school processes)

Is there a difference in how students enrolled in different programs perceive the learning environment? (perceptions/school processes)

Is there a gender difference in students' perceptions of the learning environment? (perceptions/demographic)

Intersecting Two Data Categories

Looking at the intersection of two kinds of data over time allows you to see trends developing-for example, standardized achievement test scores disaggregated by ethnicity over the past three years can help a school see whether the scores of a given ethnic group compared with those of others constitute a trend or just a fluctuation.

Do students of different ethnicities perceive the learning environment differently, and do they score differently on standardized achievement tests consistent with these perceptions? (demographic/perceptions/student learning)

Which program this year is making the biggest difference in achievement for at-risk students, and is one group of students responding more successfully to the program than are other students? (school processes/student learning/demographic)

Is there a difference in students' reports of what they like most about the school according to whether they participate in extracurricular activities? Do students who participate have higher grade-point averages than students who don't participate? (perceptions/student learning/school processes)

What instructional process did the previously non-English-speaking students enjoy most in their all-English classrooms this year? (perceptions/demographic/school processes)

Intersecting Three Data Categories

Looking at these data over a period of time will allow you to see trends, to understand the learning environment from the students' perspectives, and to know how to deliver instruction to get the best possible results for all students.

Are there differences in achievement scores for 8th grade girls and boys who report that they like school, by the type of program and grade level in which they are enrolled? (demographic/perceptions/school processes/student learning)

Intersecting Four Data Categories

Not until you intersect all data categories at the school level and over time will you be able to answer questions that allow you to predict whether the actions, processes, and programs that you are operating will meet the needs of all students. By crossing all four data categories, you are taking into account who your students are, how they prefer to learn, which subgroups of students are achieving, and with which processes students achieve.

What Does Using Data Look Like?

Sixty percent of 3rd graders at Archer Elementary School scored below the proficient level on the state's criterion-referenced reading test. To understand this achievement problem, the staff disaggregated the below-proficient 3rd grade scores (student learning) by gender and ethnicity (demographic). They discovered that the scores of boys and girls were similar but that one ethnic group had consistently lower scores. An examination of the data for the past three years revealed the same scenario.

Were there differences in the way these students were taught (school processes)? By disaggregating the student achievement scores by gender, ethnicity, and teacher, the staff noticed that each teacher's students received generally consistent scores over time, and certain teachers' students who were of this particular ethnicity had never scored at or above the proficient level in three years. At the same time, other teachers' students of this ethnicity scored above proficient. Looking at the student questionnaire results (perceptions) by ethnicity, the teachers were stunned to see that this ethnic group scored the lowest in response to such statements as "My teacher thinks I will be successful," "My teacher believes I can learn," "I am recognized for good work," "I know what I am supposed to be learning in my classes," and "Students are treated fairly at this school." Staff questionnaires showed that not all teachers agreed with the statement that "all students can learn."

After reviewing these data, the district undertook personnel changes at the school and helped the school set up new school procedures: diagnosing student learning at the beginning of the year in every grade level, clarifying what students should know and be able to do by the end of each year, aligning curriculum and instruction to district standards, and measuring progress toward learning goals throughout the year.

Taking a different approach, staff members at Canyon View High School wanted to use their data to understand why more than half of the school's 9th grade students failed the state reading proficiency examination. Working backward through the students' education experiences to determine the earliest occurrence of a characteristic common to all students who had not passed the exam, the teachers were shocked to see that most of these students had missed up to 30 or 40 days in a 180-day school year when they were 1st graders.

These 9th graders and the students in grades just below them were already getting remedial reading help, but the new data provided an opportunity to save younger students from the same fate. The district began more extensive screening of elementary and middle school students who were likely to suffer academically because of high absenteeism in early years. Teachers, counselors, and principals followed up by working closely with parents-setting up telephone trees, for example, and in some cases making home visits-to make sure that the children got to school.

Data Access

To be done well, data analysis requires the technical support of knowledgeable people and a database or data warehouse. Districts are just now beginning to buy data warehouses that facilitate the storage and analysis of a large number of data elements quickly, easily, accurately, and meaningfully. School districts or schools that do not have such a tool should consider buying a data warehouse; in fact, not having one should no longer be an option. When looking for a database or data warehouse, districts and schools should look for the following six features:

Accessibility at different levels. Stored at the district and possibly even regional or state levels, educators should be able to gain access to the data at schools and in classrooms.

Automatic graph builders. Being able to look over tables to check for accuracy is important, but the data analysis tool should be able to build graphs so that everyone can see the information in the same picture form.

Disaggregation on the fly. Anyone performing an analysis that is starting to show interesting data should be able to gain access to the next deeper levels quickly and easily.

Intuitive point-and-click or drop-and-drag technology. Everyone should be able to use the database without referring to a manual.

The ability to follow individual and group student achievement. Districts should be able to follow achievement from pre-K through grade 12.

Fast and easy creation of standard reports. Some reports-for school accountability or Title I, for example-have to be created every year and require much of the same information. Recreating the document should be possible with the click of a button.

Getting Started

Educators should start by organizing the data already on hand, such as student information and standardized test score results. Both are usually in electronic form, so importing the information into a data warehouse or data analysis tool is easy. Next, educators should think about how they can intersect that data to answer questions about program implementation. Gathering data for its own sake is counterproductive and often results in "analysis paralysis." The goal of using data to improve learning for all students should always be paramount.

The district should provide an expert to perform the major analyses for the district and each of its schools. Teachers should be able to spend their time studying the results instead of looking at the data or performing analyses themselves. They should be able to start the school year with historical data on each of their students and a full picture of what students already know and what they need to learn. And they should use ongoing measurements to make sure that all students are progressing and mastering the content.

When student learning measures are the only focus of a school's data analysis efforts, school personnel end up using their time figuring out how to look better on the student learning measures. This narrow approach has limited results. By contrast, looking at student achievement results in conjunction with the context of the school and the processes that create the results gives teachers and administrators important information about what they need to do to improve learning for all students.

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Schools can get a better picture of how to improve learning for all students by gathering, intersecting, and organizing different categories of data more effectively.

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Handout 2.1: Multiple Measures Scenarios

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Handout 2.1: Multiple Measures Scenarios

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All Resources | Expert Interview

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Dr. City suggests that teachers work collaboratively as they learn to use data efficiently in a cycle of instructional improvement. Dr. City offers examples of examining the data, developing questions, noting answers, and asking new questions until teachers reach an actionable step.

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Choose a protocol and read it on your own. Then add a comment that describes how you might use it in your local context.

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Choose a protocol and read it on your own. Then add a comment that describes how you might use it in your local context.

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Handout 2.5: Discussion Stations Protocol

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Handout 2.5: Discussion Stations Protocol

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Choose one scenario to read and respond to any of the following questions.

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Choose one scenario to read and respond to any of the following questions.

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How do the multiple measures in this scenario create a more nuanced picture of what students know and can do?

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How do the multiple measures in this scenario create a more nuanced picture of what students know and can do?

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How are the measures in the scenario relevant to the decisions at hand?

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How are the measures in the scenario relevant to the decisions at hand?

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How is this scenario influencing your thinking?

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How is this scenario influencing your thinking?

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1.     How do the multiple measures in this scenario create a more nuanced picture of what students know and can do? There is a strong correlation between interviews and results, however, is it feasible to expect teachers to have time for those interviews? Is there another method that would be useful? Google form perhaps?

2.     How are the measures in the scenario relevant to the decisions at hand? The comparison of the interim data to the summative data is so pertinent! How impactful this comparison could be.

3.     How is this scenario influencing your thinking? Inclusion of student input to the projects is vital to seeing the success of student work product in future offerings.

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I think I would have to see Discussion Stations in use to understand the logistics of who moves when, but I like the general idea and think it could prove useful.

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I think I would have to see Discussion Stations in use to understand the logistics of who moves when, but I like the general idea and think it could prove useful.