2. Data Collection Analysis
2.1 Coherent Instructional System
Analyze the LEA’s data (including sections 2.6) and answer the guiding questions to determine existing trends and patterns that support the identification of instructional needs. Complete a data-informed self-rating for each Georgia District Performance Standard (GDPS). See the Coherent Instructional System webinar for additional information and guidance.
Coherent Instruction Data
2.2 Effective Leadership
Analyze the LEA’s data (including sections 2.6) and answer the guiding questions to determine existing trends and patterns that support the identification of leadership needs. Complete a data-informed self-rating for each Georgia District Performance Standard (GDPS). See the Effective Leadership webinar for additional information and guidance.
2.3 Professional Capacity
Analyze the LEA’s data (including sections 2.6) and answer the guiding questions to determine existing trends and patterns that support the identification of professional capacity needs. Complete a data-informed self-rating for each Georgia District Performance Standard (GDPS). See the Professional Capacity webinar for additional information and guidance.
2.4 Family and Community Engagement
Analyze the LEA’s data (including sections 2.6) and answer the guiding questions to determine existing trends and patterns that support the identification of needs related to family and community engagement. Complete a data-informed self-rating for each Georgia District Performance Standard (GDPS). See the Family and Community Engagement webinar for additional information and guidance. Visit Georgia’s Family Connection Partnership’s KIDS COUNT for additional data.
2.5 Supportive Learning Environment
Analyze the LEA’s data (including sections 2.6) and answer the guiding questions to determine existing trends and patterns that support the identification of needs related to a supportive learning environment. Complete a data-informed self-rating for each Georgia District Performance Standard (GDPS). Student subgroups with a count of less than 15 are denoted by “TFS” (too few students). See the Supportive Learning Environment webinar for additional information and guidance.
2.6 Data Analysis Questions
Analyze the LEA’s data and answer the guiding questions to determine existing trends and patterns that support the identification of demographic and financial needs. Student subgroups with a count of less than 15 are denoted by “TFS” (too few students).
What perception data did you use? [examples: student perceptions about school climate issues (health survey, violence, prejudice, bullying, etc.); student/parent perceptions about the effectiveness of programs or interventions; student understanding of relationship of school to career or has an academic plan]
Georgia Cyber Academy (GCA) used the CLIP questions to create the Comprehensive Needs Assessment (CNA) survey to share with stakeholders. GCA held meetings with leadership, staff, and parents to receive feedback. GCA also worked with the PTSO, our Parent Advisory Council, human resources, and our Student Advisory Councils to obtain regular feedback. Weekly meetings are held with all areas of responsibility and concern including curriculum, academics, operations, financial, human resources, federal programs, compliance, special education, Parent, Faculty, and Student Advisories, Assessments, Counseling, and Instructional supports. GCA evaluated the information received and used that data to focus on the most prevalent needs.
What does the perception data tell you? (perception data can describe people’s knowledge, attitudes, beliefs, perceptions, competencies; perception data can also answer the question “What do people think they know, believe, or can do?")
The Comprehensive Needs Assessment perception data highlights several key areas for improvement: enhancing communication and collaboration across all administrative levels and departments, raising awareness of available services and materials for students, improving the alignment of physical materials, enhancing parent accountability, and increasing student engagement in live instruction.
What process data did you use? (examples: student participation in school activities, sports, clubs, arts; student participation in special programs such as peer mediation, counseling, skills conferences; parent/student participation in events such as college information meetings and parent workshops).
A variety of process data sources were utilized, including formal and informal classroom observations, the percentage of staff meeting TKES goals, student participation in clubs, as well as staff and student engagement in counseling services, and parent meeting attendance.
What does the process data tell you? (process data describes the way programs are conducted; provides evidence of participant involvement in programs; answers the question “What did you do for whom?”)
The process data shows a need for greater staff communication across all departments and levels. Additionally, GCA showed a need for increased student engagement with camera expectations in live class, increased accountability for parents in the learning process, and a need for social connections amongst all students at all levels of academic performance.
What achievement data did you use?
Various achievement data, including class attendance reports, assessment completion rates, MAP scores, Lexile scores, RIT scores, interim assessment scores, EOG/EOC scores, and ACCESS testing scores, was used to determine our needs. These data points provided insights into student engagement, performance, and growth, guiding our instructional strategies and support efforts.
What does your achievement data tell you?
The data shows a 7% improvement in ELA and math performance for students who have have remained at GCA for 3-years. There is a 9% increase in math and ELA performance for students that are at GCA for 5 years.
During the 2023-2024 school year, subgroups such as special education, ESOL, and MKV experienced a 4% rise in pass rates on ELA and math MAP and interim assessments compared to the previous year.
English Learners demonstrated a notable 15% increase in MAP scores between fall 2023 and spring 2024.
Preliminary data suggests a downward trend in milestone scores from 2022-2023 to 2023-2024, consistent with MAP performance and interim assessment scores
What demographic data did you use?
Students' academic achievement data (Pass/Fail of content, MAP, and Interim Assessments) and attendance by ethnicity and subgroups were analyzed to identify equity gaps, trends, and patterns.
What does the demographic data tell you?
Students in various subgroups (EL, MKV, 504, and SPED) perform below the grade-level average as measured by Interim Assessments (IA) and semester content pass rates. MKV students show the lowest performance across all subgroups and grade bands. EL students have a lower pass rate on IA3 compared to the grade level averages, with the exception of the primary grade level, where EL students performed above their peers. The truancy rate among McKinney-Vento students is ten times higher than any other subgroup. There is a persistent need to improve services for students in these subgroups through evidence-based interventions tailored to diverse learners.
Students whose parents are Limited English Proficient are performing above the grade-level average pass rates, except at the middle grades level. In addition, the gifted population is performing higher in every grade band as measured by IA3 and semester pass rates.