2.8 Data Analysis
Candidates model and facilitate the effective use of digital tools and resources to systematically collect and analyze student achievement data, interpret results, communicate findings, and implement appropriate interventions to improve instructional practice and maximize student learning. (ISTE 2h)
Artifact: Data Overview Video
Reflection:
This Data Overview was an activity created for ITEC 7405: Data Analysis and School Improvement. This activity required me to locate and review demographic and student achievement data for my school and compare it to the state in order to create a story about the strengths and weaknesses of my school. I analyzed the GKIDS data for Hand in Hand Primary School over three years and compared the school with the state kindergarten scores.
The standard 2.8 ask candidates to model and facilitate the effective use of digital tools and resources to systematically collect and analyze student achievement data, interpret results, communicate findings, and implement appropriate interventions to improve instructional practice and maximize student learning. This artifact shows I was able to collect, analyze, and communicate the data findings of my school in order to improve instruction for student learning.
Drilling through my school’s data informed me in ways a mere presentation would never have done. I was a novice at data analysis and yet I was able to systematically drill through the data to discover our school’s strengths and weaknesses. This drilling required that I collect our school and the state’s GKIDS scores to determine how we compared to one another. After this comparison was complete I drilled down further, looking at our school’s GKIDS scores for three years in language arts and math. Within these two domains I targeted the standards that appeared to be the weakest areas. I then investigated the trends in our school’s population over this three year period and how each demographic group scored on those weak standards. This helped inform which groups of students needed more support and how we might change instruction for these students’ achievement.
This data analysis was a tremendous learning experience for me and I am convinced our school needs to implement data teams as soon as possible. This was one of the most challenging projects from the Instructional Technology program and, it helped me see why data teams are so essential. Data analysis should be done as a group or team project, because it contains a great deal of information and other viewpoints will help keep teachers from jumping to conclusions and making assumptions about the data.
If I were to do this project again it would most definitely be done in a group. Groups are needed to help identify the most critical weaknesses of the school and to brainstorm ways in which instruction can be changed to meet the students’ needs. I will present this data at our first professional learning of the new school year. This will have an impact on school improvement as we discuss the findings and begin a discussion on creating data teams. It will also have an impact on student achievement as we focus on those critical areas mentioned in the report.
This Data Overview was an activity created for ITEC 7405: Data Analysis and School Improvement. This activity required me to locate and review demographic and student achievement data for my school and compare it to the state in order to create a story about the strengths and weaknesses of my school. I analyzed the GKIDS data for Hand in Hand Primary School over three years and compared the school with the state kindergarten scores.
The standard 2.8 ask candidates to model and facilitate the effective use of digital tools and resources to systematically collect and analyze student achievement data, interpret results, communicate findings, and implement appropriate interventions to improve instructional practice and maximize student learning. This artifact shows I was able to collect, analyze, and communicate the data findings of my school in order to improve instruction for student learning.
Drilling through my school’s data informed me in ways a mere presentation would never have done. I was a novice at data analysis and yet I was able to systematically drill through the data to discover our school’s strengths and weaknesses. This drilling required that I collect our school and the state’s GKIDS scores to determine how we compared to one another. After this comparison was complete I drilled down further, looking at our school’s GKIDS scores for three years in language arts and math. Within these two domains I targeted the standards that appeared to be the weakest areas. I then investigated the trends in our school’s population over this three year period and how each demographic group scored on those weak standards. This helped inform which groups of students needed more support and how we might change instruction for these students’ achievement.
This data analysis was a tremendous learning experience for me and I am convinced our school needs to implement data teams as soon as possible. This was one of the most challenging projects from the Instructional Technology program and, it helped me see why data teams are so essential. Data analysis should be done as a group or team project, because it contains a great deal of information and other viewpoints will help keep teachers from jumping to conclusions and making assumptions about the data.
If I were to do this project again it would most definitely be done in a group. Groups are needed to help identify the most critical weaknesses of the school and to brainstorm ways in which instruction can be changed to meet the students’ needs. I will present this data at our first professional learning of the new school year. This will have an impact on school improvement as we discuss the findings and begin a discussion on creating data teams. It will also have an impact on student achievement as we focus on those critical areas mentioned in the report.