2.7 Assessment
Candidates model and facilitate the effective use of diagnostic, formative, and summative assessments to measure student learning and technology literacy,
including the use of digital assessment tools and resources. (PSC 2.7/ISTE 2g)
Artifact: Data Inventory
Reflection:
The artifact used to demonstrate mastery for this standard is a data inventory for West Fannin Elementary School. The data inventory details various strands of data, collection dates, accessibility, current data use, and more effective ways to use the data. The data inventory was used to drill down the data into various levels.
There are several types of data. Aggregated, disaggregated, strand, item, and student work are all types of data. Aggregated data is summative data such as state assessments. This type of data should be reviewed annually. Examples of disaggregated data are items such as demographics, survey information, observations, and curriculum maps. This type of data should be evaluated two to four times per year. The next type of data is Benchmark or common assessment data. End of unit tests and common grade level assessments could be examples of this data. This data should be review either quarterly or at the end of every unit. Formative common assessments such as writing samples or journals should be review on a monthly basis. Finally, to be reviewed daily or weekly is classroom assessment for learning. These might be student self-assessments, performance tasks, or written responses. Reviewing this data can inform the data team if there is a student learning problem.
The data inventory is a way to break data down into categories to determine if there are problems or better uses for the data. The data inventory has data examples listed from aggregate data to formative classroom assessment. The first piece of data list is state test. The data example used is the CRCT. The CRCT is given to third thru fifth graders on all content areas. This data is reviewed by the school improvement team and grade level members to determine if there are academic deficiencies present in the school. A better use for this data would be to review all student data and determine all factors including external.
In order to determine current progress of students, West Fannin Elementary uses STAR Tests in reading a math. This is an online benchmark assessment which is given three times per year to all grade levels. The data is available to teachers and the academic coach. This data helps teachers determine where students currently are as far as standards met. The data shows students that need to be in a specialized intervention program or need to be in an excelled group.
West Fannin also used reading fluency and math fluency checks on a weekly basis. This data is reviewed by the classroom teacher to determine if progress has been made by the student. This data is currently used for student benchmarking; however, a better use for it would be to inform instruction.
When I began this class, I did not realize there were so many types of data. I was familiar with the examples provided, but I was not aware they had scientific names. I found this task to be very informative. It allowed me to evaluate all of the data methods we currently use at my school. Unfortunately, sometimes we aren’t used them in the most productive way. Many times more emphasis is put on aggregate data as opposed to student work or benchmarks. At first, I felt overwhelmed by this task; however, once I got started, I was able to decipher the data more easily.
It is necessary for all schools to educate their teachers on the various types of data. Instead of focusing on just summative data, more focus should be put on other forms on data. Overall, student work samples and benchmarks may be more informative to classroom instruction than a test given once a year. If teachers are taught to understand data, they will be more willing to use it instead of being intimidated by it.
including the use of digital assessment tools and resources. (PSC 2.7/ISTE 2g)
Artifact: Data Inventory
Reflection:
The artifact used to demonstrate mastery for this standard is a data inventory for West Fannin Elementary School. The data inventory details various strands of data, collection dates, accessibility, current data use, and more effective ways to use the data. The data inventory was used to drill down the data into various levels.
There are several types of data. Aggregated, disaggregated, strand, item, and student work are all types of data. Aggregated data is summative data such as state assessments. This type of data should be reviewed annually. Examples of disaggregated data are items such as demographics, survey information, observations, and curriculum maps. This type of data should be evaluated two to four times per year. The next type of data is Benchmark or common assessment data. End of unit tests and common grade level assessments could be examples of this data. This data should be review either quarterly or at the end of every unit. Formative common assessments such as writing samples or journals should be review on a monthly basis. Finally, to be reviewed daily or weekly is classroom assessment for learning. These might be student self-assessments, performance tasks, or written responses. Reviewing this data can inform the data team if there is a student learning problem.
The data inventory is a way to break data down into categories to determine if there are problems or better uses for the data. The data inventory has data examples listed from aggregate data to formative classroom assessment. The first piece of data list is state test. The data example used is the CRCT. The CRCT is given to third thru fifth graders on all content areas. This data is reviewed by the school improvement team and grade level members to determine if there are academic deficiencies present in the school. A better use for this data would be to review all student data and determine all factors including external.
In order to determine current progress of students, West Fannin Elementary uses STAR Tests in reading a math. This is an online benchmark assessment which is given three times per year to all grade levels. The data is available to teachers and the academic coach. This data helps teachers determine where students currently are as far as standards met. The data shows students that need to be in a specialized intervention program or need to be in an excelled group.
West Fannin also used reading fluency and math fluency checks on a weekly basis. This data is reviewed by the classroom teacher to determine if progress has been made by the student. This data is currently used for student benchmarking; however, a better use for it would be to inform instruction.
When I began this class, I did not realize there were so many types of data. I was familiar with the examples provided, but I was not aware they had scientific names. I found this task to be very informative. It allowed me to evaluate all of the data methods we currently use at my school. Unfortunately, sometimes we aren’t used them in the most productive way. Many times more emphasis is put on aggregate data as opposed to student work or benchmarks. At first, I felt overwhelmed by this task; however, once I got started, I was able to decipher the data more easily.
It is necessary for all schools to educate their teachers on the various types of data. Instead of focusing on just summative data, more focus should be put on other forms on data. Overall, student work samples and benchmarks may be more informative to classroom instruction than a test given once a year. If teachers are taught to understand data, they will be more willing to use it instead of being intimidated by it.