Example of the Analysis for Individual Student Reports (ISR)

In this section, we utilized Monisha’s profile provided by the NJDOE on its NJPEP webpage. This example demonstrates how each student’s Individual Student’s Report can be analyzed to make data-driven recommendations for instructional interventions:

Subject

Cluster Skills

Score

Proficiency

Language Arts Literacy   210 Proficient
  Writing 11.0 out of 28 Just Proficient Mean = 10.1
  Reading 21.0 out of 38 Just Proficient Mean = 18.9
  Interpreting text 10.0 out of 14 Just Proficient Mean = 8.2
  Analyzing/Critiquing Text 11.0 out of 22 Just Proficient Mean = 10.7
Mathematics   190 Partially Proficient
  Number sense, operations, & properties 7.0 out of 12 Just Proficient Mean = 6.8  
  Spatial sense & geometry 4.0 out of 12 Just Proficient Mean = 4.3
  Data analysis, probability, & discrete mathematics 7.0 out of 12 Just Proficient Mean = 6.5
 

Patterns & Algebra

1.5 out of 12 Just Proficient Mean = 5.1
  Knowledge score 19.5 out of 48 Just Proficient Mean = 22.5
  Problem solving skills 11.0 out of 33 Just Proficient Mean = 14.8

 

As the above sample Individual Student Report highlights:

1. The student achieved proficiency in Language Arts Literacy and failed to achieve proficiency in mathematics. 

2. In Language Arts Literacy, the student’s "Proficient" score indicates that she met the state standards in Language Arts Literacy and does not necessarily require any interventions to address these grade level skills.  A further analysis indicates that this student’s scores under writing and analyzing/critiquing text are only slightly above the “Just Proficient Mean”, which may consequently require some additional attention. If we then utilized our checklist of expected reading and writing skills (CPI) in this grade, and collected data from class work, homework, as well as teacher-made and district wide tests we would be in a better position to narrow down these possible weaknesses for subsequent interventions.

3. Mathematics - In the Mathematics section, the student's overall score was "Partially Proficient", indicating that she failed to meet the state standards. However, because she scored above the “JPM” scores, possible strengths are noted in the Number Sense, Concepts, & Applications, as well as the Data Analysis Clusters. On the other hand, because she scored below the “JPM” in the content clusters of Spatial Sense & Geometry, as well as Patterns, Functions, & Algebra these represent possible weaknesses that need to be addressed. These possible weaknesses contributed to the student’s “Partially Proficient” math score and can be narrowed further by utilizing our checklist of expected math skills (CPI) in this grade, and collect data from class work, homework, as well as teacher-made and district wide tests. We would then be in a better position to develop and provide more focused interventions.

Based on the above analysis, and assuming other data for this student (e.g. class work, homework, cumulative record, etc.) are consistent, the interventions will have to provide the student with individual assistance in the identified weaknesses, perhaps utilizing the precursor skills identified in the CPIs and utilizing the State’s corresponding Framework activities. In addition,

1.   The teacher can identify all students in the class that have similar strengths and weaknesses to group students for teaching and learning activities.

  1. The school and district can utilize all assessments and student data to develop school/district wide, grade-level and subject matter profiles to identify collective strengths and weaknesses. Once developed, these profiles can lead to more systemic interventions in curriculum, staff development, and other teaching and learning activities.