1 / 13

Highly Capable Identification Matrix

Highly Capable Identification Matrix. This is a step-by-step description of how the identification matrix by Drs. Lohman and Renzulli is completed and the qualifying criteria for Northshore School District’s Highly Capable services. Matrix Design.

nia
Download Presentation

Highly Capable Identification Matrix

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Highly Capable Identification Matrix This is a step-by-step description of how the identification matrix by Drs. Lohman and Renzulli is completed and the qualifying criteria for Northshore School District’s Highly Capable services.

  2. Matrix Design • The matrix is designed to give equal weight to academic achievement and cognitive ability. “The best prediction of subsequent success in schools...is (an) appropriate combination of the two.” • This system is “well grounded in research on talent development.” (Lohman, D. & Renzulli, J. (2007). A simple procedure for combining ability test scores, achievement test scores, and teacher ratings to identify academically talented children.)

  3. Reasons for Using the Matrix • Backed by the research of the co-author of the CogAT and one of the top researchers in the field of highly capable education. • Uses the same test measures we have traditionally used for identifying students in need of highly capable services.

  4. Statistical Definition of Highly Capable “Highly Capable” is generally recognized as two standard deviations from the norm, or the 97.7th (98th) percentile.

  5. Lohman-Renzulli Matrix Data Flow After students are assessed on the ITBS and CogAT, the assessments are scored, normed and assigned a point value.

  6. Lohman-Renzulli Matrix Data Flow To arrive at the verbal domain score, the ITBS reading points and CogAT verbal battery points are added together. Fictional student example:

  7. Lohman-Renzulli Matrix Data Flow To arrive at the math domain score, the CogAT quantitative and nonverbal points are added together and divided by two. This average is then added to the ITBS math points. Fictional student example:

  8. Qualifying Criteria for Placement in AAP Student profiles with the following three qualifiers indicate AAP placement: • Point value of “3” or above for allCogAT and ITBS scores • Point value of “5” or above for at least one CogAT score • Point value of “10” or above for at least one domain score

  9. Analysis of Data for Qualification • Point value of “3” or above for allCogAT and ITBS scores:

  10. Analysis of Data for Qualification • Point value of “5” or above for at least one CogATscore:

  11. Analysis of Data for Qualification • Point value of “10” or above for at least one domain score:

  12. Lohman-Renzulli Matrix Data Flow Our fictional student qualifies for AAP based on the three qualifying criteria.

More Related