Feedback through critical indicators of student performance: contributing to the assessment of high school education

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Feedback through critical indicators of student
performancecontributing to the assessment of
high school education

• David González-Barreto, PhD
• Antonio González-Quevedo, PhD
• Sonia Bartolomei-Suárez, PhD
• University of Puerto Rico Mayagüez
• http//oiip.uprm.edu

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Outline

• Summary
• Background
• Introduction and Justification
• Presentation of the Model
• Benefits of the Model
• Description and Components of the Project
• Evaluation of Two High Schools using a Subgroup
  of Critical Indicators
• Conclusions
• Acknowledgements
• Bibliography

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Summary

• Data kept at the Office of Institutional Research
  and Planning
• Students performance in their high schools
• Students performance at the university level
• Model of feedback mechanism to high schools
• Critical indicators
• High school GPA
• Ratio between students applying and students
  admitted
• Retention rates
• Graduation rates
• Grades obtained in general education courses at
  the university (e.g., Mathematics, English and
  Spanish)
• Expected outcomes for the university and the high
  schools

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Background

• Office of Institutional Research and Planning
  (OIRP) at the University of Puerto Rico at
  Mayagüez (UPRM)
• Limitation variables not studied (1, 2)
• High schools ranking
• Quality of high schools
• Pre-college preparation
• Recruitment programs
• Admission policy
• Financial assistance
• Academic intervention programs
• Previous work (3)

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Introduction and Justification

• Information available in our data warehouse
• High school grade point average
• Scores in College Entrance Examination Board
  (CEEB) tests (aptitude in Math, Spanish and
  English, and achievement in the same areas)
• Grade point average at the university level and
  at the specialty level
• Grades obtained in the college courses

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Supplier and Receptor Model of our Academic
Performance Model with Critical Indicators
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Potential Benefits of the Model

• Positive influence on high schools whose students
  attend our university
• Indicators will allow high school to assess their
  performance
• Collaboration between high schools and the
  university can be established to established
  better teaching techniques and share information
  on the preparation expected for the university
  courses from the perspective of the high schools
• The indicators can be developed based on
  geographic location of the high schools, gender
  and public or private system

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Marginal Distributions of High School GPAs and
First Year GPAs at UPRM
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Marginal Distributions of High School GPAs and
First Year GPAs at UPRM for two hypothetical high
schools
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Description of the Components of the Project

• Potential users of the model
• Parents of our applicants
• Department of Education of the Commonwealth of
  Puerto Rico
• Public and private school teachers
• High school principals and counselors
• Our Admissions Office
• Eventual availability of the model and the
  results in our site http//oiip.uprm.edu

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Evaluation of the two high schools using a
subgroup of the critical indicators

• Evaluation based on five critical indicators
• Retention rate (students staying for their second
  year of studies who entered our institution as
  first year students)
• Graduation rate (the US Department of Education
  definition)
• GPA in Math courses at the university
• GPA in Spanish courses at the university
• GPA in English courses at the university

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High school A with performance above the median
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High school B with performance below the median
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Conclusions

• This system will prove to be essential for the
  assessment of our public and private high schools
• Each school can use this system to assess the
  quality of their teaching as far a preparing the
  students for the university
• This system can be extended to assess the
  performance of universities that send us graduate
  students

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Acknowledgments

• Our former Institutional Researcher Irmannette
  Torres-Lugo, M.S.
• Our Institutional Researcher and Database
  Administrator, engineer Leo I. Vélez, M.S.
• Our Webmaster and Programmer Maira Rodríguez, B.S.

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Bibliography

• 1. Mo-Yin S Tam, Uday Sukhatme, The importance
  of high school quality in university admissions
  decisions, College and University Winter 2003,
  78(3), pp 3-8.
• 2. Gary S May, Daryl E Chubin,  A retrospective
  on undergraduate engineering success for
  underrepresented minority students, Journal of
  Engineering Education, January 2003, 92(1),
  pp 27-39.
• 3. Bartolomei-Suárez, Sonia M., González-Barreto,
  D. and González-Quevedo, A.A., Using an Expected
  Loss Function to Identify Best High Schools for
  Recruitment, Proceedings of the 10th
  International Conference on Engineering
  Education, Sept. 3-7, 2007, Coimbra, Portugal.