Predicting End-Of-Course Test Using Teacher-Made Test

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Details

Predicting how students will perform on standardized tests is relevant to all educators. This work examines the relationship of students' performance on teacher-edited benchmark assessments administered to their performance on the state's end-of-course test. Teachers have information on student achievement within specific topics based on tests, quizzes, homework, and other assignments. However, the best way to use this information in predicting high-stakes testing is unknown. Providing teachers with guidance on how to use this information would be extremely valuable. This research determines how well the data from periodically-administered tests may predict scores on the state's end-of-course test. The school implemented an intervention process that involves frequent assessment of the skills being taught. Students were taught and re-taught, tested and re-tested until they mastered the curriculum. It is my hope that the research reported here will help decision-makers on education with evidence-based guidance on how to use student data to drive instructions.

Autorentext

Roland Damasco Dante was born in the Philippines and obtained his Bachelor s and Master s degree, both in his home country. He is now on his 20th year in the teaching profession. He completed his second Master on Natural Sciences at Louisiana State University, Baton Rouge Louisiana. He is currently the Math Department Head of his school.

Weitere Informationen

  • Allgemeine Informationen
    • Sprache Englisch
    • Herausgeber LAP LAMBERT Academic Publishing
    • Gewicht 113g
    • Untertitel Using Data To Drive Instructions
    • Autor Roland Dante
    • Titel Predicting End-Of-Course Test Using Teacher-Made Test
    • Veröffentlichung 10.09.2014
    • ISBN 3659580600
    • Format Kartonierter Einband
    • EAN 9783659580604
    • Jahr 2014
    • Größe H220mm x B150mm x T4mm
    • Anzahl Seiten 64
    • GTIN 09783659580604

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