Differences in Student Outcomes between Block, Semester, and Trimester Schedules.
TL;DRAbstract
Despite the popularity of schedule modifications as a cost-effective reform to improve student outcomes, little empirical research on the consequences of alternative schedules has been conducted. The literature has been dominated by anecdotal reports. Even when empirical evidence is examined, causal comparisons of school outcomes between schedules must be interpreted with caution, due to the number of confounding variables. A review of the literature shows positive and negative outcomes that depend on how teachers make use of schedule changes. The study described in this report compared the outcomes of achievement attained by high school students educated in block, semester, and trimester schedules in 1 urban district during 4 years. The study examined student annual grade-point averages, scores on the Stanford Achievement Test 9, credits attempted and earned, and absentee rates. Descriptive and inferential statistics were utilized. Analysis of covariance was the primary tool to test f
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Despite the popularity of schedule modifications as a cost-effective reform to improve student outcomes, little empirical research on the consequences of alternative schedules has been conducted. The literature has been dominated by anecdotal reports. Even when empirical evidence is examined, causal comparisons of school outcomes between schedules must be interpreted with caution, due to the number of confounding variables. A review of the literature shows positive and negative outcomes that depend on how teachers make use of schedule changes. The study described in this report compared the outcomes of achievement attained by high school students educated in block, semester, and trimester schedules in 1 urban district during 4 years. The study examined student annual grade-point averages, scores on the Stanford Achievement Test 9, credits attempted and earned, and absentee rates. Descriptive and inferential statistics were utilized. Analysis of covariance was the primary tool to test f
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