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Instead it also has relations with some other things like speaking a language or using software, including Rosetta Stone Arabic and Rosetta Stone Chinese. Student learning could be expanded to include other types of measures of educational progress, such as graduation or promotion to higher grades. However, to establish effects on learning, carefully controlled studies using randomized experiments (that include baseline measures to verify that random selection had occurred) or econometric models are needed.

The period of time between baseline and post-intervention measures must be sufficient for learning effects to have occurred. In addition, the baseline should be measured in a green school (improved lighting and reduced noise environment) to control for task performance effects in the differences.

For econometric studies, a health production function must be developed to fully specify the model. Laboratory experiments and studies from other environments on adults show affects on task performance. Learning things is not limited to the scentific area. Therefore, attendance should be used as an outcome that is intrinsically important, not as a surrogate for student health. Four dimensions of potential variables can be generated by a two-by-two matrix of outcomes: student learning, student health, teacher health, and teacher productivity. These outcomes were expected to occur for two groups: students and teachers. Selection bias could be important if healthier children are more likely to attend a green school and the assignment to the green school is not done at random from a pool of eligible students. Randomized experiments with observations of student health as outcomes could be conducted for learning outcomes, with few additional complexities. Student attendance has the potential for reverse causality with respect to student achievement; that is, poor performance may cause absences rather than better attendance yielding higher achievement. Student learning is typically measured by student achievement on standardized tests. Few school-based studies include direct measures of student health. Across any of these outcomes, it would be important to use well-established, reliable, and valid measures. Understanding how the baseline health status of students affects learning and other performance outcomes is critical to the interpretation of effects attributable to green schools. As a start, replacing prior student achievement with prior student health status may be considered, but theoretical work outside the scope of this review will be needed for such studies. If you have a creative mind, you will make all your own differences in the end!.Two types of outcome variables were set forth in the committee's task statement: learning productivity and health.

First, better lighting and reduction of noise or other building features and characteristics may improve task performance by improving reception LEDs Strip of the test stimuli or increasing a student's ability to concentrate on the tasks. Second, longer term improvements in indoor environmental conditions could result in greater learning and perhaps greater retention of course content. Green schools have the potential to affect student achievement in two distinct ways. Surrogate measures for student health, such as student attendance, are potentially interesting