Predicting student performance in the classroom is an important area of educational research owing to its potential for helping educators identify students who may have difficulty grasping the material in a course. The goal of this research was to develop a sensitive and specific pre-semester assessment for students enrolled in general chemistry for science majors that would identify students at risk for failing the course. The student pre-semester assessment (SPSA) predicted 40.8% of the students who went on to fail first-semester general chemistry. It was a better predictor of at-risk students than the Toledo exam (27.7%), SAT (16.8%), or predicted grade point index (PGI) (29.4%). The inclusion of demographic variables did little to increase the SPSA's predictive power, but math and chemistry background and age significantly increased the accuracy of predicting at-risk students when combined with either the SAT score or the PGI.

The electroencephalogram (EEG) is a physiologic measure of cerebral function that has been used by some to assess coma and prognosticate survival and global outcome after traumatic brain injury (TBI). Surface recordings of the brain's electrical activity reveal distinct patterns that indicate injury severity, depth of unconsciousness, and patient survival. The data produced with traditional qualitative studies, however, does not allow resolution and quantification of the wave frequency spectrum present in the brain. As a result, conventional EEG typically has only been used for gross and qualitative analyses and is not practical for use in long-term patient monitoring or as a sophisticated prognostic tool. One area of investigation that is working to address the limitations of conventional EEG has been the development and implementation of Fourier Transform (FT) EEG which resolves and quantifies frequency bands present in the brain. When FT analysis is applied to EEG, it provides concurrent and continuous monitoring, resolution, and quantification of all frequencies emitted. This review discusses the history and significance of conventional EEG and provides a review of how FT-EEG, commonly referred to as Quantitative EEG (QEEG), is being used in the clinical setting. The specific applications and significance of QEEG methods regarding treatment of patients with TBI are discussed in detail. The advantages, disadvantages, and future directions of QEEG in TBI are also discussed.

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