Human Factors is a discipline that studies the body of information about human capabilities and limitations for engineering design. Human Factors combines different Engineering areas and integrates them with human information into the engineering design. This applied and multidisciplinary nature of Human Factors in turn requires that education in Human Factors should also focus on the application of knowledge to design, and encourage hands-on exercise into the learning process. A new course "Design With a Human Factors Mind" was designed to demonstrate this concept. This course abandoned the traditional classroom lecture format, using labs, field trips and guest lectures instead to expose students with various Human Factors subjects. A survey study was conducted to assess the efficiency of this teaching style. Results showed that different teaching techniques have different effects on students' performance. This case study provides some preliminary results for different teaching styles and can help other educators to design effective teaching methods in Human Factors education.

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Intelligence analysts are faced with the demanding task of identifying patterns in large volumes of complex, textual sources and predicting possible outcomes based on perceived patterns. To address this need, the Advanced Neurophysiology for Intelligence Text Analysis (ANITA) system is being developed to provide a real-time analysis system using EEG to monitor analysts' processing of textual data during evidence gathering. Both conscious and unconscious 'interest' are identified by the neurophysiological sensors based on the analyst's mental model, as related to specific sentences, indicating relevance to the analysis goal. By monitoring the evidence gathering process through neurophysiological sensors and implementation of real-time strategies, more accurate and efficient extraction of evidence may be achieved. This paper outlines an experiment that focused on identifying distinct changes in EEG signals that can be used to decipher sentences of relevance versus those of irrelevance to a given proposition.