We completed a comprehensive factor analysis of the full MMPI item pool by using recent advances in computational facilities. Nearly 20,000 MMPI protocols were collected for the analysis, however, we discarded invalid records and protocols with more than 50 missing items. Analyses were computed on a developmental sample of 5,506 subjects and a cross-validation sample of 5,632. Twenty-one replicated factors were found by using an orthogonal varimax solution. The rotated factors were submitted to several experts on MMPI for factor naming. The consensus obtained on the item factors suggests that this analysis provides an unambiguous picture of the major content dimensions in the MMPI item pool.

Our purpose in this research was to determine the extent to which computer-based instruction can replace conventional teaching in experimental psychology. In Experiment 1, students from an advanced cognition and thinking course participated in a simulation of Schallert's (1976) study of the role of context in prose comprehension and in a simulation of Carpenter and Just's (1975) study of sentence-picture verification latencies. Half of the students completed each experiment with the computer, and half were taught traditionally. Comprehension of the purpose and design of the experiments was tested immediately after the laboratory session and 1 month later during the final examination. There were no significant differences between the groups. Several students in Experiment 1 appeared to rush through the experiments and pay little attention to the explanations. In Experiment 2, we studied the effectiveness of computer-based instruction in experimental laboratory sections that did or did not require a follow-up assignment. The second variable was introduced so that some factor of seriousness or importance of the laboratory exercise could be measured. Results from this study indicated that, regardless of the perceived importance of a laboratory exercise, students who studied classic research in a traditional setting comprehended the purpose and design of the experiment better than did the students who worked on the computer. In addition, the students assigned to write up the experiment performed better than did the students who were given no follow-up assignment.

data analysis, data quantification, optimal scaling, catetorical data, nonmetric, Monte Carlo, euclidian,

No abstract

A human factors team was tasked with assessing best practices for developing a crewed space vehicle that is both reliable and robust. The team identified two broad dimensions of human factors are relevant to system design. Namely, the attributes of the product, and the processes used to develop the product. The "product" includes hardware, software, documentation, training systems, and procedures throughout all phases of the system life, including construction, testing, operation and maintenance. Three product attributes relevant to robustness are the extent to which task demands are within human capabilities, the capacity of the system to cope with unanticipated human actions, and the ability of the system to make use of unique human capabilities during non-routine situations. The "process" dimension of human factors relates to the activities that start in the early stages of design, and continue throughout the life of the system. There are, of course, no guarantees that a formal consideration of human factors throughout the design process will identify all the relevant human issues. In the absence of such a consideration, however, problems are virtually assured. Scope of our analysisHuman-system interactions occur in all phases of system development and operation, however the human factors team restricted its work to the elements that involve "direct contact" with spacecraft systems. Such interactions will encompass all phases of human activity during the design, manufacture, test, operation, and maintenance phases of the spacecraft lifespan. We therefore consider practices that accommodate and promote effective, safe, reliable, and robust human interaction with spacecraft systems. By restricting our scope to "direct contact" with the spacecraft, we by no means dismiss the importance of management and organizational factors in system performance [3].