Southern Illinois University Carbondale

About: Southern Illinois University Carbondale is a education organization based out in Carbondale, Illinois, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 13570 authors who have published 24819 publications receiving 667385 citations. The organization is also known as: SIU Carbondale & SIUC.

Assessing Teachers' Beliefs about Their Science Teaching Context

Abstract: The primary purpose of this study was to develop and apply a method for assessing teach- ers' context beliefs about their science teaching environment. Interviews with 130 purposefully selected teachers resulted in 28 categories of environmental factors and/or people who were perceived to influence science teaching. These categories were used to develop items for the Context Beliefs about Teaching Sci- ence instrument and provided evidence for content validity. Construct validity was partially confirmed through factor analysis that resulted in 26 items and two subscales on the final instrument. Using Ford's Motivation Systems Theory and Bandura's Theory of Collective Efficacy, additional evidence for construct validity was found in the modest correlation of context beliefs with outcome expectancy beliefs and the low correlation with science teaching self-efficacy beliefs. The instrument was tested using 262 teachers participating in long-term science professional development programs. These teachers possessed fairly pos- itive context beliefs and, according to Ford's theory, should be capable of effective functioning in the class- room. It was concluded that the assessment of context beliefs would complement current science teacher self-efficacy measures, thereby allowing researchers to develop profiles of science teachers' personal agency belief patterns. It could also be used to determine the factors which predict particular personal agency belief patterns, and assess teachers' perceptions of the strengths and weaknesses of school science programs, and could be used in planning and monitoring professional development experiences for science teachers. © 2000 John Wiley & Sons, Inc. J Res Sci Teach 37: 275 - 292, 2000.

Selected Predictors of Responsible Environmental Behavior: An Analysis

Abstract: In this study, we examined the relative contribution of eight variables in predicting responsible environmental behavior. Scores on a validated behavior instrument served as the criterion. High and low behavior groups selected from 171 respondents were compared using members of midwestern Sierra Clubs and Elderhostel programs as subjects. Multilinear regression analyses were used to determine the performance of each predictor variable and to ascertain the most parsimonious set of variables that predicts environmental behavior. Seven of eight variables were found to be statistically significant. They were: (1) level of environmental sensitivity, (2) perceived knowledge of environmental action strategies, (3) perceived skill in using environmental action strategies, (4) psychological sex role classification, (5) individual locus of control, (6) group locus of control, and (7) attitude toward pollution. The one nonsignificant variable was (8) belief in technology. Stepwise regression showed that the...

Optimal Decision Fusion in Multiple Sensor Systems

Abstract: The problem of optimal data fusion in the sense of the Neyman-pearson (N-P) test in a centralized fusion center is considered. The fusion center receives data from various distributed sensors. Each sensor implements a N-P test individually and independently of the other sensors. Due to limitations in channel capacity, the sensors transmit their decision instead of raw data. In addition to their decisions, the sensors may transmit one or more bits of quality information. The optimal, in the N-P sense, decision scheme at the fusion center is derived and it is seen that an improvement in the performance of the system beyond that of the most reliable sensor is feasible, even without quality information, for a system of three or more sensors. If quality information bits are also available at the fusion center, the performance of the distributed decision scheme is comparable to that of the centralized N-P test. Several examples are provided and an algorithm for adjusting the threshold level at the fusion center is provided.

Parallel Analysis: a method for determining significant principal components

Abstract: Numerous ecological studies use Principal Compo- nents Analysis (PCA) for exploratory analysis and data reduc- tion. Determination of the number of components to retain is the most crucial problem confronting the researcher when using PCA. An incorrect choice may lead to the underextraction of components, but commonly results in overextraction. Of several methods proposed to determine the significance of principal components, Parallel Analysis (PA) has proven con- sistently accurate in determining the threshold for significant components, variable loadings, and analytical statistics when decomposing a correlation matrix. In this procedure, eigen- values from a data set prior to rotation are compared with those from a matrix of random values of the same dimensionality (p variables and n samples). PCA eigenvalues from the data greater than PA eigenvalues from the corresponding random data can be retained. All components with eigenvalues below this threshold value should be considered spurious. We illus- trate Parallel Analysis on an environmental data set. We reviewed all articles utilizing PCA or Factor Analysis

The Career Futures Inventory: A Measure of Career-Related Adaptability and Optimism:

Abstract: The purpose of this study was to provide initial results on the development and validation of the Career Futures Inventory (CFI), a new 25-item measure of positive career planning attitudes. Items were originated using the rational method. Results from an item analysis of scale homogeneity and exploratory factor analysis in a sample of 690 undergraduates from a large midwestern university revealed three subscales: Career Adaptability, Career Optimism, and Perceived Knowledge. Confirmatory factor analyses indicated that the three-factor model provided an excellent fit to the data. Additional analyses established high internal consistency, temporal stability, and construct validity through examination of correlates with dispositional optimism, Big Five personality characteristics, generalized problem solving, vocationally relevant self-efficacy, interests, and numerous career-relevant attitudes and outcomes. Implications for future research and counseling practice are discussed.