The past two decades have seen a substantial increase in the availability of numerical data that individuals are faced with on a daily basis. In addition, research uncovering the multiple facets of statistical reasoning has become increasingly prominent. Both gender differences and the effect of experience or training have emerged as two key factors that influence performance in statistics. Surprisingly, though, the combined effects of these two variables have not been studied. This gap in understanding the joint effect of gender and experience on statistical reasoning is addressed in the present dissertation with six studies. In Study 1 (N = 201), participants with various levels of experience in statistics were asked to complete the Statistical Reasoning Assessment (SRA; Garfield, 2003). Although the performance of both genders improved with experience, the gender gap persisted across all experience levels. Multiple measures of individual differences were used in a confirmatory structural equation model. This model supported the idea that differences in statistical reasoning are not uniquely a matter of cognitive ability. In fact, gender was found to influence statistical reasoning directly, as well as indirectly through its influence on thinking dispositions. In Studies 2 (N = 67), 3 (N = 157), and 4 (N = 206), the role of stereotype threat was examined as a potential cause of the persisting gender gap in statistics, and value affirmation was tested as an intervention to overcome stereotype threat. Despite the fact that many women believed negative stereotypes about the ability of women in statistics, value affirmation had no significant impact on performance. To help explain this lack of effect, and in keeping with the results of the structural equation model suggesting a multi-pronged approach, efforts were turned towards a different (and potentially richer) cognitive factor. Specifically, mental representations were explored to help shed light on the root causes of those conceptual understanding differences in statistics. In Studies 5 and 6, gender differences in mental representations of statistical features were examined using a categorization paradigm. In Study 5 (N = 219), extending some of the key findings in Studies 1, 3 and 4, it was established that two courses in statistics are necessary to create a significant difference in the quality of mental representations of statistical concepts. More importantly, Study 6 (N = 208) demonstrated how constraining the task format particularly benefits women in that the quality of their reasoning significantly improved, where that of men was equal across tasks. Theoretical and practical implications of these findings are discussed.

Inductive reasoning (IR) requires efficient working memory (WM). Research shows that the prefrontal cortex (PFC) is involved during WM tasks and that PFC functioning declines with age. The ability to comprehend and update text-based information requires an intact PFC and efficient WM and IR. The current study presented a series of messages about the investigation of a warehouse fire to 48 young and 48 older adults. One message contained a piece of misinformation which another message corrected later. It was hypothesized that a memory cue to the misinformation with the correction statement should benefit older adults the most during the updating process. A text-based level and situation model level measured updating. The text-based level is only information from the text but is not necessarily verbatim. The situation model level is the overall meaning of the text, including inferences and assumptions. Results show that unlike young adults, older adults are not capable of recalling the text at the text-based level. However, older adults are capable of performing like young adults at the situation model level. This suggests that older adults are capable of updating causal information in text material as long as a memory cue to the misinformation is provided within the correction statement.

The increasing use of auditory graphs and sonifications in technology is leading to a wider variety of system users, which, in turn, suggests a need for research in how differences between individual listeners affect sound interpretation. As a first step in this arena, the current study investigates the question of whether or not cognitive abilities and musical experience predict frequency and tempo discrimination in individuals. Participants in the study were 30 undergraduate students from Georgia Institute of Technology and 20 adults from the Atlanta, Georgia community. In the cognitive ability session, participants completed the Operation Span (Ospan) task as a measure of working memory capacity and the Ravens Progressive Matrices task as a measure of spatial reasoning. In the auditory discrimination session, participants performed a tempo and a frequency discrimination task. Demographics on age, gender, handedness, years of playing a musical instrument, and years of formal musical training were also collected. A correlational analysis of all variables was performed. Paired-samples t-tests on the Weber fractions of the six threshold means were also performed to determine if there were any significant differences between the frequency thresholds and the tempo thresholds. Lastly, multiple hierarchical regressions were performed on each of the six dependent variables to identify significant predictors of frequency and tempo discrimination. The paired samples t-tests show a significant difference between 250 Hz and 840 Hz and between 250 Hz and 1600 Hz, a violation of Webers Law. However, this violation of Webers Law may be explained by the small sample size used in the study. The t-tests also show a significant difference between the means of 150 ms and 250 ms and between the means of 250 ms and 350 ms. The results of the regression analyses show that good performance on Ravens seems to predict lower thresholds at 1600 Hz. The results also show that good scores on Ospan appear to predict lower thresholds at 350 ms ICI. In addition to these significant predictors from the regression analyses, there are many significant correlations that provide further support that cognitive abilities are related to frequency and tempo discrimination.

The use of unproctored internet-based testing for employee selection is widespread. Although this mode of testing has advantages over onsite testing, researchers and practitioners continue to be concerned about potential malfeasance (e.g., cheating and response distortion) under high-stakes conditions. Therefore, the primary objective of the present study was to investigate potential malfeasance effects on the scores of an unproctored internet-based cognitive ability, and a personality test. This was accomplished by implementing a within-subjects design in which test takers first completed the tests as job applicants (high-stakes) or incumbents (low-stakes) then as research participants (low-stakes). The pattern of cognitive ability test score differences was more consonant with a psychometric practice effect than a malfeasance explanation. Thus, the results suggest that, if present, there was no evidence to indicate that wide- scale or systematic malfeasance unduly affected the test scores. This may have been due to the speeded nature of the test, which was used to preempt the potential for widespread cheating. Additionally, the unproctored personality administration resulted in similar mean shifts and similar proportions of test takers being suspected of distorting their responses as that reported in the extant literature for proctored tests. In their totality, these results suggest that an unproctored internet-based administration does not uniquely threaten personality measures in terms of elevated levels of response distortion compared to proctored measures.

The cognitive factors of spatial ability, human-computer interaction, problem solving ability, and geographic attitude have been recognized as relevant to teaching and learning GIS. The goal of this research was to examine these cognitive abilities in university students taking an introductory course in GIS; examine any changes in these abilities after completing the class; and examine the relationship between those abilities and the students’ grades in the class. It was hypothesized that students with higher cognitive ability scores would have higher grades than students with lower cognitive ability scores. Nine different self-report surveys were used to assess the students’ spatial, computer, problem solving, and geographic cognitive abilities. The surveys were administered at the beginning and end of the two academic semesters. Analysis of the students’ scores revealed a significant improvement on four of the nine cognitive ability surveys; one that measured computer experience and three that measured spatial ability. Bivariate correlations and multiple regression analyses were used to measure the relationship between the students’ scores on the cognitive ability surveys and the students’ grades. Students received grades on lecture exams, lab exercises, individual projects, and an overall grade. Only two of the bivariate correlations were statistically significant: the factors of geography attitude and learning style were significantly correlated with the students’ project grade. Multiple regression analysis also revealed a very weak relationship, explaining less than 20 percent of the variance between the scores on the cognitive ability surveys and the students’ lecture grade, lab grade, and overall grade. However, a much stronger relationship, explaining more than 45% of the variance, existed between the cognitive ability surveys and the students’ project grade. These findings suggest that cognitive processes utilized for traditional classroom learning to pass lecture exams are different than those utilized to learn the software skills necessary to complete a GIS project. Therefore, it was concluded that the cognitive ability scores are poor predictors of grades related to traditional classroom learning such as lecture exams; however, these scores are more useful as predictors of the grades on a GIS project.

Humans and chimpanzees differ in a number of phenotypic traits chief among them being a larger sized human brain and an increased propensity for cancer in humans. Apoptosis or programmed cell death plays a role during brain development and disease progression to cancer. Results from my study, based on gene expression analysis, suggest that the apoptotic function may be generally reduced in humans relative to chimpanzees. In this thesis, I test the hypothesis that the apoptotic function is generally reduced in humans relative to chimpanzees by gene expression and experimental data. The experimental data are consistent with the hypothesis and also suggest that the apoptotic function may be reduced in humans relative to chimpanzees and macaques, suggesting that the reduced apoptotic function may be an evolutionary derived condition within the human lineage. I also evaluate the role of this reduced function in humans during brain development and disease progression to cancer. In addition, I also correlate Insertion/Deletion sequence variation between humans and chimpanzees with differences in gene expression between the two species.

This study investigated the relationship between Emotional Intelligence (EI) and Satisfaction with Life (SWL) among community college students. Some researchers suggest a relationship exists between EI and important outcome variables (e.g., occupational success & satisfaction with life). However, other researchers suggest measures of EI may simply assess personality variables known to predict these variables. I used the Mayer, Salovey, and Caruso Emotional Intelligence Test (MSCEIT) to investigate how much additional variance in SWL, EI predicts after three personality variables (self-esteem,depression, and locus of control). A convenience sample of 200 Central Florida Community College Students completed the following instruments: 1) MSCEIT(Mayer, Salovey, and Caruso Emotional Intelligence Test, 2002) to assess EI. 2) RSES (Rosenberg Self-Esteem Scale, 1965) to assess self-esteem. 3) BDI-II (Beck Depression Inventory ll) Beck, Steer, and Brown (1997) to assess depression . 4) I-E Scale (Internal-External Locus of Control Scale) Rotter (1966) to assess locus of control. 5) SWLS (Satisfaction with Life Scale) Diener, Emmons, Larsen, and Griffin (1985) to assess overall (global) satisfaction with life. Bivariate correlations between the known predictor variables (self-esteem, depression, and locus of control) and the dependant measure (SWL) are in agreement (size and direction) with prior research. However, correlational analysis suggested no correlation between EI as well as all four components of EI with SWL or the known predictor variables. These findings agree with prior research reporting correlations between EI or components of EI with SWL. A series of five hierarchical regression analyses was conducted to investigate whether EI or any of the four components of EI contributes in the prediction of SWL after accounting for known predictors (self-esteem, depression, and locus of control). The results of all five hierarchical regression analysis suggest s EI as well as the components of EI do not account for additional variance in SWL among community college students.Therefore, results of the study suggest EI is not an important predictor of SWLamong community college students. Limitations of the study as well as suggestions for future research are discussed. In the final sections conclusions as well as some implications for practice in higher education are presented.

The purpose of this study was to explore the construct validity of the Kaufman Assessment Battery for Children, Second Edition (KABC-II; Kaufman & Kaufman, 2004a) and the Woodcock-Johnson Tests of Cognitive Abilities, Third Edition (WJ-III COG; Woodcock, McGrew, & Mather, 2001) with a sample of 200 preschool children, ranging in age from 4 years, 0 months to 5 years, 1 1 months, and attending preschool and daycare programs in and around a Midwestern city. This study attempted to determine if the Cattell-Horn-Carroll (CHC) factor structure represented on these tests can be identified with young children. Individual confirmatory factor analyses were conducted separately with the KABC-II and WJ-III COG. Moreover, a joint confirmatory factor analysis was conducted using both the KABC-II and WJ-III COG. The results of the individual KABC-II factor analyses indicated a two-tiered Gf Gc model provided the best fit to the data, although the three-tiered CHC model also fit the data well. This suggests the underlying factor structure of the KABC-II is well represented by the CHC theory. The WJ-III COG was best represented by an alternative CHC model, in which the Gf factor and subtests had been removed, indicating not all CHC constructs represented on the WJ-III COG can be reliably identified among young children. The joint confirmatory factor analysis indicated the strongest measures of the shared CHC factors on the KABCII and WJ-III COG, which can help to guide cross-battery assessment with preschool children. Overall, the results confirmed multiple CHC abilities can be assessed with young children, implying clinicians should be using preschool tests that provide scores for several cognitive abilities. This study also revealed the constructs of the CHC theory may be represented somewhat differently on preschool tests due to developmental influences. Strong correlations were evident between unrelated tasks, primarily because the verbal and linguistic demands of many subtests caused them to load unexpectedly on the Gc factor. Suggestions for future research include conducting the same study using preschool children with suspected disabilities, as well as with older children, examining other instruments that include a Gf factor, and conducting exploratory factor analysis with subtests from the KABC-II and WJ-III COG that contain significant components of more than one ability. / Department of Educational Psychology

There is no abstract available for this dissertation. / Department of Educational Psychology

This study investigated the utility of the cognitive measures of the Dean-Woodcock Neuropsychological Assessment System (D-WNAS) in the differential diagnosis of Alzheimer dementia (AD) from depression. Past research has found an overlap of symptoms in the early stages of AD and those found in geriatric depression. In both instances, patients are likely to report memory loss, attention deficits, and mood disturbances. As a result of this similarity, differentially diagnosing one from another is a vexing problem for the clinical practitioner. Although a number of screening measures have been offered, none have proven to be clinically useful. Some have proposed this is the result of reliance upon use of single-factor measures. Indeed, many have proposed a multiple factor assessment model would be of more utility in diagnosing AD and depression. Considering the importance of an accurate diagnosis in treatment, this study utilized a multiple factor cognitive model offered by the Dean-Woodcock Neuropsychological Assessment System to differentiate AD from depression.Specifically, subtest scores of the Woodcock-Johnson III - Tests of Cognitive Ability (WJ-III; cognitive measure of the Dean-Woodcock Neuropsychological Assessment System) were compared. Participants (n = 172) fell into one of three groups (i.e. Depressed, Demented, or Normal) based on the diagnoses of a board certified neurologist and neuropsychologist. Results showed clinical groups performed more poorly than normal participants on tests of the WJ-III. In addition, AD participants differed significantly from depressed participants on the Visual Matching and Spatial Relations tests of the WJ-III. However, in all, the WJ-III demonstrated a classification hit rate of less than 70%. Although groups were found to differ in specific ways, the classification hit rate of the WJ-III suggested it could not differentially diagnose AD from depression alone. / Department of Educational Psychology