Using a Performance Consistency Model to Explain Variations in Test-Retest Performance

Subtest-level interpretation of intelligence tests is necessary for understanding the relationship between cognitive deficiencies and academic problems and for designing interventions based on assessment results. However, the practice of subtest interpretation continues to be discouraged by those who claim that subtests have poor reliability and thus minimal interpretative power. This perception of subtest instability may be the result of misguided conceptions of reliability and not actual properties of subtests. With this in mind, the present study sought to determine the extent to which a neuropsychologically based performance model fit WISC-IV subtest test-retest data and offered an alternate means of understanding and interpreting the concept of subtest reliability. Higher rates of score progression versus regression were demonstrated for all subtests regardless of whether or not time 1 scores were above or below the mean. Rates of score increases from time 1 to time 2 varied based on the neuropsychological basis of the task being assessed. Results suggest that a neuropsychologically based performance model is superior to a traditional psychometric model for representing WISC-IV subtest reliability and the manner in which individuals use their brains when they engage tasks

The relationship between classroom climate, student self-efficacy and student achievement.

Master of Science in Construction Studies. University of KwaZulu-Natal. Durban, 2017.This study documents students’ perceptions and factors within the classroom that are perceived to impact upon the learning of mathematics. The participants of the study were first, second, third and fourth year students from four universities in South Africa namely University of Kwa-Zulu Natal, Durban University of Technology, Mangosuthu University of Technology and University of Johannesburg. The objectives of this study are: To discover whether students have a decrease or increase in self-efficacy, goal mastery and strategic learning within the current classroom climate. To discover whether classroom climate increases or decreases self-efficacy in the current classroom environment. To understand the student-instructor relationship within the current classroom climate with respect to achievement in mathematics. Quantitative methods were employed to understand the students’ views about their experiences with mathematics learning and mathematics classroom environment. A questionnaire to determine the objectives based on six constructs i.e. Self-Efficacy, Mastery Goal Structure, Instructors Challenges, Instructors Care, Student’ Expectations and Students’ Achievement was employed to solicit students’ views with regards to teaching approaches in mathematical classes. The findings revealed, that there is a correlation between Mastery Goal Structure, Instructors Care, Grade Expected and Instructor Challenge with Self-Efficacy. There was no significant correlation between Gender, Name of University and Student Achievement with Self-Efficacy

Pay Satisfaction, Job Satisfaction, Organizational Commitment and Turnover Intention in Taiwan Banking: Structural Equation Modeling

Various investigators have researched voluntary employee turnover intention within both the private and public sectors. However, little is known about employee turnover intention within the domestic private banking industry in Taiwan. This study examined the fundamental theoretical literature and empirical studies related to employee turnover intention among Taiwanese domestic private banking employees. The relationship among pay satisfaction, job satisfaction, organizational commitment and voluntary employee turnover is an important issue for any organization. Employee turnover as the result of practices within the fields of economics, human resource management, organizational behavior, psychology, and ethics have been examined in this study. This research explored those factors influencing employee turnover intention, and identified areas of future scholarly inquiry. Findings indicated that employee turnover intention is complex. Existing turnover models are unable to comprehensively explain turnover. However, existing turnover theories provide a framework within which to research the topic. Contemporary turnover theories provide valuable information for leaders to use to improve their leadership styles, training procedures, and policies, and are very useful in predicting turnover or decision-making. The purposes of this study were to explore the relationship among pay satisfaction, job satisfaction, organizational commitment, and turnover intention in the Taiwanese domestic private banking industry; to describe the degrees of pay satisfaction, job satisfaction, organizational commitment, and turnover intention of entry-level and mid-management branch office employees of Taiwanese domestic private banks and their sociodemographic characteristics; to examine existing pay satisfaction, job satisfaction, organizational commitment, and turnover theories as well as some conflicts between different theories; and to explore whether pay satisfaction plays a critical role in turnover decisions. Three research questions and 23 hypotheses were developed for this quantitative, non-experimental study. Further, this study adopted an explanatory and correlational survey to answer those questions and hypotheses using descriptive statistics, confirmatory factory analysis, and Structural Equation Modeling (SEM). Future studies may try to examine related variables in different groups, industries, cultures, or countries, and explore the relationship between employee turnover intention and the actual departure of an employee

Relations Among Brief Measures of Mathematics, Reading, and Processing Speed: A Construct Validity Study

Emphasis on regular mathematics skill assessment, intervention, and progress monitoring under the RTImodel has created a need for the development of assessment instruments that are psychometrically sound, reliable, universal, and brief. Important factors to consider when developing or selecting assessments for the school environment include what skills are assessed; mathematics curriculums typically include computation and applications as separate skills taught in sequence. It is also important to consider what additional factors may potentially influence performance on such tests due to the nature of test administration and characteristics of the test items. The current study investigated the construct validity of established, widely-used curriculum-based measurement (CBM)tests and standardized, norm-referenced tests of mathematics as well as the potential confounding influence of processing speed and reading abilities. Construct validity of the tests was assessed through an investigation of convergent and discriminant validity, using confirmatory factor analysis (CFA). Numerous prespecified, theoretical models were tested to replicate previous studies suggesting specific models of mathematics ability (convergent validity) and to identify construct-irrelevant variance (discriminant validity) imposed on tests of computation and applications by processing speed and reading. The current study extended previous work in the area of mathematics providing additional evidence for a two-factor structure of mathematics with Computation and Applications as distinct, yet related constructs and investigated the relations between mathematics constructs and processing speed and reading. Results of the current study indicated all constructs were significantly correlated with each other while mathematics constructs were more highly correlated with each other than with unrelated constructs, with the exception of Applications and Reading. Four a priori models of mathematics ranging from including a single factor to including four factors were tested using CFA. Results indicated that a four-factor model of mathematics including Computation, Applications, Processing Speed, and Readingas factors was the best-fitting model. The four-factor model was extended to test the construct-irrelevant variance imposed by Processing Speed on fluency-based tests as well as variance imposed by Reading on applications tests. Results indicated that in all but one case, no significant influence was contributed to fluency-based tests by Processing Speed or applications tests by Reading

ASSESSING THE MODEL FIT OF MULTIDIMENSIONAL ITEM RESPONSE THEORY MODELS WITH POLYTOMOUS RESPONSES USING LIMITED-INFORMATION STATISTICS

Under item response theory, three types of limited information goodness-of-fit test statistics – M2, Mord, and C2 – have been proposed to assess model-data fit when data are sparse. However, the evaluation of the performance of these GOF statistics under multidimensional item response theory (MIRT) models with polytomous data is limited. The current study showed that M2 and C2 were well-calibrated under true model conditions and were powerful under misspecified model conditions. Mord were not well-calibrated when the number of response categories was more than three. RMSEA2 and RMSEAC2 are good tools to evaluate approximate fit. The second study aimed to evaluate the psychometric properties of the Religious Commitment Inventory-10 (RCI-10; Worthington et al., 2003) within the IRT framework and estimate C2 and its RMSEA to assess global model-fit. Results showed that the RCI-10 was best represented by a bifactor model. The scores from the RCI-10 could be scored as unidimensional notwithstanding the presence of multidimensionality. Two-factor correlational solution should not be used. Study two also showed that religious commitment is a risk factor of intimate partner violence, whereas spirituality was a protecting factor from the violence. More alcohol was related with more abusive behaviors. Implications of the two studies were discussed

Una aproximación multidimensional al apoyo social: El Cuestionario de Frecuencia y Satisfacción con el Apoyo Social (CFSAS).

The Questionnaire on the Frequency of and Satisfaction with Social Support (QFSSS) was designed to assess the frequency of and the degree of satisfaction with perceived social support received from different sources in relation to three types of support: emotional, informational and instrumental. This study tested the reliability of the questionnaire and its criterion and structural validity. The data were drawn from survey interviews of 2042 Spanish people. The results show high internal consistency (values of Cronbach’s alpha range from .763 to .952). The correlational analysis showed significant positive associations between QFSSS scores and measures of subjective well-being and perceived social support, as well as significant negative associations with measures of loneliness (Pearson’s r correlation range from .11 to .97). Confirmatory factor analysis by Structural Equation Modeling suggested an internal 4-factor structure that corresponds to the sources of support analyzed: partner, family, friends and community (values for the Goodness of Fit Index (GFI) range from .93 to .95; for the Comparative Fit Index (CFI) range from .95 to .98; for Root Mean Square Error of Approximation (RMSEA) range from .10 to .07). These results confirm the QFSSS validity as a versatile tool, suitable for the detailed assessment of social support.El Cuestionario de Frecuencia y Satisfacción con el Apoyo Social (CFSAS) ha sido diseñado para evaluar la frecuencia y el grado de satisfacción con el apoyo social percibido procedente de diferentes fuentes en relación a tres tipo de apoyo: emocional, informacional e instrumental. En este estudio se comprueba la fiabilidad del cuestionario, así como su validez estructural y de criterio. Los datos fueron obtenidos de una muestra compuesta por 2042 españoles. Los resultados muestran una alta consistencia interna (rango de valores del Alpha de Cronbach entre .763 y .952). El análisis correlacional mostró relaciones positivas significativas entre el CFSAS y medidas de bienestar subjetivo y apoyo social percibido, así como relaciones negativas significativas con medidas de soledad (rango de valores de la r de Pearson entre .11 y .97). El análisis factorial confirmatorio, usando ecuaciones estructurales, sugiere una estructura interna compuesta por cuatro factores, que se corresponden con las fuentes de apoyo analizadas: pareja, familia, amigos y comunidad (rango de valores GFI entre .93 y .95, CFI entre .95 y .98, RMSEA entre .10 y .07). Estos resultados confirman la validez del CFSAS como una herramienta versátil adecuada para la valoración multidimensional del apoyo social

The Need for Meta-Analytic Thinking in Educational Technology Research

The present journal article formatted dissertation assessed the extent of meta-analytic thinking currently used educational technology research. In the first study, the author examined the journals, Computers & Education, International Journal of Computer-Supported Collaborative Learning, British Journal of Educational Technology, Australasian Journal of Educational Technology, and Educational Technology Research and Development, between 2012 and 2013 to offer empirical evidence of the field’s current status with regard to reporting results using meta-analytic thinking. These articles represented a total of 32,131 research methods and statistical techniques recorded from 1,171 articles. Findings point to little change in how educational technology researchers conduct investigations. Quantitative methods continue to dominate the field as a whole. Most authors reported the type of sampling procedure used in their investigations. Few researchers reported score reliability estimates using their own data. Findings also suggest few authors report informationally-adequate statistics. One area of concern is the tendency to report a mean without the SD about the mean. Another area of concern is the lack of reporting correlation matrices with accompanying means and standard deviations or covariance matrices. In the second study, the author conducted a meta-analysis to offer a glimpse of where the field could go once researchers begin to think meta-analytically. The author cumulated findings from nine studies which used the Technology Acceptance Model (TAM) to explain undergraduate students’ acceptance of online learning. The author used meta-analytic structural equation modeling and multiple-group analysis to test four path models. The meta-analytic findings suggest the TAM is not a valid theoretical model to explain undergraduates’ acceptance of college online courses. The multiple group analysis emphasized that the parameter estimates between studies resulted in statistically different findings, suggesting the findings across studies are not replicable

A protection motivation theory approach to improving compliance with password guidelines

Usernames and passwords form the most widely used method of user authentication on the Internet. Yet, users still find compliance with password guidelines difficult. The primary objective of this research was to investigate how compliance with password guidelines and password quality can be improved. This study investigated how user perceptions of passwords and security threats affect compliance with password guidelines and explored if altering these perceptions would improve compliance. This research also examined if compliance with password guidelines can be sustained over time. This study focuses on personal security, particularly factors that influence compliance when using personal online accounts. The proposed research model is based on the Protection Motivation Theory (PMT) (Rogers, 1975, 1983), a model widely used in information systems security research. As studies have failed to consistently confirm the association between perceived vulnerability and information security practices, the model was extended to include exposure to hacking as a predictor of perceived vulnerability. Experimental research was used to test the model from two groups of Internet users, one of which received PMT based fear appeals in the form of a password security information and training exercise. To examine if password strength was improved by the fear appeals, passwords were collected. A password strength analysis tool was developed using Shannon’s (2001) formula for calculating entropy and coded in Visual Basic. Structural equation modeling was used to test the model. The proposed model explains compliance intentions moderately well, with 54% of the variance explained by the treatment model and 43% explained by the control group model. Overall, the results indicate that efficacy perceptions are a stronger predictor of compliance intentions than threat perceptions. This study identifies three variables that predict user intentions to comply with password guidelines as particularly important. These are perceived threat, perceived password effectiveness and password self-efficacy. The results show no association between perceived vulnerability to a security attack and a user’s decision to comply. The results also showed that those who are provided with password information and training are significantly more likely to comply, and create significantly stronger passwords. However, the fear appeals used in this study had no long-term effects on compliance intentions. The results on the long-term effects of password training on the participants’ ability to remember passwords were however promising. The group that received password training with a mnemonic training component was twice as likely to remember their passwords over time. The results of this research have practical implications for organizations. They highlight the need to raise the levels of concern for information systems security threats through training in order to improve compliance with security guidelines. Communicating to users what security responses are available is important; however, whether they implement them is dependent on how effective they feel the security responses are in preventing an attack. Regarding passwords, the single most important consideration by a user is whether they have the ability to create strong, memorable passwords. At the very least, users should be trained on how to create strong passwords, with emphasis on memorization strategies. This research found mnemonic password training to have some long-term effects on users’ ability to remember passwords, which is arguably one of the most vexing challenges associated with passwords. Future research should explore the extent to which the effects of PMT based information systems security communication can be maintained over time