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There are several parallels between the acquisition of expert performance and the learning by students in high school and college courses. High school and college course experience includes prolonged, intensive practice on learning skills and knowledge in math and verbal related subjects, with the opportunity to receive feedback on learning progress through learning assessments. Students who continue on to higher education typically complete standardized tests aimed at measuring their reasoning performance in math and verbal related skills. The current work aimed to measure the relationship between completed courses relevant to the content appearing on standardized tests and the performance on those tests. This study has adopted the expert performance approach to examine the association between particular completed courses and SAT and GRE performance while increasing the precision of those estimates. Knowledge from research on different types of practice and statistical techniques aimed at addressing measurement issues from previous studies were utilized to obtain optimal estimates. The previous research has indicated positive associations between taking additional relevant courses, and engaging in additional effort to master learning in completed courses, on SAT and GRE performance. Additionally, a notable gender gap has been identified on standardized tests, with males scoring higher than females on math section performance. However, there has been a large degree of variation in the adequacy of measures of previous performance and no existing study has attempted to address bias in estimates related to issues of self-selection. In the current work, two studies were performed to attempt to optimally measure the size of the effects for the association between course taking and standardized test performance. In Study 1, the statistical techniques of hierarchical regression, two-stage least squares regression, and mixed modeling were used on the HSLS:09 dataset to obtain estimates of course taking and grade performance on the SAT-Math and SAT-Verbal. In Study 2, the techniques of hierarchical regression, propensity score matching, and quantile regression analyses were performed on a novel college sample to estimate the role of course taking, effort, and previous performance on the association between completed college major and changes in GRE-Quant and GRE-Verbal performance. Additionally, a secondary focus of examining the potential causes of the large gender gap in GRE-Quant performance was undertaken in Study 2. The results of Study 1 and Study 2 indicated support for engaging in a challenging course curriculum and maximizing effort in completed courses to optimize the benefit of course experience on standardized assessments. Evidence emerged for a unique benefit for completing courses including learning skills at a level higher than the level of content being tested directly on the SAT and GRE. The gender gap in math performance was substantially smaller when controlling for previous performance and differences in course taking. Each of these results are discussed in terms of their implication for how students may utilize course experiences to maximize their score on standardized tests and benefit from insights from studies of purposeful and deliberate practice mediating the acquisition of expert performance. / A Dissertation submitted to the Department of Psychology in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2017. / July 11, 2017. / Delliberate Practice, Educational Psychology, Higher Education, Psychology, Standardized Testing / Includes bibliographical references. / Karl A. Ericsson, Professor Directing Dissertation; Elizabeth M. Jakubowski, University Representative; Richard K. Wagner, Committee Member; Colleen M. Kelley, Committee Member; Colleen M. Ganley, Committee Member.

<p> This dissertation investigated the role of individual differences in human use of automation in a simulated command and control task. Using this knowledge we then sought to redesign the simulation interface to improve human-automation interaction. In the first study, participants completed a battery of cognitive tasks to measure working memory capacity, simple memory span, and controlled attention ability. They then performed a simulated air defense task under varying levels of workload and automation assistance. Eye tracking data recorded fixations to capture eye movements during completion of each scenario. Although individual difference measures correlated with primary task performance, they did not predict use of automation. Only average percent of fixations on the automation messaging interface correlated with automation use. Therefore, the second study introduced a redesigned automation interface with the integration of an auditory chime and a visual flicker to promote additional fixations to the message interface and encourage increased automation use. However, this redesign did not increase average fixation percentage and surprisingly resulted in lower use of automation. This finding emphasized Parasuraman and Riley&rsquo;s (1997) warning that automation can change user behavior in unintended ways. Another notable finding from the study is the unexpected result that short term memory predicted primary task performance. Further, this study provides evidence to support the use of eye tracking measures as a continuous unobtrusive measure of automation use in complex systems. Limitations and future research are also discussed.</p>

Information technology (IT) enabled information systems (IS) are widely used within most organisations today. Since the introduction of IT enabled IS in the 1980’s, there have been numerous reports of problematic and failed implementations. The implementation stage has been emphasised as the stage in the IS life cycle where a large number of issues arise, and the implementation phenomenon has been widely studied. Despite this research focus, there is still not a consensus within the IS research community about what factors lead to implementation failure, and what factors facilitate implementation success. There are many studies that examine the use of IS through models of user behaviour, typically focussing on explaining the variance of a particular variable such as usage frequency. Two such studies raised questions that were important in framing this thesis. Venkatesh, Morris, Davis, G. and Davis, F. (2003) asked whether or not efforts put into understanding factors that contribute to increased usage actually help predict IS success, and to what degree systems considered to have been successfully adopted are actually successful from an organisational perspective. Jasperson, Carter and Zmud (2005) suggested that research should look further than simple dependent variables such as usage, and that uptake of system features might be a better indicator of implementation success. Further, it was suggested that the implementation outcome might be influenced by behaviours and factors that occurred after the installation of IS, and that few models of implementation actually contained a post-adoptive stage. In order to answer these and other questions concerning the implementation of IS within organisations, a longitudinal, qualitative study of the implementation of an enterprise wide IS within an organisation was conducted using the ethnographic methodology of participant observation. The focus of the study was the impact of individual and group behaviour on the implementation success of IS. This focus necessitated exploration of the concept of implementation success, its measurement and how implementation success is perceived throughout an organisation. An important outcome from this study was a Conceptual Model of Information System Implementation within Organisations (CMISIO). The CMISIO, based upon observations from the study, describes implementation as a multi-faceted phenomenon guided within organisational constraints to achieve a pre-determined organisational fit. Organisational fit captures the notion of success, which was seen to vary depending upon the perspective of an observer within the organisation. In this way implementation success was seen to be a multi-faceted phenomenon. The intent of the model was not to reduce the implementation phenomenon to components, but rather to capture those organisational factors that lead to site-specific variations in IS implementation. There were a number of important findings from the study that have relevance for both IS researchers and practitioners. The IS implementation process can take much longer than is widely reported. Studies that only focus upon a part of the process might fail to capture salient factors that are important in the overall implementation outcome. Evidence to support the importance of Jasperson et al.’s (2005) adoption phase, as well as a later phase of adaptation was found. Adaptation, where organisational users adapt the new IS to their particular needs, can take months or years, and a lack of organisational support within this phase can lead to eventual implementation failure. An IS within an organisation is only special for a certain time, and management focus can shift before the implementation process has been completed. The organisational climate that exists at the time of implementation provides constraints that IS project teams must recognise and work within. Elements of the organisation’s culture can also be important factors in understanding motivations behind behaviours that may be either supportive of or detrimental to the implementation. The study found evidence that some behaviours seen as negative towards the IS implementation were likely motivated by psychological reactance (Brehm, 1966), where individuals react to real or perceived threats to their organisational freedom. The reactance was generated by factors not just associated with the IS, and this finding suggests that in order to predict the implementation outcome within an organisation it is necessary to understand factors other than those directly associated with the IS being implemented. Finally, the scientist-practitioner model used within psychology was suggested as a working model that could be used to help integrate the large body of IS research into organisations. The model focuses on the integration of science-based research and day-to-day practice whereby each informs the other through involvement. This proposal addresses a perceived gap between the researchers looking at IS on the one hand and practitioners implementing IS within organisations on the other.

Information technology (IT) enabled information systems (IS) are widely used within most organisations today. Since the introduction of IT enabled IS in the 1980’s, there have been numerous reports of problematic and failed implementations. The implementation stage has been emphasised as the stage in the IS life cycle where a large number of issues arise, and the implementation phenomenon has been widely studied. Despite this research focus, there is still not a consensus within the IS research community about what factors lead to implementation failure, and what factors facilitate implementation success. There are many studies that examine the use of IS through models of user behaviour, typically focussing on explaining the variance of a particular variable such as usage frequency. Two such studies raised questions that were important in framing this thesis. Venkatesh, Morris, Davis, G. and Davis, F. (2003) asked whether or not efforts put into understanding factors that contribute to increased usage actually help predict IS success, and to what degree systems considered to have been successfully adopted are actually successful from an organisational perspective. Jasperson, Carter and Zmud (2005) suggested that research should look further than simple dependent variables such as usage, and that uptake of system features might be a better indicator of implementation success. Further, it was suggested that the implementation outcome might be influenced by behaviours and factors that occurred after the installation of IS, and that few models of implementation actually contained a post-adoptive stage. In order to answer these and other questions concerning the implementation of IS within organisations, a longitudinal, qualitative study of the implementation of an enterprise wide IS within an organisation was conducted using the ethnographic methodology of participant observation. The focus of the study was the impact of individual and group behaviour on the implementation success of IS. This focus necessitated exploration of the concept of implementation success, its measurement and how implementation success is perceived throughout an organisation. An important outcome from this study was a Conceptual Model of Information System Implementation within Organisations (CMISIO). The CMISIO, based upon observations from the study, describes implementation as a multi-faceted phenomenon guided within organisational constraints to achieve a pre-determined organisational fit. Organisational fit captures the notion of success, which was seen to vary depending upon the perspective of an observer within the organisation. In this way implementation success was seen to be a multi-faceted phenomenon. The intent of the model was not to reduce the implementation phenomenon to components, but rather to capture those organisational factors that lead to site-specific variations in IS implementation. There were a number of important findings from the study that have relevance for both IS researchers and practitioners. The IS implementation process can take much longer than is widely reported. Studies that only focus upon a part of the process might fail to capture salient factors that are important in the overall implementation outcome. Evidence to support the importance of Jasperson et al.’s (2005) adoption phase, as well as a later phase of adaptation was found. Adaptation, where organisational users adapt the new IS to their particular needs, can take months or years, and a lack of organisational support within this phase can lead to eventual implementation failure. An IS within an organisation is only special for a certain time, and management focus can shift before the implementation process has been completed. The organisational climate that exists at the time of implementation provides constraints that IS project teams must recognise and work within. Elements of the organisation’s culture can also be important factors in understanding motivations behind behaviours that may be either supportive of or detrimental to the implementation. The study found evidence that some behaviours seen as negative towards the IS implementation were likely motivated by psychological reactance (Brehm, 1966), where individuals react to real or perceived threats to their organisational freedom. The reactance was generated by factors not just associated with the IS, and this finding suggests that in order to predict the implementation outcome within an organisation it is necessary to understand factors other than those directly associated with the IS being implemented. Finally, the scientist-practitioner model used within psychology was suggested as a working model that could be used to help integrate the large body of IS research into organisations. The model focuses on the integration of science-based research and day-to-day practice whereby each informs the other through involvement. This proposal addresses a perceived gap between the researchers looking at IS on the one hand and practitioners implementing IS within organisations on the other.