Task-Dependent Oscillatory Brain Activity During Oculomotor Delayed Response Task

This study used three Oculomotor Delayed Response (ODR) tasks to investigate the unique cognitive demands during the delay period. Changes in alpha power were used to index cognitive efforts during the delay period. Continuous EEGs from 25 healthy young adults (18-34 years) were recorded using dense electrode array. The data was analyzed by 6-cycle Morlet wavelet decompositions in the frequency range of 2-30 Hz to create time- frequency decompositions for four midline electrode sites. The 99% confidence intervals using the bootstrapped 20% trimmed mean of the 10 Hz frequency were used to examine the differences among conditions. Compared to two Memory conditions (Match and Non-Match), Control condition yielded significant differences in all frequencies over the entire trial period, suggesting a cognitive state difference. Compared to Match condition, the Non–Match condition had lower alpha activity during the delay period at each midline electrode site reflecting the higher cognitive effort required.

The Influence of Attentional Focus on the Self-Efficacy-Performance Relationship in a Continuous Running Task

The self-efficacy-performance relationship in continuous sport tasks has been shown to be significantly reciprocal yet unequal with stronger influences in the performance-to-self-efficacy pathway rather than self-efficacy-to-performance pathway (e.g., LaForge-MacKenzie & Sullivan, 2014b). Bandura (2012) suggested that sociocognitive variables may influence this relationship. Attention as a sociocognitve factor may bias the processing of performance and self-efficacy information (Bandura, 1982, 1997; Bandura & Jourden, 1991). As confidence and attention are important aspects of peak running performance (Brewer, Van Raalte, Linder, & VanRaalte, 1991), the primary purpose of the present study was to examine the self-efficacy-performance relationship under three conditions of attentional focus. The secondary purpose was to examine self-efficacy and performance as separate constructs under the same conditions of attention. Participants ran continuously for one kilometer in one of three randomly assigned attentional focus conditions: internal-focus (n = 51), external-focus (n = 50), and control (n = 49). Self-efficacy was assessed using a one-item measure every 200 meters. Path analyses examining the primary objective revealed significant self-efficacy-to-performance pathways in all conditions: external-focus (p < .05, βs ranging from -.17 to -.32), internal-focus (p < .05, βs ranging from -.26 to -.36), and control (p < .05, βs ranging from -.29 to -.42). Significant reciprocal relationships were absent in all conditions. ANOVAs examining the secondary objectives found significantly faster performance in the control condition at the start (F (2, 147) = 3.86, p < .05) and end of the task (F (2, 147) = 3.56, p < .05). Self-efficacy was significantly higher in the internal-focus condition at the end of the task (Self-Efficacy 4 (F (2, 147) = 3.21, p < .05) and Self-Efficacy 5 (F (2, 147) = 4.74, p < .05). In contrast to previous within-trial research (e.g., LaForge-MacKenzie & Sullivan, 2014b) self-efficacy-to-performance effects were more significant and robust than performance-to-self-efficacy effects. These results provided support for Bandura’s (2012) suggestion that sociocognitive factors may have the ability to alter the causal structure of the self-efficacy-performance relationship, proposing complexities in the self-efficacy-performance relationship (Sitzmann &Yeo, 2013). Results were discussed from both theoretical and applied perspectives.

The Order of Canada Investiture Ceremony Program (Selection of Pages)

A selection of pages from the program for the Order of Canada Investiture Ceremony in 2003 when Dorothy Wetherald Rungeling was a recipient.

The Impact of Personal Trainer’s Leadership Style on Self-Presentational Concerns, Enjoyment, Task Self-Efficacy and Intention to Exercise in an Introductory Weight Training Orientation

The purpose of the present study was to examine two leadership styles of personal trainers (bland versus enriched) to evaluate their effects on exercise-related outcomes. Participants were 103 university women with no previous experience weight training. Participants were randomly assigned to one of the two leadership style conditions. They completed primary measures prior to being introduced to the personal trainer. Next, participants completed an introductory weight training session, followed by post-manipulation measures. The leadership styles were successfully manipulated. Participants in the enriched leadership style condition reported significantly higher levels of enjoyment and intention to exercise. Participants in the bland leadership style condition reported significantly higher levels of social anxiety; no differences were found for task self-efficacy, self-presentational efficacy, social physique anxiety, or handgrip performance between groups. Thus, an enriched leadership style of personal trainers can increase positive psychological outcomes.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Examining peer-controlled KR schedules during the learning of a movement-timing task as a function of task experience.

Learners can be provided with feedback in the form of knowledge of results (KR), under self-controlled and peer-controlled schedules. Recently, McRae, Hansen, and Patterson (2015), identified that inexperienced peers can provide KR that can facilitate motor skill acquisition. However, it is currently unknown whether previous task experience differentially impacts how peers present learners with KR and whether this KR impacts motor skill acquisition. In the present study, participants were randomly assigned to become inexperienced peer facilitators, learners with an inexperienced peer, learners with self-control who later became experienced peers, learners with an experienced peer, or learners in a control group. During acquisition learners completed a serial-timing task with a goal of 2500ms and returned approximately twenty four hours later for a delayed retention, time transfer, and pattern transfer test. We predicted that during the delayed tests, learners with self-control would outperform all other groups. Furthermore, we predicted that learners who received KR from experienced peers would outperform learners who received KR from inexperienced peers. However, our results indicated that participants who received peer-controlled and self-controlled KR schedules learned the task in an equivalent manner. Thus, our results are novel as they identify that inexperienced peers can provide KR that is as effective as KR provided by experienced peers and KR requested under self-controlled conditions.