Introducing e-learning in a large multisite academic health sciences centre: a case study of e-curriculum planning and educator support /

This qualitative study investigated how a team of 7 hospital educators collaborated to develop e-curriculum units to pilot for a newly acquired learning -r management system at a large, multisite academic health sciences centre. A case study approach was used to examine how the e-Curriculum Team was structured, how the educators worked together to develop strategies to better utilize e-leaming in their ovwi practice, what e-curriculum they chose to develop, and how they determined their priorities for e-curriculum development. It also inquired into how they planned to involve other educators in using e-leaming. One set of semistructured interviews with the 6 hospital educators involved in the project, as well as minutes of team meetings and the researcher's journal, were analyzed (the researcher was also a hospital educator on the team). Project management structure, educator support, and organizational pressures on the implementation project feature prominently in the case study. This study suggests that implementation of e-leaming will be more successful if (a) educators involved in the development of e-leaming curriculum are supported in their role as change agents, (b) the pain of vmleaming current educational practice is considered, (c) the limitations of the software being implemented are recognized, (d) time is spent leaming about best practice, and (e) the project is protected as much as possible from organizational pressures and distractions.

Closing the Summer Learning Gap for Vulnerable Children: An Examination of a Summer Family Literacy Program for Junior Kindergarten Children At-Risk for Reading Difficulties

The learning gap created by summer vacation creates a significant breach in the learning cycle, where student achievement levels decrease over the course ofthe summer (Cooper et aI., 2000). In a review of 39 studies, Cooper and colleagues (1996) specified that the summer learning shortfall equals at least one month loss of instruction as measured by grade level equivalents on standardized test scores. Specifically, the achievement gap has a more profound effect on children as they grow older, where there is a steady deterioration in knowledge and skills sustained during the summer months (Cooper et aI., 1996; Kerry & Davies, 1998). While some stakeholders believe that the benefits of a summer vacation overshadow the reversing effect on achievement, it is the impact of the summer learning gap on vulnerable children, including children who are disadvantaged as a result of requiring special educational needs, children from low socioeconomic backgrounds, and children learning English as a second language, that is most problematic. More specifically, research has demonstrated that it is children's literacy-based skills that are most affected during the summer months. Children from high socioeconomic backgrounds recurrently showed gains in reading achievement over the summer whereas disadvantaged children repeatedly illustrate having significant losses. Consequently, the summer learning gap was deemed to exaggerate the inequality experienced by children from low socioeconomic backgrounds. Ultimately, the summer learning gap was found to have the most profound on vulnerable children, placing these children at an increased chance for academic failure. A primary feature of this research project was to include primary caregivers as authentic partners in a summer family literacy program fabricated to scaffold their children's literacy-based needs. This feature led to the research team adapting and implementing a published study entitled, Learning Begins at Home (LBH): A Research-Based Family Literacy Program Curriculum. Researchers at the Ontario Institute designed this program for the Study of Education, University of Toronto. The LBH program capitalized on incorporating the flexibility required to make the program adaptable to meet the needs of each participating child and his or her primary caregiver. As it has been well documented in research, the role primary caregivers have in an intervention program are the most influential on a child's future literacy success or failure (Timmons, 2008). Subsequently, a requirement for participating in the summer family literacy program required the commitment of one child and one of his or her primary caregivers. The primary caregiver played a fundamental role in the intervention program through their participation in workshop activities prior to and following hands on work with their child. The purpose of including the primary caregiver as an authentic partner in the program was to encourage a definitive shift in the family, whereby caregivers would begin to implement literacy activities in their home on a daily basis. The intervention program was socially constructed through the collaboration of knowledge. The role ofthe author in the study was as the researcher, in charge of analyzing and interpreting the results of the study. There were a total of thirty-six (36) participants in the study; there were nineteen (19) participants in the intervention group and seventeen (17) participants in the control group. All of the children who participated in the study were enrolled in junior kindergarten classrooms within the Niagara Catholic District School Board. Once children were referred to the program, a Speech and Language Pathologist assessed each individual child to identify if they met the eligibility requirements for participation in the summer family literacy intervention program. To be eligible to participate, children were required to demonstrate having significant literacy needs (i.e., below 25%ile on the Test of Preschool Early Literacy described below). Children with low incident disabilities (such as Autism or Intellectual Disabilities) and children with significant English as a Second Language difficulties were excluded from the study. The research team utilized a standard pre-test-post-test comparison group design whereby all participating children were assessed with the Test of Preschool Early Literacy (Lonigan et aI., 2007), and a standard measure of letter identification and letter sound understanding. Pre-intervention assessments were conducted two weeks prior to the intervention program commencing, and the first set of the post-intervention assessments were administered immediately following the completion of the intervention program. The follow-up post-intervention assessments took place in December 2010 to measure the sustainability of the gains obtained from the intervention program. As a result of the program, all of the children in the intervention program scored statistically significantly higher on their literacy scores for Print Knowledge, Letter Identification, and Letter Sound Understanding scores than the control group at the postintervention assessment point (immediately following the completion of the program) and at the December post-intervention assessment point. For Phonological Awareness, there was no statistically significant difference between the intervention group and the control at the postintervention assessment point, however, there was a statistically significant difference found between the intervention group and the control group at the December post-intervention assessment point. In general, these results indicate that the summer family literacy intervention program made an immediate impact on the emergent literacy skills of the participating children. Moreover, these results indicate that the summer family literacy intervention program has the ability to foster the emergent literacy skills of vulnerable children, potentially reversing the negative effect the summer learning gap has on these children.

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.