Patterns and correlates of tobacco use among young adults at college and university

This thesis describes college and university students' smoking behaviours and examines whether socioenvironmental and personal characteristics experienced during adolescence are differentially associated with their smoking participation. Results show more college students than university students currently smoke (37% and 21 % respectively) and more began smoking prior to post-secondary school (93% and 84% respectively). Early age of onset of alcohol use increased the odds of current smoking (main effect model, OR = 8.56 CI = 6.47, 11.33), especially for university students (interaction effect model, b = 2.35 CI = 7.50, 14.64). Lower levels of high school connectedness were associated with increased odds of current smoking but for university students only (interaction effect model, b = -0.15 CI = 0.84, 0.88). While limitations associated with convenience sampling and low response rate exist, this is the first Canadian study to examine college and university students separately. I t reveals that tobacco control programming needs to differ for college and university students, and early alcohol prevention and school engagement programs for adolescents may influence tobacco use. Given that both educational pathway and use of tobacco are associated with SES, future research may consider examining in more detail, SES-related socioenvironmental variables.

Teachers' professional learning within communities of mathematics-for-teaching practice

Ontario bansho is an emergent mathematics instructional strategy used by teachers working within communities of practice that has been deemed to have a transformational effect on teachers' professional learning of mathematics. This study sought to answer the following question: How does teachers' implementation of Ontario bansho within their communities of practice inform their professional learning process concerning mathematics-for-teaching? Two other key questions also guided the study: What processes support teachers' professional learning of content-for-teaching? What conditions support teachers' professional learning of content-for-teaching? The study followed an interpretive phenomenological approach to collect data using a purposive sampling of teachers as participants. The researcher conducted interviews and followed an interpretive approach to data analysis to investigate how teachers construct meaning and create interpretations through their social interactions. The study developed a model of professional learning made up of 3 processes, informing with resources, engaging with students, and visualizing and schematizing in which the participants engaged and 2 conditions, ownership and community that supported the 3 processes. The 3 processes occur in ways that are complex, recursive, nonpredictable, and contextual. This model provides a framework for facilitators and leaders to plan for effective, content-relevant professional learning by placing teachers, students, and their learning at the heart of professional learning.

Accommodating College ESL Learner Communication Needs: Perceptions, Policies, and Practices

The purpose of this qualitative inquiry was to determine how the Practical Nursing and Pharmacy Technician programs in one southern Ontario community college could more effectively accommodate ESL learners' communication needs. The literature review examined (a) linguistic issues, such as language testing and second-language learning theories, (b) organizational matters, such as ESL curriculum and teacher training, and (c) affective issues, such as motivation for second-language learning, learning styles, and the student-teacher relationship. I gathered perceptual data from the programs' administrators, faculty members, and ESL learners. Eleven participants took part in individual interviews or a focus group session. The results suggest that ESL learners need assistance with discipline-specific vocabulary and cultural nuances. College ESL learners' weak communicative competence, together with misleading acceptance standards for ESL learners and limited support available to faculty members and to students, decrease opportunities for successful completion of the programs. The results point to re-assessment of the college's admission policies and procedures, program evaluation practices that consider the needs of ESL learners, discipline-specific language support, and strategies to enhance the ESL student-teacher relationship. The study highlights theory relating to ESL learners' self-perception and engagement, as well as the importance of including the voice of college ESL learners in educational research. The results suggest that despite ESL learners' perseverance in completing their studies, power imbalances remain. The college has yet to implement organizational strategies such as discipline-specific communications and ESL courses and extended language support that could meet the communication needs of ESL learners in the two programs.

A Scalability Study and New Algorithms for Large-Scale Many-Objective Optimization

Many real-world optimization problems contain multiple (often conflicting) goals to be optimized concurrently, commonly referred to as multi-objective problems (MOPs). Over the past few decades, a plethora of multi-objective algorithms have been proposed, often tested on MOPs possessing two or three objectives. Unfortunately, when tasked with solving MOPs with four or more objectives, referred to as many-objective problems (MaOPs), a large majority of optimizers experience significant performance degradation. The downfall of these optimizers is that simultaneously maintaining a well-spread set of solutions along with appropriate selection pressure to converge becomes difficult as the number of objectives increase. This difficulty is further compounded for large-scale MaOPs, i.e., MaOPs possessing large amounts of decision variables. In this thesis, we explore the challenges of many-objective optimization and propose three new promising algorithms designed to efficiently solve MaOPs. Experimental results demonstrate the proposed optimizers to perform very well, often outperforming state-of-the-art many-objective algorithms.