Writing and science connections : integrated instruction and assessment

Learning to write is a daunting task for many young children. The purpose of this study was to examine the impact of a combined approach to writing instruction and assessment on the writing performance of students in two grade 3 classes. Five forms and traits of writing were purposefully connected during writing lessons while exhibiting links to the four strands of the grade 3 Ontario science curriculum. Students then had opportunities to engage in the writing process and to self-assess their compositions using either student-developed (experimental group/teacher-researcher's class) or teachercreated (control group/teacher-participant's class) rubrics. Paired samples t-tests revealed that both the experimental and control groups exhibited statistically significant growth from pretest to posttest on all five integrated writing units. Independent samples t-tests showed that the experimental group outperformed the control group on the persuasive + sentence fluency and procedure + word choice writing tasks. Pearson product-moment correlation r tests revealed significant correlations between the experimental group and the teacher-researcher on the recount + ideas and report + organization tasks, while students in the control group showed significant correlations with the teacher-researcher on the narrative + voice and procedure + word choice tasks. Significant correlations between the control group and the teacher-participant were evident on the persuasive + sentence fluency and procedure + word choice tasks. Qualitative analyses revealed five themes that highlighted how students' self-assessments and reflections can be used to guide teachers in their instructional decision making. These findings suggest that educators should adopt an integrated writing program in their classrooms, while working with students to create and utilize purposeful writing assessment tools.

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.