The courses in this cluster aim to provide the students with the knowledge and skills to think critically about both the research in their field and their research, including understanding of ethical and professional issues in conducting research. Through various approaches, students are supported in developing their meta-analytical thinking to get a grounding in the research happening in their field of interest, and start to identify where research gaps exist.

Cluster Learning Outcomes:

Students will,

  • Identify reliable sources of evidence for reports and presentations.
  • Recognize research gaps through the evaluation of secondary sources.
  • Analyze data using research paradigms to assess findings in relevant contexts.
  • Assess ethical and professional considerations when conducting research.

Course Descriptions:

 

comm3010 research & reporting (3 credits)

Prerequisites: COMM1020

The ability to independently research and report on a topic becomes increasingly important at the higher levels of study in a university program. By individually locating, evaluating, summarizing, and organizing secondary research sources and data, students analyze research in relation to a problem they are solving, draft a proposal, write a final report, and present their research to their peers. Students are also given the opportunity to practice effective debating techniques to help them defend a position on a solution to a technical problem. Lectures, debates, presentations, and assignments guide students as they develop their final report.

RSST1001 QUALITATIVE DESIGNS & ANALYSES (3 credits)

 

In this course, students are introduced to philosophical and methodological approaches to qualitative health research. Emphasis is on strategies for critically reviewing, integrating, and disseminating qualitative health research findings. Students conduct critical appraisals and gain skill in the application of research to inform practice.

RSST3001 Research and Statistics (3 credits)

Prerequisites: COMM1020

Familiarity with the core principles of research is important for evidence-based analysis and decision-making across multiple professions. Students understand current best practices in research approaches, designs, and methods associated with both qualitative and quantitative traditions. Further, they utilize the skills and knowledge gained in the course to evaluate sample data sets, conduct analyses, interpret outcomes, and report their findings.

RSST3002 PROBABILITY & STATISTICAL ANALYSIS (3 credits)

Prerequisites: MATH2010

Probability theory and statistical knowledge is important for engineering and other scientific fields as it provides an understanding of how data is collected and analyzed. This introductory probability and statistics course is intended for students in a variety of study areas and research fields. Students apply fundamental concepts in statistics to interpret results of a variety of statistical techniques from descriptive and inferential statistics in order to critically review and analyze statistical information. Students are introduced to various concepts in probability and the use of different probability distributions to solve problems.

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