Courses listed here may be of interest to CS HCI and KMDI students who require training in qualitative and quantitative research methods.

A number of considerations went into the list below. The courses should have wide  applicability (generalist, survey). The department offering the course should be receptive to students from other departments. Ideally, the offering department would be a member of the Collaborative Program in KMD, a program with which CS is affiliated and in which cross-departmental enrollment is normal (departments represented in this course list that are KMDI/CS collaborators are highlighted in 3.2 below). Finally, the courses would be established courses, offered each year. 

Note: While all courses listed here were reported to be regular features of the department's curriculum, be aware that the content and focus of a particular course may alter from year to year and even established courses may not be offered some years. Refer to current course calendars or inquire directly with the department (department web sites are linked in 3.2 below). When considering a cross-departmental course, always contact the instructor to discuss research interests and background before attempting to enroll.

The courses are simply listed in section 1. Section 2 provides contact information, descriptions, comments and, when available, most recent syllabi.

CONTENTS

1. Course List
1.1. Qualitative
1.2. Quantitative
2. Annotated Course List
2.1. Qualitative
2.2. Quantitative
3. Appendices
3.1 Other Courses
3.2. Course Designator Acronyms and Departments

FIS 3005Y Advanced Seminar in Research Methodologies

Department: Faculty of Information Studies
Instructor: Lynne Howarth; 416-978-4666; howarth@fis.utoronto.ca
Description: A critical examination of the nature and function of theoretical and applied research in information studies. Involves study of the principal methodologies currently accepted for the preparation of doctoral theses in these fields
Comments: Restricted to PhD students. Cross-departmental enrollment unlikely. Note: This is a full year (Y) course.

 

SOC 6301H Survey Research Methods

Department: Sociology
Instructor: Bill Magee; 416-978-5405; magee@chass.utoronto.ca
Description: This course deals with selected issues in survey research and with practical issues in survey construction. The former includes issues of epistemology, measurement, bias, validity, and generalization. The latter includes issues related to planning and running a survey, and making best use of available data and resources.
Comments: Course will be taught next year by Dean Behrens. The tentative plan is to offer it alternating years. The course regularly draws students from many departments (eg. Nursing, Geography, Physical Education).
Syllabus: [Magee, 2004/5]

SOC 6303S Field Methods

Department: Sociology
Instructor Michael Bodemann; 416-946-5897; bodemann@chass.utoronto.ca
Description: A generalist’s survey of qualitative methods. Currently this is
Sociology's required qualitative methods course. Students learn about field
methods and are required to do a major paper that involves the collection of their own qualitative data.
Comments: 2005-06 is the last year that this will be the required course. The intention is to offer it on a semi-regular basis, though probably not every year once it is no longer required.
Taught in 2004/5 by Judith Taylor (416-946-5720; jtaylor@chass.utoronto.ca).
Syllabus: [Taylor, 2004/5]
 

SOC 6712H Qualitative Methods I

Department: Sociology
Instructor: Judith Taylor; 416-946-5720; jtaylor@chass.utoronto.ca.
Description: This is a course that explores a variety of qualitative methods techniques such as
interviewing, observation, etc. Students also learn a bit about analysis and qualitative software. Students do a paper as part of a larger group qualitative data collection project.
Comments: This course will be the required qualitative methods course starting in 2006-07. It will be offered every year. Taylor has welcomed cross-departmental students in previous courses but if this course becomes required it may put pressure on enrollment numbers.
 

SOC 6713H Qualitative Research Methods II—Qualitative Interviewing

Department: Sociology
Instructor: Ping-Chun Hsiung; 416-287-7291; pchsiung@utsc.utoronto.ca
Description: This seminar focuses on the “technical aspect” of qualitative interviewing, taking students through all the steps in conducting and analyzing qualitative interviews. It is conceived as a course that would be useful after taking  Qualitative Methods I (the broad survey) and/or if a student needed to gain expertise in qualitative interviewing for their research.
Comments: Ping-Chun Hsiung has taught fieldwork methods and qualitative interviewing on a regular basis for 8 years. Study materials may not have wide relevance to students outside Sociology (i.e. primary interview data about immigrant families). Hsiung plans to offer this almost every year with a focus on qualitative interviewing.
Syllabus: [Hsiung, 2004/5]

CHL 5111H Qualitative Research Methods

Department: Public Health Science (CHL="Community Health": code designator)
Instructor Milada Disman; 416-534-310; milada.disman@utoronto.ca
Description: Generalist introduction. The course objectives are: To address the basic principles and practices of qualitative research; To provide an understanding of a wide spectrum of qualitative approaches to inquiry; To provide a comprehensive overview of the main field research strategies for qualitative research; To develop critical understanding of the strength and weaknesses of qualitative inquiry.
Comments: Milada Disman comments: “It is a generalist's introduction to qualitative methods. Qualitative course needs to include examples of studies from a substantive area. Therefore, the readings include a textbook on methodology as well as articles on health related studies. I always welcome students from other departments. These students usually do well in the course and often contribute an interesting perspective to the materials under discussion.”
Syllabus: [Disman, 2004/5]

CHL 5115H Qualitative Analysis and Interpretation

Department: Public Health Science (CHL="Community Health": code designator)
Instructor Joan Eakin; 416-978-8502; joan.eakin@utoronto.ca
Description: This is an advanced graduate-level course in qualitative research methodology that focuses on the theory, techniques and issues of data analysis and interpretation. The course is intended for individuals who already have basic experience with qualitative research methods, either through coursework or comparable research experience. The course is designed for students taking qualitative approaches to their research
Comments: Joan Eakin, has background in Sociology. Course is open to cross-departmental students. The instructor comments “I have students from varied backgrounds - lots from the health sciences (professional, or biological sciences backgrounds), others from the social sciences and humanities. If a student from computer science had a background in qualitative (i.e. some other course work, or some major involvement as a research assistant or something) he/she would be in ok shape, except that some experience with social science is really advised - it is hard to do interpretive qualitative research without some discipline based theory to draw on. Best thing is for the student to consult with me about the course and their backgrounds.”
Syllabus: [Eakin, 2004/5]

CHL 5150H Social Science Research Design: Applications to Health Issues

Department: Public Health Science (CHL="Community Health": code designator)
Instructor Kim Bercovitzk; bercovitzk@smh.toronto.on.ca
Description: To provide a critical survey of the various approaches and methodologies used in applying the social sciences to health-related research, and to use the knowledge gained to develop a research proposal. The course objectives are: To examine the assumptions of a number of different research approaches and understand how these assumptions determine how problems are conceptualized; To learn about various research methods and demonstrate the ability to apply these methods in developing and answering research questions; To develop a research proposal integrating knowledge acquired in the course
Comments: Cross-departmental opportunity unknown. Although a PHS course specific health-content may be limited: the course is a survey of methods with a generalist reading list.
Syllabus: [Bercovitzk and Strike, 2004/5]

AEC 1405H Introduction to Qualitative Research

Department: Adult Education, Community Development and Counselling Psychology, OISE/UT
Instructor: Bonnie Burstow; 416-923-6641x2740; bburstow@oise.utoronto.ca
Description:  This course articulates various theoretic groundings for qualitative research and helps students become conversant with a wide variety of qualitative methodologies (i.e. grounded theory, feminist interviewing, ethnography, participatory research, bibliographic analysis, and institutional ethnography). Gathering of information through observation, participatory observation, dialogue, and collection of documents will be considered. Emphasis is on both understanding and practice. Learners will design or co-design a concrete piece of research and take it to through the ethical review process. They will also present on at least one methodology. In line with this, they will learn about ethical conundrums, about matching methodologies with objective and values, and about methods for choosing participants. There is special emphasis on becoming critically aware as researchers – on understanding and integrating issues of power and difference
Comments: Most students who take the course are doctoral students about to embark on their doctoral research. The course is open to students of all disciplines but is targeted for those who are in an applied area. Occasionally, external students have taken the course. They did not face problems and found the course useful. NOTE: 1405 and 1406 are complementary. Once enrollment is full in 1405, priority for adding students goes to people who have already enrolled for 1406 and after that to people intending to enroll in 1406.

AEC 1406H Introduction to Qualitative Research – Part II

Department: Adult Education, Community Development and Counselling Psychology, OISE/UT
Instructor: Bonnie Burstow; 416-923-6641x2740; bburstow@oise.utoronto.ca
Description:  This course begins where Part I leaves off. Learners will deepen their knowledge of a wide variety of qualitative research methodologies. They will gain skills interviewing, judging research, exploring dilemmas, and becoming critically aware as researchers. Their primary activity will be carrying out and completing the research project designed and approved in Part I. Giving and getting help from classmates is an integral part of the process.
Comments: See comments for 1405 above. Intended as complement to 1405.
 

HDP 3201 Qualitative Research Methods in Human Development and Applied Psychology

Department: Department of Human Development and Applied Psychology, OISE/UT
Instructor: Richard Volpe; 416-934-4511; rvolpe@oise.utoronto.ca
Description: This course provides an overview of qualitative research methodology and techniques. Coverage includes major philosophy of science, historical, and contemporary (critical, post- modern, hermeneutic, constructivist and feminist) perspectives. Ethnographic, life history, individual and multiple case study, and focus group methods will be reviewed in relation to a narrative framework. Observational, interview, personal record, and archival data management will be discussed. Students will have an opportunity to design, implement, analyze, and report a micro qualitative study. Special emphasis will be placed on the use of computers and visual imaging techniques.
Comments: Rick Volpe comments: “The course is intended to be open and has worked very well as a bridge between disciplines.”

 

MIE 1402H Experimental Methods in Human Factors Research

Department: Mechanical and Industrial Engineering
Instructor: Mark Chignell; 416-978-8951; chignell@mie.utoronto.ca
Description: The course deals with practical problems associated with the design of experiments in Human Factors research, with an emphasis on the use of statistical packages and data analysis tools.  Topics covered will include analysis of variance, non- parametric statistics, balanced and unbalanced block designs (including Latin squares), confidence intervals, etc.  Stress is given to practical problems and the intuitive understanding of applied statistics.
Comments: Instructor would admit cross-departmental students. The course was designed as an MIE substitute for Ian Spence’s Design of Experiments course at Department of Psych. Course content varies from year to year, with three standard approaches to teaching. Version 1: Experimental design, with associated ANOVA analyses. Version 2: General Linear Model - ANOVA, regression, discriminant analysis, including dummy variable coding of ANOVA designs within a regression model. Version 3: Questionnaire design and analysis using factor analysis and reliability analysis.
Syllabus: [Chignell, 2004/5]

MIE 1403H  Methods in Human Factors Research

Department: Mechanical and Industrial Engineering
Instructor: Paul Milgram; 416-978-3662; milgram@mie.utoronto.ca
Description:  This course is intended for people carrying out graduate level research in Human Factors.  It covers a variety of techniques for recording and analyzing empirical data.  Topics to be covered include psychophysical methods, subjective scaling, questionnaires, signal detection theory, information theory, physiological monitoring, spectral analysis, tracking, and manual control modeling.  There is no textbook for the course.  Evaluation is based on a series of assignments related to the topics covered in class.
Comments: Instructor would admit cross-departmental students. The ability of any particular student to thrive in this course though would depend on background.  For example, the final section on manual tracking might be difficult for students who have no background in math, or control theory, or the like. Instructor typically divides course into three sections (roughly following a S-C-R (=Stimulus - Cognition - Response): approach to human functioning): 1 The first section deals with techniques for estimating things like perceptual thresholds, and covers classical psychophysics, signal detection theory, direct and indirect scaling, etc.  In that sense, I would say that it is definitely qualitative.  I always assume that any student with a background in (experimental) psychology should find this section easy;  however, I have yet to acquire any data that substantiate that hypothesis. 2.The second segment could be considered "qualitative.”  It covers topics like verbal protocol analysis, questionnaire design, and other knowledge elicitation techniques. 3 The third segment is, once again, very quantitative, and involves some (relatively) hard-core engineering modelling of human manual control.  Students without a good engineering, or mathematical, background would find this section the most difficult.
Syllabus: [Milgram, 2004/5]

PSY 330H Psychometrics

Department: Psychology
Instructor: David Goldstein; 416-978-3405; dgoldst@psych.utoronto.ca
Description: This second-year undergraduate psychology course examines human development from conception to death. The focus will be on physical, cognitive, social, and emotional development across infancy, childhood, adolescence, adulthood, and old age
Comments: Instructor is receptive to graduate students and cross-departmental enrollment. “Graduate students have taken my undergraduate course in Psychometrics (PSY 330) in the past and it would be ok with me to do it again in the future.”
Syllabus: [Goldsteinl, 2004/5]

PSY 2001H Design of Experiments I

Department: Psychology
Instructor: staff
Description: This course is designed to introduce the student to the General Linear Model and two of its most common expression: Analysis of Variance and Multiple Regression. Additionally, student will be asked to familiarize themselves with some of the current theoretical issues in realm of data analysis itself, e.g., the value of testing the null hypothesis.
Comments: Frequently taught by Doug Bors, the course will now be taken on by another faculty member, as yet unspecified.
 

PSY 2002H Multivariate Statistical Inference

Department: Psychology
Instructor: McIntosh
Description: Starting from the basis of the General Linear Model, this course will examine various multivariate methods from the perspective of what sort of inferences they support. Methods covered will include: multiple regression, canonical correlation, principal components and factor analysis, MANOVA and discriminant analysis, path analysis with some time devoted to newer methods such as partial least squares. The goal is for the student to gain a conceptual appreciation for the relations between these methods, and an understanding for when to use one over another.

PSY 2005H Structural Equation Modeling

Department: Psychology
Instructor: Cunningham
Description: Structural equation modeling is a powerful and general data analysis technique for testing theory guided questions of quantitative data. Topics such as using multiple indicators, construct validity and reliability, model identification and estimation, and model fit are covered in the context of the major programs for SEM analyses (e.g., LISREL, Mx).

STA 1001H Applied Regression Analysis

Department: Statistics
Instructor: staff
Description: Analysis of the multiple regression model by least squares; statistical properties of the least square analysis, including the Gauss Markov theorem; estimate of error; residual and regression sums of squares; distribution theory under normality of the observations; confidence regions and intervals; tests for normality; variance stabilizing transformations; multicollinearity; variable search method.
Comments: Course primarily designed for students from other departments. Prerequisites still listed (consult with instructor). Also listed as undergraduate course STA302H1. Only students outside statistics can take the course for graduate credit.

STA 1003H Sample Survey Theory and its Application Department: Statistics
Instructor: staff
Comments: Course description to follow or contact department. Course primarily designed for students from other departments. Prerequisites suggested. Also listed as undergraduate course STA322H1. Only students outside statistics can take the course for graduate credit.

STA 1004H Introduction to Experimental Design

Department: Statistics
Instructor: staff
Comments: Course primarily designed for students from other departments. No other information available.

STA 1005H Applied Multivariate Analysis

Department: Statistics
Instructor: staff
Description: Practical techniques for the analysis of multivariate data; fundamental methods of data reduction with an introduction to underlying distribution theory; basic estimation and hypothesis testing for multivariate means and variances; regression coefficients; principal components and the partial multiple and canonical correlations; multivariate analysis of variance; profile analysis and curve fitting for repeated measurements; classification and the linear discriminant function. There will be extensive use of statistical computing packages.
Comments: Course primarily designed for students from other departments. Prerequisite listed. Also listed as undergraduate course STA437H1. Only students outside statistics can take the course for graduate credit.

STA 1007H Statistics for Life and Social Scientists

Department: Statistics
Instructor: staff
Description: This course is specifically designed for life and social scientists. The course will cover many of the more advanced statistical methods (particularly, multivariate methods) used in the life and social sciences. The emphasis will be on learning how to be a critical user and interpreter of the appropriate methodologies. Data analytic methods will be emphasized. Some understanding of the relevant statistical theory will be required; however, the mathematical requirements will be kept to a minimum. The statistical software package SAS will be used to analyze data. No previous knowledge of this software is required and all relevant documentation will be made available to students as needed
Comments: Course primarily designed for students from other departments. No prerequisite. Also listed as undergraduate course STA429H1. Only students outside statistics can take the course for graduate credit.

STA 2101H Methods of Applied Statistics I

Department: Statistics
Instructor: staff
Description: The course gives an introduction to resampling methods and modern regression tools with the following approximate coverage. There is no official text but the references below are useful. S-Plus (or R) is the software package used. Bootstrap resampling: Statistical functional; empirical distribution; plug-in estimates; bootstrap simulation; bootstrap estimates of bias and variance; bootstrap-t; percentile interval; hypothesis testing; relationship to the jackknife. Smoothing and modern regression: Histograms; kernel density estimation; linear regression; least squares; scatterplot smoothing; penalized least squares; splines; smoothing parameters; cross validation; Mallow's Cp; degrees of freedom; F-tests; additive models; backfitting; logistic regression; generalized linear models; iterated weighted least squares; Fisher scoring; generalized additive models; penalized likelihood; iterated weighted backfitting; regression trees; recursive partitioning regression; projection pursuit; neural networks; MARS.
Comments: Open to cross-departmental enrollment at graduate level. Also offered as undergraduate course STA442H1.

STA 2004H Design of Experiments

Department: Statistics
Instructor: staff
Description: Experimental design is a classical foundation of statistical methods, developed initially by R.A. Fisher and many followers in the context of agricultural field trials at the Rothamsted Experimental Station, and widely used and developed in the thirties, forties and fifties in agricultural colleges throughout the United States.  The ideas developed for the design and analysis of experiments, including randomization, orthogonality, analysis of variance, and so on permeate all modern methods of statistics.  More recently design issues are being emphasized in off line quality control, response surface methodology,
and computer experiments.
 

HDP 1287H Introduction to Applied Statistics

Department: Human Development and Applied Psychology, OISE/UT
Instructor: Guanglei Hong
Comments: This is one of the courses in the now defunct Measurement and Evaluation program. It will be offered again but no further information is available. Cross-departmental opportunities may be limited. Re-registration is closed to OISE students. However, the instructor is interested in student sharing with KMDI, which offers courses of interest to OISE students. Syllabus is from previous offering by Childs
Syllabus: [Childs, 2004/5]

HDP 1288H Intermediate Statistics and Research Design

Department: Human Development and Applied Psychology, OISE/UT
Instructor: Ruth Childs; rchilds@oise.utoronto.ca / Richard Wolfe; rwolfe@oise.utoronto.ca
Comments: This is one of the courses in the now defunct Measurement and Evaluation program. It will be offered again but no further information is available. Cross-departmental opportunities may be limited. Re-registration is closed to OISE students. However, the instructor is interested in student sharing with KMDI, which offers courses of interest to OISE students. Syllabus is from previous offering by Childs
Syllabus: [Childs, 2004/5]

HDP 1289H Multivariate Analysis with Applications

Department: Human Development and Applied Psychology, OISE/UT
Instructor: Richard Wolfe; 416-923-6641x2233; rwolfe@oise.utoronto.ca
Comments: One of the courses in the now defunct Measurement and Evaluation program. It will be offered. The course is open to cross-departmental enrollment.

HDP 3227H Multi-Level Modeling in Social Scientific and Educational Research

Department: Human Development and Applied Psychology, OISE/UT
Instructor: Guanglei Hong
Comments: One of the courses in the now defunct Measurement and Evaluation program. It will be offered. The course is open to cross-departmental enrollment.

HDP 3238H Special Topics in Human Development and Applied Psychology: Doctoral Level: Tables, Charts, and Statistical Writing

Department: Human Development and Applied Psychology, OISE/UT
Instructor: Richard Wolfe; 416-923-6641x2233; rwolfe@oise.utoronto.ca
Comments: One of the courses in the now defunct Measurement and Evaluation program. It will be offered. The course is open to cross-departmental enrollment.

For example, the Department of Social Work offers “SWK 4501H Social Work Research Methods I - Qualitative Techniques” and “SWK 4502H Social Work Research Methods II - Quantitative Techniques”, and the Department of Physical Therapy offers REH 1620H "Methodological Issues in Research on Ageing and Health,” a course whose focus is on methodological issues  in conducting quantitative and qualitative research specifically with older adults.

Students interested in broader course sampling should consult the course calendars for departments. See the SGS directory of graduate programs: http://www.sgs.utoronto.ca/current/calendar/gradprogs.asp