Introductory Research Methods (SOC*2120)
Code and section: SOC*2120*01
Term: Winter 2025
Instructor: David Walters
Details
Course Prerequisites: ANTH 1150, SOC 1100, IDEV 1000 or SOC 1500
By the end of this course, students should be able to:
Analyze and evaluate qualitative and quantitative research in sociology, anthropology, criminal justice and public policy, and other related fields of study.
Apply appropriate research methodologies to address contemporary, historical, social and global issues.
Develop and practice intellectual curiosity, data (qualitative and quantitative) analytic, problem-solving, critical thinking, decision-making and listening skills.
More specifically, students will learn how to solve problems and address social challenges across a variety fields and industries, within and outside academia. A key objective of this course is to help our students be work-ready when they complete their degree programs. This course will improve career-readiness through promoting skill development and skills awareness. Students will be taught how to communicate complex analyses in easy-to-understand formats and learn how to showcase their knowledge and skills to potential employers. The data analytic component is intended to provide students with opportunities that would otherwise be beyond their reach.
Calendar Description
A general introduction to the process of social research emphasizing research design, techniques of data collection, analysis and interpretation of research results.
Course Content
This course provides an overview of research methodology and the process of conducting social research in academic and non-academic settings. Students will learn skills necessary to become a competent researcher when working with qualitative, experiment and survey data. They will be exposed to a variety of topics relating to research methods including qualitative interviews, field research (also known as participant observation), ethical issues in social research, experimental designs, survey research, qualitative and quantitative sampling, measures of central tendency and dispersion, hypothesis testing, and inferential statistics. They will also be exposed to perspectives on Indigenous research and methodologies in relation to learning and knowledge creation in Canadian higher education institutions.
Through the use innovative and cutting-edge software students will learn how to analyze complex datasets to make a meaningful impact on the social world. They will be responsible for creating a research report using real data that contains information on a variety of social topics (e.g., crime, health, equity diversity, & inclusion). This project will provide them with an opportunity to demonstrate their writing and research related skills to create a journal article/policy report with practical real-life implications. Students will also gain experience using a variety of computer software packages for qualitative (NVivo) and quantitative (SPSS & R) data analyses as well as data visualization (Tableau). With respect to quantitative methods, students will be introduced to common statistical procedures and receive an introduction on how to use artificial intelligence (AI) and machine learning to assist them in data collection and statistical programming. As recent developments in computer software and AI have made advanced statistical analyses much more assessable to social science students, a strong background in mathematics or computer programming is not required for this course.
Please note: Due to the complexity of the research project, this class is not recommended for students in first year. Attending class is extremely important, almost vital, to understand how to complete the research project. We aim to assist everyone in SOAN 2120 as much as possible; however, as there are many students enrolled in this course, we are unable to re-teach an entire lecture to students who miss class. So please do your best to attend all classes. If you plan to take this course and not attend class: May the force be with you!
* IMPORTANT: The dataset for the research project is unique this semester. Students who submit a final project using the incorrect dataset will receive a grade of 0 for the final project. The dataset for the final project will be discussed in depth in class and be available on CourseLink. The expectations for this assignment will be discussed more thoroughly in class. If you miss a component of this course (e.g., the NVivo assignment) you will not receive a zero on that assignment. Instead, the assignment will be reweighted into the Research Project (i.e., the research project will be worth 50 percent).
Required Textbooks
(e-book)
Revel for Basics of Social Research, Fourth Canadian Edition -- Access Code, 4/E Lawrence W Neuman, University of Wisconsin, Whitewater; Karen Robson ISBN-13: 9780135334614
Einmann, Trisha, Dylan Reynolds, David Walters, and Laura Wright (2020). Data Analyses for Qualitative and Quantitative Research. Pearson Education.
Course Software
The qualitative methods software that will be explored in this class is NVIVO. The statistical software packages that we will be using are called SPSS (statistical package for the social sciences) and R. The course software is available (Windows only) in the library and in the computing labs throughout the University of Guelph. All versions of the software used in this course are available to be downloaded through the university with a valid university email account at: https://guelph.onthehub.com/WebStore/Welcome.aspx Instructions on how to download the software will also be provided on CourseLink. Information on how to download R will be provided in class.
Email Communication
As per university regulations, all students are required to check their <uoguelph.ca> e-mail account regularly: e-mail is the official route of communication between the University and its students.
When You Cannot Meet a Course Requirement
When you find yourself unable to meet an in-course requirement because of illness or compassionate reasons, please advise the course instructor (or designated person, such as a teaching assistant) in writing, with your name, id#, and e-mail contact. See the Undergraduate Calendar for information on regulations and procedures for Academic Consideration.
Drop Date
Courses that are one semester long must be dropped by the end of the last day of classes; two-semester courses must be dropped by the last day of classes in the second semester. The regulations and procedures for Dropping Courses are available in the Undergraduate Calendar.
Copies of Out-Of-Class Assignments
Keep paper and/or other reliable back-up copies of all out-of-class assignments: you may be asked to resubmit work at any time.
Accessibility
The University promotes the full participation of students who experience disabilities in their academic programs. To that end, the provision of academic accommodation is a shared responsibility between the University and the student.
When accommodations are needed, the student is required to first register with Student Accessibility Services (SAS). Documentation to substantiate the existence of a disability is required, however, interim accommodations may be possible while that process is underway.
Accommodations are available for both permanent and temporary disabilities. It should be noted that common illnesses such as a cold or the flu do not constitute a disability.
Use of the SAS Exam Centre requires students to make a booking at least 14 days in advance, and no later than November 1 (fall), March 1 (winter) or July 1 (summer). Similarly, new or changed accommodations for online quizzes, tests and exams must be approved at least a week ahead of time.
More information: www.uoguelph.ca/sas
Policy for missed tests:
If you miss a required component of this course, supporting documentation must be provided prior to the due date.
Academic Misconduct
The University of Guelph is committed to upholding the highest standards of academic integrity and it is the responsibility of all members of the University community – faculty, staff, and students – to be aware of what constitutes academic misconduct and to do as much as possible to prevent academic offences from occurring. University of Guelph students have the responsibility of abiding by the University's policy on academic misconduct regardless of their location of study; faculty, staff and students have the responsibility of supporting an environment that discourages misconduct. Students need to remain aware that instructors have access to and the right to use electronic and other means of detection.
Please note: Whether or not a student intended to commit academic misconduct is not relevant for a finding of guilt. Hurried or careless submission of assignments does not excuse students from responsibility for verifying the academic integrity of their work before submitting it. Students who are in any doubt as to whether an action on their part could be construed as an academic offence should consult with a faculty member or faculty advisor.
The Academic Misconduct Policy is outlined in the Undergraduate Calendar.
Recording of Materials
Presentations which are made in relation to course work—including lectures—cannot be recorded or copied without the permission of the presenter, whether the instructor, a classmate or guest lecturer. Material recorded with permission is restricted to use for that course unless further permission is granted.
Resources
The Academic Calendars are the source of information about the University of Guelph’s procedures, policies and regulations which apply to undergraduate, graduate and diploma programs.
Disclaimer
Please note that the ongoing COVID-19 pandemic may necessitate a revision of the format of course offerings, changes in classroom protocols, and academic schedules. Any such changes will be announced via CourseLink and/or class email.
This includes on-campus scheduling during the semester, mid-terms, and final examination schedules. All University-wide decisions will be posted on the COVID-19 website (https://news.uoguelph.ca/2019-novel-coronavirus-information/) and circulated by email.
Illness
Medical notes will not normally be required for singular instances of academic consideration, although students may be required to provide supporting documentation for multiple missed assessments or when involving a large part of a course (e.g., final exam or major assignment).
COVID-19 Safety Protocols
For information on current safety protocols, follow these links:
- https://news.uoguelph.ca/return-to-campuses/how-u-of-g-is-preparing-for-your-safe-return/
- https://news.uoguelph.ca/return-to-campuses/spaces/#ClassroomSpaces
Please note, that these guidelines may be updated as required in response to evolving University, Public Health or government directives.
Turnitin
In this course, your instructor will be using Turnitin, integrated with the CourseLink Dropbox tool, to detect possible plagiarism, unauthorized collaboration or copying as part of the ongoing efforts to maintain academic integrity at the University of Guelph. Turnitin is also used in this class to detect papers created via Artificial Intelligence.
Syllabus
| Attachment | Size |
|---|---|
 SOAN2120 Web Outline W25 - Walters.docx | 32.75 KB |