Spring 2021 - IAT 802 G100

Quantitative Research Methods and Design (3)

Class Number: 6818

Delivery Method: Remote


  • Course Times + Location:

    Mo 2:30 PM – 5:20 PM

  • Prerequisites:

    Graduate student status.



Introduction to the research enterprise from a quantitative perspective. It covers structures of research that are prevalent across fields, introduces research methodologies and tools, teaches methods for interdisciplinary work and fosters a critical discourse around differences among research in different areas.


**NOTE** This course outline is from the Spring 2021 semester and is subject to change. 

Course Description & Motivation

Your education, research, and thesis work at SIAT (and beyond) requires you to engage in various forms of doing and communicating research. Moreover, your success at SIAT and beyond will in part be evaluated based on the quality of your own research and communication thereof. The overarching goal of this course is to help you develop the knowledge & skills essential for designing and conducting proper scientific and quantitative research, as well as critically analyzing, discussing, and communicating it. In sum, IAT 802 is an introduction to experimental design and research methodologies where quantitative approaches are appropriate. There will be a particular focus on research design for HCI and the sciences.

In Spring 2021, This course will be offered remotely and synchroneously using a videoconferencing system (e.g., Zoom or BB collaborate ultra built into our course management system Canvas). Students are expected to join all the live sessions during the scheduled course time, actively engage and contribute. If possible it would be great if you could have your video cameras on during class to facilitate communication, teambuilding, and feedback. Please make sure you have a suitable webcam and microphone and stable internet connection ready and tested before class, and if possible a setting where you will not be disturbed. 


Course Objectives, Learning Goals & Outcomes

The course structure and teaching/learning activities are designed around the following questions. That is, by actively participating in this course, student should be able to effectively address the following questions and perform the respective tasks:
1)    What is science, the “scientific method” and quantitative research? How do you think and argue like a good scientist?
2)    Why do science? What is scientific & quantitative research useful for?
   a)    Why could you be excited about science? What drives and excites a researcher?
   b)    What are advantages and disadvantages of quantitative & scientific research methods (as compared to other methods)? That is, what are they appropriate and useful for?
3)    What to research? Why research something?
   a)    How to devise effective research questions and hypotheses?
 b)    How to effectively motivate research questions?
4)    How to use quantitative & scientific methods properly, carefully & effectively?
   a)    Experimental design: How to design an effective experiment? What does effective mean?
 b)    Descriptive statistics: How to present data effectively? What does effective mean?
   c)     Inferential statistics: What can you conclude from quantitative data? Why? What are your chances of being wrong? How do you decide which statistical methods to use? How to apply them properly? How to do this in a given statistical analysis software?
5)    How to communicate all that effectively and scholarly?
6)    How to critically evaluate and discuss the quality of quantitative / scientific research (of yourself and others)?


  • JiTT/Reflection papers, short in-class quizzes & presentations, participation & peer evaluations/reviews 10%
  • Iron Researcher test(s): Analyze provided data & write up in scholarly manner 25%
  • Research project pitch: short written proposal + presentation 8%
  • Final project presentation in SIAT research colloquium 12%
  • Final written project report 45%
  • NOTE: Regular attendance and active, supportive participation in class and team activities is necessary to pass; else could result in point reduction/no-pass. In particular, failure to contribute sufficiently to in-class activities, individual and team assignments, failure to responsibly do your part of the teamwork, or failure to reliably attend and contribute in team meetings can result in additional point reductions beyond the participation & peer evaluation. NOTE: To be eligible for full marks in the major assignments, you must complete the corresponding weekly in-class activities. Although these may not be formally marked, completion of these activities is a prerequisite for the corresponding major assignments, and failure to complete them appropriately could result in overall point reduction. Any kind of plagiarism or other forms of academic dishonesty will automatically result in 0 points for that assignment, and potentially in more serious consequences including course failure


Teaching/learning activities may include
• Interactive lecturing and demonstrations
• Group discussions (in-class and online chat- and discussing forums)
• Short in-class writing activities • Weekly reading, writing and/or revision/reviewing assignments
• Weekly short written reflection papers (JiTTs) that provide the basis for in-class discussions and activities
• Roughly bi-weekly in-class mini-quizzes (adapted from Team-Based Learning concepts)
• Online and in-class tutorials on experimental design, probability, and statistics
• Group research projects (early in semester) and final individual research projects where students get a chance to work with actual data
• Group/individual feedback
• Peer-reviewing (formal & informal)
• Student presentations (including elevator pitch presentations and final public project presentation)
• Teams of 2-4 students each will be used for focused teamwork both in- and out-of-class

Student presentations from previous course offering can be found at iSpaceLab.com/Riecke/Teaching/#802   

Several items provided in this course and through Canvas or other means have been copied of the Copyright Act as enumerated in SFU Appendix R30.04A - Application of Fair Dealing under Policy R30.04. You may not distribute, e-mail or otherwise communicate these materials to any other person.


There are no formal pre-requisites apart from a graduate student status. although IAT804 will be quite useful. If you have never taken any quantitative research methods courses before, make sure to reserve enough time for reading especially during the first half of the course. 



Software needed: JMP & Microsoft Word (download from http://www.sfu.ca/itservices/technical/software.html)
If possible, bring a laptop and something to write to class every time. 


"How to Design & Report Experiments" (2003) by Andy Field, Graham J. Hole; 1st Edition; Sage Publications [this is the main textbook we’ll use – make sure to have your own copy by the first week of the semester!]

ISBN: 9780761973836

Open Learning Initiative Statistics courses (online learning modules such as https://oli.cmu.edu/courses/statistical-reasoning-copy/ or https://oli.cmu.edu/courses/causal-and-statistical-reasoning-open-free/, potentially with a $25.00 fee)

additional materials provided through Canvas/online


"Discovering Statistics Using R" (2012 or later) by Andy Field, Jeremy Miles, Zoe Field; Sage Publications Ltd
ISBN: 9781446200469

"Experimental Design:  From User Studies to Psychophysics" (2011) by Douglas Cunningham, Christian Wallraven; 1st Edition; A. K. Peters/CRC Press
ISBN: 9781568814681

“Applying Contemporary Statistical Techniques” (2002) by Rand R. Wilcox; 1st Edition; Academic Press

ISBN: 9780127515410

"Methods in Psychological Research" (2013 or later) by Annabel Evans, Bryan Rooney; 3rd or later Edition; Sage Publications
ISBN: 9781452261041

"Discovering Statistics Using IBM SPSS Statistics" (latest edition) by Andy Field; Sage Publications Ltd
ISBN: 9781446249185

"A First Course in Design & Analysis of Experiments" (2000) by Gary W. Oehlert; W. H. Freeman (.pdf of book & data sets available online); this book is out of print
ISBN: 9780716735106

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

Registrar Notes:


SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html


Teaching at SFU in spring 2021 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.

Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112).