Research Methods for Interactive Systems

Course manual 2025/2026

Course content

The main goal of the course is to teach students the necessary methods for conducting and evaluating research according to best practices within the multidisciplinary context of Information Science (which combines and integrates psychology, social sciences, and information communication technologies). In particular, the course will explore the application of quantitative psychological research methods (experimental design, statistical analysis) to human-computer interaction (HCI).

Students will engage with research articles, real-world examples, and a research project which will be conducted by the students themselves.

The course aligns with the Human Factors theme, the Data Science theme, and the AV theme on Research Methods. The course builds on aspects of human cognition and perception covered in prior introductory courses (Cognitie en Perceptie). In addition, it builds on the prior courses of Analyseproject, Mathematics for Information Science, as well as Data Science and , while directly preparing students for their thesis.

The central theme of the course is how users interact with complex systems, dynamic or otherwise. We address this overarching theme through research articles from a variety of different subdomains of HCI: including but not limited to user experience with technology, voice assistant interaction, (serious) games, and human-AI collaboration.

Students deepen their statistical knowledge and skills, and conduct their own HCI research (in groups of 3-5 students). The aim is to complete all phases of the research project, from formulating a good question, to choosing and using an appropriate research method, to analysing and interpreting the data collected and finally, to reporting on the research, both orally and in writing. In addition, they gain an understanding of when and how to choose a specific appropriate research design and accompanying statistical tests. This is accompanied by a comprehensive overview of relevant concepts in research design within HCI, including reliability and validity, common constructs and questionnaires in HCI, mixed methods, and a special focus on timely challenges to the field and its methods (e.g., replication crisis concerns).

Study materials

Literature

• Literature is linked to, and the statistics materials are available on Canvas.

Objectives

• The student is able to explain key concepts, methods, and challenges relevant to conducting statistics and researching human-computer interaction.
• The student displays appropriate statistical literacy (able to apppropriately select, conduct, and interpret the most common statistics - descriptive and inferential) in empirical human-computer interaction research.
• The student conducts a coherent empirical research project from start to finish focusing on a question relevant to human-computer interaction.
• The student compiles a research report following best practices that critically reflects on the scientific quality in their own research and in the broader relevant literature.
• The student is able to provide a short presentation about their research to a broad audience.
• The student is able to interpret the most common statistics (descriptive and inferential) in empirical human-computer interaction research.
• The student concisely distills their conducted research and results for presentation.

Teaching methods

• Seminar
• Lecture
• Presentation/symposium
• Self-study
• Working independently on e.g. a project or thesis

The teaching and learning methods used are lectures, seminars, poster presentations, and a group research report.

The course format is as follows: each week will feature one lecture (hoorcollege, 2 hours), one statistics seminar (werkcollege, 2 hours), and one research seminar (werkcollege, 2 hours).

Lecture (hoorcollege):

During the lectures, the academic content of the course (the required reading and associated concepts) will be presented and discussed. In order to prepare for the lecture, students should read the assigned articles (or chapters) and prepare any questions they would like to ask. 

Statistics seminar (werkcollege):

In this seminar, a specific statistical technique will be introduced in the context of its theoretical background, how it is applied and reported. Students will then be given the opportunity to practice applying it through an assignment using R. The material for each week (including relevant data files) will be linked to or provided on Canvas. 

In preparation for the statistics seminar, it is expected that students have:

• a working version of R
• studied any provided relevant materials before attending the statistics seminar each week

Success in this seminar depends on preparation. The goal is to acquire the required prior knowledge independently and to deepen and apply that knowledge during the seminar, and ask any questions that might arise.

The seminar content is assessed through the exam. Students will be expected to write pseudo-code rather than syntactically perfect code, i.e., they must be able to demonstrate an understanding of the necessary logical steps for conducting a statistical analysis in code.  

Research seminar (werkcollege):

In this seminar, students will form groups of 4 students to explore a research question of their own choosing (as long as it concerns a problem relating to human-computer interaction). In rare cases, groups of 3 or 5 can be formed with permission from the TA and the course coordinator. Each week, the TA will guide the students in conducting a specific part of the research: choosing a theme, doing a literature search, writing article summaries, formulating a research question, deciding on an appropriate method and statistical analysis technique, collecting and analysing data, reporting, and final presentation. Each week, the groups will be required to submit the relevant section of their research report, which will culminate in a group report (along with an individual reflection written by each group member). The project will conclude with the resulting (refined) research report and a (poster) presentation.

Learning activities

Attendance

Additional requirements for this course:

This course sets a minimal attendance requirement of 70% for the seminars (statistics and research). When students cannot attend, they should contact their TA prior to the session to be marked as “absence notified”. When students do not meet the requirements for attendance, they cannot finish the course with a pass mark.

Absence in the group presentations requires valid proof of absence (sent to the study councilor) and a written explanation of why the student's contribution can be handled equal in grading to the group members who were present). 

Attendance in the lectures (hoorcolleges) is optional but highly recommended.

Assessment

Passing the Course:

To pass the course, the following requirements must be met

• the average of both exam grades must each be 5.5 or higher
• the combined average of the graded seminar components (group research report and group research poster presentation) must be 5.5 or higher
• the individual reflection for the research seminar project must be submitted and meet the necessary requirements to pass (not graded)

In the event that a student does not pass the overall exam grade requirement, they can take the resit exam, the result of which is then their grade for the overall exam grade component. There is no retake option for the overall seminar exam grade requirement (except in very rare circumstances which must be handled in consultation with the study councillor).

Bonus rule:

Those groups that for the final report draft deliverable on May 18th submit an *actual* final report draft in the way that is intended - i.e., one that is actually only in need of polishing; an "accept with minor revisions" in peer review terms - are eligible for a 0.5 point bonus on the group research report grade component.

Criteria for this bonus:

1. It must have a title and complete appendix. 
2. The final report draft must fulfill the research report checklist provided in Canvas in terms of content. 
3. It must be within a 10% margin of the maximum word counts listed for each section. E.g., the method section has the final maximum word count of 1250 words > the draft of this section must be between 1125 and 1375.

Late Policy:

Any assignment submitted past the due date will be graded with a 10% penalty on a sliding scale based on 24 hour blocks. For example, if it was submitted within 24 hours late, what was initially graded an 8.5 would become a 7.5; at 24+ hours late the 8.5 becomes a 6.5; at 48+ hours late the 8.5 becomes 5.5, and so on.

The group presentation is an exception to this: the slides need to be uploaded on Canvas as a requirement to receive the grade for this seminar component, but the late policy does not apply as the grade refers to the presentation itself – there is no option for late presentations.

Inspection of assessed work

The manner of inspection will be communicated via the digitial learning environment.

Assignments

Group research project report

• The research seminar is devoted to the students' own research, which will be developed in groups. Each week, the students' research project will be discussed and progressed during the seminar: choosing a theme, doing a literature search, writing article summaries, formulating a research question, deciding on an appropriate method and statistical analysis technique, collecting and analysing data, and rigorous, comprehensive reporting. Each week, the groups will be asked to submit the relevant section of their research report for feedback, which will culminate in a group report. The final group research report is graded.

Group research project presentation

• The research project will also conclude with a presentation, that presents the conducted research project to a more generalized audience. The presentation will be accompanied by a poster that needs to be submitted; the grade covers the poster and the presentation on the final assessment day. 

Individual reflection

• Each student will also submit an individual reflection that describes their own contribution(s) to the group research project. This is not graded (pass/fail) nor is feedback provided, however, its contents can inform the grading of the group research project components and support the handling of group disputes in the event of conflicts. 

The course contains the following assignments:

• Research report (group) with reflection (individual)
• Poster presentation of research project (group)

In addition, students are given multiple deadlines for submitting early drafts of the various sections of the research report, and can then receive feedback on this from their peers and the tutors.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Additional information

Canvas:

This course has a Canvas site, where you will find all relevant materials - including required reading! - and information. This is also where you upload your assignments. It is your responsibility to check it regularly and ensure that any Canvas announcements come to your attention reasonably quickly. 

Contact information

Coordinator

• dr. K.S. Rogers

Staff

• Tjomme Schilstra MSc
• Sanne van den Berg MSc