GRA 6145 Human-Technology Interaction
GRA 6145 Human-Technology Interaction
We are increasingly surrounded by digital technology. Personal computers, smartphones, social media, intelligent personal assistants, chatbots, smart speakers, and social robots are key technologies of the digital revolution that shape our everyday lives in myriad ways. Understanding how humans interact with such technologies and what impact design has becomes ever more important. This course intends to equip students with the concepts, tools and methods to analyze and understand human interaction with digital technologies.
The course considers how technology mediates communication practices, acting as a medium for human-to-human interaction (thus interfacing with the Human-Human Interaction course), as well as how people engage with digital technology as an actor in itself through human-machine communication. In the course, students will learn about psychology and communication research in user interaction with information technologies. Students also get familiarized with interaction design and how persuasive information technologies are created. Finally, ethical and sustainability-related questions will be discussed in the course, touching on aspects such as bias, fairness, trust, transparency and environmental sustainability.
After taking this course, students should have acquired knowledge of:
- Key theories of human-technology interaction, including the role of user characteristics, technology characteristics, and contextual characteristics
- Psychological and communication principles that shape human-technology interaction
- The value of a thorough human-technology interaction understanding in practice and in different professional areas
- The importance of ethical and sustainability-related issues when it comes to human-technology interaction
After taking this course, students should be able to:
- Develop their own user- and design-oriented research project within a human-computer interaction perspective
- Apply different human-technology interaction methods such as user experiments and A/B testing, user-centered surveyes, socio-technical walkthroughs, and design-centered interviewing techniques (e.g., think-aloud protocol)
After taking this course, students should:
- Have developed a holistic understanding of human-technology interaction that goes beyond technology determinism and human determinism
- Be up-to-date about current debates in the area, especially in light of AI and smart systems
- Be able to interpret and critically evaluate human-computer interaction, human-robot interaction, human-machine communication and adjacent research
- Be able to reflect on the limitations of human-technology interaction
- Understand the social embeddedness of human-technology interaction, especially its ethical implications, including aspects of intersectionality, marginalization, and representation/inclusivenes
Fundamentals and Psychologically-oriented Human-Technology Interaction (HTI)
1. Introduction to the course: Fundamentals and theoretical foundations of HTI
2. User characteristics and the information systems use lifecycle: The role of human factors; adoption, continued use and discontinuance of technology
3. Technology characteristics in HTI: The role of design principles, persuasive technology, and system architecture in user behavior
4. Contextual factors in HTI: Context-of-use and its role particularly in mobile technology interaction
HTI Methods
5. Methods for HTI 1: Qualitative approaches for studying and evaluating user behavior
6. Methods for HTI 2: Quantitative approaches for studying and evaluating user behavior
Communication-Oriented HTI, Including Human-Machine Communication (HMC) and Computer-Mediated Communication (CMC)
7. Communication-oriented HTI: Introduction
8. Important theories and concepts in HMC: Computers Are Social Actors (CASA), Actor-Network Theory, Affordances
9. Interaction with disembodied “smart” and AI-driven technology: Chatbots, social media algorithms, augmented reality
10. Interaction with embodied “smart” and AI-driven technology: Social robots, smart speakers, virtual reality
Practicals
11. Guest lecture(s) and/or lab visit
12. Student presentations
- Lectures (with individual and interactive exercises)
- Collaborative group activities (discussions, debates etc.)
- Guest lectures
- Research project
- Self-study
Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class.
All parts of the assessment must be passed in order to get a grade in the course.
All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.
Disclaimer
Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.
Assessments |
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Exam category: Activity, Oral Form of assessment: Presentation Exam/hand-in semester: First Semester Weight: 30 Grouping: Group (2 - 4) Duration: 20 Minute(s) Comment: The students have to deliver a short group presentation and discussion towards the end of the course. The presentation should cover a user-centered analysis of an existing digital technology such as an app, a website, a digital platform, a smart speaker, or a chatbot and employ methods taught in the course. Exam code: GRA 61452 Grading scale: ECTS Resit: Examination when next scheduled course |
Exam category: Submission Form of assessment: Submission PDF Exam/hand-in semester: First Semester Weight: 70 Grouping: Group (2 - 4) Duration: 1 Semester(s) Comment: As the final deliverable of the course, the students have to submit a term paper in the form of a structured research report. The submission expands on the user-centered analysis in the group presentation and should contain a short literature review, a methods section, a results section, and a discussion section, where the practical implications of the analysis is discussed. Exam code: GRA 61453 Grading scale: ECTS Resit: Examination when next scheduled course |
All exams must be passed to get a grade in this course.
Activity | Duration | Comment |
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Teaching | 36 Hour(s) | With individual and interactive exercises |
Student's own work with learning resources | 124 Hour(s) |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.