Information on individual educational components (ECTS-Course descriptions) per semester

  
Degree programme:Master Computer Science
Type of degree:FH Master´s Degree Programme
 Full-time
 Winter Semester 2024
  

Course unit titleHuman-Machine-Interaction in Context
Course unit code024913110403
Language of instructionGerman
Type of course unit (compulsory, optional)Elective
Semester when the course unit is deliveredWinter Semester 2024
Teaching hours per week2
Year of study2024
Level of course unit (e.g. first, second or third cycle)Second Cycle (Master)
Number of ECTS credits allocated4
Name of lecturer(s)Karl-Heinz WEIDMANN


Prerequisites and co-requisites

Basic knowledge of HCI is required. This includes basic knowledge of human communication and information processing according to the ABCS concept by Ritter et al. (Ritter; Baxter; Churchill 2014) Ritter, Frank E .; Baxter, Gordon D .; Churchill, Elizabeth F. (2014). Furthermore, basic knowledge of contextual design (persona, scenarios) according to Holtzblatt et al. (Holtzblatt; Beyer 2016) and evaluation (Rubin 1994) (such as paper prototyping see (Snyder 2003) and expert evaluation see (Nielsen; Mack 1994)) are required.

Jeff Johnson (Johnson 2021) and Donald A. Norman (Norman 2013) are recommended for guidance.

Course content

Selected advanced user experience and usability topics in the areas:

  • Human decision-making
  • Application of Cognitive Science
  • UI patterns
  • Visualization and animation
  • Universal Access
  • Designing for security and privacy
  • Adaptive user interfaces
  • Alternative, pervasive, small and no-display I / O interfaces
  • Human AI Interaction (Agents and avatars / Agent Human Collaboration)
  • Mobile / ubiquitous / wearable computing
Learning outcomes

The students know various extended user experience and usability concepts for their field of application, can critically question them and develop application scenarios.

The focus is initially on getting to know (factual knowledge) the specialist areas and their overall location (meta-cognitive aspects of knowledge).

The conceptual knowledge is deepened independently and analyzed in the group in order to then implement the expansion through combination, recoil, variation, transposition, analogy, adaptation and mutation of what has been learned on the basis of research (analysis and synthesis) in individual tasks (level of evaluation and Create).

Planned learning activities and teaching methods
  • Critical "reception"
  • Discussions and free lectures
  • Case study: The students create 10-minute tutorial videos on the selected topic with a written bibliography to which reference is made.
  • Reflection: Finally, the students work on a questionnaire on the individual video tutorial contributions from their colleagues
Assessment methods and criteria

Participation, scientific essay (paper): Problem statement, discussion, paper and presentation (60%) and final synthesis report (40%).

For a positive grade, a minimum of 50% of the possible points must be achieved in each part of the examination.

Comment

 None

Recommended or required reading
  • Ritter, Frank E.; Baxter, Gordon D.; Churchill, Elizabeth F. (2014): Foundations for Designing User-Centered Systems: What System Designers Need to Know about People. London: Springer-Verlag. Available at URL: DOI: 10.1007/978-1-4471-5134-0 (Zugriff am: 02.10.2021).
  • Johnson, Jeff (2021): Designing with the mind in mind : simple guide to understanding user interface design guidelines. 3rd ed. Boston: Elsevier.
  • Holtzblatt, Karen; Beyer, Hugh (2016): Contextual Design, Second Edition: Design for Life. 2nd Ed. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.
  • Rubin, Jeffrey (1994): Handbook of Usability Testing: How to Plan, Design, and Conduct Effective Tests. 1st Ed. USA: John Wiley & Sons, Inc.
  • Snyder, Carolyn (2003): Paper prototyping: fast and easy way to design and refining user interfaces. San Francisco, Calif.; Oxford: Morgan Kaufmann ; Elsevier Science.
  • Nielsen, Jakob; Mack, Robert L. (Hrsg.) (1994): Usability Inspection Methods. 1. Aufl. New York: Wiley.
  • Norman, Don (2013): The Design of Everyday Things: Revised and Expanded Edition. 2nd Ed. New York, New York: Basic Books.
  • Kirk, Andy (2019): Data Visualisation: A Handbook for Data Driven Design. 2. Aufl. Los Angeles: SAGE Publications Ltd.
  • Card, Stuart K.; Mackinlay, Jock D.; Shneiderman, Ben (1999): “Information Visualization.” In: Readings in Information Visualization: Using Vision to Think. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., p. 1–34.
  • Browne, Dermot (2016): Adaptive User Interfaces. Academic Press.
  • Bartneck, Christoph et al. (2020): Human-Robot Interaction: An Introduction. Available at: DOI: 10.1017/9781108676649 and https://www.human-robot-interaction.org
  • Bartneck, C. et al. (2020): Mensch-Roboter-Interaktion: Eine Einführung. Carl Hanser Verlag GmbH & Company KG.
  • Lazar, Jonathan (2007): Universal Usability: Designing Computer Interfaces for Diverse User Populations. Hoboken, NJ, USA: John Wiley & Sons, Inc.
  • Kortum, Philip (2008): HCI Beyond the GUI: Design for Haptic, Speech, Olfactory, and Other Nontraditional Interfaces. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.
Mode of delivery (face-to-face, distance learning)

The contents and objectives of the course are prepared and guided by selected contributions (text, sound, image) by the students, analyzed and discussed together. Current contributions are welcome. According to the interests of the individual participants, each participant selects a topic and connects it to the main specialization. In this individual elaboration, the focus is on evaluation and creation based on solid research.

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