Communication and Media Engineering

Die zentrale Idee und Vision ist es, eine wissenschaftliche und anwendungsorientierte Elite in den modernen Technologien der Telekommunikation und digitalen Medien auszubilden.
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Quantifying the Effects of Media

Prerequisite

•  Basic knowledge of Human Computer Interaction (HCI) as well as empirical studies both using quantitative and qualitative methods.

 
Teaching methods Seminar/Lab
Learning target / Competences

The combination of the lab and the seminar enables the successful student to take a scientific look at the way media are perceived. Based on a solid knowledge of standard tools like surveys, they learn to conduct studies and interpret data:

  • get to know advanced methods of human computer interaction
  • learn how to measure user behavior with standard tools (e.g. surveys like NASA-TLX)
  • learn how to measure user behavior by acquiring physiological data 
  • understand how perceived and measured media experience can correspond or differ
  • learn how to conduct studies on media reception using the methods mentioned above
Duration 1
Hours per week 4.0
Overview
Classes 60 h
Individual / Group work: 90 h
Workload 150 h
ECTS 5.0
Requirements for awarding credit points

Assignment HA (3/4) + Presentation RE (1/4)
Responsible person

Prof. Dr. phil. Marc Oliver Korn
Recommended semester 2
Frequency Annually (ss)
Usability

Master's degree program CME
Lectures

Quantifying the Effects of Media Lab

Type Lab
Nr. M+I417
Hours per week 2.0
Content

•   advanced methods for human subject studies with media

•   measuring user behavior with standard tools (e.g. NASA-TLX, AttrakDiff)

•   measuring user behavior by acquiring physiological data (e.g. facial expressions, GSR)

•   analyze how subjective and measured media experience correlate or differ

•   visualize and describe your results in a scientific (short) paper
Literature

- Field, A. P., & Hole, G. (2003). How to design and report experiments. London; Thousand Oaks, Calif: Sage publications Ltd.

- Haapalainen, E., Kim, S., Forlizzi, J. F., & Dey, A. K. (2010). Psycho-physiological Measures for Assessing Cognitive Load. Proceedings of the 12th ACM Int. Conference on Ubiquitous Computing (pp. 301-310). ACM. http://doi.org/10.1145/1864349.1864395

- Jacko, J. (2012). The human-computer interaction handbook: fundamentals, evolving technologies, and emerging applications. (3rd ed). CRC Press.

- Zhou, J., Sun, J., Chen, F., Wang, Y., Taib, R., Khawaji, A., & Li, Z. (2015). Measurable Decision Making with GSR and Pupillary Analysis for Intelligent User Interface. ACM Trans. Comput.-Hum. Interact., 21(6), 33:1-33:23. http://doi.org/10.1145/2687924

Quantifying the Effects of Media

Type Seminar
Nr. M+I416
Hours per week 2.0
Content

•  Human Computer Interaction – a quick overview

•  human cognitive and sensory thresholds

•  emotions in media and learning

•  Affective Computing: using the computer to interpret emotions

•  emotions in facial expressions

•  emotions in galvanic skin response (GSR)

•  Brain Computer interaction (BCI)

 
Literature

•  Dix, A., Finlay, J., Abowd, G.  & Beale, R. (2003) Human Computer, Interaction (3rd Ed.), Prentice Hall

•   Ekman, P. (1993). Facial expression and emotion. American Psychologist, 48(4), 384

•   Kanjo, E., Al-Husain, L., & Chamberlain, A. (2015). Emotions in context: examining pervasive affective sensing systems, applications, and analyses. Personal and Ubiquitous Computing, 19(7), 1197–1212. http://doi.org/10.1007/s00779-015-0842-3

•   Picard, R. W. (1997). Affective Computing. MIT Press

 
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