SOW-MKI52
New Media Lab
Course infoSchedule
Course moduleSOW-MKI52
Credits (ECTS)6
CategoryMA (Master)
Language of instructionEnglish
Offered byRadboud University; Faculty of Social Sciences; Artificial Intelligence;
Lecturer(s)
PreviousNext 2
Coordinator
prof. dr. T. Bosse
Other course modules lecturer
Examiner
prof. dr. T. Bosse
Other course modules lecturer
Contactperson for the course
prof. dr. T. Bosse
Other course modules lecturer
Lecturer
M.A. De Sa Siqueira, MSc
Other course modules lecturer
Lecturer
S.H.E. Dijkstra
Other course modules lecturer
Academic year2023
Period
SEM2  (29/01/2024 to 12/07/2024)
Starting block
SEM2
Course mode
full-time
Remarks-
Registration using OSIRISYes
Course open to students from other facultiesYes
Pre-registrationNo
Waiting listNo
Placement procedure-
Aims
After this course, the student will be capable to play a role in a multi-disciplinary team and conduct empirical research in the field by means of new media technologies such as mobile apps, virtual reality or interactive installations.
Content
The course focuses on designing, building and deploying new media technologies as instruments for conducting research. The research questions addressed stem from different academic fields as well as from industry and range from data collection (e.g. experience sampling), through coaching and behavioral change, up to validation of applications of Artificial Intelligence.The student is expected to follow, in a multi-disciplinary student team, a research cycle consisting of the following steps:
  • define the research question, target user group, functionality and study protocol.
  • conceptualize an interactive application, create mock-ups and preliminary walk-throughs.
  • develop the application, distribute it and implement the study protocol.
  • conduct and analyze an empirical study using this application. 
The course will address necessary topics to follow the proposed research cycle.

Students work in multi-disciplinary teams of about 4-5 students. Throughout the course, each team will develop an 'intelligent new media application' with which they can answer a certain research question. These questions are put forward by so-called ‘stakeholders’, and should be centred around the general idea of ‘assistive technology’. For example, questions may include: 'can an intelligent mobile app help people quit smoking?', 'can a social robot be used to teach maths in primary school?', 'can a Virtual Reality application help people cope with anxiety?'. Hence, the type of technology (e.g., mobile app, social robot, VR application, serious game, …) as well as the choice of a programming language and platform to develop the application are completely open, as long as the system uses some kind of Artificial Intelligence. Moreover, students are encouraged to use new and interesting forms of sensors and devices  (e.g., an eye tracker to sense gaze movement and pupil dilation, an emotive for EEG brain monitoring, or beacons for tracking movement). To answer their research question, students will go through an entire research & development trajectory (including requirements analysis, focus groups, conceptual design, prototype implementation, usability study, and an actual experiment involving real participants).
 
Level
AI-MA
Presumed foreknowledge

Test information
Scoring is based on a final report. An additional condition is that students participate actively in the presentation and demo sessions.
Specifics
During the start of the course, a series of lectures will be organized on topics such as research opportunities from different application fields, user-centred design, usability studies, and new media technologies. Next, students will work through the proposed research cycle in multi-disciplinary teams and report back in several plenary sessions throughout the course.

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Students who are enrolled for a course are also provisionally registered for the exam. 

Resit: Manual register at (https://portal.ru.nl/home) until five working days prior to the date of the exam. No delayed registration is possible. 

We urge you to always read the course information on Brightspace. 
 
Required materials
To be announced
Will be announced in Brightspace before the start of the course.

Instructional modes
Lecture
Attendance MandatoryYes

Working group
Attendance MandatoryYes

Tests
Report
Test weight1
Test typeReport
OpportunitiesBlock SEM2