Extended Reality (ExR)
Course content
This course teaches students to understand and address a research problem within the field of extended reality (XR). XR is an umbrella term for technologies combining physical and digital worlds, including virtual reality (VR), augmented reality (AR), and mixed reality (MR). The course discusses various research areas that either (1) employ an XR technology to understand a phenomenon (e.g., as a research tool for controlled experiments), (2) address a problem with an XR technology (e.g., developing techniques for XR to support behavior change), or (3) apply new methods or theories to an existing problem in XR (e.g., the use of motor learning to develop interaction techniques).
The course combines theoretical lectures, student research presentations, and hands-on project work. In the lectures, students learn about the conceptual and technological differences of virtual, augmented, and mixed reality. They also learn about common measures and design goals in XR, such as presence and body ownership. Through the research presentations and project work, the students learn about the main XR research areas both theoretically and practically. For their projects, the students work in groups and will choose one main XR research area based on pre-defined problem statements. The course goal is to present the research area in class, develop a concept suitable for addressing the given research problem, implementing the concept as an XR application, and running a study.
MSc Programme in Computer Science
Knowledge of
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The fundamental concepts and design goals of different extended reality technologies (i.e., virtual, augmented, and mixed reality), and their advantages and disadvantages.
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The main extended reality research areas and the methods to address research problems in those areas.
Skills in
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Finding and understanding the latest research in the field of extended reality.
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Understanding and inferring the technical requirements of different XR technologies and their suitability for addressing a given research problem.
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Presenting research findings, both in writing and orally, through project work and presentations.
Competences in
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Developing a concept to address an extended reality research problem.
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Working collaboratively in groups to implement an extended reality prototype and conducting a study with it.
The course will consist of theoretical lectures introducing core
concepts for extended reality. The lectures will be accompanied by
classroom discussions.
Furthermore, the students will give research presentations of
papers related to their research area in class and lead an
accompanying discussion.
Finally, the students will work on a project; they will develop a
concept for a given problem statement and implement a prototype
using extended reality technology. They will regularly report on
the project and get feedback on their progress in
class.
Selected papers and book chapters. See Absalon when the course is set up.
Programming skills corresponding to those obtained with a
bachelor degree in Computer Science or equivalent are expected;
Experience in XR development software, such as Unity3D or Unreal
Engine, is beneficial but not required (for example through courses
on Virtual Reality or Augmented Reality). Some knowledge about
human-centred computing, for instance through courses on
Interaction Design, Human-Computer Interaction, User-Centred
Design, Computer Supported Cooperative Work or the like is
beneficial.
Academic qualifications equivalent to a BSc degree are
recommended.
As
an exchange, guest and credit student - click here!
Continuing Education - click here!
PhD’s can register for MSc-course by following the same procedure as credit-students, see link above.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Oral exam on basis of previous submission, 20 minutes
- Type of assessment details
- The overall assessment is based on a group project report and
an oral exam (without preparation).
The exam is a group exam, meaning that the groups present their project in a 10-minute group presentation followed by a 10-minute individual examination. - Examination prerequisites
-
The students must fulfill two assignments that must be passed to qualify for the exam.
The assignments are:
1) give a student research presentations,
2) hand-in a written project report proposal.
- Aid
- All aids allowed
The student can use all aids for the project and preparation for the oral exam, but during the oral exam they are not allowed to use internet or AI.
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
- Re-exam
-
As in the ordinary exam, the assessment is based on a project report and an oral exam. If the project report uses parts of a project done in a group during the course, the student must detail their contributions on the hand-in for the re-exam. In the re-exam, both the oral presentation and the exam are individual.
If the student is not yet qualified, then qualification can be achieved by resubmitting a written project report proposal and have it approved. The presentation part of the qualification can be obtained by doing a presentation in the HCC XR research seminar or the HCC general research seminar.
The assignment must be submitted and the presentation must be held no later than three weeks before the re-exam date.
Criteria for exam assessment
In order to earn the grade 12, students must demonstrate the knowledge, skills and competences described in the Learning Outcome.
Single subject courses (day)
- Category
- Hours
- Lectures
- 32
- Preparation
- 40
- Project work
- 133
- Exam
- 1
- English
- 206
Kursusinformation
- Language
- English
- Course number
- NDAK25002U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Placement
- Block 4
- Schedulegroup
-
C
- Capacity
- No limitation – unless you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
- Studyboard
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Computer Science
Contracting faculty
- Faculty of Science
Course Coordinator
- Teresa Hirzle (4-77686b6c43676c316e7831676e)
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