UV9918V1 – Collaborative use of interactive digital representations for learning
Schedule, syllabus and examination date
Collaborative use of interactive digital representations for learning in co-located and distributed settings
Digital technology is increasingly used for learning in school, the workplace, and for leisure experiences. Use of interactive digital representations in various appearances, such as simulators, animations, games and virtual worlds, highlights essential issues in technology-enhanced learning, as the opportunities provided by the technology presents learning situations that are radically different. Students using interactive simulations, such as exploring alternative mathematical solutions and procedures, or simulate complex phenomena in the atmosphere, present new opportunities for learning (Smetana & Bell, 2012; White & Pea, 2011; Chiu & Linn, 2014). Similarly, students placed in various locations using personal avatars in a 3D world to explore or build, are in a context and with tools that are fundamentally different from a traditional classroom situation (Mørch et al., 2017).
The aim of digital representations is to construct an approximation of aspects of a real-life situation that is impossible, impractical, expensive, or risky to carry out in the real world. In this course, “interactive representation” is used as a collective term for different forms of digital representations, including interactive models, simulators, interactive animations and micro-worlds. An interactive representation is an object that models a phenomenon in the world, such as geologic development of the earth over several million years, a mathematical equation or human relationships. Avatars can move around in a 3D virtual space to explore buildings and other objects by simple commands, and users can get a feel for the presence and communicability of others and opportunities in virtual objects. Learning can be accomplished by building digital objects and using them in collaboration activities as virtual objects within a virtual world. Whether the students are co-located, working with a common object or collaborating as avatars in a virtual world, the digital representations are an interactive model for learning, and offer the learner a context for collaboration that can simulate a classroom where they can interact with other students by using text-based or voice-based tools.
As the use of digital representations gains momentum, existing meta-studies provide overviews of the state of the art in the field from different perspectives. Review studies provide an additional perspective by comparing results (see literature below).
This course makes use of socio-constructive and socio-cultural perspectives to investigate collaborative use of interactive representations, but will not be restricted to these perspectives. We will study how the interaction with these objects and micro-worlds can enable and restrict activities aimed for collaborative learning processes. Depending on the object, the learner will be able to manipulate the context and/or variables of the representations and study the consequences of those changes.
To study these learning processes is challenging, but the use of interactive digital representations provides an opportunity to collect verbal and gestural data as the learners collaborate and interact with digital representations. In the course, we will explore different methods for the analysis of data, using interaction analysis for verbal and gestural data as the common approach. In addition, learning analytics will be explored for the analysis of quantitative data collected from use, in order to get a richer base for conclusions than the two approaches used in isolation.
For digital representations supporting collaborative use, we will address the following cross-cutting themes:
- the role of interaction
- conceptual learning
- large and small groups of collaborative learners
- distributed (online) collaboration vs. co-located collaboration
- simulation, gaming and role play
In addition, the course will explore the approaches and methodological issues of combining verbal and gestural data with quantitative activity data from the users.
The students may bring their own data for discussions.
After completing the course, the students will:
- Get an overview of the state of the art of collaborative use of interactive digital representations for learning in co-located and distributed settings
- Understand the principles of using representations in learning processes
- Be able to analyse digital objects and virtual worlds for learning activities and processes
- Account for challenges in design and use of representations and micro-worlds, including conditions for learning opportunities
- Have practiced interaction analysis
- Get an understanding of the possibilities of combining verbal and gestural data with quantitative data collected from user operations
- Write literature reviews and summarize research findings in learning with digital representations
PhD candidates at the Faculty of Educational Sciences will be given priority, but it is also possible for others to apply for the course. Applicants must have at least a Master's degree.
Candidates admitted to the PhD programme at the Faculty of Educational Sciences should apply through Studentweb
Other applicants may apply using this application form
Registration deadline: February 18, 2018.
This is an intensive course over three days, comprising a total of 21 hours.
Dates: March 6-7, May 3, 2018
Place: University of Oslo, Forskningsparken, meeting room Infra.
Session 1 (March 6): Literature review and meta-studies, state of the art (mainly lectures and discussions)
Session 2 (March 7): Data workshop – data presented and discussed.
Session 3 (May 3): Draft papers to be presented and discussed
You will find the timetable and the reading list on the semester webpage for this course.
To obtain 1 study point, 80% attendance in the course is required.
To obtain 4 study points, participants need to submit a course paper (7-10 pages, Times New Roman 12, line spacing 1,5) after the course. 80% attendance is required.
Deadline for paper submission is April 23, 2018.
Grades are awarded on a pass/fail scale. Read more about the grading system.