Orchestrating learning

From Stellar Deliverable 1.1

In 1990 Salomon suggested that for the computer to be an effective classroom tool, "most everything in the classroom needs to change in a way that makes curriculum, learning activities, teacher's behavior, social interactions, learning goals, and evaluation interwoven into a whole newly orchestrated learning environment" (Hopson et al., 2001, p. 51).

TEL situations are frequently characterised by a multiplicity of resources, a multiplicity of devices, a multiplicity of agents (co-learners, teachers or trainers, artificial or human agents). TEL learning situations can be very complex and it is important to understand how they are organised and how they work. Dillenbourg and Jermann (2009) discuss the potential of the word ‘orchestration’ as a metaphor for understanding and informing the design of technology enhanced learning situations, and at the same time introduce the idea of the classroom as an eco-system. Some new keywords in TEL research, such as learning scenario and classroom orchestration bear witness this priority. While scenarios describe the organisation of learning from a time, event and activity perspective, orchestration takes up the challenge of the actual implementation of all the interactions needed for a successful scenario (Niramitranon et al., 2006). It is in this sense that Fischer and Dillenbourg (2006) spoke of orchestration as the process of productively coordinating supportive interventions across multiple learning activities occurring at multiple social levels. It is also important to consider the ways in which the orchestration of a learning intervention has to adapt to the local situation, that is ‘adaptive orchestration’ that takes into account the needs and flow of the learning moment.

Understanding how learning is orchestrated can be modelled using tools designed for this purpose. Today, there are a wide variety of models and application contexts that allow meaningful comparisons. We can distinguish approaches that focus on learning objects (such as Shareable Content Object Reference Model (SCORM) ), approaches that focus on prescribed tasks (IMS learning design ), approaches that focus on interactions (Learning Design Language (LDL) ), approaches that focus on objects produced or "emerging learning objects" (Science Created by You (SCY) FP7 project ) or approaches led by the intentions (Intentions, Strategies, interactional Situations (ISiS) . Each of these models targets specific audiences or specific economic models (professional or academic training, primary, secondary or higher education, distance e-learning or blended), specific areas of knowledge (scientific knowledge, skills, communication skills etc.) or specific teaching approaches (collaborative approach, discovery learning, etc.).

The practical impact of the richer and more complex world of learning resources is the requirement for more and new collaborative competencies for using, generating and exchanging knowledge in a peer-to-peer manner and for participating in communities of learning. This presents a challenge in terms of finding methods and principles, as well as concepts and tools, to engineer learning situations and/or learning environments. One response to this challenge is the implementation of collaboration scripts, which do not only structure specific activities and interaction patterns but also support orchestration of individual and collaborative learning activities within the classroom over longer time segments (Dillenbourg & Jermann, Submitted, Dillenbourg & Tchounikine, 2007, Kobbe et al., 2007, Masterman & Lee, 2005).

Issues of orchestration and coordination are relevant whether considering learning within educational institutions or learning within the workplace. In the workplace it is often important for people to coordinate and orchestrate learning activities between each other. In this respect there is an interplay between the different roles a knowledge worker might play: the role of the worker (getting the task done), the role of the learner (improving competencies in order to be able to approach new tasks or to improve the quality of known tasks) , and the role of the expert or more knowledgeable other (helping other people getting their tasks done). Each of these roles places different demands on the orchestration process which relates to the third theme of contextualising learning (Section 2.3). It has been shown that switches between these roles takes place on the activity level (micro-level) (Eraut & Hirsh, 2007) and are strongly related to the task at hand. In addition, in the workplace learning proceeds along different learning trajectories (ibid), for example the social trajectory, the topic trajectory, and the cultural trajectory, which do not exist in isolation from each other but stay in constant interaction.

The State of the Art report pointed out that gaming is gaining increasing research interest. There is evidence in the research literature that games have the potential to contribute to learning (see for example Aldrich, 2005, Gee, 2003, Kirriemuir & McFarlane, 2004), and we suggest that the point made below by Richard Van Eck below is important:

One could argue, then, that we have largely overcome the stigma that games are “play” and thus the opposite of “work.” A majority of people believe that games are engaging, that they can be effective, and that they have a place in learning. So, now that we have everyone's attention, what are we [Digital Game Based Learning] DGBL proponents going to say? I believe that we need to change our message. If we continue to preach only that games can be effective, we run the risk of creating the impression that all games are good for all learners and for all learning outcomes, which is categorically not the case. What is needed now is (1) research explaining why DGBL is engaging and effective, and (2) practical guidance for how (when, with whom, and under what conditions) games can be integrated into the learning process to maximize their learning potential. We are ill-prepared to provide the needed guidance because so much of the past DGBL research, though good, has focused on efficacy (the message that games can be effective) rather than on explanation (why and how they are effective) and prescription (how to actually implement DGBL). (Van Eck, 2006 p 2)

As Van Eck points out, we need to find ways to understand what it is that is effective about game based learning and to use this knowledge to inform the design of games designed for learning. Related to this, it may be that new models of orchestration, tailored to new learning experiences like serious gaming, are required. The use of games significantly complicates the task of orchestration. It is not just about making the learner play, but also verifying that an activity promoting the immersion is compatible with the learning objectives, with the socio-professional constraints and with the individual values of learners. The specificities of games (players, roles, missions, rules, etc.) and known mechanism in games (mimicry, agon, alea, illynx) require us to define new ways of orchestration.

Research questions include: • In which ways can TEL learning situations be seen to be more complex than learning situations in which digital technology is not used? Is the job of orchestration necessarily more complex in these situations? Why?

• Are there key differences between orchestrating TEL learning situations in educational institutions and in the workplace? What sort of different things would teachers (or more knowledgeable others) have to take into account?

• What characteristics of gaming contribute to learning, and in which ways? How can we exploit knowledge of these characterisitics to inform the design of other learning activities?

    The role of the teacher or more knowledgeable other

    The role of assessment

    Higher order skills and knowledge domains