Difference between revisions of "Epistemic feedback"

Revision as of 14:56, 23 January 2012

Draft 1

Editor: Vanda Luengo, Laboratoire d’informatique de Grenoble

Contributors: Nicolas Balacheff, Laboratoire d’informatique de Grenoble

Definition

Epistemic feedback is a feedback provided by a learning environment specific to the piece of knowledge at stake and its learning characteristics. The computation of an epistemic feedback involves data from the learner, the pedagogical models, and the knowledge domain.

Comments on the history

The origin of the expression “epistemic feedback” can be traced in the philosophy of science (Margereau 1978 p.287) where it denotes the feedback which meaning requires the interplay between the tangible characteristics of the environment and the user knowledge or expectations. It is used in HCI research which takes into account three functional roles of human gestures: semiotic, ergotic and epistemic; the latter referring to the epistemic function of gesture which “allows humans to learn from the environment through tactile experience.” (Crowley and Martin 1997 p.1). The concept of epistemic feedback was introduced in TEL research, in the context of the design and study of virtual reality and simulation for professional training, to characterize feedback which allow learner to perceive and analyze his or her action in relation to the knowledge at stake (Luengo 2009 p.26 sqq).

Related terms

epistemic interaction, epistemic activities, epistemic affordance

Translation issues

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Disciplinary issues

Stellan Ohlson (1996) coined the term epistemic activities, to account the fact that “human beings employ their understanding, not in action, but in the generation of symbols” (ibid.p.95). He included activities such as describing, explaining, predicting, arguing, etc. In line with this approach, CSCL research adopted the term epistemic interaction for those interactions which are “potentially concerned with the expression and critical examination of foundations for proposals” (Baker et al. 2001).

The development of high quality simulations and their use for learning opens a new possibility to support the acquisition of tacit knowledge, which as well is potentially concerned by a critical examination of foundations for action. Epistemic interactions related to tacit knowledge, often ill-defined (Lynch et all. 2009), in the context of the use of simulation, aim at taking into account epistemic activities, especially controls during the action, in generating an epistemic feedback. For example, in the case of visual and haptic perceptions, the identification of the visual controls and their rational (what knowledge is mobilized to allow this visual verification) makes possible generating an epistemic feedback linked to the associated knowledge. For this king of interaction it is not necessary to propose a complete description of the action—what is actually impossible in ill-defined domains—but to identify the relevant controls of the actions from a learning perspective.

Key references

Margenau H. (1978) Physics and philosophy: selected essays. D. Reidel Co.

Baker, M.J., de Vries, E., Lund, K. & Quignard, M. (2001). Computer-mediated epistemic interactions for co-constructing scientific notions: Lessons learned from a five-year research programme. In: Dillenbourg P., Eurelings A., Hakkarainen K. (eds.) Proceedings of EuroCSCL 2001: European Perspectives on Computer-Supported Collaborative Learning (pp. 89-96). Maastricht: Maastricht McLuhan Institute (ISBN 90-5681-097-9). [1]

Crowley J. L., Martin J. (1997) Visual Processes for Tracking and Recognition of Hand. International Workshop on Perceptual User Interfaces, Banf, Ca, October 1997 <Gestures. [2]>

Luengo V. (2009) Les rétroactions épistémiques dans les Environnements Informatiques pour l’Apprentissage Humain. Habilitation à diriger de recherche. Grenoble: Université Joseph Fourier.

Ohlsson, S. (1996). Learning to do and learning to understand: A lesson and a challenge for cognitive modeling, in P. Reiman et H. Spade (dirs.), Learning in Humans and Machines: Towards an interdisciplinary learning science, Oxford, Elsevier Science, p. 37-62.

Lynch, C., Ashley, K., Pinkwart, N., & Aleven, V. (2009). Concepts, structures, and goals: Redefining ill-definedness. International Journal of Artificial Intelligence in Education.