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Nature of learner-computer interaction

Background:  CALL  practitioners, developers and researchers have frequently claimed that computerized materials are qualitatively superior because they are interactive by definition. On the other hand, a number of small-scale efficacy studies have often been inconclusive.  

Research question: How do we improve learner-computer-interactions?

What learner-computer interactions are useful, beneficial, effective ...? How can these interactions be described, classified, analyzed? How do we monitor the learning process and its results in these interactions? How can computer programs meaningfully contribute to learning interactions?  When? How often? By what medium? On the basis of what kind of analysis of the learner's contribution? What are the features of a successful learner-computer dialogue?

Suggested methodology/comments:  A variety of very different methods appear to be possible and some of these have been applied in the past. Concentration on a thorough analysis of learner data (linguistic input, tracking, secondary data) is the key. Observation of learning processes (e.g. think-aloud protocols, video taping) is another way to get valuable research data.

The methodology must be on a sound theoretical basis. Results of studies and experiments should not just contribute to the body of knowledge in CALL, but should also stand up as innovative and original in the academic domain from which the methods and the terminology were borrowed.  

Second Language Acquisition Theory, Human Computer Interaction, Learning Psychology and Discourse Analysis are academic disciplines that have the potential to provide the theoretical background.

Contact:  Mathias Schulze    mschulze@uwaterloo.ca

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