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Quantity OR quality – an inevitable dilemma in innovative CALL systems?
theories which concentrated on the teacher’s activity and for whom the learner had been a
passive object, ready to be fed with information, pedagogy nowadays turns towards the learner
himself/herself. This paradigmatic shift has also affected developments in CALL: while former
implementations had remained in the behaviouristic “thrill-and-practice” attitude, now there
are some evolving examples in which the system is not a merely content presenting teacher
anymore but rather a facilitator of learning processes (Salaberry 1996). Explanations for this
new perspective can be found in various sources, e.g. in Jean Piagets (1976) work on children
learning or in recent psychophysiological fi ndings (Markowitsch 1997).
Beyond participation there is another infl uencing factor which should not be left out in the
construction of learning environments: emotions. The philosophers Hubert Dreyfus (1995), Sir
Karl Popper (1987) or John Dewey (1964) as well as the psychologists Heinz Mandl (1983) and
Hans Markowitsch (1997) – they all see emotions as a determining factor in learning processes.
Information which is combined with emotions is stored in a deeper and more effective way. We
can use emotions to make learning easier.
Interactive contact with the learning subject as well as the provision of immediate feedback
makes this required student involvement and participation possible. This is the main advantage
of e-learning in comparison to classical learning environments. The point is to keep this in
mind and to accompany rather than to guide the user. To make his/her mistakes visible; not to
show him/her the correct solution but to offer different possible paths which might guide the
learner to the correct solution. Similar approaches have already proven to be more effective
for improving the learners’ grammatical profi ciency (Nagata and Swisher 1995).
3. Exercises and Quizzes – A Review of the Literature
A general review of the literature about how technology is used for language learning has
been given in (Gamper and Knapp 2002b, Knapp 2004). The authors summarized what kind
of exercises can be found in language learning systems and to what extend they fulfi ll our
didactic demands. They analyzed more than 60 advanced projects in detail coming up with
sometimes unsatisfying results. Artifi cial Intelligence (AI) has been seen as a big chance for
language learning environments and although there are several approaches to integrate AI in
learning systems we still are awaiting its impact. Many interesting systems did not get out of
their prototypical stage, often for reasons of lacking money. The crucial problems however
have to be searched on another level. One main problem is seen in the concentration on merely
morphologic or syntactic analysis leaving out semantic or pragmatic problems. An example for
CALL on morphologic level is Spengels, developed by the University of Nijmengen, Netherlands
(Bos and van de Plassche 1994). Spengels trains verb forms by using gap-fi lling sentences. On a
syntactic level the Web Passive Voice Tutor can be found, developed at the University of Piraeus
in Greece, training passive forms of the English language (Virvou, M. and Tsiriga, V. 2001).
Another critical point in CALL is found in the question whether oral capabilities can be learned
from written training. There do exist different good solutions working with multimedia, putting
together written and spoken text, some of them even include analysis of spoken language
produced by the learner. Such applications are Roberto’s Restaurant by the Interactive Drama
Inc. (http://www.idrama.com/Roberto.htm, 22.08.06) or LISTEN, developed at the Carnegie
Mellon University (Mostow and Aist 1999), to name only some examples. From a technical point
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