Connectionist Modeling of Experience-based Effects in Sentence ...

3.3 A Model of RC Processing
MC02’s SRN predictions. For that reason two participant groups were formed: an RC
experience group and a control experience group, both matched on reading span. Both
groups received reading training over 3-4 weeks. The RC experience group received
training mainly on SRC and ORC structures whereas the control experience group was
exposed to other structures. A pre- and a post-test carried out in the SPR paradigm
assessed both groups RC reading performance. The results show an overall improvement
of RC reading. Most importantly, however, the data revealed an interaction of
session × experience group × clause type × region as can be seen in figure 3.4.
There was a reliable difference between SRC and ORC reading times observed in both
groups in the pre-test; in particular the ORC condition was read slower. The subject/object
difference, however, decreased significantly between pre- and post-test for the
RC experience group whereas in the control group it stayed the same. Wells et al. attribute
the global reading improvement to increased familiarity with the SPR task. The
observed pattern in the experience group is similar, first, to the span × clause type
interaction in the study by King and Just (1991) reported in 2.1, and second, it resembles
the frequency × regularity interaction of the connectionist model in MC02 (see
figure 3.5). Statistically the SRNs’ mean GPE scores predicted the within-sentence and
experience-based variance in the human data extraordinarily well. There was a total fit
of GPE and reading times of R 2 = .75. In a hierarchical regression Wells and colleagues
also predicted the SRN simulation results using the human reading times. The RC experience
group data accounted for 75% of overall variance in the SRNs’ GPE scores.
Using the control group data as a predictor, which did not involve an experience factor
but merely within-sentence variance, the regression accounted only for about 65% of the
GPE variance.
The impressive result of Wells et al.’s study delivers empirical support for the implications
drawn by MC02 from the SRN simulations, namely that experience can account
for individual differences in reading skill. Notably, the Wells et al. study proved a significant
experience effect after minimal exposure amount (the training sets contained only
160 sentences in total). Furthermore, lexical and structural short term priming effects
were excluded by, first, a four weeks test distance, second, no lexical overlap between the
tests and, third, the usage of RC constructions during training that were structurally
different from testing items. Also task-related adaptation can be excluded since during
the training phase a full-sentence display was used instead of word-by-word reading.
Now, given the evidence that reading skill on certain sentence structures is affected
by previous experience with these structures it remains the question of what has been
learned; a question that evolves from the granularity problem of exposure-based theories
described in section 1.3.4. Wells and colleagues identify verb transitivity as a crucial
factor driving the learning process of the SRN. In ORCs on the one hand, embedded
verbs are necessarily transitive because the head noun has to fill an object role. On
the other hand, simple sentences and SRCs occur with transitive and intransitive verbs.
That has the consequence that only for continuation predictions of ORCs the network has
to learn to differentiate verb transitivity in the predictions whereas for the continuation
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