Anastasopoulou, Theano; (1996) Development and representation of the knowledge acquired during incidental sequence learning. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Past research on sequence learning shows that exposure to a structured series of events under incidental learning conditions results in a dissociation between performance measures of learning and measures of conscious memory. A criticism directed to previous studies, however, was that the performance speed-up did not always reflect the type of knowledge that was being tested by the tasks of conscious memory. Thus, any observed dissociation was due to a methodological artefact rather than the existence of two independent knowledge bases. The main aim of the experiments reported in this thesis was to identify the type of information that is expressed in performance measures of sequence learning under incidental conditions. Experiments 1 and 2 tested whether practice with a complex sequential structure leads to learning of rules or learning of instances and supported an instance-based process of learning. Experiments 3 and 4 demonstrated the presence of higher order sequential effects in a response time task that may have contaminated the response time index of learning in previous studies. Experiments 5 and 6 examined whether sequence learning is based on an associative or a chunking mechanism and supported the latter mechanism. Experiment 7 demonstrated a correspondence between response times and recognition ratings for chunks. Finally, Experiment 8 examined the effect of contextual interference and arbitrary parsing of the sequence during practice, on both response times in a transfer phase and tasks of conscious memory. Results showed that a combination of low contextual interference and unfavourable parsing slowed down response time performance during transfer but did not affect recognition memory. Results from all experiments provided useful insights into the characteristics of a learning mechanism based on chunking and were evaluated in terms of proposed models of sequence learning.

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