French gender attention
|Others with > 160 hours||n/a|
|Study Start Date||10/01/08|
|Study End Date||05/30/08|
|Number of participants (total)||80-100|
|Number of participants (treatment)||N/A|
|Total Participant Hours||~100|
This study extends the research question in a previous study by Presson & MacWhinney. In that experiment, explicit instruction led to better generalization and robustness to forgetting, compared to correct/incorrect feedback only. In the current study, explicitness is manipulated as well, with the more explicit condition the same as the previous study. However, the more implicit condition in this case is a highlighting manipulation, with no rules presented and in which participants see the relevant cue in capital letters to draw attention to the endings of words (e.g. "fromAGE" v. "fromage"). We want to know first if students are as effective at extracting cue patterns with this intervention as with strictly explicit instruction.
Second, we manipulate the time pressure of the task between groups. Time pressure favors procedural and automatic performance. If the highlighting condition is less explicit and equally effective, we expect an advantage within the time pressure condition. This is important because time pressure is an essential element of naturalistic language use.
This research is designed to discover the best method of producing robust learning of French nominal gender, as well as the factors that make this learning more difficult.
Background and significance
Tucker, Lambert and Rigault (1977) evaluated the L1 (first language) learning of cues to gender in French. More recently, Holmes and Dejean de la Batie (1999) produced the first study of the acquisition of grammatical gender by L2 learners. Holmes and Segui (2004) have extended the detail of these analyses, but so far only with native speakers. Carroll (1999) and Lyster (2006) have explored the role of cue validity and availability in predicting usage by learners. All of these studies underscore the importance of high validity cues for the general vocabulary. However, these cues are only marginally useful for the highest frequency forms, whose gender must be learned more or less by rote. These analyses are in very close accord with the claims of the Competition Model (MacWhinney 1978, 2006).
In the Competition Model, each cue has a strength that is based on its reliability in signaling information (as in, for example, the use of spelling to predict grammatical gender). Some cues are more reliable than others: for instance, in the case of nouns that refer to people, semantic cues (the gender of a person) are more reliable than spelling cues. Over time, a learner picks up on these reliabilities, first acquiring the most clearly reliable cues, then later pulling apart conflicting but frequently co-occurring ones. Cue conflicts are then resolved through a process of competition. A full discussion of cue conflict is found in MacDonald and MacWhinney (1991).
In the current study, we manipulate whether participants receive explicit cues to gender patterns, or merely correct / incorrect feedback with the relevant cues highlighted (through capitalization) to direct attention.
Accuracy and latency in training, as well as pre-/post-test gain scores, are dependent measures. In the post-test, there are two blocks: visual presentation (as in training) and auditory presentation (a transfer task).
Between-groups manipulations of time pressure and explicitness produce four groups:
Rule + Time Pressure
Rule - Time Pressure
Highlighting + Time Pressure
Highlighting - Time Pressure
Time pressure is operationalized by timimg out test trials after (some interval) ms.
Because prior studies (e.g., Explicitness and Category Breadth) suggest that explicitness of instruction does not affect accuracy in training, we predict equivalent performance in the learning block. Explicit presentation of the prompt would be more robust to decay and generalization if in fact the manipulation makes the cue more salient (compared to the highlighting condition).
Adding time pressure will suppress initial performance in training. We predict that this suppression will be temporary, and in fact that later performance could show a time pressure advantage, especially in the no-feedback post-test. In addition, time pressure should change the relative effectiveness of an explicit inference rule vs. noticing highlights, such that noticing is easier than inference under time pressure, therefore improving learning.
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