French gender prototypes
|Others with > 160 hours||n/a|
|Study Start Date||03/06/08|
|Study End Date||06/30/08|
|Number of participants (total)||45|
|Number of participants (treatment)||45|
|Total Participant Hours||~135|
The current study manipulates two factors in the instruction of cues to French grammatical gender.
First, half of all cues are taught with explicit text prompts on feedback, pointing out the predictive cue that signals the gender of the noun. For example, la sortie (exit) is feminine, and the prompt would show that words ending in -ie tend to be feminine (prompts take the form "ie -- F"). The other half are presented with correct/incorrect feedback only, with no input on the endings of words.
We predict that explicit instruction will be more robust to delay and generalization.
Second, we manipulate the breadth of the categories of nouns. For each cue, 14 exemplars were used as stimuli. In half of the cues, however (evenly divided between explicit and implicit blocks), 6 of those exemplars were replaced with repetitions of one "prototype" noun, meaning that half of all exposures showed the "prototype" (in quotes because we did not choose the frequent word as any sort of best example).
We predict that the frequent single noun will accelerate learning, but it is possible that the acceleration will come at the cost of reduced generalizability and transfer, if the student is too reliant on the single representation of the prototype noun.
The interaction between the two factors is most interesting: will the explicit instruction obviate the prototype, or vice versa? Does implicit instruction benefit from a salient example in the absence of explicit rule learning?
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).
We are changing instruction here based on whether or not the relevant cue is presented with a salient (because of its frequency and simplicity) prototype or with a larger number of varied exemplars.
In the current study, we also manipulate whether participants receive explicit cues to gender patterns, or merely correct / incorrect feedback. Half of all cues are presented explicitly, half without explicit prompts (counterbalanced and randomized for each participant).
First, accuracy and latency data within the three training sessions can be used to compare learning results across conditions. Accuracy and latency data from the three post-tests (immediate, 2-3 week delay, and 3 month delay) compare performance in generalization and retention. In addition, the coefficient of variability (Segalowitz & Segalowitz, 1993), calculated by dividing the standard deviation of reaction time by the mean reaction time, can be used to reflect the level of automaticity of performance over time.
In training, time on task (operationalized by session number) should be predictive of learning, both as a manipulation check and to measure the effectiveness of instructional interventions.
The instructional manipulations took the form of a 2 x 2 within-subjects design. These manipulations were explicitness (presenting the cue explicitly v. correct / incorrect feedback only) and category breadth (14 equally frequent exemplars v. 8 exemplars, 7 equally frequent and one "prototype" presented 7 times more often).
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