French gender cue learning through optimized adaptive practice
|Others with > 160 hours||n/a|
|Study Start Date||01/31/07|
|Study End Date||02/28/07|
|Number of participants (total)||~40|
|Number of participants (treatment)||21|
|Total Participant Hours||~40|
The goal of this project is to improve the ability of students of Elementary French to determine the gender of French nouns. This improvement is attained through large amounts of practice, and is measured in terms of ability to generalize to novel nouns. Like other studies conducted by MacWhinney and Pavlik (Optimizing the practice schedule), this work emphasizes the role of scheduling in attaining mastery.
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).
Our goal here is to use these findings to guide effective instruction. One way of doing so is to aim for mastery of some grammatical structure in an L2, in this case grammatical gender, to show that with efficient and optimized practice, the learning gains can be large. We do this using an optimized schedule designed by Pavlik (2005) in the FaCT System and inspired by the memory schedules of Pimsleur (1967). We expect that, with a sufficient amount of practice under the right conditions, grammatical gender assignment can become proceduralized. Although grammatical gender is a relatively simple grammatical structure, and (for English L1 speakers) should show little interference from structures in the native language, this is an important first step toward optimizing grammar learning overall as well as toward learning more about the available mechanisms to learn an L2.
French 1 classes (one at the University of Pittsburgh, one at CMU) in the fall of 2006 piloted the tutoring program, and showed substantial pre-test/post-test gains in gender assignment for novel (untrained) words:
- There was no difference in performance between CMU and Pitt (F(1,62) = .57, p > .1)
- The mean gain score was higher in training classes than in comparison classes in the normal curriculum (F(1, 62) = 11.02, p < .01)
- Mean improvement for the tutor group was 15%, because of a near ceiling effect (presumably because test items were relatively common and the binary choice task allows for a 50% chance of correctness on a given trial).
As a result of observations in the pilot, the test items in the present study are both novel and lower-frequency, and also not yet included in the class curriculum. Also, in an effort to create more pronounced learning, the criterion for finishing practice with a given rule was raised, although we restricted criteria to keep practice below 30 minutes on average for any individual session.
One primary dependent variable is percentage correct gender judgment for a given rule. Because there are only two genders in French, chance performance is at 50%.
Other possible dependent variables are latencies, percentage correct across rules, and post-test score.
In addition, analysis considers order effects in light of cue competition. For example, consider the two cues -nne (a cue to feminine gender) and -isme (a cue to masculine gender). These two cues share a feature: the final -e. Because they indicate two different outcomes, we expect conflict, especially when the cue that runs counter to the general pattern (that words ending in -e are feminine) is presented early on.
First, to ensure that the training is working, we are using a pretest-posttest design to measure the overall effects of the online training. We compare scores from students in the traditional course with no gender training with scores for students in the online course with gender training. We may use d' measures instead of point or percentage differentials to account for a possible masculine default and general problems with the binary choice task.
In order to predict how a given participant will perform in using a particular rule, we use two basic categories of independent variables: word-level and also participant-level. A sample of more specific (tentative) independent variables:
- An individual's pre-test score, past performance history, and time on task;
- The relative ease of learning particular cues in terms of how reliability interacts with lexical and cue frequency (In this study, because all stimuli presented follow the given cues, special attention should be paid to how cue conflicts within a given word influence gender choice);
- A word's cognate status, or whether the cue is semantic in nature (such that it would carry independent information).
- Mastery training with scheduling is more effective than simple repetition (for early efforts to optimize training, see Pimsleur, 1967; for a more recent approach, see Pavlik, 2005).
- Cues that do not interact with similar cues will be easier to learn than those that interact with other cues. (e.g., -on (cuing masculine gender) would conflict with the more specific and reliable -aison (cuing feminine gender)).
- Learning will be most robust if high reliability cues are taught before low reliability cues or rote training.
These predictions derive from the Competition Model (MacWhinney, 2006). Also consistent with the Competition Model, and with the literature on the use of extensive practice toward proceduralization (e.g., Anderson & Fincham, 1994), we predict these behavioral measures, perhaps later extended by mechanistic evidence, to be able to show some level of proceduralization with optimized practice, in contrast to the Ullman (2001) declarative/procedural model, which predicts that second-language learners will learn and continue to use grammar declaratively.
There is evidence for generalizable learning (correctly categorizing novel words), although this effect is driven by very high learning gains in some learners and low gains in the rest of the population. Both accuracy and latency substantially increase over time, and this effect is different for different rules, suggesting some consistent prior knowledge or misconceptions that aid or hinder learning of some cues. Preliminary analysis points also toward competition between instructed cues as explaining some variance in learning outcomes; as in the cue conflict example described above, for students who learned -isme before -nne, performance on-nne suffers significantly (F(1,17) = 7.71, p < .01). This type of analysis reflects Competition Model predictions in the learning of second language grammar.
The Competition Model explanation for these effects emphasizes the role of practice, cue availability, and lexical learning as determinants of gender cue learning, as well as cue reliability (although that itself is not manipulated in the study). Availability and reliability are measured across the vocabulary.
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- DeKeyser, R. M. (2005). What Makes Learning Second-Language Grammar Difficult? A Review of Issues. Language Learning, 55(Suppl1), 1-25.
- Holmes, V. M., & Dejean de la Batie, B. (1999). Assignment of grammatical gender by native speakers and foreign learners of French. Applied Psycholinguistics, 20, 479-506.
- Holmes, V. M., & Segui, J. (2004). Sublexical and lexical influences on gender assignment in French. Journal of Psycholinguistic Research, 33, 425-457.
- Lyster, R. (2006). Predictability in French gender attribution: A corpus analysis. French Language Studies, 16, 69-92.
- MacDonald, J. L., & MacWhinney, B. (1991). Levels of learning: A microdevelopmental study of concept formation. Journal of Memory and Language, 30, 407-430.
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- Pavlik Jr., P. (2005). Modeling order effects in the learning of information.
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- Ullman, M. T. (2001). The neural basis of lexicon and grammar in first and second language: the declarative/procedural model. Bilingualism: Language and Cognition, 4(1), 105-122.