Robinson (1997) investigated whether 60 Japanese college students would learn an English grammar rule better without or with rules, after 25 minutes of training. Robinson focused on the products of automatization, defined as the accuracy and speed of response on an immediate post-test after the 25-minute treatment.
The target rule chosen was the English dative alternation, or rather a small aspect of it, which was of reasonable difficulty for the Japanese college students in this study. Consider the two sentences:
(1) John gave the cake to Mary
John donated the piano to the church
The verbs give and donate have close meanings in the above two sentences. So, why is it that we can choose the alternative option John gave Mary the cake but not *John
An exemplary study of symbolic vs. associative learning: Robinson (1997) 101 donated the church the piano? Many speakers of English, including of course first
language speakers, are surprised to learn that give can alternate between the two options because it is an Anglo-Saxon verb, whereas Latinate verbs (e.g. donate) do not allow this word order alternative (there are several other, more abstract ways in which the alternation is motivated, explained in Pinker, 1989). In pedagogical terms, if a rule of thumb were to be given, we would tell English students that one- syllable verbs can take both word orders, whereas bi- or multiple-syllable verbs (because Latinate verbs always have at least two syllables) can only be well formed with the ‘to-phrase’. Robinson decided to use invented verbs rather than real ones, to circumvent the possibility that some participants would benefit from their existing memory of how commonly encountered verbs (e.g. give) work. Some examples of multisyllabic verb items used in the training and tests were:
(2) Nick menided some hot coffee to Sue *Sandy bivarded Patrick some Swiss cake
You see how challenging it must have been for the participants to work through these sentences and to end up with some kind of ability to judge the grammaticality of test items after 25 minutes. For the researcher the challenge was to answer the following question: Would the participants under the different conditions end up making grammaticality judgements by relying on knowledge of the monosyllabic versus disyllabic rule for when to use the to-phrase? Or would they make their judgements aided by a stock of memorized instances (the ones they encountered in the 25-minute session)?
For the implicit group, the task required that participants remember the position of words in sentences (a modification of the implicit learning condition to memorize artificial grammar strings used by Reber). The incidental group read the sentences for meaning and answered comprehension questions (a condition that resembles Krashen’s comprehensible input; see Chapter 4, section 4.3). These two groups would encounter the verbs and the syntax of those sentences but likely process the items without any awareness of a ‘rule’ being embedded in them. Consequently, Robinson predicted they would learn a stock of instances rather than an abstract rule. That is, their responses would be fast, but accuracy would be possible only for sentences already encountered in the training, and not for novel sentences that were also included in the post-tests. Two other groups in the study experienced the items under explicit learning conditions of two kinds. The participants in the less explicit of the explicit groups saw the input typographically enhanced and were encouraged to find out the underlying rule. The participants in the more explicit of the explicit groups received an explanation of the monosyllabic versus multisyllabic rule, followed by practice. This condition, therefore, was closest to the ideal in skill acquisition theory (see sections 5.2 and 5.3). The prediction for these two explicit conditions was that training would lead to abstract generalizations, precisely because the instructions asked these participants to try to discover or to use rules, respectively. They would be able to apply rules, perhaps in a slower fashion, but they would be more accurate with new sentences during
testing, because they would be able to ‘generalize’ what they learned beyond the specific items they worked with during training.
The study results supported these predictions for the most part. Interestingly, however, the instructed (skill-acquisition-like) group outperformed all other three groups, as they were faster and more accurate on both old and new sentences. But all four groups also showed the same effect regarding a relatively faster reaction for already encountered items, as if the memory of those actual instances encountered during training had also contributed to learning, not just the conceptual guide of a rule. Robinson interpreted this as evidence that effects coexist from conceptually driven abstraction and data-driven, memory-based learning, even in the instructed condition.
In the end, then, is L2 learning possible without rules? Robinson concludes that, in the absence of rules, low-level associative learning that draws on data-driven processes supported by memory is certainly possible. Learning without rules leads to the formation of memories of instances that can be accessed more easily, allowing for faster performance, but without knowledge that can be generalized to new instances. That is, without the initial provision of rules (without an explicit learning condition), learning is bottom-up (i.e. data and memory driven), and it does not lead to knowledge of a systematic rule of some kind. With rules, learning proceeds by drawing on high-level attention and conceptually driven processes supported by conscious attention, resulting in generalization with awareness.
Robinson (1997), as well as Nick Ellis (2005) and John Williams (1999), have argued that in the future debates about implicit learning must be recast in terms of the interaction between low-level associative learning that draws on data-driven processes supported by memory and high-level cognitive learning that draws on conceptually driven processes supported by conscious attention. Both types of processing for learning can occur and both can interact. A pending question for future research is whether all aspects of an L2 are equally learnable by implicit means or whether some particularly complex aspects of the L2 may require conceptually driven processing in order for associations and representations to be formed (Ellis, 2002a, p. 174).
The reconceptualization of implicit learning as statistical learning is just one of many consequences of a wider trend in cognitive psychology to reconceptualize information processing as an associative, probabilistic, rational, usage-based, grounded, dynamic and, in sum, emergent adaptation of the agent to the environment. We finish this chapter with a forward-looking bird’s-eye view of this trend.