Robert DeKeyser (1997) investigated many of the predictions of information processing and cognitive skill theory in a clever and complicated study. DeKeyser recruited 61 college student volunteers and taught them a miniature language that he called Autopractan. He did so over 11 weeks and 22 one-hour sessions, using
picture-and-sentence exercises delivered through a computer program. Autopractan comprised a small set of 16 nouns and 16 verbs and was designed to behave like natural languages, with morphological markings for gender, number and case, and the possibility of omitting the subject and having flexible word order (that is, Autopractan was a null-subject language with rich morphology). One challenge in this kind of study is that participants may not see the benefits of trying hard to study a language that they know is artificial, and therefore of no use to them outside the experiment. In an effort to address this problem, the researcher told the volunteers their monetary compensation for participating in the study would vary depending on their scores during the experiment. The difference was a modest $8 per hour for top scores versus $6 per hour for bottom scores, but this ought to have been enough of an incentive for undergraduate students in the mid-1990s!
The first phase was provision of explicit, declarative knowledge. It involved presenting all vocabulary and grammar rules of Autopractan and having participants learn them well over the first six sessions (about three weeks). The second phase was practice. It was designed to support proceduralization, or the transformation of performance from controlled to automatic. It involved different things for different groups, but it always took 15 sessions (eight weeks) and exactly the same total number of exercises for everyone. Finally, the last session in the study (session number 22) was devoted to testing participants on four Autopractan rules via comprehension and production test items.
How did the practice phase vary across conditions? One group (n = 21) practised Autopractan rules 1 and 2 only through comprehension and rules 3 and 4 only through production. A second group (n = 20) also practised the same four rules, but they practised rules 3 and 4 through comprehension and rules 1 and 2 through production. A third group (n = 20) practised all four rules as well, but all of them through half comprehension and half production exercises. Thus, this third group engaged in mixed-modality practice of all rules, but they also got half the amount of practice for each modality. For all groups, comprehension practice was done by asking participants to match sentences they read on the computer with one out of four pictures. Production practice was done by asking them to type the sentence that would describe a given picture. Negative feedback on their answers to each item during practice was immediate and included explicit explanation of the error and showing the correct response.
All 15 practice sessions were divided into cycles of practice followed by testing. During the practice, all items were done half under normal single-task conditions and half under stressful dual-task conditions. In the latter dual-task condition, participants saw a number on the screen before an Autopractan practice item would appear; they then heard beeps at irregular intervals while doing the Autopractan practice item. After responding to the item, they had to subtract the number of beeps from the number that had appeared on the screen. The intention was to see whether the level of performance would substantially deteriorate initially (a sign that controlled processing was involved) and whether the stressor would become less obtrusive over time (a sign that automatic processing was taking over performance).
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DeKeyser looked at evidence into both the process and the product of learning. In order to understand the learning process, reaction times and accuracy were plotted over the 15 testing events taken at the end of each practice session. He found that responses quickly became faster and more accurate over the first two sessions, and that by practice session four or five performance had stabilized, with the speed and accuracy of responses remaining practically constant from that point on until the last session of practice. This pattern is predicted by the power law of learning. However, performance was essentially the same for the single- and dual-task condition items across all 15 sessions, which suggested that the distracting task in the dual condition had failed to sufficiently tax cognitive resources.
In order to document the product of learning, scores on the post-tests administered in the final session of the study were also inspected. It turned out that gains were, as predicted, skill-specific. For a given rule, the participants in the first two groups outperformed each other only on the items that tested them in the same modality in which they had practised that rule. By the same token, the balanced regime of comprehension and production experienced by the third group appeared to be effective for both comprehension and practice, with gains comparable to those made by the other two groups under the same-modality conditions.
As you see, testing the predictions of cognitive skill acquisition theory for L2 learning is complicated. Few studies have been conducted using this paradigm, and even fewer exist that document automatization over a sustained period of practice like DeKeyser (1997) did.
You may have noticed that a construct that underpins all the tenets and predictions of information processing is memory. Any information that our mind entertains, whether for milliseconds or for years, goes through memory and involves some form of memory. In the next sections, we examine some basic memory concepts and selectively look at some of the SLA insights they have spurred. Two types of memory are crucial in all cognitive operations: long-term memory and working memory. As we will see, both are fundamentally involved in second language processing and learning.