Contrastive Analysis in Language Teaching, Time to Come in from the Cold. (Language Teaching & Learning)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The purpose of this short paper is to first argue that the rejection of the value of contrastive analysis (CA) input in foreign and second language teaching (FSLT) in the 70% and beyond was unjustified on both theoretical and empirical grounds and then, based on classroom-based research, demonstrate the value teachers of using CA in their teaching. ********** Very few teachers in FSLT of any experience would deny the value of some degree of explicit understanding of the grammar of the language they are learning. Though that understanding in some simple cases may be derived from exposure to comprehensible input, there is ample evidence to demonstrate that learners in normal classroom situations are unable to acquire most grammatical knowledge without the benefit of explicit grammar instruction. Furthermore, it is contended here that that understanding may be facilitated by an awareness of the differences between the L1 and the TL. To put this in concrete terms, francophones when asked a question such as How long have lived here for? will tend to reply live here two years, based on the French Je demeure ici deux ans. Similarly, they may say have 15 years and am born in Montreal calquing the French forms. To help learners overcome such problems, CA input enables them to understand the reasons such errors and thereby go some way to avoiding them. In the case of the first example, one of the errors is caused by the fact that depuis may function with both the meaning of for and since. Students need to understand this contrast and then to grasp the fact that for is used a period of time whereas since refers to the point in time at which the period began as in have lived here four years/I have lived here 1995. All language groups engaged in FSLT will make many such L1-influenced errors. Furthermore, though all errors are potentially fossilisable, a number of studies have shown that it is L1-influenced errors which will prove to be the most persistent (See Sheen 1981, Marton 1981, Mukattash 1986). Given then the substantive presence of L1-influenced errors, their tendency to become fossilised, and, assuming the validity of the premise that learners need to understand the nature of that influence in order to overcome it, it is difficult to understand how the field of language teaching and applied linguistics allowed and even encouraged the rejection of CA input in the 70% and has continued to sanction it. In order to help in the understanding of this rejection, I will trace the events which caused it and demonstrate the degree to which it was unjustified. Then, based on this and the description of classroom-based research studies, I will argue the reintegration of CA input into FSLT. Following the success of the Army Special Training Programme (partly based on behaviourist learning principles) in WW II in teaching American soldiers foreign languages, the early fifties saw the development in US universities of a structural teaching approach which was to develop into the audiolingual method (See Brookes 1964). This method revolutionalised and dominated language teaching in the decades following. CA became an integral part of the method as it was argued that habits associated with the L I would interfere with the learning of the TL. Thus, because francophones say J'ai 15 ans, they will tend to say have 15 years in English rather than I'm 15, at least in the case of beginners. Thus. CA was exploited in order to identify those linguistic habits of the LI which were different from the TL and which might, therefore, cause errors. This then informed material writers as to the forms which would require special attention in the repetition and memorisation drills which characterized the audiolingual method. Furthermore, it was argued that the large majority of errors were caused by L1 influence and that they could be predicted by CA. …
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it