From Psycholinguistic Modelling of Interlanguage in Second Language Acquisition to a Computational Model

The present article demostrates the implementation of a psycholinguistic model of second language learners' interlanguage in an Intelligent Computer Assisted Language Learning (ICALL) system for studying second language acquisition. We have focused our work on the common interlanguage structures of students at the same language level. The Interlanguage Level Model (ILM) is made up of these structures. In this paper we explain the conceptual model of ILMs, we present the experimental method followed for collecting written materiM, we describe the output of the modelling tool, and finally some conclusions and future work are outlined. 1 I n t r o d u c t i o n The main goal of this article is to show the implementation of a psycholinguistic model of second language learners' interlanguage in an Intelligent Computer Assisted Language Learning (ICALL) system for studying second language acquisition. The ICALL system, and the computational model for representing interlanguage, have been designed after previous work on psycholinguistics, artificial intelligence, and computational linguistics. This article will be focused on the computational model of interlanguage. Description of the ICALL system can be found in (Maritxalar et al., 1994). The concepts transitional dialects (Corder, 1971) and approximate systems (Nemser, 1971) are precursors to interlanguage (Selinker, 1972) (Selinker, 1992). Their aim was to define communicative and grammatical competence in second languages. All of them have these common features: a) a student's discourse is i n d e p e n d e n t f r o m the nat ive language (L1) and the target l a n g u a g e (L2) and it is the product of a s t ruc tured l inguist ic syst e m ; b) the linguistic system is va r i ab l e during the learning process and it is v e r y similar in s t u d e n t s of the same language level , with the exception of some differences, results of a person's learning experience. In our case, the above mentioned characteristics are the basis for modelling the interlanguage. For example, as the linguistic system is very similar in students of the same level, we can infer that we will have an interlanguage model for each level. Therefore, in our ICALL system we find a module where the different Interlanguage Level Models (ILMs) of each language level are represented. Representation of the ILMs will be presented in this article. Our work is based on corpus analysis. At this moment we have focused on the implementation of the morphological and morphosyntactic competence at word level. Work at word level is important in our case because Basque is an agglutinative language with rich morphosyntactic information within words. We have studied texts written by Spanish students of Basque. We are aware of the limits of the modelling only taking into account written material. Spoken material could also be collected for a better modelling. However, as the computational tools we have for studying Basque are only for writing studies, we have discarded the treatment of the spoken output of the learners. In the next section we will explain the conceptual model of ILMs by means of the KADS Domain Description Language (DDL) proposed in Schreiber (Schreiber et al., 1993). Next, we will give an idea of the experimental method used in order to collect written material and the top-down methodology used in order to model interlanguage in support of the selected corpora. After that, we will describe some of the implemented tools for modelling ILMs. Martxalar, Diaz de Ilarraza ~ Maite Oronoz 50 Computational Model of Interlanguage Montse Maritxalar, Arantza Dfaz de llarraza and Make Oronoz (1997) From Psycholingulstic Modelling of Inter language in Second Language Acquisition to a Computational Model. In T.M. Ellison (ed.) CoNLL97: Computational Natural Language Learning, ACL pp 50-59. {~) 1997 Association for Computational Linguistics Then, we will describe the output of the modelling tool, in order to compare the information given by the computational tool and the conceptual model of ILMs proposed before. Finally, some conclusions and future work are presented. 2 A Conceptual Model for Interlanguage Level Models In this section we show the psycholinguistic model for Interlanguage Level Models (ILMs). The ILMs characterise different grammars of the interlanguage the ideal learner can have for the second language at each language level. It must be noted that, although some linguistic structures are particular to each student, others are common to all students at the same level. These common structures are those which will be represented in the ILMs. We represent ILMs by means of two different types of sequences of models: consecutive sequences and embodied sequences. For each level, two different kinds of knowledge are represented: the variable knowledge, the knowledge the student is supposed to be learning; and, the fixed knowledge, the knowledge the learner has already acquired. The knowledge the language learners have acquired at a concrete level includes the knowledge acquired at previous levels. However, the knowledge they are learning at each level follows a different structure: each model from each level is independent from other levels, although intersections between knowledge at different levels t an occur at times. The set of different variable language structures at each language level consists of consecutive sequences of models, while the set of fixed ones consists of embodied sequences (see Fig. 1). When we say fixed knowledge or variable knowledge we refer to the language structures the learners have in their interlanguage, without making any distinction between the representation of correct and "incorrect" structures. When we specify interlanguage all the language structures, right and "deviant", are represented in the same way. It must be noted that while a language structure used by high level learners can be considered deviant, the same structure in the case of beginners could be seen as correct at their level. For example a deviation at 10th level like avoiding the word ote 'could' (i.e. nor da? 'who is?' instead of nor ore da? 'who could be?' ) is not considered a deviation in lower levels of the language. Language structures of the interlanguage are context-dependent (Selinker, 1992). Language learners create discourse domains as contexts for interlanguage development. c L lg