COMPUTER AIDED LANGUAGE LEARNING

INTRODUCTION

 Gamper and Knapp (2002) define Computer-Aided

Language Learning (CALL) as “a research field which

explores the use of computational methods and techniques

as well as new media for language learning and

teaching” (p. 329). In more general terms, CALL can

be thought of as the use of computers to help learn

languages. As a sub-category of Computer-Aided

Learning (CAL), CALL deals exclusively with learning

languages. Specific examples of CALL tools and

utilities include games, tests, exercises, and word

processing, and their use in a CALL session is

determined by the syllabus, software, teacher, or

learner. 

The popularity of CALL is constantly increasing as

multimedia developments and technology are advancing.

In the last few years, CALL systems have

become fully integrated with audio and video support,

creating interesting and attractive presentations. With

the Internet emerging, a new platform for CALL

systems has evolved. Thus, there has been a move

from CD-ROM-based CALL to online Web-based

CALL, enabling more connectivity and interactivity

with other students or teachers. Important examples

of why CALL has moved to Web-based mediums

include the ability to carry out audio and

videoconferencing, use chat rooms and e-mail, and

communicate with native speakers of the language.

CALL METHODOLOGY
As Hubbard (1996) points out, the question for many
language teachers now seems to be not whether, but
how computers can aid in the language learning
process. The use of computers in language acquisition
is becoming common practice, a challenge for research,
and a business opportunity.
In 1987 Hubbard found that courseware reviews
commonly focus on technical considerations, and that
this was sometimes at the expense of language teaching
and learning considerations. He proposed a CALL
Methodological Framework (Hubbard, 1987) that
synthesises the previously developed frameworks of
Philips (1985) and Richards and Rodgers (1982). Key
players in Hubbard’s (1987) framework are the learner,
the developer, the evaluator, and the teacher.
Hubbard’s methodology consists of three modules—
development, evaluation, and implementation—in
which “development necessarily precedes evaluation
while both development and evaluation precede implementation.”
Furthermore in this framework, an integral
approach to evaluation, development, and implementation
is followed where “evaluation can inform
development and implementation experiences can
inform both development and evaluation” (Hubbard,
1996, p. 20).

Development Module

Hubbard’s development module comprises three sections:
approach, design, and procedure. In the approach
section, linguistic assumptions and learning
assumptions are the two principal determining elements.
The two fundamental components of the
design section are the learner profiles and the syllabus.
Finally, the procedure section of the development
model contains the elements to be considered in
the actual layout of the program that presents the
materials (Hubbard, 1996).

Evaluation Module
The evaluation module is made up of three sections:
teacher fit (approach), learner fit, (design) and operational
description (procedure). This module focuses
on pedagogical issues like learning style, teaching approach, and linguistic assumptions (Hubbard, 1996).
Although not addressed by Hubbard, one can assume
that the evaluation module can also contain elements
of usability evaluation of the CALL system.

Implementation Module
The implementation module is constituted by the
areas to be considered for the implementation such as
accessibility, the flow of a CALL lesson, learner use
of courseware, and teacher control. Hubbard (1996)
states: “The two aspects of particular note are the
central role of teacher control in learner use and the
importance of supporting preparatory and follow-up
activities” (p. 31).

Future of CALL
In this section we discuss several elements related to
the present and the immediate future of CALL. There
are examples of CALL systems today that we could
not even think of years ago. In the same way, and due
to the largely increased interest in CALL research and
applications, in the future there will probably be
CALL systems available with functionality that at the
present either seem unattainable or unrealistic.

Intelligent CALL
Intelligent Computer-Assisted Language Learning
(ICALL) has already started to be implemented.
ICALL explores the use of Artificial Intelligence
methods and techniques for language learning (Gamper
& Knapp, 2002). The following is a brief description
of a few AI techniques that are starting to be used in
CALL systems:
• Speech recognition technologies have reached
the stage where CALL learners can talk into the
microphone, and their pronunciation and fluency
are tested, giving them results on their
progress. One such CALL software that takes
advantage of speech recognition technologies is
the “Tell me more education®” packages (see
http://www.auralog.com). In the future, speech
recognition will reach the stage where a conversational
conversational
mode can exist between the learner and
the computer, just like the learner would have a
conversation with a “living” person.
• Expert systems work by storing large amounts of
knowledge about language learning. This knowledge
includes questions and answers, typical
mistakes, and learning strategies. It is then used
to analyse the learners’ interaction with the
computer and produce detailed feedback.
Other AI techniques for CALL include Machine
Translation (e.g., “Babel Fish Translation®”; see
http://babelfish.altavista.com) and Intelligent Tutoring
Systems (e.g., personalised learning environments).

Computer-Assisted Language Testing
Computer-Assisted Language Testing (CALT) can be
defined as “an integrated procedure in which language
performance is elicited and assessed with the help of
a computer” (Niojons, 1994). Like CALL, CALT is
not a relatively new field, but interest in this area has
increased significantly in the past few years. A very
common example of the use of CALT is for multiple
choice questions. If the testing system is designed and
implemented correctly, then the results of the computer
testing will be immediate and without errors,
whereas if multiple choice questions are corrected by
people, there is always the possibility of human error,
and also the process is a lot lengthier and time
consuming. CALT systems can be used for reading
tests, listening tests, and writing tests. Games can also
be used as CALT systems. For example, hangman is
a great word game, and is fun and engaging. It is
important, however, for CALT programs to provide
the learners with clear and accurate feedback results.
One of the most successful CALT systems is the
one used for the TOEFL exams. The Test of English
as a Foreign Language (TOEFL) is taken worldwide
by nearly a million people each year. It is an important
test since the results determine whether students are
to be accepted into many U.S. universities. TOEFL
used to be a ‘pen-and-pencil’ exam, but since 1998 it
has become, and still is, a computer-based exam
taking advantage of CALT.
CALT will continue to play a vital role in the future
of Computer-Assisted Language Learning.

C O N C L U S I O N
In this article we defined CALL, presented a CALL
methodological framework, and discussed the future
of CALL. As Ahmad, Corbett, Rogers, and Sussex
(1985) pointed out, CALL arose from the combination
of two separate factors: educational needs and technological
means. The constant advances in technology
are creating new and exciting opportunities for the
delivery of CALL systems. However, one must not
focus solely on the technology side of CALL. Pedagogical
issues are also extremely important for a
successful language learning process. With both pedagogy
and technology together as the focus of CALL
research, the final systems implemented more accurately
meet the language learning educational needs by
providing a plethora of language learning activities.
Today CALL is more popular than ever. The Internet
and the World Wide Web have provided us with
delivery methods that have created language learning
opportunities that were unimaginable a few decades
ago. Videoconferencing has given us virtual classrooms.
The field of CALL is continually gaining
interest. Intelligent CALL includes techniques like
speech recognition to test the learner’s pronunciation
and accent. The future of CALL looks promising!




Source : https://www.researchgate.net/publication/264042313_Computer-Aided_Language_Learning/