1) Computer-assisted language learning (CALL) involves using computer technology to help facilitate foreign language education, from early "little" programs that provided basic drills to later more sophisticated "courseware". 2) Early CALL programs focused on activities like vocabulary drills, gap-filling exercises, and multiple choice tests, while later purpose-built programs provided more complete lessons with stimuli, learner responses, feedback, and branching. 3) Natural language processing (NLP) technologies like parsers can be used in CALL to check grammar, analyze learner errors, and provide targeted feedback as part of a personalized learning experience.

1. CALL:
Computer-Assisted Language Learning

2. 2/14
Computer-Assisted (Language)
Learning
• “Little” programs
• Purpose-built learning programs
(courseware)
• Using existing technology for educational
purposes
• CALL and NLP
• Learner corpora

3. 3/14
“Little” programs
• From earliest days of “microcomputers”,
enthusiasts saw ways to implement
programs to help learners
– Programmed in low-level languages, eg Basic
– Crude implementations based on activities
which were already part of (language)
learning
– e.g. vocabulary drills, gap-filling exercises

4. 4/14
“Little” programs
• Often admirable attempts to use new
technology
• Usually programs were “one-off”
– No separation of algorithms and data
– Each exercise was a self-contained program
• Quite easy to “modularise”
– have a generic program which would “load” a
data file, containing quiz questions and
answers

5. 5/14
Issues
• Content / design determined by technological or
pedagogical concerns/issues?
– Find some use for technology that is available, or
– Design programs to do what you really want
• Flexibility and reuse
– Lot of effort goes into design, so best if design allows for multiple
reuse
– Notion of “authoring” packages
– Allowing multiple correct answers
• Student-driven learning
– Student can work at own time and pace
– Role of teacher (if any) very different
– Some systems designed for “teach-yourself” scenario

6. 6/14
Typical CALL programs at this level
• Multiple-choice tests
• Matching activities
• Item list learning and testing
– Vocabulary test (L1→L2, L2 →L1, picture naming)
– Writing system (eg Japanese, Chinese characters)
• Gap filling drills
– Grammatical forms (agreement, tenses)
– Vocabulary
• Note difficulty of allowing creative language use, due to
need to check right answer
– E.g. “compete this sentence with an appropriate adjective”
– Alternative allowable answers must be explicitly predicted

7. 7/14
Purpose-built CALL programs
• “Courseware”
• Much more than computerized exercises
• “Typical CALL programs present a stimulus to which the
learner must respond. The stimulus may be presented in
any combination of text, still images, sound, and motion
video. The learner responds by typing at the keyboard,
pointing and clicking with the mouse, or speaking into a
microphone. The computer offers feedback, indicating
whether the learner’s response is right or wrong and, in
the more sophisticated CALL programs, attempting to
analyse the learner’s response and to pinpoint errors.
Branching to help and remedial activities is a common
feature of CALL programs.” (wikipedia)

8. 8/14
Learner’s input – typed, spoken, other GUI
Stimulus – text, picture, sound, video
Is response appropriate?
Feedback to user
Lesson plan
Student model
Explanations etc.

9. 9/14
Using existing technology
• Use in the classroom of technology
designed for other purposes
– Playing computer games in the L2
– Using L2 word processors, spell checkers and
other packages
– Speech recognition as pronunciation training
– Use of synthetic speech to create spoken
language material
– Use of MT (mainly to illustrate language
differences)

10. 10/14
CALL and NLP
• What is the role of parsing technology in
CALL?
– Parsers can allow creative writing to be part of
CALL package
– Parser as a grammar checker
– Parser as an error checker

11. 11/14
Parser as a grammar checker
• Especially with beginners and intermediate
learners, since range of structures and
vocabulary is more limited
• Parsers can (usually) not only say whether a
sentence is grammatical, but also why (and
where) it is ungrammatical
• Errors can trigger feedback messages, and can
send information to the student model
– For example, errors in agreement might indicate that
student hasn’t yet grasped this concept, so needs
some more instruction

12. 12/14
Parser as an error checker
• Parsing mechanism can also be used to
look for particular (expected) errors
• “Grammar of errors”: parser has rules
which specifically capture ungrammatical
sentences
• If input can be parsed, then there is an
error
• Otherwise, sentence is “correct” (ie no
error detected)

13. 13/14
Grammar checking for language
learners
• Long experience of language teaching
tells us what errors to expect
– Some errors are due to inherent complexities
of the language
– Other errors are due to interference from a
particular L1

14. 14/14
Learner corpora
• Language teaching meets corpus
linguistics
• several efforts to collect corpora of
learners’ writing
– Notably International Corpus of Learner
English (ICLE), Louvain University
• several efforts to collect corpora of
learners’ writing
– Study of “interlanguage”