1. APPLICATIONS
1.1. INTELLIGENT LANGUAGE TUTORING SYSTEM (ILTS)
1.1.1. Contextual, corrective feedback
1.1.1.1. Pedagogically appropriate/informative
1.1.1.2. Exact location and source of error
1.1.1.3. Large range of unanticipated errors
1.1.1.4. Spelling, morphological, syntactic and semantic errors
1.1.2. Identifies, interprets errors & correct constructions
1.1.3. Focus on learner-computer interactions
1.1.4. Used in regular L2 curricula
1.1.4.1. E-Tutor (L2 German)
1.1.4.2. Robo-Sensei (L2 Japanese)
1.1.4.3. Tagarella (L2 Portuguese)
1.1.5. Inductive approach
1.1.6. Less restrictive than text books
1.1.7. Dickinson et al. (2008)
1.1.7.1. L2 Korean particle usage through embedded CMC environment.
1.2. LANGUAGE TOOLS
1.3. ADVANTAGES
1.3.1. Opportunities for learner-computer interactions with computer reactions
1.3.2. Detects errors
1.3.3. Gives error-specific feedback
1.3.4. Gap between learner's interlanguage and the target language through salient modified language input
2. COMPUTER AS A TOOL
2.1. MICROSOFT RESEARCH ESL ASSISTANT
2.1.1. Web-based proof reading
2.1.1.1. Target: syntactic, morphological, lexical selection errors.
2.1.1.2. Correction suggestions
2.1.1.3. Allows exploring and comparing usage to real-world examples
2.2. WERTi (NLP ARCHITECTURE)
2.2.1. Visually enhanced webpages
2.2.1.1. Highlights/annotations of grammatical forms
3. OTHER ICALL TOOLS
3.1. Context-sensitive inflectional paradigms
3.1.1. Morphological analyzers
3.1.2. Grammar and spell checkers
3.1.3. Online dictionaries
4. NATURAL LANGUAGE PROCESSING (NLP)
4.1. computer model of human language - linguistic representation of student input.
4.1.1. Informative, error specific feedback
4.1.2. Instructional guidance/scaffolding
4.1.3. Current learner interlanguage state
5. EXPERT SYSTEMS
5.1. Provides the knowledge base of the facts.
5.1.1. Rich source of a linguistic knowledge
5.1.2. Access knowledge base during task completion
5.2. Provides rules about the language
5.2.1. Comprehensive reference tool in learner-computer interactions