Learner modelling through interactional data collection
David Alfter
Språkbanken
University of Gothenburg
WHY
HOW
WHAT
Learner modeling
Why
Language learning individual experience
Learner differences
- Prior knowledge
- Learning speed
- Learning style
- Language background
Online learning platforms rarely personalized
Fixed progression path
Personalized learning environments
Collection of available tools
How
Collect data from learners using the platform
Profile: static
Learner model: dynamic
- Track learner activity on platform
- Continuous assessment
- Stealth assessment
What
Profile
Education background
Language background
Swell project
Interdisciplinary
Collaboration with teachers
Learner model
Data collected during interaction with learning platform
General data
Not learner-specific
- Current time
- Frequency of use
- Time since last visit
- Screen size of device
- IP address
- Geolocation
Multiple choice vocabulary exercise
- Time taken
- History
- Final answer
Variables to collect
Spelling exercise
Spelling exercise
- Frequent (L1 specific) misspellings
- Difficult sounds
- Diagnostic and prognostic
Hypothesis testing
Evaluation of automatically graded vocabulary list
Grading of new vocabulary items
Adaptive diagnostic test
Different exercise types
- Bundled gaps
- Vocabulary knowledge
- Sentence rearrangement
- Sentence composition
- Multiple choice
Teacher evaluation
To infinity and beyond
- Morphology
- Grammar
Error analysis
Error groups
Thank you for your attention!
Please clap and don't ask tough questions
Learner modelling through interactional data collection
By daalft
Learner modelling through interactional data collection
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