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A Domain Specific Language to retrieve objective
indicators for foreign language learning in virtual
worlds
Antonio Balderas
Anke Berns
Manuel Palomo-Duarte
Juan Manuel Dodero
Raul Gomez-Sanchez
Iván Ruiz-Rube
ISELEAR'15
Contents
● Introduction
● Design and architecture
● Proposal
● Case Study
– Settings
– Hypothesis
– Analysis
● Conclusions
Introduction
● Foreign language courses (ECTS)
– few hours of language practice in class
– many hours of independent learning
● We use 3D virtual worlds to:
– Encourage independent learning
– Provide a fun and “natural” learning environment
● Issues with monitoring and assessment:
– Aim: make learning analytics available for everyone
Introduction
Some game worlds we implemented for
language learning:
Design and architecture
● We use the Opensim virtual world engine
– Well-known reliable open source
– Client-server approach
Design and architecture
● We use the Opensim virtual world engine
– Interesting game information is stored
– Programming skills are needed to get it
SQL +
script
Design and architecture
● We use the Opensim virtual world engine
– We propose using a Domain Specific Language to
retrieve information from students' interaction in
Opensim Virtual Worlds
VWQL
Proposal
● Virtual Worlds Query Language (VWQL)
– Model-drive approach (xtext + EMF) → EvalSim
– Syntax:
Evidence name_of_the_evidence:
get students [id_of_the_student]
show ( words [dict] | sentences | single | turns | time |
points )+
Proposal
● Hypothesis contrast / indicator refinement cycle
Initial proposal
VWQL
query
Satisfies?
submit
reply
NO
YES
analyze
refine
Case study: settings
● German as a second foreign language course
– 5 students (B1 CEFR) participated
● Virtual world implements a joint shopping task:
– Two players: client and shop-assistant
– Coordination communicating via text-chat
Case study: hypothesis
● Skill:
– make themselves understood in the foreign language
● Following hypothesis was established:
– A student had difficulties to make himself understood if he
needed 2+ sentences, per turn, to communicate with his
teammate
● Initial proposed query:
Evidence time_sentences:
get students
show time , sentences
Student1 Student2 Student3 Student4 Student5
0
10
20
30
40
50
60
70
80
90
Minutes played
Sentences
Case study: first analysis
Student Speaking
pace
Student1 1.22
Student2 1.50
Student3 0.80
Student4 2.22
Student5 1.50
Case study: refinement
● Refined query: focus on sentences and turns
rather than on time and sentences
Evidence sentences_turns:
get students
show sentences , turns
Case study: second analysis
Student Average of
sentences per turn
Student1 1.83
Student2 2.00
Student3 2.14
Student4 4.10
Student5 2.00
Conclusions
● We have defined VWQL, the first Opensim virtual
world Specific Language
– Easy syntax, no programming skills needed
● We proposed a refinement cycle to scale
monitoring or assessment
– It was applied to a simple case study
● Future work: extend the language to identify
exclamations, Wh-questions, etc.
Thank you for your attention!
Questions?

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A DSL to retrieve objective indicators for foreign language learning in virtual worlds

  • 1. A Domain Specific Language to retrieve objective indicators for foreign language learning in virtual worlds Antonio Balderas Anke Berns Manuel Palomo-Duarte Juan Manuel Dodero Raul Gomez-Sanchez Iván Ruiz-Rube ISELEAR'15
  • 2. Contents ● Introduction ● Design and architecture ● Proposal ● Case Study – Settings – Hypothesis – Analysis ● Conclusions
  • 3. Introduction ● Foreign language courses (ECTS) – few hours of language practice in class – many hours of independent learning ● We use 3D virtual worlds to: – Encourage independent learning – Provide a fun and “natural” learning environment ● Issues with monitoring and assessment: – Aim: make learning analytics available for everyone
  • 4. Introduction Some game worlds we implemented for language learning:
  • 5. Design and architecture ● We use the Opensim virtual world engine – Well-known reliable open source – Client-server approach
  • 6. Design and architecture ● We use the Opensim virtual world engine – Interesting game information is stored – Programming skills are needed to get it SQL + script
  • 7. Design and architecture ● We use the Opensim virtual world engine – We propose using a Domain Specific Language to retrieve information from students' interaction in Opensim Virtual Worlds VWQL
  • 8. Proposal ● Virtual Worlds Query Language (VWQL) – Model-drive approach (xtext + EMF) → EvalSim – Syntax: Evidence name_of_the_evidence: get students [id_of_the_student] show ( words [dict] | sentences | single | turns | time | points )+
  • 9. Proposal ● Hypothesis contrast / indicator refinement cycle Initial proposal VWQL query Satisfies? submit reply NO YES analyze refine
  • 10. Case study: settings ● German as a second foreign language course – 5 students (B1 CEFR) participated ● Virtual world implements a joint shopping task: – Two players: client and shop-assistant – Coordination communicating via text-chat
  • 11. Case study: hypothesis ● Skill: – make themselves understood in the foreign language ● Following hypothesis was established: – A student had difficulties to make himself understood if he needed 2+ sentences, per turn, to communicate with his teammate ● Initial proposed query: Evidence time_sentences: get students show time , sentences
  • 12. Student1 Student2 Student3 Student4 Student5 0 10 20 30 40 50 60 70 80 90 Minutes played Sentences Case study: first analysis Student Speaking pace Student1 1.22 Student2 1.50 Student3 0.80 Student4 2.22 Student5 1.50
  • 13. Case study: refinement ● Refined query: focus on sentences and turns rather than on time and sentences Evidence sentences_turns: get students show sentences , turns
  • 14. Case study: second analysis Student Average of sentences per turn Student1 1.83 Student2 2.00 Student3 2.14 Student4 4.10 Student5 2.00
  • 15. Conclusions ● We have defined VWQL, the first Opensim virtual world Specific Language – Easy syntax, no programming skills needed ● We proposed a refinement cycle to scale monitoring or assessment – It was applied to a simple case study ● Future work: extend the language to identify exclamations, Wh-questions, etc.
  • 16. Thank you for your attention! Questions?