ENG 5 Q4 WEEk 1 DAY 1 Restate sentences heard in one’s own words. Use appropr...
A Domain Specific Language 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
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
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 )+
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.