BERKELEY INSTITUTE OF DESIGN BD Localized Iterative Design for Language Learning in Underdeveloped Regions: The PACE Framework Matthew Kam Divya Ramachandran Varun Devanathan John Canny Berkeley Institute of Design & Computer Science Division University of California, Berkeley Anuj Tewari Dhirubhai Ambani Institute of Information & Communication Technology (India) CHI 2007 San Jose, CA
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BERKELEY INSTITUTE OF DESIGN Localized Iterative Design for Language Learning in Underdeveloped Regions: The PACE Framework Matthew Kam Divya Ramachandran.
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BERKELEY INSTITUTE OF DESIGN
BDLocalized Iterative
Design for Language Learning in
Underdeveloped Regions:
The PACE Framework
Matthew KamDivya RamachandranVarun DevanathanJohn CannyBerkeley Institute of Design &Computer Science DivisionUniversity of California,
Berkeley
Anuj TewariDhirubhai Ambani Institute ofInformation & CommunicationTechnology (India)
CHI 2007San Jose, CA
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Relevance of English as a Second Language (ESL) in India
• English is a global language: 1.2 to 1.5 billion people in >170 countries (Crystal 1997)
• ESL is taught in almost all schools in India
• Mastery of English is the “single most influential factor that determines access to … important avenues of economic and social advancement” (Kishwar 2005)
• 90% of indigenous web content in India is in English
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
“World Language” Fluency
• Low-income populations in Africa, Asia and Latin America desire to improve command of an appropriate “world language” (Clegg, Ogange & Rodseth 2003; Faust & Nagar 2001; Kapadia 2005)
• Widely spoken language, e.g. English, Mandarin, Spanish, etc.
• Regional dialect is not necessarily native language for low-income groups
• “World language” fluency opens the door to further education, “New Economy” jobs, higher incomes, social prestige, etc.
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Schools Fail at “World Languages”
• Schools in developing countries have limited impact
• For example, in India:
• Rural ESL teachers communicated with us through interpreters
• 43% to 61% of school-going-age children do not attend school regularly (Azim Premji Foundation 2004)
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Our Envisioned Solution
• Mobile games that target learning anytime, anywhere
• Make ESL learning resources more accessible
• Make learning process more enjoyable
• Run on cellphones, the fastest growing technology platform in the developing world
• Target local language learning needs
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Case for e-Learning Games
• Enhance motivation and learning (Jenkins 2005)
• Incorporate good learning principles (Gee 2003)
• Prior randomized experiment (Banerjee et al. 2005)
• 2 years, >10,000 urban slums students in India
• Played math computer games twice per week
• Significant gains in math test scores
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Central Question
How can we promote reuse when localizing language learning software applications with communities in the developing world?
Recurrent challenges:
• Limited time for iterative design in the field
• Wide disparity in age, etc. for each literacy level
• Limited exposure to high technology
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Related Work: Localization
• Adapting software for a local context involves two steps
1. Internationalization
2. Localization
• Previous work have mostly focused on the user-interface, not content (e.g. Marcus and Gould 2000, Smith et al. 2004, Yeo 2001)
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Design Pattern
• “Template” solution to previous problem
• For ESL learning task, a design pattern is the steps that learner engages in to develop language skills
• Benefits:
• Represent solutions to frequent problems in skeletal form
• Encourages reuse, avoids reinventing the wheel
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Example Learning Activity (from: Rosetta Stone)
• Word-picture matching activity
• Targets vocabulary building and listening comprehension
• Teaches four words
• Highlights each picture as its word is played aloud
• Then tests learner
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Solution (Suppose X=4, i.e. teach 4 words per round):
Repeat step 1 for X times:1. Says a word and displays its meaning pictorially
Repeat steps 2-3 for X times:2. Displays one of the X words from step 13. Give learner at least X pictures to choose from, and feedback on whether or not his choice was correct
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Related Work: Design Patterns• Patterns have not been used in instructional
design for language learning nor software localization
• Have been used in
• Urban planning and architecture (Alexander 1977)
• Software engineering (Gamma et al. 1995 aka “Gang of 4”)
• Interaction design (Borchers 2001)
• Website design (Van Duyne et al. 2002)
• Computer science education (Bergin)
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
PACE Framework
• The four components of PACE framework
• Pattern
• Activity
• Curriculum
• Exercise
• Pattern Activity Curriculum Exercise
• Modular design and reuse
• Localize only those parts that need changing
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Early Lessons (Spring 2006)• Worked on over 30 ESL learning games
• Introduced patterns after finishing initial designs
• Initial lessons• Use patterns as a “generative” design tool,
not in “formulaic” manner• Facilitate iteration on user-interfaces and
curriculum by keeping them separatePattern ? ? Exercise on cellphone
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
On to Round 2! (Summer 2006)
• Distilled >50 patterns
• Shortlisted 11 patterns for language beginners
• Letter-sound correspondences (reading and writing skills)
• Word-meaning associations (listening and reading skills)
• Pronunciation (speaking skills)
• Syllable segmentation (reading skills)
• Consulted ESL teacher with teaching experience in rural Central America on these patterns
PACE: Pattern Activity Curriculum Exercise
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Sample of Commercial Packages• Reviewed >35 language learning
applications from commercial market
• Sample was selected based on proxy indicators
• Professional customer base
• Excellent ratings from previous purchasers on e-commerce, home schooling, etc. websites
• Selected for balance between listening, reading, speaking and writing skills
PACE: Pattern Activity Curriculum Exercise
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Approach to Extracting Patterns
• Theory
• First language acquisition for children (Bruner 1983)
• Second language acquisition for children & adults (Bialystok & Hakuta 1994, Krashen 2003)
This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Conclusion
• Design patterns
• Capture best practices (internationalization)
• Facilitate adaptation to local contexts (localization)
• Yield positive learning outcomes
• PACE framework facilitates
• Rapid iterative design in the field
• Flexibility for differences in age groups and learner levels
• Reuse, learnability and scalability
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This material is based upon work supported by the National Science Foundation under Grant No. 0326582.
Acknowledgement
• Local community partners (India) • Urvashi Sahni, Pratim Basu, Siddharth Bhagwani
• Colleagues• Ruth Alexander, Asya Grigorieva, Dimas
Guardado, Jeffrey Heer, Kristopher Hom, Maksim Lirov, Aaron McKee, Anand Raghavan, Priyanka Reddy, Aretha Samuel, Monish Subherwal, Susan Woolley
• Anonymous reviewers and Associate Chairs• National Science Foundation (Grant No. 0326582)• Microsoft Research (Digital Inclusion award)• Intel Undergraduate Research Program