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Conversation table using Google Hangout:
from online chat to F2F chat
-written fluency and oral fluency
development2014 WAFLT Fall Conference
Nov. 8th, 2014
Kazuhide Takeuchi - Indiana University Bloomington
Outline
1.
2.
3.
4.
5.
Purpose/motivation of the study
Previous studies
Present study
Result/analysis
Conclusion/suggestion
Purpose and motivation of this study
1. Time management
• Four skills and culture
• Larger class size
• Curriculum
2. Practice opportunity
• Balance of input and output
• Participants’ level difference
3. Assessment
• Subjective and objective
• Practicality
Previous studies
• CMC increase participation, motivation, understanding
Payne and Ross (2005), Blake (2009), Yang et al (2012)
• Higher improvement on speaking than face-to-face
Payne and Whitney (2002)
• Written production are related to oral production
Payne and Whitney (2002), Toyoda and Harrison (2002)
• Higher production rate = higher fluency
Kormos and Denes (2004), Ginther et al (2010)
• Other characteristics influencing fluency
• Complexity, location of disfluency, balance
Lennon (1989), Brand and Gotz (2011)
Hypothesis
1. Online text chat style conversation table helps learners’ oral fluency
development.
2. Temporal measures and holistic rating have a positive correlation.
Study 1
Spring 2014
• Who?
• 4 Volunteered students from second and third year Japanese
• 2 male and 2 female
• One 3rd year student and three Japanese native speakers
participated only conversation table
• What?
• Treatment: weekly online text-chat style conversation table
on Google Hangout. (about 6 weeks during the spring 2014)
• Assessment: pre/post-test free speaking task (few minutes
about winter/spring break)
• Holistic rating and temporal measures
What is Google Hangouts?
• Free instant messaging and video chat
• Free! For Google+ account holder
• No limitation for text-chat participants
• Can be a private or an open group
• Accessible from computer and smartphone
Google Hangouts sample
Temporal measures
• Speaking rate (SR) = total number of mora divided by total time (including
pause)
• Articulation rate (AR) = total number of mora divided by total speaking time
(excluding pause)
• Phonation time ratio (PR) = total speaking time divided by total time
• Mean length of run (MR) = total number of mora (excluding filled pause)
divided by total number of runs (speech segment occurring between pause
of 0.25sec or grater)
*in this study, pause (filled/unfilled) was defined a duration of silence or non-word sound
(i.e. filler) longer than 0.25seconds.
Lennon 1990, Towel et al. (1996), Cucchiarini (1999), Kormos and Denes (2004), Payne and
Ross (2005), Blake (2009), Ginther (2010), and Brand and Gotz (2011)
<Insert audio here>
なつやすみに、あ~・・ともだちと~うみにいき~(pause)ました。
Summer break time (filler) friends with (filler) beach direction go (pause)-past
na tsu
ya su mi ni
ah~ to mo da chi to~
u mi
I went to a beach with friends this summer.
Speaking time = Total time = Mora = 19 Run = 4
SR: = AR: = PR: = MR: 19/4 = 4.75
ni
iki~(pause) ma shi ta
Results
Holistic Rating
Did not participate
5
conversation table.
4
3
2
1
0
3.1
3.2
pre
2.1
post
2.2
Result 2
Changes in production rate
2.00
1.60
1.20
0.80
0.40
0.00
-0.40
3.1
3.2
2.1
-0.80
-1.20
-1.60
SR
AR
PR
MR
2.2
Results and analysis
• Very small improvement on production and rating.
• Improvement without participating conversation table.
But,
• Higher production rate = higher holistic rating
• Improvement on rate => improvement on rating
Some positive results, but too small sample…
Study 2
Fall 2014
• Who?
• Two volunteered second year Japanese students
• Both are male.
• What?
• Treatment: weekly conversation table (two weeks: face-toface, two weeks: Google Hangout), Posting comment once a
week
• Assessment: pre/post-test free speaking task (few minutes
about summer/fall break)
• Holistic rating and temporal measures
Students’ reaction and reflection
• (Unofficial survey)
• Result…
Conclusion and suggestions
• Relationship between:
• written and oral production
• Errors and fluency
• Quantitative and qualitative analysis
• Needs analysis
• What and when do students want to do?
• Most students requested more “speaking” practice in class.
*informal survey showed that 90% were not interested or too busy for
conversation table / extra curriculum activities.
• Scheduling (increase/maintain participation)
• Make use of chat history
References
• Payne, J., & Ross, B. M. (2005). Synchronous CMC, Working Memory, and L2 Oral
Proficiency Development. Language Learning & Technology, 9(3), 35-54.
• Kormos, J., & Denes, M. (2004). Exploring Measures and Perceptions of Fluency
in the Speech of Second Language Learners. System: An International Journal Of
Educational Technology And Applied Linguistics, 32(2), 145-164.
• Yang, Y. C., Gamble, J., & Tang, S. S. (2012). Voice over Instant Messaging as a
Tool for Enhancing the Oral Proficiency and Motivation of English-as-a-ForeignLanguage Learners. British Journal Of Educational Technology, 43(3), 448-464.
• Toyoda, E., & Harrison, R. (2002). Categorization of text chat communication
between learners and native speakers of Japanese. Language Learning And
Technology, 6(1), 82-99.
• Towell, R. R., & And, O. (1996). The Development of Fluency in Advanced
Learners of French. Applied Linguistics, 17(1), 84-119.
• Blake, C. (2009). Potential of Text-Based Internet Chats for Improving Oral Fluency in
a Second Language. Modern Language Journal, 93(2), 227-240.
• Cucchiarini, C., Strik, H., & Boves, L. (2000). Quantitative Assessment of Second
Language Learners' Fluency by Means of Automatic Speech Recognition Technology.
Journal Of The Acoustical Society Of America, 107(2), 989-999.
• Payne, S. J., & Whitney, P. J. (2002). Developing L2 Oral Proficiency Through
Synchronous CMC: Out-put, working memory, and interlanguage development.
CALICO Journal, 20, 7-32.
• Lennon, P. (1990). Investigating Fluency in EFL: A quantitative approach. Language
Learning, 40, 387-412.
• Ginther, A., Dimova, S., & Yang, R. (2010). Conceptual and empirical relationships
between temporal measures of fluency and oral English proficiency with
implications for automated scoring. Language Testing, 27(3), 379-399.
• Brand, C., & Gotz, S. (2011). Fluency versus accuracy in advanced spoken learner
language A multi-method approach. International Journal Of Corpus Linguistics,
16(2), 255-275.
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