Automated Voice Homophones

gog trans The last thing an EFL instructor wants is English learners sounding like robots, however, I have designed an easy to use activity with the automated voice function on Google Translate to not only challenge my students but also help them take advantage of opportunities to learn English outside of school.

Thanks to this week’s readings from my MA in EdTech course from Michigan State University, I have given more thought to learning environments outside of my classroom in order to prepare a 21st century lesson plan. One idea, from Thomas and Brown (2011), that the new culture of learning “emerges from the environment” (p. 37), particularly grabbed my attention and left me with two questions. Has the 21st century brought any challenges to people’s interaction with the world and if so does my EFL classroom help students address these challenges?

I thought specifically about the environment of Taichung, Taiwan, where my EFL students and I live. Without a doubt, the biggest challenge I faced when learning Mandarin here was understanding automated voice systems. Now, more than ever before, computerised and recorded voices speak to us from phones, on public transportation, in airports, and any number of other places. These interactions are fundamentally difficult because of poor intonation or reception and the inability of the listener to read facial expressions or ask questions. At the same time, there is no better challenge for language learners to build their skills at “listening for gist”, where one must try to understand content even if one doesn’t catch every word.

Within the last few years, English has gained a ubiquitous presence in Taiwan, so that even the elevator in the shopping mall will announce floors in Mandarin and English. I feel having language learners practice and play with an automated voice in class trains a relevant 21st century life skill and helps build what Hobbs (2011) calls a core competency of accessing information as students are better prepared to deal with this technology on their own outside of class.

As written in my lesson plan, the curriculum objective is centered around homophones with the automated voice game serving as a final assessment of students’ writing and listening comprehension. Why homophones? For paying close attention to context, there is nothing better than trying to differentiate words that sound exactly the same but have different meanings. Students will exhibit other core competencies from Hobbes (2011) as they analyze vocabulary in meaningful ways, then create contextualized sentences that will become the gaming questions shared with the whole class. While playing the game in teams, students must act collaboratively to analyze and reflect on the accuracy of their opponents work and their own if elements of their work are “Challenged”. Thomas and Brown (2011) suggest that play is how people generate knew understanding (p. 99), and I am confident that this game will provide some “Aha!” moments that cement knew language.

Complete Lesson Plan: Automated Voice Homophones


References

Hobbs, R. (2011). Digital and media literacy: Connecting culture and classroom. Thousand, Oaks, CA: Corwin/Sage.

Thomas, D., & Brown, J. S. (2011). A new culture of learning: Cultivating the imagination for a world of constant change. Lexington, Ky: CreateSpace?.

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