بررسی نقش استفاده از نرم‌افزار اصلاح خودکار در یادگیری زبان انگلیسی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 عضو هیئت علمی دانشگاه شهید رجایی

2 گروه زبان، دانشکده علوم انسانی، دانشگاه تربیت دبیر شهید رجایی

چکیده

هدف این پژوهش بررسی نقش استفاده از نرم‌افزار اصلاح خودکار در یادگیری زبان انگلیسی است. 203 دانشجوی درس زبان عمومی در این پژوهش شرکت نمودند. روش پژوهش توصیفی و از نوع همبستگی است. نحوه استفاده از نرم‌افزار اصلاح خودکار توسط شرکت‌کنندگان به‌وسیله‌ی پرسشنامه‌ی استفاده از نرم‌افزار اصلاح خودکار (ASUS) مورد ارزیابی قرار گرفت. این پرسشنامه نحوه‌ی استفاده از نرم‌افزار اصلاح خودکار را با در نظر گرفتن پنج مؤلفه موردبررسی قرار می‌دهد: اهمیت مهارت هجی کلمات، آگاهی از نحوه کار با نرم‌افزار، ارزش آموزشی نرم‌افزار، عملکرد نرم‌افزار در تصحیح غلط‌ها و نقش نرم‌افزار در اصلاح اشتباهات دیکته‌ای و نگارشی. یادگیری زبان بر اساس فعالیت‌های کلاسی و آزمون نهایی درس زبان عمومی مورد ارزیابی قرار گرفت. داده‌ها با استفاده از آمار توصیفی (میانگین و انحراف استاندارد) و آمار استنباطی (ضریب همبستگی و رگرسیون) مورد تحلیل قرار گرفت. نتیجه ضریب همبستگی نشان داد که رابطه‌ی مثبت و معناداری بین یادگیری زبان و استفاده از نرم‌افزار اصلاح خودکار و 4 مؤلفه‌ی آن وجود دارد؛ درحالی‌که قوی‌ترین ضرایب همبستگی مربوط به مؤلفه‌ی اول یعنی اهمیت مهارت هجی کردن در یادگیری زبان هنگام کار با نرم‌افزار (r=.215, p<.01) و مؤلفه‌ی سوم یعنی ارزش آموزشی نرم‌افزار (r=.214, p<.01) است. نتیجه‌ی رگرسیون نشان داد که این دو مؤلفه تسهیل‌کننده‌ی یادگیری زبان هستند و می‌توانند به‌طور معناداری بیش از 10% از واریانس آن را پیش‌بینی نمایند.

چکیده تصویری

بررسی نقش استفاده از نرم‌افزار اصلاح خودکار در یادگیری زبان انگلیسی

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

The role of autocorrect software use in learning English as a foreign language

نویسندگان [English]

  • Mehrak Rahimi 1
  • Ali Shahryari 2
1 English Department, Faculty of Humanities, Shahid Rajaee Teacher Training University
2 English Department, Faculty of Humanities, Shahid Rajaee Teacher Training University
چکیده [English]

This study aimed at examining the role of autocorrect software use in learning English as a foreign language. 203 university students of General English courses participated in the study. Their use of autocorrect software was evaluated by Autocorrect Software Use Scale (ASUS). ASUS assesses autocorrect software use with respect to five components including the importance of spelling skills in learning English with autocorrect, students’ awareness of the way autocorrect works, its educational value, its error correction function, and its value in improving English spelling and writing skills. Achievement in learning English was assessed by both formative and summative evaluations in General English course. The data were analyzed by both descriptive (mean and standard deviation) and inferential statistics (correlation and regression methods). The results of correlation showed that there was a positive and significant relationship between learning English and ASUS and its four components; while the strongest correlations were related to factor 1, the importance of spelling skills in learning English (r= .215, p<.01) and factor 3, educational value of autocorrect software (r= .214, p<.01). The result of multiple regressions revealed that these factors function as the facilitator of learning English and can significantly predict more than 10% of its variance.

کلیدواژه‌ها [English]

  • Software
  • Autocorrect
  • Learning
  • English
  • students

 [1]Wood, N. (2014). Autocorrect awareness: Categorizing autocorrect changes and measuring authorial perceptions, (Unpublished master’s thesis), Florida University, US.  

 

[2] Baron, D. (2009). A better pencil: Readers, writers, and the digital revolution. Oxford: Oxford Unviersity Press.

 

 [3] Sorrentino, J. (2008). Is spell check creating a generation of dummies? Education.com. N.p., 11 Jan. 2008. Web. 08 Oct. 2013.

 

[4] Ross, K. (2007). Does text messaging hurt student writing skills: Teachers say text messages r ruining kids’ riting skills. American Teacher.

 

[5] Leki, I., Cumming, A., & Silvia, T. (2008). A synthesis of research on second language writing. UK: Routledge.

 

[6] Weigle, S. C. (2014). Considerations for teaching second language writing. In M. Celce-Murcia, D. M. Brinton, and M. A. Snow, Teaching English a second or foreign language (pp. 222-237). US: Heinle.

 

[7]  Zamel, V. (1983). The composing processes of advanced ESL students: Six case studies. TESOL Quarterly, 17(2), 165-187.

 

[8] Ferris, D. R. & B. Roberts (2001). Error feedback in L2 writing classes: How explicit does it need to be?. Journal of Second [i]Language Writing, 10, 161-184.

 

[9] Li, M. (2012). Use of Wikis in second/foreign language classes: A literature review. CALL-EJ, 13, 17-35.

 

[10] Daffern, T., Mackenzie, N., &  Hemmings, B. (2017). Predictors of writing success: How important are spelling, grammar and punctuation? Australian Journal of Education, 61(1), 75-87.

 

[11] Dich, N. L. (2012). Cross-linguistic study of spelling in English as a foreign language: The role of first language orthography in EFL spelling, (Unpublished doctoral dissertation), Cornell University, US.

 

[12] Mehrpour, S., &  Ghayour, M. (2017).  The effect of educational computerized games on learning English spelling among Iranian children. The Reading Matrix: An International Online Journal, 17(2), 165-178.

 

[13] Nichols, L. M.  (1996).  Pencil and paper versus word processing:  A  Comparative study of creative writing in the elementary school. Journal of Research on Computing in Education, 29, 159-166.

 

[14] Warschauer, M. (1998): Computer and language learning: An overview. Language Teaching, 31(2), 57-71.

 

[15] Phinney, M., & Khouri, S. (1993): Computers, revision, and ESL writers: The role of experience. Journal of Second Language Writing, 2(3), 257-277.

 

[16] Beck, N., & Fetherston, T. (2003): The effects of incorporating a word processor into a year three writing program. Information Technology in Childhood Education Annual, 1, 139-161.

 

[17] Hayles, N. K. (2012). How we think: Digital media and contemporary technogenesis. Chicago: University of Chicago Press.

 

[18] Wood, L. A., Rankin, J. L., & Beukelman, D. R. (1997). Word prompt programs: Current uses and future possibilities. American Journal of Speech-Language Pathology, 6(3), 57-65.

 

[19] Newell, A. F., Booth, L., Arnott, J., & Beattie, W. (1992). Increasing literacy levels by the use of linguistic prediction. Child Language Teaching and Therapy 8(2), 138-187.

 

[20] Lewis, R. (1998). Enhancing the writing skills of students with learning disabilities through technology: An investigation of the effects of text entry tools, editing tools, and speech synthesis.

 

[21] Sheehan, C. (2009). Spell-check crutch curtails correctness. CBSNews. CBS Interactive. In

 

[22] Clark, L. (2013). Auto-correct generation can't spell common words such as 'necessary' and 'separate'" Mail Online. N.p., 21 May 2012. Web. 08 Oct. 2013.

 

[23] Hiscox, L, Leonavičiūtė, E., & Humby, ,T. (2014).The effects of automatic spelling correction software on understanding and comprehension in compensated Dyslexia: Improved recall following dictation. Dyslexia,20(3), 208-24.

 

[24] Alhusban, A. (2016). The impact of modern technological tools on students writing skills in English as a second language. US-China Education Review, 6(7), 438-443.

 

[25] Bronowicki, K. A. (2014). Technology's adverse effects on students' writing: An emphasis on formal writing is needed in an academic curriculum, (Unpublished master’s thesis), State University of New York College at Brockport.

 

[26]     Arif, A. S., Sylla, C., & Mazalek, A. (2016). Learning new words and spelling with autocorrections.  In ISS ’16 Proceedings of the 2016 ACM International Conference on Interactive Surfaces and Spaces (pp. 409-414), Ontario, Canada.

 

[27] McSweeney, M. A. (2017). I text English to everyone: Links between second-language texting and academic proficiency. Languages, 2(7), 1-15.

 

[28] Honarvar, A., & Jalalipour, J. (2016). General English readings (10th ed). Tehran: SRTTU Press.

 

[29] Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed). Boston: Pearson Education.

 

[30] Nejati, R., & Ashrafi, H. R. (2017). Statistics made simple. Tehran: SRTTU Press.

 

[31] Techrasa (2018). 53 Million Mobile Internet Users in Iran Until March 2018.

 

[32] Naevdal, F. (2207). Home-PC usage and achievement in English. Computers & Education, 49, 1112–1121.

 

[33] Shankweilert, D., & Lundquist, E. (1993). On the relations between learning to spell and learning to read. Haskins Laboratories Status Report on Speech Research, SR-113, 135-144.

 

[34] Rahimi, M., & Miri, S. S. (2015). Technology Use and Acceptance among Pre-Service Teachers of English as a Foreign Language: The Case of a Learning Management System and an Educational Blog. In J. E. Aitken (Ed.), Cases on communication technology for second language acquisition and cultural learning (pp. 87-107). US: IGI Global.

 

[35] Tran, L. (2007). Learners’ motivation and identity in the Vietnamese EFL writing classroom. English Teaching: Practice and Critique, 6(1), 151-163.

 

[36] Abulafia, D. (2013). Art of essay-writing damaged by Twitter and Facebook.

 

[37] Alqunayeer , H. S. (2016). The impact of teaching through Twitter on students’ vocabulary learning: A case study of Qassim University. World Journal of English, 6(2), 35-43.

 

[38] Carrington, V. (2205). Txting: The end of civilization (again)? Cambridge Journal of Education, 35, 161-75.

 

[39] Plester, B., Wood, C., Bell, V. (2008). Txt msg n school literacy: Does texting and knowledge of text abbreviations adversely affect children’s literacy attainment? Literacy, 42, 137-44.

 

[40] Mittal, R. (2015). Is texting really hurting our literary skills: How to overcome its effects. IOSR Journal of Humanities and Social Science, 20(10), 1-5.

 

[41] Land Nystrom, R. (2017). Autocorrect – friend or foe? Helping students become better writers in a digital world.