The Effect of Data-driven Learning on Academic English Vocabulary Teaching

doi:10.3969/j.issn.1674-8921.2020.01.008

Abstract

Abstract:

This study is a practical exploration of academic English vocabulary teaching based on data-driven learning (DDL). DDL (Tribble & Jones 1990; Stevens 1991), based on a corpus index, is a form of computer-assisted instruction that encourages students to actively understand the meaning and usage patterns of vocabulary by observing real corpus. The authors of this study adopted a convenient sampling method to select non-English major undergraduates in the academic English listening and speaking class of a university in Shanghai as research participants, and conducted an eight-week academic English vocabulary teaching experiment by using DDL. The triangulation method combining questionnaire survey and classroom observation was used to study the acceptance of DDL and the limitations in the implementation process. Findings showed that DDL could really stimulate students’ interest in academic English vocabulary learning, and it was highly recognized by students. But students also believe that sometimes it is difficult to guess word meaning from corpus context. Therefore, the difficulty of corpus should attract the attention of teachers. In the future academic English vocabulary teaching, teachers can use DDL mode to improve the innovation and scientificalness of academic English vocabulary teaching.

Key words: academic English, data-driven learning, vocabulary teaching

CLC Number:

H319

LIU Qin, KE Qingbao. The Effect of Data-driven Learning on Academic English Vocabulary Teaching[J]. Contemporary Foreign Languages Studies, 2020, 20(1): 58-67.

Figures/Tables 3

References 26

[1]	Barabadi, E. & Y. Khajavi. 2017. The effect of data-driven approach to teaching vocabulary on Iranian students’ learning of English vocabulary[J]. Cogent Education 4(1): 1-13.
[2]	Carter, R. 1998. Vocabulary: Applied Linguistic Perspective (2^nd edn.)[M]. London: Routledge.
[3]	Cobb, T. 2007. Computing the vocabulary demands of L2 reading[J]. Language Learning & Technology 11(3): 38-63.
[4]	Dale, E. 1946. Audio-visual Methods in Teaching[M]. New York: The Dryden Press.
[5]	Guan, X. 2013. A study on the application of data-driven learning in vocabulary teaching and learning in China’s EFL class[J]. Journal of Language Teaching and Research 4(1): 105-112.
[6]	Horst, M., T. Cobb & I. Nicolae. 2005. Expanding academic vocabulary with a collaborative on-line database[J]. Language Learning & Technology 9(2): 90-110.
[7]	Huston, S. 2002. Corpora in Applied Linguistics[M]. Cambridge: Cambridge University Press.
[8]	Jacob, N. 2016. The effects of data-driven learning upon vocabulary acquisition for secondary international school students in Vietnam[J]. European Association for Computer Assisted Language Learning 28(2): 166-186.
[9]	Liu, D. & J. Ping. 2009. Using a corpus-based lexicogrammatical approach to grammar instruction in EFL and ESL contexts[J]. The Modern Language Journal 93(1): 61-78. doi: 10.1111/j.1540-4781.2009.00828.x URL
[10]	Nation, I. S. P. 2001. Learning Vocabulary in Another Language[M]. Cambridge: Cambridge University Press.
[11]	Read, J. 2000. Assessing Vocabulary[M]. Cambridge: Cambridge University Press.
[12]	Schmitt, N. 2000. Vocabulary in Language Teaching[M]. Cambridge: Cambridge University Press.
[13]	Stevens, V. 1991. Classroom concordancing: Vocabulary materials derived from relevant, authentic text[J]. English for Specific Purposes 10(1): 35-46. doi: 10.1016/0889-4906(91)90014-N URL
[14]	Thurstun, J. & C. Candlin. 1998. Concordancing and the teaching of the vocabulary of academic English[J]. English for Specific Purposes 17(3): 267-280. doi: 10.1016/S0889-4906(97)00013-6 URL
[15]	Tribble, C. & J. Jones. 1990. Concordances in the Classroom[M]. London: Longman.
[16]	Yoon, H. & A. Hirvela. 2004. ESL student attitudes toward corpus use in L2 writing[J]. Journal of Second Language Writing 13(4): 257-283. doi: 10.1016/j.jslw.2004.06.002 URL
[17]	楚向群. 2007. 高级英语词汇自主学习的语料库方法[J]. 外语电化教学(5): 12-17.
[18]	邓联健. 2006. 二语产出性词汇能力发展综述[J]. 外语与外语教学(2): 25-27.
[19]	李文中、濮建忠. 2001. 语料库索引在外语教学中的应用[J]. 解放军外国语学院学报(2): 20-25.
[20]	梁三云. 2005. 语料库与词汇教学策略的研究[J]. 外语电化教学(5): 33-36.
[21]	刘萍、刘座雄. 2018. 基于ESP语料库的学术英语词汇学习法的有效性研究[J]. 外语研究(3): 56-62.
[22]	濮建忠. 2003. 英语词汇教学中的类联接、搭配及词块[J]. 外语教学与研究(6): 438-445.
[23]	权立宏. 2009. 英语口语词汇学习的语料库方法探讨[J]. 广东外语外贸大学学报(3): 79-82.
[24]	王家义. 2012. 基于语料库的英语词汇教学:理论与应用[J]. 外语学刊(4): 127-130.
[25]	闫长红. 2018. 英语课堂教学对基于语料库的词汇学习研究[J]. 中国教育学刊(S1): 94-96.
[26]	甄凤超. 2005. 语料库数据驱动的外语学习:思想,方法和技术[J]. 外语界(4): 21-29.

	总数	非常赞同	比较赞同	一般	不赞同	非常反对	平均数	众数	标准差
Q1	44	24(54.5%)	14(31.8%)	6(13.6%)	0	0	4.41	5	0.73
Q2	44	21(47.7%)	16(36.4%)	6(13.6%)	1(2.3%)	0	4.30	5	0.80
Q3	44	22(50%)	14(31.8%)	8(18.2%)	0	0	4.32	5	0.77
Q4	44	25(56.8%)	13(29.5%)	6(13.6%)	0	0	4.43	5	0.73
Q5	44	21(47.7%)	17(38.6%)	6(13.6%)	0	0	4.34	5	0.71
Q6	44	26(59.1%)	12(27.3%)	6(13.6%)	0	0	4.45	5	0.73
Q7	44	13(29.5%)	21(47.7%)	9(20.5%)	1(2.3%)	0	4.05	4	0.78
Q8	44	3(6.8%)	10(22.7%)	22(50.0%)	6(13.6%)	3(6.8%)	3.09	3	0.96
Q9	44	9(20.5%)	15(34.1%)	17(38.6%)	3(6.8%)	0	3.68	3	0.88
Q10	44	6(13.6%)	15(34.1%)	15(34.1%)	7(15.9%)	1(2.3%)	3.41	4	1.00
Q11	44	14(31.8%)	19(43.2%)	8(18.2%)	2(4.5%)	1(2.3%)	3.98	4	0.95
Q12	44	15(34.1%)	11(25.0%)	14(31.8%)	1(2.3%)	0	3.83	5	1.06
Q13	44	15(34.1%)	18(40.9%)	11(25.0%)	0	0	4.09	4	0.77
Q14	44	12(27.3%)	18(40.9%)	12(27.3%)	2(4.5%)	0	3.91	4	0.86

			Q8	Q9	Q10	Q13	Q14
斯皮尔曼 Rho	Q8	相关系数	1.000	0.473^*	0.657^*	0.030	0.045
		显著性(双尾)		0.001	000	0.849	0.772
		个案数	44	44	44	44	44
	Q9	相关系数	0.473^*	1.000	0.564^**	-0.098	-0.034
		显著性(双尾)	0.001	.	000	0.527	0.825
		个案数	44	44	44	44	44
	Q10	相关系数	0.657^*	0.564^**	1.000	-0.079	0.022
		显著性(双尾)	0.000	0.000		0.608	0.885
		个案数	44	44	44	44	44
	Q13	相关系数	0.030	-0.098	-0.079	1.000	0.686^**
		显著性(双尾)	0.849	0.527	0.608		0.000
		个案数	44	44	44	44	44
	Q14	相关系数	0.045	-0.034	0.022	0.686^**	1.000
		显著性(双尾)	0.772	0.825	0.885	0.000	.
		个案数	44	44	44	44	44