Teacher Engagement With Technology-Enhanced Text Adaptation for Reading Assessment: A Case Study

Kai Guo, *Jing Chen, Jun Lei and Tan Jin
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Kai Guo: Shanghai Jiao Tong University, China
*Jing Chen: Sun Yat-sen University, China
Jun Lei: Ningbo University, China
Tan Jin: Sun Yat-sen University, China

International Journal of Computer-Assisted Language Learning and Teaching (IJCALLT), 2021, vol. 11, issue 4, 100-112

Abstract: In the assessment of English as a foreign language (EFL) reading proficiency, text adaptation is an important and challenging task for teachers. Although an increasing number of technology tools are available to facilitate text adaptation, research exploring how teachers engage with technology-enhanced text adaptation (TETA) is scarce. Drawing on a three-dimension framework consisting of behavioral, cognitive, and affective criteria of engagement, this case study investigated four Chinese EFL teachers' engagement with TETA facilitated by Eng-Editor, an online text complexity evaluation tool, in preparing reading assessment materials. Data from multiple sources were collected in the study. Firstly, the teachers' original and adapted texts were analyzed to reveal their behavioral engagement. Secondly, individual interviews were conducted with each teacher to unveil their cognitive and affective engagement. Results show diverse characteristics of teacher engagement with TETA along the three-dimension framework; moreover, various factors that influenced their engagement are also revealed. The paper concludes by providing suggestions for designing training programs to support teachers' employment of TETA.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jcallt:v:11:y:2021:i:4:p:100-112

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