Most Effective Compensation Strategies Enhancing Reading Fluency with Smart Board Technology
DOI:
https://doi.org/10.31185/lark.5668Keywords:
adjusting the message, using a circumlocution or synonym, compensation strategies, getting help, guessing intelligently, reading fluency, selecting the topics, smart board, and technology.Abstract
The development of reading fluency requires effective strategies and especially in a contemporary language learning environment. Smart Board technology with compensatory strategies offers interactive support and makes students more interacting and helps them develop reading fluency. This study aims to examine the effect of smart board-assisted compensation strategies on the reading fluency among EFL preparatory school students and identify which compensation strategies, when supported by smart board technology, are most effective in enhancing students’ reading fluency. The sample of this experimental study consists of (58) female students, divided into two equal groups control and experimental from the 5th preparatory school students for girls (Al-Furat private Secondary School) in Baghdad. The study instruments are observational checklist for compensation strategies prepared by the researcher and pre-posttest of reading fluency. The results of study indicate that smart board-based compensation strategies have a considerable positive impact on enhancing reading fluency of EFL students. The experimental group did better than the control group. Moreover, the findings showed that not all compensation strategies are equally effective, the most frequently and successfully applied strategies were guessing intelligently and getting help, whereas adjusting the message and selecting the topic were less effective.
References
1. Future studies may focus on the effects of smart board-based compensation on other language skills like writing, speaking or listening.
2. Future research could determine the efficacy of these strategies in a variety of educational stages, gender, or in a public-school environment to extrapolate the results.
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