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Volume 15 Number 3, Autumn 2018, Pages 566-899   


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Investigating the Role of Task Value, Surface/Deep Learning Strategies, and Higher Order Thinking in Predicting Self-regulation and Language Achievement

    Ali Asghar Ghasemi & Hamid Reza Dowlatabadi


This study aims to identify and investigate the role of task value (drawn from expectancy-value theory), surface/deep learning strategies, and critical thinking for predicting language learners' self-regulation and ultimate language achievement in a single framework. To this end, 190 participants, majoring in English at bachelor's level at a state university in Iran, were selected based upon convenience sampling. A structural equation model showed that both motivational and cognitive components were significant predictors of language achievement and self-regulation. The results reveal that task value is a positive predictor of deep/surface learning strategies and metacognitive self-regulation, which provides evidence that awareness of the importance and value of a task, directs learners to choose more appropriate self-regulation strategies to monitor their process of learning and structure their own cognitive manners. The findings demonstrated that critical thinking predicts improvement in language achievement. Theoretically speaking, it has been argued that the ability to critically analyze learning materials and evaluate information enables learners with advanced proficiency to actively take part in the learning process, be further dedicated to their tasks, and more effectively and efficiently engaged in learning strategies, therefore making more successful learners. Finally, the implication for teachers and policy makers is discussed.

Keywords: task value, critical thinking, surface learning strategies, deep learning strategies, self-regulation.