Exploring the effect of a flexible scaffolding for promoting deep learning in smart classrooms

Exploring the effect of a flexible scaffolding for promoting deep learning in smart classrooms

연구 분야: Artificial Intelligence

학회: Education and Information Technologies

Achieving deep learning in smart classrooms is an important issue in smart education. Research suggests that deep learning requires special scaffolding to support students’ learning flexibility according to their own needs. In this regard, this study proposes a smart-classroom-oriented learning scaffolding that can reflect flexibility in learning tasks, learning activities, learning processes, and instructional decision-making. A six-week experimental study was conducted with 98 high school students and the results suggest that the proposed flexible scaffolding has a positive effect in promoting deep learning in smart classrooms regarding 1 ) students’ classroom engagement (F(1, 84) = 12.00, p < .001, η2 = 0.13) and their flow state obtained during engaged in learning (F(1, 84) = 14.45, p < .001,η2 = 0.15); 2) students’ deep learning approaches adoption (F(1, 84) = 9.33, p < .01, η2 = 0.10), including deep strategies (F(1, 84) = 9.33, p < .01,η2 = 0.10) and deep motive (F(1, 84) = 6.24, p < .05, η2 = 0.07); and, 3) development and transfer of higher-order abilities, for instance, English writing creativity (F (1,83) = 17.61, p < .001,η2 = 0.18). The result demonstrated the potential of the proposed scaffolding in guiding teachers to design deep learning task sheets and supporting students’ flexible deep learning in smart classrooms.