An effective approach using blended learning to assist the average students to catch up with the talented ones

Jiyou Jia, Dongfang Xiang, Zhuhui Ding, Yuhao Chen, Ying Wang, Yin Bai, Baijie Yang

Abstract


Because the average students are the prevailing part of the student population, it is important but difficult for the educators to help average students by improving their learning efficiency and learning outcome in school tests. We conducted a quasi-experiment with two English classes taught by one teacher in the second term of the first year of a junior high school. The experimental class was composed of average students (N=37), while the control class comprised talented students (N=34). Therefore the two classes performed differently in English subject with mean difference of 13.48 that is statistically significant based on the independent sample T-Test analysis. We tailored the web-based intelligent English instruction system, called Computer Simulation in Educational Communication (CSIEC) and featured with instant feedback, to the learning content in the experiment term, and the experimental class used it one school hour per week throughout the term. This blended learning setting with the focus on vocabulary and dialogue acquisition helped the students in the experimental class improve their learning performance gradually. The mean difference of the final test between the two classes was decreased to 3.78, while the mean difference of the test designed for the specially drilled vocabulary knowledge was decreased to 2.38 and was statistically not significant. The student interview and survey also demonstrated the students’ favor to the blended learning system. We conclude that the long-term integration of this content oriented blended learning system featured with instant feedback into ordinary class is an effective approach to assist the average students to catch up with the talented ones.

https://doi.org/10.34105/j.kmel.2013.05.003


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Laboratory for Knowledge Management & E-Learning, The University of Hong Kong