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An Expert System Approach to Support Blended Learning in Context-Aware Environment

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10949))

Abstract

With the development of mobile internet and devices, the flexibility and portability of digital learning have improved continuously. Students can interact with mobile devices to support blended learning in context-aware environment. In this study, an expert system named Plant-expert which can provide decision-making questions for students to acquire knowledge about plant classification was developed. To explore the learning effectiveness of Plant-expert, another app named Plant-general that only contains information pages of target plants was designed. An experiment has been conducted on a secondary school biology course to evaluate the effectiveness of the proposed method. The experimental group with 46 students using Plant-expert in campus with target plants and the control group with 47 students using Plant-general in the same campus. We conducted pre-test, post-test and delayed test to evaluate learning achievement of students and used the Paas (1992) cognitive load rating scale to measure the mental effort of students invested into blended learning activities. The experimental results show that the proposed approach can improve the learning achievements of the students, and not increases mental effort.

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Acknowledgement

This research was conducted in Xinhuang Academy of the First high school of Changsha. The authors thank also all the teachers and students who have participated in the experiment.

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Correspondence to Cixiao Wang .

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Wang, C., Wu, F. (2018). An Expert System Approach to Support Blended Learning in Context-Aware Environment. In: Cheung, S., Kwok, Lf., Kubota, K., Lee, LK., Tokito, J. (eds) Blended Learning. Enhancing Learning Success. ICBL 2018. Lecture Notes in Computer Science(), vol 10949. Springer, Cham. https://doi.org/10.1007/978-3-319-94505-7_3

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  • DOI: https://doi.org/10.1007/978-3-319-94505-7_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94504-0

  • Online ISBN: 978-3-319-94505-7

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