Design and implementation of an intelligent biology vocabulary learning cloud system for college students
Specialized vocabulary presents a big challenge for college students especially when learning professional science curriculums such as biology, chemistry, etc. The traditional rote memorization, which is used by 89% students in China, has its limitation on efficiency and sustainability. This paper shows a new cloud-based cross-platform vocabulary learning system to give a more efficient and intelligent solution for vocabulary learning. The system can be used to search words, learn vocabulary and make a self-test. The search module contains a multifunctional dictionary, which supports speech recognition, can provide a precise, textbook and bilingual interpretation of a biology word. To learn vocabulary, users can add words to an exclusive word book and revise them anytime they want. The self-test function allows users to check their proficiency. Once a mistake appears, the word will be classified as errors and then added to a unique collection. The range of the test can be customized by users among the word book, error collection, the whole dictionary, or randomly mixed. The system greatly facilitates students' learning process and is expected to improve the learning outcome. Also, the compatibility in different systems enables students to learn vocabulary at any time through a smart phone or a computer.
2017 3rd IEEE International Conference on Computer and Communications, ICCC 2017
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Sun, Qiming; Zhang, Changjiang; and Meng, Yu, "Design and implementation of an intelligent biology vocabulary learning cloud system for college students" (2017). Kean Publications. 1601.