Abstract
With the advent of the big data era, significant changes have taken place in every aspect of education. To effectively evaluate the academic performance of college students, this paper firstly establishes a scientific evaluation index system for student portrait. Taking the course Object-Oriented Programming as an example, the authors collected various data on the academic performance of college students. The collected data were normalized, and the weight of each evaluation index was determined through analytic hierarchy process (AHP). Next, a fuzzy evaluation model was constructed based on big data, and used to assess each dimension of college students’ academic performance. The evaluation reveals the problems of college students in learning and practice, and helps to generate the portrait of each student. The research results promote the realization of personalized education.
Highlights
Big data and its diverse applications have changed people’s life styles and work methods, brought new opportunities for the innovation in education [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]
Using data mining, learning analysis, data visualization and other technologies, the behavioral data related to the academic performance of college students could be analyzed and integrated to assess the learning situation of college students; the data obtained via the mentioned techniques enable college students to discover their problems in the learning and practice process, and the teachers could make use of these data to give targeted and personalized instructions
After reviewing the research works of Cumming and Miller [20], Hedgcock [21], Fabra-Mata and Mygind [22] and Amundsen and D’Amico [23] concerning the academic performance evaluation of college students, we have summarized the reform measures for the said matter as follows: first, reform the evaluation methods, that is, apply multiple evaluation methods to evaluate multiple subjects; here multiple subjects include teachers, students, and peers; and multiple evaluation methods can be exams, classroom observations, and practice activities, etc
Summary
Big data and its diverse applications have changed people’s life styles and work methods, brought new opportunities for the innovation in education [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]. The literature review we conducted suggested that currently there’re very few research papers concerning the evaluation of the academic performance of college students using big data, and a few relevant studies were aimed at designing personalized learning evaluation systems borrowing the idea of big data concept; the data of such systems were mostly collected from the online learning trajectories of students, offline evaluation factors were less considered. The Ministry of Education has requested to improve the teaching quality of undergraduate education and target at cultivating all-round talents, in this context, it becomes a development trend in the field of education to reform the evaluation concept and content, and make full use of big data, AI and other new-generation information technologies to construct a comprehensive system for the evaluation of college students’ academic performance [24,25,26,27,28,29,30,31,32,33]
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