Analysis and application of computer modeling for MOOC
C Si - Cyber Security Intelligence and Analytics: Proceedings …, 2020 - Springer
C Si
Cyber Security Intelligence and Analytics: Proceedings of the 2020 …, 2020•SpringerThis paper investigates the reasons for the relatively low proportion of MOC learners in
higher education. After analyzing the existing data, it was found that the number of MOOCs
has been increasing in the past 1–2 years, but the number of learners has not increased
year-on-year, and the proportion of total students in the school is low. The study analyzes
the factors that may affect the choice of MOOCs by analyzing the learners themselves, and
uses Logistic models to model the influencing factors and the results of MOOCs. Based on …
higher education. After analyzing the existing data, it was found that the number of MOOCs
has been increasing in the past 1–2 years, but the number of learners has not increased
year-on-year, and the proportion of total students in the school is low. The study analyzes
the factors that may affect the choice of MOOCs by analyzing the learners themselves, and
uses Logistic models to model the influencing factors and the results of MOOCs. Based on …
Abstract
This paper investigates the reasons for the relatively low proportion of MOC learners in higher education. After analyzing the existing data, it was found that the number of MOOCs has been increasing in the past 1–2 years, but the number of learners has not increased year-on-year, and the proportion of total students in the school is low. The study analyzes the factors that may affect the choice of MOOCs by analyzing the learners themselves, and uses Logistic models to model the influencing factors and the results of MOOCs. Based on the analysis of the test results, it is concluded that the selection of the types of variables in the equation should be determined according to the best overall fit of the equation. This paper uses the known form of the equation to classify and filter the possibility of students choosing MOOC. Using this result, the teaching management department can target the non-selected students among the high-interest groups in MOOCs in a targeted manner, so as to increase the proportion of MOOC learners in the students and fully reflect the advantages of MOOC.
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