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There exists an increasing demand for online education; however, faculty may question the value of online courses as they grapple with making a connection between the face-to-face classroom and the online learning experience. Much research has focused on factors relating to student engagement, although we posit that faculty engagement represents an important aspect in the online learning context that has been fairly overlooked in the engagement research stream. Therefore, understanding the factors that influence a faculty's intention to teach an OL course in addition to their level of engagement in teaching an online learning course is vital to the growth and success of an OL program. Therefore, in this study, we seek to not only understand the factors that influence faculty's intention to teach online learning courses but also an instructor's level of faculty engagement in online learning courses. We sought a novel lens with which to examine this phenomenon, so this study utilizes the perceived characteristics of innovation (PCI) to examine the relationships between faculty engagement and intention to teach online learning courses. We conducted a survey of 99 instructors from a large public university in order to assess the impact of PCI on faculty engagement and intention to teach online courses. Structural equation modeling (SEM) was employed to analyze the data, concluding that result demonstration, relative advantage, and compatibility influence a faculty's level of engagement in an online learning course, which in turn influences their intention to teach an OL course. We discuss how this research can be utilized in order to more effectively allocate scarce resources by focusing on the relative advantage of online learning, the measurability of online learning, and the way in which it can be compatible with instructors teaching preferences. We present this study to enable the beginning of a new stream of research into faculty engagement.

This paper analyzes the correlation between Civics teaching and student management in colleges and universities by establishing a multiple linear regression model to study the influence of Civics teaching on student management. Based on the questionnaire data, it analyzes the level of civics teaching and student management in 20 colleges and universities in City A. Based on the balanced panel data, it conducts benchmark regression analysis and dynamic panel analysis on the data of Civics education and student management and investigates the effect of the integration of college and university student management with the Civics teaching work. The results show that in the dynamic panel analysis, the estimated coefficients of the core explanatory variable of Civic and political education in each column are 0.028, 0.032, 0.033, 0.038, with positive significant coefficients, indicating that Civic and political education activities help to improve the level of management of students in regional colleges and universities. This study tests the positive influence of the integration of Civic and Political teaching work on student management and provides a certain reference value for colleges and universities to improve the level of student management.

An innovation and entrepreneurship education model centered around Timmons’ entrepreneurial process is suggested in this study after an initial analysis of applied bachelor universities, innovation and entrepreneurship education, and innovation and entrepreneurship courses. Second, a neural network with BP and an artificial neural network is used to build an assessment system for the efficiency of school innovation and entrepreneurship courses. Finally, examples were used to quantitatively study data on the approval of innovation and entrepreneurship classes and students’ graduation selections. The findings reveal that satisfaction with the innovation and entrepreneurship course may be successfully assessed using data analysis techniques because there is just a variance of 0.037 between the input assessment, with the lowest average score of 4.938 and the multidimensional experience assessment, with the highest average score of 4.975.