Evaluation Algorithm of Ideological and Political Assistant Teaching Effect in Colleges and Universities under Network Information Dissemination

Ideological and political course is a key course to implement the fundamental task of building morality and cultivating people. Teaching evaluation is an important part of the construction of ideological and political courses. Constructing a perfect teaching evaluation index system is an urgent need to further deepen the teaching reform of ideological and political courses and improve the teaching quality of ideological and political courses. In order to improve the practical application effect of mixed teaching mode, an online and offline mixed teaching effect evaluation method based on big data analysis is proposed. Firstly, the big data in the process of mixed teaching are collected by using big data technology, and the evaluation index system is constructed from three dimensions. The required data are extracted according to the index, and then the association rules between the relevant data of the evaluation index are established, the phase space distribution of the data is obtained. Finally, the constraint parameter analysis method is used to fuse the control variables and explanatory variables of the index-related data to realize the online and offline mixed teaching effect evaluation. The application analysis results show that the method in this paper obtains ideal evaluation results of online and offline mixed teaching effects, which is conducive to improving teaching quality.

Study on College English Online Teaching Model in Mixed Context Based on Genetic Algorithm and Neural Network Algorithm

College English classroom teaching evaluation is an important basis for understanding teaching level and improving teaching quality. The traditional college English classroom teaching evaluation is mainly carried out through questionnaires and scales, but this method is time-consuming and laborious, inevitably introduces subjective errors, and reduces the accuracy and credibility of the evaluation results. In recent years, the rise and development of wisdom education not only provides a more convenient and efficient modern education form but also brings new ideas for classroom teaching evaluation. A subjective and objective fusion statistical evaluation model based on multidirectional genetic variation method and optimized neural network is proposed. The algorithm avoids subjective errors and improves the accuracy and reliability of the evaluation results, and a comprehensive evaluation model is constructed. Finally, according to different evaluation indexes, a systematic visualization scheme is designed to generate students’ classroom learning evaluation report and teachers' classroom teaching evaluation report, respectively, and visualize them on the web.

The Design of Teaching Evaluation and Organization System Based on the Internet of Things Using Fuzzy Comprehensive Evaluation Software

Educational evaluation is the main method of modern education management and guidance. Through a systematic collection of information and quantitative and qualitative analysis, value judgments can be made on the degree to which education adapts to needs, which can effectively improve the teaching development of applied undergraduate colleges. This article applies the Internet of Things technology to the information collection process of teaching evaluation in applied undergraduate colleges. This paper establishes an Internet of Things architecture to collect information on the impact indicators of the teaching evaluation process and builds a teaching evaluation index system. On this basis, this article combines fuzzy comprehensive evaluation for the quantification and evaluation process of index information. Through comparative analysis, the program can provide an effective way to construct a teaching evaluation system suitable for application-oriented undergraduate colleges. Constructing the research-based undergraduate classroom teaching evaluation index system aims at guiding the transformation of the concept of teaching and learning of teachers and students in research universities, perfecting the teaching and learning methods, improving the quality of teaching and learning, and promoting the common development of teachers and students.

Educational needs of severe trauma treatment simulation based on mixed reality: Applying focus group interviews to military hospital nurses

Purpose: The purpose of this study is to identify the educational needs of a severe trauma treatment simulation program based on mixed reality which combines element of both virtual reality and augmented reality.Methods: Focus group interviews were conducted with ten military hospital nurses on February 4 and 5, 2021. The collected data were analyzed using a qualitative content analysis. As a framework for data analysis, the educational needs were clustered into the following four categories: teaching contents, teaching methods, teaching evaluation, and teaching environment.Results: The educational needs for each category that emerged were as follows: three subcategories including “realistic education reflecting actual clinical practice” and “motivating education” for teaching contents; five subcategories including “team-based education,” “repeated education that acts as embodied learning,” and “stepwise education” for teaching methods; six subcategories including “debriefing through video conferences,” “team evaluation and evaluator in charge of the team,” “combination of knowledge and practice evaluation” for teaching evaluation; six subcategories including “securing safety,” “similar settings to real clinical environments,” “securing of convenience and accessibility for learners,” and “operating as continuing education” for teaching environment.Conclusion: The findings of this study can provide a guide for the development and operation of a severe trauma treatment simulation program based on mixed reality. Moreover, it suggests that research to identify the educational needs of various learners should be conducted.

Facing Big Data Information Fusion and Data Mining Technology to Construct College Physical Education Teaching Evaluation System

The purpose is to enrich the evaluation system of physical education (PE) teaching in colleges and universities and to improve PE teaching methods and improve teaching quality. Based on big data information fusion and data mining technology, firstly, the related theories of teaching evaluation are analyzed and expounded, as well as the characteristics and principles of the construction of college PE teaching evaluation system. Secondly, from the perspective of evaluation index system of sports teachers’ teaching and students’ sports teaching, the content and evaluation index of college sports teaching evaluation are analyzed under the background of big data information fusion and data mining by questionnaire survey. Combined with model test, the results show that traditional college sports teacher pays more attention to the design and teaching methods of PE and ignore the learning process of students. The evaluation process of PE ignores the individual differences of students, the feedback method lacks openness, and the evaluation process is isolated. Based on the big data technology and teaching evaluation theory, the evaluation index is designed for PE teaching in colleges and universities. The average value of the first layer indexes is above 4, and the coefficient of variation is less than 0.2, which can basically reflect the content of PE teaching evaluation and provide some reference for the research of PE teaching evaluation.

Evaluation of Blended Oral English Teaching Based on the Mixed Model of SPOC and Deep Learning

With the deep integration of “internet + education” and the continuous advancement of education reform, blended teaching has become the main method of university education reform. Blended education combines the advantages of traditional education and online education to complement each other. It not only takes advantage of the flexibility and autonomy of online education but also retains the benefits of emotional communication between teachers and students in offline education. With the increase in practical exploration of blended teaching in universities, teaching evaluation is an important part of teaching, and blended teaching evaluation should also attract attention. The purpose of this paper is to study the mixed oral English teaching evaluation based on the mixed mode of SPOC and deep learning. On the basis of analyzing the teaching design principles of the mixed mode of SPOC and deep learning and the principles of constructing the teaching evaluation after half a semester of teaching investigations conducted by the two classes of English majors, the impact of the SPOC and deep learning mixed teaching mode on students’ spoken English was studied through the method of covariance analysis. The experimental results show that the mixed teaching mode of SPOC and deep learning has been able to fully stimulate students’ interest in oral English learning and improve students’ oral English ability, critical thinking of students, ability to solve problems, group cooperation, and effective communication. Self-directed learning and self-reflection have all had a positive impact.

The pregnancy drop: How teaching evaluations penalize pregnant faculty

The “leaky pipeline” and the “maternal wall” have for decades described the loss of women in STEM and the barriers faced by working mothers. Of the studies examining the impact of motherhood or pregnancy on faculty in higher education, most focus on colleagues’ attitudes towards mothers; few studies explore pregnancy specifically, only a handful examine student evaluations in particular, and none include female faculty in engineering. This study is the first to compare student evaluations across fields from female faculty when they were pregnant against when they were not. Two scenarios were considered: (1) the lived experiences of faculty who taught classes while pregnant and while not pregnant and (2) an experiment in which students submitted teaching evaluations for an actress whom half the students believed was pregnant while the other half did not. Among faculty respondents, women of colour received lower scores while pregnant and these scores lowered further when women were in engineering and/or had severe symptoms. Depending on their demographics, students who participated in the experiment were awarded teaching evaluation scores that differed when they believed the instructor was pregnant. Findings suggest that in fields with fewer women, the maternal wall is amplified and there is a unique intersectional experience of it during pregnancy. These findings may be useful for Tenure and Promotion committees to understand and therefore account for pregnancy bias in teaching evaluations.

Evaluation of Physical Education Teaching Based on Analytic Hierarchy Process

The evaluation of physical education (PE) teaching plays an important role in improving the teaching quality and students’ physical fitness. Taking five colleges in a Chinese province for example, this paper surveys the status quo of college PE teaching evaluation, and reveals several problems with the evaluation: the evaluation index system (EIS) is incomplete, and the subjects are not diverse. Based on the survey results and previous findings, questionnaire survey, the Delphi method, analytic hierarchy process (AHP), logic analysis, and mathematical statistics were combined to construct an EIS for college PE teaching evaluation, determine the weights of indices on each level, design a standard scale, and develop the evaluation framework and flow. The research results promote the development of college PE teaching, and provide a reference for reforming the teaching evaluation of other disciplines.