Evaluation Of Teaching Methods Research Articles

Genetically optimized neural network for college English teaching evaluation method

Genetically optimized neural network for college English teaching evaluation method

Application Big Data and Intelligent Optimization Algorithms on Teaching Evaluation Method for Higher Vocational Institutions

INTRODUCTION: The optimization of the teaching evaluation system, as an essential part of teaching reform in higher vocational colleges and universities, is conducive to the development of higher vocational colleges and universities' disciplines, making the existing teaching more standardized.OBJECTIVES: Aiming at the problems of inefficiency, incomplete index system, and low assessment accuracy in evaluation methods of higher vocational colleges and universities.METHODS: Proposes a teaching evaluation method for higher vocational colleges and universities with a big data mining algorithm and an intelligent optimization algorithm. Firstly, the teaching evaluation index system of higher vocational colleges and universities is downgraded and analyzed by using principal component analysis; then, the random forest hyperparameters are optimized by the grey wolf optimization algorithm, and the teaching evaluation model of higher vocational colleges and universities is constructed; finally, the validity and stability of the proposed method is verified by simulation experimental analysis.RESULTS: The results show that the proposed method improves the accuracy of the evaluation model.CONCLUSION: Solves the problems of low evaluation accuracy, incomplete system, and low efficiency of teaching evaluation methods in higher vocational colleges.

Research on 3D Human Motion Visualization for Immersive Teaching Mechanism - 3D Pose Reconstruction form the Tradition Motion Video for Teaching and Evaluation

Objective: Based on the three-dimensional (3D) visualization technology of human motion, the immersive teaching mechanism of human motion was proposed. At present, the training and learning of human motion could not observe the 3D information of its posture due to the issue of two-dimensional (2D) perspective, which had many shortcomings. Methods: This article proposed new teaching mechanisms, including personal immersive assisted instruction, multi person immersive interactive teaching, and immersive teaching evaluation method for motion learning. The design of the three methods were carried out in the background of artificial intelligence (AI). Results: Combining with current advanced AI algorithms, the concept of visualizing 3D human motion for immersive teaching method was conceived, and a specific implementation framework diagram and description of the main work of each teaching mechanism are provided. The personal immersive assisted instruction method would be a powerful tool for enhancing individual learning experiences in the realm of 3D human motion visualization. The multi-person immersive interactive teaching took 3D human motion visualization to the next level by facilitating collaborative learning experiences. The immersive teaching evaluation method for human motion training was pivotal for assessing the effectiveness of these immersive techniques. Conclusion: After the evaluation and analysis, this mechanism had been proven to be an effective teaching mechanism for pose learning. 3D human motion visualization for the immersive teaching held the promising prospects in the field of education and instructional practices.

Music Learning Motivation of College Students Majoring in Early Childhood Education: An Empirical Study from China

This study aims to explore the music learning motivation levels of Chinese college students majoring in early childhood education, and analyze the differential effects of demographic variables such as gender, age, grade, and hometown background. The research design used descriptive statistics and Mann-Whitney U test to conduct statistical analysis on the collected questionnaire data. The results showed that age and hometown background have a significant impact on students' learning motivation. Students aged 17 to 19 scored higher on internal learning motivation than students aged 20 to 22; students from rural areas scored higher than urban students on both motivations. Although the effects of gender and grade exist, they are not significant. These results suggest that the specific needs of diverse student groups should be taken into account in music education practice. To improve students' music learning motivation, it is recommended that educators should design more personalized and culturally relevant courses, while using diverse teaching evaluation methods to stimulate students' intrinsic interest and identity.

The Effectiveness of Distance Learning Assessment Practices: Case Study

Assessment is an essential component of the educational process as it tracks the progress of lessons, activities and facilitates learning through formative assessment or measures performance towards graduation or entry to higher levels of education or employment through summative assessment. However, increasing student enrollments in open-access educational institutions and the need for frequent assessments have led to a shift towards ICT (information and communication technologies) based remote assessment methods. The emergence of health emergencies and the strategy of Moroccan higher education has further accelerated this transition from traditional in-person assessments to remote assessments. This study uses a transversal research design to analyze the impact of distance assessment practices at Sultan Moulay Slimane University in Morocco. The research method includes the development of a benchmark for distance education evaluation methods and a statistical survey of randomly selected students (293) in eight university establishments, as well as other stakeholders involved in the remote assessment process. The objective is to determine the evaluation methodologies most appropriate to the specific context of Sultan Moulay Slimane University. Data is analyzed using descriptive statistics.

EFL Teacher's Perceptions of Using Flipped Classrooms in Language Teaching for Higher Education

The Flipped Classroom in higher education language teaching through the eyes of EFL teachers. The advent of technology in education has led to a change in the way conventional ways of pedagogy have been taught, thus raising questions. The study uses qualitative methods including in-depth interviews, focus group discussions, and reflective narratives, to address different aspects of EFL teachers’ experiences of the flipped classroom approach. Educators are also sampled from different institutions, of different levels of experience, and also with various cultures. The results highlight that EFL instructors’ views and experiences are more contextual. The approach is analyzed with the aim of demonstrating the impact of the approach on the teacher-student relationship, student involvement, as well as the student’s overall experience. In addition, it looks into the implementation issues, showing a way of how an organization or a class may cope with a new teaching philosophy. It also brings out emerging themes such as learner autonomy, technology integration, and a new definition for teachers’ roles in a Flipped Classroom structure. It further examines the cognitive shifts in EFL teachers and the modifications in their teaching methods, evaluation methods, and bespoke learning resources over time. In addition, professional development for teachers and language education programs needs additional support and materials to help them through the complex linguistic environment. The study adds to the literature on innovations in EFL settings, giving policymakers and curriculum developers a basis for improving teaching practice. A detailed examination of the relationship between EFL teachers and the Flipped Classroom model in higher education language teaching is presented in this research. It contributes significantly to the ongoing discussion about the best practices for language education in the digital era by untangling the strands of perceptions, challenges, and adaptations.

Innovative Research on the Quality Evaluation Method of English Translation Teaching in Colleges and Universities Based on Neural Network Modeling

Abstract This paper presents BP neural network as an evaluation tool for English translation instruction in colleges and universities. It does this by analyzing and combing the structure of BP neural networks, combining the five first-level indices with the assessment of indexes data preprocessing method, and building an evaluation system based on BP neural networks. We get sample data for the teaching quality assessment indexes based on the example teaching, evaluate it, and confirm that the BP neural network is feasible to use in the evaluation model. Two randomly selected college English language teaching classrooms are used as an example for the class, and the teaching quality rating method is utilized and analyzed. The teaching quality evaluation system’s findings are used to investigate the influencing factors that affect the quality of English translation teaching in higher education institutions. The teaching effect is also discussed about the impact of course time and content arrangements. According to the analysis, the English translation teaching evaluation index system built around the BP neural network model has a substantial amount of credibility because Kendall’s harmony coefficient W = 0.756 χ 2 = 7.687 χ 2 (p − 0.025) = 7.249 indicates that the consistency credibility of the instructional quality evaluation system goes to the test at a significant level of P = 0.025 and the opinions are very uniform.

Design of Teaching Mode and Evaluation Method of Effect of Art Design Course from the Perspective of Big Data

Design of Teaching Mode and Evaluation Method of Effect of Art Design Course from the Perspective of Big Data

Exploration and Practice of Educational Teaching Evaluation Reform in Higher Vocational Colleges Based on Big Data Technology

Abstract This paper constructs an evaluation model of education and teaching in higher vocational colleges based on big data technology, which focuses on students’ individual development and adapts to the “double-high program” goal. The evaluation index system of education and teaching quality established by the study contains 5 first- and 22 second-level indicators. The empirical Analysis takes QH College in R province as an example and analyzes the educational teaching data from 2018-2023. During this period, the mean values of secondary indicators of education teaching quality evaluation in QH College ranged from 2.7083 to 3.2886. The highest mean value of the rating of teaching objectives A1 and the lowest mean value of teaching standards A2. The coefficient of variation of teaching scenario B3 was the highest at 0.4887, and the coefficient of variation of building teaching resources was the smallest at 0.2587. In terms of the comprehensive evaluation of the quality of teaching and learning in higher vocational colleges and universities, the evaluation index system of QH College was categorized as “strong”. In addition, the study also analyzed the vulnerability of the evaluation of education and teaching in higher vocational colleges. From 2010 to 2023, the mean values of the vulnerability index of teaching quality evaluation of five higher vocational colleges in R province were 0.9693, 1.0536, 1.0507, 0.9993, 1.0407, respectively, with a significant turnaround in 2013, when the risk was significantly reduced. Synthesizing these data, this study provides an effective teaching model and evaluation method for higher education institutions to achieve high quality educational development.

The Reform and Practice of the Blend Teaching Mode with Ideological and Political Elements in the Teaching of Cold Chain Logistics Courses

With the development of economy, the demand for cold chain logistics talents is higher and higher. The traditional teaching mode has been difficult to adapt to the needs of the new era. How to effectively integrate the ideological and political elements of the curriculum, stimulate students’ learning motivation, and make full use of various resources online and offline, inside and outside the school, to improve the teaching quality, is a problem that needs to be considered and solved at present. According to the practical experience of the school in carrying out the teaching reform of the cold chain logistics course, a blend teaching mode and integrating the ideological and political aspects of the course has been constructed in various ways, including online and offline, in-school and off-campus, in-class and extracurricular. It puts forward measures such as co-construction of teaching resources in multiple ways, integration of ideological and political elements in the whole process, co-construction of educational content in multiple ways, implementation of blend teaching in multiple ways, and reform of teaching evaluation methods. Combined with concrete practice, the actual effect of the reform is analyzed and summarized.

Exploring the Innovation of Informative English Teaching Evaluation in the Age of Mathematical Intelligence

Abstract With the informatization of education, the traditional English teaching evaluation method is increasingly unable to meet the needs of cultivating talents in colleges and universities. In this paper, we constructed an informatized English teaching evaluation system using two modules: students’ classroom learning status evaluation and teachers’ teaching quality evaluation. Using informationized face detection and expression recognition technology, the evaluation axis of students’ classroom learning status is established as “students’ head-up rate - students’ expression - students’ concentration - classroom learning status”. The fuzzy comprehensive judgment model based on a genetic algorithm was established by constructing a judgment matrix and calculating the weights of teaching quality evaluation indexes using a hierarchical analysis method. The experimental and control groups analyzed the English teaching evaluation system’s application. Regarding English achievement, the post-experimental scores of the students in the experimental class were 8.57 points higher than those of the control class, with a highly significant difference (P<0.01). In terms of student literacy, students in the experimental class showed significant improvement in four indicators, including learning motivation, learning situation and cognition, and their attitudes toward the quality of English teaching were in the range between satisfaction and comparative satisfaction, and the overall performance of the application practice of the English education evaluation system was good.

Analysis of Integration Path in English Education and Teaching in Colleges and Universities under the Background of Informatization

Abstract For colleges and universities, it is imperative to actively respond to the current new teaching mode and to put information technology into English teaching in the new situation. This paper improves the random forest algorithm by using the sparrow search algorithm to calculate the Gini index score of each evaluation index feature. By addressing the impurities of nodes in the tree, the importance of each index in the forest can be ranked. Further, the improved random forest algorithm is combined with convolutional neural network to construct the obtained English teaching evaluation method to explore the practical effect of the informationized English teaching integration path established in this paper in teaching. The results show that the average scores of the five colleges and universities’ average scores of “technology-enabled teaching” and “awareness and attitude” indicators are high, respectively 4.27 and 4.16. In contrast, the scores of “social support” indicators are low. The average score for “social support” is low, only 3.24. After the teaching practice, the number of “excellent” scores in teaching expansion increased by 15. This paper’s integration path for informationized English teaching has precise results, a certain degree of universality, and serves as a reference for future exploration of the path.

Exploration of Factors Influencing the Satisfaction of Liberal Arts Education in the Organizing and Operating of Liberal Arts Education in a Junior College

This study aims to determine how the college-authorities level variables such as the development, organization, operation, and facilities of liberal arts education affect students' satisfaction of liberal arts education courses through their class participation attitude and the degree of their competency improvement. For this purpose, a survey was conducted among students at a vocational college. The questionnaire covered of demand reflection, curriculum organization, course composition, teaching and learning and evaluation methods, support facilities, class participation attitude, perception of competency improvement, and satisfaction. To check the relationship between these variables, we examined the fitting and validity of the measurement model and structural model, and then analyzed them using the structural equation model. The results showed that teaching and learning and evaluation methods, support facilities, and perception of competency improvement were variables that directly affected student satisfaction of liberal arts education. At the same time, the results also showed that demand reflection, curriculum organization, course composition, and instructional attitude were indirectly affected. Teaching and learning, and assessment methods and support facilities, which are directly related to students, seem to have a relatively large impact on student satisfaction with liberal arts education. Nevertheless, in order to improve liberal arts education, more attention to its overall operation practices at the college-authorities level is necessary.

A quantitative analysis of the influence of ideological and political education on students’ learning satisfaction

In China, ideological and political education is currently the hot direction of teaching reform in various colleges and universities, yet the development of appropriate teaching evaluation methods needs to catch up. This study addresses the pressing need for a preliminary investigation into the complex relationships among ideological and political education, the students’ learning satisfaction and teaching quality. This research examines the influence of teaching and ideological and political education quality on students’ satisfactions by designing a set of scales, collecting about 3800 questionnaires. Utilizing Structural Equation Modeling (SEM) and qualitative interviews, this study reveals that the teaching quality directly affects students’ learning satisfaction and ideological and political education. Notably, ideological and political education can also affect students’ learning satisfaction. The findings underscore the importance of including ideological and political education assessments in evaluating courses. This research contributes to the ongoing dialogue on effective teaching evaluation methods in the context of evolving educational practices.

Retracted: Standardized Evaluation Method of Pronunciation Teaching Based on Deep Learning

Retracted: Standardized Evaluation Method of Pronunciation Teaching Based on Deep Learning

Application Integrated Deep Learning Networks Evaluation Methods of College English Teaching

INTRODUCTION: The construction of English evaluation methods in colleges and universities, as the essential part of English teaching in colleges and universities, is conducive to the improvement of the quality of English teaching in colleges and universities, which makes the existing English teaching more objective and reasonable, and makes the means of English teaching rich in science.
 OBJECTIVES: Aiming at the current wisdom teaching evaluation design methods exist evaluation indexes exist objectivity is not strong, accuracy is poor, single method and other problems.
 METHODS:Proposes a college English teaching evaluation method based on a deep learning network. First, the evaluation index system of English in colleges and universities is constructed by analyzing the principle of selecting evaluation indexes of English in colleges and universities; then, the deep learning network is improved through self-coder and integrated learning methods to construct the evaluation model of English teaching in colleges and universities; finally, the effectiveness and efficiency of the proposed method is verified through simulation experiment analysis.
 RESULTS: The results show that the proposed method improves the accuracy of the evaluation model.
 CONCLUSION: Solved the problems of low evaluation accuracy and non-objective system indexes of English teaching evaluation methods in colleges and universities.

The Application and Potential of Artificial Intelligence Participating in College Teaching Evaluation

The dominance could be applied to many more areas as new artificial intelligence (AI) advances. There are great defects in the traditional evaluation methods of higher education. The evaluation of people is dominant, resulting in excessively subjective results and wasting human resources. These issues adversely affect many stakeholders. Therefore, the combination of the objectivity of artificial intelligence and the traditional method of teaching evaluation has an exploratory significance for the development of teaching and emphasizes the technical ability that the new artificial intelligence can realize. The purpose of this study is to explore the potential of a new method for artificial intelligence in higher education evaluation. Based on the analysis of existing experimental case reports and related studies by the method of literature synthesis, it is certain that the new artificial intelligence will help improve the quality of teaching evaluation in higher education. This has a positive impact on all fields, including schools, teachers, and students. The teaching objectives of the school can be better and more efficiently accomplished under the evaluation system. This study confirms the feasibility of incorporating artificial intelligence into university evaluation.

The Differential Effects of Labeling: How to Do Direct Teaching and E-learning Affect Teachers' Beliefs in Distance Learning

The COVID-19 pandemic with successive lockdowns has caused university education all over the world to suddenly move from face-to-face to online teaching. This study investigates the impact of the teaching method on teachers' beliefs in light of the Corona Covid-19 pandemic. To achieve the objectives of the study, the analytical descriptive approach was used. The researcher developed a questionnaire that was applied to a random sample of 352 faculty members at King Faisal University. The questionnaire was conducted electronically in two stages. In the first stage, the term "direct teaching" was used, and in the second stage it was replaced by the term "distance teaching". The factor validity of the questionnaire was built, and it resulted in three main factors according to the teachers' beliefs, which are: teaching methods, evaluation methods, course organization, and management. The results showed that there was a difference in the level of teachers' beliefs about the factor (teaching methods) according to the teaching method, as the level of teachers' beliefs for the direct teaching method was high, and the distance education method was medium. It also showed a match in the level of teachers' beliefs according to the two methods of direct teaching and distance learning for workers (evaluation methods, course organization, and management), where the level was high. The results of the (T) test showed that the teaching method affects the teachers' beliefs and that the direct teaching method is superior to distance teaching in all factors. The researcher recommends the necessity of sustainable professional development for teachers in the technological aspect through the preparation of professional courses and conferences, and the development of comprehensive plans for the transition to distance education at the time of need and necessity that are flexible and implementable.

Learning in the Digital Age: Harnessing Decision Support Systems and Case Study for Physics Tutoring Program

In the contemporary educational landscape, the integration of Decision Support Systems (DSS), particularly the Simple Additive Weighting (SAW) method, offers a structured approach to evaluating teaching methods. This study focused on applying the SAW DSS in a Physics Tutoring Program. The results highlighted Interactive Simulations as the most effective teaching approach, emphasizing the role of technology in modern education. Hands-on Experiments and Group Discussions followed closely, underscoring the importance of experiential learning. Traditional Lectures, while foundational, benefit from enhanced interactivity. The SAW DSS's systematic approach ensures objective decision-making, though weight assignment can introduce subjectivity. A notable research gap emerged around the integration of SAW DSS with advanced educational technologies and its application across diverse cultural contexts. Future research avenues include refining the SAW method with real-time feedback and AI integration. In conclusion, as education evolves, tools like the SAW DSS provide invaluable insights, necessitating continuous adaptation to meet dynamic educational needs.

An English course practice evaluation system based on multi-source mobile information and IoT technology

With the increased use of online English courses, the quality of the course directly determines its efficacy. Recently, various industries have continuously employed Internet of Things (IoT) technology, which has considerable scene adaptability. To better supervise the specific content of English courses, we discuss how to apply multi-source mobile Internet of Things information technology to the practical evaluation system of English courses to boost the performance of English learning evaluation. Therefore, by analyzing the problems of existing English course evaluation and the characteristics of multi-source mobile Internet of Things information technology, this article designs an English course practical evaluation system based on multi-source data collection, processing, and analysis. The system can collect real-time student voices, behavior, and other data through mobile devices. Then, analyze the data using cloud computing and data mining technology and provide real-time learning progress and feedback. We can demonstrate that the accuracy of the evaluation system can reach 80.23%, which can effectively improve the efficiency of English learning evaluation, provide a new method for English teaching evaluation, and further improve and optimize the English education teaching content to meet the needs of the actual teaching environment.