Evaluation Of Teaching Effectiveness Research Articles

The Application and Trends of Blended Teaching Models in Teaching Chinese as a Foreign Language

In the context of technological advancements, such as "Internet +," the integration of online and offline elements in the form of blended teaching has emerged as a focal point in the realm of teaching Chinese as a foreign language. This study employs a literature analysis approach to initially summarize the current application status of blended teaching in the teaching of Chinese as a foreign language and to analyze three primary issues currently prevalent in this context. Subsequently, recommendations for the implementation of blended teaching in the teaching of Chinese as a foreign language are proposed from the perspectives of instructional design models, implementation of teaching strategies, and evaluation of teaching effectiveness. Finally, the potential development prospects of blended teaching in the teaching of Chinese as a foreign language are discussed.

Construction and Application of a College English Blended Teaching System Based on Multi-Source Data Fusion

By using modern data analysis techniques, this study aims to construct an innovative university English teaching effectiveness evaluation model based on particle swarm algorithm and support vector machine. The model is designed to improve assessment accuracy and personalization. The research process includes the methodology of data collection, preprocessing, model construction and evaluation. The experimental results show that the model can more accurately assess students' English learning effectiveness and provide customized suggestions for personalized education. This research is important for improving the quality of university English education, promoting personalized learning, and providing support tools for educational decision makers.

Digital Technology: Research on the Construction and Application of Blended Teaching Curriculum of Practical Physical Education Classroom Teaching Skills in the Big Data Background

Big data is bringing discipline to education. Under the guidance of digital technology, education has ushered in the upsurge of digital reform, digital course teaching has gradually entered the public's vision, and the upsurge of digital course open education is coming. The paper adopts the research methods of literature, field investigation and logical analysis, and takes the construction of digital curriculum mixed teaching course based on the platform of Superstar Learning as the research object. This paper constructs the curriculum construction ideas in three stages of "pre-class, mid-class and after-class", and draws the following conclusions through the research of blended teaching curriculum practice in the big date background: Build digital media teaching resource library, record multi-platform online teaching videos, practice dual-track mixed teaching, pre-set interactive classroom teaching activities, after-school homework to consolidate and improve classroom learning, online examination to achieve teaching effect evaluation and feedback, etc. And summed up four practical experiences of multi-style one-click check-in function to help class attendance, interactive teaching activity function to achieve subject participation, paperless online evaluation function to detect learning effect, digital courses to break the limitation of time and space. Digital technology improves the convenience of course teaching and forms a visual teaching effect. Digital technology provides new ideas for digital curriculum teaching. The existence of digital curriculum provides more possibilities for personalized learning, while hybrid teaching promotes the interaction and cooperation between students and teachers. Build an online learning platform based on big data to support computer technology, and guide students to conduct simulation and practice in the teaching process.

Application of ChatGPT-based blended medical teaching in clinical education of hepatobiliary surgery

Objective This study evaluates the effectiveness of incorporating the Chat Generative Pre-trained Transformer (ChatGPT) into the clinical teaching of hepatobiliary surgery for undergraduate medical students. Materials and methods A group of 61 medical undergraduates from the Affiliated Hospital of Guizhou Medical University, undergoing hepatobiliary surgery training, were randomly assigned to either an experimental group (31 students) using ChatGPT-based blended teaching or a control group (30 students) with traditional teaching methods. The evaluation metrics included final exam scores, teaching satisfaction, and teaching effectiveness ratings, analyzed using SPSS 26.0 (SPSS Inc., Chicago, IL) with t-tests and χ 2 tests. Results The experimental group significantly outperformed the control group in final exam theoretical scores (86.44 ± 5.59 vs. 77.86 ± 4.16, p < .001) and clinical skills scores (83.84 ± 6.13 vs. 79.12 ± 4.27, p = .001). Additionally, the experimental group reported higher teaching satisfaction (17.23 ± 1.33) and self-evaluation of teaching effectiveness (9.14 ± 0.54) compared to the control group (15.38 ± 1.5 and 8.46 ± 0.70, respectively, p < .001). Conclusions The integration of ChatGPT into hepatobiliary surgery education significantly enhances theoretical knowledge, clinical skills, and overall satisfaction among medical undergraduates, suggesting a beneficial impact on their educational development.

Harmonizing Perceptions: Exploring Alignment of Numerical and Textual Evaluation Through Fine-Grained Sentiment Analysis

The assessment of faculty teaching effectiveness plays a pivotal role in shaping educational practices and ensuring academic excellence. While numerical evaluations provide quantifiable measures of teaching effectiveness, textual comments offer valuable qualitative insights into the faculty's instructional methods and interactions. However, discrepancies between these evaluation formats may hinder the accurate assessment of faculty performance. This study aims to determine the alignment between the numerical and textual evaluations of faculty teaching effectiveness using fine-grained sentiment analysis and determine the relationship between numerical ratings and textual comments to identify patterns of consistency or divergence. A large dataset of anonymized BSCS students’ feedback is analyzed through sentiment analysis to extract sentiments expressed in the textual comments. The study results reveal a misalignment between students’ subjective perceptions expressed in the textual comments and the numerical ratings. This misalignment arises due to several factors, such as student communication style variations, individual interpretations of rating scales, or subjective biases. This study advances faculty evaluation methodologies and offers useful recommendations for organizations looking to improve assessment procedures as well as educational institutions that want to improve the precision and efficacy of their faculty evaluation systems for better faculty development and decision-making.

The Evaluation of College Chinese Teaching Effect Based on Internet of Things Technology

Aiming at the problem of the evaluation of College Chinese teaching, based on the development of internet of things technology, this paper discusses the teaching rules of internet of things technology in detail and makes relevant analysis. Then, college students of different grades are selected and applied to the specific evaluation of College Chinese teaching based on internet of things technology. The experimental results show that college students of different grades have different effects on College Chinese teaching based on internet of things technology. In addition, in the process of College Chinese teaching, freshmen and sophomores have a positive evaluation of the effect of Chinese teaching and have a strong interest in Chinese learning while senior students have the worst evaluation and interest in learning. Finally, the paper analyzes the possible problems in the evaluation of College Chinese teaching based on internet of things technology.

Psychometric Properties of the Persian Version of Student Evaluation of Online Teaching Effectiveness (SEOTE) questionnaire Among Medical Sciences’ Students

Background: Due to the increasing number of online educations, traditional methods for evaluation of different on-line education methods are not suitable and there is a need for a valid and reliable tool in this field. This study aimed to examine the validity and reliability of the Student Evaluation of Online Teaching Effectiveness (SEOTE) questionnaire among Medical Sciences’ students in Tabriz, Iran.&#x0D; Methods: Using convenience sampling method, the present study included 230 students of Medical Sciences (e.g., mean age of 21.96 ±3.47 years) in Tabriz, Iran. The SEOTE questionnaire was used to collect the data. Forward–backward translation, construct validity and content validity were utilized to check the validity of the questionnaire. In addition, temporal stability was calculated using the test-retest method and Internal Consistency Coefficient (ICC).&#x0D; Results: It was confirmed that the SEOTE has appropriate content validity using the content validity index (CVI) of 0.80 and content validity ratio CVR of 0.70. Exploratory factor analysis (EFA) identified the following two factors for domain identification of “communication” and “learning”. A Cronbach’s alpha of 0.97 was obtained for the questionnaire’s reliability, and ICC was used to confirm the temporal stability of the questionnaire (95% Confidence Interval [CI]: 0.966-0.977).&#x0D; Conclusion: This study confirms that the Persian version of SEOTE questionnaire is a valid and reliable tool for evaluation of on-line teaching among Medical Sciences’ students.

Online Teaching Effect Evaluation and Analysis Using Combined Weighting Technique

An evaluation index system of online teaching satisfaction was established based on the data of a questionnaire survey. In addition, an evaluation index system of an online teaching effect with four first-level indexes and 14 second-level indexes was constructed from the aspects of pre-class preparation, video production, classroom teaching, and after-class guidance. Then, a combination weighting–Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model was established using the analytic hierarchy process (AHP), Criteria Importance Through Inter-criteria Correlation method, and TOPSIS model. The objective is to evaluate the online teaching effect of 10 engineering technology universities in Henan Province. Results show that the online teaching effect of these universities is generally satisfactory. In addition, video production and classroom teaching are important factors affecting online teaching, which, however, is slightly influenced by pre-class preparation. On this basis, this study proposes to enhance online assessment, improve students’ attention in class, strengthen teacher–student communication, actively perfect teaching resources, and create a good learning environment.

Correction to: Accountability in the evaluation of teacher effectiveness: views of teachers and administrators

Correction to: Accountability in the evaluation of teacher effectiveness: views of teachers and administrators

Reviewing Teacher Effectiveness in Improving Student Learning

This research is dealing with the review of teacher effectiveness in improving student learning. A qualitative research method by using technique of library research was applied in analyzing the data in this research. There are four aspects of teacher effectiveness reviewed by the researchers: firstly, the nature of teacher’s effectiveness; secondly, teacher effectiveness based on the teacher’s performance; thirdly, teacher effectiveness based on the student’s achievement; and fourthly, benefits of teacher effectiveness for improving student learning. The results from four aspects which are reviewed give a comprehensive definition of effective teachers and specific method on how to evaluate teacher effectiveness based on teacher performance such as supervisors’ rating, students’ evaluation of teachers, peer-reviewed assessment, and self-evaluation. In addition, the review also evaluated teacher effectiveness based on student’s achievement in which value-added models were exemplified to the measurement of the effectiveness. Last, beyond teachers’ contribution to student achievement; this library research also includes how effective teachers impact student learning which obviously contribute to important outcomes for students as benefits for learning improvement.

The Application of Blending Learning in the Animation Major in Colleges and Universities in the Era of “Internet +”

This paper mainly discusses the application of blending learning in animation teaching. Blending learning is a combination of traditional teaching mode and online teaching mode, which can provide students with more flexible and independent learning methods and improve teachers' teaching quality and teaching effect. This paper analyzes and discusses the current situation of animation major, the present situation and configuration of blending learning, the teaching design of blending learning, the enlightenment, significance, and practical application of blending learning in animation teaching. Universities and teachers should strengthen research and practice in technical equipment and technical support, students' autonomous learning ability and willingness, adaptability and innovation of teaching contents and methods, evaluation and monitoring of teaching quality and teaching effect, so as to promote the application and development of blending learning in animation teaching.

Test Format, Learning Confidence, and Perceptions of Teaching Effectiveness

Background Both multiple-choice and short-answer tests can be beneficial to learning in the classroom. However, fact-based multiple-choice questions, because they include the correct answer as a response option, could lead to inflated estimates of learning and higher evaluations of teaching effectiveness. Objective The objective of this study was to examine the effects of test format on perceptions of learning and teaching. Method Undergraduate students ( N = 123) completed either a multiple-choice or short-answer test based on a brief psychology lesson. Then, they predicted their performance on later tests of knowledge and evaluated the quality of the lesson. Results Taking a multiple-choice test led to predictions about future performance that were 10% higher than those taking a short-answer test. No consistent differences emerged in participants’ evaluations of teaching effectiveness between the two test formats. Conclusion These results suggest that test format may significantly influence students’ confidence in their ability to produce answers on future tests. Teaching Implications Teachers who want to take advantage of testing as a metacognitive learning tool should adopt question formats that utilize recall of information from memory without retrieval cues.

Impelementasi Data Mining terhadap Evaluasi Kinerja Guru dalam Mengajar Menggunakan Metode Naive Bayes Classifier

Teachers are an important resource in supporting the teaching and learning process. The quality of teachers needs attention because it determines the quality of the teaching and learning process. This research aims to create a system that is able to classify performance as Very Good, Good, and Fair as seen from Pedagogical Competency, Personality Competency, Social Competency, Professional Competency using Naive Bayes Classifier calculations. Implementation of the Naive Bayes Classifier classification using numerical calculations. Based on a dataset divided into 80 training data and 20 testing data, the final test calculation achieved an accuracy level of 85% with precision results of 60% then recall of 57.14%. After carrying out calculations and obtaining test results, they will be distributed into the system using PHP and MySQL which are designed to carry out teacher performance assessment classifications. The prediction results obtained from the system are consistent with the results of manual calculations. Based on the research conducted, the system developed can be implemented in a way that makes it easier to evaluate teaching effectiveness.

Construction of College English teaching effect evaluation model based on artificial intelligence and output-oriented approach

Construction of College English teaching effect evaluation model based on artificial intelligence and output-oriented approach

Preschool Teachers Teaching Quality Evaluation Based on Neural Network Algorithms

Based on the current teaching situation of preschool teachers, in order to comprehensively evaluate the effectiveness of early childhood teaching, research have constructed a teaching quality evaluation model using fuzzy synthesis method and expert method. This model can handle the fuzzy relationship between evaluation indicators and achieve the evaluation of teaching quality. Considering that the teaching evaluation is influenced by many factors, the Genetic Algorithm back propagation (GA-BP) neural network algorithm is chosen for the solution model construction of the preschool teacher teaching quality. The entropy method chosen for the data calculation is to complete the preschool teaching quality evaluation. In the mean square error test for solving the model, the improved GA-BP model converged after 40 iterations with the model convergence speed increased by 34.65%. In the evaluation and prediction of preschool teacher indicators, the improved GA-BP model accurately evaluated the teacher classroom teaching indicators. In sample 3, sample 6, and sample 9, the improved GA-BP model scored 91, 89, and 88 points, respectively, close to the true scoring results. The improved model’s accuracy was high as 90% in teacher skills, personality charm, and academic research evaluation. The improved model also effected better in the application of the preschool teaching quality evaluation. The application effect of this model in teaching effectiveness evaluation and teacher quality evaluation is good, providing valuable reference for the establishment of early childhood education evaluation system.

Identification of English Teaching Effectiveness and Students’ English Proficiency Development in Colleges and Universities Combining Refined Bilinear Attention Networks

Abstract With the current application of artificial intelligence in education, English teaching methods in colleges and universities are developing rapidly. In this paper, we explore the application of the streamlined bilinear attention network to enhance students’ English proficiency and evaluate teaching effectiveness to improve teaching efficiency and improve students’ English proficiency. The study applies the bilinear attention mechanism to effectively process visual information during college English teaching using computerized visual learning methods to improve the accuracy of classroom teaching quality assessment. The methodology includes implementing a bilinear attention mechanism and applying a deformable convolution module to extract more accurate image features and optimize model performance. The model achieves 98.89% accuracy in facial expression recognition on the CK+ dataset, and 88.5% and 78.9% on the RAF-DB and Fer2013 datasets, respectively. Through online emotion evaluation experiments, the model performed well in recognizing emotional activity in teaching videos, which is highly consistent with the manual evaluation results. In analyzing students’ English proficiency development, the model-assisted teaching method can significantly improve students’ listening, grammar, phonetics, and many other abilities, with a mean value of self-evaluation reaching 4.09576 points. It shows the effectiveness of the streamlined bilinear attention network in assessing the teaching effectiveness of English teaching in colleges and universities and improving students’ abilities. Not only does the model accurately identify emotional activity in the classroom, but it also enhances students’ English learning.

MOOC distance teaching effect evaluation method based on fuzzy entropy

MOOC distance teaching effect evaluation method based on fuzzy entropy

A Multi agent interactive teaching effect evaluation method based on matrix method

A Multi agent interactive teaching effect evaluation method based on matrix method

MOOC distance teaching effect evaluation method based on fuzzy entropy

MOOC distance teaching effect evaluation method based on fuzzy entropy

A multi-agent interactive teaching effect evaluation method based on matrix method

A multi-agent interactive teaching effect evaluation method based on matrix method