Classroom Teaching Research Articles

SPECIFIC FEATURES OF THE DEVELOPMENT AND APPLICATION OF SOFT SKILLS AS A COMPONENT OF COMPETITIVENESS OF FUTURE MANAGERS

The current conditions for the development of young professionals pose challenges: the COVID-19 quarantine and Russia's invasion of Ukraine have led to the spread of distance learning, affecting the development of soft skills. Despite the resumption of classroom teaching, issues like poor communication, inability to present or argue opinions, and problems working in teams persist. However, these can be addressed using modern technologies and teaching methods. This study aims to analyze the impact of interactive teaching methods on developing soft skills among university students. Soft skills are crucial for future managers' careers. The article examines the peculiarities of developing and applying soft skills as key to the competitiveness of future managers in the Ukrainian context, integrating innovative educational practices. Emphasizing the importance of interactive learning tools, the study highlights their relevance for preparing future managers for modern labor market challenges, applicable in both online and offline settings.

Teaching and Learning English in Japanese Classrooms: Teachers’ Perspectives

Teaching and Learning English in Japanese Classrooms: Teachers’ Perspectives

Arabic Language Teaching in Arabic Preparatory Schools

This study aims to highlight, describe and analyse the experiment conducted at the Arabic Preparatory School for Girls in Bandar Seri Begawan (SPABSB) and explore how it can be utilised to improve the teaching of Arabic to non-Arabic speakers. The Arabic school in Brunei seeks to leverage modern theories and methods of language teaching. The school established a committee to oversee all aspects related to the Arabic language. This committee aims to enhance Arabic language instruction by mandating that all teachers of Arabic language and religious studies, as well as students, communicate in Arabic. They additionally translated posters and publications into Arabic, while arranging professional development events to educate teachers on language teaching theories and methods. They develop class activity books and materials for extensive Arabic practice both inside and outside the classroom. Furthermore, they organise various intensive learning activities to promote Arabic language usage, such as competitions encompassing plays, speeches, group presentations, calligraphy, and singing in Arabic. They also initiated numerous activities aimed at teaching Arabic culture, including Arabic festivals, expeditions, Arabic Week, and open days. The school encourages the use of Arabic language in all activities and events. This study found that the approach adopted by the (SPABSB) serves as a valid model for other newly established schools. It emphasises a balance between extracurricular activities organised by the administration and academic pursuits within the classroom. It suggests the integration of Arabic language use both inside and outside the classroom, highlighting that traditional classroom teaching alone may not suffice to enhance Arabic language proficiency and develop students' skills

Experience of intelligent speech robot in music online classroom based on deep learning and virtual reality

This study designs and implements an intelligent voice robot music online classroom teaching platform, providing students with a more personalized and interactive learning experience. Research the application of deep learning technology to establish a speech recognition model for music teaching, achieving accurate recognition and understanding of student speech; Combining speech recognition technology and robot interaction technology, construct an intelligent speech robot teaching platform to achieve interactive speech learning; Finally, utilizing virtual reality technology to create an immersive music teaching environment, enhancing students’ sense of participation and learning effectiveness. Through research and analysis of the needs of students and teachers, the functions and characteristics of the intelligent voice robot music online classroom teaching platform have been determined. We have established a comprehensive platform architecture and implemented functional modules such as speech recognition, virtual reality environment construction, and teaching resource management. Designed diverse interactive teaching and learning modes, enhancing the fun and effectiveness of learning. This study successfully designed and implemented an intelligent voice robot music online classroom teaching platform based on deep learning and virtual reality, injecting new vitality and possibilities into music teaching.

Exploration of the Reform of Applied Linguistics Course Under the “Internet+” Platform and the BOPPPS Model

The teaching of linguistics courses in traditional teaching mode brings students problems such as cognitive burden, insufficient learning motivation, and lack of understanding of the course setting. According to the established problems and students’ learning situation, we analyze the students’ learning situation, select an experimental control class among the classes of the same grade and the same major studying the course, and carry out the course teaching reform by combining the characteristics of the applied linguistics course. The experimental class that adopts the BOPPPS model in teaching design relies on the “Internet+” Bodoudou platform to assist in teaching quizzes and carry out classroom teaching reform. The control class adopts the traditional teaching mode. At the same time, in the final results and pre- and post-questionnaire surveys, it was found that after adopting the BOPPPS model of teaching, students have made greater progress in absorbing and applying knowledge than in the previous period. The use of BOPPPS model teaching improves the absorption and mastery of knowledge, and the cultivation of learning habits is better than that of traditional teaching.

Optimization of Primary School English Classroom Teaching under the Digital Background

Optimization of Primary School English Classroom Teaching under the Digital Background

Analysis and Research on the Integration of Mathematical Culture into Course Ideological and Political Education Cases

This article starts with mathematical culture and combines classic stories such as Cao Chong's weighing of the elephant and Han Xin's divide of oil. Analyze the ideological and political elements embedded in mathematical culture and effectively integrate them into classroom teaching. So as to achieve a silent effect on moistening things and implement the fundamental task of cultivating virtue and talent. Finally, strategies for classroom teaching are provided to provide some ideas for the reform of ideological and political education in university courses.

From traditional teaching to flipped classroom: Impact on learning in engineering degrees

Computer engineering students should develop competences related to the contents of databases design and SQL queries. For this purpose, the recommendations on the convenience of changing the traditional teaching methodology to the flipped classroom are followed. In this article we present a quantitative study in which we compare the potential for the development of engineering students' competences in the design and use of databases of the flipped classroom methodology and the traditional teaching methodology. The results obtained in the evaluation of the subject in two different courses are compared. In the first course, traditional teaching methodology was used. In the second one, flipped classroom was used when its implementation had already been tried and tested. The results of the content blocks of database design and SQL queries are compared, according to the type of learning promoted. In this article we show evidence that the implementation of the flipped classroom teaching methodology provides different results depending on the learning promoted and on the specific contents in the subject of relational databases. The benefits of implementing the flipped classroom depend on the content and type of learning promoted. We have found evidence that they improve theoretical learning outcomes for database design and in the resolution of non-reproductive activities in the SQL queries block. No conclusive benefits are reported for students’ competency development for either of the two content blocks.

Developing and validating a knowledge-based AI assessment system for learning clinical core medical knowledge in otolaryngology

BackgroundClinical core medical knowledge (CCMK) learning is essential for medical trainees. Adaptive assessment systems can facilitate self-learning, but extracting experts' CCMK is challenging, especially using modern data-driven artificial intelligence (AI) approaches (e.g., deep learning). ObjectivesThis study aims to develop a multi-expert knowledge–aggregated adaptive assessment scheme (MEKAS) using knowledge-based AI approaches to facilitate the learning of CCMK in otolaryngology (CCMK-OTO) and validate its effectiveness through a one-month training program for CCMK-OTO education at a tertiary referral hospital. MethodsThe MEKAS utilized the repertory grid technique and case-based reasoning to aggregate experts' knowledge to construct a representative CCMK base, thereby enabling adaptive assessment for CCMK-OTO training. The effects of longitudinal training were compared between the experimental group (EG) and the control group (CG). Both groups received a normal training program (routine meeting, outpatient/operation room teaching, and classroom teaching), while EG received MEKAS for self-learning. The EG comprised 22 UPGY trainees (6 postgraduate [PGY] and 16 undergraduate [UGY] trainees) and 8 otolaryngology residents (ENT-R); the CG comprised 24 UPGY trainees (8 PGY and 16 UGY trainees). The training effectiveness was compared through pre- and post-test CCMK-OTO scores, and user experiences were evaluated using a technology acceptance model-based questionnaire. ResultsBoth UPGY (z = −3.976, P < 0.001) and ENT-R (z = −2.038, P = 0.042) groups in EG exhibited significant improvements in their CCMK-OTO scores, while UPGY in CG did not (z = −1.204, P = 0.228). The UPGY group in EG also demonstrated a substantial improvement compared to the UPGY group in CG (z = −4.943, P < 0.001). The EG participants were highly satisfied with the MEKAS system concerning self-learning assistance, adaptive testing, perceived satisfaction, intention to use, perceived usefulness, perceived ease of use, and perceived enjoyment, rating it between an overall average of 3.8 and 4.1 out of 5.0 on all scales. ConclusionsThe MEKAS system facilitates CCMK-OTO learning and provides an efficient knowledge aggregation scheme that can be applied to other medical subjects to efficiently build adaptive assessment systems for CCMK learning. Larger-scale validation across diverse institutions and settings is warranted further to assess MEKAS's scalability, generalizability, and long-term impact.

Evaluation of flipped classroom teaching quality for civil engineering courses

The impact of civil engineering course education on civil engineers is profound and crucial. Due to the hierarchical and ambiguous nature of quality assessment for flipped classroom teaching, there is an urgent demand for a rational and effective approach to conduct such assessments. This would enable the targeted formulation of instructional improvement methods based on assessment outcomes, ultimately elevating the quality of pedagogy. This study combines the analytic hierarchy process and fuzzy evaluation method. The fuzzy evaluation method is utilized to identify four primary evaluation factor sets, fourteen secondary judgment factor sets, and five evaluation outcome sets, with subsequent quantification of the assessment results. The analytic hierarchy process is employed to ascertain the weight coefficients of the evaluation factors. The comprehensive assessment model for flipped classroom teaching quality is established. The assessment results indicate that the overall quality of flipped classroom teaching in the civil engineering major at Anhui University of Science and Technology, conducted through the platform of Superstar Learning Hub, falls within the ‘Good’ category. The fuzzy comprehensive evaluation score for extracurricular learning quality is the lowest, and the weight proportion attributed to flipped classroom infrastructure is the highest. Consequently, several targeted improvement measures are proposed to enhance the quality of flipped classroom teaching.

Virtual Reality and 6G Based Smart Classroom Teaching Using Artificial Intelligence

Virtual Reality and 6G Based Smart Classroom Teaching Using Artificial Intelligence

The supply chain advantages and application strategies of artificial intelligence and the Internet of Things

This work addresses issues such as inadequate teaching methods, a lack of teaching resources, and low proactiveness in current accounting education. It introduces a novel teaching approach termed “Just-in-Time Teaching (JITT) cloud teaching,” which integrates “real-time teaching” with the Internet of Things-based “cloud teaching model” specifically for accounting education. First, the current status of accounting education in secondary vocational schools is investigated through a questionnaire survey. Subsequently, adjustments are made to the traditional teaching model, considering the limitations in teaching media creation channels and challenges in teaching activities. The teaching content of accounting education is designed in terms of mind maps, curriculum type, and problem design. The findings indicate: (1) Almost half of the surveyed teachers have heard of but never used the JITT cloud teaching, and the proportion is the largest. Some teachers have used but disapprove of JITT cloud teaching. (2) The proportion of students using website learning resources is 43.81%, while the proportion using mobile learning applications is 38.34%. (3) There is a significant difference between the traditional teaching mode and the JITT teaching mode in terms of “classroom teaching” and “sense of responsibility”. The average values under the JITT teaching mode have significantly improved compared to the traditional one. (4) The experimental group has a higher proportion of students scoring 90–100, which is 58%, significantly higher than the control group. The above research results indicate that there are still many possibilities for the practical application of the JITT teaching method in the future Moreover, applying the JITT cloud teaching model contributes to enhancing teaching quality and supports students’ learning.

Developing a fuzzy comprehensive assessment model for English translation for college studentso

College students are learning a foreign language must know how to translate the spoken or written content from the respective language into English. These approaches do not help the college students to develop the capacity for rational thinking and adequate the motivation for the English translation. The educational principles are not in line with the qualities of the students in the typical English translation classroom teaching, and the teaching methods are out-dated. In the older process of the teaching English translation, many unreliable, vague aspects need to be considered, such as recognizing students’ fundamental English knowledge, unique circumstances, language proficiency, cultural differences, and the ambiguity of the source language. The main issue with the current English translation evaluation methodology is that it cannot be easily to deal with thecomplex fuzzy indices when judging the accuracy of the student translations. An algorithm named FCAM-AHP-ANFIS is proposed to provide an effective and accurate method for evaluating and predicting students’ English translation outcomes to overcome the traditional shortcomings. According to the proposed approach, students can learn about passive translation, but they may struggle to actively improve their translation skills. College students can benefit from the decision-making aid provided by the extensive evaluation technique due to its high availability and precision. The fundamental benefit of the fuzzy technique over more traditional forms of the assessment is that it accounts for the ambiguity and uncertainty of the making judgments at the human level and provides a coherent framework that includes the indistinct findings of the several steps in evaluating an English translation. The Fuzzy Comprehensive Assessment Model (FCAM) is a decision-making method that uses the fuzzy logic to assess the quality of English translations among the college students. The Analytic Hierarchy Process (AHP) is employed to calculate each criterion’s relative importance and determine the optimal weighting for each criterion utilized in the assessment model. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is used to analyze the translated data and generate predictions for the students’ translation outcomes. The experimental outcomes show the accuracy of the English translation assessment scores are 95.6% with 97% precision, 96% recall, and 96.5% of f1-score metric in addition to Root Mean Square (RMSE) and Mean Absolute Error (MAE).

"Four New and Three High" Mathematical Modeling Course Construction

After years of inheritance, innovation and integration, the mathematical modeling curriculum has been reformed from the aspects of education concept, training goal, teaching system, teaching material system, course content, teaching method and learning mode. Teaching "four new" design is to organically integrate the ideological and political elements with professional characteristics into the course teaching, innovate the course content, teaching methods and evaluation methods, enhance the students' independent learning ability, and realize the integration of teaching and ideological and political education. The transformation of "three high" innovation resources into teaching: high-level design, high-quality requirements, high-level implementation, relying on high-level scientific research and innovation resources, timely transformation into teaching resources through classroom teaching, extracurricular science and innovation, school-enterprise exchanges and other ways, and focusing on cultivating students' practical ability and innovation ability.

Application of CNN based Regognition Technology in Public English Teaching in College Intelligent Classroom

With the advancement of intelligent technology, CNN-based recognition technology has been integrated into public English teaching in universities. This implementation contributes to enhancing teaching quality, nurturing students’ English proficiency, and holds significant educational and practical value. To address the issue of low traditional attendance efficiency in intelligent classrooms for public English teaching, a face recognition model based on CNN recognition technology has been developed. R-CNN is utilized for object detection, along with pyramid pooling and non-maximum suppression to acquire the optimal candidate region for face detection. Furthermore, K-Means clustering is combined to enhance Fast R-CNN, thereby improving detection accuracy. Experimental results demonstrated that among the three networks - Fast R-CNN, Faster R-CNN, and CNN -Faster R-CNN maintained a high recognition rate and exhibited faster convergence speed, showcasing superior overall performance. Specifically, at 500 iterations, the three networks require 23.7 seconds, 26.8 seconds, and 34.2 seconds, respectively. For facial expression recognition, Faster R-CNN achieved the highest recognition rate, indicating its exceptional detection efficiency and potential for aiding teaching management. This study offers novel technical support for public English teaching in intelligent university classrooms, effectively enhancing teaching efficacy and learning experiences. Its practical significance extends to promoting educational reform and improvement.

Intelligent Education Managemnt System Design for Universities based on MTCNN Face Recognition Algorithm

Face recognition technique has made significant advancements in security and attendance, but its application in teaching management is minimal. To address the issues of insufficient teacher resources and declining educational quality, the paper designs an intelligent education management system for colleges and universities based on improved Multi-task Cascaded Convolutional Neural Networks (MTCNN) face recognition. The purpose is to achieve accurate recognition of faces through improved facial recognition technology, thereby analyzing the attendance status of students, and improving the efficiency and quality of educational resource utilization. Firstly, an improved MTCNN facial recognition technology is adopted to achieve realtime monitoring of student status and attendance in the classroom through a B/S network structure. Secondly, through cluster deployment and load balancing, system stability and response speed can be improved. The results indicated that the improved MTCNN had better facial recognition accuracy and GPU utilization than traditional systems under different occlusion conditions. When there was no occlusion, recognition accuracy was 99.4%. However, when occlusion was presented at 10%, 20%, and 30%, the accuracy dropped to 92.3%, 84.25%, and 73.4%, respectively. Additionally, when the number of concurrent users was 1000, the maximum GPU utilization rate was 75%, which was 11% lower than traditional MTCNN systems. The use of an improved MTCNN facial recognition-based intelligent education management system in universities can effectively enhance the quality of classroom teaching and monitor the status of students. Further optimization of algorithm performance is needed in subsequent research to support larger-scale concurrent user usage while reducing hardware resource consumption.

Classroom Teaching of Engineering Courses Assisted by Artificial Intelligence and Digital Twin Systems

This paper explores the integration of Artificial Intelligence (AI) and Digital Twin systems in the classroom teaching of engineering courses, with a focus on the Industrial Robot Technology course1. It addresses the challenges of traditional practical teaching methods and proposes a new model that leverages AI and Digital Twin technology to enhance student engagement, improve learning outcomes, and better prepare students for the demands of the industry. The paper discusses the implementation of AI-assisted teaching, the creation of a ubiquitous teaching ecology, and the strengthening of vocational skills through digital twin.

Teachers’ Perceptions, Attitudes and Competency on Internet, Communication, and Technology Integration in the EFL Classroom in Indonesia

&lt;p style="text-align:justify"&gt;This study sheds light on perceptions and attitudes toward obtaining competency of English teachers at Senior High Schools regarding the integration of Internet, communication, and technology (ICT) in the English classroom in Indonesia. The research involved 113 English teachers from 11 different sub-districts in Riau Province-Indonesia, and data were collected through online questionnaires utilizing Google Forms. Quantitative data were analyzed using SPSS 24.0, while qualitative data were analyzed using a three-stage analysis involving data reduction, data display, and verification. The study’s findings revealed positive perceptions and favorable attitudes toward the integration of ICT in EFL classrooms. Importantly, EFL teachers’ competency in ICT significantly influenced their teaching performance. Qualitative insights highlighted obstacles faced by English teachers, such as limited internet networking and inadequate facilities, impacting their experiences due to the absence of ICT training and socialization from schools. Based on the findings, there is an urgent need to address challenges faced by teachers in rural areas, emphasizing the pivotal role of ICT for effective teaching and learning in EFL classrooms.&lt;/p&gt;

Evaluation and selection of E-learning websites using intuitionistic fuzzy confidence level based Dombi aggregation operators with unknown weight information

In recent years, the surge in online learning has eclipsed traditional classroom teaching, elevating the prominence of e-learning platforms. However, the quest for a reliable methodology to evaluate these platforms has remained pressing. While several studies have explored this domain, none have integrated decision experts’ confidence levels. This study bridges this gap by seamlessly incorporating confidence levels into Dombi aggregation operators within an intuitionistic fuzzy framework. The study introduces two innovative operators: the confidence-level intuitionistic fuzzy Dombi weighted averaging operator (CIFDWA) and the confidence-level intuitionistic fuzzy Dombi weighted geometric operator (CIFDWG). These operators are employed to form a novel multi-attribute group decision-making (MAGDM) approach, which is demonstrated by applying them to select the optimal e-learning website in a real-world scenario. The “Stepwise Weight Assessment Ratio Analysis (SWARA)” method is utilized to determine criteria weights. The findings highlight the critical importance of sub-criteria such as topic diversity, pricing, content credibility, data security, and user interface simplicity. The analysis reveals Unacademy as the leading platform, closely followed by Byju’s. Through meticulous comparative analysis and sensitivity evaluations, we underscore the stability and coherence of the proposed model. The study’s novelty lies in its innovative approach to integrating confidence levels in multi-attribute group decision-making scenarios, promising broader applications across various real-world contexts. Educational advisers and management can leverage this methodology to empower students with informed choices.

Exploration of Chinese Synonym Learning Methods for Indonesian Students

It is well known that the richness of Chinese vocabulary is unrivaled, including Chinese synonyms. The highly developed performance of the Chinese language can be seen in the synonyms of the Chinese language. Learning Chinese synonyms is simple but complex, and requires us to understand the nuances between them and be good at recognizing them so that we can use them accurately. Through the experience of learning and teaching, this paper finds that Indonesian students often encounter difficulties with Chinese synonyms. In addition, through the short time of this paper's internship, this paper also finds that in Indonesian classroom teaching, teachers' explanation of synonyms is not clear and to the point. This time, this paper tries to suggest some pedagogical methods for Chinese teachers to teach synonyms. This article is just a guideline, and we hope that this article can be a reference for the Chinese language teaching community.