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In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

This study aims to examine how teacher candidates (TCs) in Türkiye and the USA navigate their intercultural communication skills in a telecollaboration project.

Forty-eight TCs participated (26 in Türkiye and 22 in the USA) in the study. TCs discussed critical issues in multicultural education on an online learning platform for six weeks. Their discussions were analyzed using content and discourse analysis.

The findings indicated that TCs approached the telecollaborative space as a translingual contact zone and positioned themselves and their interlocutors in the discourse by using the personal pronouns; I, we, you and they. When they positioned themselves using we (people in Türkiye/USA), they spoke on behalf of everyone included in the scope of we. Their interlocutors responded to these positionings either by accepting this positioning and responding with a parallel positioning or by engaging in translingual negotiation strategies to revise the scope of we and sharing some differences/nuances in beliefs and practices in their community.

When TCs talk about their culture and community in a singular manner using we, they frame them as the same across every member in that community. When they ask questions to each other using you, the framing of the questions prime the respondents to sometimes relay their own specific experiences as the norm or consider experiences from different points of view through translingual negotiation strategies. A singular approach to culture(s) may affect the marginalized communities the most because they are lost in this representation, and their experiences and voices are not integrated in the narratives or integrated with stereotypical representation.

Teachers and teacher educators should first pay attention to their language choices, especially use of pronouns, which may communicate inclusion or exclusion in intercultural conversations. Next, they should prepare their students to adopt and practice language choices that communicate respect for cultural diversity and are inclusive of marginalized populations.

Speakers’ pronoun use includes identity construction in discourse by drawing borders around and between communities and cultures with generalization and particularity, and by patrolling those borders to decide who is included and excluded. As a response, interlocutors use pronouns either to acknowledge those borders and respond with corresponding ones from their own context or negotiate alternative representations or further investigate for particularity or complexity. In short, pronouns could lead the direction of intercultural conversations toward criticality and complexity or otherwise, and might be reasons where there are breakdowns in communication or to fix those breakdowns.

This study shows that translingual negotiation strategies have explanatory power to examine how speakers from different language backgrounds negotiate second and third order positionings in the telecollaborative space.

The theory of third order inference is a theory of how cultural beliefs influence individuals' decisions under conditions of interdependence and uncertainty. In this study, I build on prior work extending the theory to the role of third order information on social trust in public goods dilemmas. Namely, I argue that when second order information on the beliefs of those relevant to the group task are present, this information should influence decision-making over first and third order.

I test this argument in an experimental public goods game. After measuring first order social trust, participants are randomly sorted into one of four conditions – two that pair third and second order information on social trust as parallel and two that pair them as in conflict.

The results suggest that in the presence of second order information on social trust, third order information doesn't have an effect on cooperation.

The study extends the theory of third order inference to understanding the role of social trust at the first, second, and third levels in public goods dilemmas. It puts second order information in competition with third order in predicting cooperation. It suggests that resolving the uncertainty over the second order beliefs of a collective is key to preventing inefficient equilibriums when second and third order beliefs conflict.

The research aims to discuss technical and vocational students' long-term and complete evaluation of learning effectiveness under school-wide thematic teaching design.

This study adopted a mixed qualitative and quantitative approach to measure the learning effectiveness of thematic teaching in technical vocational schools using the Kirkpatrick model. Qualitative research conducted in-depth interviews with 32 interviewees, including students, parents, teachers, graduate alumni and the supervisors of off-campus internship units. Quantitative research conducted a questionnaire survey on vocational students. A total of 221 valid questionnaires were collected. In addition, this research conducts another quantitative survey on cooperative enterprises to compare the actual effect of the implementation of the school-wide thematic teaching students with the others, and a total of 35 valid questionnaires were collected.

The results of the research found that the effectiveness of thematic teaching method can achieve the expected goals of each level of Kirkpatrick model. The students taking thematic teaching are significantly better and fitting in the industry expects. Therefore, this research suggests the comprehensive introduction of school-wide thematic teaching to other school operators.

This research is the first study used the Kirkpatrick model to evaluate the effectiveness of school-wide thematic teaching design in hospitality education and providing a practical case for schools. This research combined qualitative and quantitative research methods to investigate the effectiveness of the teaching method through multiple perspectives. Through the feedback from supervisors of the hospitality industry, the school-wide thematic teaching design provides a good foundation for technical and vocational graduates.

This study explores the impact of Industry Revolution 4.0 (IR4.0) on learning factory implementation in Universiti Malaysia Pahang (UMP). A learning factory is an action-oriented approach to teaching with participants acquiring competencies through structured self-learning processes in a production–technological learning environment. It integrates different teaching methods with the main objective of moving traditional teaching methods to become closer to real industrial problems. However, there is still limited information that can be used to evaluate the impact of IR4.0 on its implementation in UMP. Therefore, this study focuses on exploring the challenges faced by UMP in developing their learning factory and examines the effectiveness of UMP Learning Factory as a new teaching and learning process to support Industry 4.0.

First of all, identifying a problem was done, and information regarding the topic was obtained via research from various sources. Example of sources is online journals, books, the Internet and others. It is essential to understand the rationale behind why the research should be carried out as well as the objectives of the study in relation to the topic of interest. After that, a survey of the relevant literature was carried out to compile more pertinent material and run it through the lens of the selected subject. It makes the process of establishing a theoretical framework easier, and it also improves one's knowledge of the research being done. The next step in the process involves selecting responders based on the research. In order to calculate the appropriate sample size for this study, we must identify the entire population so that we can ensure that the findings we obtain are reliable. The entire population are first filtered based on the purpose of the research, and only then is it possible to establish the size of the needed sample of respondents. This research study's data gathering techniques consisted of five steps; however, in this particular study, the researcher only employed two approaches, which focused on individual interviews and semi-structured interviews, respectively. In order to address both the study purpose and the research questions, the interview questions that were developed were meant to relate to one another. During this interview procedure, the interviewees will have the option to elaborate or supply an increasing amount of pertinent data and information. Participants in the interview who have accumulated a significant amount of experience in the relevant sector are better positioned to provide both their personal and professional perspectives. The researcher will utilize audio to gather the script from the responder so that they may collect the data for analysis. The researcher is able to find the precise data analysis from the responses with the assistance of this programme. As a result, the researcher's question to the responders can be considered credible and genuine. Each respondent may read a particular question in the questionnaire in the same manner. As a result, although the question may be trusted, this fact is mostly irrelevant given that it lacks internal validity and hence does not make it possible to answer the research topic. In conclusion, the findings of this study are analysed, and conclusions are drawn from them.

In order to explore and answer research questions that are tailored to research objectives, the purpose of this study is to investigate such questions. The primary purpose of this study is to evaluate the influence that Industry 4.0 will have on the instructional methodology that will be utilized at UMP. Regarding the second aim, the purpose is to investigate the difficulties that the Universiti Malaysia Pahang encounters in the process of creating the Learning Factory. The final goal is to investigate how well UMP Learning Factory performs as a novel approach to education and training that is intended to assist Industry 4.0. The University of Malaya in Penang (UMP), which is widely regarded as one of the premier educational institutions of its kind in Malaysia, has recently implemented a learning factory as one of its pedagogical approaches. The university's deployment of the learning factory is very recent, and as such, there is room for improvement to make the most of the potential offered by this instructional approach. However, the findings of this research indicate that there is a favourable influence on both learning and teaching. The influence of the implementation of Learning Factory, which is becoming one technique of educational reform, is one of the most important factors to consider. According to the study's findings, UMP has successfully developed a learning factory that has a major influence on the learning process and is extremely good at what it does. The student benefits from an enhanced teaching and learning experience as a direct result of the contribution made by the learning factory. When it comes to generating a learning component based on the result, several obstacles have been identified. If UMP or other institutions intend to create a new learning factory, the problems might be considered factors to consider. In the teaching and learning process context, it has been demonstrated that a learning factory is particularly successful. The learning factory approach is one of the teaching techniques that makes the students understand better and have the experience of handling and controlling the equipment. Because this method introduces the hands-on approach, it is one of the teaching methods. The learning factory method is one that, in its most fundamental form, may be particularly beneficial for students to prepare themselves for the arduous process of joining the workforce. The classroom setting will be quite similar to that of a factory, and the student will improve their general collaboration. In addition to this, they will be able to operate machines and have knowledge regarding the machines that are found in the learning factory. The learning factory makes a significant contribution to the knowledge transfer process in UMP by facilitating the development of a deeper comprehension of certain bodies of information. When compared to more traditional methods of transferring information, the student will have a much easier time comprehending the material that is taught to them through the use of the hands-on learning technique.

This study gained some information about the impact of IR4.0 towards educational transformation, which is expected to give positive results. Basically, this research will provide further explanation about IR4.0 and educational transformation in UMP focus on learning factory. Generally, the implementation of IR4.0 in education will produce a positive result and help the students in the future. The result from this case study will hopefully be beneficial to society. The finding from this research will be used as references to all, especially top management and technical staff of UMP, for further understanding of the impact of the implementation of the learning factory. While conducting this research, seven respondents were selected from the two faculty with their own learning factories, Faculty of Industrial Management (FIM) and Faculty of Technology (FTEK). The researcher targeted lecturers and technical staff as their respondents. The overall result from the interview session was analysed. All the result is based on the interview answer to the researcher's question

The study aims to assess the effectiveness of engaging tutors in designing and using ICT integrated lesson activities in strengthening their pedagogical use of ICT competences.

Survey data from an intervention group of 70 tutors from two teachers colleges (TCs) were used to compare their level of ICT competences and domains of professional practice before and after the intervention. Document analysis, lesson observations and feedback from the learning management system (LMS) were used to describe tutors’ experiences from the intervention.

There was a statistically significant increase in tutors’ level of pedagogical use of ICT competences and domains of professional practice associated with hands-on practice in designing and implementing the intervention.

The intervention focus on hands-on practice, actual teaching and learning needs, and the use of active learning strategies like flipped classroom and the LMS, were useful means for tutors to make sense of pedagogical use of ICT competences.

The results offer useful insights to teacher education institutions and policymakers on how to prepare professional learning and supportive policies to enhance teaching and learning with ICT for addressing the learning needs of the subject matter.

Creating 16 ICT integrated lesson activities helped tutors to learn pedagogical use of ICT competences by doing. Use of such intervention could be a useful strategy in teacher education institutions to reposition ICT competence development from reproducing technological competences toward developing knowledge creators who could innovate their pedagogical practice with support from mentors, digital learning resources and networks.

Through the action research study, this paper aims to examine how e-portfolios improve students’ critical, reflective and creative thinking as part of higher-order thinking skills (HOTS). Besides, this paper also explores how e-portfolios enhance students’ speaking skills. The study is carried out to improve the current state by identifying and solving problems in specific contexts.

This investigation was designed to seek the improvement of the students’ higher-order thinking and speaking skills after the implementation of the e-portfolio. Action research was chosen because action research is suitable to bring change and improvement in the system or assume to bring progress in the system. This study was designed in two phases, featuring reflection and connection between previous and new data.

By completing this action research study, the authors assisted students in improving their higher-order thinking and speaking skills. The improvement was related to the indicators for learning success, which were explained in this research. The HOTS criteria include the capacity to analyze essential facts and arguments that the students presented in their spoken works logically and critically.

HOTS encompasses critical, logical, creative and metacognitive thinking skills. Future research should go further into the usage of e-portfolios in the development of students’ metacognitive capacities. Moreover, because this investigation was carried out using action research methods, it is crucial to recognize that no generalizability can be offered for the findings.

The study’s findings should also benefit practitioners and instructors endeavoring to enhance students’ e-portfolios, critical thinking and digital skills in the classroom.

The discussion focuses on important development topics. Everyone, not just students, should be encouraged to participate in creating and developing our technological future. The analysis offers unique and essential perspectives into what to explore for such a substantial attempt as implementing digital technology, specifically to construct an e-portfolio.

Despite the widespread usage of e-portfolios in English as a foreign language (EFL) instruction, there is a lack of research on how e-portfolios can enhance EFL students’ HOTS and speaking abilities. Hence, this study addresses a deficiency in existing research by examining the potential of e-portfolios to enhance students’ HOTS and oral communication skills within the context of EFL.

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture.

Initiating a practical model for embedding transformative learning in education that will promote sustainable development is a challenge for higher education. Siam University decided to assign a task force with the mission to work with communities in order to propose guidelines of learning for sustainability (LfS) based on real-life experiences. Selected communities which have agreed to be the community living labs for teaching and learning activities of the university were chosen based on the Bray and Thomas’ Cube Model. There are differences in sizes (number of members), locations (urban, suburban), and histories (old settlement with long history and rich culture and the newly settlement communities consisting of migrated members). Community-based participatory research (CBPR) was applied in the study. The initial model was developed from the synthesis of experiential work with communities in sustainability-related projects. After revision, the “Learning for Sustainability Action Model” was proposed. Success factors in implementing the model were also suggested.