Self-learning Ability Research Articles

Reform and Exploration of Teaching Modes in Data Processing Courses for Humanities and Social Sciences Majors

This article explores innovative teaching methods such as personalized instruction, fostering students' self-learning abilities and creative thinking, integrating multimedia technology for blended learning both online and offline, incorporating research into teaching, diversifying evaluation methods, and enhancing teachers' self-efficacy for improving teaching effectiveness. Taking the course "Python Data Processing and Analysis" as a case study, the article applies these approaches in practical teaching. The research findings indicate a significant improvement in teaching effectiveness, with noticeable enhancements in student engagement and performance.

Summary of Research on Highway Bridge Vehicle Force Identification

Vehicle force identification is one of the core technical problems to be solved urgently in the management of transportation infrastructure, and it has also been a research hotspot in recent years. To promote the application of vehicle force identification technology on bridges and explore its development direction, the development status of indirect vehicle force identification methods based on bridge response is reviewed during this study. The basic theories of two major methods, including bridge weigh-in-motion (BWIM) and moving force identification (MFI), are described in detail in this study, and then, the key technical principles of bridge force identification are revealed. Secondly, the development status of BWIM in recent years is reviewed from three aspects, including test accuracy, applicability and test efficiency. Combined with a variety of theories, the current status of MFI is analyzed from the establishment of the solution to the equation. Finally, the development direction of an artificial neural network and machine vision technology are prospected in this study. The BP neural network has good self-learning ability and self-adaptive ability, but the algorithm needs to be improved. The identification method based on machine vision represents the current development direction in vehicle force identification, with great potential.

Exploring the Impact of Online Translation on Writing Revision among Chinese Non-English Major Students

The present study examined the efficacy of online translation as an auxiliary revision tool for Chinese non-English majors, assessing its influence on writing performance and the students’ perceptions of its role in the revision process. This study employed writing task, questionnaire survey, and semi-structured interview to examine the efficacy of online translation as an auxiliary revision tool for Chinese non-English majors, assessing its influence on writing performance and the students’ perceptions of its role in the revision process. A total of 94 Chinese non-English majors who learn English as a foreign language (EFL) participated in the study. The results indicate that compared with those who revise their texts independently, those Chinese non-English majors who refer to online translation in the process of revision, made significantly more changes at the below-clause and clause and above levels in terms of revision domain, with increased additions and substitutions. Additionally, having access to online translation in the process of revision, Chinese non-English majors significantly increased their text length in final drafts, with decreased error rate, more low-frequency and sophisticated words, and varied lexical choices. Besides, virtually most of the participants use online translation frequently in English writing activities with a generally positive attitude towards the integration of online translation into English writing revision. For English teachers, they can consider allowing students to use online translation in the process of revision and giving students sufficient guidance on how best to realize its fullest potential. For Chinese non-English majors, they’d better keep improving their self-learning ability and double-check the online translation output by using other resources.

Soft skills unveiled: a comprehensive exploration of employer preferences and employability essentials

Soft skills have become a critical factor in enhancing individual employability. A deeper understanding of the specific soft skills valued by employers in various types of enterprises enables higher education institutions to more precisely cultivate these qualities in students. This study focuses on 15 essential soft skill indicators categorized into three key facets: personal, social, and methodological skills. Through the analysis of 366,077 job advertisements, we establish keyword libraries for different indicators, facilitating the identification of the types of soft skills emphasized in each advertisement. Our findings reveal that small and medium-sized enterprises (SMEs) prioritize a range of soft skills, except for creativity/innovation skills, analytical skills, and continuous improvement skills. On the other hand, state-owned enterprises (SOEs) exhibit a demand for as many as 14 out of 15 soft skill indicators, surpassing private enterprises, except for creativity/innovation skills. However, this emphasis on different soft skills does not necessarily result in salary differentials. Soft skill requirements linked to personal traits, such as professional ethics, commitment to work, stress resistance, and self-learning abilities, do not correlate with higher salaries. Conversely, soft skills related to socialization, like teamwork, leadership, and social networking, are associated with higher salaries. The results of this study reveal employers’ demand for various soft skills. Nevertheless, it is worth noting that this demand is not adequately reflected in salary levels. Employers should carefully consider and strive for a more equitable representation of soft skills in the determination of salaries.

Application effect of BOPPPS teaching model on fundamentals of nursing education: a meta-analysis of randomized controlled studies.

BOPPPS (bridge-in, learning objective, pretest, participatory learning, posttest, and summary) is a student-centered, closed-loop teaching model that emphasizes real-time communication and feedback. The purpose of this study was to review and evaluate the effect of BOPPPS teaching model in "Fundamentals of Nursing" teaching. We conducted a meta-analysis of randomized controlled trials (RCTs) based on the BOPPPS teaching model in "Fundamentals of Nursing" teaching. To review domestic and foreign databases for the period 2010 to September 2023. Finally, 13 RCTs were included and the teaching outcomes were measured and analyzed. Two researchers independently identified, selected, and extracted data from the study and examined the risk of bias. The primary outcomes were students' examination scores (theoretical scores: scores obtained in the nursing fundamentals course, reflecting students' understanding and mastery of the course content; practical scores: assessment results based on practical application or experimental skills, evaluating students' practical skill level). The secondary outcomes were self-learning ability score: indicators assessing students' self-directed learning ability, reflecting their competence in independent learning and autonomous exploration; and satisfaction rate of teaching effect: the overall satisfaction rate of students with the teaching effects experienced during teaching process reflects the proportion of students' acceptance and satisfaction with the teaching program. The results were evaluated using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) profiler software. The GRADE profiler software is used to assess and grade the recommendations according to the GRADE (Grading of Recommendations Assessment, Development, and Assessment) criteria. A total of 13 studies were included, consisting of 2,991 nursing students. Among them, 1,465 students were in the BOPPPS teaching group, while 1,526 students were in the traditional teaching group. The summary analysis of the main outcomes showed that the BOPPPS teaching model had significantly higher scores in theoretical score (MD = 3.35, 95% CI: 2.35-4.35, Z = 6.56, p < 0.00001), practice score (MD = 4.50, 95% CI: 1.95-7.05, Z = 3.45, p = 0.0006), and self-learning ability score (MD = 6.76, 95% CI: 5.38-8.14, Z = 9.60, p < 0.00001) compared to the traditional teaching group. The satisfaction rate of students in the BOPPPS teaching group regarding teaching effectiveness was 89% (95% CI = 0.84-0.93). The differences were statistically significant (p < 0.05). The GRADE evidence level for theoretical score and satisfaction rate of teaching effect is low. The evidence level for practice score is very low, and for self-learning ability score is moderate. The BOPPPS teaching mode is helpful to improve the theoretical score, practice score, and self-learning ability score of "Fundamentals of Nursing," and improve the satisfaction rate of students to the teaching effect. The teaching effect is better than the traditional teaching method.

Practical exercises of computer-aided process synthesis for chemical engineering undergraduates

The study presents ten different exercises covering various computational tools. These exercises are practical applications presented to improve the understanding and skills of students in important concepts of chemical-aided process synthesis. A few exercises aim to build a foundation in computational techniques for chemical engineering undergraduates. The exercises are based on a spreadsheet that covers the design of regression analysis to find the optimum Antoine constants, array calculation for multicomponent distillation material balance, and the generation of a Gantt chart to plan and study the activities of batch processes. The other exercises included an introduction to process simulation, simulation, and reactor rating, and a simulation of multicomponent shortcut distillation. These exercises provide students with hands-on experience in utilizing process simulation software essential for analysing and optimizing chemical processes in real-world scenarios. The exercises also included the design of a heat exchanger network and solving a linear programming problem. An anonymous survey was collected from the cohort that had undergone the exercises, and the practical grades were compared with the batch that did not study the proposed exercises. Additionally, student feedback on practical exercises was collected. Based on the experience of the course coordinator and the collected feedback from participants, it was clear that the exercises helped students to inculcate critical thinking and self-learning abilities. An article essentially sheds light on the computer-aided practical exercises that enable chemical engineering graduates to engage in lifelong learning.

The level of self-learning ability among university students in the light of dealing with innovative technologies

Introduction. A crucial topic of investigation in modern education is the study of self-learning abilities among college students, especially in using innovative technologies. In order to improve educational practices and student results, it is crucial to understand how students adapt to and use digital tools and online resources for self-directed learning. This is because these resources are becoming increasingly important to academic performance. The purpose of this study is to explore how college students utilize digital tools and online resources for self-learning. Study participants and methods. This investigation, which involved 500 pupils, set out to answer four primary questions: (1) the confidence that college students have in their abilities to learn independently with the help of digital tools; (2) how students' use and familiarity with cutting-edge tools change as they progress through college; (3) whether there are any gender variations in students' ability to learn on their own using modern technology; and (4) whether or not there are any relationships between students' grades and their use of cutting-edge study tools, using a Likert-scale survey. Results. The results demonstrated that out of 500 college students, 60% had faith in self-directed learning through innovative technology, with 200 agreeing and 100 strongly agreeing. On the other side, nearly a quarter were uneasy, with seventeen percent remaining indifferent and sixty-five percent strongly opposing. Just 10% of first-year students reported often utilizing tools, indicating reduced tool utilization and comfort. Whereas half of the fourth-year students regularly used them, the other half used them more frequently and were more comfortable with them. The study did not find any notable difference in the usage of technology for self-learning based on gender. There was an association between grade point average and technology use; students whose GPAs were between 3.5 and 4.0 were more likely to use technology frequently (4.8 out of 5.0) and were more comfortable using it (4.5 out of 5.0). Practical significance. This study has the ability to shed light on current educational procedures and strategies, which is where its practical significance lies. Teachers can gain a better grasp of how students make use of and adjust to digital resources for independent study in order to incorporate these technologies into lessons in a way that may improve students' learning experiences and outcomes. Insights from this study regarding the link between tech use and higher GPAs can help schools design better online classrooms. More personalized and efficient methods of higher education instruction can be a result of the study's impact on educational technology policy decisions.

Microstructure and deterioration mechanism of hydraulic concrete under variable temperature dry-wet cycles

In the variable water level area, hydraulic concrete structures are susceptible to variable temperature and alternating dry-wet cycles, especially for thin-walled structures. To elucidate alterations in the microstructure and strength of hydraulic concrete subjected to variable temperature dry-wet cycles, this paper firstly conducted a durability test on hydraulic concrete. Subsequently, CT scan images of the specimens are acquired during the variable temperature dry-wet cycle. Secondly, in view of the shortcomings of existing threshold methods for CT image pore segmentation, a new image segmentation method (RASLPSO-TV-Top-hat) is proposed by using Tensor voting and Top-hat technology, combined with a Reverse Adaptive Particle Swarm Optimization algorithm with Self-Learning ability. The evolution process of pore structure (microcracks) of hydraulic concrete under the variable temperature dry-wet cycles is captured. Thirdly, an in-depth analysis is conducted on the compressive strength and acoustic emission characteristics. The analysis shows that with the number of cycles increases, there is a discernible interconnection among the pore structures. This interconnection leads to a noteworthy reduction in the compressive strength of the concrete. Additionally, the cumulative number of Acoustic Emission ringing events exhibits an initial rise followed by a subsequent decline. The study successfully identifies the patterns governing the deterioration of strength and microstructure evolution in hydraulic concrete. The mechanism underlying the decline in performance of hydraulic concrete under variable temperature dry-wet cycles is elucidated. It provides a reliable and valuable basis for the safety assessment of hydraulic concrete structures in the variable water level area.

An Exploration of Blended Teaching Model for College English Vocabulary Based on the “VocabGo” Platform

With the rapid development of information technology in foreign language teaching, the blended teaching model that integrates online learning with offline classrooms has become the typical trend of college English teaching. Based on the analysis of the existing problems in vocabulary learning in current traditional teaching and the platform of “VocabGo”, this study explores a blended teaching model that includes vocabulary preview before class, vocabulary testing during class, and consolidation and improvement after class. This model expands the content of vocabulary teaching, emphasizes student-centeredness, and is conducive to the cultivation of students’ learning interest and self-learning ability, which has significant practical implications for the reform of college English teaching. Keywords: College, English Vocabulary, Blended Teaching, VocabGo.

Optuna-DFNN: An Optuna framework driven deep fuzzy neural network for predicting sintering performance in big data

Sintering performance index can reflect the quality of sintered ore, and the level of sintered ore performance directly affects the stability of blast furnace production. Accurate prediction of sinter performance metrics is essential to optimise sinter quality, improve production efficiency and reduce energy consumption. Based on the sintering big data, this paper proposes the Optuna-DFNN model by combining the fuzzy neural network algorithm, the deep neural network algorithm and the Optuna framework to address the problems of difficulty in tuning the parameter, lack of self-learning ability, and poor generalisation of the model of the traditional method when faced with the input of multiple parameters. The paper predicts the four prediction indexes of yield rate, return fines ratio, drum index and RDI+3.15 respectively. Among them, the relative error of the prediction of the yield rate is within 1.3 %, the relative error of the prediction of the return fines ratio is within 2.8 %, the relative error of the prediction of the drum index is within 0.32 %, and the relative error of the prediction of the RDI+3.15 is within 1.4 %. The results indicate that the Optuna-DFNN model has better performance in predicting sintering performance metrics. Based on the Optuna-DFNN sintered ore performance prediction model, the quality of sintered ore can be accurately predicted, the sintering process parameters can be adjusted in a timely manner, the sintering process can be optimized, and the utilization coefficient of sintering can be improved. Provide a reference for the optimisation of production processes, with a positive impact on cost reduction, environmental protection and increased sustainability of production.

Differences between Academically Outstanding and Non-achieving Female Students in Achievement Motivation and Self-Learning Ability

هدف الدراسة: زيادة اهتمام المملكة العربية السعودية بتمكين المرأة كانت سبباً في رفع مستوى الاهتمام بالأبحاث التي تُعنى بدراسة المتغيرات المتعلقة بتحسين المستوى الأكاديمي لطالبات الجامعة. ونتيجة لتدريس الباحث لعدد من طالبات الجامعة لمدة سنوات ظهرت مشكلة الدراسة في التساؤل عن أسباب تفوق بعض الطالبات وتأخر بعضهن، وكانت الفكرة في الدراسة هي الفروق بين الطالبات المتفوقات وغير المتفوقات دراسياً في الدافعية للإنجاز والقابلية للتعلم الذاتي؛ ومن ثم التحقق من العلاقة الارتباطية بين القابلية للتعلم الذاتي والدافعية للإنجاز لدى الطالبات المتفوقات. المنهجية: بلغت عينة الدراسة (112) طالبة من طالبات جامعة الملك خالد: (53) طالبة متفوقة، و(59) طالبة غير متفوقة، وذلك عن طريق تحديد المعدلات الدراسية لكل منهن. ولقياس متغيرات الدراسة استخدم مقياس القابلية للتعلم الذاتي من إعداد عيد (2018)، ومقياس الدافعية للإنجاز من إعداد عيد (2012). النتائج: توجد فروق بين متوسطات درجات الطالبات المتفوقات ودرجات الطالبات غير المتفوقات دراسياً في الدافعية للإنجاز والقابلية للتعلم الذاتي، وذلك لصالح الطالبات المتفوقات دراسياً. وتوجد علاقة ارتباطية موجبة بين الدافعية للإنجاز والقابلية للتعلم الذاتي لدى الطالبات المتفوقات دراسياً.

A Self-learning Ability Assessment Method Based on Weight-Optimised Dfferential Evolutionary Algorithm

INTRODUCTION: The research on the method of cultivating college students' autonomous ability based on experiential teaching is conducive to college students' change of learning mode and learning thinking, improving the utilisation rate of educational resources, as well as the reform of education.OBJECTIVES: Addressing the current problems of unquantified analyses, lack of breadth, and insufficient development strategies in the methods used to develop independent learning skills in university students.METHODS: This paper proposes an intelligent optimisation algorithm for the cultivation of college students' independent learning ability in experiential teaching. Firstly, the characteristics and elements of college students' independent learning are analysed, while the strategy of cultivating college students' independent learning ability in experiential teaching is proposed; then, the weight optimization method of cultivating college students' independent learning ability based on experiential teaching is proposed by using the improved intelligent optimization algorithm; finally, the validity and feasibility of the proposed method are verified through experimental analysis.RESULTS: The results show that the proposed method has a wider range of culture effects.CONCLUSION: Addressing the problem of poor generalisation in the development of independent learning skills among university students.

Analysis of the Current Situation and Influencing Factors of Knowledge, Attitude, and Practice of Nursing Informatics Among Intern Nursing Students

Objective: To investigate the current situation of knowledge, attitude, and practice (KAP) of nursing informatics for intern nursing students. Methods: A total of 213 intern nursing students were selected as subjects. Results: The total score of the questionnaire of knowledge dimension was 10.32 ± 3.23; the score of attitude dimension was 58.78 ± 6.80; the score of practice dimension was 29.06 ± 14.35. Logistic regression analysis showed that further learning plans, telemedicine hospital intern experience, self-learning ability, and telecare training were the related influencing factors of KAP (P &lt; 0.05). Conclusions: The current KAP level of nursing informatics among intern nursing students was low to moderate. Hence, the strengthening of school courses and skill training programs is urgently needed.

Analysis of the Aptitude of Teachers and Students of Economic Education in Facing the Challenges of Implementation of MBKM Curriculum

The implementation of the Free Learning Program of Free Campus (MBKM) in higher education is a significant focal point today. This study aims to assess the readiness of both educators and students for the MBKM curriculum. Conducted qualitatively, the research engaged faculty and students from the PGRI University of Wiranegara Economic Education Studies Program. Regarding lecturers, preparedness involves multifaceted aspects. They must enhance comprehension of MBKM's objectives and advantages, alongside understanding the curriculum alterations. Furthermore, managing augmented workload due to additional MBKM courses becomes imperative. On the other hand, students’ preparedness is equally pivotal. They must grasp the benefits of MBKM, comprehend their responsibilities in time management and study planning, adapt to new settings, and nurture the motivation for self-development. The readiness factors for both educators and learners in the MBKM implementation are interconnected and mutually reinforcing. Educators, equipped to handle MBKM changes, can offer effective guidance to students. Simultaneously, well-prepared students can fully leverage MBKM opportunities. Consequently, lecturers need to refine their understanding, pedagogical prowess, and workload management. Students, on the other hand, must cultivate awareness, self-learning abilities, adaptability, and intrinsic motivation for personal development. Adequate preparation for the MBKM curriculum can yield maximum benefits, enabling faculty and students to explore interests, talents, and expertise beyond the confines of their prescribed course of study. This readiness aligns teachers and students to make the most of the MBKM curriculum, fostering comprehensive growth and skill development.

Transfer Learning-Motivated Intelligent Fault Diagnosis Designs: A Survey, Insights, and Perspectives.

Over the last decade, transfer learning has attracted a great deal of attention as a new learning paradigm, based on which fault diagnosis (FD) approaches have been intensively developed to improve the safety and reliability of modern automation systems. Because of inevitable factors such as the varying work environment, performance degradation of components, and heterogeneity among similar automation systems, the FD method having long-term applicabilities becomes attractive. Motivated by these facts, transfer learning has been an indispensable tool that endows the FD methods with self-learning and adaptive abilities. On the presentation of basic knowledge in this field, a comprehensive review of transfer learning-motivated FD methods, whose two subclasses are developed based on knowledge calibration and knowledge compromise, is carried out in this survey article. Finally, some open problems, potential research directions, and conclusions are highlighted. Different from the existing reviews of transfer learning, this survey focuses on how to utilize previous knowledge specifically for the FD tasks, based on which three principles and a new classification strategy of transfer learning-motivated FD techniques are also presented. We hope that this work will constitute a timely contribution to transfer learning-motivated techniques regarding the FD topic.

Evaluation of the effectiveness of using flipped classroom in puncture skills teaching

BackgroundThe effectiveness of flipped classroom (FC) on puncture skills in medical education is still uncertain. This study aimed to assess the role of the FC model in puncture skills and investigate the acceptance and approval of FC among medical students and instructors.MethodsA mixed research approach of quasi-experimental research design and descriptive qualitative research was conducted in September 2022 for one month, using an FC teaching method that combined instructional videos and group learning. The study participants were 71 fifth-year medical students from two classes at a Chinese medical school and four instructors. The medical students were randomly divided into two groups: the traditional classroom (TC) group (Group A) and the FC group (Group B). For teaching, Group B used FC, and Group A used PowerPoint-based TC. The effectiveness of the two teaching models was assessed with Objective Structured Clinical Examination (OSCE), and questionnaires were distributed to the medical students and instructors after the assessment. Two independent sample t-tests were used to analyse the differences in demographic data and the OSCE scores of the two groups of medical students.ResultsGroup B scored higher in puncture skills than Group A, especially regarding abdominal puncture (p = 0.03), thoracentesis (p < 0.001), bone marrow puncture (p < 0.001) and average performance of puncture skills (p < 0.001). For lumbar puncture, no difference in skill scores was observed between groups A and B (p > 0.409). The medical students thought that the FC improved their self-learning ability and helped them acquire knowledge. Regarding the OSCE of their skills, most medical students thought that it was more innovative and objective than traditional examinations and that it was better for assessing their overall abilities. Both the FC and OSCE were supported by the medical students. The instructors were also satisfied with the students’ performance in the FC and supported the teaching model, agreeing to continue using it.ConclusionsThis study shows that FC teaching that combines instructional videos and group learning is a reliable and well-received teaching method for puncture skills, which supplements and expands existing teaching methods in the medical field.

Research on the Teaching Reform of French as a Second Foreign Language based on Learning Motivation

With the rapid development of the global economy, there is an increasing demand for talent's foreign language abilities, and French has become a second language course offered by more and more universities. However, in the current teaching of French as a second foreign language in various universities, there are problems such as emphasis on imparting textbook knowledge, insufficient training of students' language abilities, and low interest in learning, resulting in low teaching efficiency. In the learning process, learners themselves are the ultimate decision-makers of learning outcomes, and their learning motivation is directly related to their enthusiasm and initiative in learning. Therefore, in the teaching of French as a second foreign language, teachers should not only play their own role, but also explore and mobilize students' learning enthusiasm, strengthen their learning motivation, improve their self-learning ability, and achieve a student-centered and two-way interaction between teachers and students in French teaching.

Fusion model of weight on bit in horizontal exploration hole based on wavelet transform and machine learning

During the horizontal drilling of the development of energy and the geological exploration, the loss of axial feed pressure is serious due to the frictional resistance in horizontal hole. As the length of the drilling pipe increases, the problem of insufficient drilling pressure becomes increasingly prominent. It is imperative to master weight on bit (WOB) in time and accurately for the adjustment of drilling parameters. Limited by the long drilling pipe, it is difficult and costly to measure WOB directly. Therefore, a novel model of WOB prediction was established. The model realized the coupling of wavelet transform and neural network. Five easily available parameters, feed pressure, rotational speed, torque, pump pressure and drilling-fluid flow rate were selected as input to the model. The WOB was taken as the only output of model. First, Morlet wavelet was used to reform the structure of hidden layer and output layer of neural network. In the reformed model, the self-learning and adaptive ability of neural network and the ability for local information extraction of wavelet transform were fully stimulated. Then, embedded genetic algorithm (GA) was used to optimize the weights and wavelet parameters of the model, which improves the global optimization ability of the model. The established model was named GA-WNN, and the experimental results demonstrate that the R2 of prediction model reaches 0.9982. The mean absolute percentage error (MAPE) of GA-WNN prediction can yield as low as 6.22%, while the MAPE of standard neural network prediction can yield as high as 47.04%. Furthermore, the accuracy of the model was further verified by response surface methodology (RSM), and the results show that the predicted data of the model can meet the requirements of RSM for data quality. The RSM analysis of WOB based on predicted data was successfully carried out, and the interaction influence between drilling parameters on WOB were obtained, which provides reference for parameter adjustment. The high-quality algorithm of WOB prediction provides support for long-distance horizontal drilling.

Imitation learning enabled fast and adaptive task scheduling in cloud

Studies of resource provision in cloud computing have drawn extensive attention, since effective task scheduling solutions promise an energy-efficient way of utilizing resources while meeting diverse requirements of users. Deep reinforcement learning (DRL) has demonstrated its outstanding capability in tackling this issue with the ability of online self-learning, however, it is still prevented by the low sampling efficiency, poor sample validity, and slow convergence speed especially for deadline constrained applications. To address these challenges, an Imitation Learning Enabled Fast and Adaptive Task Scheduling (ILETS) framework based on DRL is proposed in this paper. First, we introduce behavior cloning to provide a well-behaved and robust model through Offline Initial Network Parameters Training (OINPT) so as to guarantee the initial decision-making quality of DRL. Next, we design a novel Online Asynchronous Imitation Learning (OAIL)-based method to assist the DRL agent to re-optimize its policy and to against the oscillations caused by the high dynamic of the cloud, which promises DRL agent moving towards the optimal policy with a fast and stable process. Extensive experiments on the real-world dataset have demonstrated that the proposed ILETS can consistently produce shorter response time, lower energy consumption and higher success rate than the baselines and other state-of-the-art methods at the accelerated convergence speed.

Developing self-learning abilities for students in the context of the Covid-19 pandemic: A case study in Vietnam

The COVID-19 pandemic has drastically changed educational settings around the world, making a drastic shift to online learning. This health crisis affected schools and the educational systems in developing countries like Vietnam in a major way as they struggled with problems because variations existed at levels of technology availability, readiness for distance. This research aims to discuss the development of self-learning abilities in Vietnamese students during the pandemic. It will emphasize how the students cope with online learning, how effective were the digital platforms for it, and the systems that helped bring about this change. This is a mixed-method study that incorporates quantitative data in the form of student and teacher surveys as well as qualitative insights derived from interviews and foci groups. This methodology would enable to provide a comprehensive understanding of student experiences and challenges faced by students while adapting to self-learning. The findings report on a plethora of adaptive strategies employed by the students and successes and challenges. The major challenges are with respect to the discrepancies in accessibility to digital tools, varying levels of self-motivation as well as the need to be better online pedagogies. However, in the midst of all these challenges, so many students showed outstanding adaptability and resilience in self-learning development skills. The research firmly draws the conclusion that the pandemic has proven a catalytic effect over significant educational shifts in Vietnam, and practice reorientation must require robust digital infrastructure, equivalent learning resources accessible to all students as well as new pedagogical appropriateness interventions. The findings of this study inform the policymakers and the educators in every capacity in charting their future education strategies not only for Vietnam but also for other similar setups across the world.