Using Web Corpora to Develop Students’Autonomous Learning Compe⁃ tence for English Vocabulary—An Action Research

This study conducted an action research on facilitating students’vocabulary autonomous learning competence by applying web corpora into vocabulary teaching in EFL classroom.The research last for one semester(15 weeks),53intermediateEnglish learners.whose age ranged from 20 to 22 were the subjects.The data was collected usingquestionnaire,teacher’s log,students’diaries and interview.The findings were discussed in the light of interventions and recommendations in the classroom instruction.

Results of the virtual simulation teaching method on autonomous learning competencies of undergraduate nursing students

Background:With the continuous development of information technology,most universities use mobile teaching platforms for classroom teaching.With the help of the national virtual simulation experimental teaching project sharing platform,students can enhance self-directed learning through the virtual simulation operations of the project.Purpose:To explore the application of virtual simulation experiment in teaching the fundamentals of nursing practice based on the Platform of the National Virtual Simulation Experiment Teaching Project during the COVID-19 pandemic analyze the impact of this teaching method on the autonomous learning ability of undergraduate nursing students.Methods:Convenience sampling was used to select 121 nursing undergraduates from Y University’s School of Nursing;the online teaching of fundamentals of nursing practice was conducted to the students.After taking the course,questionnaires were distributed to the undergraduate nursing students to collect their perceptions regarding the use of the virtual simulation experiment platform and autonomous learning competencies.Results:Most students expressed their preference for the virtual simulation teaching platform,and their satisfaction with the project evaluation was high 83.05%.They hoped to promote the application in future experimental teaching.Undergraduate nursing students believed that the virtual simulation teaching platform was conducive to cultivating clinical thinking ability,could stimulate learning interest,enhanced autonomous learning competencies.Conclusion:During the pandemic,the virtual simulation teaching platform for a lecture on in nursing education has achieved good results in both the aspects of teaching and student learning.Teachers efficiently used their training time and reduced their teaching burden.Moreover,the laboratory cost was also reduced.For undergraduate nursing students,the system was conducive to cultivating clinical thinking ability,stimulating their interest in learning,enhancing their learning and comprehension abilities and learning initiative.

Research on College Studentst'Autonomous EFL Learning Affer Course Exemption

By analyzing the English learning logs of 12 students in a provincial university in south-west China after they had been exempted from taking college English courses,this study investigated college students’autonomous EFL(English as a foreign language)learning after course exemption,including the use of mediational means in EFL learning,EFL learning hours,and other factors affecting EFL learning,in the hope of giving new perspectives on college ELF curriculum design,teaching,and education management.

Toward Trustworthy Decision-Making for Autonomous Vehicles:A Robust Reinforcement Learning Approach with Safety Guarantees

While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present a novel robust reinforcement learning approach with safety guarantees to attain trustworthy decision-making for autonomous vehicles.The proposed technique ensures decision trustworthiness in terms of policy robustness and collision safety.Specifically,an adversary model is learned online to simulate the worst-case uncertainty by approximating the optimal adversarial perturbations on the observed states and environmental dynamics.In addition,an adversarial robust actor-critic algorithm is developed to enable the agent to learn robust policies against perturbations in observations and dynamics.Moreover,we devise a safety mask to guarantee the collision safety of the autonomous driving agent during both the training and testing processes using an interpretable knowledge model known as the Responsibility-Sensitive Safety Model.Finally,the proposed approach is evaluated through both simulations and experiments.These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies.

Surveying on English Mobile Learning Among University Students: Current State and Influencing Factors

Mobile learning integrates mobile technology with digital learning,offering flexible,personalized content and portable equipment.It enables access to rich content and enhances learning efficiency.Therefore,it has become mainstream to utilize mobile devices for English learning among university students’English learning.The current study aims to examine the current situation and influencing factors of university students’English mobile learning.98 university students in one university of Shanghai participated the study and the questionnaire was used to collect the data.The results indicated that most university students already have electronic devices to support mobile learning.Personal factors,environmental factors,digital literacy,and technological capabilities are the main factors affecting university students’English mobile learning.The current study has implications for learners,teachers,and software developers.Learners should adjust their learning motivation,play an active role,and fully utilize the mobile platform to obtain resources and improve learning efficiency.Teachers should incorporate the advantages of mobile teaching and promote categorized and tiered teaching.Software developers should add new functions on the basis of meeting the basic needs of learners and continuously innovate the mobile learning platform.

Evaluation of Chinese Learning Efficiency of International Students in China:Comparing by Dimension

This paper introduces the Value Engineering method to calculate the value coefficient of Chinese learning efficiency for 377 international students by dimension.Results suggest that attention should be paid to male,European and American,rural,introverted,and“work or education needs”international students;Give full play to the driving role of the reference-type,explore the space for improving the learning efficiency of the improvement-type and attention-type,and pay attention to the problems of problem-type international students.

Evaluation of Chinese Learning Efficiency of International Students in China

This paper investigates the related factors of Chinese learning engagement and performance of 377 students from three universities in Guangzhou of China,employs the value engineering method,and calculates the value coefficient of learning efficiency.From the value coefficient of Chinese language learning,it proves that over 60%of international students studying in China have a higher efficiency in learning Chinese.

Efficacy of Online Learning and Influence on Skin and Eyes Among College Students

To evaluate the efficacy of online learning and explore the impact of long-term use of electronic products on facial skin as well as eyes.A cross-sectional survey was conducted to 180 sophomores in Xi′an Jiaotong University by cluster random sampling from September to October 2021.The questionnaire covering study condition,skin lesion and Ocular Surface Disease Index.χ_(2) test was used to compare the facial skin condition among different groups,and spearman correlation test was used to test the correlation of rank data.During online education,students′learning pressure is reduced,their autonomy is improved,and the learning efficiency is reduced.There were differences in the incidence of facial itching and papules among different groups.Duration of use of electronic products was positively correlated with the facial itching,with an r value of 0.231(P<0.05);the proportion of pigmentation in non-blue light protection groups(12.8%)was higher than that in blue light protection groups(1.7%),the difference was statistically significant(χ_(2)=8.384,P<0.05).The prevalence of dry eye among college students is 66.7%,and the proportion of moderate to severe dry eye is 34.5%.The study autonomy has been improved during online teaching.Long-term use of electronic products and no blue light protection have an impact on facial skin.Students should enhance the knowledge of skin-care and eye-care and develop better habits.

An Investigation on the Influence of Middle School Students'Grammar Learning Self-efficacy on Their Learning Performance

In middleschool English teaching,grammar instruction has always been an important and challenging aspect.Due to the strong influence of grammar explanation in Chinese,learning English grammar may be affected by negative transfer from their native language,which could pose certain obstacles to English acquisition.Self-efficacy,as a major emotional factor influencing learners'internal regulation strategies,has attracted wide attention from researchers both domestically and internationally for its impact on learning performance.High self-efficacy helps learners develop a more positive mindset towards learning,thereby contributing to improved learning performance.Therefore,this study focuses on investigating the relationship between grammatical self-efficacy and learning performance of English grammar among middle school students.This research contributes to a complementary understanding of grammatical self-efficacy among educators,enhancing their teaching skills,and effectively guiding students to learn English grammar with a more positive and healthy mindset,presenting a future grammar instruction in middle school English teaching.

On Affective Strategies use in College Students' Autonomous English Learning

Autonomous study emphasizes the learner's initiative,enthusiasm and creativity.In all fields of education,there is growing emphasis on "learner-centered" teaching methods and the ability of learner autonomy.Many experts and scholars have found that learning strategies plays an important role in English language learning,but the importance of affective strategy use in English learning is often ignored by people.Therefore,this paper focuses on the frequencies of affective strategies use in English learning and their relationships so as to enable college students to use positive affective strategies effectively to improve their autonomous learning ability.

Research into college students＇ English autonomous learning capability and the necessity of cultivating metacognitive strategies

Through the research into college students＇ English autonomous learning ability of the non-English major students. That the cause why university students＇ English autonomous learning ability is weak is proved to be that they do not value the use of learning strategies. The use of learning strategies can promote the formation and enhancement of autonomous learning ability of the learners. Metacognitive strategy is a high-level management skill which can enable the learners to plan, regulate, monitor and evaluate actively their own learning process. Massive researches have proved whether metacognitive strategy is used successfully or not can directly affect the student learning result. So, it is necessary for teachers to cultivate and train the students to use metacogitive strategy in the university English teaching.

A Stacking Machine Learning Model for Student Performance Prediction Based on Class Activities in E-Learning

After the spread of COVID-19,e-learning systems have become crucial tools in educational systems worldwide,spanning all levels of education.This widespread use of e-learning platforms has resulted in the accumulation of vast amounts of valuable data,making it an attractive resource for predicting student performance.In this study,we aimed to predict student performance based on the analysis of data collected from the OULAD and Deeds datasets.The stacking method was employed for modeling in this research.The proposed model utilized weak learners,including nearest neighbor,decision tree,random forest,enhanced gradient,simple Bayes,and logistic regression algorithms.After a trial-and-error process,the logistic regression algorithm was selected as the final learner for the proposed model.The results of experiments with the above algorithms are reported separately for the pass and fail classes.The findings indicate that the accuracy of the proposed model on the OULAD dataset reached 98%.Overall,the proposed method improved accuracy by 4%on the OULAD dataset.

Efficient Intelligent E-Learning Behavior-Based Analytics of Student’s Performance Using Deep Forest Model

E-learning behavior data indicates several students’activities on the e-learning platform such as the number of accesses to a set of resources and number of participants in lectures.This article proposes a new analytics systemto support academic evaluation for students via e-learning activities to overcome the challenges faced by traditional learning environments.The proposed e-learning analytics system includes a new deep forest model.It consists of multistage cascade random forests with minimal hyperparameters compared to traditional deep neural networks.The developed forest model can analyze each student’s activities during the use of an e-learning platform to give accurate expectations of the student’s performance before ending the semester and/or the final exam.Experiments have been conducted on the Open University Learning Analytics Dataset(OULAD)of 32,593 students.Our proposed deep model showed a competitive accuracy score of 98.0%compared to artificial intelligence-based models,such as ConvolutionalNeuralNetwork(CNN)and Long Short-TermMemory(LSTM)in previous studies.That allows academic advisors to support expected failed students significantly and improve their academic level at the right time.Consequently,the proposed analytics system can enhance the quality of educational services for students in an innovative e-learning framework.

Effects of Perceived Teacher Support on Student Behavioral Engagement in the Blended Learning Environment:Learning Experience as a Mediator

Blended learning(BL)has been widely adopted to improve students’academic achievements in higher education.However,its success relies mainly on student engagement,which plays an essential role in active learning and provides a rich understanding of students’experiences.The study utilized three self-designed scales-the Teacher Support Scale,Student Engagement Scale,and Student Learning Experience Scale-to gauge and examine the impact and relationship between perceived teacher support,student behavioral engagement,and the intermediary role of learning experiences.A cohort of 899 college students undertaking the obligatory College English course through BL modes across five Chinese universities actively participated by completing a comprehensive questionnaire.The results showed significant correlations between perceived teacher support,learning experience,and behavioral engagement.Perceived teacher support significantly predicted students’behavioral engagement,with socio-affective support exerting the most substantial predictive effects.All predictive effects were partially mediated by learning experience(learning mode,online resources,overall LMS-based learning,interaction with their instructor and peers,and learning outcome).The influence of perceived teacher support on behavioral engagement differed between students who reported the most positive(vs.negative)learning experiences.Suggestions for further research are offered for consideration.

An Analysis of College Students＇ Autonomous English Learning Ability under the Network Environment

Referring to the questionnaire survey and literature materials, this paper describes the current situation of college students＇ insufficient autonomous English learning ability and thefactors that influence this ability; it also suggests feasible suggestions under the network environment. Students （N= 178） from different grades, majors, universities and areas responded to a questionnaire survey, and the collected data were analyzed. The results indicate that complex external environment and insufficient internal subject cognition influence college students＇ autonomous English learning ability. Finally, this paper suggests that a good network environment is necessary for autonomous learners to enhance insufficient autonomous English learning ability and interaction, continuous thinking and cultural introduction are also indispensable to develop this ability.

A Combined Reinforcement Learning and Model Predictive Control for Car-Following Maneuver of Autonomous Vehicles

Model predictive control is widely used in the design of autonomous driving algorithms.However,its parameters are sensitive to dynamically varying driving conditions,making it difficult to be implemented into practice.As a result,this study presents a self-learning algorithm based on reinforcement learning to tune a model predictive controller.Specifically,the proposed algorithm is used to extract features of dynamic traffic scenes and adjust the weight coefficients of the model predictive controller.In this method,a risk threshold model is proposed to classify the risk level of the scenes based on the scene features,and aid in the design of the reinforcement learning reward function and ultimately improve the adaptability of the model predictive controller to real-world scenarios.The proposed algorithm is compared to a pure model predictive controller in car-following case.According to the results,the proposed method enables autonomous vehicles to adjust the priority of performance indices reasonably in different scenarios according to risk variations,showing a good scenario adaptability with safety guaranteed.

A Structural Analysis of Senior High School Students’English Achievement Goal Orientation,Learning Anxiety,and Autonomous Learning Behavior

The present study aimed to investigate senior high school students to explore the relationships among their English achievement goal orientations,learning anxiety,and autonomous learning behavior.748 first-year senior high school students in Guizhou Province,China were selected as participants.A comprehensive questionnaire measuring the above variables was designed to collect the data.The Structural Equation Modeling(SEM)was used to analyze the data.The results showed that the model had good fit to the sample.The students’mastery goals and performance-approach goals positively contributed to their autonomous learning behavior,whereas their performance-avoidance goals were negatively associated with their autonomous learning behavior.The students’mastery goals effectively reduced their learning anxiety,but their performance-approach goals and performance-avoidance goals engendered learning anxiety.The students’learning anxiety and their autonomous learning behavior were negatively correlated.

Using TED to Enhance Student Autonomous Learning

Based on the literature review about autonomous learning,the study put forward four steps for using TED to enhance student autonomous learning,which are preparation,activity design,presentation and evaluation. By doing so,both teachers and students can achieve their teaching and learning objectives.

Path Exploration of Autonomous Learning in College Students＇ Ideological and Political Theory Course

Ideological and political theory teaching course is the public compulsory course of college students, which is the effective measures of conducting socialism core value system education for college students and realizing the ideological political and moral quality cultivation and improvement of chinese characteristic socialism successors, the ideological and political theory course learning of college students has obvious features in chinese university education, reflecting the party central committee＇ s great attention to college students＇ ideological and political education, and we should strengthen college students＇ ideological and political theory education, explore autonomous learning path of university exploration college students and promote the combination of theory and practice of college students, realizing autonomous learning, autonomous education and autonomous improvement, in order to effectively improve the effect of ideological and political theory education.

The Impact of Online Courses towards Students in Autonomous Learning Based on New Media Technologies

In the 21st century,the rapid development of online technology has dramatically transformed people’s way of lives.The emergence of high-tech products has also boosted modern education to embrace informationization and virtualization.With the promotion and development of online courses,autonomous learning is now emerging among students in colleges and universities.If they want to learn relevant professional knowledge,they could use networking and information technology with relevant devices.This learning method could not only impact traditional education but also facilitate students to explore new ways to learn autonomously.This paper is to discuss the impact of online courses towards students in autonomous learning by analyzing its current learning situation,the feature of this new form and its effects towards students.