The Nature and Use of Technology-Based Self-Regulated Learning Strategies Among EFL Students

This study explored the nature and use of technology-based self-regulated learning(SRL)strategies among the Chinese university students.A total of 20 undergraduate students in China's Mainland were invited to participate in a focus group interview.The students reported using four types of technology-based SRL strategies including cognitive,meta-cognitive,social behavioral,and motivational regulation strategies.Among the strategies,technology-based vocabulary learning was reported to be a dominant strategy by the students.This study opens a new window to understanding how English as a foreign language(EFL)students utilize different strategies to learn English in technology-based learning context.

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.

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.

On Reducing Students' Anxiety in English Listening through Cooperative Learning

Listening is an important means by which English learners can obtain information and communicate with others. Therefore, listening is an important skill of English learning and listening training is an indispensible part of language learning. However, listening can easily be affected by anxiety. Anxiety, an obvious psychological phenomenon in listening and speaking, has negative effect on language input, process and output. Although anxiety has negative influence on English listening, it can be overcome by Cooperative Learning (CL). CL can reduce anxiety, improve communication ability and strengthen learners' confidence, etc.

On Improving Students' Learning Efficiency in English Teaching

In our country,traditional English teaching attaches excessive importance to the explanation of vocabulary and grammar,causing students' disability in language practice.This paper provides some strategies to improve students' learning efficiency.

Investigation of English learning strategy employed by senior middle school students in Zhanjiang City： A comparison of students from urban and rural areas

After a review of learning strategy research in China and abroad, this paper made an investigation on the differences in use of learning strategies reported by urban and rural students from four middle schools in Zhanjiang city. The investigation revealed the following findings： urban students employ cognitive and social strategies more frequently than rural students; urban students reported a wider range of strategies compared with their rural peers; urban students of intermediate achievements employ more social strategies than their rural peers, while rural students use affective strategy significantly more often; urban and rural students reported different patterns of gender difference.

English Learning Strategies Employed by EFL Postgraduate Students in Southwest China

English learning strategies play an important role in the language proficiency for EFL learners. Both frequency and patterns of English learning strategies use were found to be significantly related to language proficiency. The present investigation aimed to investigate a) an overall strategy use of postgraduate students in southwest China; and b) to examine the relationship as well as patterns of variations in frequency of students' reported strategy use with reference to their gender and field of study. The subjects of this study were 200 postgraduates in the universities of southwest China. A written questionnaire based on the Strategy Inventory for Language Learning(SILL) was adapted and biodata was added for background information. The findings of the research showed that the postgraduates, on the whole, reported medium frequency of use of English learning strategies. The results of the data analysis also demonstrated that frequency of postgraduates' reported use of English learning strategies varied significantly in terms of gender and field of study. The implications, limitations and recommendations for further research were also discussed.

A Study on Left-behind Junior Students'Foreign Language Learning Anxiety

Since the 1960s, foreign language educators and researchers home and abroad have started to pay attention to the influence of the affective variables including language learning anxiety on foreign language learning. This thesis tried to find out the factors that may influence the foreign language learning anxiety level of left-behind students and put forward ways to help lower down the foreign language learning anxiety level of the left-behind junior middle school students.

The Analysis on the Role of Motivation in College Students’ English Learning

Foreign language teaching is a very complicated process that includes varied factors.Among those factors,the learner's factors are very important.Learner is the main part of a foreign language learning and teaching.In recent years,considerable research has been focused on the study of the foreign language learners,especially on their motivations.Learners'motivation plays a very important role in Chinese college students'English learning.

Personality Trait Detection via Transfer Learning

Personality recognition plays a pivotal role when developing user-centric solutions such as recommender systems or decision support systems across various domains,including education,e-commerce,or human resources.Tra-ditional machine learning techniques have been broadly employed for personality trait identification;nevertheless,the development of new technologies based on deep learning has led to new opportunities to improve their performance.This study focuses on the capabilities of pre-trained language models such as BERT,RoBERTa,ALBERT,ELECTRA,ERNIE,or XLNet,to deal with the task of personality recognition.These models are able to capture structural features from textual content and comprehend a multitude of language facets and complex features such as hierarchical relationships or long-term dependencies.This makes them suitable to classify multi-label personality traits from reviews while mitigating computational costs.The focus of this approach centers on developing an architecture based on different layers able to capture the semantic context and structural features from texts.Moreover,it is able to fine-tune the previous models using the MyPersonality dataset,which comprises 9,917 status updates contributed by 250 Facebook users.These status updates are categorized according to the well-known Big Five personality model,setting the stage for a comprehensive exploration of personality traits.To test the proposal,a set of experiments have been performed using different metrics such as the exact match ratio,hamming loss,zero-one-loss,precision,recall,F1-score,and weighted averages.The results reveal ERNIE is the top-performing model,achieving an exact match ratio of 72.32%,an accuracy rate of 87.17%,and 84.41%of F1-score.The findings demonstrate that the tested models substantially outperform other state-of-the-art studies,enhancing the accuracy by at least 3%and confirming them as powerful tools for personality recognition.These findings represent substantial advancements in personality recognition,making them appropriate for the development of user-centric applications.

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.

Enhancing personalized exercise recommendation with student and exercise portraits

The exercise recommendation system is emerging as a promising application in online learning scenarios,providing personalized recommendations to assist students with explicit learning directions.Existing solutions generally follow a collaborative filtering paradigm,while the implicit connections between students(exercises)have been largely ignored.In this study,we aim to propose an exercise recommendation paradigm that can reveal the latent connections between student-student(exercise-exercise).Specifically,a new framework was proposed,namely personalized exercise recommendation with student and exercise portraits(PERP).It consists of three sequential and interdependent modules:Collaborative student exercise graph(CSEG)construction,joint random walk,and recommendation list optimization.Technically,CSEG is created as a unified heterogeneous graph with students’response behaviors and student(exercise)relationships.Then,a joint random walk to take full advantage of the spectral properties of nearly uncoupled Markov chains is performed on CSEG,which allows for full exploration of both similar exercises that students have finished and connections between students(exercises)with similar portraits.Finally,we propose to optimize the recommendation list to obtain different exercise suggestions.After analyses of two public datasets,the results demonstrated that PERP can satisfy novelty,accuracy,and diversity.

How to Stimulate College Students' English Learning Motivation

Motivation to language learning is a complex set of variables including effort, desire to achieve goals, as well as attitudes toward the learning of the language. Individuals' motivation to second-language learning also includes their motivation orientations, interest in the second language, attitudes toward the second-language group, attitudes toward the second-language learning situations and second-language anxiety. Based on the basic theories and approaches, teaching activities are part of motivation in English classes. The teacher of language should have a good influence on students and develop students' keen interest in study in order to strengthen their intrinsic motivation, and set up some new goals for students to pursue and give the feedback to reinforce their inner drive and confidence. Thus, students will become major conductors, make full use of their potentials and enhance their study results.

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.

Design of a Student Recommendation Platform Based on Learning Behavior and Habit Training

This study innovatively built an intelligent analysis platform for learning behavior,which deeply integrated the cutting-edge technology of big data and Artificial Intelligence(AI),\mined and analyzed students’learning data,and realized the personalized customization of learning resources and the accurate matching of intelligent learning partners.With the help of advanced algorithms and multi-dimensional data fusion strategies,the platform not only promotes positive interaction and collaboration in the learning environment but also provides teachers with comprehensive and in-depth students’learning portraits,which provides solid support for the implementation of precision education and the personalized adjustment of teaching strategies.In this study,a recommender system based on user similarity evaluation and a collaborative filtering mechanism is carefully designed,and its technical architecture and implementation process are described in detail.