A Comparative Study on Verb-Noun Collocation Errors of Chinese EFL Learners with Different Language Proficiency

This study presents a comparative analysis of verb-noun collocation errors made by Chinese EFL learners with different language proficiency.Linguistic data from two sub-corpora of CLEC(Chinese Learner English Corpus,Gui&Yang,1999)consist of the compositions written freely by Chinese senior high school students(ST2)and the 3rd-and 4th-year English majors of Chinese universities(ST6).The study results show that four types of verb-noun collocation errors are frequently made due to incorrect L1 translation,misuse of relative synonyms,misuse of delexical verbs,and misuse of part of speech;the number of errors decreases with the development of language proficiency,especially errors by incorrect L1 translation and relative synonyms.And for both ST2 and ST6 EFL learners,errors resulted from incorrect L1 translation account for nearly a half with the same high-frequency words.It is also found that ST6 learners’competence in collocation and synonym identification doesn’t grow with the increase of their vocabulary,as is shown in the case of overusing delexical verbs in collocation,the same error made by ST2 learners,who have a significantly weaker command of delexical verbs.Implications of the findings are also discussed with the purpose of raising the awareness of collocation pedagogy and enhancing EFL learners’collocation competence.

Prevalence of visual impairment and estimation of refractive errors among school children in Kakamega,Kenya

AIM:To investigate the prevalence of visual impairment(VI)and provide an estimation of uncorrected refractive errors in school-aged children,conducted by optometry students as a community service.METHODS:The study was cross-sectional.Totally 3343 participants were included in the study.The initial examination involved assessing the uncorrected distance visual acuity(UDVA)and visual acuity(VA)while using a+2.00 D lens.The inclusion criteria for a subsequent comprehensive cycloplegic eye examination,performed by an optometrist,were as follows:a UDVA<0.6 decimal(0.20 logMAR)and/or a VA with+2.00 D≥0.8 decimal(0.96 logMAR).RESULTS:The sample had a mean age of 10.92±2.13y(range 4 to 17y),and 51.3%of the children were female(n=1715).The majority of the children(89.7%)fell within the age range of 8 to 14y.Among the ethnic groups,the highest representation was from the Luhya group(60.6%)followed by Luo(20.4%).Mean logMAR UDVA choosing the best eye for each student was 0.29±0.17(range 1.70 to 0.22).Out of the total,246 participants(7.4%)had a full eye examination.The estimated prevalence of myopia(defined as spherical equivalent≤-0.5 D)was found to be 1.45%of the total sample.While around 0.18%of the total sample had hyperopia value exceeding+1.75 D.Refractive astigmatism(cil<-0.75 D)was found in 0.21%(7/3343)of the children.The VI prevalence was 1.26%of the total sample.Among our cases of VI,76.2%could be attributed to uncorrected refractive error.Amblyopia was detected in 0.66%(22/3343)of the screened children.There was no statistically significant correlation observed between age or gender and refractive values.CONCLUSION:The primary cause of VI is determined to be uncorrected refractive errors,with myopia being the most prevalent refractive error observed.These findings underscore the significance of early identification and correction of refractive errors in school-aged children as a means to alleviate the impact of VI.

An Insight Survey on Sensor Errors and Fault Detection Techniques in Smart Spaces

The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart environments.To address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed analysis.This analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.

Relationships between Terrain Features and Forecasting Errors of Surface Wind Speeds in a Mesoscale Numerical Weather Prediction Model

Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SMS-WARR(Shanghai Meteorological Service-WRF ADAS Rapid Refresh System),are analyzed to quantitatively reveal the relationships between the forecasted surface wind speed errors and terrain features,with the intent of providing clues to better apply the NWP model to complex terrain regions.The terrain features are described by three parameters:the standard deviation of the model grid-scale orography,terrain height error of the model,and slope angle.The results show that the forecast bias has a unimodal distribution with a change in the standard deviation of orography.The minimum ME(the mean value of bias)is 1.2 m s^(-1) when the standard deviation is between 60 and 70 m.A positive correlation exists between bias and terrain height error,with the ME increasing by 10%−30%for every 200 m increase in terrain height error.The ME decreases by 65.6%when slope angle increases from(0.5°−1.5°)to larger than 3.5°for uphill winds but increases by 35.4%when the absolute value of slope angle increases from(0.5°−1.5°)to(2.5°−3.5°)for downhill winds.Several sensitivity experiments are carried out with a model output statistical(MOS)calibration model for surface wind speeds and ME(RMSE)has been reduced by 90%(30%)by introducing terrain parameters,demonstrating the value of this study.

Towards Lessening Learners’Aversive Emotions and Promoting Their Mental Health:Developing and Validating a Measurement of English Speaking Demotivation in the Chinese EFL Context

While a plethora of studies has been conducted to explore demotivation and its impact on mental health in second language(L2)education,scanty research focuses on demotivation in L2 speaking learning.Particularly,little research explores the measures to quantify L2 speaking demotivation.The present two-phase study attempts to develop and validate an English Speaking Demotivation Scale(ESDS).To this end,an independent sample of 207 Chinese tertiary learners of English as a Foreign Language(EFL)participated in the development phase,and another group of 188 Chinese EFL learners was recruited for the validation of the scale.Exploratory Factor Analysis(EFA)and Confirmatory Factor Analysis(CFA)were employed to determine the factor structure of the scale.The EFA results revealed a six-factor solution with Teacher-related Factors in Learning Spoken English(TFLSE),Interest and Valence in Learning Spoken English(IVLSE),Self-efficacy in Learning Spoken English(SELSE),Negative Peer Influence in Learning Spoken English(NPILSE),Undesirable Environment for Learning Spoken English(UELSE),and Negative Influence of Assessment and Learning Materials in speaking class(NIALM).In the validation phase,Confirmatory Factor Analysis(CFA)was performed to validate the internal structure of the scale.The CFA results showed that the model fits the data well.Overall,the ESDS is a robust and trustworthy psychometric tool that could be utilized to examine L2 speaking demotivation.Implications for diminishing EFL learners’demotivation,lessening their aversive emotions and promoting their mental health are also discussed.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

An Empirical Study of Chinese English Learners' Attitudes toward Errors and Error Correction in Question-asking

Based on the questionnaire, this study found that :1) Elementary learners were inclined to commit more global errors compared to their local errors, whilst advanced learners make more local errors; 2) Interlingual factors were more influential than intralingual factors in elementary learners' error making, but for advanced learners, intralingual factors played relatively a much more important role in error making; 3) Elementary learners preferred explicit correction whilst advanced learners favoured im?plicit correction in question-asking.

Numerical Investigations on the Resonance Errors of Multiscale Discontinuous Galerkin Methods for One-Dimensional Stationary Schrödinger Equation

In this paper,numerical experiments are carried out to investigate the impact of penalty parameters in the numerical traces on the resonance errors of high-order multiscale discontinuous Galerkin(DG)methods(Dong et al.in J Sci Comput 66:321–345,2016;Dong and Wang in J Comput Appl Math 380:1–11,2020)for a one-dimensional stationary Schrödinger equation.Previous work showed that penalty parameters were required to be positive in error analysis,but the methods with zero penalty parameters worked fine in numerical simulations on coarse meshes.In this work,by performing extensive numerical experiments,we discover that zero penalty parameters lead to resonance errors in the multiscale DG methods,and taking positive penalty parameters can effectively reduce resonance errors and make the matrix in the global linear system have better condition numbers.

The Impact of Comment Style on Learners’ Essay Revisions

This paper investigates how the type of written feedback provided by teachers affects learners’ ability to revise essays. A total of 120 participants participated in two rounds of essay composition and feedback delivery. The findings indicate that learners who receive comments in the form of questions are more prone to make revisions compared to those receiving statements or imperatives. These results hold significant implications for educators and the ways they utilize written feedback to enhance learners’ writing skills.

Analysis of Young Learners’Listening Skills

The importance of listening as one of the communication skills cannot be overstated.However,in many areas,listening is neglected.For young learners,learning to listen is even more beneficial for their future studies,therefore,listening skills should be given due importance.

Enhancing Learners’Performance in Grade 7 Mathematics Through 50-30-20 Exercise

Assessment exercises constitute a crucial component of the teaching and learning process,serving the purpose of gauging the degree to which learning objectives have been accomplished.This study aims to assess the mathematics performance of Grade 7 learners using the 50-30-20 exercise.Specifically,this study seeks to determine the learners’pre-test and post-test mean scores,identify significant differences between the pre-test and post-test results,evaluate learners’exercises,and propose enhanced exercises.The research employs a quasi-experimental design,with 40 Grade 7 learners in the school year 2023-2024 as participants,selected through purposive non-random sampling.Statistical data analysis involves the use of mean,standard deviation,paired t-test,and Cohen’s D effect size.Ethical considerations were paramount,as evidenced by a letter of authorization from the school head outlining the strict adherence to voluntary participation,informed parental consent,anonymity,confidentiality,risk mitigation,results-sharing protocols,and the commitment to keeping research data confidential.The data yielded a remarkable outcome:the experimental group exhibited improvement in both the pre-test and post-test.This result substantiates the initial objective of the study,showcasing a noteworthy and favorable performance among the participants.Consequently,it suggests that a majority of the participants strongly agree that the 50-30-20 exercises contribute to enhancing their understanding and problem-solving skills,as well as their ability to grasp mathematical concepts and improve their overall performance in mathematics.Therefore,the 50-30-20 exercises not only facilitated students in understanding mathematics lessons but were also aligned with the Department of Education’s development plan.

Entangled relationship:Chinese parents’involvement in young learners’English tests

Young learners’English(YLE)tests have become increasingly prevalent among and important to Chinese English learners and their parents.In China,parents are actively involved in their children’s education and test-taking decisions,and their participation has given rise to a series of social impacts.Although parent involvement has received increasing public and academic attention in newspaper and scholarly articles,there exists no thorough analysis of current research on parents’roles in young learners’test-taking.To address this gap,we systemically analyzed Chinese newspaper articles and academic articles between 2011 and 2021 to elicit Chinese parents’roles in YLE test-taking.Our thematic analysis of the literature identifies the ways in which parents influence their children’s test-taking experiences,and how the tests affect this influence.Specifically,our results elicit 1)parents’engagement in YLE testing;2)parents’understanding of the intended uses of YLE tests;3)parents’perception and consequences of their involvement in YLE testing;and 4)parents’backgrounds.This analysis reveals the popularity of YLE tests among young learners and their parents in China and public concern over test-related issues.It also broadens our understanding of YLE testing impact and suggests future potential research directions.

Common Errors Committed by Second Language Learners in the Use of Interrogative

This study examines the common errors committed by the high school students at Para aque High School.Results reveal the development sequence of different types of interrogative,causes of the developmental errors are also discussed.

A Corpus-based Study on High Frequency Grammatical Errors in theWritten Production by Chinese EFL Learners

The present study is a corpus-based error analysis of IL written production by Chinese EFL learners. Based on the Interlanguage theory, the research chooses the tagged WECCL as the data base, and makes an overall investigation of the high frequency grammatical errors committed by Chinese EFL learners.

Crosslinguistic Influence of the First Language: Interlingual errors in the writing of ESL Saudi learners

Writing as a productive skill is challenging for the learners as it requires rich linguistic and cognitive abilities to match words with ideas well. A learner of any language as Second Language (SL), for example English, Arabic, Chinese, or German, enters an early, natural, and inevitable stage of making various errors in writing compositions. The errors could be due to dissimilar linguistic systems of the two languages (L1 and L2) or the lack of understanding the SL linguistic rules. This study focuses on investigating the frequent and common inter-lingual errors (the negative influence) committed by Arabic-speaking learners of English as Second Language (ESL). The study is based on Error Analysis (EA) of the essays of a group of English major undergraduate students from the University of Bisha, Al-Namas, Saudi Arabia. Contrastive Analysis Hypothesis (CAH)is included to predict most of the errors in the collected samples. The findings of the study show that common errors in the data are interlingual (54.03%). The errors within the Grammatical Category include the misuse of tenses, dropping the subjects, dropping verb to be-copular and word order misplacement. The majority of errors in the study are due to the interference of L1 linguistic system including the different orthographic, phonological,morpho-syntactic components. For instance, the participants’ dropping subjects in English can be attributed to the fact that Arabic as L1 and as Null Subject Language (NSL), unlike English, allows subject drop. The results also find that within the Lexical Category,preposition and article errors are the most frequent errors and that spelling errors are the most dominant errors within the Mechanics Category. The study gives some pedagogical implications and suggestions to avoid and minimize the interlingual errors of such type. For instance, teachers need to focus more on enlightening their students about the contrastive language systems from the early stage of learning ESL.

An Analysis on Sources of Learners' Spoken English Errors

Chinese learners often commit different oral errors in their English learning process.Having a clear knowledge of the sources of these errors will help learners learn English better.This paper makes a study of the sources of spoken English errors.It starts by giving a distinction between mistakes and errors.The sources of errors are comprehensively explored.Hopefully,it can provide clues for the improvement of spoken English learning.

A Description of Oral Errors for English Speaking Learners in Technical Colleges

Technical college students often commit different oral errors in their English learning. The type of students'spoken English errors is analyzed in this paper and the common errors are classified into four groups: phonological errors, lexical errors, grammatical errors and pragmatic errors. The result shows that lexical errors and grammatical errors are more common for learners from technical colleges.

Prevalence of refractive errors in children of Puerto Rico

AIM:To determine the prevalence of refractive error in 5-to 17-year-old schoolchildren in Puerto Rico.METHODS:A quantitative descriptive study of 2867 children aged 5 to 17y from all seven educational regions of Puerto Rico was conducted from 2016–2019.Refractive error was determined via static and subjective refraction.Children with distance acuity≤20/40 or near visual acuity≤20/32 had a cycloplegic refraction.Data analysis included descriptive statistics,correlation coefficient,Kruskal-Wallis,Chi-square,and t test calculations.RESULTS:Twenty percent of the children had a spherical equivalent refractive error≤-0.50 D,3.2%had a spherical equivalent≥+2.00 D,and 10.4%had astigmatism≥1 D.There was a statistically(but non-clinically)significant myopic change in spherical equivalent refractive error with age(P<0.001).The prevalence of myopia increased with age(P<0.001)but not hyperopia(P=0.59)or astigmatism(P=0.51).Males had a significantly higher hyperopic spherical equivalent than females(P<0.001).Females had a higher prevalence of myopia(P<0.001)than males,but there was no difference in the hyperopia(P=0.74)or astigmatism prevalence(P=0.87).CONCLUSION:The prevalence of a spherical equivalent equal to or less than-0.50 D(myopia,20.7%)is one of the highest among similar-aged children worldwide.Further studies should explore the rate of myopia progression in children in Puerto Rico.Individual children must be monitored to examine the need for treatment of myopia progression.

Robust Beamforming Under Channel Prediction Errors for Time-Varying MIMO System

The accuracy of acquired channel state information(CSI)for beamforming design is essential for achievable performance in multiple-input multiple-output(MIMO)systems.However,in a high-speed moving scene with time-division duplex(TDD)mode,the acquired CSI depending on the channel reciprocity is inevitably outdated,leading to outdated beamforming design and then performance degradation.In this paper,a robust beamforming design under channel prediction errors is proposed for a time-varying MIMO system to combat the degradation further,based on the channel prediction technique.Specifically,the statistical characteristics of historical channel prediction errors are exploited and modeled.Moreover,to deal with random error terms,deterministic equivalents are adopted to further explore potential beamforming gain through the statistical information and ultimately derive the robust design aiming at maximizing weighted sum-rate performance.Simulation results show that the proposed beamforming design can maintain outperformance during the downlink transmission time even when channels vary fast,compared with the traditional beamforming design.