Learning Scale Research Articles

Revisiting the Construct Validity of Self-Regulating Capacity in Vocabulary Learning Scale: The Confirmatory Composite Analysis (CCA) Approach

Abstract Research into self-regulating capacity in vocabulary learning is recognized as a significant topic within the second language domain. The self-regulating capacity in vocabulary learning scale (SRCvoc; Tseng et al. 2006) is arguably the most widely used tool for assessing this construct. The common factor model, which is applied through confirmatory factor analysis and exploratory factor analysis, has been the primary methods for validating the SRCvoc. However, previous studies have encountered difficulties in obtaining good model fit and generated results that deviate from supporting the theory. We argue the constructs of the SRCvoc are inherently composites, rather than common factors, and should therefore be evaluated using confirmatory composite analysis. In this study, we compared the results of CFA and CCA, highlighting the shortcomings of CFA in supporting the construct validity of composite constructs such as SRCvoc. CFA failed to satisfy the conceptual and empirical perspectives of SRCvoc. In contrast, our data supported the construct validity of SRCvoc solely through CCA. We also evaluated the criterion-related validity of SRCvoc via the composite model and showed that SRCvoc constructs were positively and moderately associated with L2 vocabulary achievement.

The Effect of Augmented Reality Applications on Intravenous Catheter Placement Skill in Nursing Students: A Randomized Controlled Study

BackgroundAugmented reality (AR) is an emerging technology that is beginning to find use in health science education due to the advantages it brings to the teaching-learning process. This present study assessed the use of AR for the development of IV catheter placement skills in nursing students and the effects of the process on their learning satisfaction and self-confidence levels. MethodsThis randomized controlled study was completed with 91 nursing students in October, 2021, from whom data were collected using the Student Satisfaction and Self-Confidence in Learning Scale (SCLS) and the Intravenous Catheter Placement Procedure Steps Form (IVC-PPSF). ResultsAlthough higher scores were recorded in the experimental group, there was no significant difference in the IV catheter placement success scores or satisfaction of the students (p > 0.05). The difference was statistically significant for Self-Confidence (p < 0.05). ConclusionThe use of an AR application for the teaching of IV catheter placement was found to increase the self-confidence levels of the students. Expanding the use of AR applications into the teaching of other nursing practices will contribute positively to student success levels.

Object Balance: Smartphone-based Media Development

The current transformation of technology and information is very fast, making it easier to create media. Physics concepts that are known to be very abstract and difficult can be easily understood by providing a visual representation using a Smartphone so that they can be studied anywhere and anytime. This study aims to determine the feasibility and student responses for the development of physics media on the material of rigid body equilibrium using APP Inventor. The research and development (R&amp;D) method was used. The results of this study were in the form of learning media based on Android (.apk), which contains materials, videos, simulations, examples of problem-solving, and evaluations designed in a way as to attract students’ interest in learning scales and making it easier to understand the concept of rigid bodies.&#x0D; Keywords: object balance, smartphone, media development

Pre-pregnancy ozone and ultrafine particulate matter exposure during second year of life associated with decreased cognitive and adaptive functioning at aged 2–5 years

BackgroundThis study sought to investigate the association of prenatal and early life exposure to a mixture of air pollutants on cognitive and adaptive outcomes separately in children with or without autism spectrum disorder (ASD). MethodsUtilizing data from the CHARGE case-control study (birth years: 2000–2016), we predicted daily air concentrations of NO2, O3, and particulate matter <0.1 μm (PM0.1), between 0.1 and 2.5 μm (PM0.1-2.5), and between 2.5 and 10 μm (PM2.5-10) using chemical transport models with ground-based monitor adjustments. Exposures were evaluated for pre-pregnancy, each trimester, and the first two years of life. Individual and combined effects of pollutants were assessed with Vineland Adaptive Behavior Scales (VABS) and Mullen Scales of Early Learning (MSEL), separately for children with ASD (n = 660) and children without ASD (typically developing (TD) and developmentally delayed (DD) combined; n = 753) using hierarchical Bayesian Kernel Machine Regression (BKMR) models with three groups: PM size fractions (PM0.1, PM0.1-2.5, PM2.5-10), NO2, and O3. ResultsPre-pregnancy Ozone was strongly negatively associated with all scores in the non-ASD group (group posterior inclusion probability (gPIP) = 0.83–1.00). The PM group during year 2 was also strongly negatively associated with all scores in the non-ASD group (gPIP = 0.59–0.93), with PM0.1 driving the group association (conditional PIP (cPIP) = 0.73–0.96). Weaker and less consistent associations were observed between PM0.1-2.5 during pre-pregnancy and ozone during year 1 and VABS scores in the ASD group. ConclusionsThese findings prompt further investigation into ozone and ultrafine PM as potential environmental risk factors for neurodevelopment.

Scalable Learning Framework for Detecting New Types of Twitter Spam with Misuse and Anomaly Detection.

The growing popularity of social media has engendered the social problem of spam proliferation through this medium. New spam types that evade existing spam detection systems are being developed continually, necessitating corresponding countermeasures. This study proposes an anomaly detection-based framework to detect new Twitter spam, which works by modeling the characteristics of non-spam tweets and using anomaly detection to classify tweets deviating from this model as anomalies. However, because modeling varied non-spam tweets is challenging, the technique's spam detection and false positive (FP) rates are low and high, respectively. To overcome this shortcoming, anomaly detection is performed on known spam tweets pre-detected using a trained decision tree while modeling normal tweets. A one-class support vector machine and an autoencoder with high detection rates are used for anomaly detection. The proposed framework exhibits superior detection rates for unknown spam compared to conventional techniques, while maintaining equivalent or improved detection and FP rates for known spam. Furthermore, the framework can be adapted to changes in spam conditions by adjusting the costs of detection errors.

183 Earlier Surgery is Associated With Improved Post-operative Language Development in Children With Tuberous Sclerosis Complex (TSC)

INTRODUCTION: Early life epilepsy in TSC has been strongly associated with lifelong intellectual disability. While improved seizure control correlates with improvements in quality of life and cognition, the importance of surgery timing in young children has not been well-studied. METHODS: Changes in patients’ preoperative (0-12 months) to postoperative (36 months) scores in neuropsychologic tests—including the Mullen Scales of Early Learning (MSEL), Vineland Adaptive Behavior Scales, Second Edition (VABS-II), and the Preschool Language Scales, 5th addition (PLS-5)—were calculated. Pearson correlation and multivariate linear regression models were used to correlate changes in test scores with age at surgery and separately with duration of epilepsy prior to surgery. Analysis was limited to those patients who demonstrated improved seizure control post-operatively (n = 18). RESULTS: Age at surgery had a statistically significant negative correlation with changes in the combined verbal sub-tests of the MSEL (R = -0.41, p = 0.04) and predicted the change in that measure outcome in a multivariate linear regression model (β: -0.09, p = 0.03). Similar trends were seen for the change in the total language score of the PLS-5 (R = -0.38, p = 0.06; β: -0.21, p = 0.07). Results were similar when the duration of epilepsy prior to surgery was assessed as the independent variable. However there were no clear trends with the VABS-II questionnaires, even in language domains. CONCLUSIONS: Our data shows that successful earlier surgery and shorter epilepsy duration prior to surgery are both associated with improved post-operative language development in a small cohort of patients with TSC. Prospective clinical trials are necessary to further elucidate this relationship.

An Efficient and Adaptive Granular-Ball Generation Method in Classification Problem.

Granular-ball computing (GBC) is an efficient, robust, and scalable learning method for granular computing. The granular ball (GB) generation method is based on GB computing. This article proposes a method for accelerating GB generation using division to replace k -means. It can significantly improve the efficiency of GB generation while ensuring an accuracy similar to that of the existing methods. In addition, a new adaptive method for GB generation is proposed by considering the elimination of the GB overlap and other factors. This makes the GB generation process parameter-free and completely adaptive in the true sense. In addition, this study first provides mathematical models for the GB covering. The experimental results on some real datasets demonstrate that the two proposed GB generation methods have accuracies similar to those of the existing method in most cases, while adaptiveness or acceleration is realized. All the codes were released in the open-source GBC library at https://www.cquptshuyinxia.com/GBC.html or https://github.com/syxiaa/gbc.

Health Care Clinical Preceptors' Attitudes Towards Interprofessional Education in Saudi Arabia: A Cross-Sectional Study.

IPE fosters a dynamic learning environment that may promote students' knowledge, abilities, and collaborative approach towards addressing challenging clinical circumstances. While much has been reported in the literature regarding these diverse IPE learning environments, limited information exists regarding clinical preceptors' attitude and perceptions of IPE, especially in Saudi Arabia. Given the impact clinical preceptors have on the formation of healthcare students exploring their perceptions, which may impact their actions is imperative. The study focused on understanding the attitudes and perceptions of clinical preceptors towards IPE in a healthcare setting in Saudi Arabia. The study was conducted in Saudi Arabia. Data was collected via Email letter of solicitation (LOS) which included a link to the Readiness for Interprofessional Learning Scale (RIPLS) survey. The LOS was sent to all the health care programs in Saudi Arabia. The study surveyed 182 clinical preceptors. The findings revealed consistent favorable opinions towards "Teamwork and Collaboration". The majority of preceptors concurred that learning alongside other students would increase students' efficiency on healthcare teams and deepen their comprehension of clinical issues. The "Roles and Responsibilities" category, however, obtained lower ranks in general from the preceptors. Not surprising, differences in rankings were greatest between preceptors who had and did not have IPE exposure, there were significant variations in views toward "Teamwork and Collaboration", "Negative Professional Identity", and "Roles and Responsibilities". Preceptors exposed to IPE showed lower median ratings for "Negative Professional Identity" and "Roles and Responsibilities" and better median scores for "Teamwork and Collaboration". The attitudes and perceptions of preceptors who had experienced IPE were more favorable toward IPE and thus may foster it more effectively in the students they work with. Therefore, ensuring that all preceptors are aware of and have experience with IPE is important as we seek to promote person-centered care.

Readiness of Interprofessional Education on Maternal Health of Medical and Dental Students: A Mixed-Methods Study

Background: The high mortality rate and various health problems for maternal are of great concern in Indonesia. Oral and dental health of maternal receives less attention from both patients and health workers. The need for collaborative practices between doctors and dentists to optimize the health care of maternal. Interprofessional education is prepared to form medical and dental practitioners who are ready to interprofessional collaboration practice. Therefore, careful preparation is needed so that the learning process goes well and produces the desired results.This study aims to analyze the readiness of interprofessional education on maternal health among medical and dental students.Methods: This study was used mix methods. The cross-sectional quantitative method uses the questionnaire of readiness interprofessional learning scale (RIPLS) which has been modified and validated by Tyastuti (2014), containing 3 sub-scales. The qualitative method uses case studies with focus group discussions of student representatives.Results: There were 139 medical students and 49 dentistry students, both of whom had good readiness respectively 65,51 and 66,45 with a p value of 0,175. There was no significant difference in IPE readiness between the two. Good IPE readiness shows the development of teamwork, a good impression of IPE. However, there are problems that must be corrected such as bad attitudes and perceptions as well as problems in the field during home visits.Conclusion: Medical students and dental students have good readiness for maternal health of IPE, proven to give a good impression and establish teamwork. However, it still needs improvement to be even better.

Physics-Informed Graph Neural Operator for Mean Field Games on Graph: A Scalable Learning Approach

Mean-field games (MFGs) are developed to model the decision-making processes of a large number of interacting agents in multi-agent systems. This paper studies mean-field games on graphs (G-MFGs). The equilibria of G-MFGs, namely, mean-field equilibria (MFE), are challenging to solve for their high-dimensional action space because each agent has to make decisions when they are at junction nodes or on edges. Furthermore, when the initial population state varies on graphs, we have to recompute MFE, which could be computationally challenging and memory-demanding. To improve the scalability and avoid repeatedly solving G-MFGs every time their initial state changes, this paper proposes physics-informed graph neural operators (PIGNO). The PIGNO utilizes a graph neural operator to generate population dynamics, given initial population distributions. To better train the neural operator, it leverages physics knowledge to propagate population state transitions on graphs. A learning algorithm is developed, and its performance is evaluated on autonomous driving games on road networks. Our results demonstrate that the PIGNO is scalable and generalizable when tested under unseen initial conditions.

디지털 기반 학습 환경에서의 자기조절학습 척도 개발을 위한 예비문항 연구

Purpose: This study aims to develop preliminary items for creating a self-regulated learning scale in a digital learning environment for upper-grade elementary school students. Method: The research involves analyzing prior studies on digital learning and self-regulated learning. Surveys and interviews with upper-grade elementary students were conducted to define and identify factors in self-regulated learning in their digital learning experiences. Preliminary items were then selected and validated for content. Results: Self-regulated learning in a digital environment is defined as the process where students use digital tools to support their learning, become aware of their learning situations, and independently regulate various aspects of their learning. The self-regulated learning measurement tool consists of five areas with 32 preliminary items. Conclusion: This study attempts to reframe the traditional concept of self-regulated learning within the context of a digital learning environment. It focuses on developing a scale for self-regulated learning applicable to younger learners.

The role of social and emotional skills on adolescents’ life satisfaction and academic performance

The COVID-19 pandemic, which emerged in 2019, has had a significant impact on the mental health of adolescents, leading to symptoms such as anxiety and depression, and a decrease in their overall life satisfaction. In the educational context, social and emotional competencies have gained increasing importance due to their potential to enhance various aspects of academic, personal, and professional life. This study aimed to assess the socioemotional competencies of 1,270 secondary school students and explore their connection with life satisfaction and academic achievement. For this purpose, the Social and Emotional Learning Scale, the Spanish adaptation of the Life Satisfaction Scale, and an ad-hoc questionnaire that collected the sociodemographic variables of gender, age, and academic performance, were administered. The Mann-Whitney U test for two independent samples, the Kruskal-Wallis H test for independent samples, and the Spearman’s correlation analysis were conducted to examine the relationships between the variables. In summary, the study revealed statistically significant differences social and emotional competencies based on gender, but there were no discernible differences based on age. Furthermore, the results indicated a positive relationship between life satisfaction, social and emotional competencies, and academic performance. The findings of this study hold significant importance as they contribute to our understanding of the factors impacting the well-being of adolescents. Hence, in the current post-pandemic era, there is an even greater urgency to design and implement high-quality interventions centered around social and emotional learning in education, particularly from an early age.

Self Directed Learning Scale at University Context

This research was carried out to investigate a relationship between self-directedness, self-involvement, expressive language, self-assessment, language varieties, metacognitive skills, editing and problem solving, text processing, knowledge rehearsal, idea planning, goal oriented monitoring and evaluating, peer learning, feedback handling, interest enhancement, motivational self-talk, and emotional control and the main and forming factors of self-directedness, self-involvement, expressive language, self-assessment, language varieties, metacognitive skills, editing and problem solving, text processing, knowledge rehearsal, idea planning, goal oriented monitoring and evaluating, peer learning, feedback handling, interest enhancing, motivational self-talk, and emotional control of self directed learning. A convenience sample approach was used to recruit English majors from a range of State University of Yogyakarta. All participants were recruited intentionally, and that they were informed that they might leave the study at any moment either during collecting data. The participant criteria include second-year English major students from various State Universities of Yogyakarta. As the result of pearson correlation in this research, it was found that there was a substantial relationship between the variables examined in this research. Moreover, as the result of factor analysis in this research was found that from the 11 variables included in the research namely self involvement, expressive language, self assessment, language varieties, metacognitive skills, editing and problem solving, Cognition, Metacognition, Social Behavior, and Motivational Regulation, they can be grouped into two main factors. The implications of these findings lie in a deeper understanding of the underlying conceptual structure of self-directed learning in a university context. With the identification of the key factors emerging from these variables, a more focused approach can be developed to enhance students' self-directed learning. This can also aid in the development of more precise and measurable assessment instruments to gauge progress in crucial aspects of self-directed learning. Thus, the implications of these findings can enrich teaching and learning practices in higher education settings.

A Model for Estimating the Economic Costs of Computer Vision Systems That Use Deep Learning

Deep learning, the most important subfield of machine learning and artificial intelligence (AI) over the last decade, is considered one of the fundamental technologies underpinning the Fourth Industrial Revolution. But despite its record-breaking history, deep learning’s enormous appetite for compute and data means that sometimes it can be too costly to practically use. In this paper, we connect technical insights from deep learning scaling laws and transfer learning with the economics of IT to propose a framework for estimating the cost of deep learning computer vision systems to achieve a desired level of accuracy. Our tool can be of practical use to AI practitioners in industry or academia to guide investment decisions.

Integration of 21st Century Skills into Secondary School English Classes and the Challenges faced by Teachers

The aim of this study is to examine the utilization of 21st century skills by secondary school English language teachers and to investigate whether their background has a role in using these skills. The study also aims to shed light on the challenges teachers face when integrating these skills into their teaching practices. A mixed-methods research design, which incorporates the scale and interviews, was used to accomplish the aims of the study. The data were obtained online using 21st Century Teaching and Learning scale developed by Hixson, Ravitz, and Whisman (2012) and semi-structured interviews. A total of 119 teachers were reached using convenience and snowball sampling methods, with 26 of them participating in the interviews. The quantitative findings of the study showed that teachers used 21st century skills approximately once or three times a month, and the most used skill was using technology as a tool for learning, while local connections were the least. According to the t-test results, a significant difference was found in the use of these skills between private and public school teachers, with private school teachers employing these skills more frequently than their public school counterparts. Furthermore, it was revealed that teachers who received 21st century skills training integrated some of the 21st century skills into their lessons more often than those who did not. In addition, it was found that years of experience played a role in the implementation of these skills. According to the post-hoc test, less experienced teachers integrated 21st century skills more frequently than more experienced teachers. On the other hand, the teachers’ educational backgrounds did not show any significant difference in using these skills. According to the findings obtained from the content analysis of the interviews, the lack of qualified in-per service training on 21st century skills, poor curricula, lack of required materials and infrastructure, and unsupportive attitudes of the administrators were the challenges encountered by teachers.

A Preliminary Trial of an Early Surveillance Program for Autism and Developmental Delays within General Practices

AbstractThere are inequities in engagement with established early childhood developmental surveillance programs, eclipsing disadvantaged families. The current study sought to address this by dovetailing developmental surveillance with immunization visits and other opportunistic contacts with children at general practices). While 53 General Practices were recruited, significant COVID-19 disruptions resulted in only 81 children being screened (both parent-administered and GP completed). Of the 81 children, 11 screened positive and all of them along with 5% of screen negatives (i.e. 4 children) received clinician-administered reference-standard assessment for autism and developmental delay (DD) using Autism Diagnostic Observation Schedule (ADOS), Autism Diagnostic Interview Schedule –Revised (ADI-R), and Mullen Scales of Early Learning (MSEL). All children found by reference-standard assessment to have probable autism and/or DD had screened positive during the screening process, and 90.9% of children who screened positive were found by reference-standard assessment to have probable DD or autism. The findings provide early evidence for the feasibility and usefulness of parent completed and GP administered developmental measures during opportunistic contacts with GPs as a promising method to facilitate early identification of DD or autism.

Maternal preconception and prenatal stressful life events in association with child neurodevelopmental outcome in MARBLES: A high familial likelihood cohort

BackgroundPrenatal stressful life events (SLEs) have been inconsistently associated with autism spectrum disorder (ASD). Mothers who are already raising a child with ASD could experience compounding effects of prenatal SLEs. This study prospectively examined prenatal SLEs in association with child neurodevelopmental outcomes in a high familial likelihood cohort. MethodsParticipants were 317 mother-child pairs from the Markers of Autism Risk in Babies: Learning Early Signs (MARBLES) Study, where pregnant women have previously had at least one other child with ASD. Mothers were interviewed during and at the end of pregnancy about whether they had experienced any of 7 SLE categories relating to finance, marriage, death, and more.Child neurodevelopment at three years old was classified as typically developing (TD), Non-TD, or ASD using an algorithm applied to Autism Diagnostic Observation Schedule (ADOS) and the Mullen Scales of Early Learning (MSEL) scores. Relative risk ratios (RRR) with TD as the reference outcome were estimated using multinomial logistic regression. ResultsExperiencing legal problems was significantly associated with an increased relative risk of child Non-TD (RRR 3.75; 95% CI: 1.15, 12.22). However, this finding was based on a small sample size (n = 6) and should be interpreted with caution. All other associations with Non-TD and ASD were non-significant. ConclusionsFindings agree with previous literature suggesting prenatal SLEs might not increase likelihood for ASD and most were not associated with Non-TD. Future studies measuring perceived stress or stress biomarkers are warranted to further understand the true association of prenatal stress and likelihood of ASD.

Virtual Reality Simulation in a Health Assessment Laboratory Course: A Mixed-methods Explanatory Study Examining Student Satisfaction and Self-confidence.

The purpose of this mixed-methods study was to examine the relationship between virtual reality simulation (VRS) and student satisfaction and self-confidence in a health assessment laboratory course. Second-year students (n=37) completed a postoperative respiratory distress scenario using Elsevier's Simulation Learning System with Virtual Reality. All participants completed the Satisfaction and Self-Confidence in Learning Scale; a subset participated in 1:1 semistructured interviews. Satisfaction and self-confidence scores were strongly correlated. VRS experiences of fidelity, communication confidence and competence, learning with peers, integrated learning and critical thinking, and a safe space to learn were related to students' satisfaction and self-confidence. VRS experiences are correlated with high student satisfaction and self-confidence.

Scalable Learning for Spatiotemporal Mean Field Games Using Physics-Informed Neural Operator

This paper proposes a scalable learning framework to solve a system of coupled forward–backward partial differential equations (PDEs) arising from mean field games (MFGs). The MFG system incorporates a forward PDE to model the propagation of population dynamics and a backward PDE for a representative agent’s optimal control. Existing work mainly focus on solving the mean field game equilibrium (MFE) of the MFG system when given fixed boundary conditions, including the initial population state and terminal cost. To obtain MFE efficiently, particularly when the initial population density and terminal cost vary, we utilize a physics-informed neural operator (PINO) to tackle the forward–backward PDEs. A learning algorithm is devised and its performance is evaluated on one application domain, which is the autonomous driving velocity control. Numerical experiments show that our method can obtain the MFE accurately when given different initial distributions of vehicles. The PINO exhibits both memory efficiency and generalization capabilities compared to physics-informed neural networks (PINNs).

Enhancing Critical Digital Literacy of Preservice Preschool Teachers through Service Learning: The Moderator of Online Social Capital

This research delves into the examination of the correlation between service learning and critical digital literacy among preservice preschool teachers in Taiwan, with a particular emphasis on the role of online social capital. The survey took place in Taiwan with preservice preschool teachers who willingly completed a questionnaire. Initially, there were 416 data samples for further statistical analysis. This study utilizes literature reviews and theoretical reflections to examine the observed variables and factors in the “Service Learning and Critical Digital Literacy Scales” (SLCDL) questionnaire. To assess these aspects, a Chinese questionnaire is used, covering “service learning”, “critical digital literacy”, and “online social capital”. Using partial least squares analysis, researchers investigate the intricate interplay of online social capital in shaping the nexus between service learning experiences and the advance of critical digital literacy competencies. These results showed that service learning increased critical digital literacy among preservice preschool teachers, and online social capital played a mediating role in this relationship between service learning and critical digital literacy. We should actively encourage preservice preschool teachers to increase their critical awareness by understanding vulnerability and experiencing reality from the perspective of community partners. In addition, we need to provide more service learning opportunities that incorporate online social capital to enhance their critical digital literacy.