Background: Children who face difficulties in gross motor skill development may withdraw from physical activities, experience low self-esteem, and suffer from social anxiety. Physical education plays a vital role in fostering gross motor development, especially when delivered through enjoyable and engaging activities such as fun games. Objectives: This study aimed to investigate the impact of fun game–based learning on the development of gross motor skills in early primary school children. Methods: The study employed a quasi-experimental design with a non-equivalent control group. A total of 36 second-grade students from SDIT Mutiara Hati in Malang participated in this study. Participants were assigned to one of three groups: a control group, a group-based fun games intervention, and an individual-based fun games intervention. The interventions were implemented three times a week for 30 minutes over a period of seven weeks. Gross motor skills were measured before and after the intervention using the Test of Gross Motor Development–Third Edition (TGMD-3), a reliable and validated instrument. Data were analyzed using homogeneity and normality tests, paired-sample t-tests, one-way ANOVA, and Tukey's HSD post hoc tests, with a significance level set at p < 0.05 (SPSS version 25). Results: Both the individual and group fun game–based learning interventions produced significant improvements in gross motor skills compared with the control group (p < 0.05). Moreover, a significant difference was found between the two intervention types, indicating that the mode of fun game delivery influences outcomes (p < 0.05). Conclusions: Fun game–based learning, whether delivered individually or in groups, effectively enhances gross motor skills among early primary school children. Additionally, individual fun game–based learning demonstrated a significantly greater improvement compared to group-based learning.
Ahmad Muttaqin Darussalam, Sugiharto Sugiharto, Sapto Adi
A math teacher uses a remedial education intervention to help one student with a counting dyscalculia problem. Dyscalculia is a catchy term for a variety of problems with math that affect learning and performance. The author of this study created this new theory-driven intervention with the aim of identifying primary school teachers using reconnect learning to help students with the potential to experience dyscalculia learn to count and in this case the ability to count to 10 which will be seen to achieve the learning goal. which is desired. the author used a qualitative approach to identify elementary school teachers using reconnective learning to help students with the potential to experience dyscalculia learn to count. Interviews, class observations, and introspective diaries all contributed to the data set. The author conducted the research, which was conducted at a public elementary school in Gresik, East Java, Indonesia, conducted in Grade 1 with a total of 20 students. After initial screening using the Indonesian Dyscalculia instrument. Students with dyscalculia have learning problems in mathematics that are characterized by underlying difficulties with numerical representation and processing. They can have problems with basic arithmetic such as counting and recognizing numbers. Helping students with Dyscalculia succeed in mathematics through early treatment is a promising area of research. A shortage of instructional scaffolding that helps Dyscalculia students organize their learning process while also addressing cognitive deficiencies and arithmetic competency gaps remains. Pseudonym Mrs. Sinta (elementary school math teacher) and Riki (a student potentially at risk of Dyscalculia) are involved in the current investigation. The results showed that the recommended interventions helped students become more proficient in calculations. Since most of the literature on remedial interventions for students with disabilities key significance to education is the focus of this research, an approach that shifts the emphasis from instructional tactics (devices, tools, interactions) to students' cognitive skills, an intervention that shows promise for helping students who are at risk of falling behind. in cognitive numbers. This study provides a solution to the posed question by showing how primary school teacher might use Reconnecting Learning to aid kids at risk for dyscalculia in their pursuit of numeric literacy. Mrs. Sinta (a pseudonym) is an elementary school teacher who employs the Reconnecting Learning paradigm in her own education. Success in learning to count to ten was shown to be one of Reconnecting Learning's intended outcomes.
This study explored the interrelationship between Learning Style (LS) and AcademicAchievement (AA) of students (11-15 years old) enrolled in schools following the SamacheerKalvi syllabus (Unified Education Board of the state of Tamil Nadu) among a total of 3026 schoolgoing children from the four zones of Coimbatore in the state of Tamil Nadu during November2021 to March 2022. A cross-sectional research design was used. Misra’s Learning Style Inventory(LSI) was administered to define the Learning Style of the children. AA was analysed using theiryearly report card for five major exams. Subject–wise average marks scored (Tamil, English,Mathematics, Science, and Social Science) were computed and graded. Children’s learning stylewas found to be significantly associated with all the subjects except the second language (Tamil).The enactive reproducing style had a positive impact on their academic achievement in English,Mathematics, and Science. Verbal constructive style affected their academic achievementnegatively. Figural constructive and figural reproducing learning styles were found to have apositive impact on Mathematics, Science, and Social Science.
Student learning outcomes are influenced by the PBL approach assisted by Nearpod media. This research methodology is quantitative with an experimental strategy. This study used a nonequivalent control group design pattern in a quasi-experimental research approach. Researchers chose this design in order to use Nearpod media to implement PBL principles. There are two groups, namely the control group that uses the learning model and classroom media as a comparison, and the experimental group that uses Nearpod media as a complement to the PBL paradigm. 50 fifth-grade children from Citrodiwangsan 2 Lumajang Elementary School made up the study's population. They were divided into two classes. There are 25 pupils in class 5A and 25 students in class 5B. Probability sampling combined with random sampling was the method used for sampling in this investigation. The three phases of the research process were the planning phase, the research implementation phase, and the research completion phase. Tests, observations, documentation, and interviews were the approaches used to acquire data for this study. Using the SPSS Version 26 software, the data analysis methods employed in this study included t-tests, homogeneity tests, and normality tests. The Kolmogorov-Smirnov test was used to perform the normalcy test. To ascertain the extent to which the PBL paradigm, aided by Nearpod media, impacted the Civics learning outcomes of grade V students at SD Citrodiwangsan 2 Lumajang, the Shomogeneity test using Leven's statistics, and the t-test employed the independent sample t-test.
BACKGROUND: Dental anxiety (DA) has an impact on the quality of dental treatment and may have long-lasting implications for children. A recent study introducing experiential learning (EL) into children's oral health promotion resulted in better oral hygiene. The purpose of the study is to evaluate whether EL can reduce children's DA. METHODS: In September 2018, we recruited 988 children aged 7-8 years from 24 classes to participate in a cluster-randomized trial. Classes were randomly assigned to EL (in which children received a lively presentation on oral health and participated in a role play in a simulated dental clinic in the classroom) or the Tell-Show-Do (TSD) group (in which children received a conventional TSD behavior management). The primary outcome was the prevalence of high DA after the procedure of pit and fissure sealant (PFS), assessed by a modified Children's Fear Survey Schedule-Dental Subscale. Secondary outcomes were changes in blood pressures (BP) and pulse rates (PR) before and after the PFS procedure. The intervention effects were estimated by means of mixed effect models, which included covariates of gender and school (and baseline value for BP and PR only), and a random cluster effect. RESULTS: In 396 children of the EL group who received the PFS treatment, the prevalence of high DA (score ≥ 38) was 18.5%, compared with 24.3% in 391 children of the TSD group (OR = 0.65; 95% confidence interval, 0.46-0.93; P = 0.019). The increases in BP and PR after the PFS were also significantly less in the EL group. CONCLUSION: School-based experiential learning intervention before a dental visit is feasible and effective in reducing children's dental anxiety during PFS. TRIAL REGISTRATION: The trial was registered in Chinese Clinical Trial Registry on 5 January 2020 (No.: ChiCTR2000028878 , retrospectively registered).
ABSTRACT: Current automated pain assessment methods only focus on infants or youth. They are less practical because the children who suffer from postoperative pain in clinical scenarios are in a wider range of ages. In this article, we present a large-scale Clinical Pain Expression of Children (CPEC) dataset for postoperative pain assessment in children. It contains 4104 preoperative videos and 4865 postoperative videos of 4104 children (from 0 to 14 years of age), which are collected from January 2020 to December 2020 in Anhui Provincial Children's Hospital. Moreover, inspired by the dramatic successful applications of deep learning in medical image analysis and emotion recognition, we develop a novel deep learning-based framework to automatically assess postoperative pain according to the facial expression of children, namely Children Pain Assessment Neural Network (CPANN). We train and evaluate the CPANN with the CPEC dataset. The performance of the framework is measured by accuracy and macro-F1 score metrics. The CPANN achieves 82.1% accuracy and 73.9% macro-F1 score on the testing set of CPEC. The CPANN is faster, more convenient, and more objective compared with using pain scales according to the specific type of pain or children's condition. This study demonstrates the effectiveness of deep learning-based method for automated pain assessment in children.
BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a considerably common childhood-onset neurodevelopmental disorder, often associated with socio-behavioral and academic difficulties. There is an increased risk for development of a range of future problems such as psychiatric disorders, difficulties in employment, and relationships. The aim of this study was to know the prevalence and determinants of ADHD among primary school children in district Dehradun and to assess the learning difficulties and classroom behavior in these students. MATERIALS AND METHODS: In this cross-sectional study, overall, 228 students (aged 6–12 years) studying in a primary school were assessed for ADHD after seeking the written informed consent from their parents. The data were analyzed using Excel sheet and SPSS software (22.0 version). For all qualitative measures, frequency and percentages were calculated, and for quantitative measures, mean and standard deviation were calculated. For analysis of categorical values, Chi-square test was used. P < 0.05 was considered statistically significant. RESULTS: The prevalence of ADHD was found to be 11.8% based on the teacher tool only and 1.75% based on the parent and teacher tools combined. ADHD was found to be significantly more in males. Inattention was the most prevalent subtype of ADHD, and children screened positive for ADHD had significant learning difficulties at various levels. CONCLUSION: The possibility of ADHD in students with academic difficulties should not be ignored as children with ADHD usually face significant problems at school such as learning difficulties and have been shown to be at increased risk for a broad range of negative outcomes. Early identification and treatment of ADHD can significantly reduce the rates of some of these poor outcomes. Screening these children in the early years will help the parents, children, teachers, and community at large.
Gurpreet Kaur Chawla, Ruchi Juyal, Deep Shikha et al.
BACKGROUND: Electronic medical records provide large-scale real-world clinical data for use in developing clinical decision systems. However, sophisticated methodology and analytical skills are required to handle the large-scale datasets necessary for the optimisation of prediction accuracy. Myopia is a common cause of vision loss. Current approaches to control myopia progression are effective but have significant side effects. Therefore, identifying those at greatest risk who should undergo targeted therapy is of great clinical importance. The objective of this study was to apply big data and machine learning technology to develop an algorithm that can predict the onset of high myopia, at specific future time points, among Chinese school-aged children. METHODS AND FINDINGS: Real-world clinical refraction data were derived from electronic medical record systems in 8 ophthalmic centres from January 1, 2005, to December 30, 2015. The variables of age, spherical equivalent (SE), and annual progression rate were used to develop an algorithm to predict SE and onset of high myopia (SE ≤ -6.0 dioptres) up to 10 years in the future. Random forest machine learning was used for algorithm training and validation. Electronic medical records from the Zhongshan Ophthalmic Centre (a major tertiary ophthalmic centre in China) were used as the training set. Ten-fold cross-validation and out-of-bag (OOB) methods were applied for internal validation. The remaining 7 independent datasets were used for external validation. Two population-based datasets, which had no participant overlap with the ophthalmic-centre-based datasets, were used for multi-resource validation testing. The main outcomes and measures were the area under the curve (AUC) values for predicting the onset of high myopia over 10 years and the presence of high myopia at 18 years of age. In total, 687,063 multiple visit records (≥3 records) of 129,242 individuals in the ophthalmic-centre-based electronic medical record databases and 17,113 follow-up records of 3,215 participants in population-based cohorts were included in the analysis. Our algorithm accurately predicted the presence of high myopia in internal validation (the AUC ranged from 0.903 to 0.986 for 3 years, 0.875 to 0.901 for 5 years, and 0.852 to 0.888 for 8 years), external validation (the AUC ranged from 0.874 to 0.976 for 3 years, 0.847 to 0.921 for 5 years, and 0.802 to 0.886 for 8 years), and multi-resource testing (the AUC ranged from 0.752 to 0.869 for 4 years). With respect to the prediction of high myopia development by 18 years of age, as a surrogate of high myopia in adulthood, the algorithm provided clinically acceptable accuracy over 3 years (the AUC ranged from 0.940 to 0.985), 5 years (the AUC ranged from 0.856 to 0.901), and even 8 years (the AUC ranged from 0.801 to 0.837). Meanwhile, our algorithm achieved clinically acceptable prediction of the actual refraction values at future time points, which is supported by the regressive performance and calibration curves. Although the algorithm achieved balanced and robust performance, concerns about the compromised quality of real-world clinical data and over-fitting issues should be cautiously considered. CONCLUSIONS: To our knowledge, this study, for the first time, used large-scale data collected from electronic health records to demonstrate the contribution of big data and machine learning approaches to improved prediction of myopia prognosis in Chinese school-aged children. This work provides evidence for transforming clinical practice, health policy-making, and precise individualised interventions regarding the practical control of school-aged myopia.
Web-based learning, defined as the purposeful use of internet technology to impart knowledge, has gained attention as an educational tool in developing countries. However, limited evidence exists on how children with learning disabilities in impoverished regions adopt such methods. This study aims to identify the variables influencing the adoption of web-based learning among children with learning disabilities, focusing on performance expectancy, effort expectancy, social influence, and training. The research utilized survey questionnaires to assess these factors among 196 children with learning disabilities enrolled in mathematics and Arabic classes in Jordan's Balqa governorate. Results revealed a positive relationship between behavioral intention and the acceptance of web-based learning systems, highlighting the critical role of the identified variables. The findings underscore the importance of tailoring web-based learning systems to the needs of children with learning disabilities, offering actionable insights for system developers and educators in similar contexts. Recommendations include prioritizing user-friendly designs, targeted training programs, and strategies to enhance social and performance-related perceptions to improve learning outcomes. Keywords: Effort expectancy; learning disabilities; performance expectancy; social influence; training; web-based learning
Suleiman D. Al-Ahmad, Ali Alawammreh, Abdallah Mishael Obeidat et al.
This study was motivated by the decline in student learning outcomes in the odd semester of the 2022/2023 school year which was caused by students paying less attention to the explanation and material from the teacher during the learning process. Such as not doing assignments on time, often chatting alone when the teacher explains, lack of interest in learning, and there are some children who have low learning outcomes. Therefore, it is necessary to instill discipline in learning since childhood, because it will help children control themselves in the formation of self-awareness in learning without an element of compulsion. This study aims to determine the relationship between learning discipline and students' interest in learning. The research method used is a quantitative method with a correlational approach that uses ex post facto research. The sample in the study was class III students with a total of 14 people, whose sampling used the saturated sample method because all students in class III were sampled in the study. Data collection was carried out using questionnaire and documentation techniques. The results showed that: 1) There is a significant relationship between learning discipline and student learning outcomes with a Thitung value of 8.131. 2) There is a significant relationship between learning discipline and student learning outcomes with a Thitung of 3.459. 3). There is a significant relationship simultaneously between learning discipline and learning interest on student learning outcomes with a T-count of 6.698.
