Educational Practice Research Articles

Impact of Artificial Intelligence on Islamic Education: Effectiveness, Innovation, and Socio Cultural Influence

Objective: This study discusses the role of AI in Islamic education, from the aspects of effectiveness, innovation in learning, and socio-culture. This study includes how artificial intelligence allows better learning for the students, innovative teaching methods, and social and cultural change in Islamic education.Methods: This research is a meta-analysis that aims to synthesize data from several studies related to the application of AI in Islamic education. Cohen’s d was used to compute the effect size quantifying the effect of AI on learning deviations learning effectiveness, learning innovation, and learning socio-culture.Results: The results show that AI has moderate but significant impact on Islamic education. The most influential factors are socio-cultural factors (the influences of social factors) and recent educational innovative reforms (innovation), followed by learning effectiveness (focusing on adaptive learning and the connectedness of the learning environment). The findings provide evidence that the incorporation of AI is beneficial for enhancing learning outcomes and facilitating cultural and social transformation in the context of Islamic education.Novelty: This research sheds light on the effects that AI can have on Islamic education, and presents a unique take on the issue, focusing on improving learning outcomes, and capturing innovation in the socio-cultural context. It also calls for more research into how external forces access to technology, teacher involvement, community buy-in can shape this work.Theory and Policy Implications: The results affirm the importance of integrating AI into Islamic education and recommend that policymakers focus on AI-based projects that align with local cultural contexts and technological capacity. It is recommended in the study to customise the operation of AI-based learning solutions according to general Islamic educational values and the needs of students. Additional studies are needed to capture the broader ramifications of AI on educational policies and practices in different socio-cultural contexts.

Perspectives of Early Childhood Education Teachers in Kenya and Nepal Regarding Pedagogical Practices Essential to Meeting Learners’ Needs

ABSTRACT This phenomenological collaborative study (Creswell, 2013) examined the perspectives of early childhood education teachers (n = 16) regarding educational practices and policies essential for preparing learners for a globalized 21st century. While findings showed widespread opposition of current educational policies, particularly those prioritizing neoliberal economic goals through high-stakes standardized testing, participants opposed commodification of education. Instead, they supported decolonizing and culturally appropriate education (Adebisi, 2016), designed to equip learners with the skills necessary to thrive in the globalized 21st century. Among other preferred practices, participants embraced active, learner-centered, holistic, and locally contextualized education. Resultingly, this study recommends strongly replacing of the current decontextualized neoliberal-based education systems in Kenya and Nepal with context-based educational practices.

Bridging the Gap: Exploring Practices and Challenges for Including Children with Disabilities in Mainstream Classroom

This study aimed to explore the perception of students with disability towards the existing practice of inclusive education in mainstream schools. The qualitative research design along with interpretative phenomenological approach was employed in this study. Four students with disabilities including physical, deaf and children with visual impairment were purposively selected from integrated school located in Kathmandu Valley. In-depth interview was taken through semi-structured interview guidelines. The thematic analysis technique was applied to generate findings. The themes were discussed by linking with prospective and literature. The findings reported as setting disable friendly infrastructure, professional development opportunity for teachers, technology-based instruction and teacher’s collaboration are essential strategies for inclusion. Meaningful inclusive education practices maintain a supportive and equitable learning environment for all types of children including those with disabilities. To implement inclusive practices in the classroom, administrative hurdles, infrastructure barriers, technological barriers, environmental barriers and legislative barriers are the major challenges in practising equity strategies in the classroom. The findings can contribute to set up effective practices for combating such challenges. By using the scope of the study, the policy maker, education planners and teachers can level up appropriate strategies for increasing the access of children with disability in education.

Analysis of Mining Equipment Procurement Plan and Logistics Path Optimization Based on QUBO Model

By analyzing the configuration and operation plan of mining equipment, this paper establishes a linear programming model and converts it into the corresponding quadratic unconstrained binary optimization (QUBO) form. Based on this, the simulated annealing solver built-in in Kaiwu SDK and CIM simulator are used to study the configuration and operation plan of mining equipment. For work one: it is required to provide a procurement plan that maximizes profits within the budget range, that is, to determine the required excavator models and corresponding quantities. This problem is based on the premise of not considering the service life of excavators, with the maximum value of the product of the four excavator models and their corresponding long-term profits and quantities as the objective function, and with the constraints of start-up capital budget and excavator type, a 0-1 integer programming model is established. By using the decision variable of the model as a 0-1 variable and the constraint as an inequality constraint, the constraint is then transformed into the corresponding Hamiltonian operator, and the penalty term coefficient P is introduced and added to the objective function, thereby transforming it into QUBO form. Due to the low complexity and linearity of the model, the Kaiwu SDK's built-in simulated annealing solver and CIM simulator were used to solve the problem and obtain the final maximum profit and procurement plan. For work two: compared to work one, the condition of equipment lifespan of 5 years has been added, and it is required to plan the model and quantity of excavators that need to be purchased, while providing the matching relationship between excavators and mining trucks. This problem requires consideration of various cost conditions, with the difference between revenue and cost within five years as the objective function, and matching constraints, quantity constraints, and budget constraints as constraints, ultimately constructing a general linear programming model. By using inequality constraint relationships, the relaxation variable s in binary expression is introduced to express the constraint term, thereby transforming it into QUBO form. Afterwards, Kaiwu SDK was used to solve the procurement plan and obtain the matching relationship between excavators and mining trucks. For work three: Based on work two, the number of devices has been increased. For the constructed linear programming model, it can be transformed into a QUBO model or even a subQUBO model. Firstly, preprocess the data and use Spearman correlation analysis to determine the degree of correlation between the data, visualizing the data. For the constructed linear programming model, compared to problem two, only parameter variables were added, and the constraint conditions were consistent with problem two. A relaxation variable s was introduced to construct a constraint term, which was then transformed into a QUBO model. Combined with classical calculations, the subQUBO method was used. Finally, the procurement plan was obtained through Kaiwu SDK and a new matching relationship between excavators and mining trucks was provided. **************** ACKNOWLEDGEMENTS**************** This work is supported by ministry of education industry-university cooperative education project (Grant No.: 231106441092432), the research and practice of integrating "curriculum thought and politics" into the whole process of graduation design of Mechanical engineering major: (Grant. No.: 30120300100-23-yb-jgkt03), research on the integration mechanism of "course-training-competition-creation-production" for innovation and entrepreneurship of mechanical engineering majors in applied local universities (Grant. No.: CXKT202405), Mechanical manufacturing equipment design school-level "gold class" construction project (Grant. No.: 30120324001).

Interference and precursor signal analysis based on random forest and improved logistic regression model

Coal is the main energy and industrial raw material in China. In order to prevent the risks of coal mining and ensure the safety and efficiency of coal mining, this paper established random forest model, ADF and MK test model and logistic regression model, and used autocorrelation function algorithm, Fourier transform and sliding window transformation of time series data to analyze and optimize the characteristics of interference signals and precursor characteristics. For the first work, the huge data is preprocessed, tested, and outliers are removed, and the time characteristics are taken to aggregate and classify the data. For work (1.1), data parameters were sorted out, Fourier transform prediction signal model was initially established, and characteristic values were extracted by wavelet transform. Finally, autocorrelation function algorithm was used to optimize and analyze the results. The final results were shown in Table 4 for the data characteristics of electromagnetic radiation (EMR) interference signals and Table 5 for the interference signals of acoustic propagation signals. For work (1.2), a random forest model is established, with sliding window transformation of time series data, window size is specified, boundary processing mode is specified, and label value is defined as interference and normal. The data set is divided into training set and test set in the way of eighty-two allocation. After AE training, there are three stages of training. Finally, random forest algorithm is used to calculate the electromagnetic radiation interference signal interval. For work (2.1), the model and algorithm of work 1 are used to identify the trend characteristics of the data before the occurrence of electromagnetic radiation and acoustic emission signals, and the signal data are judged to have a "slightly rising" trend. The statistical values are compared by KS trend test, and the trend characteristics of normal and precursor signals are calculated by using the autocorrelation function algorithm. A trend feature table is obtained for the precursory feature data of electromagnetic radiation and acoustic propagation signal. For work (2.2), Augmented dickey-Fuller and MK test models of the system were established. For work 3, a logistic regression model is established to predict the probability of precursor feature data appearing at the last moment of multiple time periods. By using maximum likelihood estimation to train model parameters, the characteristics of the last data collection moment of each time period are predicted, and the probability of precursor feature appearing at each moment is output. As shown in Table 14, the probability of precursor features appearing at the time when the data of multi-classification logistic regression is located is obtained. **************** ACKNOWLEDGEMENTS**************** This work is supported by ministry of education industry-university cooperative education project (Grant No.: 231106441092432), the research and practice of integrating "curriculum thought and politics" into the whole process of graduation design of Mechanical engineering major: (Grant. No.: 30120300100-23-yb-jgkt03), research on the integration mechanism of "course-training-competition-creation-production" for innovation and entrepreneurship of mechanical engineering majors in applied local universities (Grant. No.: CXKT202405), Mechanical manufacturing equipment design school-level "gold class" construction project (Grant. No.: 30120324001).

Research on Cargo Volume Prediction and Personnel Scheduling in Logistics Centers

With the rise of e-commerce logistics networks, cargo volume prediction in sorting centers has become increasingly important and a key research topic. The aim of this study is to predict the daily cargo volume and daily cargo volume of 57 sorting centers in the future, in order to optimize the human resource allocation of logistics network sorting centers. LSTM model, ARIMA model, and integer programming model based on genetic algorithm were established according to the different problems. Regarding problem one: In the task of predicting daily and hourly cargo volume for the next 30 days, the ARIMA model is used. The ARIMA model has shown advantages in short-term forecasting and has been applied to predict the hourly cargo volume of each sorting center within 30 days. By combining these two models, the final prediction data can be obtained. Regarding problem two: Draw a directed graph to visually display the data and provide visual support for subsequent analysis. Based on the average transportation volume of sorting centers and changes in transportation routes over the past 90 days, use a mathematical model to calculate the rate of change in cargo volume after changing transportation routes. For sorting centers that have not been affected, sum the rate of change and calculate the average. Finally, use mathematical models to calculate the revised predicted daily and hourly cargo volumes. Regarding problem three: constructing an integer linear programming model based on genetic algorithm, whose decision variables involve the attendance of formal and temporary workers in different shifts of each sorting center. In the model construction, strict constraints were set to ensure the completion of cargo volume processing, prioritize the use of formal workers, and maintain a balance of actual hourly labor efficiency. Use a linear programming solver to accurately calculate the optimal attendance allocation for each shift in each sorting center. Regarding problem four: Taking SC1 sorting center as an example, and based on the prediction results of problem two, a shift attendance plan model for formal and temporary workers was constructed. On this basis, this study aims to minimize the total number of formal and temporary workers as the objective function, and considers the constraint conditions that the attendance rate of each formal worker does not exceed 85% and the continuous attendance days do not exceed 7 days. I wrote code to solve the model and successfully obtained an optimized scheduling plan. **************** ACKNOWLEDGEMENTS**************** This work is supported by ministry of education industry-university cooperative education project (Grant No.: 231106441092432), the research and practice of integrating "curriculum thought and politics" into the whole process of graduation design of Mechanical engineering major: (Grant. No.: 30120300100-23-yb-jgkt03), research on the integration mechanism of "course-training-competition-creation-production" for innovation and entrepreneurship of mechanical engineering majors in applied local universities (Grant. No.: CXKT202405), Mechanical manufacturing equipment design school-level "gold class" construction project (Grant. No.: 30120324001).

Navigating inclusive education in mainstream primary schools: a phenomenological study of teachers’ perceptions and experiences

ABSTRACT This study explored primary school teachers’ perceptions and experiences of inclusive education within a mainstream setting in Southern England. Using a phenomenological approach, semi-structured interviews were conducted with seven teachers from diverse career stages and roles within a single primary school. Thematic analysis revealed four key themes: (1) An Individualised Approach, emphasising personalised teaching strategies; (2) Know Your Limits, highlighting systemic constraints; (3) It's Who We Are, underscoring the importance of school culture; and (4) Experience Builds Knowledge, reflecting the role of professional growth in inclusive practice. Findings indicate that teachers’ implementation of inclusive education is shaped by a complex interplay of individual approaches, systemic limitations, school culture, and professional experience. The study contributes to the field by providing a nuanced understanding of teachers’ lived experiences, interpreted through multiple theoretical lenses including Social-Ecological Systems Theory and Critical Theory. Implications span classroom practice, school leadership, policy development, and teacher education, emphasising the need for a holistic, ecosystem-wide approach to inclusive education. The research highlights the importance of ongoing professional development, supportive school cultures, and policy alignment in fostering effective inclusive practices. Limitations include the small sample size and single-school focus, suggesting avenues for future larger-scale and longitudinal research.

Learning to engage with the »other«? – postfoundational perspectives on affects and emotions in argumentation trainings against right-wing populism

ABSTRACT In the context of the rise of right-wing populism, new debates on democratic education have emerged which focus on the role of affect. The paper puts forth a postfoundational perspective on affects and emotion, proposing an analysis of how democratic education practices mobilize certain feelings. In the empirical analysis of argumentation trainings in the context of higher education, it is demonstrated that the observed practices have ambivalent effects. On the one hand, participants demonstrate motivation and commitment to argue for their own positions and to passionately oppose populist positions in public discourse. Conversely, this motivation operates, at least in part, through a process of ‘othering,’ which transforms individuals with right-wing populist worldviews, at least in part, into obstinate individuals in need of moralization.

Activities, Resources, and Learning Environment: A Case Study of Science Learning at Sekolah Alam

This study examines science education activities, resources, and the learning environment at Sekolah Alam Al Fath Jambi Junior High School. Using a case study approach, the research involves direct observations, interviews with teachers and students, and learning materials analysis to understand the impact of various learning methods on student outcomes. The findings highlight that science learning activities align with the Sekolah Alam concept, emphasizing project-based, experiential, nature-based, and collaborative approaches. Learning occurs inside and outside the classroom, utilizing the natural surroundings for exploration and field experiments. Resources include school gardens, outbound areas, natural materials, and collaborations with local experts. The learning environment, assessed through the WIHIC questionnaire, supports student success through dimensions like cohesiveness, teacher support, involvement, task orientation, cooperation, equity, enjoyment, and academic efficacy. This study underscores the effectiveness of nature-integrated and experiential approaches in enhancing science learning outcomes and offers recommendations for advancing educational practices in similar settings.

The Obstacles and Paths of Family Education Concepts and Cognition to Promote the Development of Digital Education

The transformative growth of digital education has highlighted its potential to revolutionize learning, yet it faces notable challenges, particularly concerning the role of family education. Families are critical in supporting students in digital learning, but generational gaps, cultural attitudes, and cognitive lags often hinder the effective adoption of digital tools. This article explores the intersection of family education concepts and digital learning, emphasizing the obstacles families face. Through a comprehensive analysis, the study identifies key barriers, including extreme attitudes toward digital education and the cultural and generational gaps that limit parental engagement. It also evaluates the pivotal role of family involvement in aligning with modern educational demands. Based on these findings, the article proposes actionable strategies: increasing family awareness through training, fostering home-school collaboration, encouraging balanced use of traditional and digital methods, and developing policies that address socioeconomic barriers. These approaches aim to bridge gaps in family education and promote equitable digital learning opportunities. By integrating family education practices with the changing requirements of digital education, this study emphasizes the need for family involvement in building a supportive and inclusive educational ecosystem.

Establishment of a rapid and quantitative method for detecting the range of infection exposure in preclinical dental education

BackgroundsSafe dental treatments that prevent nosocomial and cross-infections are essential for patients and dental workers. However, dental students sometimes pay inadequate attention to infection control, especially in preclinical practice, because of too much focus on technical training, such as the use of equipment, etc. The spread of infections such as SARS-CoV-2, antibiotic-resistant bacteria, and oral bacteria are sometimes lethal for medically compromised patients. Thus, the rapid and inexpensive detection system to detect and measure dental practice-related infection spread during preclinical treatment is highly desired for dental education. This study aimed to establish a method to quantify and visualize infected areas using dental phantoms for safe and effective preclinical dental practices.MethodsAt first, we developed artificial saliva as an in vitro study, including food-derived bacteria and fluorescence dye, which is safe for application to preclinical practice education. In vitro study, the correlation between adenosine triphosphate (ATP) levels and Lactobacillus colony numbers in yogurt was examined using the ATP fluorescent method, with colony counting on yogurt only and a mixture of yogurt and ultraviolet (UV)-sensitive hand lotion. The mixed liquid of yogurt and hand lotion was used as artificial saliva. Second, we used this artificial saliva in preclinical education. The degree of contamination of personal protective equipment and dental chairs in preclinical practice using this artificial saliva was determined using the ATP fluorescent method and measuring the luminescence areas among 10 dentists, 10 dental residents, and 10 fifth-grade dental students.ResultsATP levels and Lactobacillus colony numbers in yogurt were positively correlated with yogurt alone and a mixture of yogurt and UV-sensitive hand lotions (correlation coefficient ≒ 1). Preclinical education using a mixture of artificial saliva successfully quantified and visualized infectious areas and droplets, which revealed significant differences in ATP amounts in personal protective equipment among groups according to years of experience as dental practitioners (p < 0.05).ConclusionsAn education system for infection control constructed using artificial saliva containing Lactobacillus and a UV-sensitive fluorescent hand lotion quantified the infectious areas and degrees. Thus, this method is effective in preclinical practice using dental phantoms.

Exploring Physiotherapy Students’ Competencies in Clinical Setting Around the World: A Scoping Review

Clinical education is a fundamental component of physiotherapy entry-level education programs, with practice education being a core element. The aim of this scoping review is to identify and define the competencies of physiotherapy students in clinical settings. This review followed the five steps of the Arksey and O’Malley framework, employing a search strategy that utilized Mesh terms. Searches were performed in PubMed, CINAHL, Scopus, ERIC, WOS, and PsycINFO, with additional exploration of the grey literature. The inclusion criteria were defined using Peter’s concept: (population) physiotherapy students; (concept) competencies aligned with the WCPT educational framework; (context) clinical environment. A total of 1798 sources were identified, and 86 studies were finally selected. Studies originated from 14 countries, with the United States, Australia, and Canada being the most represented. Of the selected studies, 62 used specific tools to identify competencies. The “Clinical Performance Instrument” and the “Assessment of Physiotherapy Practice” were the most frequently used instruments and covered all of the World Physiotherapy competencies’ domains. “Clinical Competence” emerged as the most widely recognized and utilized term across countries. Among the WCPT domains, “Physiotherapy Assessment and Intervention”, “Ethical and Professional Practice”, and “Communication” were the most represented, whereas “Evidence-Based Practice” and “Quality Improvement” were the least mentioned.

Film production and screen media: HyFlex practice and adaptive pedagogies in tertiary-level film education

Film production and screen media: HyFlex practice and adaptive pedagogies in tertiary-level film education

Constructivist instructional approaches: A systematic review of evaluation‐based evidence for effectiveness

AbstractConstructivist instructional approaches have gained significant popularity in education as educators seek to create more engaging and effective learning environments. However, the effectiveness of these approaches in promoting student learning remains a subject of debate. This systematic review aims to synthesise existing evaluation‐based research on the effectiveness of constructivist approaches in improving student learning outcomes compared to traditional instructional methods, and to identify specific empirically proven effective constructivist approaches. Using standard review methodology, we searched ERIC, Education Research Complete, British Education Index, Social Science Citation Index, and Applied Social Sciences Index and Abstracts as sources of quasi‐ or true‐experimental educational studies published in the last 10 years (2014–2023). Inclusion/exclusion criteria were based on the PICO (population, intervention, comparison, outcome) framework and the year and language of publications. A total of 1315 studies were identified. Studies were screened by two independent reviewers who also extracted the data and accessed the study quality and risk of bias using the Joanna Briggs Institute (JBI) critical appraisal tool. Thirty‐two articles met the inclusion criteria. Content analysis was used to code, analyse and synthesise the texts. This review study identified seven broad instructional approaches with a wide range of specific implementation strategies, rooted in constructivist learning theory, that revealed significant improvements in the various domains of learning. In conclusion, there is sufficient empirical data to be able to state with certainty that these instructional approaches are proven alternatives to the traditional method. Implications for educators, curriculum planners and researchers are briefly discussed. Context and implicationsRationale for this study: Constructivist and process‐based learning approaches have been given more significance recently. Evidence‐informed practice requires practitioners and policy makers to integrate current best evidence with client context in order to provide meaningful and potentially effective services across a range of presenting problems. Systematic reviews are a crucial part of this process, providing practitioners and researchers with transparent, rigorous and informative syntheses of research in a given area. Hence, this systematic review is conducted with the purpose to identify empirically proven effective constructivist teaching‐learning approaches and implementation strategies that could be valuable input for curriculum planners and educators.Why the new findings matter: The findings from this systematic review are important in highlighting the most effective constructivist teaching‐learning approaches and showing important developments in the research area. As such, the findings can inform policy and practice for teacher education and professional development at national and international scales.Implications for educators, curriculum planners and researchers: Firstly, educators will benefit greatly by understanding the constructivist approach of teaching. By using the teaching‐learning strategies identified by this review study, educators can provide the necessary ground to increase students' motivation, academic achievement and academic vitality, as well as reduce their academic procrastination. Secondly, curriculum planners can incorporate these constructivist instructional strategies in curriculum planning and in the development and preparation of framework/guidelines for achievements of intended learning outcomes. Finally, the ideas and experiences in the examined articles would inspire educational researchers to explore further the potential of constructivist instructional methods focusing on unexplored areas identified and discussed by this review.

Feasibility Trial of a Technology-Delivered Intervention for Opioid Use Disorder Recovery Postpartum

This randomized feasibility trial aimed to 1) assess methodology for a subsequent efficacy trial and 2) examine the usability and acceptability of Project BETTER’s hybrid technology-delivered educational intervention for pregnant people receiving medication for opioid use disorder within a perinatal addiction treatment clinic. Participants were randomized to the technology-delivered educational intervention or standard practice control (brochure). Project BETTER’s intervention offers three modules (pregnancy-to-postpartum transition, Neonatal Opioid Withdrawal Syndrome, child welfare interactions) via Computerized Intervention Authoring System (CIAS 3.0). Inclusion criteria were: ≥18 years of age, <34 weeks pregnant, currently receiving medication for opioid use disorder (MOUD), and had engaged in care ≤10 weeks during their current pregnancy. Study visits included an online survey, brief interview, and medical record review. Mean perceived helpfulness scores were compared by study condition using independent samples t-test. The screening process identified 49 potential participants, n = 31 (63%) of whom were recruited. Twenty-nine participants were randomized (intervention: n = 16, control: n = 13). Participants (n = 29) were reproductive age [M = 30.0 years (SD = 4.4)], 66% white and 31% Black with a median estimated gestational age of 24 weeks. Most participants (69%) received buprenorphine. Study completion rate was 83%. Most participants completed study components remotely. Among participants in the intervention group, 56% completed at least one module. Participants perceived the intervention to be as helpful as the brochure (intervention: 5.28 ± 0.98, control: 5.39 ± 0.56, p = 0.387) and highly acceptable. With protocol modifications, scale up to a larger clinical trial is feasible and acceptable to pregnant people receiving MOUD.

SOCIO-DEMOGRAPHIC FACTORS ASSOCIATED WITH DIARRHEA IN CHILDREN UNDER 5 YEARS IN PESHAWAR

Childhood diarrhea is a leading cause of morbidity and mortality among children under five, particularly in low- and middle-income countries like Pakistan. This study investigates the socio-demographic factors associated with the prevalence of diarrhea in children under five years of age in Peshawar, with the aim of identifying key determinants and providing evidence-based recommendations for targeted public health interventions. A cross-sectional study design was employed, involving 300 households selected through simple random sampling from urban and rural areas of Peshawar. Data were collected between January and June 2024 using a structured questionnaire covering socio-demographic characteristics, sanitation practices, healthcare access, and child health history. The data were analyzed using SPSS version 25, with descriptive statistics summarizing the study population and chi-square tests assessing associations between socio-demographic factors and diarrhea incidence. The findings revealed that children aged 1-3 years were most affected, with significant associations between diarrhea prevalence and maternal education, household income, family size, and sanitation practices. Poor hand hygiene, untreated water sources, and inadequate toilet facilities were identified as key risk factors. Despite the use of oral rehydration salts (ORS) and rotavirus vaccinations, gaps in awareness about diarrhea prevention persisted, highlighting the need for community education programs. This study underscores the critical role of socio-demographic and environmental factors in shaping the burden of childhood diarrhea in Peshawar. The results emphasize the importance of integrated strategies, including improved access to clean water and sanitation, parental education, and strengthened healthcare services, to reduce the incidence of diarrhea and improve child health outcomes. These findings provide valuable insights for policymakers and healthcare practitioners aiming to address this pressing public health issue.

The Current State of STEM Education in the United States: Strengths and Shortcomings

STEM education (Science, Technology, Engineering, and Mathematics) has been revered for many decades for its potential to foster innovation, critical thinking, and problem-solving skills essential for the modern workforce. However, while the benefits of STEM are widely acknowledged, significant challenges remain in its implementation, particularly in addressing the needs of a diverse and evolving society. This paper explores both the advantages and the disadvantages of current STEM educational practices. Through a thorough review of existing research and empirical data, we identify key areas where STEM succeeds in providing baseline skills for a prolific STEM career, and also key areas where STEM education falls short, such as inclusivity, accessibility, and the integration of interdisciplinary approaches. We argue that for STEM to truly fulfill its purpose, it must undergo substantial improvements to better accommodate diverse populations and contemporary societal demands. Our findings suggest that a more holistic and equitable approach to STEM education is necessary, one that not only preserves disciplinary integrity but also promotes cultural relevance and broadens participation across all demographics. This research highlights and attempts to specify the urgent need for systemic changes to ensure that STEM education can effectively contribute to a more inclusive and fruitful society in the future.

Preliminary validation of two math screening tools to identify gifted students in grades 3–5 in Jordan

IntroductionEarly screening for mathematically gifted students (MGSs) in Jordan and other Arab countries is limited, posing challenges in identifying and providing appropriate educational services. This study evaluates the validity and reliability of the Arabiya Calculation Test and Math Curriculum-Based Measurement (M-CBM) as tools for effectively screening and supporting MGSs in inclusive education settings. These tools were developed based on the Jordanian curriculum and international assessment tools and require further validation for use in other Arabic-speaking countries.MethodsA quantitative research design was employed, using the Arabiya Calculation Test and M-CBM to assess 78 MGSs in grades 3, 4, and 5 across three schools in Jordan. The tools’ reliability and validity were evaluated, with findings specifically limited to these grades. Performance differences among students and correlations between the two measures were analyzed.ResultsThe findings demonstrated that both the Arabiya Calculation Test and M-CBM are valid and reliable tools for identifying MGSs. These tools effectively differentiated performance across grades 3, 4, and 5. In addition, the significant correlation between these two measures supported their validity in identifying gifted students.DiscussionThe results have important implications for educational practice and policy in Jordan and similar Arab countries. Accurate identification of gifted students may facilitate tailored instruction and enrichment programs, improving the experience of inclusive education. These assessment tools offer the potential to identify gifted students early and meet their needs within an inclusive school environment.

Romantic Competence and Courtship Skills: From the First Romantic Impulse to the Management of Mutuality.

When adolescents have their first romantic experiences and start to form couples for the first time, these are normative practices which provide them with company, support and intimacy. However, the protagonists can also find them stressful and, at times, complicated. Romantic competence (RC) consists of a set of individual and mutual skills which are used to facilitate our emotional and social lives. In this study, we aim to deepen our knowledge about how RC is used, and the patterns or profiles present in the use of these skills. 2,400 Spanish adolescents (47.7% girls) between the ages of 12 and 18 took part in the study. A confirmatory factor analysis divided RC into individual or mutual competences, and, using cluster analysis, established three clearly defined profiles to describe the protagonists: ineffective in procedural and mutual management skills; ineffective in procedural skills and competent in mutual management skills; and competent in procedural and mutual management skills. The main discriminating factors for defining these profiles were age and romantic experience. The results show that older adolescents with more romantic experience perceive themselves as being more skilled in both individual and mutual competences, and that there is a progressive development of RC skills from initiating a relationship to its later stages. Our discussion of the results hopes to shed more light on the complexity of adolescents' intimate romantic lives, as well as to illustrate the importance of this knowledge for improving educational practices and helping prevent problems such as the psychogenesis of gender-based violence.

Student Voice: Reviewing two decades of the literature to guide the next 20 years

Attention to students and their education experiences has become increasingly important in the 21st century. Student experience - particularly active and agentic practices captures in terms like 'student voice' and 'partnership' - was an obvious choice in response to Journal of University Teaching and Learning Practice (JUTLP) editors' commissioned series of literature reviews analysing 20 years of the journal's publications. A hybrid method for the systematic review was guided by the question: What has been published about student voice and partnership in JUTLP, and how has this scholarship evolved over the journal's 20-year history? A student voice and partnership framework adapted from Fielding (2004, 2012) was developed to provide theoretical guidance for the review. In total, 92 publications were identified and described quantitatively (year, country, research design, etc) and qualitatively using reflexive thematic analysis. Overall, the findings show increased publications over time that document active student involvement in developing, shaping ,designing, evaluating or researching alongside staff. The upward trend of partnership is a marked change from early JUTLP publications that studied students as objects of research and sources of data with passive roles in education practices and student life activities. The trend is toward students as active, agentic participants, partners and leaders in shaping and influencing their education experiences. Moving into the next 20 years, the JUTLP community is urged to engage with students as co-authors, co-researchers, and co-designers to report on educational praxis with staff and to open up new avenues for student contributions to knowledge and the mission of JUTLP.