Search

The learning process can be conceptualized as a dynamic system constantly evolving and adapting in response to a variety of stimuli and inputs. This paper presents a novel approach to competency-based assessment that integrates a dynamic assignment design of personalized activities with the aid of a 3D matrix array structure. This structure, named Topic, Activity, and Competency (TAC) cuboid, provides a detailed view of the student's progress, enabling the design of tailored curricular strategies to facilitate the development of competencies. Personalized activities serve as control inputs that adapt to each learner's state, driving a feedforward that promotes proactive improvement. An automation process becomes necessary to cope with the increased data volume from the TAC cuboid and the information complexity. The concept model registers TAC cuboid information, enabling a dynamic analysis to forward an adequate workload when required to facilitate students' achievement of their expected mathematical competencies. Additionally, the paper discusses the initial application of these models in an educational role-playing game, demonstrating their effectiveness in a gamified learning environment. [ABSTRACT FROM AUTHOR]

Structural inequities in graduate education perpetuate inequity for students with historically minoritized identities. This paper reviews previous reports of inequities faced by students with minoritized identities and suggests a path forward for improving equitable access to doctoral study. Specifically, this paper suggests investing in the scholarship of teaching and learning while using Gardner's model of doctoral student development to provide targeted support at different levels of operation: the institution, the department, and the individual. Evidence for suggested supports is also provided and a call for further research on the effects of such programs for recruitment, retention, and graduation of minoritized students is made. [ABSTRACT FROM AUTHOR]

This paper aims to identify the factors that are positively or negatively impacting students' well-being and their academic engagement. We used partial least-squares structural equation modeling (PLS-SEM) using the data collected through a questionnaire from four countries: Romania, Turkey, Slovakia, and Bulgaria. The model includes seven factors that influence the well-being of students and indirectly their academic engagement: stressors in the students' lives; professors' support; social support from family and friends; the students' perceived satisfaction in their lives; engaging in activities during their leisure time; self-exploration regarding their careers; and environmental exploration regarding their careers. The results show that all factors, except for stressors and environmental exploration regarding their careers, positively influence the students' well-being and thus their academic engagement. These findings are useful for university professors and managers in better organizing activities to increase academic performance. [ABSTRACT FROM AUTHOR]

International students face unique challenges in pursuing higher education in a foreign country. To address these challenges and enhance their academic experience, higher education institutions are increasingly exploring the use of artificial intelligence (AI) applications. This research essay aims to investigate the impact of AI on the education of international students. Instead of a traditional literature review, it employs a research approach to examine the potential applications of AI and discuss associated concerns. The research paper explores various AI applications, such as personalized learning experiences, adaptive testing, predictive analytics, and chatbots for learning and research. By analyzing the role of AI in education for international students, this research paper sheds light on how AI can improve learning efficiency and provide customized educational support. Additionally, it identifies significant risks and limitations, including privacy concerns, cultural differences, language proficiency, and ethical implications, which must be effectively addressed. The findings contribute to a better understanding of the potential impact of AI on international students' educational experiences and offer insights into the integration of AI into educational administration and learning processes. [ABSTRACT FROM AUTHOR]

Handwriting is a complex perceptual motor task that requires years of training and practice before complete mastery. Its acquisition is crucial, since handwriting is the basis, together with reading, of the acquisition of higher-level skills such as spelling, grammar, syntax, and text composition. Despite the correct learning and practice of handwriting, some children never master this skill to a sufficient level. These handwriting deficits, referred to as developmental dysgraphia, can seriously impact the acquisition of other skills and thus the academic success of the child if they are not diagnosed and handled early. In this review, we present a non-exhaustive listing of the tools that are the most reported in the literature for the analysis of handwriting and the diagnosis of dysgraphia. A variety of tools focusing on either the final handwriting product or the handwriting process are described here. On one hand, paper-and-pen tools are widely used throughout the world to assess handwriting quality and/or speed, but no universal gold-standard diagnostic test exists. On the other hand, several very promising computerized tools for the diagnosis of dysgraphia have been developed in the last decade, but some improvements are required before they can be available to clinicians. Based on these observations, we will discuss the pros and cons of the existing tools and the perspectives related to the development of a universal, standardized test of dysgraphia combining both paper-and-pen and computerized approaches and including different graphomotor and writing tasks. [ABSTRACT FROM AUTHOR]

Evaluating students' academic performance is crucial for assessing the quality of education and educational strategies. However, it can be challenging to predict and evaluate academic performance under uncertain and imprecise conditions. To address this issue, many research works have employed fuzzy concepts to analyze, predict, and make decisions about students' academic performance. This paper investigates the use of fuzzy concepts in research related to evaluating, analyzing, predicting, or making decisions about student academic performance. The paper proposes a fuzzy model, called FPM (Fuzzy Propositional Model), for reasoning and predicting students' academic performance. FPM aims to address the limitations of previous studies by incorporating propositional logic with fuzzy sets concept, which allows for the representation of uncertainty and imprecision in the data. FPM integrates and transforms if-then rules into weighted fuzzy production rules to predict and evaluate academic performance. This paper tests and evaluates the FPM in two scenarios. In the first scenario, the model predicts and examines the impact of absenteeism on academic performance where there is no clear relation between the two parts of the dataset. In the second scenario, the model predicts the final exam results using the lab exam results, where the data are more related. The FPM provides good results in both scenarios, demonstrating its effectiveness in predicting and evaluating students' academic performance. A comparison study of the FPM's results with a linear regression model and previous work showed that the FPM performs better in predicting academic performance and provides more insights into the underlying factors affecting it. Therefore, the FPM could be useful in educational institutions to predict and evaluate students' academic performance, identify underlying factors affecting it, and improve educational strategies. [ABSTRACT FROM AUTHOR]

Student engagement is recognised as being a critical factor linked to student success and learning outcomes. The same holds true for online learning and engagement in higher education, where the appetite for this mode of learning has escalated worldwide over several decades, and as a result of COVID-19. At the same time teachers in higher education are increasingly able to access and utilise tools to identify and analyse student online behaviours, such as tracking evidence of engagement and non-engagement. However, even with significant headway being made in fields such as learning analytics, ways in which to make sense of this data, and to utilise data to inform interventions and refine teaching approaches, continue to be areas that would benefit from further insights and exploration. This paper reports on a project that sought to investigate whether low levels of student online engagement could be enhanced through a course specific intervention strategy designed to address student engagement with online materials in a regional university. The intervention used course learning analytics data (CLAD) in combination with the behavioral science concept of nudging as a strategy for increasing student engagement with online content. The study gathered qualitative and quantitative data to explore the impact of nudging on student engagement with 187 students across two disciplines, Education and Regional/Town Planning. The results not only revealed that the use of the nudge intervention was successful in increasing the levels of engagement in online courses but also revealed that the prerequisites for nudging were needed in order to increase success rates. The paper points to the value for the broader awareness, update, and use of learning analytics as well as nudging at a course, program, and institutional level to support student online engagement. [ABSTRACT FROM AUTHOR]

This paper explores the dynamics of student engagement and demographic influences in Massive Open Online Courses (MOOCs). The study analyzes multiple facets of Brazilian MOOC participation, including re-enrollment patterns, course completion rates, and the impact of demographic characteristics on learning outcomes. Using survey data and statistical analyses from the public Aprenda Mais Platform, this study reveals that MOOC learners exhibit a strong tendency toward continuous learning, with a majority re-enrolling in subsequent courses within a short timeframe. The average completion rate across courses is around 42.14%, with learners maintaining consistent academic performance. Demographic factors, notably, race/color and disability, are found to influence enrollment and completion rates, underscoring the importance of inclusive educational practices. Geographical location impacts students' decision to enroll in and complete courses, highlighting the necessity for region-specific educational strategies. The research concludes that a diverse array of factors, including content interest, personal motivation, and demographic attributes, shape student engagement in MOOCs. These insights are vital for educators and course designers in creating effective, inclusive, and engaging online learning experiences. [ABSTRACT FROM AUTHOR]

School learning environments play a crucial role in both student and faculty outcomes; however, the limited funding allocated to public school facilities can result in poor environmental conditions which can hinder occupant health and performance. Existing school facilities must then explore affordable retrofit strategies that can effectively improve health and performance outcomes. The emerging field of biophilic design offers significant potential for improving existing school environments with benefits for both the students and faculty. Through case study research, this study proposes a toolkit of 42 biophilic retrofits for existing K-12 schools in a set of stakeholder cards that illustrate precedents, known impacts, and their relevance to high-performance schools. Additionally, a stakeholder card sorting study was conducted to establish the perceived viability and impact of each strategy. The findings reveal that biophilic retrofit design strategies are perceived by school community stakeholders to be impactful with varying levels of affordability. These findings further demonstrate that a toolkit of biophilic interventions for K-12 schools will offer invaluable insights to improve student and faculty conditions. [ABSTRACT FROM AUTHOR]

The use of active learning activities for evaluation purposes has been reported to improve results in all areas within the education field. In this paper we describe a generic multilevel structure for educational escape rooms, along with a use case where such a design was applied for assessment in a course within the STEM area. Furthermore, a project-based learning activity was also added to complement that assessment. The results obtained expose an increase in both academic performance and success rate, where the percentage rises in both cases go in line to the literature. Additionally, a high level of engagement was measured during those active learning activities, which is reported to lead to better performance and improved learning. Hence, this high engagement seems to be the primary source of the increments experienced. [ABSTRACT FROM AUTHOR]

Improving physical, mental and cognitive health is a strategic choice to help developing countries cross the middle-income trap. This paper used data from the 2019 China Rural Children Health and Nutrition Survey (n = 826), and used the Ordered Probit (Oprobit), Logit and ordinary least squares (OLS) analytical methods to systematically analyze the implications of parental migration on multidimensional health. The results indicate that parental migration significantly harms the physical and mental health of rural children, and that mobile phone addiction has a significant moderating effect. Moreover, parental migration has a greater impact on the physical health, mental health and cognitive ability of boys and rural children with low family income, while parents with higher nutrition knowledge and education can effectively improve the physical health and cognitive ability of their children. In conclusion, in order to improve the multidimensional health of rural children, the government should strengthen the policy of care and support for children whose parents migrate. Schools and families should pay attention to the supervision of rural children's mobile phone addiction. [ABSTRACT FROM AUTHOR]

This paper investigates the transmission of educational attainment from parents to offspring as a mediator of intergenerational class mobility in Europe. The study covers the last two decades with data drawn from a cross-national large-scale sample survey, namely the European Social Survey (ESS), for the years 2002–2018. Interest has focused on the question of the persistence of inequality of educational opportunities by examining the attainment of nominal levels of education and the association between the educational attainment of the parent with the highest level of education and their descendants. The study also covers new trends in social mobility that consider education as a "positional good", and a novel method of incorporating educational expansion into the transition probabilities is proposed, providing answers to whether the rising accessibility of educational qualifications attenuates the association between social origin and educational attainment. Therefore, the concept of positionality is taken into account in the estimation of intergenerational transition probabilities, and to complement the analysis, mobility measures are provided for both methods, nominal and positional. The proposed positional method is validated through a correlation analysis between the upward mobility scores (nominal and positional) with the Education Expansion Index (EEI) for the respective years. The upward mobility scores estimated via the positional method are more highly correlated with the EEI for all years, indicating a better alignment with the broader trends in educational participation and achievement. [ABSTRACT FROM AUTHOR]

Malnutrition among in-school children is a complex issue influenced by socio-economic, environmental, and health-related factors, posing significant challenges to their well-being and educational trajectories in developing countries. This review synthesized evidence on the multifaceted aspects of child malnutrition within the educational setting in developing countries. This review followed the six steps outlined by Arksey and O'Malley's framework. Four main databases (PubMed, CENTRAL, JSTOR, and Scopus) were searched. Additional searches were conducted in WHO Library, ProQuest, HINARI, Google Scholar, and Google. Reference lists of eligible papers were checked. This review found that low family income, varying family sizes, parental employment status, and educational levels significantly impact malnutrition among in-school children and adolescents. Environmental elements, including rural/urban residence, household sanitation, and living conditions, also influence malnutrition. In addition, nutrition knowledge, dietary habits, nutrient deficiencies, physical activity, and prevalent health conditions compound the risk of malnutrition. This study underscores the extensive health impact of malnutrition on general health, specific nutrient deficiencies, fetal/maternal health concerns, and overall morbidity. Also, malnutrition affects school performance and attendance, impacting cognitive abilities, and academic achievements. Addressing these challenges requires comprehensive policy actions aligned with Sustainable Development Goals, emphasizing poverty alleviation, health literacy, and gender equity. [ABSTRACT FROM AUTHOR]

Middle leaders are important conduits for school policy and are often required to lead, champion and monitor change initiatives in their departments. This paper examines secondary school middle leaders' self-reported theories, promotion and leadership of culturally responsive teaching approaches for student equity. The study participants (n = 170) are curriculum leaders in state secondary schools throughout New Zealand, serving a range of diverse populations, including Indigenous Māori students. The quantitative and qualitative data for this project were thematically analysed to inquire into middle leaders' articulation of their culturally responsive theories, practices, and pedagogical and curriculum leadership to assist members of their departments in supporting Māori student educational success. The study found that although middle leaders could clearly articulate culturally responsive, sustaining and revitalising pedagogies and leadership in alignment with government policies and expectations, they were less clear about the measures they used to evidence these practices. In addition, less than 30% of the middle leader participants mentioned academic achievement as an element of Māori student success, and few mentioned the importance of systematic monitoring of achievement data, or using them to support better learning outcomes for Māori students (184). [ABSTRACT FROM AUTHOR]

The education sector has been quick to recognize the power of predictive analytics to enhance student success rates. However, there are challenges to widespread adoption, including the lack of accessibility and the potential perpetuation of inequalities. These challenges present in different stages of modeling, including data preparation, model development, and evaluation. These steps can introduce additional bias to the system if not appropriately performed. Substantial incompleteness in responses is a common problem in nationally representative education data at a large scale. This can lead to missing data and can potentially impact the representativeness and accuracy of the results. While many education-related studies address the challenges of missing data, little is known about the impact of handling missing values on the fairness of predictive outcomes in practice. In this paper, we aim to assess the disparities in predictive modeling outcomes for college student success and investigate the impact of imputation techniques on model performance and fairness using various notions. We conduct a prospective evaluation to provide a less biased estimation of future performance and fairness than an evaluation of historical data. Our comprehensive analysis of a real large-scale education dataset reveals key insights on modeling disparities and the impact of imputation techniques on the fairness of the predictive outcome under different testing scenarios. Our results indicate that imputation introduces bias if the testing set follows the historical distribution. However, if the injustice in society is addressed and, consequently, the upcoming batch of observations is equalized, the model would be less biased. [ABSTRACT FROM AUTHOR]

Mindset theory assumes that students' beliefs about their intelligence—whether these are fixed or can grow—affects students' academic performance. Based on this assumption, mindset theorists have developed growth mindset interventions to teach students that their intelligence or another attribute can be developed, with the goal of improving academic outcomes. Though many papers have reported benefits from growth mindset interventions, others have reported no effects or even detrimental effects. Recently, proponents of mindset theory have called for a "heterogeneity revolution" to understand when growth mindset interventions are effective and when—and for whom—they are not. We sought to examine the whole picture of heterogeneity of treatment effects, including benefits, lack of impacts, and potential detriments of growth mindset interventions on academic performance. We used a recently proposed approach that considers persons as effect sizes; this approach can reveal individual-level heterogeneity often lost in aggregate data analyses. Across three papers, we find that this approach reveals substantial individual-level heterogeneity unobservable at the group level, with many students and teachers exhibiting mindset and performance outcomes that run counter to the authors' claims. Understanding and reporting heterogeneity, including benefits, null effects, and detriments, will lead to better guidance for educators and policymakers considering the role of growth mindset interventions in schools. [ABSTRACT FROM AUTHOR]

Online collaborative learning has become a new norm for online teaching at colleges, and improving the quality of online collaborative learning is an inevitable requirement for deepening the information age of education. This paper establishes a multiple mediating effect model based on a self-regulated learning integration model to explore the influence of college students' Internet-specific epistemic beliefs on academic achievement in online collaborative learning contexts. The results of a survey of 503 college students participating in online group collaborative learning showed that college students' Internet-specific epistemic beliefs in online collaborative learning contexts significantly and positively predicted academic achievement. Moreover, college students' metacognitive strategies partially mediated the relationship between Internet-specific epistemic justification and academic achievement. In addition, college students' mastery goal orientation and achievement approach goal orientation had significant partial mediating effects between Internet-specific epistemic beliefs and academic achievement. College students' mastery goal orientation and metacognitive strategies had significant chain mediating effects between Internet-specific epistemic beliefs and academic achievement. Finally, suggestions, significance, limitations, and future research directions are discussed. [ABSTRACT FROM AUTHOR]

The objective of this paper was to scope the challenges associated with data-sharing governance for machine learning applications in education research (MLER) within the South African context. Machine learning applications have the potential to assist student success and identify areas where students require additional support. However, the implementation of these applications depends on the availability of quality data. This paper highlights the challenges in data-sharing policies across institutions and organisations that make it difficult to standardise data-sharing practices for MLER. This poses a challenge for South African researchers in the MLER space who wish to advance and innovate. The paper proposes viewpoints that policymakers must consider to overcome these challenges of data-sharing practices, ultimately allowing South African researchers to leverage the benefits of machine learning applications in education effectively. By addressing these challenges, South African institutions and organisations can improve educational outcomes and work toward the goal of inclusive and equitable education. [ABSTRACT FROM AUTHOR]

In a virtual learning environment, it is important to be able to correctly assess students to help them receive the best possible education. This can have a big impact on the way disabled students learn and their goals for gaining a high level of qualification. This paper investigated different fuzzy logic-based techniques for student academic evaluations in a 3D virtual learning environment (VLE). Some of the techniques were found to be especially helpful for disabled students, and the paper also described the development and design of evaluation systems that take this into account. The study used fuzzy logic to study how well disabled students are doing in their classes over a whole year. This fuzzy logic was developed using MATLAB software, which uses features extracted from student evaluations. Disabled students' characteristics (such as experience and understanding, problem-solving skills, etc.) have been measured and combined with a 3D virtual learning environment built using open-source software, Moodle, and Sloodle. This way, disabled students can interact with their courses inside a 3D VLE using Sloodle. According to the findings, which were based on 20 disabled students, fuzzy logic technology used in 3D Virtual Learning Environments (VLEs) produces different results than traditional assessments. The difference between the two is about 3.9 points on average. [ABSTRACT FROM AUTHOR]

Due to COVID-19, the researching of educational data and the improvement of related systems have become increasingly important in recent years. Educational institutions seek more information about their students to find ways to utilize their talents and address their weaknesses. With the emergence of e-learning, researchers and programmers aim to find ways to maintain students' attention and improve their chances of achieving a higher grade point average (GPA) to gain admission to their desired colleges. In this paper, we predict, test, and provide reasons for declining student performance using various machine learning algorithms, including support vector machine with different kernels, decision tree, random forest, and k-nearest neighbors algorithms. Additionally, we compare two databases, one with data related to online learning and another with data on relevant offline learning properties, to compare predicted weaknesses with metrics such as F1 score and accuracy. However, before applying the algorithms, the databases need normalization to meet the prediction format. Ultimately, we find that success in school is related to habits such as sleep, study time, and screen time. More details regarding the results are provided in this paper. [ABSTRACT FROM AUTHOR]

Background: Proper vision is absolutely critical to children's academic performance, as vision problems can drastically affect learning ability. Currently, the existing literature in this field is somewhat inconsistent and carries several controversies about the influence of vision on academic performance. In this study, citation networks were utilized in order to analyze the relationship between publications and authors, the most-cited publication, and the different research areas. Additionally, the most commonly utilized publication sources along with the most common research areas were also pinpointed. Methods: The aforementioned search was executed in the Web of Science database, with a time range beginning in 1941 and ending in 2022. In order to scrutinize the publications, VOSviewer, CiteSpace software, and the Citation Network Explorer were utilized for analysis about the most-cited publication and the different research areas. Results: Overall, 1342 papers were found in all fields along with 2187 citation networks. Moreover, 2020 was the year with the most publications, including 127 publications and 4 citation networks. Bull et al., published in 2008, was the most-cited work, reaching a citation index of 975. The clustering function managed to identity four groups with the most engaging research topics from researchers: motor visual skills, visual memory, the influence of vision on the different learning styles, and abnormal development of the visual system. Conclusions: In the end, the topic with the greatest interest was the influence of visual motor skills on academic performance. Ideally, this paper will assist fellow researchers in quickly noting which topics are of greatest interest and how research in this area has evolved. [ABSTRACT FROM AUTHOR]

Prior studies emphasize the value of friends' support for children/adolescents who have a disability or suffer from mental ill-health or a long-term illness. However, few studies have explored how a caring role affects those young friend carers themselves. This paper addresses a gap in the research by focusing on this hitherto neglected group of young carers to explore the impact of providing care to friends. An online survey was employed for a cross-national study conducted in 2018–2019 in Sweden, Italy, Slovenia, the Netherlands, Switzerland, and the United Kingdom to examine the incidence of adolescent young friend carers, the extent of care they provide, and their self-reported health, well-being, and school situation. The survey was completed by 7146 adolescents, aged 15–17, and 1121 of them provided care to a friend with a health-related condition, most frequently mental ill-health. They carried out high levels of caring activities, and a quarter of them also provided care to a family member. They experienced both positive and negative aspects of caring. Nevertheless, in comparison with adolescents who provided care to family members, they reported more health problems, with a dominance of mental ill-health, and they received lower levels of support. Since adolescent friends play a valuable role for young people with health-related conditions, especially mental ill-health, it is important to find ways of optimizing their caring experiences in order that those adolescents who choose to care for a friend can do so without it having a negative impact on their own mental health, well-being, and life situation. [ABSTRACT FROM AUTHOR]

For a lot of beginners, learning to program is challenging; similarly, for teachers, it is difficult to draw on students' prior knowledge to help the process because it is not quite obvious which abilities are significant for developing programming skills. This paper seeks to shed some light on the subject by identifying which previously recorded variables have the strongest correlation with passing an introductory programming course. To do this, a data set was collected including data from four cohorts of students who attended an introductory programming course, common to all Engineering programmes at a Chilean university. With this data set, several classifiers were built, using different Machine Learning methods, to determine whether students pass or fail the course. In addition, models were trained on subsets of students by programme duration and engineering specialisation. An accuracy of 68% was achieved, but the analysis by specialisation shows that both accuracy and the significant variables vary depending on the programme. The fact that classification methods select different predictors depending on the specialisation suggests that there is a variety of factors that affect a student's ability to succeed in a programming course, such as overall academic performance, language proficiency, and mathematical and scientific skills. [ABSTRACT FROM AUTHOR]

In this paper, we will analyze how a few initial vocational education and training (VET) schools have elaborated wide-ranging responses to early leaving from education and training in Liguria (Italy) and Catalonia (Spain). In contrast with many members of the EU and the OECD, the prevailing institutional arrangements in these two countries hardly support disadvantaged youths to catch up with basic academic performance and find an appealing pathway between compulsory and post-compulsory education. Despite this bias of official policies, we argue that some initial VET schools manage to navigate the interface between social structure and agency and accommodate the aspirations of disadvantaged students by involving local stakeholders and shaping school time organization in a particular way. [ABSTRACT FROM AUTHOR]

With the rapid development of higher education, the evaluation of the academic growth potential of universities has received extensive attention from scholars and educational administrators. Although the number of papers on university academic evaluation is increasing, few scholars have conducted research on the changing trend of university academic performance. Because traditional statistical methods and deep learning techniques have proven to be incapable of handling short time series data well, this paper proposes to adopt topological data analysis (TDA) to extract specified features from short time series data and then construct the model for the prediction of trend of university academic performance. The performance of the proposed method is evaluated by experiments on a real-world university academic performance dataset. By comparing the prediction results given by the Markov chain as well as SVM on the original data and TDA statistics, respectively, we demonstrate that the data generated by TDA methods can help construct very discriminative models and have a great advantage over the traditional models. In addition, this paper gives the prediction results as a reference, which provides a new perspective for the development evaluation of the academic performance of colleges and universities. [ABSTRACT FROM AUTHOR]

Blockchain is a new and modern technology that is gradually being used in various fields due to its ability to decentralize and organize secure and reliable data exchange and storage. One of the related research areas generating increasing interest is the field of education, with particular focus on the digitization and automation of educational management processes and the ability to store and verify digital documents about student progress. The main goal of this study is to develop a platform that creates a unified digital register of students' educational achievements, which is one of the most pressing issues in the field of education, based on the Ethereum blockchain architecture. Blockchain is expensive; therefore, there is a need to consider performance criteria when evaluating any decision made about the technology, especially the most important aspects such as predicting traffic behavior, estimating transaction costs and providing the necessary indicators of system quality and functionality. However, most research ignores the evaluation of performance indicators, such as throughput, the speed of transactions and the amount of data stored in the Ethereum blockchain database, which are the main evaluation criteria. This paper aims to eliminate this gap by evaluating the performance of the developed platform and by discussing the obtained experimental results. Thus, the main results of this work are the design and deployment of a blockchain platform and the analysis of its transaction costs. We conclude that the proposed blockchain solution is applicable as a system for the accounting and verification of loans and student academic achievements. [ABSTRACT FROM AUTHOR]

Teachers are urged to provide differentiated instruction (DI), that is, deliberately adapting instruction to the learning needs of all students. DI can positively affect students' academic achievement and their social and emotional development, as well as foster teacher job satisfaction. However, international research, as well as research in the Dutch context, has shown that teachers feel unprepared to provide DI. Hence, the development of teacher professional development (TPD) programs is necessary. In the current paper, the design of a TPD intervention to support DI is presented, in which the content and design approach were deliberately chosen. The intervention content was based on an analysis of the skills and knowledge expert teachers use when providing DI. The design of the intervention was based on the whole-task approach from the 4C/ID model to promote the transfer of learning, among other things. Based on the experiences of the teachers participating in the training pilot (n = 4), we provide our recommendations for future TPD for DI. The next step will be to study the effects of this TPD program on a larger scale to obtain insight into what design characteristics do or do not work, which can be used to further improve this TPD intervention. [ABSTRACT FROM AUTHOR]

With the globalization of higher education, academic evaluation is increasingly valued by the scientific and educational circles. Although the number of published papers of academic evaluation methods is increasing, previous research mainly focused on the method of assigning different weights for various indicators, which can be subjective and limited. This paper investigates the evaluation of academic performance by using the statistical K-means (SKM) algorithm to produce clusters. The core idea is mapping the evaluation data from Euclidean space to Riemannian space in which the geometric structure can be used to obtain accurate clustering results. The method can adapt to different indicators and make full use of big data. By using the K-means algorithm based on statistical manifolds, the academic evaluation results of universities can be obtained. Furthermore, through simulation experiments on the top 20 universities of China with the traditional K-means, GMM and SKM algorithms, respectively, we analyze the advantages and disadvantages of different methods. We also test the three algorithms on a UCI ML dataset. The simulation results show the advantages of the SKM algorithm. [ABSTRACT FROM AUTHOR]

Background: Numerous studies have been conducted to explicate the scope of emotional intelligence in educational success and coping with stress in different academic sectors, but very few have been conducted with dental students. This scoping review aimed to ascertain the role of emotional intelligence in academic performance and stress factors among dental students. Methods: All publications in the English language between 2001 and 2020 were retrieved employing MeSh keywords. Academic resources such as Pubmed, Pubmed Central, EMBASE, Web of Science, EBSCO-Host, Cochrane, PROSPERO, and ARU E-library were comprehensively searched for empirical research. One thousand, three hundred and fifty-nine papers were screened according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards for inclusion and exclusion criteria. These publications were then evaluated further by deleting duplicates, examining full-text articles, and conducting an abstract assessment. This review included a critical appraisal of 24 articles. Results: The narrative analysis method was applied to evaluate the data retrieved from publications regarding EI, academic performance, and stress factors. The review found that EI had a greater impact on the educational success of dental students throughout their clinical years. Moreover, EI may be a key tool in coping with stress and negative emotions. Higher EI scores were shown to be associated with better performance in organizational and leadership abilities, which are important for career advancement. Conclusion: The review suggested including EI training in the dental curriculum. Furthermore, EI should be used as a selection criterion for admission to dental education. [ABSTRACT FROM AUTHOR]

The challenges and tensions experienced by mid-career faculty (MCF) can lead to frustration, disengagement, or leaving the professoriate altogether, a trend noted by researchers prior to and especially after the pandemic. In this article, we explore the role that collegial support and career reflection and assessment strategies targeting mid-career faculty can play to preserve institutional vitality, support faculty agency, and promote student success. Additionally, we propose initiatives and supports that may assist these faculty members in staying in the academy and staying well as they pursue professional fulfillment and work towards their goals, including promotion to full professorship. We contend that post-secondary campuses should invest in keeping MCF engaged because of the crucial roles they serve on campus. [ABSTRACT FROM AUTHOR]

The adoption of the active learning paradigm presents a series of challenges and uncertainties. However, its adoption may result in better academic results and a more engaging attitude towards learning. In this sense, this paper presents a case scenario in which such a change of paradigm has been deployed, where escape rooms have been introduced as an assessment tool in an active learning context. The way to move through those escape rooms is by taking a series of questionnaires based on the knowledge acquired, such that failing a test keeps the group in the same position and passing it makes them move according to the grades obtained. Surveys and comments offered by students show they were more motivated and engaged after this task, and an improvement in academic performance has been detected. [ABSTRACT FROM AUTHOR]

Who benefits when economic costs to the pursuit of higher education are diminished? Can such reforms advance the educational trajectory of historically marginalized groups, including women and indigenous people, or are historic social inequalities replicated in the use of new opportunities? The 2016 Ley de Gratuidad in Chile presents a unique opportunity to examine who benefits and how when the state provides a policy guaranteeing free higher education at participating universities. Given the systematic biases and cultural norms faced by women and indigenous people in Chile and the broad design of the state-led policy, the educational reform constitutes an important test of the extent to which lowering costs can facilitate education across an economically and socially diverse population. Leveraging data from two waves of a household survey, this paper finds that educational attainment, measured in the number of years of schooling achieved by respondents, is significantly higher for those who receive such a benefit, consistent with the design and intent of the policy. More surprisingly, these increases in years of education occur for women and indigenous people, even though no programmatic element emphasizes these groups. The results suggest that state financing is significantly associated with promoting higher education in the population and that women, the poor, and indigenous people are significant beneficiaries of this effect despite the social and cultural barriers in the country. [ABSTRACT FROM AUTHOR]

Schools offer a unique environment to influence children's physical activity (PA) levels positively. This study aims to systematically review the evidence surrounding how PA affects academic performance by analysing how the frequency, intensity, time, and type of PA mediate academic performance outcomes. This review was conducted using the PRISMA framework. Keyword searches were conducted in Science Direct, PubMed, and SPORTDiscus. Children that were obese, typically developing, typical weight, disabled, with a developmental disability, from a low socio-economic background, or an ethnic minority were included. A total of 19 studies were included, with a total of 6788 participants, a mean age of 9.3 years (50.2% boys, and 49.8% girls). Overall, 63.2% were nondisabled, while 36.8% were diagnosed with a disability. Two authors met, reviewed papers with regard to the inclusion criteria, and agreed on outputs to be included. Evidence suggests that associations between PA and academic performance were primarily positive or nonsignificant. PA levels of 90 min plus per week were associated with improved academic performance, as was PA performed at moderate to vigorous intensity. The optimal duration of PA was 30–60 min per session, whilst various sports induced positive academic effects. Importantly, findings support that PA does not have a deleterious effect on academic performance but can enhance it. [ABSTRACT FROM AUTHOR]

Schools can have a significant role in affecting the mental health and wellbeing of both students and staff, with considerable implications for society as a whole. Hence, there is a need for school-based interventions to both assist those experiencing mental health problems and to implement activities and policies that facilitate the enhancement and maintenance of good mental health. Unlike most school mental health interventions that are focussed on, and specific to, the school setting, the Act–Belong–Commit Mentally Healthy Schools Framework is based on the principles of the Act–Belong–Commit community-wide general population mental health promotion campaign, which has been adapted to the school setting via the World Health Organisation's Health Promoting Schools Framework. The Mentally Healthy Schools Framework is a whole-school approach to enhancing both student and staff mental health. This paper reports the findings of a preliminary impact survey administered to students after the adoption of the Framework in a number of primary and secondary schools in Western Australia. Students from two schools that had only recently adopted the Framework completed a "Baseline" questionnaire, and students from three schools that had been implementing the Framework for at least 17 months completed a "Follow-up" questionnaire. The results suggest that the Mentally Healthy Schools Framework, adapted from a community-wide campaign, can have a positive impact on students in terms of increasing openness about mental health, increasing awareness of behaviours conducive to good mental health, and increasing engagement in behaviours to improve their mental health. Such positive impacts have clear implications not only for prevention of mental disorders, but for academic achievement, employment, and overall contribution to society. [ABSTRACT FROM AUTHOR]

Due to the rapidly increasing number of students at universities in recent years, universities may arrange students from different majors in the same class, which may bring several challenges in teaching and learning for students and teachers, such as poor class experience, less class discussion and more workload for teachers. In this paper, we investigate the learning achievements of students with different major backgrounds based on a large-size course of Introduction to Java Programming. Approaches of difficulty index, incrimination index, failure rate, median average mark, average mark and standard deviation are used to evaluate students' learning achievements based on students' coursework assignments, continuous assessment and the final exam. Results show that major backgrounds could significantly affect learning achievements even in the same teaching and learning environment. To achieve a better learning experience and performance, we finally divided the original module into two separate modules for students with different major backgrounds. [ABSTRACT FROM AUTHOR]

The recent COVID-19 pandemic has increased students' stress as they may feel under increased pressure to have a good performance and compensate for the disruption to their education. Improving attention levels and learning capacity may assist in ameliorating academic performance. Qigong is a traditional Chinese medicine technique that appears to have positive effects on the management of mental health and may provide tools for coping with stressful situations. This paper explores data obtained while conducting a previous study and includes an excess of data from a total of 44 participants who were previously divided into an experimental Qigong group and a sham Qigong control group. The improvements in specific auditory processing and reaction times may indicate benefits in attention and learning capacity. These improvements were more pronounced in the experimental Qigong group compared to the sham Qigong group. Qigong may be able to assist in improving students' academic performance and can be easily integrated into physical education classes. It could also assist students to cope with the increased academic pressure resulting from the COVID-19 pandemic context. [ABSTRACT FROM AUTHOR]

Teachers and students are the two basic elements in educational activities. Students are educated but are not exactly passive recipients of education. With subjective initiative, all educational impacts must be through the initiative of students to achieve the desired effect. Therefore, all activities of education must start from mobilizing students' initiative and motivation so that they have sufficient motivation to learn actively and well. The effective analysis of employment data, at the statistical level of data analysis, is a favorable basis to support the influence of teachers on students. However, most of the previous methods are C4.5 algorithms, decision tree generation algorithms based on rough sets, etc., which are commonly used for employment data analysis. None of them can sufficiently deal with the problem of different decision accuracy requirements and noise adaptability. In this paper, we analyze the employment data of a university in 2012 as an example and compare the analysis results with those of the C4.5 algorithm and decision tree generation algorithm based on a rough set. The results show that the decision tree algorithm based on the multiscale rough set model generates a simple decision tree structure. In addition, our methods do not have indistinguishable datasets and are fast in terms of computing. This study provides an effective guide to the relevance of teachers' cognitive abilities and teaching motivations for students' employment. [ABSTRACT FROM AUTHOR]

Addressing challenges posed by the Sustainable Development Goals (SDGs) will require the next generation of engineers from all disciplines to be equipped with specific skills. Given this context, a professional skills survey was designed, drawing on previous European-level research. Its results provide valuable localised insights for educators into the most important skills for the next generation of engineers (on the island of Ireland) to achieve the SDGs. They also reveal some variance in the views of employers, academics, and students. [ABSTRACT FROM AUTHOR]

To derive a latent trait (for instance ability) in a computer adaptive testing (CAT) framework, the obtained results from a model must have a direct relationship to the examinees' response to a set of items presented. The set of items is previously calibrated to decide which item to present to the examinee in the next evaluation question. Some useful models are more naturally based on conditional probability in order to involve previously obtained hits/misses. In this paper, we integrate an experimental part, obtaining the information related to the examinee's academic performance, with a theoretical contribution of maximum entropy. Some academic performance index functions are built to support the experimental part and then explain under what conditions one can use constrained prior distributions. Additionally, we highlight that heuristic prior distributions might not properly work in all likely cases, and when to use personalized prior distributions instead. Finally, the inclusion of the performance index functions, arising from current experimental studies and historical records, are integrated into a theoretical part based on entropy maximization and its relationship with a CAT process. [ABSTRACT FROM AUTHOR]

Pre-service teacher preparation (PSTP) is generally considered a significant predictor of student achievements. This paper adopted a multi-tier linear model to estimate the PSTP effects on student performance by taking teachers and students in the high schools of Haidian District, Beijing, China, as the research population. It used exploratory factor analysis to classify PSTP into two categories: content knowledge preparation and pedagogical content knowledge preparation; and described the status of PSTP in three subjects: Chinese, mathematics, and chemistry. The study found differences in PSTP by subject. In Chinese, teachers' content knowledge preparation significantly negatively affected student performance, and their pedagogical content knowledge preparation significantly positively influenced student performance. In mathematics, PSTP had no significant effect on student performance. In chemistry, teachers' pedagogical content knowledge preparation had a significantly negative effect on student performance. Based on the findings of the empirical study, the study proposes further identifying PSTP's role in student performance by subject, strengthening the focus on pre-service preparation skills in recruiting Chinese and chemistry teachers, and developing a more suitable system for teacher selection and training. [ABSTRACT FROM AUTHOR]

The main purpose of modern intelligence tests has been to predict individual differences in academic performance, first of children, then adolescents, and later extending to adults. From the earliest Binet–Simon scales to current times, most one-on-one omnibus intelligence assessments include both process subtests (e.g., memory, reasoning) and content subtests (e.g., vocabulary, information). As somewhat parallel developments, intelligence theorists have argued about the primacy of the process components or the content components reflecting intelligence, with many modern researchers proposing that process constructs like working memory are the fundamental determinant of individual differences in intelligence. To address whether there is an adequate basis for re-configuring intelligence assessments from content or mixed content and process measures to all-process measures, the question to be answered in this paper is whether intellectual process assessments are more or less valid predictors of academic success, in comparison to content measures. A brief review of the history of intelligence assessment is provided with respect to these issues, and a number of problems and limitations of process measures is discussed. In the final analysis, there is insufficient justification for using process-only measures to the exclusion of content measures, and the limited data available point to the idea that content-dominated measures are more highly predictive of academic success than are process measures. [ABSTRACT FROM AUTHOR]

Author Note: Standardization data and analysis from the Kaufman Test of Educational Achievement, Second Edition-Comprehensive Form (KTEA-2). Copyright © 2004 NCS Pearson, Inc. Used with permission. All rights reserved. Standardization data and analysis from the Kaufman Assessment Battery for Children, Second Edition (KABC-II). Copyright © 2004 NCS Pearson, Inc. Used with permission. All rights reserved. Standardization data from the Wechsler Intelligence Scale for Children, Fifth Edition (WISC-5). Copyright © 2014 NCS Pearson, Inc. Used with permission. All rights reserved. Multidimensional scaling (MDS) was used as an alternate multivariate procedure for investigating intelligence and academic achievement test score correlations. Correlation coefficients among Wechsler Intelligence Scale for Children, Fifth Edition (WISC-5) and Wechsler Individual Achievement Test, Third Edition (WIAT-III) validity sample scores and among Kaufman Assessment Battery for Children, Second Edition (KABC-II) and Kaufman Test of Educational Achievement, Second Edition (KTEA-2) co-norming sample scores were analyzed using multidimensional scaling (MDS). Three-dimensional MDS configurations were the best fit for interpretation in both datasets. Subtests were more clearly organized by CHC ability and academic domain instead of complexity. Auditory-linguistic, figural-visual, reading-writing, and quantitative-numeric regions were visible in all models. Results were mostly similar across different grade levels. Additional analysis with WISC-V and WIAT-III tests showed that content (verbal, numeric, figural) and response process facets (verbal, manual, paper-pencil) were also useful in explaining test locations. Two implications from this study are that caution may be needed when interpreting fluency scores across academic areas, and MDS provides more empirically based validity evidence regarding content and response mode processes. [ABSTRACT FROM AUTHOR]

Pedagogical innovation involving information and communications technology (ICT) may offer teachers the opportunity to create engaging learning environments in engineering courses. In this paper, we present a gamification teaching experience whose primary objective is to improve motivation, and we obtained results for students of a mathematics course during their first year at university. For this case study, we used Classcraft®, which is a role-playing game supported by a digital platform and a mobile application that has been developed to answer teachers' classroom management needs. We hypothesized that using this application as ICT could enhance learning and promote the development of the four "super skills" (or the Four C's): critical thinking, communication, collaboration, and creativity. In order to explore the educational effectiveness of the methodology, a comparison between a gamification group of students and a control group was carried out. Our results showed that the mean mark obtained by the control group students was lower than that obtained by the gamification group students. In addition, the Nemenyi test showed that the Four C's were improved thanks to the Classcraft® activities and group project. Overall, course participants positively evaluated the use of the gamification platform. [ABSTRACT FROM AUTHOR]

This paper explores how the entry profiles of engineering students are related to their academic performance during the first year of university in a sample of 255 first-year engineering students (77 females and 178 males) at a university in Northeast Mexico. The predictors used were the high school grade point average (HSGPA), Scholastic Aptitude Test (SAT) results, the first admission test, and a Spanish adaptation of the Survey of Study Habits and Attitudes Test (SSHA) from Brown and Holtzman. The SSHA adaptation was tested for internal consistency reliabilities via Cronbach's alpha globally (0.92) and for the following categories: delay avoidance (DA: 0.79), work methods (WM: 0.81), teacher approval (TA: 0.89), and educational acceptance (EA: 0.74). The results were compared with those of other studies to validate their consistency. To assess the different entry profiles between high- and low-achieving students, we performed a Kruskal–Wallis test and found significant differences (p < 0.001) between both profiles for all variables. We then measured the relationships between the variables and academic success by constructing a correlation table, where HSGPA, SAT, and DA showed the highest correlations: 0.61, 0.40, and 0.36, respectively. With these outcomes, a predictive model via a logistic regression ( R 2 = 0.52 ) was built to forecast first year academic performance in the specific context. [ABSTRACT FROM AUTHOR]

Intelligence, as well as working memory and attention, affect the acquisition of mathematical competencies. This paper aimed to examine the influence of working memory and attention when taking different mathematical skills into account as a function of children's intellectual ability. Overall, intelligence, working memory, attention and numerical skills were assessed twice in 1868 German pre-school children (t1, t2) and again at 2nd grade (t3). We defined three intellectual ability groups based on the results of intellectual assessment at t1 and t2. Group comparisons revealed significant differences between the three intellectual ability groups. Over time, children with low intellectual ability showed the lowest achievement in domain-general and numerical and mathematical skills compared to children of average intellectual ability. The highest achievement on the aforementioned variables was found for children of high intellectual ability. Additionally, path modelling revealed that, depending on the intellectual ability, different models of varying complexity could be generated. These models differed with regard to the relevance of the predictors (t2) and the future mathematical skills (t3). Causes and conclusions of these findings are discussed. [ABSTRACT FROM AUTHOR]

Despite the lasting interest towards the relationship between intelligence and creativity, comparably less attention is paid to its age-related changes. Our paper considers the organization of fluid intelligence and psychometric indicators of creativity and is based on the experimental data obtained for children aged 11 (n = 99) and for young adults (n = 77). We used two figural and verbal tasks with and without time limit. We found that the age-related differences in creativity are dependent on the context and the type of testing. The young adults were different from the children, having higher indicators of verbal and figurative creativity, except for the originality of the drawings created within the Incomplete Figures test, and having considerably higher test results for fluid intelligence. These age-related differences, together with the discovered closer relationship between the creativity indicators in the young adults group compared to the children, might suggest insufficient contribution of the components of the executive control of information selection (inhibition, shifting, and updating), which had not fully formed in eleven-year-olds. The comparison of the various indicators of creativity suggests that the most complex task for the children was the composition of an original sentence by joining nouns from various semantic categories. [ABSTRACT FROM AUTHOR]

Youth with a history of traumatic or non-traumatic acquired brain injury are at increased risk for long-lasting cognitive, emotional, behavioral, social, and physical sequelae post-injury. Such sequelae have great potential to negatively impact this population's academic functioning. Consistently, poorer academic achievement and elevated need for educational supports have been well-documented among youth with a history of acquired brain injury. The current paper reviews the literature on neuropsychological, psychiatric, and academic outcomes of pediatric acquired brain injury. A discussion of special education law as it applies to this patient population, ongoing limitations within the field, and a proposal of solutions are also included. [ABSTRACT FROM AUTHOR]

In recent years, using micro-lectures (a short video of less than ten minutes) as a digital learning medium has become popular for integrating technology into mathematics lessons, providing new experiences to students and helping them to master mathematical concepts. It is important to note that the effectiveness of a micro-lecture depends on how teachers use it and on students' perceptions of learning support media. Therefore, this research aims to determine Junior High School students' achievements and satisfaction using micro-lectures on the topic of Direct and Inverse Proportions. Teachers' micro-lectures in this research were designed based on their teaching styles, learning objectives, and considering the needs of their students. A quasi-experiment with 3, 2, and 1 pretest-posttest design with experimental and control groups was also used. In the first and second experimental groups, teachers used the same version of the micro-lectures in their classrooms as the main learning medium and at home to preview and review Direct and Inverse Proportions materials. At the same time, the control group used conventional expository learning activities. Finally, a learning satisfaction questionnaire was used to determine students' perceptions of using micro-lectures in their mathematics lessons. Findings indicate that the use of micro-lectures in the experimental classes I and II is better than in the control class and led to improved learning achievements and student satisfaction. Meanwhile, there is no significant difference between using micro-lectures inside and outside classrooms. Students' report cards also showed that their learning satisfaction using this technique was higher than the control class. Practical implications and suggestions for further investigation are to be also discussed at the end of the paper. [ABSTRACT FROM AUTHOR]

Despite the increasing amount of research on social media, there are few studies on the use of WhatsApp to assess academic performance. Surprisingly, students use social media during lectures, causing a problem. According to the literature, students utilize WhatsApp throughout academic activities where it is prohibited. Researchers and policymakers must pay attention to this problem to understand its impact on academic achievement. In this paper, by using multivariate statistical methods, we investigate the impact of WhatsApp use on academic performance. We construct a questionnaire for this investigation and apply it to a case study based on a sample of 258 students of management from India. We determine the prevalence of WhatsApp employment among these students and note that many of them utilize the app for academic purposes. We found a positive association between time spent on WhatsApp and students' grade point average (GPA) based on factor, principal component, correlation, and chi-square analyses. Answering questions on the app in class is related to the program's ability to help students learn. More use of the app in class leads to a lower GPA. However, sometimes, using the app might help students learn and perform better. We identify that many students disseminate materials through the app for academic purposes, contributing to their academic performance. Furthermore, this app is utilized for communicating with their teachers. Computations were carried out with the R and SPSS software. [ABSTRACT FROM AUTHOR]

Cerebral Visual Impairment (CVI) has become the leading cause of children's visual impairment in developed countries. Since CVI may negatively affect neuropsychomotor development, an early diagnosis and characterization become fundamental to define effective habilitation approaches. To date, there is a lack of standardized diagnostic methods to assess CVI in children, and the role of visual functions in children's neuropsychological profiles has been poorly investigated. In the present paper, we aim to describe the clinical and neuropsychological profiles and to investigate the possible effects of visual functions on neuropsychological performance of a cohort of children diagnosed with CVI. Fifty-one children with CVI were included in our retrospective analysis (inclusion criteria: verbal IQ > 70 in Wechsler scales; absence of significant ocular involvement). For each participant, we collected data on neuropsychological assessment (i.e., cognitive, cognitive visual, and learning abilities), basic visual functions (e.g., Best Corrected Visual Acuity—BCVA, contrast sensitivity, and ocular motor abilities) and global development features (e.g., neurological signs and motor development delay) based on standardized tests, according to patients' ages. The results showed that oculomotor dysfunction involving saccades and smooth pursuit may be a core symptom of CVI and might have a significant impact on cognitive visual and other neuropsychological abilities. Furthermore, visual acuity and contrast sensitivity may influence cognitive, cognitive visual, and academic performances. Our findings suggest the importance of a comprehensive assessment of both visual and neuropsychological functions in children when CVI is suspected, which is needed to provide a more comprehensive functional profile and define the best habilitation strategy to sustain functional vision. [ABSTRACT FROM AUTHOR]