Educational Software Research Articles

PENGUATAN PENDIDIKAN DAYAH DI ERA DIGITAL

This study aims to analyze the implementation of digitalization at Dayah Darul Muarif and its impact on the quality of education. The digitalization at this dayah includes the use of educational software, online learning, and the integration of information technology in teaching and administrative management. The results of the study show that digitalization brings various positive impacts, such as increased access to information, more interactive learning, and management efficiency. However, the implementation of digitalization also faces several challenges, including infrastructure limitations, human resource readiness, and high implementation costs. With continuous support from various parties and appropriate strategies, this dayah can continue to optimize digital technology to improve the quality of its education. This study provides important insights for other traditional educational institutions that wish to adopt digital technology in their education systems.

A comparison of super-resolution microscopy techniques for imaging tightly packed microcolonies of an obligate intracellular bacterium.

Conventional optical microscopy imaging of obligate intracellular bacteria is hampered by the small size of bacterial cells, tight clustering exhibited by some bacterial species and challenges relating to labelling such as background from host cells, a lack of validated reagents, and a lack of tools for genetic manipulation. In this study we imaged intracellular bacteria from the species Orientia tsutsugamushi (Ot) using five different fluorescence microscopy techniques: standard confocal, Airyscan confocal, instant Structured Illumination Microscopy (iSIM), three-dimensional Structured Illumination Microscopy (3D-SIM) and Stimulated Emission Depletion Microscopy (STED). We compared the ability of each to resolve bacterial cells in intracellular clumps in the lateral (xy) axis, using full width half maximum (FWHM) measurements of a labelled outer membrane protein (ScaA) and the ability to detect small, outer membrane vesicles external to the cells. We next compared the ability of each technique to sufficiently resolve bacteria in the axial (z) direction and found 3D-STED to be the most successful method for this. We then combined this approach with a custom 3D cell segmentation and analysis pipeline using the open-source, deep learning software, Cellpose to segment the cells and subsequently the commercial software Imaris to analyze their 3D shape and size. Using this combination, we demonstrated differences in bacterial shape, but not their size, when grown in different mammalian cell lines. Overall, we compare the advantages and disadvantages of different super-resolution microscopy techniques for imaging this cytoplasmic obligate intracellular bacterium based on the specific research question being addressed.

Household Economic Losses and Community Knowledge Determine Control Strategies: A Case of Cerebral Coenurosis in Small Ruminants in Northern Tanzania

Cerebral coenurosis affects sheep and goats worldwide and has zoonotic implications. Information on the financial burden and understanding of the disease and control practices may inform control strategies. A cross-sectional study was conducted in Babati and Ngorongoro Districts, Tanzania, to determine economic losses, farmers’ knowledge, and attitudes and practices on the control of coenurosis in small ruminants. A structured questionnaire was administered to 558 households for data collection. The total annual loss was TZS 122.8 M (USD 52.9 K) for Babati and TZS 656.5 M (USD 282.9 K) for Ngorongoro District. The average annual household financial loss was TZS 356.8 K (USD 153.83) for Babati and TZS 3.1 M (USD 1.3 K) for Ngorongoro District. Almost 90% of respondents were aware of coenurosis while less than 1% of the respondents had no knowledge of it at all. The average knowledge score was 5.85 out of 16 (36.6%), which implies a low level of knowledge on coenurosis. About 94% of respondents showed a willingness to participate and pay the control costs. Given the economic loss and favorable attitudes toward control participation, delivery of an educational package on epidemiology and control of coenurosis to livestock keepers may trigger collaborative and sustainable intervention.

NJmat: Data-Driven Machine Learning Interface to Accelerate Material Design.

Machine learning techniques have significantly transformed the way materials scientists conduct research. However, the widespread deployment of machine learning software in daily experimental and simulation research for materials and chemical design has been limited. This is partly due to the substantial time investment and learning curve associated with mastering the necessary codes and computational environments. In this paper, we introduce a user-friendly, data-driven machine learning interface featuring multiple "button-clicking" functionalities to streamline the design of materials and chemicals. This interface automates the processes of transforming materials and molecules, performing feature selection, constructing machine learning models, making virtual predictions, and visualizing results. Such automation accelerates materials prediction and analysis in the inverse design process, aligning with the time criteria outlined by the Materials Genome Initiative. With simple button clicks, researchers can build machine learning models and predict new materials once they have gathered experimental or simulation data. Beyond the ease of use, NJmat offers three additional features for data-driven materials design: (1) automatic feature generation for both inorganic materials (from chemical formulas) and organic molecules (from SMILES), (2) automatic generation of Shapley plots, and (3) automatic construction of "white-box" genetic models and decision trees to provide scientific insights. We present case studies on surface design for halide perovskite materials encompassing both inorganic and organic species. These case studies illustrate general machine learning models for virtual predictions as well as the automatic featurization and Shapley/genetic model construction capabilities. We anticipate that this software tool will expedite materials and molecular design within the scope of the Materials Genome Initiative, particularly benefiting experimentalists.

Evaluating the impact of nonverbal behavior on language ability ratings

Nonverbal behavior can impact language proficiency scores in speaking tests, but there is little empirical information of the size or consistency of its effects or whether language proficiency may be a moderating variable. In this study, 100 novice raters watched and scored 30 recordings of test takers taking an international, high stakes proficiency test. The speech samples were each 2 minutes long and ranged in proficiency levels. The raters scored each sample on fluency, vocabulary, grammar, and comprehensibility using 7-point semantic differential scales. Nonverbal behavior was extracted using an automated machine learning software called iMotions, and data was analyzed with ordinal mixed effects regression. Results showed that attentional variance predicted fluency, vocabulary, and grammar scores, but only when accounting for proficiency. Higher standard deviations of attention corresponded with lower scores for the lower-proficiency group, but not the mid/higher-proficiency group. Comprehensibility scores were only predicted by mean valence when proficiency was an interaction term. Higher mean valence, or positive emotional behavior, corresponded with higher scores in the lower-proficiency group, but not the mid/higher-proficiency group. Effect sizes for these predictors were quite small, with small amounts of variance explained. These results have implications for construct representation and test fairness.

A Typology of Teachers’ Self-reported Use of Student Data from Computer-Based Assessment Programmes in Secondary Education

Teachers in secondary education have to deal with a growing diversity in student population, which asks for differentiation of their teaching. Computer-based assessments (CBA’s) are educational software tools that, for a particular school subject, allow students to practice their knowledge or skills, leading to results about students’ performance or ability level at that point in time. Information derived from CBA’s (known as learning analytics) has the potential to support teachers to differentiate by informing them of each student’s current level. In this study, our aim was to provide a typology of how and why teachers in secondary education use analytics, with the subsequent aim of providing recommendations for teacher professional development. Four profiles were found: high users, selective users, early stage users, and non-users. We provide recommendations for each of these profiles.

Systematic Review of Open-Source Software for Technical and Vocational Education and Training (TVET)

In the era of Industry 4.0, software is essential for connecting technologies, creating smart systems, and driving innovation across industries. There are several challenges and limitations related to software in Technical and Vocational Education and Training (TVET), such as software cost, software piracy, and limited modification access to the software. This demonstrates the demand for new approaches that may deal with these issues and offer alternatives by using the open-source software. The paper aims to explore on the utilization and impact of Open-Source Software (OSS) in TVET based on three main themes: (1) hardware compatibility using OSS, (2) teaching and learning aids using OSS, and (3) online learning practice using OSS. Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, the research, based on 21 articles selected from Scopus and Eric databases, reveals that OSS is compatible with hardware used in TVET programs, offers diverse teaching and learning aids, and is suitable for online learning environment. These findings underscore OSS's potential as an alternative in meeting TVET requirements, fostering dynamic learning environments, and improving pedagogical approaches, accessibility, and cost-effectiveness in TVET institutions.

تطوير مادة تعليم مهارة القراءة بالمدخل منهج 2013 على أساس برنامج لقتورا انفيير في مدرسة محمدية سوجه واراس الثانوية بوجونجارا

The result of requirement analysis showed that the teaching materials included on learning media has not been appropriate yet with the 2013 curriculum. One of the factors behind is the learning process in the classroom still uses lecture method and reading method. The purpose of this research is to know how to develop teaching materials by using Lectora Inspire software that can be used in learning qiraah, know its specification and apply the software in learning qiraah to increase students’ interest and learning outcomes. Research method used in this research is Research and Development (R & D) with research design of pre-test and post-Test control group design. The steps in this study include the analysis of problems and needs, data collection, product design, design validation to media experts and material experts, design revisions, product testing to students of class X SMA Muhammadiyah Sugihwaras Bojonegoro with sample 25 students of experimental class. The teaching materials developed with lectora inspire software consist of six chapters which are all contained in the Arabic language of class X. Based on the results of media and material experts stated that those media developed belong proper category as learning media. The result of hypothesis test analysis by using T test showed that the value of significance = 0,000 <0,05 which means Ha accepted and Ho rejected. The mean score of the students of the experimental class is (83.2) greater than the average score of the control class students (69.4). The results of student questionnaires also indicated that the responses and students' assessment of the media is also positive. Therefore, it can be concluded that the development of reading skill with lectora inspire software for qiraah learning has a significant influence.

Deep learning assisted quantitative analysis of Aβ and microglia in patients with idiopathic normal pressure hydrocephalus in relation to cognitive outcome.

Neuropathologic changes of Alzheimer disease (AD) including Aβ accumulation and neuroinflammation are frequently observed in the cerebral cortex of patients with idiopathic normal pressure hydrocephalus (iNPH). We created an automated analysis platform to quantify Aβ load and reactive microglia in the vicinity of Aβ plaques and to evaluate their association with cognitive outcome in cortical biopsies of patients with iNPH obtained at the time of shunting. Aiforia Create deep learning software was used on whole slide images of Iba1/4G8 double immunostained frontal cortical biopsies of 120 shunted iNPH patients to identify Iba1-positive microglia somas and Aβ areas, respectively. Dementia, AD clinical syndrome (ACS), and Clinical Dementia Rating Global score (CDR-GS) were evaluated retrospectively after a median follow-up of 4.4 years. Deep learning artificial intelligence yielded excellent (>95%) precision for tissue, Aβ, and microglia somas. Using an age-adjusted model, higher Aβ coverage predicted the development of dementia, the diagnosis of ACS, and more severe memory impairment by CDR-GS whereas measured microglial densities and Aβ-related microglia did not correlate with cognitive outcome in these patients. Therefore, cognitive outcome seems to be hampered by higher Aβ coverage in cortical biopsies in shunted iNPH patients but is not correlated with densities of surrounding microglia.

Changing the conversation: Empowering community pharmacists to address pneumococcal vaccine hesitancy

BackgroundAlthough pneumococcal vaccine is recommended for everyone 65 years of age and older, only 58% of Canadians in this age group have been vaccinated, well below the Public Health Agency of Canada’s target of 80%. To improve uptake, a stepped-wedge cluster randomized trial testing the effectiveness of a community pharmacist intervention was developed. ObjectiveThis prespecified sub-study aimed to uncover and quantify factors contributing to vaccine hesitancy by exploring the nature of patient-pharmacist conversations about pneumococcal vaccine. MethodsBeginning each month (April– August 2023), participating pharmacies were randomly selected to receive an education package designed to enhance pharmacists’ knowledge, skills, and abilities in promoting pneumococcal vaccination. Pharmacists provided usual care (control stage) until they received the educational package and transitioned to the intervention stage. Weekly scorecards tracked patient-pharmacist conversations about pneumococcal vaccination. Chi-squared tests compared time taken for each conversation and patient-reported reason(s) for refusal between control and intervention stages. ResultsThirteen pharmacies from across Alberta were included in the analysis, reporting 656 patient-pharmacist conversations (control stage n = 271, intervention stage n = 385). Time taken for pneumococcal vaccine conversations decreased after pharmacies received the education package (65% of conversations resulting in vaccination took <20 minutes in the control stage, compared to 88% in the intervention stage (P = 0.004)). The most common patient-reported reason for refusal, needing more time to think about the vaccine, remained similar between stages (P = 0.23). However, during the intervention stage, fewer patients refused vaccination due to lack of time to receive it today (P = 0.016) and perceived lack of benefit (P = 0.035), but more patients refused vaccination due to cost barriers (P = 0.026). ConclusionThe education provided in this study changed the reasons for refusing vaccines, suggesting the nature of patient-pharmacist conversations became more efficient and informed. Similar interventions could be adopted across Canada and the United States to help combat vaccine hesitancy.

A Study to Assess the Effectiveness of Video-Assisted Teaching Programme on Knowledge Regarding Biodegradable and Non-Biodegradable Waste among School Children in Selected School, Namakkal District

Background: Worldwide burden of waste increases day-through- day results in environmental issues including pollutants, climatic exchange and so forth. Video-assisted coaching programme concerning biodegradable and non- biodegradable waste improves the knowledge amongst faculty youngsters.  Objectives: To assess the effectiveness of video assisted teaching software on expertise regarding biodegradable and non- biodegradable waste among faculty children. design: Pre- experimental one organization pretest posttest design.Setting: selected school, Namakkal. 50 college kids, pleasing the inclusion standards had been selected via handy sampling method.  Selection Criteria: Decided on school, Namakkal. 50 college children, pleasing the inclusion standards have been decided on thru on hand sampling approach  Methods: The take a look at turned into carried out with 50 school children. based questionnaire turned into used because the evaluation tool.  Results: The look at findings concluded that the video- assisted teaching become powerful on improving know- how regarding biodegradable and non-biodegradable waste among college youngsters with paired t-check rating fifty four.25 which turned into statistically giant to p&lt;0.001. No massive association between the school children’s knowledge and their demographic variables.  Conclusion: The locating of the have a look at concluded that the video-assisted teaching was very powerful in enhancing the level of know-how of school children regarding biodegradable and non-biodegradable waste. there was an awesome development in knowledge rating between pre-take a look at and post-test 57.6% (forty three.6% - seventy one.6%) among college kids χ2=20.seventy four with statistical significance at p=zero.00011. therefore, video-assisted teaching has proved as a method to improve the knowledge of college kids regarding biodegradable and non-biodegradable wast.

GEOWISATA DAN WISATA EDUKASI: MERANCANG PAKET WISATA UNTUK KAWASAN RAWAN BENCANA

The government is currently focused on creating sustainable tourism destinations in disaster areas, with special attention given to developing geotourism as a form of educational tourism. This research aims to design educational tour packages with a geotourism theme specifically for disaster-prone areas. The study was conducted in the Tangkubanparahu Volcano disaster-prone area of North Bandung, using a combination of observations, interviews, and library documents. The data obtained was analyzed through descriptive and map analysis. The results of the research showed that geotourism has great potential as a theme for educational tourism packages in the Tangkubanparahu Volcano disaster-prone area. The 10 km route includes natural, cultural, and man-made tourist attractions which are supported by the availability of tour guides

Integration of AI and Metaheuristics in Educational Software: A Hybrid Approach to Exercise Generation

Integration of AI and Metaheuristics in Educational Software: A Hybrid Approach to Exercise Generation

Enhancing Geometry Understanding in Grade 8: Development and Evaluation of a Learning Package

This study developed and evaluated a comprehensive learning package for Grade 8 Geometry, aligned with the curriculum to address diverse student needs. The package included a teacher’s guide, modules, manipulatives, PowerPoint presentations, and lesson plans. Evaluators assessed the package based on instructional, content, and technical quality, rating it as very good. A quasi-experimental approach was employed to measure the package's effectiveness in enhancing geometric knowledge and problem-solving skills. The study involved two schools, one public and one private, each with two sections of Grade 8 students. One section in each school served as the experimental group, while the other served as the control group. Effectiveness was determined by comparing pretest and posttest scores using appropriate statistical tests. The results indicated significant improvements in student performance due to the learning package, with notable differences between public and private school students. These findings emphasize the importance of tailored educational interventions that consider the specific contexts of different school environments. It is recommended that teachers adopt this learning package to enhance student learning in geometry.

Development of educational software for stainless steel selection and evaluating usability using the System Usability Scale (SUS)

Development of educational software for stainless steel selection and evaluating usability using the System Usability Scale (SUS)

A holistic framework to model student's cognitive process in mathematics education through fuzzy cognitive maps

This study introduces a pioneering framework for modeling students' cognitive processes in mathematics education through Fuzzy Cognitive Maps (FCMs). By integrating key educational theories—Duval's Semiotic Representation Theory, Niss's Mathematical Competencies, Marton's Variation Theory, and the broad Engagement, Motivation, and Participation framework— the model offers a comprehensive and holistic understanding of students' cognitive landscapes. This research underscores the necessity of a multidimensional approach to capturing the intricate interplay of cognitive, affective, and behavioral factors in students' mathematical learning experiences. The novelty lies in its methodological innovation, employing FCMs to transcend traditional qualitative analyzes and facilitate quantitative insights into students' cognitive processes. This approach is particularly relevant in the current era dominated by digital learning environments and artificial intelligence, where real-time, automated analysis of student interactions is increasingly vital. The proposed FCM has been developed over the years with a data-driven approach; the concepts and relationships in it have been derived from the literature and refined by the author's experience in the field. Illustrated through case studies, the framework's utility is demonstrated in diverse contexts, highlighting how the quantitative data obtained are confirmed by qualitative approach: analyzing the impact of remote learning during the Covid-19 pandemic on student engagement and exploring Augmented Reality's role in enhancing mathematical conceptualization. These applications show the framework's adaptability and its potential to integrate new technologies in educational practices. However, the transition from qualitative to quantitative methodologies poses a challenge, given the prevalent use of qualitative approaches in mathematics education research. Additionally, the technological implementation of the FCM model in educational software presents practical hurdles, necessitating further development to ensure ease of integration and use in real-time educational settings. Future work will focus on bridging these methodological gaps and overcoming technological challenges to broaden the FCM model's applicability and enhance its contribution to advancing mathematics education.

Effect of short-term intensive design-based STEM learning on executive function: an fNIRS study of the left-behind children.

Design-based STEM learning is believed to be an effective cross-disciplinary strategy for promoting children's cognitive development. Yet, its impact on executive functions, particularly for disadvantaged children, still need to be explored. This study investigated the effects of short-term intensive design-based STEM learning on executive function among left-behind children. Sixty-one Grade 4 students from a school dedicated to the left-behind children in China were sampled and randomly assigned to an experimental group (10.70 ± 0.47years old, n = 30) or a control group (10.77 ± 0.43years old, n = 31). The experimental group underwent a two-week design-based STEM training program, while the control group participated in a 2-week STEM-related reading program. Both groups were assessed with the brain activation from 4 brain regions of interest using functional near-infrared spectroscopy (fNIRS) and behavioral measures during a Stroop task before and after the training. Analysis disclosed: (i) a significant within-group time effect in the experimental group, with posttest brain activation in Brodmann Area 10 and 46 being notably lower during neutral and word conditions; (ii) a significant between-group difference at posttest, with the experimental group showing considerably lower brain activation in Brodmann Area 10 and Brodmann Area 46 than the control group; and (iii) a significant task effect in brain activity among the three conditions of the Stroop task. These findings indicated that this STEM learning effectively enhanced executive function in left-behind children. The discrepancy between the non-significant differences in behavioral performance and the significant ones in brain activation implies a compensatory mechanism in brain activation. This study enriches current theories about the impact of Science, Technology, Engineering, and Mathematics (STEM) learning on children's executive function development, providing biological evidence and valuable insights for educational curriculum design and assessment.

Effectiveness of a community-led shared book reading intervention in Syrian refugee children: a randomised controlled trial

Community-led, shared book reading programs may help improve refugee children’s reading abilities and attitudes towards reading. We Love Reading (WLR)—a light-touch, community-led, shared book reading program—was evaluated in a pre-registered, wait-listed, randomised controlled trial (AEARCTR-0006523). 322 Syrian refugee mother–child dyads (children: 4–8-year-olds, 50.0% female) in Jordan were tested at two timepoints, 15 weeks apart. WLR did not significantly affect child literacy or child-reported child attitudes toward reading (ps > 0.05). Mothers did report improved child attitudes toward reading from WLR (p = 0.046, η2 = 0.013). The intervention did not lead to improvements in family relationships (ps > 0.05). WLR may have promise in improving attitudes toward reading in forcibly displaced children but did not affect literacy or child-reported attitudes toward reading; these results provide insight into what changes are needed for effective shared book reading interventions in this population.

Longitudinal Changes in Choroidal Vascularity in Myopic and Non-Myopic Children.

The purpose of this study was to evaluate longitudinal changes in choroidal vascular characteristics in childhood, and their relationship with eye growth and refractive error. Analysis of high-resolution optical coherence tomography (OCT) scans, collected over an 18-month period as part of the Role of Outdoor Activity in Myopia (ROAM) study, was conducted in 101 children (41 myopic, 60 non-myopic, age 10-15 years). OCT images were automatically analyzed and binarized using a deep learning software tool. The output was then used to compute changes in macular choroidal vascularity index (CVI), choroidal luminal, and stromal thickness over 18-months. Associations of these variables with refractive error and axial length were analyzed. CVI decreased significantly, whereas luminal and stromal thickness increased significantly over 18 months (all P < 0.001). The magnitude of change was approximately double in stromal tissue compared to luminal tissue (luminal β = 2.6 µm/year; 95% confidence interval [CI] = -1.0 to 4.1 µm/year; stromal β = 5.2 µm/year; 95% CI = 4.0, 6.5 µm/year). A significant interaction between baseline axial length and change in CVI over time (P = 0.047) was observed, with a greater CVI reduction in those with shorter axial lengths. Significant associations were observed between the change in CVI, luminal thickness, stromal thickness, and change in axial length over time (all P < 0.05). Faster axial eye growth was associated with smaller reductions in CVI, and less increase in choroidal luminal and stromal thickness. The changes in choroidal vascularity, particularly in the stromal component, may thus be a marker for eye growth. This knowledge of the longitudinal changes in choroidal vascularity in childhood and their relationship with eye growth may assist clinicians in the future to better predict eye growth and myopia progression in childhood.

We’re all just looking at the stars; how behavioral economics helps us understand the barriers to education programming in Tanzania

PurposeWe’re all just looking at the stars; how behavioral economics helps us understand the barriers to education programming in Tanzania.Design/methodology/approachThis article uses a qualitative approach to explore the behaviorally normed barriers to quality classroom instruction that contribute towards low learning outcomes. Themed text analysis was applied to qualitative secondary data from seventeen classroom observations and teacher interviews collected from low-performing schools in rural Tanzania.FindingsIt was found that teachers in poor-performing schools in Tanzania were focused on the delivery of curriculum and pedagogy, with a misplaced belief that their pupils were performing adequately. The study found no evidence of teacher resistance to change; instead, the teachers were content and often happy to implement the reading program, believing that teaching phonics-based instruction improved their teaching approach. Teachers sought confirmation of their quality instructional practice from convenient yet inaccurate sources that did not include effective pupil assessment.Research limitations/implicationsAs a result of the chosen research approach, findings may lack generalizability.Practical implicationsWhile existing models of teacher change rely on logic and reason for decision-making, this paper provides evidence that teacher models of change are much more complex and irrational, aligned more closely with insights from behavioral economics (BE). Additionally, this paper justifies that traditional research frameworks that study what works provide an incomplete picture to support effective program improvement.Originality/valueThe application of behavioral economics to research and education programming focused on reducing the restraining forces rather than pushing incentives and other program components.