Search results for: learning assessment

Authors: Claudia Mertens, Amanda Shufflebarger

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Step one: What we know about effective learning for pupils with SEN: results of 2 systematic reviews: Before establishing principles and practices for teaching and learning of pupils with SEN, we need a good overview of the results of empirical studies conducted in the respective field. Therefore, two systematic reviews on the use of digital tools in inclusive and non-inclusive school settings were conducted - taking into consideration studies published in German: One systematic review included studies having undergone a peer review process, and the second included studies without peer review). The results (collaboration of two German universities) will be presented during the conference. Step two: Students’ results of a research lab on “inclusive media education”: On this basis, German students worked on “inclusive media education” in small research projects (duration: 1 year). They were “education majors” enrolled in a course on inclusive media education. They conducted research projects on topics ranging from smartboards in inclusive settings, digital media in gifted math education, Tik Tok in German as a Foreign Language education and many more. As part of their course, the German students created an academic conference poster. In the conference, the results of these research projects/papers are put into the context of the results of the systematic reviews. Step three: Global Classroom: The German students’ posters were critically discussed in a global classroom in cooperation with Indiana University East (USA) and Hamburg University (Germany) in the winter/spring term of 2022/2023. 15 students in Germany collaborated with 15 students at Indiana University East. The IU East student participants were enrolled in “Writing in the Arts and Sciences,” which is specifically designed for pre-service teachers. The joint work began at the beginning of the Spring 2023 semester in January 2023 and continued until the end of the Uni Hamburg semester in February 2023. Before January, Uni Hamburg students had been working on a research project individually or in pairs. Didactic Approach: Both groups of students posted a brief video or audio introduction to a shared Canvas discussion page. In the joint long synchronous session, the students discussed key content terms such as inclusion, inclusive, diversity, etc., with the help of prompt cards, and they compared how they understood or applied these terms differently. Uni Hamburg students presented drafts of academic posters. IU East students gave them specific feedback. After that, IU East students wrote brief reflections summarizing what they learned from the poster. After the class, small groups were expected to create a voice recording reflecting on their experiences. In their recordings, they examined critical incidents, highlighting what they learned from these incidents. Major results of the student research and of the global classroom collaboration can be highlighted during the conference. Results: The aggregated results of the two systematic reviews AND of the research lab/global classroom can now be a sound basis for 1) improving accessibility for students with SEN and 2) for adjusting teaching materials and concepts to the needs of the students with SEN - in order to create successful learning.

Keywords: digitalization, inclusion, inclusive media education, global classroom, systematic review

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Authors: Davoud Maleki

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Today, education and investment in human capital is a long-term investment without which the economy will be stagnant Stayed. Higher education represents a type of investment in human resources by providing and improving knowledge, skills and Attitudes help economic development. Providing efficient human resources by increasing the efficiency and productivity of people and on the other hand with Expanding the boundaries of knowledge and technology and promoting technology such as the responsibility of training human resources and increasing productivity and efficiency in High specialized levels are the responsibility of universities. Therefore, the university plays an infrastructural role in economic development and growth because education by creating skills and expertise in people and improving their ability.In recent decades, Iran's higher education system has been faced with many problems, therefore, scholars have looked for it is to identify and validate the causal factors affecting the responsiveness and productivity of non-governmental universities. The data in the qualitative part is the result of semi-structured interviews with 25 senior and middle managers working in the units It was Islamic Azad University of Tehran province, which was selected by theoretical sampling method. In data analysis, stepwise method and Analytical techniques of Strauss and Corbin (1992) were used. After determining the central category (answering for the sake of the beneficiaries) and using it in order to bring the categories, expressions and ideas that express the relationships between the main categories and In the end, six main categories were identified as causal factors affecting the university's responsiveness and productivity.They are: 1- Scientism 2- Human resources 3- Creating motivation in the university 4- Development based on needs assessment 5- Teaching process and Learning 6- University quality evaluation. In order to validate the response model obtained from the qualitative stage, a questionnaire The questionnaire was prepared and the answers of 146 students of Master's degree and Doctorate of Islamic Azad University located in Tehran province were received. Quantitative data in the form of descriptive data analysis, first and second stage factor analysis using SPSS and Amos23 software were analyzed. The findings of the research indicated the relationship between the central category and the causal factors affecting the response The results of the model test in the quantitative stage confirmed the generality of the conceptual model.

Keywords: accountability, productivity, non-governmental, universities, foundation data theory

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Authors: Charlotte Brenner, Fisayo Latilo, McKenna Causey

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This study explores the transformation of teacher candidates' beliefs regarding inclusion and inclusive teaching practices during their instructional and practicum experiences in the Canadian context. With the increasing diversity of schools, the study investigates how teacher candidates' beliefs impact their implementation of inclusive teaching practices, which are essential for meeting diverse student needs. The research examines the influence of teacher education programs, transformative learning experiences, and inclusive practicum placements on teacher candidates' beliefs about inclusion. Using a multiple case study approach, the study assesses teacher candidates' initial beliefs, documents changes in these beliefs after coursework on inclusion, and explores the supports and constraints affecting belief development in both university and practicum settings. Preliminary findings suggest that teacher candidates generally hold positive beliefs about inclusion at the outset of their teacher education programs. However, coursework and practicum experiences significantly shape their understanding of diversity, strategies for inclusion, and awareness of broader social issues related to inclusive classrooms. The research underscores the critical role of teacher education programs in shaping teacher candidates' beliefs about inclusion and highlights the value of transformative learning experiences and inclusive practicum placements in enhancing their understanding of equity and inclusion. Continued research is necessary to identify specific elements within courses and practicum experiences that promote positive beliefs about inclusive teaching practices, ultimately contributing to the creation of more equitable classrooms and improved student outcomes.

Keywords: inclusion, beliefs, teacher candidates, inclusive teaching practices

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Authors: Kumar Divyendra

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Underwater Sensor Networks (UWSNs) have wide applications in areas such as water quality monitoring, marine wildlife management etc. A typical UWSN system consists of a set of sensors deployed randomly underwater which communicate with each other using acoustic links. RF communication doesn't work underwater, and GPS too isn't available underwater. Additionally Automated Underwater Vehicles (AUVs) are deployed to collect data from some special nodes called Cluster Heads (CHs). These CHs aggregate data from their neighboring nodes and forward them to the AUVs using optical links when an AUV is in range. This helps reduce the number of hops covered by data packets and helps conserve energy. We consider the three-dimensional model of the UWSN. Nodes are initially deployed randomly underwater. They attach themselves to the surface using a rod and can only move upwards or downwards using a pump and bladder mechanism. We use graph theory concepts to maximize the coverage volume while every node maintaining connectivity with at least one surface node. We treat the surface nodes as landmarks and each node finds out its hop distance from every surface node. We treat these hop-distances as coordinates and use them for AUV navigation. An AUV intending to move closer to a node with given coordinates moves hop by hop through nodes that are closest to it in terms of these coordinates. In absence of GPS, multiple different approaches like Inertial Navigation System (INS), Doppler Velocity Log (DVL), computer vision-based navigation, etc., have been proposed. These systems have their own drawbacks. INS accumulates error with time, vision techniques require prior information about the environment. We propose a method that makes use of the earth's magnetic field values for navigation and combines it with other methods that simultaneously increase the coverage volume under the UWSN. The AUVs are fitted with magnetometers that measure the magnetic intensity (I), horizontal inclination (H), and Declination (D). The International Geomagnetic Reference Field (IGRF) is a mathematical model of the earth's magnetic field, which provides the field values for the geographical coordinateson earth. Researchers have developed an inverse deep learning model that takes the magnetic field values and predicts the location coordinates. We make use of this model within our work. We combine this with with the hop-by-hop movement described earlier so that the AUVs move in such a sequence that the deep learning predictor gets trained as quickly and precisely as possible We run simulations in MATLAB to prove the effectiveness of our model with respect to other methods described in the literature.

Keywords: clustering, deep learning, network backbone, parallel computing

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Authors: Ari Prasetyo, Taufik Faturohman

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The COVID-19 pandemic in Indonesia is part of the ongoing worldwide pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was confirmed to have spread to Indonesia on 2 March 2020. Moreover, the government of Indonesia has been conducting a local lockdown to limit people's movement from one city to another city. Therefore, this situation has impact on business operation, especially on highway companies listed on the Indonesia stock exchange. This study evaluates and measures three companies’ financial performance and health conditions before and during the COVID-19 pandemic from 2016 – 2020. The measurement is conducted by using financial ratio analysis and the Altman Z-score method. The ratio used to measure the financial ratio analysis is taken from the decree of the Ministry of SOE’s KEP-100/MBU/2002 about the company’s health level condition. From the decree, there are eight financial ratios used such as return on equity (ROE), return on investment (ROI), current ratio, cash ratio, collection period, inventory turnover, total asset turnover, and total equity to total asset. Altman Z-score is used to calculate the financial distress condition. The result shows that the highway companies for the period 2016 – 2020 are as follows: PT Jasa Marga (Persero) Tbk (AA, BB, BB, BB, C), PT Citra Marga Nusaphala Persada Tbk (BB, AA, BB, BBB, C), and PT Nusantara Infrastructure Tbk (BB, BB, AA, BBB, C). In addition, the Altman Z-score assessment performed in 2016-2020 shows that PT Jasa Marga (Persero) Tbk was in the grey zone area for 2015-2018 and in the distress zone for 2019-2020. PT Citra Marga Nusaphala Persada Tbk was in the grey zone area for 2015-2019 and in the distress zone for 2020. PT Nusantara Infrastructure Tbk was in the grey zone area for 2015-2018 and in the distress zone for 2019-2020.

Keywords: financial performance, financial ratio, Altman Z-score, financial distress, highway company

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Authors: Mohammed Nasir Kajama, Ngozi Claribelle Nwogu, Edward Gobina

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Pt/γ-Al2O3 membrane catalysts were prepared via an evaporative-crystallization deposition method. The obtained Pt/γ-Al2O3 catalyst activity was tested after characterization (SEM-EDAX observation, BET measurement, permeability assessment) in the catalytic oxidation of selected volatile organic compound (VOC) i.e. propane, fed in mixture of oxygen. The VOC conversion (nearly 90%) obtained by varying the operating temperature showed that flow-through membrane reactor might do better in the abatement of VOCs.

Keywords: VOC combustion, flow-through membrane reactor, platinum supported alumina catalysts

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Authors: Lidia Lombardi

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Waste management in Europe and North America is evolving towards sustainable materials management, intended as a systemic approach to using and reusing materials more productively over their entire life cycles. Various waste management strategies are prioritized and ranked from the most to the least environmentally preferred, placing emphasis on reducing, reusing, and recycling as key to sustainable materials management. However, non-recyclable materials must also be appropriately addressed, and waste-to-energy (WtE) offers a solution to manage them, especially when a WtE plant is integrated within a complex system of waste and wastewater treatment plants and potential users of the output flows. To evaluate the environmental effects of such system integration, Life Cycle Assessment (LCA) is a helpful and powerful tool. LCA has been largely applied to the waste management sector, dating back to the late 1990s, producing a large number of theoretical studies and applications to the real world as support to waste management planning. However, LCA still has a fundamental role in helping the development of waste management systems supporting decisions. Thus, LCA was applied to evaluate the environmental performances of a Municipal Solid Waste (MSW) management system, with improved separate material collection and recycling and an integrated network of treatment plants including WtE, anaerobic digestion (AD) and also wastewater treatment plant (WWTP), for a reference study case area. The proposed system was compared to the actual situation, characterized by poor recycling, large landfilling and absence of WtE. The LCA results showed that the increased recycling significantly increases the environmental performances, but there is still room for improvement through the introduction of energy recovery (especially by WtE) and through its use within the system, for instance, by feeding the heat to the AD, to sludge recovery processes and supporting the water reuse practice. WtE offers a solution to manage non-recyclable MSW and allows saving important resources (such as landfill volumes and non-renewable energy), reducing the contribution to global warming, and providing an essential contribution to fulfill the goals of really sustainable waste management.

Keywords: anaerobic digestion, life cycle assessment, waste-to-energy, municipal solid waste

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Authors: Nikolett Deutsch, Éva Pintér, Péter Bagó, Miklós Hetényi

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Strategic technology management has emerged and evolved parallelly with strategic management paradigms. It focuses on the opportunity for organizations operating mainly in technology-intensive industries to explore and exploit technological capabilities upon which competitive advantage can be obtained. As strategic technology management involves multifunction within an organization, requires broad and diversified knowledge, and must be developed and implemented with business objectives to enable a firm’s profitability and growth, excellence in strategic technology management provides unique opportunities for organizations in terms of building a successful future. Accordingly, a framework supporting the evaluation of the technological readiness level of management can significantly contribute to developing organizational competitiveness through a better understanding of strategic-level capabilities and deficiencies in operations. In the last decade, several innovation maturity assessment models have appeared and become designated management tools that can serve as references for future practical approaches expected to be used by corporate leaders, strategists, and technology managers to understand and manage technological capabilities and capacities. The aim of this paper is to provide a comprehensive review of the state-of-the-art innovation maturity frameworks, to investigate the critical lessons learned from their application, to identify the similarities and differences among the models, and identify the main aspects and elements valid for the field and critical functions of technology management. To this end, a systematic literature review was carried out considering the relevant papers and articles published in highly ranked international journals around the 27 most widely known innovation maturity models from four relevant digital sources. Key findings suggest that despite the diversity of the given models, there is still room for improvement regarding the common understanding of innovation typologies, the full coverage of innovation capabilities, and the generalist approach to the validation and practical applicability of the structure and content of the models. Furthermore, the paper proposes an initial structure by considering the maturity assessment of the technological capacities and capabilities - i.e., technology identification, technology selection, technology acquisition, technology exploitation, and technology protection - covered by strategic technology management.

Keywords: innovation capabilities, innovation maturity models, technology audit, technology management, technology management maturity models

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Authors: Chun-Yu Chen, Kua-Rong Wu, Yu-Cheng Chen, Perng-Jy Tsai

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Cooking fumes are known containing polycyclic aromatic hydrocarbons (PAHs) and aldehydes, and some of them have been proven carcinogenic or possibly carcinogenic to humans. Considering their chronic health effects, long-term exposure data is required for assessing cooking workers’ lifetime health risks. Previous exposure assessment studies, due to both time and cost constraints, mostly were based on the cross-sectional data. Therefore, establishing a long-term exposure data has become an important issue for conducting health risk assessment for cooking workers. An approach was proposed in this study. Here, the generation rates of both PAHs and aldehydes from a cooking process were determined by placing a sampling train exactly under the under the exhaust fan under the both the total enclosure condition and normal operating condition, respectively. Subtracting the concentration collected by the former (representing the total emitted concentration) from that of the latter (representing the hood collected concentration), the fugitive emitted concentration was determined. The above data was further converted to determine the generation rates based on the flow rates specified for the exhaust fan. The determinations of the above generation rates were conducted in a testing chamber with a selected cooking process (deep-frying chicken nuggets under 3 L peanut oil at 200°C). The sampling train installed under the exhaust fan consisted respectively an IOM inhalable sampler with a glass fiber filter for collecting particle-phase PAHs, followed by a XAD-2 tube for gas-phase PAHs. The above was also used to sample aldehydes, however, installed with a filter pre-coated with DNPH, and followed by a 2,4-DNPH-cartridge for collecting particle-phase and gas-phase aldehydes, respectively. PAHs and aldehydes samples were analyzed by GC/MS-MS (Agilent 7890B), and HPLC-UV (HITACHI L-7100), respectively. The obtained generation rates of both PAHs and aldehydes were applied to the near-field/ far-field exposure model to estimate the exposures of cooks (the estimated near-field concentration), and helpers (the estimated far-field concentration). For validating purposes, both PAHs and aldehydes samplings were conducted simultaneously using the same sampling train at both near-field and far-field sites of the testing chamber. The sampling results, together with the use of the mixed-effect model, were used to calibrate the estimated near-field/ far-field exposures. In the present study, the obtained emission rates were further converted to emission factor of both PAHs and aldehydes according to the amount of food oil consumed. Applying the long-term food oil consumption records, the emission rates for both PAHs and aldehydes were determined, and the long-term exposure databanks for cooks (the estimated near-field concentration), and helpers (the estimated far-field concentration) were then determined. Results show that the proposed approach was adequate to determine the generation rates of both PAHs and aldehydes under various fan exhaust flow rate conditions. The estimated near-field/ far-field exposures, though were significantly different from that obtained from the field, can be calibrated using the mixed effect model. Finally, the established long-term data bank could provide a useful basis for conducting long-term exposure assessments for cooking workers exposed to PAHs and aldehydes.

Keywords: aldehydes, cooking oil fumes, long-term exposure assessment, modeling, polycyclic aromatic hydrocarbons (PAHs)

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Authors: Salima R. Rajwani, Tazeen Ali, Rubina Barolia, Yasmin Parpio, Nasreen Alwani, Salima B. Virani

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Introduction: Nurses and physicians have a critical role in initiating lifesaving interventions during cardiac arrest. It is important that timely delivery of high quality Cardio Pulmonary Resuscitation (CPR) with advanced resuscitation skills and management of cardiac arrhythmias is a key dimension of code during cardiac arrest. It will decrease the chances of patient survival if the healthcare professionals are unable to initiate CPR timely. Moreover, traditional training will not prepare physicians and nurses at a competent level and their knowledge level declines over a period of time. In this regard, simulation training has been proven to be effective in promoting resuscitation skills. Simulation teaching learning strategy improves knowledge level, and skills performance during resuscitation through experiential learning without compromising patient safety in real clinical situations. The purpose of the study is to evaluate the effectiveness of simulation training in Advanced Cardiac Life Support Courses by using the selfefficacy tool. Methods: The study design is a quantitative research design and non-randomized quasi-experimental study design. The study examined the effectiveness of simulation through self-efficacy in two instructional methods; one is Medium Fidelity Simulation (MFS) and second is Traditional Training Method (TTM). The sample size was 220. Data was compiled by using the SPSS tool. The standardized simulation based training increases self-efficacy, knowledge, and skills and improves the management of patients in actual resuscitation. Results: 153 students participated in study; CG: n = 77 and EG: n = 77. The comparison was done between arms in pre and post-test. (F value was 1.69, p value is <0.195 and df was 1). There was no significant difference between arms in the pre and post-test. The interaction between arms was observed and there was no significant difference in interaction between arms in the pre and post-test. (F value was 0.298, p value is <0.586 and df is 1. However, the results showed self-efficacy scores were significantly higher within experimental group in post-test in advanced cardiac life support resuscitation courses as compared to Traditional Training Method (TTM) and had overall (p <0.0001) and F value was 143.316 (mean score was 45.01 and SD was 9.29) verses pre-test result showed (mean score was 31.15 and SD was 12.76) as compared to TTM in post-test (mean score was 29.68 and SD was 14.12) verses pre-test result showed (mean score was 42.33 and SD was 11.39). Conclusion: The standardized simulation-based training was conducted in the safe learning environment in Advanced Cardiac Life Suport Courses and physicians and nurses benefited from self-confidence, early identification of life-threatening scenarios, early initiation of CPR, and provides high-quality CPR, timely administration of medication and defibrillation, appropriate airway management, rhythm analysis and interpretation, and Return of Spontaneous Circulation (ROSC), team dynamics, debriefing, and teaching and learning strategies that will improve the patient survival in actual resuscitation.

Keywords: advanced cardiac life support, cardio pulmonary resuscitation, return of spontaneous circulation, simulation

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Authors: Hossein Rezaie

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Academic institutions, esp. universities, have been known as cradles of learning and teaching great thinkers while creating the type of knowledge that is supposed to be bereft of utilitarian motives. Nonetheless, it seems that such intellectual centers have entered into a competition with each other for attracting the attention of potential clients. The traditional values of (higher) education such as nurturing criticality and fostering intellectuality in students have been replaced with strategic planning, quality assurance, performance assessment, and academic audits. Not being immune from the whims and wishes of marketization, the system of higher education in the UK has been recalibrated by policy makers to address the demand and supply of student education, academic research and other university activities on the basis of monetary factors. As an immediate example in this vein, the Russell Group in the UK, which is comprised of 24 leading UK research universities, has explicitly expressed it policy on its official website as follows: ‘Russell Group universities are global businesses competing for staff, students and funding with the best in the world’. Furthermore, certain attempts have been made to corporatize the system of HE which have been manifested in remodeling of university governing bodies on corporate lines and developing measurement scales for indicating the performance of teaching practitioners. Nevertheless, it seems that such structural changes in policies toward the system of HE have bearing on the practices of practitioners and educators as well as the identity of students who are the customers of educational services. The effects of marketization have been examined mainly in terms of students’ perceptions and motivation, institutional policies and university management. However, the teaching practitioner side seems to be an under-studied area with regard to any changes in its expectations, satisfaction and perception of professional identity in the aftermath of introducing market-wise values into HE of the UK. As a result, this research aims to investigate the possible outcomes of market-driven values on the practitioner side of HE in the UK and finally seeks to address the following research questions: 1-How is the change in the mission of HE in the UK reflected in institutional documents? 1-A- How is the change of mission represented in job adverts? 1-B- How is the change of mission represented in university prospectuses? 2-How are teaching practitioners represented regarding their roles and obligations in the prospectuses and job ads published by UK HE institutions? In order to address these questions, the researcher will analyze 30 prospectuses and job ads published by Russel Group universities by taking Critical Discourse Analysis as his point of departure and the analytical methods of genre analysis and Systemic Functional Linguistics to probe into the generic features and representation of participants, in this case teaching practitioners, in the selected corpus.

Keywords: higher education, job advertisements, marketization of higher education, prospectuses

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Authors: Tudor Deaconescu, Andrea Deaconescu

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The utilization of pneumatic muscles in the actuation of industrial systems is still in its early stages, hence studies on the constructive solutions which include an assessment of their functional performance with a focus on one of the most important characteristics-energy efficiency are required. A quality indicator that adequately reflects the energy efficiency of an actuator is the energy-to-mass ratio. This ratio is computed in the paper for various types and sizes of pneumatic muscles manufactured by Festo, and is subsequently compared to the similar ratios determined for two categories of pneumatic cylinders.

Keywords: pneumatic cylinders, pneumatic muscles, energy-to-mass ratio, muscle stroke

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Authors: Yash Jain

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The US Center for Disease Control has recommended wearing masks to slow the spread of the virus. The research uses a video feed from a camera to conduct real-time classifications of whether or not a human is correctly wearing a mask, incorrectly wearing a mask, or not wearing a mask at all. Utilizing two distinct datasets from the open-source website Kaggle, a mask detection network had been trained. The first dataset that was used to train the model was titled 'Face Mask Detection' on Kaggle, where the dataset was retrieved from and the second dataset was titled 'Face Mask Dataset, which provided the data in a (YOLO Format)' so that the TinyYoloV3 model could be trained. Based on the data from Kaggle, two machine learning models were implemented and trained: a Tiny YoloV3 Real-time model and a two-stage neural network classifier. The two-stage neural network classifier had a first step of identifying distinct faces within the image, and the second step was a classifier to detect the state of the mask on the face and whether it was worn correctly, incorrectly, or no mask at all. The TinyYoloV3 was used for the live feed as well as for a comparison standpoint against the previous two-stage classifier and was trained using the darknet neural network framework. The two-stage classifier attained a mean average precision (MAP) of 80%, while the model trained using TinyYoloV3 real-time detection had a mean average precision (MAP) of 59%. Overall, both models were able to correctly classify stages/scenarios of no mask, mask, and incorrectly worn masks.

Keywords: datasets, classifier, mask-detection, real-time, TinyYoloV3, two-stage neural network classifier

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Authors: Lai Wenfang

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Tthis study will describe how to use artificial intelligence (AI) technology to build the user-oriented platform for integrated archival service. The platform will be launched in 2020 by the National Archives Administration (NAA) in Taiwan. With the progression of information communication technology (ICT) the NAA has built many systems to provide archival service. In order to cope with new challenges, such as new ICT, artificial intelligence or blockchain etc. the NAA will try to use the natural language processing (NLP) and machine learning (ML) skill to build a training model and propose suggestions based on the data sent to the platform. NAA expects the platform not only can automatically inform the sending agencies’ staffs which records catalogues are against the transfer or destroy rules, but also can use the model to find the details hidden in the catalogues and suggest NAA’s staff whether the records should be or not to be, to shorten the auditing time. The platform keeps all the users’ browse trails; so that the platform can predict what kinds of archives user could be interested and recommend the search terms by visualization, moreover, inform them the new coming archives. In addition, according to the Archives Act, the NAA’s staff must spend a lot of time to mark or remove the personal data, classified data, etc. before archives provided. To upgrade the archives access service process, the platform will use some text recognition pattern to black out automatically, the staff only need to adjust the error and upload the correct one, when the platform has learned the accuracy will be getting higher. In short, the purpose of the platform is to deduct the government digital transformation and implement the vision of a service-oriented smart government.

Keywords: artificial intelligence, natural language processing, machine learning, visualization

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Authors: Morteza Rahiminejad

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There are over 1200 cities and municipalities all around Iran, including 30 mega cities, which municipal organizations, Interior ministries, and city councils supervise. Even so, there has been neither any research about the process of success nor performance assessment in municipalities. In this research an attempt is made to build a comprehensive theory (or model) to show the reasons or success process among the local governments. The present research is based on the contingency approach in which the relevant circumstances are important, and both environment and situations call for their own management methods. The methodology of research is grounded theory, which uses Atlas.ti software as a tool.

Keywords: success, municipality, Iran, theory building

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Rabie Fadil, Parshuram Aarotale, Shubha Majumder, Bijay Guargain

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Hemorrhage is the loss of blood from the circulatory system and leading cause of battlefield and postpartum related deaths. Early detection of hemorrhage remains the most effective strategy to reduce mortality rate caused by traumatic injuries. In this study, we investigated the physiological changes via non-invasive cardiac signals at rest and under different hemorrhage conditions simulated through graded lower-body negative pressure (LBNP). Simultaneous electrocardiogram (ECG), photoplethysmogram (PPG), blood pressure (BP), impedance cardiogram (ICG), and phonocardiogram (PCG) were acquired from 10 participants (age:28 ± 6 year, weight:73 ± 11 kg, height:172 ± 8 cm). The LBNP protocol consisted of applying -20, -30, -40, -50, and -60 mmHg pressure to the lower half of the body. Beat-to-beat heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean aerial pressure (MAP) were extracted from ECG and blood pressure. Systolic amplitude (SA), systolic time (ST), diastolic time (DT), and left ventricle Ejection time (LVET) were extracted from PPG during each stage. Preliminary results showed that the application of -40 mmHg i.e. moderate stage simulated hemorrhage resulted significant changes in HR (85±4 bpm vs 68 ± 5bpm, p < 0.01), ST (191 ± 10 ms vs 253 ± 31 ms, p < 0.05), LVET (350 ± 14 ms vs 479 ± 47 ms, p < 0.05) and DT (551 ± 22 ms vs 683 ± 59 ms, p < 0.05) compared to rest, while no change was observed in SA (p > 0.05) as a consequence of LBNP application. These findings demonstrated the potential of cardiac signals in detecting moderate hemorrhage. In future, we will analyze all the LBNP stages and investigate the feasibility of other physiological signals to develop a predictive machine learning model for early detection of hemorrhage.

Keywords: blood pressure, hemorrhage, lower-body negative pressure, LBNP, machine learning

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Authors: Carolin Schulze

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Characterized by a positive interdependence of learners, cooperative learning (CL) is one possibility of successfully dealing with the increasing heterogeneity of students. Various positive effects of CL on the mental, physical and social health of students have already been documented. However, this structure is still rarely used in physical education (PE). Moreover, there is a lack of information about factors that determine the successful implementation of CL in PE. Therefore, the objective of the current study was to find out factors that determine the successful implementation of CL in PE using a digital questionnaire that was conducted from November to December 2022. In addition to socio-demographic data (age, gender, teaching experience, and education level), frequency of using CL, implementation strategies (theory-led, student-centred), and positive and negative effects of CL were measured. Furthermore, teachers were asked to rate the success of implementation on a 6-point rating scale (1-very successful to 6-not successful at all). For statistical analysis, multiple linear regression was performed, setting the success of implementation as the dependent variable. A total of 224 teachers (mean age=44.81±10.60 years; 58% male) took part in the current study. Overall, 39% of participants stated that they never use CL in their PE classes. Main reasons against the implementations of CL in PE were no time for preparation (74%) or for implementation (61%) and high heterogeneity of students (55%). When using CL, most of the reported difficulties are related to uncertainties about the correct procedure (54%) and the heterogeneous performance of students (54%). The most frequently mentioned positive effect was increased motivation of students (42%) followed by an improvement of psychological abilities (e.g. self-esteem, self-concept; 36%) and improved class cohesion (31%). Reported negative effects were unpredictability (29%), restlessness (24%), confusion (24%), and conflicts between students (17%). The successful use of CL is related to a theory-based preparation (e.g., heterogeneous formation of groups, use of rules and rituals) and a flexible implementation tailored to the needs and conditions of students (e.g., the possibility of individual work, omission of CL phases). Compared to teachers who solely implemented CL theory-led or student-adapted, teachers who switched from theory-led preparation to student-centred implementation of CL reported more successful implementation (t=5.312; p<.001). Neither frequency of using CL in PE nor the gender, age, the teaching experience, or the education level of the teacher showed a significant connection with the successful use of CL. Corresponding to the results of the current study, it is advisable that teachers gather enough knowledge about CL during their education and to point out the need to adapt the learning structure according to the diversity of their students. In order to analyse implementation strategies of teachers more deeply, qualitative methods and guided interviews with teachers are needed.

Keywords: diversity, educational technology, physical education, teaching styles

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Authors: Zongping Wang, Chengjun Cui, Jiacun Wang

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The concept of intelligence has been widely used to access an individual's cognitive abilities to learn, form concepts, understand, apply logic, and reason. According to the multiple intelligence theory, there are eight distinguished types of intelligence. One of them is the bodily-kinaesthetic intelligence that links to the capacity of an individual controlling his body and working with objects. Motor intelligence, on the other hand, reflects the capacity to understand, perceive and solve functional problems by motor behavior. Both bodily-kinaesthetic intelligence and motor intelligence refer directly or indirectly to bodily capacity. Inspired by these two intelligence concepts, this paper introduces motional intelligence (MI). MI is two-fold. (1) Body strength, which is the capacity of various organ functions manifested by muscle activity under the control of the central nervous system during physical exercises. It can be measured by the magnitude of muscle contraction force, the frequency of repeating a movement, the time to finish a movement of body position, the duration to maintain muscles in a working status, etc. Body strength reflects the objective of MI. (2) Level of psychiatric willingness to physical events. It is a subjective thing and determined by an individual’s self-consciousness to physical events and resistance to fatigue. As such, we call it subjective MI. Subjective MI can be improved through education and proper social events. The improvement of subjective MI can lead to that of objective MI. A quantitative score of an individual’s MI is motional quotient (MQ). MQ is affected by several factors, including genetics, physical training, diet and lifestyle, family and social environment, and personal awareness of the importance of physical exercise. Genes determine one’s body strength potential. Physical training, in general, makes people stronger, faster and swifter. Diet and lifestyle have a direct impact on health. Family and social environment largely affect one’s passion for physical activities, so does personal awareness of the importance of physical exercise. The key to the success of the MQ study is developing an acceptable and efficient system that can be used to assess MQ objectively and quantitatively. We should apply different accessing systems to different groups of people according to their ages and genders. Field test, laboratory test and questionnaire are among essential components of MQ assessment. A scientific interpretation of MQ score is part of an MQ assessment system as it will help an individual to improve his MQ. IQ (intelligence quotient) and EQ (emotional quotient) and their test have been studied intensively. We argue that IQ and EQ study alone is not sufficient for an individual’s all round development. The significance of MQ study is that it offsets IQ and EQ study. MQ reflects an individual’s mental level as well as bodily level of intelligence in physical activities. It is well-known that the American Springfield College seal includes the Luther Gulick triangle with the words “spirit,” “mind,” and “body” written within it. MQ, together with IQ and EQ, echoes this education philosophy. Since its inception in 2012, the MQ research has spread rapidly in China. By now, six prestigious universities in China have established research centers on MQ and its assessment.

Keywords: motional Intelligence, motional quotient, multiple intelligence, motor intelligence, all round development

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Authors: Aliya Kamilyevna Salahova

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This study examines the effectiveness of the Kids Science Labs intervention program, based on STEM, in fostering independent thinking among preschool and elementary school children and its influence on their academic achievement. Through a comprehensive methodology involving interviews, surveys, observations, case studies, and statistical tests, data were collected from various sources to accurately analyze the program's effects. The findings indicate a significant positive impact on children's independent thinking abilities, leading to improved academic performance in mathematics and science, enhanced learning motivation, and a propensity to critically evaluate problem-solving approaches. This research contributes to the theoretical understanding of how STEM activities can foster independent thinking and academic success in young children, providing valuable insights for the development of educational programs. Introduction: The goal of this study is to investigate the influence of the Kids Science Labs intervention program, grounded in STEM, on the development of independent thinking skills among preschool and elementary school children. By addressing this objective, we aim to explore the program's potential to enhance academic performance in mathematics and science. The study's findings have theoretical significance as they shed light on the ways in which STEM activities can foster independent thinking in young children, thus enabling educators to design effective learning programs that promote academic success. Methodology: This study employs a robust methodology that includes interviews, surveys, observations, case studies, and statistical tests. These methods were carefully selected to collect comprehensive data from multiple sources, such as documents and records, ensuring a thorough analysis of the program's effects. The use of diverse data collection and analysis procedures facilitated an in-depth exploration of the research questions and yielded reliable results. Results: The results indicate that children participating in the Kids Science Labs program experienced a sustained positive impact on their independent thinking abilities. Moreover, these children demonstrated improved academic performance in mathematics and science, displaying higher learning motivation and the capacity to critically evaluate problem-solving methods and seek optimal solutions. Theoretical Importance: This study contributes significantly to the existing theoretical knowledge by elucidating how STEM activities can foster independent thinking and enhance academic success in preschool and elementary school children. The findings have practical implications for educators, empowering them to develop learning programs that stimulate independent thinking, leading to improved academic performance in young children. Discussion: The findings of this research affirm that the Kids Science Labs intervention program is highly effective in fostering independent thinking among preschool and elementary school children. The program's positive impact extends to improved academic performance in mathematics and science, highlighting its potential to enhance learning outcomes. Educators can leverage these findings to develop educational programs that promote independent thinking and elevate academic achievement in young children. Conclusion: In conclusion, the Kids Science Labs intervention program has been found to be highly effective in fostering independent thinking among preschool and elementary school children. Furthermore, participation in the program correlates with improved academic performance in mathematics and science. The study's outcomes underscore the importance of developing educational initiatives that stimulate independent thinking in young children, thereby enhancing their academic success.

Keywords: STEM in preschool, STEM in elementary school, kids science labs, independent thinking, STEM activities in early childhood education

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Authors: Li-hsing Shih, Wei-Jen Hsu

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Recently, the sale of electrical vehicles (EVs) has increased dramatically due to maturing technology development and decreasing cost. Governments of many countries have made regulations and policies in favor of EVs due to their long-term commitment to net zero carbon emissions. However, due to uncertain factors such as the future price of EVs, forecasting the future market share of EVs is a challenging subject for both the auto industry and local government. This study tries to forecast the market share of EVs using conjoint models and Monte Carlo simulation. The research is conducted in three phases. (1) A conjoint model is established to represent the customer preference structure on purchasing vehicles while five product attributes of both EV and internal combustion engine vehicles (ICEV) are selected. A questionnaire survey is conducted to collect responses from Taiwanese consumers and estimate the part-worth utility functions of all respondents. The resulting part-worth utility functions can be used to estimate the market share, assuming each respondent will purchase the product with the highest total utility. For example, attribute values of an ICEV and a competing EV are given respectively, two total utilities of the two vehicles of a respondent are calculated and then knowing his/her choice. Once the choices of all respondents are known, an estimate of market share can be obtained. (2) Among the attributes, future price is the key attribute that dominates consumers’ choice. This study adopts the assumption of a learning curve to predict the future price of EVs. Based on the learning curve method and past price data of EVs, a regression model is established and the probability distribution function of the price of EVs in 2030 is obtained. (3) Since the future price is a random variable from the results of phase 2, a Monte Carlo simulation is then conducted to simulate the choices of all respondents by using their part-worth utility functions. For instance, using one thousand generated future prices of an EV together with other forecasted attribute values of the EV and an ICEV, one thousand market shares can be obtained with a Monte Carlo simulation. The resulting probability distribution of the market share of EVs provides more information than a fixed number forecast, reflecting the uncertain nature of the future development of EVs. The research results can help the auto industry and local government make more appropriate decisions and future action plans.

Keywords: conjoint model, electrical vehicle, learning curve, Monte Carlo simulation

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Authors: Suantak Demkhosei Vaiphei

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Mental illness is still considered as an illness not to be treated, resulting India becoming the most depressed country in the world. At present, 150 million Indians are suffering from mental illness and desperately in need of immediate care assessment for their mental health condition. However, only 0.06 per cent of India’s health budget is devoted to mental health treatment, in which the available data suggests that the state of spending the sanctioned budget in this regard is abysmal. Lack of awareness, ignorance, social stigma, and discriminations becomes the underlying factors for worsening the individual mental health conditions. Unfortunately, India becomes the most depressed country in the world, which is hugely affected by anxiety, schizophrenia, and bipolar disorder followed by China and USA as per the latest World Health Organization report. The National Care of Medical Health stated that at least 6.5 per cent of the Indian populations are under serious mental disorder both in the rural and the urban areas’Mental health is the integral part of health and can be affected by a range of psychosocial-economic factors that need comprehensive strategically approach for promotion, prevention, treatment, and recovery. In a low- and middle-income country like India, the advance progress in mental health service is visible consistently slow and minimal. Some of the major barriers can be seen in the existing public health priorities and its influence on funding; challenges to delivery of basic mental health care in the primary care settings; the minimal numbers of well-trained professionals in the area of mental health care; and lack of mental health perspective in public-health leadership. The existing barriers according to WHO (2007) are; lack of funding for mental health services is the core barrier in implementing quality mental health services, including inadequate coordinated and consensus based national mental health advocacy and plans, the absence of mental health in major donor priorities, marketing of expensive pharmaceuticals by industry, cost-effectiveness information on mental health services that is unknown to senior decision-makers and social stigma among others. Moreover, lack of strong mental health advocacy in countries to increase resources for mental health services and the role of social stigma and the view that mental health is a private responsibility are also the two barriers to mental health.

Keywords: mental health, depression, stigma, barriers

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Authors: Allison Tucker, Carolyn Clarke, Erin Keith

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Introduction: In education, the determination to uncover privileged practices requires critical reflection to be placed at the center of both pre-service and in-service teacher education. Confronting deficit thinking about children’s abilities and shifting to holding an image of the child as capable and competent is necessary for teachers to engage in responsive pedagogy that meets children where they are in their learning and builds on strengths. This paper explores the ways in which early elementary teachers' perceptions of the assets of children might shift through the pedagogical use of video clubs. Video club is a pedagogical practice whereby teachers record and view short videos with the intended purpose of deepening their practices. The use of video club as a learning tool has been an extensively documented practice. In this study, a video club is used to watch short recordings of playing children to identify the assets of their students. Methodology: The study on which this paper is based asks the question: What are the ways in which teachers’ image of the child and teaching practices evolve through the use of video club focused on the strengths of children demonstrated during play? Using critical reflection, it aims to identify and describe participants’ experiences of examining their personally held image of the child through the pedagogical tool video club, and how that image influences their practices, specifically in implementing play pedagogy. Teachers enrolled in a graduate-level play pedagogy course record and watch videos of their own students as a means to notice and reflect on the learning that happens during play. Using a co-constructed viewing protocol, teachers identify student strengths and consider their pedagogical responses. Video club provides a framework for teachers to critically reflect in action, return to the video to rewatch the children or themselves and discuss their noticings with colleagues. Critical reflection occurs when there is focused attention on identifying the ways in which actions perpetuate or challenge issues of inherent power in education. When the image of the child held by the teacher is from a deficit position and is influenced by hegemonic dimensions of practice, critical reflection is essential in naming and addressing power imbalances, biases, and practices that are harmful to children and become barriers to their thriving. The data is comprised of teacher reflections, analyzed using phenomenology. Phenomenology seeks to understand and appreciate how individuals make sense of their experiences. Teacher reflections are individually read, and researchers determine pools of meaning. Categories are identified by each researcher, after which commonalities are named through a recursive process of returning to the data until no more themes emerge or saturation is reached. Findings: The final analysis and interpretation of the data are forthcoming. However, emergent analysis of the data collected using teacher reflections reveals the ways in which the use of video club grew teachers’ awareness of their image of the child. It shows video club as a promising pedagogical tool when used with in-service teachers to prompt opportunities for play and to challenge deficit thinking about children and their abilities to thrive in learning.

Keywords: asset-based teaching, critical reflection, image of the child, video club

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Authors: Salam Kodsi

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In this research, we sought to focus on constructive play and examine its components in the context of two different educational approaches: Waldorf and normative schools. When they are free to choose, construction is one of the forms of play most favored by children. Its short-term and long-term cognitive contributions are apparent in various areas of development. The lack of empirical studies about play in Waldorf schools, which addresses the possibility of this incidental learning inspired the need to enrich the body of existing knowledge. 90 children (4-6 yrs.old) four preschools ( two normative, two Waldorf) participated in a small homogeneous city. Naturalistic observations documented the time frame, physical space, and construction materials related to the freeform building; processes of construction among focal representative children and its products. The study’s main finding with respect to the construction output points to a connection between educational approach and level of construction sophistication. Higher levels of sophistication were found at the Waldorf preschools than at the mainstream preschools. This finding emerged due to the differences in the level of sophistication among the older children in the two types of preschools, while practically no differences emerged among the younger children. Discussion of the research findings considered the differences between the play environments in terms of time, physical space, and construction materials. The construction processes were characterized according to the design model stages. The construction output was characterized according to the sophistication scale dimensions and the connections between approach, age and gender, and sophistication level.

Keywords: constructive play, preschool, design process model, complexity

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Authors: Eyitayo Francis Adanlawo

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Television is one of humanity’s most important means of communication, a channel through which societal norms and values can be transferred to youths. The imagination created by foreign television programmes ultimately leads to strong emotional responses. Though some foreign films and programmes are educational in nature, the view that the majority of them are inimical to the youths’ positive-believe-system is rife. This has been occasioned by the adoption of repugnant alien cultures, imitation of vulgar slangs, weird hairdo and most visibly an adjustment in values. This study theoretically approaches two research questions: do youths act out the life style of characters seeing in foreign films? Is moral decadence, indiscipline, and vulgar habits being the results of the contents of foreign programmes and films? To establish the basis for relating foreign films watched to social vices as violence, sexual pervasiveness, cultural and traditional moral pollution on youths; Observational learning Theory and Reinnforcement Theory were utilized to answer the research questions and established the effect of foreign films content on youths. We conclude that constant showcasing of violent themes was highly responsible for the upsurge in social vices prevalent among the youths and can destroy the basis of the societal, cultural orientation. Recommendations made range from the need for government to halt the importation of foreign films not censored; the need for local films to portray more positive messages and the need for concrete steps to be taken to eradicate or minimise the use of programme capable of exerting negative influence.

Keywords: media (television), moral decadence, youths, values, observation learning theory, reinforcement theory

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Authors: Avani Jain, Hasmukh Jain, S. Shelley, M. Indirani, Shilpa Kalal, Jayakanth Amalachandran

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Aim of the Study: To assess the effect of orally administered Itopride on gall bladder ejection fraction by fatty meal cholescintigraphy in patients with diabetes. Materials and Methods: Thirty patients (20 males, 10 females, mean age 46+10 yrs) with history of diabetes mellitus (mean duration 4.8+4.1 yrs, fasting blood glucose level 130+35 mg/dl and 2-hours post-prandial blood glucose level 196+76 mg/dl) and found to have gall bladder dysfunction on fatty-meal stimulated cholescintigraphy were selected for this study. These patients underwent a repeat cholescintigraphy similar to baseline study, with 50 mg of Itopride orally along with fatty meal. Pre- and post-Itopride GBEF were then compared to assess the effect of Itopride on gall bladder contraction. Results: Out of these 30 patients, 2 had dyskinetic, 4 had akinetic, 22 had moderately hypokinetic and the remaining 2 had hypokinetic gall bladder function in the baseline study with > 60% GBEF being taken as the normal value. Mean percentage of GBEF in the baseline study was 32%+13% and the mean percentage of GBEF in the post-Itopride study was 57%+17% with change in mean percentage of GBEF being 24%+21%. GBEF of the “baseline study” was significantly lower as compared to GBEF in the “post-Itopride study” (p < 0.05). Conclusion: Diabetic patients with biliary-type pain often tend to have impaired gallbladder function. Cholescintigraphy with fatty meal-stimulation is a simple, cheap and useful investigation for assessment of gallbladder dysfunction in these patients, before any structural changes occur within the lumen or wall of the gall bladder. Improvement in gallbladder ejection fraction after oral administration of a single dose of Itopride, a newer prokinetic drug with fewer side effects, as assessed by cholescintigraphy, provides enough evidence of future therapeutic response. Administration of Itopride, in therapeutic dosage, therefore may be expected to cause significant improvement in gallbladder ejection fraction and hence prolong stone formation within the gall bladder and also prevent the associated long term complications. Hence, based on scintigraphic evidence, Itopride may be recommended, by clinicians, for management of symptomatic diabetic patients having gallbladder dysfunction.

Keywords: itopride, gall bladder ejection fraction, fatty meal, cholescintigraphy, diabetes

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Authors: Lebeza Alemu Tenaw, Fei Wan Ngai

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Background: Postpartum depression is the most common mental health disorder that occurs after childbirth, and it is more prevalent among teenage mothers compared to adults. Although there is emerging evidence suggesting psychosocial interventions can decrease postpartum depression, there are no consistent findings regarding the effectiveness of these interventions, especially for teenage mothers. The current review aimed to investigate the effectiveness of psychosocial interventions in preventing postpartum depression among teenage mothers. Methods: The Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) manual was implemented to select articles from online databases. The articles were searched using the Population, Intervention, Control, and Outcome (PICO) model. The quality of the articles was assessed using the Cochrane Collaboration Risk of Bias assessment tool. The statistical analyses were performed using Stata 17, and the effect size was estimated using the standard mean difference score of depression between the intervention and control groups. Heterogeneity between the studies was assessed through the I2 statistic and Q statistic, while the publication bias was evaluated using the asymmetry of the funnel plot and Egger's test. Results: In this systematic review, a total of nine articles were included. While psychosocial interventions demonstrated in reducing the risk of postpartum depression compared to usual maternal care, it is important to note that the mean difference score of depression was significant in only three of the included studies. The overall meta-analysis finding revealed that psychosocial interventions were effective in preventing postpartum depression, with a pooled effect size of -0.5 (95% CI: -0.95, -0.06) during the final time postpartum depression assessment. The heterogeneity level was found to be substantial, with an I2 value of 82.3%. However, no publication bias was observed. Conclusion: The review findings suggest that psychosocial interventions initiated during the late antenatal and early postnatal periods effectively prevent postpartum depression. The interventions were found to be more beneficial during the first three months of the postpartum period. However, this review also highlighted that there is a scarcity of interventional studies conducted in low-income countries, indicating the need for further studies in diverse communities.

Keywords: teenage pregnancy, postpartum depression, review

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Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

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Authors: Orhan Akınoğlu, Arif Çömek, Ersin Elmacı, Tuğba Gündoğdu

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The concept map is known to be a powerful tool to organize the ideas and concepts of an individuals’ mind. This tool is a kind of visual map that illustrates the relationships between the concepts of a certain subject. The effect of concept mapping on cognitive and affective qualities is one of the research topics among educational researchers for last decades. We educators want to utilize it both as an instructional tool or an assessment tool in classes. For that reason, this study aimed to determine the effect of concept mapping as a learning strategy in science classes on students’ academic achievement and attitude. The research employed a randomized pre-test post-test control group design. Data collected from 60 sixth grade students participated in the study from a randomly selected primary school in Turkey. Sixth-grade classes of the school were analyzed according to students’ academic achievement, science attitude, gender, mathematics, science courses grades, and their GPAs before the implementation. Two of the classes found to be equivalent (t=0,983, p>0,05) and one of them was defined as experimental and the other one control group randomly. During a 5-weeks period, the experimental group students (N=30) used the paper-based concept mapping method while the control group students (N=30) were taught with the traditional approach according to the science and technology education curriculum for light and sound subject. Both groups were taught by the same teacher who is experienced using concept mapping in science classes. Before the implementation, the teacher explained the theory of the concept maps and showed how to create paper-based concept mapping individually to the experimental group students for two hours. Then for two following hours she asked them to create some concept maps related to their former science subjects and gave them feedback by reviewing their concept maps to be sure that they can create during the implementation. The data were collected by science achievement test, science attitude scale and personal information form. Science achievement test and science attitude scale were implemented as pre-test and post-test while personal information form was implemented just as once. The reliability coefficient of the achievement test was KR20=0,76 and Cronbach’s Alpha of the attitude scale was 0,89. SPSS statistical software was used to analyze the data. According to the results, there was a statistically significant difference between the experimental and control group for academic achievement but not for attitude. The experimental group had significantly greater gains from academic achievement test than the control group (t=0,02, p<0,05). The findings showed that the paper-and-pencil concept mapping can be used as an effective method for students’ academic achievement in science classes. The results have implications for further researches.

Keywords: concept mapping, science education, constructivism, academic achievement, science attitude

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Authors: B. El Fadil, R. Najar

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STEM education is promoted by many scholars and curricula around the world, but it is not yet well established in the province of Quebec in Canada. In addition, effective instructional STEM activities and design methods are required to ensure that students and teachers' needs are being met. One potential method is the Engineering Design Process (EDP), a methodology that emphasizes the importance of creativity and collaboration in problem-solving strategies. This article reports on a case study that focused on using the EDP to develop instructional materials by means of making a technological artifact to teach mathematical variables and functions at the secondary level. The five iterative stages of the EDP (design, make, test, infer, and iterate) were integrated into the development of the course materials. Data was collected from different sources: pre- and post-questionnaires, as well as a working document dealing with pupils' understanding based on designing, making, testing, and simulating. Twenty-four grade seven (13 years old) students in Northern Quebec participated in the study. The findings of this study indicate that STEM activities have a positive impact not only on students' engagement in classroom activities but also on learning new mathematical concepts. Furthermore, STEM-focused activities have a significant effect on problem-solving skills development in an interdisciplinary approach. Based on the study's results, we can conclude, inter alia, that teachers should integrate STEM activities into their teaching practices to increase learning outcomes and attach more importance to STEM-focused activities to develop students' reflective thinking and hands-on skills.

Keywords: engineering design process, motivation, stem, integration, variables, functions

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