Search results for: learning disability health review

Authors: Scott McCutcheon, Karen Schreder

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Higher education is facing a new reality. Student connection with coursework, instructor, and peers competes with online gaming, screen time, and instant gratification. Pedagogical methods that align student connection and critical thinking in a content-rich environment are important in supporting student learning, a sense of community, and emotional health. This mixed methods study focuses on exploring how the use of educational escape rooms (EERs) can support student learning and learning retention while fostering engagement with each other, the instructor, and the coursework. EERs are content-specific, cooperative, team-based learning activities designed to be completed within a short segment of a typical class. Data for the study was collected over three semesters and includes results from the implementation of EERs in science-based and liberal studies courses taught by different instructors. Twenty-seven students were surveyed regarding their learning experiences with this pedagogy, and interviews with four student volunteers were conducted to add depth to the survey data. A key finding from this research indicates that students felt more connected to each other and the course content after participating in the escape room activity. Additional findings point to increased engagement and comprehension of the class material. Data indicates that the use of an EER pedagogy supports student engagement, well-being, subject comprehension, and student-student and student-instructor connection.

Keywords: gamification, innovative pedagogy, student engagement, student emotional well being

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Authors: F. Slaven, M. Uys, Y. Erasmus

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The South African National Mental Health Education Programme (SANMHEP) was a National Department of Health (NDoH) initiative to strengthen mental health services in South Africa in collaboration with the Foundation for Professional Development (FPD), SANOFI and the various provincial departments of health. The programme was implemented against the backdrop of a number of challenges in the management of mental health in the country related to staff shortages and infrastructure, the intersection of mental health with the growing burden of non-communicable diseases and various forms of violence, and challenges around substance abuse and its relationship with mental health. The Mental Health Care Act (No. 17 of 2002) prescribes that mental health should be integrated into general health services including primary, secondary and tertiary levels to improve access to services and reduce stigma associated with mental illness. In order for the provisions of the Act to become a reality, and for the journey of mental health patients through the system to improve, sufficient and skilled health care providers are critical. SANMHEP specifically targeted Medical Doctors and Professional Nurses working within the facilities that are listed to conduct 72-hour assessments, as well as District Hospitals. The aim of the programme was to improve the clinical diagnosis and management of mental disorders/conditions and the understanding of and compliance with the Mental Health Care Act and related Regulations and Guidelines in the care, treatment and rehabilitation of mental health care users. The course used a blended-learning approach and trained 1 120 health care providers through 36 workshops between February and November 2019. Of those trained, 689 (61.52%) were Professional Nurses, 337 (30.09%) were Medical Doctors, and 91 (8.13%) indicated their occupation as ‘other’ (of these more than half were psychologists). The pre- and post-evaluation of the face-to-face training sessions indicated a marked improvement in knowledge and confidence level scores (both clinical and legislative) in the care, treatment and rehabilitation of mental health care users by participants in all the training sessions. There was a marked improvement in the knowledge and confidence of participants in performing certain mental health activities (on average the ratings increased by 2.72; or 27%) and in managing certain mental health conditions (on average the ratings increased by 2.55; or 25%). The course also required that participants obtain 70% or higher in their formal assessments as part of the online component. The 337 participants who completed and passed the course scored 90% on average. This illustrates that when participants attempted and completed the course, they did very well. To further assess the effect of the course on the knowledge and behaviour of the trained mental health care practitioners a mixed-method outcome evaluation is currently underway consisting of a survey with participants three months after completion, follow-up interviews with participants, and key informant interviews with department of health officials and course facilitators. This will enable a more detailed assessment of the impact of the training on participants' perceived ability to manage and treat mental health patients.

Keywords: mental health, public health facilities, South Africa, training

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Authors: Hua Cao, Laurent Peyrodie, Olivier Agnani, Cecile Donze

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Multiple sclerosis (MS) is a disease, which affects the central nervous system, and causes balance problem. In clinical, this disorder is usually evaluated using static posturography. Some linear or nonlinear measures, extracted from the posturographic data (i.e. center of pressure, COP) recorded during a balance test, has been used to analyze postural control of MS patients. In this study, the trend (TREND) and the sample entropy (SampEn), two nonlinear parameters were chosen to investigate their relationships with the expanded disability status scale (EDSS) score. Forty volunteers with different EDSS scores participated in our experiments with eyes open (EO) and closed (EC). TREND and two types of SampEn (SampEn1 and SampEn2) were calculated for each combined COP’s position signal. The results have shown that TREND had a weak negative correlation to EDSS while SampEn2 had a strong positive correlation to EDSS. Compared to TREND and SampEn1, SampEn2 showed a better significant correlation to EDSS and an ability to discriminate the MS patients in the EC case. In addition, the outcome of the study suggests that the multi-dimensional nonlinear analysis could provide some information about the impact of disability progression in MS on dynamics of the COP data.

Keywords: balance, multiple sclerosis, nonlinear analysis, postural sway

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Authors: Jessy Rugeyo, William Donner

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This research delves into the resilience of Rwanda's public health infrastructure amidst natural disasters, a critical issue given that the Northern Province alone has witnessed no fewer than 1500 cases of disaster ranging from floods and landslides in the last five years, with more than 200 people killed and thousands of homes destroyed, according to MINEMA. In an era where climate change escalates the frequency and intensity of such disasters, fortifying the resilience of public health systems is paramount. This study offers a comprehensive analysis of the existing state of Rwanda's public health infrastructure and its ability to manage such crises. Employing a mix of literature review, case studies, and policy analysis, the study discerns key vulnerabilities and brings to light the intricacies of disaster management in Rwanda. Case studies centered around past natural disasters in Rwanda provide critical insights into the strengths and weaknesses of the existing disaster response mechanisms. A thorough critique of related disaster management and public health infrastructure policies reveals areas of commendable practice, along with gaps calling for policy enhancements. Findings guide the proposition of targeted strategies to bolster the resilience of Rwanda's public health infrastructure. This research serves as a significant contribution to the domains of disaster studies and public health, offering valuable insights for policymakers, public health and disaster management professionals in Rwanda and similar contexts. It presents actionable recommendations for improvement, underscoring the potential for enhancing Rwanda's disaster management capacity. By advocating for the strengthening of public health infrastructure resilience, the research highlights the potential for improved public health outcomes following natural disasters, thereby showcasing significant implications for public health and disaster management in the country, particularly in the face of a changing climate.

Keywords: public health infrastructure, disaster resilience, natural disaster, disaster management, emergency preparedness, health policy

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Authors: Keneilwe Maremi, Marlien Herselman, Adele Botha

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The main purpose and focus of this paper are to determine the Interoperability Maturity Models to consider when using School Management Systems (SMS). The importance of this is to inform and help schools with knowing which Interoperability Maturity Model is best suited for their SMS. To address the purpose, this paper will apply a scoping review to ensure that all aspects are provided. The scoping review will include papers written from 2012-2019 and a comparison of the different types of Interoperability Maturity Models will be discussed in detail, which includes the background information, the levels of interoperability, and area for consideration in each Maturity Model. The literature was obtained from the following databases: IEEE Xplore and Scopus, the following search engines were used: Harzings, and Google Scholar. The topic of the paper was used as a search term for the literature and the term ‘Interoperability Maturity Models’ was used as a keyword. The data were analyzed in terms of the definition of Interoperability, Interoperability Maturity Models, and levels of interoperability. The results provide a table that shows the focus area of concern for each Maturity Model (based on the scoping review where only 24 papers were found to be best suited for the paper out of 740 publications initially identified in the field). This resulted in the most discussed Interoperability Maturity Model for consideration (Information Systems Interoperability Maturity Model (ISIMM) and Organizational Interoperability Maturity Model for C2 (OIM)).

Keywords: interoperability, interoperability maturity model, school management system, scoping review

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Authors: Jude Harrison

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Child protection is a complex and sensitive practice. The core responsibility is the care and protection of children and young people who have been subject to or who are at risk from abuse and neglect. The work involves investigating allegations of harm, preparing for and making representations to the legal system, and case planning and management across a continuum of complicated care interventions. Professionals’ learning for child protection practice is evident in a range of literature investigating multiple learning processes such as university preparation, student placements, professional supervision, training, and other post-qualifying professional development experiences at work. There is, however, very limited research into how caseworkers learn in and through their daily practice. Little is known, therefore, about how learning at work unfolds for caseworkers, the dimensions in which it can be understood or the ways in which it can be best facilitated and supported. Compounding this, much of the current child protection learning literature reflects an orthodox conception of learning as mentalistic and individualised, in which knowledge is typically understood as abstract theory or as technical skill or competency. This presentation outlines key findings from a PhD research study that explored learning at work for statutory child protection caseworkers from an alternative interpretation of learning using a practice theory approach. Practice theory offers an interpretation of learning as performative and grounded in situated experience. The findings of the study show that casework practice is both a mode and site of learning. The study was ethnographic in design based and followed 17 child protection caseworkers via in-depth interviews, observations and participant reflective journaling. Inductive and abductive analysis was used to organise and interpret the data and expand analysis, leading to themes. Key findings show learning to be a sociomaterial property of doing; the social ontological character of learning; and teleoaffectivity as a feature of learning. The findings contribute to theoretical and practical understandings of learning and practice in child protection, child welfare and the professional learning literature more broadly. The findings have potential to contribute to policy directions at state, territory and national levels to enhance child protection practice and systems.

Keywords: adiult learning, workplace learning, child welfare, sociomaterial, practice theory

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Authors: Bochen Jia, Francesco Zhu

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People are constantly surprised at how real and immersive virtual reality (VR) is, even though the technology is still rudimentary, and we are only scratching the surface of its possibilities. Therefore, this literature review built a body of knowledge of existing technology that can be used to improve immersiveness in VR. For this paper, "Sense of Presence (SoP)" was chosen as the terminology to describe immersiveness in VR. Eight studies that tested VR technologies were identified. Many other studies were included to back up the incentives behind these technologies. VR technologies include vibration, airflow, thermal components, EMS, and quadcopters. Study results from selected papers were analyzed, compared, and generally positive. Seven studies had positive results, and only one had negative results. Vibration is the most effective option to improve SoP.

Keywords: virtual reality, sense of presence, self-awareness, literature review

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Authors: Metkel Gebremedhin, Biruk Kebede, Guash Abay

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Job satisfaction largely determines the productivity and efficiency of human resources for health. There is scanty evidence on factors influencing the job satisfaction of health extension professionals (HEPs) in Addis Ababa. The objective of this study was to determine the level of and factors influencing job satisfaction among extension health workers in Addis Ababa city. This was a cross-sectional study conducted in Addis Ababa, Ethiopia. Among all public health centers found in the Addis Ababa city administration health bureau that would be included in the study, a multistage sampling technique was employed. Then we selected the study health centers randomly and urban health extension professionals from the selected health centers. In-depth interview data collection methods were carried out for a comprehensive understanding of factors affecting job satisfaction among Health extension professionals (HEPs) in Addis Ababa. HEPs working in Addis Ababa areas are the primary study population. Multivariate logistic regression with 95% CI at P ≤ 0.05 was used to assess associated factors to job satisfaction. The overall satisfaction rate was 10.7% only, while 89.3%% were dissatisfied with their jobs. The findings revealed that variables such as marital status, staff relations, community support, supervision, and rewards have a significant influence on the level of job satisfaction. For those who were not satisfied, the working environment, job description, low salary, poor leadership and training opportunities were the major causes. Other factors influencing the level of satisfaction were lack of medical equipment, lack of transport facilities, lack of training opportunities, and poor support from woreda experts. Our study documented a very low level of overall satisfaction among health extension professionals in Addis Ababa city public health centers. Considering the factors responsible for this state of affairs, urgent and concrete strategies must be developed to address the concerns of extension health professionals as they represent a sensitive domain of the health system of Addis Ababa city. Improving the overall work environment, review of job descriptions and better salaries might bring about a positive change.

Keywords: job satisfaction, extension health professionals, Addis Ababa

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Authors: J. Kontoleon, D.Gall, M.Pidskalny

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FisherONE offers a distinct pedagogic model for senior secondary education that integrates advanced technology to meet the learning needs of Year 11 and 12 students across Catholic schools in Queensland. As a fully online platform, FisherONE employs pedagogy that combines flexibility with personalized, data-driven learning. The model leverages tools like the MaxHub hybrid interactive system and AI-powered learning assistants to create tailored learning pathways that promote student autonomy and engagement. This paper examines FisherONE’s success in employing pedagogic strategies through technology. Initial findings suggest that students benefit from the blended approach of virtual assessments and real-time support, even as AI-assisted tools remain in the proof-of-concept phase. The study outlines how FisherONE plans to continue refining its educational methods to better serve students in distance learning environments, specifically in challenging subjects like physics. The integration of technology in FisherONE enhances the effectiveness of teaching and learning, addressing common challenges in online education by offering scalable, individualized learning experiences. This approach demonstrates the future potential of technology in education and the role it can play in fostering meaningful student outcomes.

Keywords: AI-assisted learning, innovative pedagogy, personalized learning, senior education, technology in education

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Authors: Vincent Liu

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Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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Authors: Emily Jin, Harry Sharples, Anne Weist

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Introduction: NICE Evidence Search Student Champion Scheme is a peer-assisted learning scheme that aims to improve the routine use of evidence-based information by future health and social care staff. The focus is on the NICE evidence search portal that provides selected information from more than 800 reliable health, social care, and medicines sources, including up-to-date guidelines and information for the public. This paper aims to evaluate the effectiveness of the scheme when implemented in Liverpool School of Medicine and to understand the experiences of those attending. Methods: Twelve student champions were recruited and trained in February 2020 as peer tutors during a workshop facilitated by NICE. Cascade sessions were then organised and delivered on an optional basis for students, in small groups of < 10 to approximately 70 attendees. Surveys were acquired immediately before and 8-12 weeks after cascade sessions (n=47 and 45 respectively). Data from these surveys facilitated the analysis of the scheme. Results: Surveys demonstrated 74% of all attendees frequently searched for health and social care information online as a part of their studies. However, only 15% of attendees reported having prior formal training on searching for health information, despite receiving such training earlier on in the curriculum. After attending cascade sessions, students reported a 58% increase in confidence when searching for information using evidence search, from a pre-session a baseline of 36%. Conclusion: NICE Evidence Search Student Champion Scheme provided clear benefits for attending students, increasing confidence in searching for peer-reviewed, mainly secondary sources of health information. The lack of reported training represents the unmet need that the champion scheme satisfies, and this likely benefits student champions as well as attendees. Increasing confidence in searching for healthcare information online may support future evidence-based decision-making.

Keywords: evidence-based medicine, NICE, medical education, medical school, peer-assisted learning

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Authors: Nanyonjo Juliet

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Across Sub-Saharan Africa, it’s increasingly becoming an absolute necessity for either parents or governments to encourage learners, most particularly those attending high schools, to study a second or foreign language other than the “official language” or the language of instruction in schools. The major second or foreign languages under consideration include but are not necessarily limited to English, French, German, Arabic, Swahili/Kiswahili, Spanish and Chinese. The benefits of learning a second (foreign) language in the globalized world cannot be underestimated. Amongst others, it has been expounded to especially involve such opportunities related to traveling, studying abroad and widening one’s career prospects. Research has also revealed that beyond these non-cognitive rewards, learning a second language enables learners to become more thoughtful, considerate and confident, make better decisions, keep their brain healthier and generally – speaking, broaden their world views. The methodology of delivering a successful 2nd language – learning process by a professionally qualified teacher is located in motivation. We strongly believe that the psychology involved in teaching a foreign language is of paramount importance to a learner’s successful learning experience. The aim of this paper, therefore, is to explore and show the importance of motivation in the teaching and learning of a given 2nd (foreign) language in the local Ugandan high schools.

Keywords: second language, foreign language, language learning, language teaching, official language, language of instruction, globalized world, cognitive rewards, non-cognitive rewards, learning process, motivation

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Authors: S. Wietrzychowski

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This systematic review incorporates concepts used in the field of positive psychology in order to integrate important elements into suicide prevention programs for children and adolescents. The goal of this review is to help students and professionals gain insight to available prevention programs for suicide and to incorporate aspects of positive psychology into these programs. Evidence-based interventions such as Positive Youth Development will be discussed in detail in its relation to prevention and positive psychology. Concepts such as hope, optimism, coping, and resilience will be related to these interventions in order to improve these interventions. The review will also explain how these programs can help prevent suicidal thoughts and/or behaviors. Research on mentorship programs and early intervention programs will be included and related to the aforementioned positive psychology concepts. Since children and adolescents are such a vulnerable population, the review will highlight specific considerations for working with children in order to prevent risk factors for suicide and to build protective factors. This review will discuss the effectiveness of school-based programs that are integrated with positive psychology. Elements of these programs that have been shown to be most effective in preventing suicide in schools will also be identified. As a result of this presentation, participants will be able to 1) List at least 2 evidence-based suicide prevention programs, 2) Understand the connection between specific positive psychology concepts and suicide prevention, 3) Identify at least 3 factors which protect against suicide, 4) Describe at least 3 risk factors for suicide, and 5) Think critically about the positive elements of suicide prevention programs.

Keywords: children, adolescents, suicide, positive

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

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Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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Authors: Mahalingam Palaniandi

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Higher education plays vital role in the nation building process for a country and the rest of world. The higher education sector develops the change-agents for the various fields which will help the human-kind wheel to run further. Conventional and traditional class-room based learning and teaching was followed in many decades which is one-to-one and one-to-many. In a way, these are simplest form of learners to be assembled in a class room wherein the teacher used the blackboard to demonstrate the theory and laboratories used for practical. As the technology evolved tremendously for the last 40 years, the teaching and learning environment changed slowly, wherein, the learning community will be anywhere in the world and teacher deliver the content through internet based tools such as video conferencing, web based conferencing tools or E-learning platforms such as Blackboard or noodle. Present day, the mobile technologies plays an important tool to deliver the teaching content on-the-go. Both PC based and mobile based learning technology brought the learning and teaching community together in various aspects. However, as the learning technology also brought various hurdles for learning processes such as plagiarism and not using the reference books entirely as most of the students wants the information instantaneously using internet without actually going to the library to take the notes from the millions of the books which are not available online as e-books which result lack of fundamental knowledge of the concepts complex theories. However, technology is inseparable in human life, now-a-days and every part of it contains piece of information technology right from computers to home appliances. To make use of the IT based learning and teaching at most efficiency, we should have a proper framework and recommendations laid to the learning community in order to derive the maximum efficiency from the IT based teaching and leaning. This paper discusses various IT based tools available for the learning community, efficiency from its usage and recommendations for the suitable framework that needs to be implemented at higher education institutions which makes the learners stronger in both theory as well as real-time knowledge of their studies that is going to be used in their future for the better world.

Keywords: higher education, e-learning, teaching learning, eLearning tools

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Authors: S. K. Ashiquer Rahman

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This paper presents a knowledge mediation platform, “ePLANETe Blue” that addresses the challenge of building knowledge partnerships for higher education. The purpose is to present, as an institutional perception, the ‘ePLANETe' idea and functionalities as a practical and pedagogical innovation program contributing to the collaborative learning goals in higher education. In consequence, the set of functionalities now amalgamated in ‘ePLANETe’ can be seen as an investigation of the challenges of “Collaborative Learning Digital Process.” It can exploit the system to facilitate collaborative education, research and student learning in higher education. Moreover, the platform is projected to support the identification of best practices at explicit levels of action and to inspire knowledge interactions in a “virtual community” and thus to advance in deliberation and learning evaluation of higher education through the engagement of collaborative activities of different sorts.

Keywords: mediation, collaboration, deliberation, evaluation

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Authors: Ying Zhou, Jian-Hua Wang

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Based upon the self-determination theory and self-regulated learning theory, this study examined the predictiveness of goal orientation and self-regulated learning strategies on academic achievement of adult students in distance learning. The results show a positive relation between goal orientation and the use of self-regulated strategies, and academic achievements. A significant and positive indirect relation of mastery goal orientation through self-regulated learning strategies was also found. In addition, results pointed to a positive indirect impact of performance-approach goal orientation on academic achievement. The effort regulation strategy fully mediated this relation. The theoretical and instructional implications are discussed. Interventions can be made to motivate students’ mastery or performance approach goal orientation and help them manage their time or efforts.

Keywords: goal orientation, self-regulated strategies, achievement, adult distance students

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Authors: Christie DeGregorio

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In today's rapidly evolving educational landscape, adult learners are becoming an increasingly significant demographic. These individuals often possess a wealth of life experiences and diverse interests that can greatly influence their learning styles. Recognizing and incorporating these interests into educational practices can lead to enhanced engagement, motivation, and overall learning outcomes for adult learners. This essay aims to explore the significance of incorporating adult learners' interests into learning styles and provide an overview of the methodologies used in related studies. When investigating the incorporation of adult learners' interests into learning styles, researchers have employed various methodologies to gather valuable insights. These methodologies include surveys, interviews, case studies, and classroom observations. Surveys and interviews allow researchers to collect self-reported data directly from adult learners, providing valuable insights into their interests, preferences, and learning styles. Case studies offer an in-depth exploration of individual adult learners, highlighting how their interests can be integrated into personalized learning experiences. Classroom observations provide researchers with a firsthand understanding of the dynamics between adult learners' interests and their engagement within a learning environment. The major findings from studies exploring the incorporation of adult learners' interests into learning styles reveal the transformative impact of this approach. Firstly, aligning educational content with adult learners' interests increases their motivation and engagement in the learning process. By connecting new knowledge and skills to topics they are passionate about, adult learners become active participants in their own education. Secondly, integrating interests into learning styles fosters a sense of relevance and applicability. Adult learners can see the direct connection between the knowledge they acquire and its real-world applications, which enhances their ability to transfer learning to various contexts. Lastly, personalized learning experiences tailored to individual interests enable adult learners to take ownership of their educational journey, promoting lifelong learning habits and self-directedness.

Keywords: integration, personalization, transferability, learning style

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Authors: Hyoshin Kim

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Most post-secondary educational institutions have offered a wide variety of professional development programs and resources in order to advance the quality of education. Such programs are designed to support faculty members by focusing on topics such as course design, behavioral learning objectives, class discussion, and evaluation methods. These are based on good intentions and might help both new and experienced educators. However, the fundamental flaw is that these ‘effective methods’ are assumed to work regardless of what we teach and whom we teach. This paper is focused on intercultural intelligence and its application to education. It presents a comprehensive literature review on context and cultural diversity in terms of beliefs, values and worldviews. What has worked well with a group of homogeneous local students may not work well with more diverse and international students. It is because students hold different notions of what is means to learn or know something. It is necessary for educators to move away from certain sets of generic teaching skills, which are based on a limited, particular view of teaching and learning. The main objective of the research is to expand our teaching strategies by incorporating what students bring to the course. There have been a growing number of resources and texts on teaching international students. Unfortunately, they tend to be based on the deficiency model, which treats diversity not as strengths, but as problems to be solved. This view is evidenced by the heavy emphasis on assimilationist approaches. For example, cultural difference is negatively evaluated, either implicitly or explicitly. Therefore the pressure is on culturally diverse students. The following questions reflect the underlying assumption of deficiencies: - How can we make them learn better? - How can we bring them into the mainstream academic culture?; and - How can they adapt to Western educational systems? Even though these questions may be well-intended, there seems to be something fundamentally wrong as the assumption of cultural superiority is embedded in this kind of thinking. This paper examines how educators can incorporate intercultural intelligence into the course design by utilizing a variety of tools such as pre-course activities, peer learning and reflective learning journals. The main goal is to explore ways to engage diverse learners in all aspects of learning. This can be achieved by activities designed to understand their prior knowledge, life experiences, and relevant cultural identities. It is crucial to link course material to students’ diverse interests thereby enhancing the relevance of course content and making learning more inclusive. Internationalization of higher education can be successful only when cultural differences are respected and celebrated as essential and positive aspects of teaching and learning.

Keywords: intercultural competence, intercultural intelligence, teaching and learning, post-secondary education

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Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

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Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

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Authors: Layla Albdr

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Saudi Arabia instituted the policy of Sensitizing and Training Stakeholders for E-learning and witnessed wide adoption in many institutions. However, it is at the infancy stage and needs time to develop to mirror the US and UK. The majority of the higher education institutions in Saudi Arabia have adopted E-learning as an alternative to traditional methods to advance education. Conversely, effective implementation of the policy of sensitization and training of stakeholders for E-learning implementation has not been attained because of various challenges. The objectives included determining the challenges and opportunities of the E-learning policy of sensitization and training of stakeholders in Saudi Arabia's higher education and examining if sensitization and training of stakeholder's policy will help promote the implementation of E-learning in institutions. The study employed a descriptive research design based on qualitative analysis. The researcher recruited 295 students and 60 academic staff from four Saudi Arabian universities to participate in the study. An online questionnaire was used to collect the data. The data was then analyzed and reported both quantitatively and qualitatively. The analysis provided an in-depth understanding of the opportunities and challenges of E-learning policy in Saudi Arabian universities. The main challenges identified as internal challenges were the lack of educators’ interest in adopting the policy, and external challenges entailed lack of ICT infrastructure and Internet connectivity. The study recommends encouraging, sensitizing, and training all stakeholders to address these challenges and adopt the policy.

Keywords: e-learning, educational policy, Saudi Arabia, policy of sensitization and training

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Authors: Nasrin Mohammadhasani, Rosa Angela Fabio

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The attention to relevance information is the key element for learning. Otherwise, Attention Deficit Hyperactivity Disorder (ADHD) students have a fuzzy visual pattern that prevents them to attention and remember learning subject. The present study aimed to test the hypothesis that the presence of a pedagogical agent can effectively support ADHD learner's attention and learning outcomes in a multimedia learning environment. The learning environment was integrated with a pedagogical agent, named Koosha as a social peer. This study employed a pretest and posttest experimental design with control group. The statistical population was 30 boys students, age 10-11 with ADHD that randomly assigned to learn with/without an agent in well designed environment for mathematic. The results suggested that experimental and control groups show a significant difference in time when they participated and mathematics achievement. According to this research, using the pedagogical agent can enhance learning of ADHD students by gaining and guiding their attention to relevance information part on display, so it can be considered as asocial cue that provides theme cognitive supports.

Keywords: attention, computer assisted instruction, multimedia learning environment, pedagogical agent

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Authors: Lindy Van Vliet, Saloni Phadke, Anthea Nelson, Ann Gallant

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Comprehensive and compassionate palliative care and support requires an integrated system of care that draws on formal health and social service providers working together with community and informal networks to ensure that patients and families have access to the care they need. The objective of this study is to further explore and understand the community supports, services, and informal networks that health care professionals and social service providers rely on to allow their patients to die in their homes and communities. Drawing on an interpretivist, exploratory, qualitative design, our multidisciplinary research team (medicine, nursing and social work) conducted interviews with 15 health care and social service providers in the Ottawa region. Interview data was audio-recorded, transcribed and analyzed using a reflexive thematic analysis approach. The data deepens our understandings of the facilitators and barriers that arise as health care and social service providers attempt to build networks of care for patients with life limiting illnesses and families. Three main findings emerged: First, the variability that arises due to systemic barriers in accessing and providing care; second, the exceptionally challenging workload that providers are facing as they work to address complex social care needs (housing, disability, food security), along with escalating palliative care needs; and, finally, the lack of structural support that providers and informal care networks receive. Conclusion: These findings will facilitate and build stronger person-centred/relationship-centred principles and practices between providers, patients, community, and informal care networks by highlighting the systemic barriers to accessing and providing person-centred care. Further, they will have important implications for future partnerships in integrated care delivery programs and initiatives, community policies, education programs, and provincial and national palliative care strategies.

Keywords: public health palliative care, palliative care nursing, care networks, informal care, integrated health care

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Authors: Mahesh Balan U, Rohith Srinivaas Mohanakrishnan, Venkat Subramanian

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Positive and unlabeled learning (PU) has gained more attention in both academic and industry research literature recently because of its relevance to existing business problems today. Yet, there still seems to be some existing challenges in terms of validating the performance of PU learning, as the actual truth of unlabeled data points is still unknown in contrast to a binary classification where we know the truth. In this study, we propose a novel PU learning technique based on the Pseudo-F measure, where we address this research gap. In this approach, we train the PU model to discriminate the probability distribution of the positive and unlabeled in the validation and spy data. The predicted probabilities of the PU model have a two-fold validation – (a) the predicted probabilities of reliable positives and predicted positives should be from the same distribution; (b) the predicted probabilities of predicted positives and predicted unlabeled should be from a different distribution. We experimented with this approach on a credit marketing case study in one of the world’s biggest fintech platforms and found evidence for benchmarking performance and backtested using historical data. This study contributes to the existing literature on semi-supervised learning.

Keywords: PU learning, semi-supervised learning, pseudo f measure, classification

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Authors: Naduni Ranasinghe

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E-learning environments are getting more popular than any other due to the impact of COVID19. Even though e-learning is one of the best solutions for the teaching-learning process in the academic process, it’s not without major challenges. Nowadays, machine learning approaches are utilized in the analysis of how behavioral factors lead to better adoption and how they related to better performance of the students in eLearning environments. During the pandemic, we realized the academic process in the eLearning approach had a major issue, especially for the performance of the students. Therefore, an approach that investigates student behaviors in eLearning environments using a data-intensive machine learning approach is appreciated. A hybrid approach was used to understand how each previously told variables are related to the other. A more quantitative approach was used referred to literature to understand the weights of each factor for adoption and in terms of performance. The data set was collected from previously done research to help the training and testing process in ML. Special attention was made to incorporating different dimensionality of the data to understand the dependency levels of each. Five independent variables out of twelve variables were chosen based on their impact on the dependent variable, and by considering the descriptive statistics, out of three models developed (Random Forest classifier, SVM, and Decision tree classifier), random forest Classifier (Accuracy – 0.8542) gave the highest value for accuracy. Overall, this work met its goals of improving student performance by identifying students who are at-risk and dropout, emphasizing the necessity of using both static and dynamic data.

Keywords: academic performance prediction, e learning, learning analytics, machine learning, predictive model

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Authors: Ahmet Karakuş, Akif Can Kilic, Emre Alptekin

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A growing number of studies have been conducted to determine how well-being may be predicted using well-designed models. It is necessary to investigate the backgrounds of features in order to construct a viable Subjective Well-Being (SWB) model. We have picked the suitable variables from the literature on SWB that are acceptable for real-world data instructions. The goal of this work is to evaluate the model by feeding it with SWB characteristics and then categorizing the stress levels using machine learning methods to see how well it performs on a real dataset. Despite the fact that it is a multiclass classification issue, we have achieved significant metric scores, which may be taken into account for a specific task.

Keywords: machine learning, multiclassification problem, subjective well-being, perceived stress scale

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Authors: Nadwah Onwi, Puspa Maniam, Azmawanie A. Aziz, Fairus Mukhtar, Nor Azrita Mohamed Zin, Nurul Haslina Mohd Zin, Nurul Fatehah Ismail, Mohamad Safwan Yusoff, Susilidianamanalu Abd Rahman, Siti Munirah Harris, Maryam Aizuddin

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Objective: Malaysia has a growing number of individuals with complex communication needs (CCN). The initiation of augmentative and alternative communication (AAC) intervention may facilitate individuals with CCN to understand and express themselves optimally and actively participate in activities in their daily life. AAC is defined as multimodal use of communication ability to allow individuals to use every mode possible to communicate with others using a set of symbols or systems that may include the symbols, aids, techniques, and strategies. It is consequently critical to evaluate the deficits to inform treatment for AAC intervention. However, no known measurement tools are available to evaluate the user with CCN available locally. Design: A systematic review (SR) is designed to analyze the psychometric properties of AAC assessment for adolescents with CCN published in peer-reviewed journals. Tools are rated by the methodological quality of studies and the psychometric measurement qualities of each tool. Method: A literature search identifying AAC assessment tools with psychometrically robust properties and conceptual framework was considered. Two independent reviewers screened the abstracts and full-text articles and review bibliographies for further references. Data were extracted using standardized forms and study risk of bias was assessed. Result: The review highlights the psychometric properties of AAC assessment tools that can be used by speech-language therapists applicable to be used in the Malaysian context. The work outlines how systematic review methods may be applied to the consideration of published material that provides valuable data to initiate the development of Malay Language AAC assessment tools. Conclusion: The synthesis of evidence has provided a framework for Malaysia Speech-Language therapists in making an informed decision for AAC intervention in our standard operating procedure in the Ministry of Health, Malaysia.

Keywords: augmentative and alternative communication, assessment, adolescents, complex communication needs

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Authors: Benguerine Zohra, Merzak Siham, Pr. Chelghoum

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Introduction: The widespread production and consumption of antibiotics have raised significant concerns due to various adverse effects and the development of bacterial resistance. This increasing resistance to currently available antibiotics necessitates the search for new antibacterial agents. One alternative strategy to combat antibiotic-resistant bacteria is the use of natural antimicrobial substances such as plant extracts. This study aims to provide an overview of the antibacterial effects of Salvia officinalis (sage), a plant native to the Middle East and Mediterranean regions. Materials and Methods: This review was conducted by searching studies in databases such as PubMed, Scopus, JSTOR, and SpringerLink. The search terms were “Salvia officinalis L.” and “antibacterial effects.” Only studies that met our inclusion criteria (in English, focusing on the antibacterial effects of Salvia officinalis L., and primarily dated from 2012 to 2023) were considered for further review. Results and Discussion: The initial search strategy identified approximately 78 references, of which only 13 articles were included in this review. The synthesis of these articles revealed that multiple data sources confirm the antimicrobial effects of S. officinalis. Its essential oil and alcoholic extract exhibit strong bactericidal and bacteriostatic effects against both Gram-positive and Gram-negative bacteria. Conclusion: The significant value of the extract, oil, and leaves of S. officinalis demands further studies on other useful and unknown properties of this multipurpose plant.

Keywords: salvia officinalis, literature review, antibacterial., botany

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Authors: Clement C. Aladi, Zhaoxia Yi

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This study investigates factors influencing the implementation of flexible curricula in e-learning in Information Systems (IS) higher education. Drawing from curriculum theorists and contemporary literature, and using the Technology, Pedagogy, and Content Knowledge (TPACK) framework, it explores teacher-related challenges and their impact on curriculum flexibility implementation. By using the PLS-SEM, the study uncovers these factors and hopes to contribute to enhancing curriculum flexibility in delivering online and blended learning in IS higher education.

Keywords: flexible curriculum, online learning, e-learning, technology

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Authors: Herlena Hayati, Diyan Reni Jayathi, Hairida Anggun, Citra Amelia

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This systematic review research is aimed to find out anemia maternal during pregnancy as a risk factor of low birth weight. This research was done by searching some journals which have associated to maternal anemia during pregnancy with low birth weight that had been published in journal accreditation and scopus index. Study literature that researcher had been done by March – April 2016 through online library of UI. The journals that had been selected according to inclusive criteria and exclusive criteria had been through the critial appraisal process. This systematic review towards 4 journals that had been selected and published showed the significant result statistically that anemia maternal is one of the risk factors which causes low birth weight. Anemia maternal on the first-trimester pregnancy showed significant association with low birth weight. Moderate anemia and severe anemia also showed significant association with low birth weight. Meanwhile, mild anemia doesn’t have an association with low birth weight. The conclusion of this study is anemia maternal (as an independent risk factor) have an influence towards low birth weight.

Keywords: anemia maternal, low birth weight, pregnancy, systematic review

Procedia PDF Downloads 284