Search results for: institutional learning outcomes

Authors: Dylan Shiting Lu, Samson Okello, Anita Chunyan Wei, Daniel Xiao Li

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Mammotome vacuum-assisted breast biopsy (MVB) introduced in 1995 can be used for the removal of benign breast lesions. Whether or not MVB is a better option compared to conventional open surgery is inconclusive. We aim to compare the clinical and patient-related outcomes between MVB and open surgery to remove benign breast tumors less than 5 cm in women. We searched English and Chinese electronic databases with the keywords of Mammotome, clinical trial (CT), vacuum-assisted breast biopsy for studies comparing MVB and open surgery until May 2021. We performed a systematic review and random-effects meta-analysis to compare incision size, operation time, intraoperative blood loss, healing time, scar length, patient satisfaction, postoperative hematoma rate, wound infection rate, postoperative ecchymosis, and postoperative sunken skin among those who have Mammotome and those who have surgery. Our analysis included nine randomized CTs with 1155 total patients (575 Mammotome, 580 surgery) and mean age 40.32 years (standard deviation 3.69). We found statistically significant favorable outcomes for Mammotome including blood loss (ml) [standardized mean difference SMD -5.03, 95%CI (-7.30, -2.76)], incision size (cm) [SMD -12.22, 95%CI (-17.40, -7.04)], operation time (min) [SMD -6.66, 95%CI (-9.01, -4.31)], scar length (cm) [SMD -7.06, 95%CI (-10.76, -3.36)], healing time (days) [SMD -6.57, 95%CI (-10.18, -2.95)], and patient satisfaction [relative risk RR 0.38, 95%CI (0.13, 1.08)]. In conclusion, Mammotome vacuum-assisted breast biopsy compared to open surgery shows better clinical and patient-related outcomes. Further studies should be done on whether or not MVB is a better option for benign breast tumors excision.

Keywords: clinical and patient outcomes, open surgery, Mammotome vacuum-assisted breast biopsy, meta-analysis

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Authors: Triana Fitriastuti, Pipiet Larasatie, Alex Vanderstraten

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Many scholars have demonstrated the negative impacts of the perception of organizational politics on organizational outcomes. The model proposed in this study analyzes the impact of the perception of organizational politics on job satisfaction. In the same way, ingratiation as a moderator variable is tested. We applied regression analysis to test the hypothesis. The findings of the current research, which was conducted with 240 employees in the public sector in Indonesia, show that the perception of organizational politics has a negative effect on job satisfaction. In contrast, ingratiation plays a role that fully moderates the relationship between organizational politics and organizational outcomes and changes the correlation between the perception of organizational politics on job satisfaction. Employees who use ingratiation as a coping mechanism tend to do so when they perceive a high degree of organizational politics.

Keywords: ingratiation, impression management, job satisfaction, perception of organizational politics

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Authors: S. Alfalah, J. Falah, T. Alfalah, M. Elfalah, O. Falah

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The field of education is an ever-evolving area constantly enriched by newly discovered techniques provided by active research in all areas of technologies. The recent years have witnessed the introduction of a number of promising technologies and applications to enhance the teaching and learning experience. Virtual Reality (VR) applications are considered one of the evolving methods that have contributed to enhancing education in many fields. VR creates an artificial environment, using computer hardware and software, which is similar to the real world. This simulation provides a solution to improve the delivery of materials, which facilitates the teaching process by providing a useful aid to instructors, and enhances the learning experience by providing a beneficial learning aid. In order to assure future utilization of such systems, students’ perceptions were examined toward utilizing VR as an educational tool in the Faculty of Information Technology (IT) in The University of Jordan. A questionnaire was administered to IT undergraduates investigating students’ opinions about the potential opportunities that VR technology could offer and its implications as learning and teaching aid. The results confirmed the end users’ willingness to adopt VR systems as a learning aid. The result of this research forms a solid base for investing in a VR system for IT education.

Keywords: information, technology, virtual reality, education

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Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

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Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: bioassay, machine learning, preprocessing, virtual screen

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Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

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The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

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Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

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Authors: Ahmed Sami Hammami, Mohamed Jellazi

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Background: The aim of the study is to evaluate the magnitude of different psychological outcomes among Tunisian health care professionals (HCP) during the COVID-19 pandemic and to identify the associated factors. Methods: HCP completed a cross-sectional questionnaire from April 4th to April, 28th 2020. The survey collected demographic information, factors that may interfere with the psychological outcomes, behavior changes and mental health measurements. The latter was assessed through 3 scales; the 7-item questions Insomnia Severity Index, the 2-item Patient Health Questionnaire and the 2-item Generalized Anxiety Disorder. Multivariable logistic regression was conducted to identify factors associated with psychological outcomes. Results: A total of 503 HCP successfully completed the survey; among those, n=493 consented to enroll in the study, 411 [83.4%] were physicians, 323 [64.2%] were women and 271 [55%] had a second-line working position. A significant proportion of HCP had anxiety 35.7%, depression 35.1% and insomnia 23.7%. Females, those with psychiatric history and those using public transport exhibited the highest proportions for overall symptoms compared to other groups e.g., depression among females vs. males: 44,9% vs. 18,2%, P=0.00. Those with a previous medical history and nurses, had more anxiety and insomnia compared to other groups e.g. anxiety among nurses vs. interns/residents vs. attending 45,1% vs 36,1% vs 27,5%; p=0.04. Multivariable logistic regression showed that female gender was a risk factor for all psychological outcomes e.g. female sex increased the odds of anxiety by 2.86; 95% confidence interval [CI], 1, 78-4, 60; P=0.00, whereas having a psychiatric history was a risk factor for both anxiety and insomnia. (e.g. for insomnia OR=2,86; 95% [CI], 1,78-4,60; P=0.00), Having protective equipment was associated with lower risk for depression (OR=0,41; 95% CI, 0,27-0,62; P=0.00) and anxiety. Physical activity was also protective against depression and anxiety (OR=0,41, 95% CI, 0,25-0,67, P=0.00). Conclusion: Psychological symptoms are usually undervalued among HCP, though the COVID-19 pandemic played a major role in exacerbating this burden. Prompt psychological support should be endorsed and simple measures such as physical activity and ensuring the necessary protection are paramount to improve mental health outcomes and the quality of care provided to patients.

Keywords: COVID-19 pandemic, health care professionals, mental health, protective factors, psychological symptoms, risk factors

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Authors: Guadalupe López-Bonilla

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Students of all educational levels participate in literacy practices that may involve print or digital media. Scholars from the New Literacy Studies distinguish practices that fulfill institutional purposes such as those established at schools from literate practices aimed at doing other kinds of activities, such as reading instructions in order to play a video game; the first are known as institutional practices while the latter are considered vernacular literacies. When students perform these kinds of activities they engage with print and digital media according to the demands of the task. In this paper, it is aimed to discuss the results of a research project focusing on literacy practices of high school students at 10 urban cybercafés in Mexico. The main objective was to analyze the literacy practices of students performing both school tasks and vernacular literacies. The methodology included a focused ethnography with online and face to face observations of 10 high school students (5 male and 5 female) and interviews after performing each task. In the results, it is presented how students treat texts as open, dynamic and relational artifacts when engaging in vernacular literacies; while texts are conceived as closed, authoritarian and fixed documents when performing school activities. Samples of each type of activity are shown followed by a discussion of the pedagogical implications for improving school literacy.

Keywords: digital literacy, text, school literacy, vernacular practices

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Authors: Bryony Pound

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This study investigated how views of green or urban space affect learning performance. It provides evidence of the value of visual access to greenspace in work and learning environments, and builds on the extensive research into the cognitive and learning-related benefits of access to green and natural spaces, particularly in learning environments. It demonstrates that benefits of visual access to natural spaces whilst learning can produce statistically significant faster responses than those facing urban views after only 5 minutes. The primary hypothesis of this research was that a greenspace view would improve short-term learning. Participants were randomly assigned to either a view of parkland or of urban buildings from the same room. They completed a psychological test of two stages. The first stage consisted of a presentation of words from eight different categories (four manmade and four natural). Following this a 2.5 minute break was given; participants were not prompted to look out of the window, but all were observed doing so. The second stage of the test involved a word recognition/false memory test of three types. Type 1 was presented words from each category; Type 2 was non-presented words from those same categories; and Type 3 was non-presented words from different categories. Participants were asked to respond with whether they thought they had seen the words before or not. Accuracy of responses and reaction times were recorded. The key finding was that reaction times for Type 2 words (highest difficulty) were significantly different between urban and green view conditions. Those with an urban view had slower reaction times for these words, so a view of greenspace resulted in better information retrieval for word and false memory recognition. Importantly, this difference was found after only 5 minutes of exposure to either view, during winter, and with a sample size of only 26. Greenspace views improve performance in a learning task. This provides a case for better visual access to greenspace in work and learning environments.

Keywords: benefits, greenspace, learning, restoration

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Authors: Nahla Khatib

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This study investigated several learning difficulties that affected the classroom learning experience of preservice students who are studying general science and methods of teaching science students at Faculty of Educational Studies at the Arab Open University (AOU) in Amman, Jordan. The focus questions for this study were to find answers for the following: 1. What are the main areas of learning difficulty among preservice students towards science education? 2. What are the main aspects of reducing obstacles towards success in science education? To achieve this goal, the researcher prepared a questionnaire which included 30 items to point out the learning difficulties among preservice students towards science education. The questionnaire was distributed among students enrolled in the general science courses 1&2 and methods of teaching science courses at the beginning of the spring semester of year (2013-2014). After collecting the filled questionnaire a descriptive statistical analysis was carried out (means and standard deviation) for the items of the questionnaire. After analyzing the data statistically our findings showed that student control–factors as well as course controlled factor, factors related to the nature of science, and factors related to the role of instructor affected student success toward science education. The study was concluded with a number of recommendations.

Keywords: nature of science, preservice teachers, science education, learning difficulties

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Authors: Anne-Lena Kampen, Øivind Kure

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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN

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Authors: Rosaline Govender

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This research study is an exploration of the self-directed professional development of teachers who teach in public schools in an era of democracy and educational change in South Africa. Amidst an ever-changing educational system, the teachers in this study position themselves as self-directed teacher-learners where they adopt particular learning practices which enable change within the broader discourses of public schooling. Life-story interviews were used to enter into the private and public spaces of five teachers which offer glimpses of how particular systems shaped their identities, and how the meanings of self-directed teacher-learner shaped their learning practices. Through the Multidimensional framework of analysis and interpretation the teachers’ stories were analysed through three lenses: restorying the field texts - the self through story; the teacher-learner in relation to social contexts, and practices of self-directed learning.This study shows that as teacher-learners learn for change through self-directed learning practices, they develop their agency as transformative intellectuals, which is necessary for the reworking of South African public schools.

Keywords: professional development, professionality, professionalism, self-directed learning

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Authors: Jonathan J. Foo, Keng Hao Chew

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Interest in virtual reality (VR) technologies as virtual learning environments have been on the rise in recent years. With thanks to the aggressively competitive consumer electronics environment, VR technology has been made affordable and accessible to the average person with developments like Google Cardboard and Oculus Go. While the promise of virtual access to unique virtual learning environments with the benefits of experiential learning sounds extremely attractive, there are still concerns over user comfort in the psychomotor, cognitive, and affective domains. Reports of motion sickness and short durations create doubt and have stunted its growth. In this paper, a multidimensional framework is proposed for the evaluation of VR learning environments within the three dimensions: tactual quality, didactic quality, and autodidactic quality. This paper further proposes a mixed-methods experimental research plan that sets out to evaluate a virtual reality training simulator in the context of amateur sports fencing. The study will investigate if an immersive VR learning environment can effectively simulate an authentic learning environment suitable for instruction, practice, and assessment while providing the user comfort in the tactual, didactic, and autodidactic dimensions. The models and recommendations developed for this study are designed in the context of fencing, but the potential impact is a guide for the future design and evaluation of all VR developments across sports and technical classroom education.

Keywords: autodidactic quality, didactic quality, tactual quality, virtual reality

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Authors: Kristin Thooft

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— Increasing pressure to manage healthcare costs has resulted in shifting care towards ambulatory settings and is driving a focus on cost transparency. There are few nurse staffing to workload models developed for ambulatory settings, less for multi-specialty clinics. Of the existing models, few have been evaluated against outcomes to understand any impact. This evaluation took place after the AWARD model for nurse staffing to workload was implemented in a multi-specialty clinic at a regional healthcare system in the Midwest. The multi-specialty clinic houses 26 medical and surgical specialty practices. The AWARD model was implemented in two specialty practices in October 2020. Donabedian’s Structure-Process-Outcome (SPO) model was used to evaluate outcomes based on changes to the structure and processes of care provided. The AWARD model defined and quantified the processes, recommended changes in the structure of day-to-day nurse staffing. Cost of care per patient visit, total visits, a total nurse performed visits used as structural and process measures, influencing the outcomes of cost of care and access to care. Independent t-tests were used to compare the difference in variables pre-and post-implementation. The SPO model was useful as an evaluation tool, providing a simple framework that is understood by a diverse care team. No statistically significant changes in the cost of care, total visits, or nurse visits were observed, but there were differences. Cost of care increased and access to care decreased. Two weeks into the post-implementation period, the multi-specialty clinic paused all non-critical patient visits due to a second surge of the COVID-19 pandemic. Clinic nursing staff was re-allocated to support the inpatient areas. This negatively impacted the ability of the Nurse Manager to utilize the AWARD model to plan daily staffing fully. The SPO framework could be used for the ongoing assessment of nurse staffing performance. Additional variables could be measured, giving a complete picture of the impact of nurse staffing. Going forward, there must be a continued focus on the outcomes of care and the value of nursing

Keywords: ambulatory, clinic, evaluation, outcomes, staffing, staffing model, staffing to workload

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Authors: Sofia Hartati

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This research is aimed at describing training in early childhood education program empirically, describing teachers ability to plan lessons empirically, and acquiring empirical data as well as analyzing the influence of guided and independent training toward teachers competence in planning early childhood learning program. The method used is an experiment. It collected data with a population of 76 early childhood educators in Tunjung Teja Sub District area through random sampling technique and grouped into two namely 38 people in an experiment class and 38 people in a controlled class. The technique used for data collections is a test. The result of the research shows that there is a significant influence between training for guided educators toward Teachers Ability toward Planning Early Childhood Learning Program. Guided training has been proven to improve the ability to comprehend planning a learning program. The ability to comprehend planning a learning program owned by teachers of early childhood program comprises of 1) determining the characteristics and competence of students prior to learning; 2) formulating the objective of the learning; 3) selecting materials and its sequences; 4) selecting teaching methods; 5) determining the means or learning media; 6) selecting evaluation strategy as a part of teachers pedagogic competence. The result of this research describes a difference in the competence level of teachers who have joined guided training which is relatively higher than the teachers who joined the independent training. Guided training is one of an effective way to improve the knowledge and competence of early childhood educators.

Keywords: competence, planning, teachers, training

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Authors: C. W. Kan

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Fabrics can be treated to equip them with certain functional properties in which water repellency is one of the important functional effects. In this study, commercial water repellent agent was used under different application conditions to cotton fabric. Finally, the water repellent effect was evaluated by standard testing method. Thus, the aim of this study is to illustrate the proper application of water repellent finishing to cotton fabric and the results could provide guidance note to the students in learning this topic. Acknowledgment: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: learning materials, water repellent, textiles, cotton

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Authors: Anne-Marie Tuomala

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Education for sustainable development (ESD) aims to provide students with the attitudes, values, and behaviors necessary for the contribution to sustainability. The research was implemented as a part of the Horizons Europe research project, where each partner organization had at least one pilot project locally. The pilot in question was an online course about the basics of the natural stone industry in Finland and its sustainability and circular economy aspects. The course was open to all students of applied universities in Finland, and it was implemented twice during the research. The Stone from Finland association participated in the course design, and it was also an expert in the local context and real-life provider. The multiple case-study method was chosen, as it enables purposeful sampling of cases that are tailored to the specific study. It was also assumed that it predicts quite comparable results of two different course implementations of the course with the same topic and content. The Curtin University of Technology’s Attitudes Towards Thinking and Learning Survey was adapted. The results show the importance of the trans-disciplinary nature of sustainability education. In addition, the new industry areas with the general - but also industry-specific sustainability issues - must be introduced to students and encourage them to do critically reflective learning. Surveys that guide them to analyze their own attitudes to thinking and learning may expose students to their weaknesses but also result in forms of more active sustainability interaction.

Keywords: education for sustainable development, learning attitudes, learning of circular economy, virtual learning

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Authors: Boy Subirosa Sabarguna, Aria Kekalih, Irzan Nurman

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Introduction: Software in the form of Clinical Decision Support System could help students in understanding the mind set of decision-making in diagnosis and treatment at the stage of general practitioners. This could accelerate and ease the learning process which previously took place by using books and experience. Method: Gather 1000 members of the National Medical Multimedia Digital Community (NM2DC) who use the “flowchart of diagnosis and treatment” software, and analyse factors related to: display, speed in learning, convenience in learning, helpfulness and usefulness in the learning process, by using the Likert Scale through online questionnaire which will further be processed using percentage. Results and Discussions: Out of the 1000 members of NM2DC, apparently: 97.0% of the members use the software and 87.5% of them are students. In terms of the analysed factors related to: display, speed in learning, convenience in learning, helpfulness and usefulness of the software’s usage, the results indicate a 90.7% of fairly good performance. Therefore, the “Flowchart of Diagnosis and Treatment” software has helped students in understanding the decision-making of diagnosis and treatment. Conclusion: the use of “Flowchart of Diagnosis and Treatment” software indicates a positive role in helping students understand decision-making of diagnosis and treatment.

Keywords: usage, software, diagnosis and treatment, medical education

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Authors: Feng Yang

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Machine learning (ML), especially deep learning (DL), has been extensively applied to many applications in recently years and gained great success in solving different problems, including scientific problems. However, conventional ML/DL methodologies are purely data-driven which have the limitations, such as need of ample amount of labelled training data, lack of consistency to physical principles, and lack of generalizability to new problems/domains. Recently, there is a growing consensus that ML models need to further take advantage of prior knowledge to deal with these limitations. Physics-informed machine learning, aiming at integration of physics/domain knowledge into ML, has been recognized as an emerging area of research, especially in the recent 2 to 3 years. In this work, physics-informed ML, specifically physics-informed neural network (NN), is employed and implemented to estimate the displacements at x, y, z directions in a solid mechanics problem that is controlled by equilibrium equations with boundary conditions. By incorporating the physics (i.e. the equilibrium equations) into the learning process of NN, it is showed that the NN can be trained very efficiently with a small set of labelled training data. Experiments with different settings of the NN model and the amount of labelled training data were conducted, and the results show that very high accuracy can be achieved in fulfilling the equilibrium equations as well as in predicting the displacements, e.g. in setting the overall displacement of 0.1, a root mean square error (RMSE) of 2.09 × 10−4 was achieved.

Keywords: deep learning, neural network, physics-informed machine learning, solid mechanics

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Authors: Rochelle Botha-Marais

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When lecturing future educators in South Africa, praxis is an indispensable aspect that is often neglected. Without properly understanding how the theory taught in lecture halls relates to their future position as educators, we can not expect these students to be fully equipped future teachers. To enable education students at the Vaal Campus of the North West University - who have the Afrikaans language as major - to discover the link between theory and practice, the author created an assignment on phonetics in which the use of technology was incorporated. In the past, students had to submit an assignment or worksheet and they did not get the opportunity to apply their newly found knowledge in a practical manner. For potential future teachers, this application is essential. This paper will demonstrate how technology is used in the second year Afrikaans education module to promote student engagement and self-directed learning. Students were introduced to innovative new technologies alongside more familiar applications to shape a 21st century learning environment where students can think, communicate, solve problems, collaborate and take responsibility for their own teaching and learning. The paper will also reflect on student feedback pertaining the use and efficiency of technology in the Afrikaans module and the possible impact thereof on their own teaching and learning landscape. The aim of this paper is to showcase how technology can be used to maximize the students learning experience and equip future education students with the tools and knowledge to introduce technology-enhanced learning in their own teaching practice.

Keywords: education students, theory and practice, self-directed learning, student engagement, technology

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Authors: Peeranan Wisanskoonwong, Sumitta Sawangtook

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Practicum in Midwifery II is the subject that affects most students to be stressed and anxious because they lack of experiences and self-confidence in delivery baby. This study is a qualitative research. That research objectives were (1) to study learning through reflective practice of nursing students (2) to explain the effects of learning through reflective practice of nursing students in the delivery room. The selected key informant method was criterion-based selection. Thirty-two of fourth-year nursing students in Kuakarun Faculty of nursing who practiced in Delivery room at Taksin Hospital in academic year 2014 were selected. Data collection was data triangulation which consisted of in-depth interview, group discussion and reading students’ reflective practice journal. The research instruments were students’ reflective practice journal, semi-structured questionnaires for in-depth interview, group discussion. Data analysis was thematic analysis. The research result found that: The learning method through reflective practice of nursing students in the delivery room were (1) reflective practice journal (2) dialogue (3) critical thinking and problem solving (4) incident analysis (5) self-criticism (6) observation and evaluation of practice. There were eight issues that students learned through their reflective practice were that (1) students' ethics and morality. (2) students' knowledge and comprehension (3) creative thinking of students (4) communications and collaboration (5) experiential learning of students (6) students’memories and impressions (7) students’experience in delivery baby (8) self-learning of students. Learning through reflective practice supported students’ awareness in improving knowledge and learning continuously and systematically. It helped to adjust the attitude to learning and leadership to be careful which help develop their skills, including critical thinking and understand themselves and understand others. Recommendation for applying research results: midwifery and nursing lecturers can apply these results to be a guide for development their clinical teaching in delivery rooms and other wards.

Keywords: learning, reflection, birth, qualitative research

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Authors: A. Elbyed

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Nowadays, ontologies are used for achieving a common understanding within a user community and for sharing domain knowledge. However, the de-centralized nature of the web makes indeed inevitable that small communities will use their own ontologies to describe their data and to index their own resources. Certainly, accessing to resources from various ontologies created independently is an important challenge for answering end user queries. Ontology mapping is thus required for combining ontologies. However, mapping complete ontologies at run time is a computationally expensive task. This paper proposes a system in which mappings between concepts may be generated dynamically as the concepts are encountered during user queries. In this way, the interaction itself defines the context in which small and relevant portions of ontologies are mapped. We illustrate application of the proposed system in the context of Technology Enhanced Learning (TEL) where learners need to access to learning resources covering specific concepts.

Keywords: resources query, ontologies, ontology mapping, similarity measures, semantic web, e-learning

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Authors: Mohamed Mamdouh Al-Banna, Warda Youssef Mohamed Morsy, Hanaa Ali El-Feky, Ashraf Hussein Abdelmohsen

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Background: The mechanically ventilated patients need a special nursing care with continuous closed observation. The patients’ body mass index may affect their prognosis or outcomes. Aim of the study: to investigate the relationship between BMI and selected outcomes of critically ill mechanically ventilated patients. Research Design: A descriptive correlational research design was utilized Research questions: a) what is the BMI profile of mechanically ventilated patients admitted to critical care units over a period of six months? b) What is the relationship between body mass index and frequency of organ dysfunction, length of ICU stay, weaning from mechanical ventilation, and the mortality rate among adult critically ill mechanically ventilated patients? Setting: different intensive care units of Cairo University Hospitals. Sample: A convenience sample of 30 mechanically ventilated patients for at least 72 hours. Tools of data collection: Three tools were utilized to collect data pertinent to the current study: tool 1: patients’ sociodemographic and medical data sheet, tool 2: BURNS Wean Assessment Program (BWAP) checklist, tool 3: Sequential organ failure assessment (SOFA score) sheet. Results: The majority of the studied sample (77%) was males, and (26.7 %) of the studied sample were in the age group of 18-28 years old, and (26.7 %) were in the age group of 40-50 years old. Moreover, two thirds (66.7%) of the studied sample were within normal BMI. No significant statistical relationship between BMI category and ICU length of stay or the mortality rate among the studied sample, (X² = 11.31, P value = 0.79), (X² = 0.15, P value = 0.928) respectively. No significant statistical relationship between BMI category and the weaning trials from mechanical ventilation among the studied sample, (X² = 0.15, P value = 0.928). No significant statistical relationship was found between BMI category and the occurrence of organ dysfunction among the studied sample, (X² = 2.54, P value = 0.637). Conclusion: No relationship between the BMI categories and the selected patients’ outcomes (weaning from MV, length of ICU stay, occurrence of organ dysfunction, mortality rate). Recommendations: Replication of this study on a larger sample from different geographical locations in Arab Republic of Egypt, conducting farther studies to assess the effect of the quality of nursing care on the mechanically ventilated patients’ outcomes.

Keywords: mechanical ventilation, body mass index, outcomes of mechanically ventilated patient, organ failure

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Authors: Fares Hedayatit, Arnauld Joly, Panagiotis Papadimitriou

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Many machine learning tasks such as text annotation usually require training over very big datasets, e.g., millions of web documents, that can be represented in a sparse input space. State-of the-art tree-based ensemble algorithms cannot scale to such datasets, since they include operations whose running time is a function of the input space size rather than a function of the non-zero input elements. In this paper, we propose an efficient splitting algorithm to leverage input sparsity within decision tree methods. Our algorithm improves training time over sparse datasets by more than two orders of magnitude and it has been incorporated in the current version of scikit-learn.org, the most popular open source Python machine learning library.

Keywords: big data, sparsely representable data, tree-based models, scalable learning

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Authors: N. Ayob, N. C. Nkosi, R. P. Burger, S. J. Piketh, F. Letlaila, O. Maphosa

Abstract:

South African higher tertiary institution have been faced with high dropout rates. About 50 to 60% of first years drop out to due to various reasons one being inadequate academic support. Geography 111 (GEOG 111) module is historically known for having below 50% pass rate, high dropout rate and identified as a first year risk module. For the first time GEOG 111 (2021) on the Mahikeng Campus admitted 150 students pursuing more than 6 different qualifications (BA and BSc) from the Humanities Faculty and FNAS. First year students had difficulties transitioning from secondary to tertiary institutions as we shifted to remote learning while we navigate through the Covid-19 pandemic. The traditional method of teaching does not encourage students to help each other. With remote learning we do not have control over what the students share and perhaps this can be a learning opportunity to embrace peer learning and change the manner in which we assess the students. The purpose of this pilot study was to assist GEOG111 students with academic challenges whilst improving their University experience. This was a qualitative study open to all GEOG111, repeaters, students who are not confident in their Geographical knowledge and never did Geography at high school level. The selected 9 Golden Key International Honour Society Geography mentors attended an academic mentor training program with module lecturers. About 17.6% of the mentees did not have a geography background however, 94% of the mentees passed, 1 mentee had a mark of 38%. 11 of the participants had a mark >60% with one student that excelled 70%. It is evident that mentorship helped students reach their academic potential. Peer learning and mentoring are associated with improved academic performance and allows the students to take charge of their learning and academic experience. Thus an important element as we transform pedagogies at higher learning institutions.

Keywords: geography, risk module, peer mentoring, peer learning

Procedia PDF Downloads 151

Authors: Violeta Damjanovic-Behrendt

Abstract:

This paper presents an approach for optimal cyber security decisions to protect instances of a federated Internet of Things (IoT) platform in the cloud. The presented solution implements the repeated Stackelberg Security Game (SSG) and a model called Stochastic Human behaviour model with AttRactiveness and Probability weighting (SHARP). SHARP employs the Subjective Utility Quantal Response (SUQR) for formulating a subjective utility function, which is based on the evaluations of alternative solutions during decision-making. We augment the repeated SSG (including SHARP and SUQR) with a reinforced learning algorithm called Naïve Q-Learning. Naïve Q-Learning belongs to the category of active and model-free Machine Learning (ML) techniques in which the agent (either the defender or the attacker) attempts to find an optimal security solution. In this way, we combine GT and ML algorithms for discovering optimal cyber security policies. The proposed security optimization components will be validated in a collaborative cloud platform that is based on the Industrial Internet Reference Architecture (IIRA) and its recently published security model.

Keywords: security, internet of things, cloud computing, stackelberg game, machine learning, naive q-learning

Procedia PDF Downloads 350

Authors: C. W. Kan

Abstract:

Cotton is the most commonly used material for apparel purpose because of its durability, good perspiration absorption characteristics, comfort during wear and dyeability. However, proneness to creasing and wrinkling give cotton garments a poor rating during actual wear. Resin finishing is a process to bring out crease or wrinkle free/resistant effect to cotton fabric. Thus, the aim of this study is to illustrate the proper application of resin finishing to cotton fabric, and the results could provide guidance note to the students in learning this topic. Acknowledgment: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: learning materials, resin, textiles, wrinkle

Procedia PDF Downloads 253

Authors: Zyra Cheska Hidalgo, Joehiza Mae Renon, Kzarina Buen, Girlie Mitrado

Abstract:

ABSTRACT: The global coronavirus disease (COVID-19) has dramatically impacted the lives of many, including education and our economy. Thus, it presents a massive challenge for medical education as instructors are mandated to deliver their lectures virtually to ensure the continuity of the medical education process and ensure students' safety. The purpose of this research paper is to determine the lived experiences of paramedical students who are engaged in virtual hands-on learning and to determine the different coping strategies they used to deal with virtual hands-on learning. The researchers used the survey method of descriptive research design to determine the lived experiences and coping strategies of twenty (20) paramedical students from Lorma Colleges (particularly the College of Medicine Department). The data were collected through online questionnaires, particularly with the use of google forms. This study shows technical issues, difficulty in adapting styles, distractions and time management issues, mental and physical health issues, and lack of interest and motivation are the most common problems and challenges experienced by paramedical students. On the other hand, the coping strategies used by paramedical students to deal with those challenges include time management, engagement in leisure activities, acceptance of responsibilities, studying, and adapting. With the data gathered, the researchers concluded that virtual hands-on learning effectively increases the knowledge of paramedical students. However, teaching and learning barriers must have to be considered to implement virtual hands-on learning successfully.

Keywords: virtual hands-on learning, E-learning, paramedical students, medical education

Procedia PDF Downloads 129

Authors: John G. Vongas, Raghid Al Hajj

Abstract:

We investigated the effects of winning and losing on men’s testosterone and assessed whether androgen reactivity affected their empathic accuracy and their aggression. We also explored whether their power motivation would moderate the relationships between competitive, hormonal, and behavioral outcomes. In Experiment 1, 84 males competed on a task that allegedly gauged their leadership potential and future earnings, after which they interpreted people’s emotional expressions. Results showed that winners were more capable of accurately inferring others’ emotions compared to losers and this ability improved with increasing power. Second, testosterone change mediated the relationship between competitive outcomes and empathic accuracy, with post-competitive testosterone increases relating to more accuracy. In Experiment 2, 72 males again competed after which they were measured on two aggression subtypes: proactive and reactive. Results showed that neither the competitive outcome nor the testosterone change had a significant effect on either types of aggression. However, as power increased, winners aggressed more proactively than losers whereas losers aggressed more reactively than winners. Finally, in both experiments, power moderated the relationship between competitive outcomes and testosterone change. Collectively, these studies add to existing research that explores the psychophysiological effects of competition on individuals’ empathic and aggressive responses.

Keywords: competition, testosterone, power motivation, empathic accuracy, proactive aggression, reactive aggression

Procedia PDF Downloads 302

Authors: Jingwen Shan

Abstract:

In order to explore the key factors affecting the robot program learning intention of school students, this study takes the technology acceptance model as the theoretical basis and invites 167 students from Jiading District of Shanghai as the research subjects. In the robot course, the model of school students on their learning behavior is constructed. By verifying the causal path relationship between variables, it is concluded that teachers can enhance students’ perceptual usefulness to robotics courses by enhancing subjective norms, entertainment perception, and reducing technical anxiety, such as focusing on the gradual progress of programming and analyzing learner characteristics. Students can improve perceived ease of use by enhancing self-efficacy. At the same time, robot hardware designers can optimize in terms of entertainment and interactivity, which will directly or indirectly increase the learning intention of the robot course. By changing these factors, the learning behavior of primary and secondary school students can be more sustainable.

Keywords: TAM, learning behavior intentions, robot courses, primary and secondary school students

Procedia PDF Downloads 148