Search results for: electronic learning

Authors: Sinead Impey, Gaye Stephens, Lucy Hederman, Declan O'Sullivan

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Continued paper use in the clinical area post-Electronic Health Record (EHR) adoption is regularly linked to hardware and software usability challenges. Although paper is used as a workaround to circumvent challenges, including limited availability of a computer, this perspective does not consider the important role paper, such as the nurses’ handover sheet, play in practice. The purpose of this study is to confirm the hypothesis that paper use post-EHR adoption continues as paper provides both a cognitive tool (that assists with workflow) and a compensation tool (to circumvent usability challenges). Distinguishing the different motivations for continued paper-use could assist future evaluations of electronic record systems. Methods: Qualitative data were collected from three clinical care environments (ICU, general ward and specialist day-care) who used an electronic record for at least 12 months. Data were collected through semi-structured interviews with 22 nurses. Data were transcribed, themes extracted using an inductive bottom-up coding approach and a thematic index constructed. Findings: All nurses interviewed continued to use paper post-EHR adoption. While two distinct motivations for paper use post-EHR adoption were confirmed by the data - paper as a cognitive tool and paper as a compensation tool - further finding was that there was an overlap between the two uses. That is, paper used as a compensation tool could also be adapted to function as a cognitive aid due to its nature (easy to access and annotate) or vice versa. Rather than present paper persistence as having two distinctive motivations, it is more useful to describe it as presenting on a continuum with compensation tool and cognitive tool at either pole. Paper as a cognitive tool referred to pages such as nurses’ handover sheet. These did not form part of the patient’s record, although information could be transcribed from one to the other. Findings suggest that although the patient record was digitised, handover sheets did not fall within this remit. These personal pages continued to be useful post-EHR adoption for capturing personal notes or patient information and so continued to be incorporated into the nurses’ work. Comparatively, the paper used as a compensation tool, such as pre-printed care plans which were stored in the patient's record, appears to have been instigated in reaction to usability challenges. In these instances, it is expected that paper use could reduce or cease when the underlying problem is addressed. There is a danger that as paper affords nurses a temporary information platform that is mobile, easy to access and annotate, its use could become embedded in clinical practice. Conclusion: Paper presents a utility to nursing, either as a cognitive or compensation tool or combination of both. By fully understanding its utility and nuances, organisations can avoid evaluating all incidences of paper use (post-EHR adoption) as arising from usability challenges. Instead, suitable remedies for paper-persistence can be targeted at the root cause.

Keywords: cognitive tool, compensation tool, electronic record, handover sheet, nurse, paper persistence

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Authors: Seyed Mehdi Ghezi, Hesam Hasanpoor

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This scientific article explores enhancement methods for ensemble learning with the aim of improving the performance of classifiers in the analysis and classification of brain signals. The research approach in this field consists of two main parts, each with its own strengths and weaknesses. The choice of approach depends on the specific research question and available resources. By combining these approaches and leveraging their respective strengths, researchers can enhance the accuracy and reliability of classification results, consequently advancing our understanding of the brain and its functions. The first approach focuses on utilizing machine learning methods to identify the best features among the vast array of features present in brain signals. The selection of features varies depending on the research objective, and different techniques have been employed for this purpose. For instance, the genetic algorithm has been used in some studies to identify the best features, while optimization methods have been utilized in others to identify the most influential features. Additionally, machine learning techniques have been applied to determine the influential electrodes in classification. Ensemble learning plays a crucial role in identifying the best features that contribute to learning, thereby improving the overall results. The second approach concentrates on designing and implementing methods for selecting the best classifier or utilizing meta-classifiers to enhance the final results in ensemble learning. In a different section of the research, a single classifier is used instead of multiple classifiers, employing different sets of features to improve the results. The article provides an in-depth examination of each technique, highlighting their advantages and limitations. By integrating these techniques, researchers can enhance the performance of classifiers in the analysis and classification of brain signals. This advancement in ensemble learning methodologies contributes to a better understanding of the brain and its functions, ultimately leading to improved accuracy and reliability in brain signal analysis and classification.

Keywords: ensemble learning, brain signals, classification, feature selection, machine learning, genetic algorithm, optimization methods, influential features, influential electrodes, meta-classifiers

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Authors: Kanyaporn Sommeechai

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Air cadets who aspire to become military pilots upon graduation undergo rigorous training at military academies. As first-year cadets are akin to civilian freshmen, they encounter numerous challenges within the seniority-based military academy system. Imposed routines, such as mandatory morning runs and restrictions on mobile phone usage for two semesters, have the potential to impact their learning process and motivation to study, including second language (L2) acquisition. This study aims to investigate the motivational dynamics and L2 learning transitions experienced by air cadets. To achieve this, a Retrodictive Qualitative Modelling approach will be employed, coupled with the adaptation of the three-barrier structure encompassing institutional factors, situational factors, and dispositional factors. Semi-structured interviews will be conducted to gather rich qualitative data. By analyzing and interpreting the collected data, this research seeks to shed light on the motivational factors that influence air cadets' L2 learning journey. The three-barrier structure will provide a comprehensive framework to identify and understand the institutional, situational, and dispositional factors that may impede or facilitate their motivation and language learning progress. Moreover, the study will explore how these factors interact and shape cadets' motivation and learning experiences. The outcomes of this research will yield fundamental data that can inform strategies and interventions to enhance the motivation and language learning outcomes of air cadets. By better understanding their motivational dynamics and transitions, educators and institutions can create targeted initiatives, tailored pedagogical approaches, and supportive environments that effectively inspire and engage air cadets as L2 learners.

Keywords: second language, education, motivational dynamics, learning transitions

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Authors: Eyibo Ebengeobong Eddie, Halil Zafer Alibaba

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The neglect of classroom acoustics is dominant in most educational facilities, meanwhile, hearing and listening is the learning process in this kind of facilities. A classroom should therefore be an environment that encourages listening, without an obstacles to understanding what is being taught. Although different studies have shown teachers to complain that noise is the everyday factor that causes stress in classroom, the capacity of individuals to understand speech is further affected by Echoes, Reverberation, and room modes. It is therefore necessary for classrooms to have an ideal acoustics to aid the intelligibility of students in the learning process. The influence of these acoustical parameters on learning and teaching in schools needs to be further researched upon to enhance the teaching and learning capacity of both teacher and student. For this reason, there is a strong need to provide and collect data to analyse and define the suitable quality of classrooms needed for a learning environment. Research has shown that acoustical problems are still experienced in both newer and older schools. However, recently, principle of acoustics has been analysed and room acoustics can now be measured with various technologies and sound systems to improve and solve the problem of acoustics in classrooms. These acoustic solutions, materials, construction methods and integration processes would be discussed in this paper.

Keywords: classroom, acoustics, materials, integration, speech intelligibility

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Authors: Kai Qian, Lixin Tao

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Mobile devices such as smartphones are getting more and more popular in our daily lives. The security vulnerability and threat attacks become a very emerging and important research and education topic in computing security discipline. There is a need to have an innovative mobile security hands-on laboratory to provide students with real world relevant mobile threat analysis and protection experience. This paper presents an authentic teaching and learning mobile security approach with smartphone devices which covers most important mobile threats in most aspects of mobile security. Each lab focuses on one type of mobile threats, such as mobile messaging threat, and conveys the threat analysis and protection in multiple ways, including lectures and tutorials, multimedia or app-based demonstration for threats analysis, and mobile app development for threat protections. This authentic learning approach is affordable and easily-adoptable which immerse students in a real world relevant learning environment with real devices. This approach can also be applied to many other mobile related courses such as mobile Java programming, database, network, and any security relevant courses so that can learn concepts and principles better with the hands-on authentic learning experience.

Keywords: mobile computing, Android, network, security, labware

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Authors: Mehrab Karimian

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The present research aimed to investigate the problems of teaching and learning English in middle schools in Esfahan, Iran. These problems are associated with the learner, teacher, textbook, syllabus, and language policy. The instrument used was a self-constructed likert scale questionnaire. All the variables had a hand in the problems among which textbook, syllabus and language policy had the most effect. Twenty five problems were distinguished among which some are as follows: students do not consider pair work important; most of the time, most teachers do not speak in English in the classroom; the textbook does not include CDs or cassettes, does not consists of all the English Skills; the syllabus does not include one or two projects for students apart from the midterm or final test, Language Policy being not completely familiar with the steps of EFL teaching, does not selecting the most qualified and proficient teachers in EFL teaching. It can be concluded that the language policy should take a practical step in reducing the problems by changing the textbooks and providing more teaching aids for the teachers.

Keywords: teaching and learning english, problems of teaching and learning english, middle school, Iran

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Authors: Martina Holenko Dlab, Natasa Hoic-Bozic

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This paper presents an original approach to student and group activity level assessment that relies on certainty factors theory. Activity level is used to represent quantity and continuity of student’s contributions in individual and collaborative e‑learning activities (e‑tivities) and is calculated to assist teachers in assessing quantitative aspects of student's achievements. Calculated activity levels are also used to raise awareness and provide recommendations during the learning process. The proposed approach was implemented within the educational recommender system ELARS and validated using data obtained from e‑tivity realized during a blended learning course. The results showed that the proposed approach can be used to estimate activity level in the context of e-tivities realized using Web 2.0 tools as well as to facilitate the assessment of quantitative aspect of students’ participation in e‑tivities.

Keywords: assessment, ELARS, e-learning, recommender systems, student model

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Authors: Priyadarshini Kiran, Gulshan Kumar

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: Social media are becoming the most important tools for interaction among learners, pedagogues and parents where everybody can share, exchange, comment, discuss and create information and knowledge in a collaborative way. The present case study attempts to highlight the role of social media (WhatsApp) in nurturing learning habits in toddlers with the help of parents in primary education. The Case study is based on primary data collected from a primary school situated in a small town in the northern state of Uttar Pradesh, India. In research methodology, survey and structured interviews have been used as a tool collected from parents and pedagogues. The findings Suggest: - To nurture learning habits in toddlers, parents and pedagogues use social media site (WhatsApp) in real-time and that too is convenient and handy; - Skill enhancement on the part of Pedagogues as a result of employing innovative teaching-learning techniques; - Social media sites serve as a social connectivity tool to ward off negativity and monotony on the part of parents and pedagogues in the wake of COVID- 19

Keywords: innovative teaching-learning techniques, pedagogues, social media, nurture, toddlers

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Authors: Aanuoluwapo Olusola Adesanya, Adesina Joseph

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This paper examined the class-size and instructional materials as correlates of pupils learning and academic achievement in primary school. The population of the study comprised 198 primary school pupils in three selected schools in Ogun State, Nigeria. Data were collected through questionnaire and were analysed with the use of multiple regression and ANOVA to analysed the correlation between class-size, instructional materials (independent variables) and learning achievement (dependent variable). The findings revealed that schools having an average class-size of 30 and below with use of instructional materials obtained better results than schools having more than 30 and above. The main score were higher in the school in schools having 30 and below than schools with 30 and above. It was therefore recommended that government, stakeholders and NGOs should provide more classrooms and supply of adequate instructional materials in all primary schools in the state to cater for small class-size.

Keywords: class-size, instructional materials, learning, academic achievement

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Authors: Onesimus Bulus Shiaki

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The study investigated the effect of cooperative learning strategy on mathematics achievement and retention among senior secondary school students of different abilities in Taraba State Nigeria. Cooperative learning strategy could hopefully contribute to students’ achievement which will spur the teachers to develop strategies for better learning. The quasi-experimental of pretest, posttest and control group design was adopted in this study. A sample of one hundred and sixty-four (164) Senior Secondary Two (SS2) students were selected from a population of twelve thousand, eight hundred and seventy-three (12,873) SS2 Students in Taraba State. Two schools with equivalent mean scores in the pre-test were randomly assigned to experimental and control groups. The experimental group students were stratified according to ability levels of low, medium and high. The experimental group was guided by the research assistants using the cooperative learning instructional package. After six weeks post-test was administered to the two groups while the retention test was administered two weeks after the post-test. The researcher developed a 50-item Mathematics Achievement Test (MAT) which was validated by experts obtaining the reliability coefficient of 0.87. Mean scores and standard deviations were used to answer the research questions while the Analysis of Co-variance (ANCOVA) was used to test the hypotheses. Major findings from the statistical analysis showed that cooperative learning strategy has a significant effect on the mean achievement of students as well as retention among students of high, medium and low ability in mathematics. However, cooperative learning strategy has no effect on the interaction of ability level and retention. Based on the results obtained, it was therefore recommended that the adoption of the use of cooperative learning strategy in the teaching and learning of mathematics in senior secondary schools be initiated, maintained and sustained for the benefit of senior secondary school students in Taraba State. Periodic Government sponsored in-service training in form of long vacation training programme, workshops, conferences and seminars on the nature, scope, and use of cooperative learning strategy should be organized for senior secondary school mathematics teachers in Taraba state.

Keywords: ability level, cooperative learning, mathematics achievement, retention

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Authors: Maria Isabel Garcia-Planas, Maria Victoria Garcia-Camba

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The use of brain stem auditory evoked potential (BAEP) is a common way to study the auditory function of people, a way to learn the functionality of a part of the brain neuronal groups that intervene in the learning process by studying the behaviour of wave VI. The latest advances in neuroscience have revealed the existence of different brain activity in the learning process that can be highlighted through the use of innocuous, low-cost, and easy-access techniques such as, among others, the BAEP that can help us to detect early possible neurodevelopmental difficulties for their subsequent assessment and cure. To date and to the authors' best knowledge, only the latency data obtained, observing the first to V waves and mainly in the left ear, were taken into account. This work shows that it is essential to take into account both ears; with these latest data, it has been possible had diagnosed more precise some cases than with the previous data had been diagnosed as 'normal' despite showing signs of some alteration that motivated the new consultation to the specialist.

Keywords: ear, neurodevelopment, auditory evoked potentials, intervals of normality, learning disabilities

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Authors: S. R. M. Krishna, R. Santosh Kumar, V. Kamakshi Prasad

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Machine learning techniques are applied for the analysis of the impact of mental illness on the burden of disease. It is calculated using the disability-adjusted life year (DALY). DALYs for a disease is the sum of years of life lost due to premature mortality (YLLs) + No of years of healthy life lost due to disability (YLDs). The critical analysis is done based on the Data sources, machine learning techniques and feature extraction method. The reviewing is done based on major databases. The extracted data is examined using statistical analysis and machine learning techniques were applied. The prediction of the impact of mental illness on the population using machine learning techniques is an alternative approach to the old traditional strategies, which are time-consuming and may not be reliable. The approach makes it necessary for a comprehensive adoption, innovative algorithms, and an understanding of the limitations and challenges. The obtained prediction is a way of understanding the underlying impact of mental illness on the health of the people and it enables us to get a healthy life expectancy. The growing impact of mental illness and the challenges associated with the detection and treatment of mental disorders make it necessary for us to understand the complete effect of it on the majority of the population.

Keywords: ML, DAL, YLD, YLL

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Authors: Anjum Afrooze

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The curriculum at General Sciences department in Prince Sultan University includes ‘Physical science’ for Computer Science, Information Technology and Business courses. Students are apathetic towards Physical Science and question, as to, ‘How this course is related to their majors?’ English is not a native language for the students and also for many instructors. More than sixty percent of the students come from institutions where English is not the medium of instruction, which makes student learning and academic achievement challenging. After observing the less enthusiastic student cohort for two consecutive semesters, the instructor was keen to find effective strategies to enhance learning and further encourage deep learning by engaging students in different tasks to empower them with necessary skills and motivate them. This study is participatory action research, in which instructor designs effective tasks to engage students in their learning. The study is conducted through two semesters with a total of 200 students. The effectiveness of this approach is studied using questionnaire at the end of each semester and teacher observation. Major outcomes of this study were overall improvement in students attitude towards science learning, enhancement of multiple skills like note taking, problem solving, language proficiency and also fortifying confidence. This process transformed instructor into engaging and reflecting practitioner. Also, these strategies were implemented by other instructors teaching the course and proved effective in opening a path to changes in related areas of the course curriculum. However, refinement in the strategies could be done based on student evaluation and instructors observation.

Keywords: group activity, language proficiency, reasoning skills, science learning

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Authors: Dalia Almaghaslah

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Design thinking approach; empathize, define, ideate prototype, test, implement, was used to assess outpatient experiences in two hospital pharmacies in the Asir region, Saudi Arabia. Semi-structured interviews were conducted with 40 patients. The data were analyzed using thematic analysis. The findings suggested that patients were generally satisfied with pharmaceutical services provided in both pharmacies. Pharmacists were found to have enough knowledge, good attitude, and efficient communication and counselling skills. Non-pharmacy-related factors such as cultural factors (gender segregation), long waiting times, uncomfortable waiting areas, lack of electronic prescribing, number waiting system were found to have a negative impact on patients' experiences and satisfaction. Prototypes will be used to test the effects of implementing the electronic system in Al -mahal hospital and to test changing the physical layout of the waiting area in Asir hospital.

Keywords: design thinking, hospital pharmacy, patient satisfaction, Saudi Arabia

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Authors: Rashika Sharma

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The campuses at tertiary institutes can act as a social environment for peer to peer connections. However, socialization is not the only aspect that campuses provide. The campus can act as a learning environment that has often been termed as the campus curriculum. Many tertiary institutes have taken steps to make their campus a ‘green campus’ whereby initiatives have been taken to reduce their impact on the environment. However, as visible as these initiatives are, it is debatable whether these have any effect on students’ and their understanding of sustainable campus operations. Therefore, research was conducted to evaluate the effectiveness of sustainable campus operations in raising students’ awareness of sustainability. Students at two vocational institutes participated in this interpretive research with data collected through surveys and focus groups. The findings indicated that majority of vocational education students remained oblivious of sustainability initiatives on campuses.

Keywords: campus learning, education for sustainability, social learning, vocational education

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Authors: Hala Shaari, Nuredin Ahmed

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Teaching computer programming is recognized to be difficult and a real challenge. The biggest problem faced by novice programmers is their lack of understanding of basic programming concepts. A visualized learning tool was developed and used by volunteered first-year students for two semesters. The purposes of this paper are firstly, to emphasize factors which directly affect the performance of our students negatively. Secondly, to examine whether the proposed tool would improve their performance and learning progression. The results of adopting this tool were conducted using a pre-survey and post-survey questionnaire. As a result, students who used the learning tool showed better performance in their programming subject.

Keywords: factors, novice, programming, visualization

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Authors: Cahit Perkgöz

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Artificial intelligence has brought new approaches to solving problems in almost every research field in recent years. One of these topics is shape design and optimization, which has the possibility of applications in many fields, such as nanotechnology and electronics. A properly constructed cost function can eliminate the need for labeled data required in deep learning and create desired shapes. In this work, the network parameters are optimized differentially, which differs from traditional approaches. The methods are tested for physics-related structures and successful results are obtained. This work is supported by Eskişehir Technical University scientific research project (Project No: 20ADP090)

Keywords: deep learning, shape design, optimization, artificial intelligence

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Authors: Mohammad Rostami, Mohammad Reza Forghani, Elahe Neshat, Fatemeh Yaghoobi

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An Ad Hoc network consists of wireless mobile equipment which connects to each other without any infrastructure, using connection equipment. The best way to form a hierarchical structure is clustering. Various methods of clustering can form more stable clusters according to nodes' mobility. In this research we propose an algorithm, which allocates some weight to nodes based on factors, i.e. link stability and power reduction rate. According to the allocated weight in the previous phase, the cellular learning automaton picks out in the second phase nodes which are candidates for being cluster head. In the third phase, learning automaton selects cluster head nodes, member nodes and forms the cluster. Thus, this automaton does the learning from the setting and can form optimized clusters in terms of power consumption and link stability. To simulate the proposed algorithm we have used omnet++4.2.2. Simulation results indicate that newly formed clusters have a longer lifetime than previous algorithms and decrease strongly network overload by reducing update rate.

Keywords: mobile Ad Hoc networks, clustering, learning automaton, cellular automaton, battery power

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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Authors: Shamim Ahsan

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Abstract Global digital advances associated with consumer’s strong inclination for the state of art digital technologies is causing overwhelming social and environmental challenges for global community. During recent years not only economic advances of electronic industries has taken place at steadfast rate, also the generation of e-waste outshined the growth of any other types of wastes. The estimated global e-waste volume is expected to reach 65.4 million tons annually by 2017. Formal recycling practices in developed countries are stemming economic liability, opening paths for illegal trafficking to developing countries. Informal crude management of large volume of e-waste is transforming into an emergent environmental and health challenge in. Contrariwise, in several studies formal and informal recycling of e-waste has also exhibited potentials for economic returns both in developed and developing countries. Some research on China illustrated that from large volume of e-wastes generation there are recycling potential in evolving from ∼16 (10−22) billion US$ in 2010, to an anticipated ∼73.4 (44.5−103.4) billion US$ by 2030. While in another study, researcher found from an economic analysis of 14 common categories of waste electric and electronic equipment (WEEE) the overall worth is calculated as €2.15 billion to European markets, with a potential rise to €3.67 billion as volumes increase. These economic returns and environmental protection approaches are feasible only when sustainable policy options are embraced with stricter regulatory mechanism. This study will critically review current researches to stipulate how global e-waste generation and sustainable e-waste recycling practices demonstrate future economic development potential in terms of both quantity and processing capacity, also triggering complex some environmental challenges.

Keywords: E-Waste, , Generation, , Economic Potential, Recycling

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Authors: Khaled Alotaibi

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This paper deals with developing reasoning thinking and the intrinsic-extrinsic motivation for learning, and enhancing the academic achievement of a sample of students at Teachers' College in King Saud University. The study sample included 58 students who were divided randomly into two groups; one was an experimental group with 20 students and the other was a control group with 22 students. The following tools were used: e-courses by using I-map, Reasoning Thinking Tes, questionnaire to measure the intrinsic-extrinsic motivation for learning and an academic achievement test. Experimental group was taught using e-courses by using I-map, while the control group was taught by using traditional education. The results showed that: - There were no statistically significant differences between the experimental group and the control group in Reasoning thinking skills. - There were statistically significant differences between the experimental group and the control group in the intrinsic-extrinsic motivation for learning in favor of the experimental group. - There were statistically significant differences between the experimental group and the control group in academic achievement in favor of the experimental group.

Keywords: reasoning, thinking, intrinsic motivation, active learning

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Authors: Mridul Sharma, Praveen Saroha

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In today's world, everyone has become so busy in their to-do tasks and daily routine that they tend to ignore some of the basal components of our life, including exercise and diet. This comparative study analyzes the pathways of the relationship between exercise and brain plasticity and also includes another variable diet to study the effects of diet on learning by answering questions including which diet is known to be the best learning supporter and what are the recommended quantities of the same. Further, this study looks into inter-relation between diet and exercise, and also some other approach of the relation between diet and exercise on learning apart from through Brain Derived Neurotrophic Factor (BDNF).

Keywords: brain derived neurotrophic factor, brain plasticity, diet, exercise

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Authors: Jui Hsuan Hung, Jeng Yi Tzeng

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Engineering education in the higher education is always male dominated. Therefore, women learning in this environment is an important research topic for feminists, gender researchers and engineering education researchers, especially in the era of gender mainstreaming. The research topics are from the dialectical discussion of feminism and science development history, gender issues of science education, to the subject choice of female students. These researches enrich the field of gender study in engineering education but lack of describing the detailed images of women in engineering education, including their learning, obstacles, needs or feelings. Otherwise, in order to keep up with the industrial trends of emphasizing group collaboration, engineering education turns from traditional lecture to creative group inquiry pedagogy in recent years. Creative project based learning is one of the creative group inquiry pedagogy which the engineering education in higher education adopts often, and it is seen as a gender-inclusive pedagogy in engineering education. Therefore, in order to understand the real situation of women learning in engineering education, this study took place in a course (Introduction to Engineering) offered by the school of engineering of a university in Taiwan. This course is designed for freshman students to establish basic understanding engineering from four departments (Chemical Engineering, Power Mechanical Engineering, Materials Science, Industrial Engineering and Engineering Management). One section of this course is to build a Hydraulic Robot designed by the Department of Power Mechanical Engineering. 321 students in the school of engineering took this course and all had the reflection questionnaire. These students are divided into groups of 5 members to work on this project. The videos of process of discussion of five volunteered groups with different gender composition are analyzed, and six women of these five groups are interviewed. We are still on the process of coding and analyzing videos and the qualitative data, but several tentative findings have already emerged. (1) The activity models of groups of both genders are gender segregation, and not like women; men never be the ‘assistants’. (2) The culture of the group is developed by the major gender, but men always dominate the process of practice in all kinds of gender composition groups. (3) Project based learning is supposed to be a gender-inclusive learning model in creative engineering education, but communication obstacles between men and women make it less women friendly. (4) Gender identity, not professional identity, is adopted by these women while they interact with men in their groups. (5) Gender composition and project-based learning pedagogy are not the key factors for women learning in engineering education, but the gender conscience awareness is.

Keywords: engineering education, gender education, creative project based learning, women learning

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Authors: Rishi Kanth Saripalle

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Medical experts highly recommend to include physical activity in everyone’s daily routine irrespective of gender or age as it helps to improve various medical issues or curb potential issues. Simultaneously, experts are also diligently trying to provide various healthcare services (interventions, plans, exercise routines, etc.) for promoting healthy living and increasing physical activity in one’s ever increasing hectic schedules. With the introduction of wearables, individuals are able to keep track, analyze, and visualize their daily physical activities. However, there seems to be no common agreed standard for representing, gathering, aggregating and analyzing an individual’s physical activity data from disparate multiple sources (exercise pans, multiple wearables, etc.). This issue makes it highly impractical to develop any data-driven physical activity applications and healthcare programs. Further, the inability to integrate the physical activity data into an individual’s Electronic Health Record to provide a wholistic image of that individual’s health is still eluding the experts. This article has identified three primary reasons for this potential issue. First, there is no agreed standard, both structure and semantic, for representing and sharing physical activity data across disparate systems. Second, various organizations (e.g., LA fitness, Gold’s Gym, etc.) and research backed interventions and programs still primarily rely on paper or unstructured format (such as text or notes) to keep track of the data generated from physical activities. Finally, most of the wearable devices operate in silos. This article identifies the underlying problem, explores the idea of reusing existing standards, and identifies the essential modules required to move forward.

Keywords: electronic physical activity record, physical activity in EHR EIM, tracking physical activity data, physical activity data standards

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Authors: Mariana Paz Sajon, Paula Cecilia Primogerio, Mariana Albarracin

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This study recovers an experience of teacher training carried out in an Undergraduate Business School from a private university in Buenos Aires, Argentina. The purpose of the project was to provide teachers with an opportunity to reflect on their teaching practices at the university. The aim of the study is to systematize lessons and challenges that emerge from this teacher training experience. A group of teachers who showed a willingness to learn teaching abilities was selected to work. They completed a formative journey working in learning communities starting from the immersion in different aspects of teaching and learning, class observations, and an individual and collaborative reflection exercise in a systematic way among colleagues. In this study, the productions of the eight teachers who are members of the learning communities are analyzed, framed in an e-portfolio that they prepared during the training journey. The analysis shows that after the process of shared reflection, traits related to powerful teaching and meaningful learning have appeared in the classes. For their part, teachers reflect having reached an awareness of their own practices, identifying strengths and opportunities for improvement, and the experience of sharing their own way and knowing the successes and failures of others was valued. It is an educational journey of pedagogical transformation of the teachers, which is infrequent in business education, which could lead to a change in teaching practices for the entire Business School. The present study involves theoretical and pedagogic aspects of education in a business school in Argentina and its flow-on implications for the workplace that may be transferred to other educational contexts.

Keywords: Argentina, learning community, meaningful learning, powerful teaching, reflective practice

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Authors: Sutharsini Jesuthasan, N. Umakanth

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Presently the impact of electronic word of mouth on consumer’s purchasing intentions very popular one for a long time period. Even though now this E-WOM got a new evolution through social media. Before this new concept, general people were able to speak with any people on the internet. But likely social media enable people to talk with colleagues, friends and other people on the internet. Meanwhile, this new path way of E-WOM might be more powerful in terms of confusing purchase intention. And negative side of E-WOM very important in this competitive era. So, this study elaborates the negative E-WOM within the context of social media such as face book. And especially this study identifies the influence of negative E-WOM in social media on consumer’s purchase intention. Virtual snowball sampling method was used by researcher to identify the hidden population. Finally, spss 20.0 also used for data analysis purpose. And conclusion and recommendations are given based on the findings. And this research also will support to both parties such as researcher and participants.

Keywords: word of mouth, social media, purchase intention, electronic word of mouth

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Authors: Jose Gay D. Gallego

Abstract:

This study examined the learning performance in General Psychology of 297 freshmen of the CPSU-Main through the Pre and Post Tests. The instructional intervention via Universal Design for Learning (UDL) was applied to 33% (97 out of 297) of these freshmen as the Treatment Group while the 67% (200) belonged to the Control Group for traditional instructions. Statistical inferences utilized one-way Analysis of Variance for mean differences; Pearson R Correlations for bivariate relationships, and; Factor Analysis for significant components that contributed most to the Universal Design for Learning instructions. Findings showed very high levels of students’ acquired UDL skills. Results in the pre test in General Psychology, respectively, were low and average when grouped into low and high achievers. There was no significant mean difference in the acquired nine UDL components when categorized into seven colleges to generalize that between colleges they were on the same very high levels. Significant differences were found in three test areas in General Psychology in eight colleges whose students in College of teacher education taking the lead in the learning performance. Significant differences were also traced in the post test in favor of the students in the treatment group. This proved that UDL really impacted the learning performance of the low achieving students. Significant correlations were revealed between the components of UDL and General Psychology. There were twenty four significant itemized components that contributed most to UDL instructional interventions. Implications were emphasized to maximizing the principles of UDL with the contention of thoughtful planning related to the four curricular pillars of UDL: (a) instructional goals, (b) instructional delivery methods, (c) instructional materials, and (d) student assessments.

Keywords: universal design for learning, enhanced performance, teaching innovation, technology in education, social science area

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Authors: Ramzi Rihane, Yassine Benayed

Abstract:

Epilepsy is a chronic neurological disorder characterized by recurrent, unprovoked seizures resulting from abnormal electrical activity in the brain. Timely and accurate detection of these seizures is essential for improving patient care. In this study, we leverage the UK Bonn University open-source EEG dataset and employ advanced deep-learning techniques to automate the detection of epileptic seizures. By extracting key features from both time and frequency domains, as well as Spectrogram features, we enhance the performance of various deep learning models. Our investigation includes architectures such as Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), 1D Convolutional Neural Networks (1D-CNN), and hybrid CNN-LSTM and CNN-BiLSTM models. The models achieved impressive accuracies: LSTM (98.52%), Bi-LSTM (98.61%), CNN-LSTM (98.91%), CNN-BiLSTM (98.83%), and CNN (98.73%). Additionally, we utilized a data augmentation technique called SMOTE, which yielded the following results: CNN (97.36%), LSTM (97.01%), Bi-LSTM (97.23%), CNN-LSTM (97.45%), and CNN-BiLSTM (97.34%). These findings demonstrate the effectiveness of deep learning in capturing complex patterns in EEG signals, providing a reliable and scalable solution for real-time seizure detection in clinical environments.

Keywords: electroencephalogram, epileptic seizure, deep learning, LSTM, CNN, BI-LSTM, seizure detection

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Authors: Essang Anwana Onuntuei, Chinyere Blessing Azunwoke

Abstract:

The study focused on probing the effectiveness of online consumer privacy and protection laws, electronic transaction laws, privacy and data protection laws, and cybercrime legislation amid frequent cyber-attacks and malware types worldwide. An empirical analysis was engaged to uncover ties and causations between the stringency and implementation of these legal structures and the prevalence of cyber threats. A deliberate sample of seventy-eight countries (thirteen countries each from six continents) was chosen as sample size to study the challenges linked with trending regulations and possible panoramas for improving cybersecurity through refined legal approaches. Findings establish if the frequency of cyber-attacks and malware types vary significantly. Also, the result proved that various cybercrime laws differ statistically, and electronic transactions law does not statistically impact the frequency of cyber-attacks. The result also statistically revealed that the online Consumer Privacy and Protection law does not influence the total number of cyber-attacks. In addition, the results implied that Privacy and Data Protection laws do not statistically impact the total number of cyber-attacks worldwide. The calculated value also proved that cybercrime law does not statistically impact the total number of cyber-attacks. Finally, the computed value concludes that combined multiple cyber laws do not significantly impact the total number of cyber-attacks worldwide. Suggestions were produced based on findings from the study, contributing to the ongoing debate on the validity of legal approaches in battling cybercrime and shielding consumers in the digital age.

Keywords: cybercrime legislation, cyber attacks, consumer privacy and protection law, detection, electronic transaction law, prevention, privacy and data protection law, prohibition, prosecution

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Authors: Dominic Huschke, Rudolf Keil

Abstract:

New driving functionalities like highly automated driving have a major impact on the electrics/electronics architecture of future vehicles and inevitably lead to higher safety requirements. Partly due to these increased requirements, the vehicle industry is increasingly looking at semiconductor switches as an alternative to conventional melting fuses. The protective functionality of semiconductor switches can be implemented in hardware as well as in software. A current approach discussed in science and industry is the implementation of a model of the protected low voltage power cable on a microcontroller to calculate its temperature. Here, the information regarding the current is provided by the continuous current measurement of the semiconductor switch. The signal to open the semiconductor switch is provided by the microcontroller when a previously defined limit for the temperature of the low voltage power cable is exceeded. A setup for the testing of the described principle for electronic fuse protection of a low voltage power cable is built and successfullyvalidated with experiments afterwards. Here, the evaluation criterion is the deviation of the measured temperature of the low voltage power cable from the specified limit temperature when the semiconductor switch is opened. The analysis is carried out with an assumed ambient temperature as well as with a measured ambient temperature. Subsequently, the experimentally performed investigations are simulated in a virtual environment. The explicit focus is on the simulation of the behavior of the microcontroller with an implemented model of a low voltage power cable in a real-time environment. Subsequently, the generated results are compared with those of the experiments. Based on this, the completely virtual design of the described approach is assumed to be valid.

Keywords: automotive wire harness, electronic fuse protection, low voltage power cable, semiconductor-based fuses, software-based validation

Procedia PDF Downloads 105