Search results for: enabling learning environment

Authors: T. Hopkin, S. Lu, P. Rogers, M. Sexton

Abstract:

Housing Associations (HAs) contribute circa 20% of the UK’s housing supply. HAs are however under increasing pressure as a result of funding cuts and rent reductions. Due to the increased pressure, a number of processes are currently being reviewed by HAs, especially how they manage and learn from defects. Learning from defects is considered a useful approach to achieving defect reduction within the UK housebuilding industry. This paper contributes to our understanding of how HAs learn from defects by undertaking an initial round table discussion with key HA stakeholders as part of an ongoing collaborative research project with the National House Building Council (NHBC) to better understand how house builders and HAs learn from defects to reduce their prevalence. The initial discussion shows that defect information runs through a number of groups, both internal and external of a HA during both the defects management process and organizational learning (OL) process. Furthermore, HAs are reliant on capturing and recording defect data as the foundation for the OL process. During the OL process defect data analysis is the primary enabler to recognizing a need for a change to organizational routines. When a need for change has been recognized, new options are typically pursued to design out defects via updates to a HAs Employer’s Requirements. Proposed solutions are selected by a review board and committed to organizational routine. After implementing a change, both structured and unstructured feedback is sought to establish the change’s success. The findings from the HA discussion demonstrates that OL can achieve defect reduction within the house building sector in the UK. The paper concludes by outlining a potential ‘learning from defects model’ for the housebuilding industry as well as describing future work.

Keywords: defects, new homes, housing association, organizational learning

Procedia PDF Downloads 300

Authors: Charléa M. Smith, Raiden L. Schodowski, Arletty Pinel

Abstract:

Due to the COVID-19 pandemic, the Faculty of Medical Sciences of The University of the West Indies (UWI) Mona in Kingston, Jamaica, had to rapidly migrate to digital and blended learning. Students in the preclinical stage of the program transitioned to full-time online learning, while students in the clinical stage experienced decreased daily patient contact and the implementation of a blend of online lectures and virtual clinical practice. Such sudden changes were coupled with the institutional pressure of the need to introduce a novel approach to education without much time for preparation, as well as additional strain endured by the faculty, who were overwhelmed by serving as frontline workers. During the period July 20 to August 23, 2021, this study surveyed preclinical and clinical students to capture their experiences with these changes and their recommendations for future use of digital modalities of learning to enhance medical education. It was conducted with a fellow student of the 2021 cohort of the MultiPod mentoring program. A questionnaire was developed and distributed digitally via WhatsApp to all medical students of the UWI Mona campus to assess students’ experiences and perceptions of the advantages, challenges, and impact on individual knowledge proficiencies brought about by the transition to predominantly digital learning environments. 108 students replied, 53.7% preclinical and 46.3% clinical. 67.6% of the total were female and 30.6 % were male; 1.8% did not identify themselves by gender. 67.2% of preclinical students preferred blended learning and 60.3% considered that the content presented did not prepare them for clinical work. Only 31% considered that the online classes were interactive and encouraged student participation. 84.5% missed socialization with classmates and friends and 79.3% missed a focused environment for learning. 80% of the clinical students felt that they had not learned all that they expected and only 34% had virtual interaction with patients, mostly by telephone and video calls. Observing direct consultations was considered the most useful, yet this was the least-used modality. 96% of the preclinical students and 100% of the clinical ones supplemented their learning with additional online tools. The main recommendations from the survey are the use of interactive teaching strategies, more discussion time with lecturers, and increased virtual interactions with patients. Universities are returning to face-to-face learning, yet it is unlikely that blended education will disappear. This study demonstrates that students’ perceptions of their experience during mobility restrictions must be taken into consideration in creating more effective, inclusive, and efficient blended learning opportunities.

Keywords: blended learning, digital learning, medical education, student perceptions

Procedia PDF Downloads 144

Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: big data, machine learning, smart city, social cost, transportation network

Procedia PDF Downloads 240

Authors: Abbos Utkirov

Abstract:

Total Quality Management (TQM) in the context of educational institutions requires careful planning and the implementation of an annual quality program to achieve its vision effectively. By applying TQM concepts, the higher education system can experience significant improvements. This study aims to examine TQM in higher education, focusing on Critical Success Factors (CSF) and their implementation across all areas. The study ultimately concludes that CSF and their execution play a crucial role in higher education institutions. Some institutions have already benefited from TQM methods by dedicating themselves to the system and using it to achieve their objectives. Through this review, recent studies shed light on how the TQM system can employ various strategies and hypotheses to empower employees, foster a positive and supportive environment, and emphasize the importance of enabling students to unleash their full potential.

Keywords: total quality management (TQM), critical success factor (CSF), organizational performance, quality management practices

Procedia PDF Downloads 77

Authors: Dante J. Dorantes-González, Aldrin Balsa-Yepes

Abstract:

Existing learning techniques such as problem-based learning, project-based learning, or case study learning are learning techniques that focus mainly on technical details, but give no specific guidelines on learner’s experience and emotional learning aspects such as arousal salience and valence, being emotional states important factors affecting engagement and retention. Some approaches involving emotion in educational settings, such as social and emotional learning, lack neuroscientific rigorousness and use of specific neurobiological mechanisms. On the other hand, neurobiology approaches lack educational applicability. And educational approaches mainly focus on cognitive aspects and disregard conditioning learning. First, authors start explaining the reasons why it is hard to learn thoughtfully, then they use the method of neurobiological mapping to track the main limbic system functions, such as the reward circuit, and its relations with perception, memories, motivations, sympathetic and parasympathetic reactions, and sensations, as well as the brain cortex. The authors conclude explaining the major finding: The mechanisms of nonconscious learning and the triggers that guarantee long-term memory potentiation. Afterward, the educational framework for practical application and the instructors’ guidelines are established. An implementation example in engineering education is given, namely, the study of tuned-mass dampers for earthquake oscillations attenuation in skyscrapers. This work represents an original learning technique based on nonconscious learning mechanisms to enhance long-term memories that complement existing cognitive learning methods.

Keywords: emotion, emotion-enhanced memory, learning technique, STEM

Procedia PDF Downloads 76

Authors: Zhuang Hou, Xiaolei Cao

Abstract:

The general public and medical professionals recognized the importance of accurately measuring and storing blood oxygen levels and heart rate during the COVID-19 pandemic. The demand for accurate contactless devices was motivated by the need for cross-infection reduction and the shortage of conventional oximeters, partially due to the global supply chain issue. This paper evaluated a contactless mini program HealthyPai’s heart rate (HR) and oxygen saturation (SpO2) measurements compared with other wearable devices. In the HR study of 185 samples (81 in the laboratory environment, 104 in the real-life environment), the mean absolute error (MAE) ± standard deviation was 1.4827 ± 1.7452 in the lab, 6.9231 ± 5.6426 in the real-life setting. In the SpO2 study of 24 samples, the MAE ± standard deviation of the measurement was 1.0375 ± 0.7745. Our results validated that HealthyPai utilizing the Integrated Image Deep Learning Solution (IIDLS) framework, can accurately measure HR and SpO2, providing the test quality at least comparable to other FDA-approved wearable devices in the market and surpassing the consumer-grade and research-grade wearable standards.

Keywords: remote photoplethysmography, heart rate, oxygen saturation, contactless measurement, mini program

Procedia PDF Downloads 116

Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

Abstract:

Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

Procedia PDF Downloads 153

Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias

Abstract:

Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.

Keywords: healthcare, fall detection, transformer, transfer learning

Procedia PDF Downloads 111

Authors: Chen-Ya Juan

Abstract:

In recent years, the increasing number of children with special needs has brought a lot of attention by many scholars and experts in education, which enforced the preschool teachers face the harsh challenge in the classroom. To protect the right of equal education for all children, enhance the quality of children learning, and take care of the needs of children with special needs, the special education paraprofessional becomes one of the future employment trends for students of the department of the early childhood care and education. Problem-based learning is a problem-oriented instruction, which is different from traditional instruction. The instructor first designed an ambiguous problem direction, following the basic knowledge of early intervention, students had to find clues to solve the problem defined by themselves. In the class, the total instruction included 20 hours, two hours per week. The primary purpose of this paper is to investigate the relationship of student academic scores, self-awareness, learning motivation, learning attitudes, and early intervention knowledge. A total of 105 college students participated in this study and 97 questionnaires were effective. The effective response rate was 90%. The student participants included 95 females and two males. The average age of the participants was 19 years old. The questionnaires included 125 questions divided into four major dimensions: (1) Self-awareness, (2) learning motivation, (3) learning attitudes, and (4) early intervention knowledge. The results indicated (1) the scores of self-awareness were 58%; the scores of the learning motivations was 64.9%; the scores of the learning attitudes was 55.3%. (2) After the instruction, the early intervention knowledge has been increased to 64.2% from 38.4%. (3) Student’s academic performance has positive relationship with self-awareness (p < 0.05; R = 0.506), learning motivation (p < 0.05; R = 0.487), learning attitudes (p < 0.05; R = 0.527). The results implied that although students had gained early intervention knowledge by using PBL instruction, students had medium scores on self-awareness and learning attitudes, medium high in learning motivations.

Keywords: college students, children with special needs, problem-based learning, learning motivation

Procedia PDF Downloads 142

Authors: Hamza Zidoum

Abstract:

This paper investigates the impact of human genetic variation on the function of human proteins using machine-learning algorithms. Single-Nucleotide Polymorphism represents the most common form of human genome variation. We focus on the single amino-acid polymorphism located in the coding region as they can affect the protein function leading to pathologic phenotypic change. We use several supervised Machine Learning methods to identify structural properties correlated with increased risk of the missense mutation being damaging. SVM associated with Principal Component Analysis give the best performance.

Keywords: single-nucleotide polymorphism, machine learning, feature selection, SVM

Procedia PDF Downloads 360

Authors: Maaly Jarrah

Abstract:

In a study abroad context, students have the advantage of immersing themselves in the environment of the target language and being exposed to it. However, in and a stay home context, where English is not the mother tongue, students’ exposure to the second language is often times restricted to the classroom. Although language teachers are keen to develop inside class room activities and practices that increase the suitability of students to acquire a second language (Cook & Singleton, 2014), many would agree that class time is too limited to enhance students’ oral fluency skills. Consequently, creating opportunities outside the classroom for students to speak English is an effective strategy in compensating for students’ limited use of the L2. In an argument by Ortega (2012) external classroom activities have equal significance in enabling students learn English as a second language. The author further asserts that the activities provide a non-educational environment from which a student may feel free and comfortable to acquire new language skills. This study investigates the significance of outside classroom activities in promoting students’ oral proficiency. In addition, it reports on students’ perceptions of such activities. 15 participants from the American University of Kuwait took part in this study. Open-ended interviews were done to find out what the participants thought of these activities, and what they gained from them. Interview results show that students found outside classroom activities very effective in improving not only their oral fluency skills, but their confidence and critical thinking skills as well. The implications of this research study are for language practitioners and language programs in the EFL context to be aware of the benefits of incorporating outside classroom activities in language teaching.

Keywords: language teaching, oral fluency, outside classroom activities

Procedia PDF Downloads 439

Authors: Natalia Sáez, Dina Shulfman

Abstract:

There is an important research gap regarding accessible pedagogical techniques for teaching foreign languages to adults with visual impairments. English as a foreign language (EFL), in particular, is needed in many countries to expand occupational opportunities and improve living standards. Within EFL research, teaching and learning prepositions have only recently gained momentum, considering that they constitute one of the most difficult structures to learn in a foreign language and are fundamental for communicating about spatial relations in the world, both on the physical and imaginary levels. Learning to use prepositions would not only facilitate communication when referring to the surrounding tangible environment but also when conveying ideas about abstract topics (e.g., justice, love, society), for which students’ sociocultural knowledge about space could play an important role. By potentiating visually impaired students’ ability to construe mental spatial imagery, this study made efforts to explore pedagogical techniques that cater to their strengths, helping them create new worlds by welcoming and expanding their sociocultural funds of knowledge as they learn to use English prepositions. Fifteen visually impaired adults living in Chile participated in the study. Their first language was Spanish, and they were learning English at the intermediate level of proficiency in an EFL workshop at La Biblioteca Central para Ciegos (The Central Library for the Blind). Within this workshop, a series of activities and interviews were designed and implemented with the intention of uncovering students’ spatial funds of knowledge when learning literal/physical uses of three English prepositions, namely “in,” “at,” and “on”. The activities and interviews also explored whether students used their original spatial funds of knowledge when learning metaphorical uses of these prepositions and if their use of spatial imagery changed throughout the learning activities. Over the course of approximately half a year, it soon became clear that the students construed mental images of space when learning both literal/physical and metaphorical uses of these prepositions. This research could inform a new approach to inclusive language education using pedagogical methods that are relevant and accessible to students with visual impairments.

Keywords: EFL, funds of knowledge, prepositions, spatial cognition, visually impaired students

Procedia PDF Downloads 64

Authors: Hiromi Kawasaki, Satoko Yamasaki, Mika Iwasa, Tomoko Iki, Akiko Takaki

Abstract:

In basic nursing, the conditions necessary for maintaining human health -temperature, humidity, illumination, distance from others, noise, moisture, meals, and excretion- were explained. Nursing students often think of these conditions in the context of a hospital room. In order to make students think of these conditions in terms of an environment necessary for maintaining health and preventing illness for residents, in the third year of community health nursing, students learned how to assess and improve the environment -particularly via the case of shelters in the event of a disaster. The importance of environmental management has increased in 2020 as a preventive measure against COVID-19 infection. We verified the effect of the lessons, which was decided to be conducted through distance learning. Sixty third-year nursing college students consented to participate in this study. Environmental standard knowledge for conducting environmental assessment was examined before and after class, and the percentage of correct answers was compared. The χ² test was used for the test, with a 5% significance level employed. Measures were evaluated via a report submitted by the students after class. Student descriptions were analyzed both qualitatively and descriptively with respect to expected health problems and suggestions for improvement. Students have already learned about the environment in terms of basic nursing in their second year. The correct answers for external environmental values concerning interpersonal distance, illumination, noise, and room temperature (p < 0.001) increased significantly after taking the class. Humidity was registered 83.3% before class and 93.3% after class (p = 0.077). Regarding the body, the percentage of students who answered correctly was 70% or more, both before and after the class. The students’ reports included overcrowding, high humidity/high temperature, and the number of toilets as health hazards. Health disorders to be prevented were heat stroke, infectious diseases, and economy class syndrome; improvement methods were recommended for hyperventilation, stretching, hydration, and waiting at home. After the public health nursing class, the students were able to not only propose environmental management of a hospital room but also had an understanding of the environment in terms of the lives of individuals, environmental assessment, and solutions to health problems. The response rate for basic items learned in the second year was already high before and after class, and interpersonal distance and ventilation were described by students. Students were able to use what they learned in basic nursing about the standards of the human mind and body. In the external environment, the memory of specific numerical values was ambiguous. The environment of the hospital room is controlled, and interest in numerical values may decrease. Nursing staff needs to maintain and improve human health as well as hospital rooms. With COVID-19, it was thought that students would continue to not only consider this point in reference to hospital rooms but also in regard to places where people gather. Even in distance learning, students were able to learn the important issues and lessons.

Keywords: environmental assessment, evacuation center, nursing education, nursing students

Procedia PDF Downloads 84

Authors: Ercan Eker, Muhammer Karaman, Akif Aslan, Hakan Tanrikuluoglu

Abstract:

Deficiency of institutional memory and knowledge management can result in information security breaches, loss of prestige and trustworthiness and the worst the loss of know-how and institutional knowledge. Traditional learning management within organizations is generally handled by personal efforts. That kind of struggle mostly depends on personal desire, motivation and institutional belonging. Even if an organization has highly motivated employees at a certain time, the institutional knowledge and memory life cycle will generally remain limited to these employees’ spending time in this organization. Having a learning management system in an organization can sustain the institutional memory, knowledge and know-how in the organization. Learning management systems are much more needed especially in public organizations where the job rotation is frequently seen and managers are appointed periodically. However, a learning management system should not be seen as an organizations’ website. It is a more comprehensive, interactive and user-friendly knowledge management tool for organizations. In this study, the importance of using learning management systems in the process of emerging tacit knowledge is underlined.

Keywords: knowledge management, learning management systems, tacit knowledge, institutional memory

Procedia PDF Downloads 361

Authors: Salwa Aftab, Sehrish Riaz

Abstract:

The objective of this study was to check the impact of grade sensitivity on learning motivation and academic performance of students and to remove the degree of difference that exists among students regarding the cause of their learning motivation and also to gain knowledge about this matter since it has not been adequately researched. Data collection was primarily done through the academic sector of Pakistan and was depended upon the responses given by students solely. A sample size of 208 university students was selected. Both paper and online surveys were used to collect data from respondents. The results of the study revealed that grade sensitivity has a positive relationship with the learning motivation of students and their academic performance. These findings were carried out through systematic correlation and regression analysis.

Keywords: academic performance, correlation, grade sensitivity, learning motivation, regression

Procedia PDF Downloads 380

Authors: Rafia Rafique, Arifa Khadim

Abstract:

This research investigates the moderating role of job satisfaction between organizational learning and work performance among nurses. Correlation research design was used. Non-probability purposive sampling technique was utilized to recruit a sample of 110 nurses from public hospitals situated in the city of Lahore. The construct of organizational learning was measured using subscale of Integrated Scale for Measuring Organizational Learning. Job satisfaction was measured with the help of Job Satisfaction Survey. Performance of employees (task performance, contextual performance and counterproductive work behavior) was assessed by Individual Work Performance Questionnaire. Job satisfaction negatively moderates the relationship between organizational learning and counterproductive work behavior. Education has a significant positive relationship with organizational learning. Age, current hospital experience, marital satisfaction and salary of the nurses have positive relationship while number of children has significant negative relationship with counterproductive work behavior. These outcomes can be insightful in understanding the dynamics involved in work performance. Based on the result of this study relevant solutions can be proposed to improve the work performance of nurses.

Keywords: counterproductive work behavior, nurses, organizational learning, work performance

Procedia PDF Downloads 420

Authors: Jatuphum Ketchatturat

Abstract:

Value-added assessment has been used for developing the model of monitoring and evaluation of student's learning achievement. The steps of model development consist of 1) study and analyisis of the school and the district report system of student achievement and progress, 2) collecting the data of student achievement to develop the value added indicator, 3) developing the system of value-added assessment by participatory action research approach, 4) putting the system of value-added assessment into the educational district of secondary school, 5) determining the quality of the developed system of value-added assessment. The components of the developed model consist of 1) the database of value-added assessment of student's learning achievement, 2) the process of monitoring and evaluation the student's learning achievement, and 3) the reporting system of value-added assessment of student's learning achievement.

Keywords: learning achievement, monitoring and evaluation, value-added assessment

Procedia PDF Downloads 399

Authors: Vishnu Pratap Singh Kirar, Madhuri Saxena

Abstract:

Advancement in sequence data generation technologies is churning out voluminous omics data and posing a massive challenge to annotate the biological functional features. With so much data available, the use of machine learning methods and tools to make novel inferences has become obvious. Machine learning methods have been successfully applied to a lot of disciplines, including computational biology and bioinformatics. Researchers in computational biology are interested to develop novel machine learning frameworks to classify the huge amounts of biological data. In this proposal, it plan to employ novel machine learning approaches to aid the understanding of how apparently innocuous mutations (in intergenic DNA and at synonymous sites) cause diseases. We are also interested in discovering novel functional sites in the genome and mutations in which can affect a phenotype of interest.

Keywords: genome wide association studies (GWAS), next generation sequencing (NGS), deep learning, omics

Procedia PDF Downloads 79

Authors: Sanghoon Shim, Jaehwan Jung, Sung-Ah Kim

Abstract:

As the digital technology develops, studies on the TUI (Tangible User Interface) that links the physical environment utilizing the human senses with the virtual environment through the computer are actively being conducted. In addition, there has been a tremendous advance in computer design making through the use of computer-aided design techniques, which enable optimized decision-making through comparison with machine learning and parallel comparison of alternatives. However, a complex design that can respond to user requirements or performance can emerge through the intuition of the designer, but it is difficult to actualize the emerged design by the designer's ability alone. Ancillary tools such as Gaudí's Sandbag can be an instrument to reinforce and evolve emerged ideas from designers. With the advent of many commercial tools that support 3D objects, designers' intentions are easily reflected in their designs, but the degree of their reflection reflects their intentions according to the proficiency of design tools. This study embodies the environment in which the form can be implemented by the fingers of the most basic designer in the initial design phase of the complex type building design. Leapmotion is used as a sensor to recognize the hand motions of the designer, and it is converted into digital information to realize an environment that can be linked in real time in virtual reality (VR). In addition, the implemented design can be linked with Rhino™, a 3D authoring tool, and its plug-in Grasshopper™ in real time. As a result, it is possible to design sensibly using TUI, and it can serve as a tool for assisting designer intuition.

Keywords: design environment, digital modeling, hand gesture, TUI, virtual reality

Procedia PDF Downloads 356

Authors: Doddy T. P. Enggarsyah, Soebowo Musa

Abstract:

Covid-19 pandemic has changed business environments and has spread economic contagion rapidly, as the stringent lockdowns and social distancing, which were initially intended to cut off the spread, have instead cut off the flow of economies. With no existing experience or playbook to deal with such a crisis, the prolonged pandemic can lead to bankruptcies, despite the fact that there are cases of companies that are not only able to survive but also to increase sales and create more jobs amid the economic crisis. This quantitative research study clarifies conflicting findings on organizational inertia whether it is a better strategy to implement during a disruptive environment. 316 respondents who worked in diverse firms operating in various industry types in Indonesia have completed the survey with a response rate of 63.2%. Further, this study clarifies the roles and relationships between organizational inertia, organizational creativity, organizational agility, and organizational resilience that potentially have determinants factors on firm performance in a disruptive environment. The findings of the study confirm that the organizational inertia of the firm will set up strong protection on the organization's fundamental orientation, which eventually will confine organizations to build adequate creative and adaptability responses—such fundamental orientation built from path dependency along with past success and prolonged firm performance. Organizational inertia acts like a control mechanism to ensure the adequacy of the given responses. The term adequate is important, as being overly creative during a disruptive environment may have a contradictory result since it can burden the firm performance. During a disruptive environment, organizations will limit creativity by focusing more on creativity that supports the resilience and new technology adoption will be limited since the cost of learning and implementation are perceived as greater than the potential gains. The optimal path towards firm performance is gained through organizational resilience, as in a disruptive environment, the survival of the organization takes precedence over firm performance.

Keywords: disruptive environment, organizational agility, organizational creativity, organizational inertia, organizational resilience

Procedia PDF Downloads 100

Authors: Syamimi Shamsuddin, Hanafiah Yussof, Fazah Akhtar Hanapiah, Salina Mohamed, Nur Farah Farhan Jamil, Farhana Wan Yunus

Abstract:

Robot-based intervention for children with autism is an evolving research niche in human-robot interaction (HRI). Recent studies in this area mostly covered the role of robots in the clinical and experimental setting. Our previous work had shown that interaction with a robot pose no adverse effects on the children. Also, the presence of the robot, together with specific modules of interaction was associated with less autistic behavior. Extending this impact on school-going children, interactions that are in-tune with special education lessons are needed. This methodological paper focuses on how a robot can be incorporated in a current learning environment for autistic children. Six interaction scenarios had been designed based on the existing syllabus to teach communication skills, using the Applied Behavior Analysis (ABA) technique as the framework. Development of the robotic experience in class also covers the required set-up involving participation from teachers. The actual research conduct involving autistic children, teachers and robot shall take place in the next phase.

Keywords: autism spectrum disorder, ASD, humanoid robot, communication skills, robot-assisted learning

Procedia PDF Downloads 349

Authors: Samer Abu Ghazaleh, Jawdat Gousous

Abstract:

E-learning in general started in Jordan around ten years ago in universities and at different departments and colleges. This paper will investigate the possibility to apply e-learning in architecture department at University of Jordan. As known architecture departments in general depend greatly in its syllabus upon design courses and studios, which consists nearly one third of its total credit hours. A survey has been conducted for architectural students at the University of Jordan and several conclusions have been reached irrespective of age, gender and nationality of the students, where the main problem was the way of the communication between the tutor and the student.

Keywords: cellular telephone, design courses, e-learning, internet

Procedia PDF Downloads 454

Authors: N. Didiş Körhasan, D. Kaltakçı Gürel

Abstract:

Many students have difficulty in learning physics from elementary to university level. In addition, students' expectancy, attitude, and motivation may be influenced negatively with their experience (failure) and prejudice about physics learning. For this reason, physics educators, who are also physics teachers, search for the best ways to make students' learning of physics easier by considering cognitive, affective, and psychomotor issues in learning. This research critically discusses the history of physics education, fundamental pedagogical approaches, and models to teach physics, and transformation of physics education with recent research.

Keywords: pedagogy, physics, physics education, science education

Procedia PDF Downloads 247

Authors: Sagheer Ahmad

Abstract:

Teaching is a sacred profession whereby students are developed in their mental abilities to cope with the challenges of the remote world. Thinkers have developed plenty of interesting ways to make the learning process quick and absorbing for the students. However, third world countries are still lacking these remote facilities in the institutions, and therefore, teaching is totally dependent upon the skills of the teachers. Skillful teachers use self-devised and stimulating ideas to grab the attention of their students. Most of the time their ideas are based on local grounds with which the students are already familiar. This self-explanatory characteristic is the base of several local ideologies to disseminate scientific knowledge to new generations. Biology is such a subject which largely bases upon hypotheses, and teaching it in an interesting way is needful to create a friendly relationship between teacher and student, and to make a fantastic learning environment. Taxonomic classification if presented as it is, may not be attractive for the secondary school students who just start learning about biology at elementary levels. Presenting this hierarchy by exemplifying Kingdom, Phylum, Class, Order, family, genus and Species as comparatives of our division into continents, countries, cities, towns, villages, homes and finally individuals could be an attention-grabbing approach to make this concept get into bones of students. Similarly, many other interesting approaches have also been adopted to teach students in a fascinating way so that learning science subjects may not be boring for them. Discussing these appealing ways of teaching students can be a valuable stimulus to refine teaching methodologies about science, thereby promoting the concept of friendly learning.

Keywords: biology, innovative approaches, taxonomic classification, teaching

Procedia PDF Downloads 235

Authors: B. Bricklin Zeff

Abstract:

This research explores the development and application of a specialized chatbot tailored for a nursing English course, with a primary objective of augmenting student engagement through situational content and responsiveness to key expressions and vocabulary. Introducing the chatbot, elucidating its purpose, and outlining its functionality are crucial initial steps in the research study, as they provide a comprehensive foundation for understanding the design and objectives of the specialized chatbot developed for the nursing English course. These elements establish the context for subsequent evaluations and analyses, enabling a nuanced exploration of the chatbot's impact on student engagement and language learning within the nursing education domain. The subsequent exploration of the intricate language model development process underscores the fusion of scientific methodologies and artistic considerations in this application of artificial intelligence (AI). Tailored for educators and curriculum developers in nursing, practical principles extending beyond AI and education are considered. Some insights into leveraging technology for enhanced language learning in specialized fields are addressed, with potential applications of similar chatbots in other professional English courses. The overarching vision is to illuminate how AI can transform language learning, rendering it more interactive and contextually relevant. The presented chatbot is a tangible example, equipping educators with a practical tool to enhance their teaching practices. Methodologies employed in this research encompass surveys and discussions to gather feedback on the chatbot's usability, effectiveness, and potential improvements. The chatbot system was integrated into a nursing English course, facilitating the collection of valuable feedback from participants. Significant findings from the study underscore the chatbot's effectiveness in encouraging more verbal practice of target expressions and vocabulary necessary for performance in role-play assessment strategies. This outcome emphasizes the practical implications of integrating AI into language education in specialized fields. This research holds significance for educators and curriculum developers in the nursing field, offering insights into integrating technology for enhanced English language learning. The study's major findings contribute valuable perspectives on the practical impact of the chatbot on student interaction and verbal practice. Ultimately, the research sheds light on the transformative potential of AI in making language learning more interactive and contextually relevant, particularly within specialized domains like nursing.

Keywords: chatbot, nursing, pragmatics, role-play, AI

Procedia PDF Downloads 41

Authors: Dian Hartiningsih, Miranda Diponegoro, Evita Eddie Singgih

Abstract:

In facing the 21st century, children need to be prepared in reaching their optimum development level which encompasses all aspect of growth and to achieve the learning goals which include not only knowledge and skill, but also disposition and feeling. Teachers as the forefront of education need to be equipped with the understanding and skill of a learning method which can prepare the children to face this 21st century challenge. Project approach is an approach which utilizes active learning which is beneficial for the children. Subject to this research are kindergarten teachers at Dwi Matra Kindergarten and Kirana Preschool. This research is a quantitative research using before and after study design. The result suggest that through preliminary training program on learning with project approach, the kindergarten teachers ability to explain project approach including understanding, benefit and stages of project approach have increased significantly, the teachers ability to design learning with project approach have also improved significantly. The result of learning design that the teachers had made shows a remarkable result for the first stage of the project approach; however the second and third design result was not as optimal. Challenges faced in the research will be elaborated further in the research discussion.

Keywords: project approach, teacher training, learning method, kindergarten

Procedia PDF Downloads 319

Authors: Subramaniam Chandran, A. Geetha

Abstract:

This paper addresses three issues: how to prepare instructional design for imparting English language skill from inter-disciplinary self-learning material; how the disadvantaged students are benefited from such kind of language skill imparted through m-learning; and how do the m-learners perform better than the other learners. This paper examines these issues through an experimental study conducted among the distance learners enrolled in preparatory program for bachelor’s degree. This program is designed for the disadvantage learners especially for the school drop-outs to qualify to pursue graduate program through distant education. It also explains how mobile learning helps them to enhance their capacity in learning despite their rural background and other disadvantages. In India nearly half of the students enrolled in schools do not complete their study. The pursuance of higher education is very low when compared with developed countries. This study finds a significant increase in their learning capacity and mobile learning seems to be a viable alternative where conventional system could not reach the disadvantaged learners. Improving the English language skill is one of the reasons for such kind of performance. Exercises framed from the relevant self-learning material for enhancing English language skill not only improves language skill but also widens the subject-knowledge. This paper explains these issues out of the study conducted among the disadvantaged learners.

Keywords: English language skill, disadvantaged learners, distance education, m-learning

Procedia PDF Downloads 642

Authors: Joshefina Bengoechea Fernandez, Alex Bell

Abstract:

In its 2021 guidance for policy makers, the UNESCO has proposed 4 areas where AI can be applied in educational settings: These are: 1) Education management and delivery; 2) Learning and assessment; 3) Empowering teachers and facilitating teaching, and 4) Providing lifelong learning possibilities (UNESCO, 2021). Like with wblockchain technologies, AI will automate the management of educational institutions. These include, but are not limited to admissions, timetables, attendance, and homework monitoring. Furthermore, AI will be used to select relevant learning content across learning platforms for each student, based on his or her personalized needs. A problem educators face is the “one-size-fits-all” approach that does not work with a diverse student population. The purpose of this paper is to illustrate if the implementation of Technology is the solution to the Problems faced in Higher Education. The paper builds upon a constructivist approach, combining a literature review and research on key publications and academic reports.

Keywords: artificial intelligence, learning platforms, students personalised needs, life- long learning, privacy, ethics

Procedia PDF Downloads 84

Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi

Abstract:

In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.

Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh

Procedia PDF Downloads 123

Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

Procedia PDF Downloads 405