Search results for: support learning
11562 Collaborative Reflexive/Reflective Teaching and Action Research in TESL
Authors: O. F. Elkommos
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Teaching English as a Second Language (TESL) has become a very rich area of research. Practitioners or teachers of English as a foreign or a second language are now promoting both collaborative learning and collaborative teaching. Students learning a language collaboratively and cooperatively are learning in a better environment of team work where they learn from each other. Further, teaching English collaboratively also creates an enriching environment that is also very enriching to students’ and teachers’ experiences of learning and teaching. Moreover, action research stems from actual teacher concerns and students’ needs. Reflection in turn, on the experience of the material taught and the delivery of material is becoming an integral part of the teaching and learning experience self- evaluation and self-development. In this case, the concern of the research field in the area of TESL will be the development of teaching delivery, material and quality of learning. In the present research, the TESL module taught to year two students in the Faculty of Arts and Humanities, British University in Egypt (BUE) will be evaluated reflexively by the students and teachers. The module was taught to students in two different specialisms. It was taught and delivered through collaborative teaching and was evaluated by both teachers and students as very successful and enjoyable. The reflections of both teachers and students as well as student results confirm that it was a success.Keywords: action research, addressing differentiation, collaborative teaching, reflective teaching and learning, reflexive learning, reflexive teaching, self-development, self-evaluation, TESL
Procedia PDF Downloads 11411561 A Comparative Study of Language Learning Strategy Use of Iranian Kurdish Bilingual and Persian Monolingual in EFL Context
Authors: Reza Khani, Ziba Hosseini
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This study was an attempt to investigate the difference between learners of Iranian Kurdish–Persian bilingual language and Persian monolinguals, regarding language strategy use (LLS). The participants of the study were 120 monolingual Persian and 120 bilingual Kurdish studying English as a foreign language (EFL). Data were collected using strategy inventory for language learning SILL. The results show bilingual reported higher use of language learning strategies in all categories of SILL except memory strategies.Keywords: language learning, memory, monolingual, comparative study
Procedia PDF Downloads 39311560 Perceptions of Islamic Education Teachers on the Implementation of 21st Century Learning Practices
Authors: Hafizul Rasdi
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This study was conducted to find out the perceptions of Islamic Education teachers on the implementation of 21st century learning practices in Kuching, Sarawak. This study uses the field method. Eight respondents were selected based on the interviews and focus group discussions conducted among teachers in four primary school in Kuching, Sarawak. This study is focused to find out the perceptions of Islamic Education teachers on the implementation of 21st century learning as well as the importance of 21st century learning in the subject of Islamic Education. Data were collected using library research, semi-structured interview transcripts and focus group discussions. Data analysis methods used was descriptive analysis. The findings of the study have shown that Islamic Education teachers in primary school in Kuching, Sarawak agreed on the implementation of 21st Century Learning Practices in Islamic Education subject. The finding also show that the application of 21st Century Learning Practices in the subject of Islamic Education can help improve students mastery of the subject.Keywords: perceptions, Islamic education, 21st century learning practices, teachers
Procedia PDF Downloads 6311559 Promoting Organizational Learning Facing the Complexity of Public Healthcare: How to Design a Voluntary, Learning-Oriented Benchmarking
Authors: Rachel M. Lørum, Henrik Eriksson, Frida Smith
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Purpose: In recent years, the use of benchmarks for the improvement of healthcare has become increasingly common. There has been an increasing interest in why improvement initiatives so often fail to eliminate the problems they aspire to solve. Benchmarking comes with its fair share of challenges and problems, such as capturing the dynamics and complexities of the care environments, among others. In this study, we demonstrate how learning-oriented, voluntary benchmarks in the complex environment of public healthcare could be designed. Findings: Our four most important findings were the following: first, important organizational learning (OL) regarding the complexity of the service and implications on how to design a benchmark for learning and improvement occurred during the process. Second, participation by a wide range of professionals and stakeholders was crucial for capturing the complexity of people and organizations and increasing the quality of the template. Third, the continuous dialogue between all organizations involved was an important tool for ongoing organizational learning throughout the process. The last important finding was the impact of the facilitator’s role through supporting progress, coordination, and dialogue. Design: We chose participatory design as the research design. Data were derived from written materials such as e-mails, protocols, observational notes, and reflection notes collected during a period of 1.5 years. Originality: Our main contributions are the identification of important strategies, initiatives, and actors to involve when designing voluntary benchmarks for learning and improvement.Keywords: organizational learning, quality improvement, learning-oriented benchmark, healthcare, patient safety
Procedia PDF Downloads 10211558 Educational Infrastructure a Barrier for Teaching and Learning Architecture
Authors: Alejandra Torres-Landa López
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Introduction: Can architecture students be creative in spaces conformed by an educational infrastructure build with paradigms of the past?, this question and others related are answered in this paper as it presents the PhD research: An anthropic conflict in Mexican Higher Education Institutes, problems and challenges of the educational infrastructure in teaching and learning History of Architecture. This research was finished in 2013 and is one of the first studies conducted nationwide in Mexico that analysis the educational infrastructure impact in learning architecture; its objective was to identify which elements of the educational infrastructure of Mexican Higher Education Institutes where architects are formed, hinder or contribute to the teaching and learning of History of Architecture; how and why it happens. The methodology: A mixed methodology was used combining quantitative and qualitative analysis. Different resources and strategies for data collection were used, such as questionnaires for students and teachers, interviews to architecture research experts, direct observations in Architecture classes, among others; the data collected was analyses using SPSS and MAXQDA. The veracity of the quantitative data was supported by the Cronbach’s Alpha Coefficient, obtaining a 0.86, figure that gives the data enough support. All the above enabled to certify the anthropic conflict in which Mexican Universities are. Major findings of the study: Although some of findings were probably not unknown, they haven’t been systematized and analyzed with the depth to which it’s done in this research. So, it can be said, that the educational infrastructure of most of the Higher Education Institutes studied, is a barrier to the educational process, some of the reasons are: the little morphological variation of space, the inadequate control of lighting, noise, temperature, equipment and furniture, the poor or none accessibility for disable people; as well as the absence, obsolescence and / or insufficiency of information technologies are some of the issues that generate an anthropic conflict understanding it as the trouble that teachers and students have to relate between them, in order to achieve significant learning). It is clear that most of the educational infrastructure of Mexican Higher Education Institutes is anchored to paradigms of the past; it seems that they respond to the previous era of industrialization. The results confirm that the educational infrastructure of Mexican Higher Education Institutes where architects are formed, is perceived as a "closed container" of people and data; infrastructure that becomes a barrier to teaching and learning process. Conclusion: The research results show it's time to change the paradigm in which we conceive the educational infrastructure, it’s time to stop seen it just only as classrooms, workshops, laboratories and libraries, as it must be seen from a constructive, urban, architectural and human point of view, taking into account their different dimensions: physical, technological, documental, social, among others; so the educational infrastructure can become a set of elements that organize and create spaces where ideas and thoughts can be shared; to be a social catalyst where people can interact between each other and with the space itself.Keywords: educational infrastructure, impact of space in learning architecture outcomes, learning environments, teaching architecture, learning architecture
Procedia PDF Downloads 40211557 Decision Support System for Optimal Placement of Wind Turbines in Electric Distribution Grid
Authors: Ahmed Ouammi
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This paper presents an integrated decision framework to support decision makers in the selection and optimal allocation of wind power plants in the electric grid. The developed approach intends to maximize the benefice related to the project investment during the planning period. The proposed decision model considers the main cost components, meteorological data, environmental impacts, operation and regulation constraints, and territorial information. The decision framework is expressed as a stochastic constrained optimization problem with the aim to identify the suitable locations and related optimal wind turbine technology considering the operational constraints and maximizing the benefice. The developed decision support system is applied to a case study to demonstrate and validate its performance.Keywords: decision support systems, electric power grid, optimization, wind energy
Procedia PDF Downloads 14311556 Recommendations as a Key Aspect for Online Learning Personalization: Perceptions of Teachers and Students
Authors: N. Ipiña, R. Basagoiti, O. Jimenez, I. Arriaran
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Higher education students are increasingly enrolling in online courses, they are, at the same time, generating data about their learning process in the courses. Data collected in those technology enhanced learning spaces can be used to identify patterns and therefore, offer recommendations/personalized courses to future online students. Moreover, recommendations are considered key aspects for personalization in online learning. Taking into account the above mentioned context, the aim of this paper is to explore the perception of higher education students and teachers towards receiving recommendations in online courses. The study was carried out with 322 students and 10 teachers from two different faculties (Engineering and Education) from Mondragon University. Online questionnaires and face to face interviews were used to gather data from the participants. Results from the questionnaires show that most of the students would like to receive recommendations in their online courses as a guide in their learning process. Findings from the interviews also show that teachers see recommendations useful for their students’ learning process. However, teachers believe that specific pedagogical training is required. Conclusions can also be drawn as regards the importance of personalization in technology enhanced learning. These findings have significant implications for those who train online teachers due to the fact that pedagogy should be the driven force and further training on the topic could be required. Therefore, further research is needed to better understand the impact of recommendations on online students’ learning process and draw some conclusion on pedagogical concerns.Keywords: higher education, perceptions, recommendations, online courses
Procedia PDF Downloads 25411555 Design of Mobile Teaching for Students Collaborative Learning in Distance Higher Education
Authors: Lisbeth Amhag
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The aim of the study is to describe and analyze the design of mobile teaching for students collaborative learning in distance higher education with a focus on mobile technologies as online webinars (web-based seminars or conferencing) by using laptops, smart phones, or tablets. These multimedia tools can provide face-to-face interactions, recorded flipped classroom videos and parallel chat communications. The data collection consists of interviews with 22 students and observations of online face-to-face webinars, as well two surveys. Theoretically, the study joins the research tradition of Computer Supported Collaborative learning, CSCL, as well as Computer Self-Efficacy, CSE concerned with individuals’ media and information literacy. Important conclusions from the study demonstrated mobile interactions increased student centered learning. As the students were appreciating the working methods, they became more engaged and motivated. The mobile technology using among student also contributes to increased flexibility between space and place, as well as media and information literacy.Keywords: computer self-efficacy, computer supported collaborative learning, distance and open learning, educational design and technologies, media and information literacy, mobile learning
Procedia PDF Downloads 35311554 A Comparative Study of Deep Learning Methods for COVID-19 Detection
Authors: Aishrith Rao
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COVID 19 is a pandemic which has resulted in thousands of deaths around the world and a huge impact on the global economy. Testing is a huge issue as the test kits have limited availability and are expensive to manufacture. Using deep learning methods on radiology images in the detection of the coronavirus as these images contain information about the spread of the virus in the lungs is extremely economical and time-saving as it can be used in areas with a lack of testing facilities. This paper focuses on binary classification and multi-class classification of COVID 19 and other diseases such as pneumonia, tuberculosis, etc. Different deep learning methods such as VGG-19, COVID-Net, ResNET+ SVM, Deep CNN, DarkCovidnet, etc., have been used, and their accuracy has been compared using the Chest X-Ray dataset.Keywords: deep learning, computer vision, radiology, COVID-19, ResNet, VGG-19, deep neural networks
Procedia PDF Downloads 15011553 Application of ICT in the Teaching and Learning of English Language in Nigerian Secondary Schools
Authors: Richard Ayobayowa Foyewa
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This work examined the application of ICT in the teaching and learning of English language in Nigerian secondary schools. The definition of ICT was given briefly before areas in which the ICT could be applied in teaching and learning of English language were observed. Teachers’ attitudes towards the use of the computer and Internet facilities were also observed. The conclusion drawn was that ICT is very relevant in the teaching and learning of English language in Nigerian secondary schools. It was therefore recommended that teachers who are not computer literate should go for the training without further delay; government should always employ English language teachers who are computer literates. Government should make fund available in schools for the training and re-training of English language teachers in various computer programmes and in making internet facilities available in secondary schools.Keywords: ICT, Nigerian secondary schools, teaching and learning of English
Procedia PDF Downloads 30711552 Data Augmentation for Automatic Graphical User Interface Generation Based on Generative Adversarial Network
Authors: Xulu Yao, Moi Hoon Yap, Yanlong Zhang
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As a branch of artificial neural network, deep learning is widely used in the field of image recognition, but the lack of its dataset leads to imperfect model learning. By analysing the data scale requirements of deep learning and aiming at the application in GUI generation, it is found that the collection of GUI dataset is a time-consuming and labor-consuming project, which is difficult to meet the needs of current deep learning network. To solve this problem, this paper proposes a semi-supervised deep learning model that relies on the original small-scale datasets to produce a large number of reliable data sets. By combining the cyclic neural network with the generated countermeasure network, the cyclic neural network can learn the sequence relationship and characteristics of data, make the generated countermeasure network generate reasonable data, and then expand the Rico dataset. Relying on the network structure, the characteristics of collected data can be well analysed, and a large number of reasonable data can be generated according to these characteristics. After data processing, a reliable dataset for model training can be formed, which alleviates the problem of dataset shortage in deep learning.Keywords: GUI, deep learning, GAN, data augmentation
Procedia PDF Downloads 17211551 Moving from Computer Assisted Learning Language to Mobile Assisted Learning Language Edutainment: A Trend for Teaching and Learning
Authors: Ahmad Almohana
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Technology has led to rapid changes in the world, and most importantly to education, particularly in the 21st century. Technology has enhanced teachers’ potential and has resulted in the provision of greater interaction and choices for learners. In addition, technology is helping to improve individuals’ learning experiences and building their capacity to read, listen, speak, search, analyse, memorise and encode languages, as well as bringing learners together and creating a sense of greater involvement. This paper has been organised in the following way: the first section provides a review of the literature related to the implementation of CALL (computer assisted learning language), and it explains CALL and its phases, as well as attempting to highlight and analyse Warschauer’s article. The second section is an attempt to describe the move from CALL to mobilised systems of edutainment, which challenge existing forms of teaching and learning. It also addresses the role of the teacher and the curriculum content, and how this is affected by the computerisation of learning that is taking place. Finally, an empirical study has been conducted to collect data from teachers in Saudi Arabia using quantitive and qualitative method tools. Connections are made between the area of study and the personal experience of the researcher carrying out the study with a methodological reflection on the challenges faced by the teachers of this same system. The major findings were that it is worth spelling out here that despite the circumstances in which students and lecturers are currently working, the participants revealed themselves to be highly intelligent and articulate individuals who were constrained from revealing this criticality and creativity by the system of learning and teaching operant in most schools.Keywords: CALL, computer assisted learning language, EFL, English as a foreign language, ELT, English language teaching, ETL, enhanced technology learning, MALL, mobile assisted learning language
Procedia PDF Downloads 16211550 Teachers’ and Students’ Reactions to a Guided Reading Program Designed by a Teachers’ Professional Learning Community
Authors: Yea-Mei Leou, Shiu-Hsung Huang, T. C. Shen, Chin-Ya Fang
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The purposes of this study were to explore how to establish a professional learning community for English teachers at a junior high school, and to explore how teachers and students think about the guided reading program. The participants were three experienced English teachers and their ESL seventh-grade students from three classes in a junior high school. Leveled picture books and worksheets were used in the program. Questionnaires and interviews were used for gathering information. The findings were as follows: First, most students enjoyed this guided reading program. Second, the teachers thought the guided reading program was helpful to students’ learning and the discussions in the professional learning community refreshed their ideas, but the preparation for the teaching was time-consuming. Suggestions based on the findings were provided.Keywords: ESL students, guided reading, leveled books, professional learning community
Procedia PDF Downloads 36811549 The Possible Double-Edged Sword Effects of Online Learning on Academic Performance: A Quantitative Study of Preclinical Medical Students
Authors: Atiwit Sinyoo, Sekh Thanprasertsuk, Sithiporn Agthong, Pasakorn Watanatada, Shaun Peter Qureshi, Saknan Bongsebandhu-Phubhakdi
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Background: Since the SARS-CoV-2 virus became extensively disseminated throughout the world, online learning has become one of the most hotly debated topics in educational reform. While some studies have already shown the advantage of online learning, there are still questions concerning how online learning affects students’ learning behavior and academic achievement when each student learns in a different way. Hence, we aimed to develop a guide for preclinical medical students to avoid drawbacks and get benefits from online learning that possibly a double-edged sword. Methods: We used a multiple-choice questionnaire to evaluate the learning behavior of second-year Thai medical students in the neuroscience course. All traditional face-to-face lecture classes were video-recorded and promptly posted to the online learning platform throughout this course. Students could pick and choose whatever classes they wanted to attend, and they may use online learning as often as they wished. Academic performance was evaluated as summative score, spot exam score and pre-post-test improvement. Results: More frequently students used online learning platform, the less they attended lecture classes (P = 0.035). High proactive online learners (High PO) who were irregular attendee (IrA) had significantly lower summative scores (P = 0.026), spot exam score (P = 0.012) and pre-post-test improvement (P = 0.036). In the meanwhile, conditional attendees (CoA) who only attended classes with attendance check had significantly higher summative score (P = 0.025) and spot exam score (P = 0.001) if they were in the High PO group. Conclusions: The benefit and drawbacks edges of using an online learning platform were demonstrated in our research. Based on this double-edged sword effect, we believe that online learning is a valuable learning strategy, but students must carefully plan their study schedule to gain the “benefit edge” meanwhile avoiding its “drawback edge”.Keywords: academic performance, assessment, attendance, online learning, preclinical medical students
Procedia PDF Downloads 15011548 Deliberate Learning and Practice: Enhancing Situated Learning Approach in Professional Communication Course
Authors: Susan Lee
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Situated learning principles are adopted in the design of the module, professional communication, in its iteration of tasks and assignments to create a learning environment that simulates workplace reality. The success of situated learning is met when students are able to transfer and apply their skills beyond the classroom, in their personal life, and workplace. The learning process should help students recognize the relevance and opportunities for application. In the module’s learning component on negotiation, cases are created based on scenarios inspired by industry practices. The cases simulate scenarios that students on the course may encounter when they enter the workforce when they take on executive roles in the real estate sector. Engaging in the cases has enhanced students’ learning experience as they apply interpersonal communication skills in negotiation contexts of executives. Through the process of case analysis, role-playing, and peer feedback, students are placed in an experiential learning space to think and act in a deliberate manner not only as students but as professionals they will graduate to be. The immersive skills practices enable students to continuously apply a range of verbal and non-verbal communication skills purposefully as they stage their negotiations. The theme in students' feedback resonates with their awareness of the authentic and workplace experiences offered through visceral role-playing. Students also note relevant opportunities for the future transfer of the skills acquired. This indicates that students recognize the possibility of encountering similar negotiation episodes in the real world and realize they possess the negotiation tools and communication skills to deliberately apply them when these opportunities arise outside the classroom.Keywords: deliberate practice, interpersonal communication skills, role-play, situated learning
Procedia PDF Downloads 20311547 Reducing Support Structures in Design for Additive Manufacturing: A Neural Networks Approach
Authors: Olivia Borgue, Massimo Panarotto, Ola Isaksson
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This article presents a neural networks-based strategy for reducing the need for support structures when designing for additive manufacturing (AM). Additive manufacturing is a relatively new and immature industrial technology, and the information to make confident decisions when designing for AM is limited. This lack of information impacts especially the early stages of engineering design, for instance, it is difficult to actively consider the support structures needed for manufacturing a part. This difficulty is related to the challenge of designing a product geometry accounting for customer requirements, manufacturing constraints and minimization of support structure. The approach presented in this article proposes an automatized geometry modification technique for reducing the use of the support structures while designing for AM. This strategy starts with a neural network-based strategy for shape recognition to achieve product classification, using an STL file of the product as input. Based on the classification, an automatic part geometry modification based on MATLAB© is implemented. At the end of the process, the strategy presents different geometry modification alternatives depending on the type of product to be designed. The geometry alternatives are then evaluated adopting a QFD-like decision support tool.Keywords: additive manufacturing, engineering design, geometry modification optimization, neural networks
Procedia PDF Downloads 24311546 The Role of Interpersonal and Institutional Trusts for the Public Support of Welfare State
Authors: Nazim Habibov, Alena Auchynnikava, Lida Fan
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The exploration of the relationship between social trust and the support of the welfare system in transitional countries has attracted growing interests in recent decades. This study estimates the effects of interpersonal and institutional trust on the support of the welfare system in 27 countries in Eastern Europe the former Soviet Union. We estimate the data sets from the Life-in-Transition Survey 2010 and 2016 with binomial regression models. The results indicate that both interpersonal and institutional trust have positive effects on the support for the welfare system in all the three areas under investigation: helping the needy, public healthcare and public education, both in the less developed countries of the former Soviet Union and in the more developed Eastern European countries. Furthermore, the positive effects of interpersonal and institutional trust on support for helping the needy, public healthcare and public education were found to grow over time. In conclusion, this study confirms that interpersonal and institutional trusts have positive effects for the public support of the welfare system in these transitional countries under investigation, regardless of their level of development.Keywords: central and eastern Europe, former Soviet union, international social welfare policy, comparative social welfare policy
Procedia PDF Downloads 12111545 The Impact of Artificial Intelligence on E-Learning
Authors: Sameil Hanna Samweil Botros
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The variation of social networking websites inside higher training has garnered enormous hobby in recent years, with numerous researchers thinking about it as a possible shift from the conventional lecture room-based learning paradigm. However, this boom in research and carried out research, but the adaption of SNS-based modules has not proliferated inside universities. This paper commences its contribution with the aid of studying the numerous fashions and theories proposed in the literature and amalgamates together various effective aspects for the inclusion of social technology within e-gaining knowledge. A three-phased framework is similarly proposed, which informs the important concerns for the hit edition of SNS in improving the student's mastering experience. This suggestion outlines the theoretical foundations as a way to be analyzed in sensible implementation across worldwide university campuses.Keywords: eLearning, institutionalization, teaching and learning, transformation vtuber, ray tracing, avatar agriculture, adaptive, e-learning, technology eLearning, higher education, social network sites, student learning
Procedia PDF Downloads 811544 Effects of Research-Based Blended Learning Model Using Adaptive Scaffolding to Enhance Graduate Students' Research Competency and Analytical Thinking Skills
Authors: Panita Wannapiroon, Prachyanun Nilsook
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This paper is a report on the findings of a Research and Development (R&D) aiming to develop the model of Research-Based Blended Learning Model Using Adaptive Scaffolding (RBBL-AS) to enhance graduate students’ research competency and analytical thinking skills, to study the result of using such model. The sample consisted of 10 experts in the fields during the model developing stage, while there were 23 graduate students of KMUTNB for the RBBL-AS model try out stage. The research procedures included 4 phases: 1) literature review, 2) model development, 3) model experiment, and 4) model revision and confirmation. The research results were divided into 3 parts according to the procedures as described in the following session. First, the data gathering from the literature review were reported as a draft model; followed by the research finding from the experts’ interviews indicated that the model should be included 8 components to enhance graduate students’ research competency and analytical thinking skills. The 8 components were 1) cloud learning environment, 2) Ubiquitous Cloud Learning Management System (UCLMS), 3) learning courseware, 4) learning resources, 5) adaptive Scaffolding, 6) communication and collaboration tolls, 7) learning assessment, and 8) research-based blended learning activity. Second, the research finding from the experimental stage found that there were statistically significant difference of the research competency and analytical thinking skills posttest scores over the pretest scores at the .05 level. The Graduate students agreed that learning with the RBBL-AS model was at a high level of satisfaction. Third, according to the finding from the experimental stage and the comments from the experts, the developed model was revised and proposed in the report for further implication and references.Keywords: research based learning, blended learning, adaptive scaffolding, research competency, analytical thinking skills
Procedia PDF Downloads 40811543 Life Prediction Method of Lithium-Ion Battery Based on Grey Support Vector Machines
Authors: Xiaogang Li, Jieqiong Miao
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As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines.For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square errorKeywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error
Procedia PDF Downloads 45211542 Interaction Tasks of CUE Model in Virtual Language Learning in Travel English for Taiwanese College EFL Learners
Authors: Kuei-Hao Li, Eden Huang
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Motivation suggests the willingness one person has towards taking action. Learners’ motivation has frequently been regarded as the most crucial factor in successful language acquisition. Without sufficient motivation, learners cannot achieve long-term learning goals despite remarkable abilities. Therefore, the study aims to investigate motivation of interaction tasks designed by the researchers for college EFL learners in Travel English class in virtual reality environment, integrating CUE model, Cognition, Usage and Expansion in the course. Thirty college learners were asked to join the virtual language learning website designed by the researchers. Data was collected via feedback questionnaire, interview, and learner interactions. The findings indicated that the course in the CUE model in language learning website of virtual reality environment was effective at motivating EFL learners and improving their oral communication and social interactions in the learning process. Some pedagogical implications are also provided in helping both language instructors and EFL learners in virtual reality environment.Keywords: motivation, virtual reality, virtual language learning, second language acquisition
Procedia PDF Downloads 38211541 Reflections of AB English Students on Their English Language Experiences
Authors: Roger G. Pagente Jr.
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This study seeks to investigate the language learning experiences of the thirty-nine AB-English majors who were selected through fish-bowl technique from the 157 students enrolled in the AB-English program. Findings taken from the diary, questionnaire and unstructured interview revealed that motivation, learners’ belief, self-monitoring, language anxiety, activities and strategies were the prevailing factors that influenced the learning of English of the participants.Keywords: diary, English language learning experiences, self-monitoring, language anxiety
Procedia PDF Downloads 59011540 A Collaborative Teaching and Learning Model between Academy and Industry for Multidisciplinary Engineering Education
Authors: Moon-Soo Kim
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In order to cope with the increasing demand for multidisciplinary learning between academy and industry, a collaborative teaching and learning model and related operational tools enabling applications to engineering education are essential. This study proposes a web-based collaborative framework for interactive teaching and learning between academy and industry as an initial step for the development of a web- and mobile-based integrated system for both engineering students and industrial practitioners. The proposed web-based collaborative teaching and learning framework defines several entities such as learner, solver and supporter or sponsor for industrial problems, and also has a systematic architecture to build information system including diverse functions enabling effective interaction among the defined entities regardless of time and places. Furthermore, the framework, which includes knowledge and information self-reinforcing mechanism, focuses on the previous problem-solving records as well as subsequent learners’ creative reusing in solving process of new problems.Keywords: collaborative teaching and learning model, academy and industry, web-based collaborative framework, self-reinforcing mechanism
Procedia PDF Downloads 31711539 Charting the Course: Using group Charters to Enhance Engagement and Learning Outcomes
Authors: Angela Knox
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Student diversity in postgraduate classes puts major challengesoneducatorsseekingtoencouragestudentengagementand desired learning outcomes. This paper outlines the impact of a set of teaching initiatives aimed at addressing challenges associated with teaching and learning in an environment characterized by diversity in the student cohort. The study examines postgraduate students completing the core capstone unit within a specialized business degree. Although relatively small, the student cohort is highly diverse in terms of cultural backgrounds represented, prior learning and/or qualifications,aswellasdurationandtypeofworkexperiencerelevant to the degree being completed. The wide range of cultures, existing knowledge, and experience create enormous challenges with respect to students’ learning needs and outcomes. Subsequently, a suite of teaching innovations has been adopted to enhance curriculum content/delivery and the design of assessments. This paperexplores the impact of formalized group charters on students’ learning outcomes. Data from surveys and focus groups are used to assess the effectiveness of these practices. The results highlight the effectiveness of formalizedgroup charters in addressing diverse student needs and enhancing student engagement and learning outcomes. Thesefindings suggest that such practices would benefit students’ learning in environments marked by diversity in the student cohort. Specific recommendationsareofferedforothereducatorsworkingwithdiverse classes.Keywords: assessment design, curriculum content, curriculum delivery, group charter, student diversity
Procedia PDF Downloads 12911538 Using Machine Learning to Monitor the Condition of the Cutting Edge during Milling Hardened Steel
Authors: Pawel Twardowski, Maciej Tabaszewski, Jakub Czyżycki
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The main goal of the work was to use machine learning to predict cutting-edge wear. The research was carried out while milling hardened steel with sintered carbide cutters at various cutting speeds. During the tests, cutting-edge wear was measured, and vibration acceleration signals were also measured. Appropriate measures were determined from the vibration signals and served as input data in the machine-learning process. Two approaches were used in this work. The first one involved a two-state classification of the cutting edge - suitable and unfit for further work. In the second approach, prediction of the cutting-edge state based on vibration signals was used. The obtained research results show that the appropriate use of machine learning algorithms gives excellent results related to monitoring cutting edge during the process.Keywords: milling of hardened steel, tool wear, vibrations, machine learning
Procedia PDF Downloads 4011537 Predicting Provider Service Time in Outpatient Clinics Using Artificial Intelligence-Based Models
Authors: Haya Salah, Srinivas Sharan
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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time
Procedia PDF Downloads 11511536 Efl Learner’s Perceptions of Online Learning and Motivation
Authors: Sonia Achour
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Owing to the outbreak of the Corona pandemic, the shift to online learning took place abruptly. Neither practitioners nor learners were prepared for this sudden move. Higher education providers were compelled to implement online courses on a very short notice. Sultan Qaboos University is one among these. The question of motivation attracted a great number of educators. A case study was carried out so as to shed some lights on students' perceptions towards virtual learning and how it influenced their motivation to learning. The data was collected by means of semi-structured interviews of a focused group of 16 students along with classroom observation over a 12 week period. Both interviews and class observation revealed that there was a general negative feeling about the online teaching platform and its impact on the learners' motivation. Several factors were identified, namely the absence of interaction, social isolation, inconsistency of instructional knowledge, unfamiliarity with the new learning environment, IT illiteracy, and teacher development. The researcher aims at demonstrating the effect of virtual classrooms on students' motivation to acquire L2. The findings may be used to inform future decisions about courses, curriculum design. And teacher developmentKeywords: online learning, motivation, EFL context, virtual setting
Procedia PDF Downloads 8311535 Active Development of Tacit Knowledge: Knowledge Management, High Impact Practices and Experiential Learning
Authors: John Zanetich
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Due to their positive associations with student learning and retention, certain undergraduate opportunities are designated ‘high-impact.’ High-Impact Practices (HIPs) such as, learning communities, community based projects, research, internships, study abroad and culminating senior experience, share several traits bin common: they demand considerable time and effort, learning occurs outside of the classroom, and they require meaningful interactions between faculty and students, they encourage collaboration with diverse others, and they provide frequent and substantive feedback. As a result of experiential learning in these practices, participation in these practices can be life changing. High impact learning helps individuals locate tacit knowledge, and build mental models that support the accumulation of knowledge. On-going learning from experience and knowledge conversion provides the individual with a way to implicitly organize knowledge and share knowledge over a lifetime. Knowledge conversion is a knowledge management component which focuses on the explication of the tacit knowledge that exists in the minds of students and that knowledge which is embedded in the process and relationships of the classroom educational experience. Knowledge conversion is required when working with tacit knowledge and the demand for a learner to align deeply held beliefs with the cognitive dissonance created by new information. Knowledge conversion and tacit knowledge result from the fact that an individual's way of knowing, that is, their core belief structure, is considered generalized and tacit instead of explicit and specific. As a phenomenon, tacit knowledge is not readily available to the learner for explicit description unless evoked by an external source. The development of knowledge–related capabilities such as Aggressive Development of Tacit Knowledge (ADTK) can be used in experiential educational programs to enhance knowledge, foster behavioral change, improve decision making, and overall performance. ADTK allows the student in HIPs to use their existing knowledge in a way that allows them to evaluate and make any necessary modifications to their core construct of reality in order to amalgamate new information. Based on the Lewin/Schein Change Theory, the learner will reach for tacit knowledge as a stabilizing mechanism when they are challenged by new information that puts them slightly off balance. As in word association drills, the important concept is the first thought. The reactionary outpouring to an experience is the programmed or tacit memory and knowledge of their core belief structure. ADTK is a way to help teachers design their own methods and activities to unfreeze, create new learning, and then refreeze the core constructs upon which future learning in a subject area is built. This paper will explore the use of ADTK as a technique for knowledge conversion in the classroom in general and in HIP programs specifically. It will focus on knowledge conversion in curriculum development and propose the use of one-time educational experiences, multi-session experiences and sequential program experiences focusing on tacit knowledge in educational programs.Keywords: tacit knowledge, knowledge management, college programs, experiential learning
Procedia PDF Downloads 25311534 Multi-Modal Visualization of Working Instructions for Assembly Operations
Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger
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Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.Keywords: assembly, assistive technologies, augmented reality, manufacturing, visualization
Procedia PDF Downloads 15711533 Experiential Learning: Roles and Attributes of an Optometry Educator Recommended by a Millennial Generation
Authors: E. Kempen, M. J. Labuschagne, M. P. Jama
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There is evidence that experiential learning is truly influential and favored by the millennial generation. However, little is known about the role and attributes an educator has to adopt during the experiential learning cycle, especially when applied in optometry education. This study aimed to identify the roles and attributes of an optometry educator during the different modes of the experiential learning cycle. Methods: A qualitative case study design was used. Data was collected using an open-ended questionnaire survey, following the application of nine different teaching-learning methods based on the experimental learning cycle. The total sample population of 68 undergraduate students from the Department of Optometry at the University of the Free State, South Africa were invited to participate. Focus group interviews (n=15) added additional data that contributed to the interpretation and confirmation of the data obtained from the questionnaire surveys. Results: The perceptions and experiences of the students identified a variety of roles and attributes as well as recommendations on the effective adoption of these roles and attributes. These roles and attributes included being knowledgeable, creating an interest, providing guidance, being approachable, building confidence, implementing ground rules, leading by example, and acting as a mediator. Conclusion: The findings suggest that the actions of an educator have the most substantial impact on students’ perception of a learning experience. Not only are the recommendations based on the views of a millennial generation, but the implementation of the personalized recommendations may also transform a learning environment. This may lead an optometry student to a deeper understanding of knowledge.Keywords: experiences and perceptions, experiential learning, millennial generation, recommendation for optometry education
Procedia PDF Downloads 111