Search results for: language learning model
20238 Teaching College Classes with Virtual Reality
Authors: Penn P. Wu
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Recent advances in virtual reality (VR) technologies have made it possible for students to experience a virtual on-the-scene or virtual in-person observation of an educational event. In an experimental class, the author uses VR, particularly 360° videos, to virtually engage students in an event, through a wide spectrum of educational resources, such s a virtual “bystander.” Students were able to observe the event as if they were physically on site, although they could not intervene with the scene. The author will describe the adopted equipment, specification, and cost of building them as well as the quality of VR. The author will discuss (a) feasibility, effectiveness, and efficiency of using VR as a supplemental technology to teach college students and criteria and methodologies used by the authors to evaluate them; (b) barriers and issues of technological implementation; and (c) pedagogical practices learned through this experiment. The author also attempts to explore (a) how VR could provide an interactive virtual in-person learning experience; (b) how VR can possibly change traditional college education and online education; (c) how educators and balance six critical factors: cost, time, technology, quality, result, and content.Keywords: learning with VR, virtual experience of learning, virtual in-person learning, virtual reality for education
Procedia PDF Downloads 30020237 Human Posture Estimation Based on Multiple Viewpoints
Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo
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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.Keywords: multi-view, pose estimation, ST-GCN, joint fusion
Procedia PDF Downloads 6120236 Learning from Inclusive Education of Exceptional and Normal Children in Primary School for Architectural Design
Authors: T. Pastraporn, J. Panida, P. Gasamapong, N. Jintana
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The study of inclusive educational environment of exceptional and normal children at the regional centre for special education aimed to establish guidelines for creating an environment for inclusive education. Buildings utilization of thirty-five elementary schools providing inclusive educational program in Bangkok were analyzed to study the following aspects: 1) The environment of exceptional and normal students’ inclusive classes at the regional centre for special education 2) The patterns of the environment suited to the exceptional and normal students’ inclusive classes 3) Environmental management policies for the inclusive classes of exceptional and normal students. Information was gathered from surveys, observations, questionnaires, document analysis, interviews, and non-experimental research. The findings showed that the usable spaces in school buildings were designated to enhance the three kinds of social learning experience: 1) Support class control 2) Help developing students’ personality consisting of physical, verbal and emotional expressions that are socially accepted 3) Recognition and learning, which are needed for the increasing of learning experience, were caused by having an interaction with the environment. Thus, the school buildings’ space designation positively affected the environmental management of exceptional and normal students’ inclusive classes.Keywords: learning environment, inclusive education, school buildings, exceptional and normal children
Procedia PDF Downloads 32320235 Language and Study Skill Needs: A Case Study of ESP Learners at the Language Centre of Sultan Qaboos University, Oman
Authors: Ahmed Mohamed Al-Abdali
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Providing English for Specific Purposes (ESP) courses that are more closely geared to the learners’ needs and requirements in their fields of study undoubtedly enhance learners’ interest and success in a highly academic environment. While needs analysis is crucial to the success of ESP courses, it has not received sufficient attention from researchers in the Arab world. Oman is no exception from the Arab countries as this fact is realised in the ESP practices in the Omani higher educational context. This presentation, however, discusses the perceptions of the Language Centre (LC) students at Sultan Qaboos University (SQU), Oman, in relation to the requirements of their science colleges. The discussion of the presentation will be based on a mixed-method-approach study, which included semi-structured interviews, questionnaires and document analyses. These mixed methods have allowed for closer investigation of the participants' views, backgrounds and experiences. It is hoped that the findings of this study will be used to recommend changes to the ESP curriculum in the LC of SQU so that it better meets the needs of its students and requirements of the science colleges.Keywords: curriculum, ESP, ELT, needs analysis, college requirements
Procedia PDF Downloads 31420234 A Mathematical Equation to Calculate Stock Price of Different Growth Model
Authors: Weiping Liu
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This paper presents an equation to calculate stock prices of different growth model. This equation is mathematically derived by using discounted cash flow method. It has the advantages of being very easy to use and very accurate. It can still be used even when the first stage is lengthy. This equation is more generalized because it can be used for all the three popular stock price models. It can be programmed into financial calculator or electronic spreadsheets. In addition, it can be extended to a multistage model. It is more versatile and efficient than the traditional methods.Keywords: stock price, multistage model, different growth model, discounted cash flow method
Procedia PDF Downloads 39820233 The Effect of Computer-Based Formative Assessment on Learning Outcome
Authors: Van Thien NGO
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The purpose of the study is to examine the effect of student response systems in computer-based formative assessment on learning outcomes. The backward design course is a tool to be applied for collecting necessary assessment evidence. The quasi-experimental research design involves collecting pre and posttest data on students assigned to the control group and the experimental group. The sample group consists of 150 college students randomly selected from two of the eight classes of electrical and electronics students at Cao Thang Technical College in Ho Chi Minh City, Vietnam. Findings from this research revealed that the experimental group, in which student response systems were applied, got better results than the controlled group, who did not apply them. Results show that using student response systems for technology-based formative assessment is vital and meaningful not only for teachers but also for students in the teaching and learning process.Keywords: student response system, computer-based formative assessment, learning outcome, backward design course
Procedia PDF Downloads 12520232 Compounding and Blending in English and Hausa Languages
Authors: Maryam Maimota
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Words are the basic building blocks of a language. In everyday usage of a language, words are used and new words are formed and reformed in order to contain and accommodate all entities, phenomena, qualities and every aspect of the entire human life. This research study seeks to examine and compare some of the word formation processes and how they are used in forming new words in English and Hausa languages. The study focuses its main attention on blending and compounding as word formation processes and how the processes are used adequately in the formation of words in both English and Hausa languages. The research aims to find out, how compounding and blending are used, as processes of word formation in these two languages. And also, to investigate the word formation processes involved in compounding and blending in these languages, and the nature of words that are formed. Therefore, the research tries to find the answers to the following research questions; What types of compound and blended forms are found and how they are formed in the English and Hausa languages? How these compounded and blended forms functioned in both English and Hausa languages in different context such as in phrases and sentences structures? Findings of the study reveal that, there exist new kind of words formed in Hausa and English language under blending, which previous findings did not either reveal or explain in detail. Similarly, there are a lot of similarities found in the way these blends and compounds forms in the two languages, however, the data available shows that, blends in the Hausa language are more, when compared to the blends in English. The data of this study will be gathered based on discourse found in newspaper, articles, novels, and written literature of the Hausa and English languages.Keywords: blending, compounding, morphology, word formation
Procedia PDF Downloads 37420231 Workplace Development Programmes for Small and Medium-Sized Enterprises in Europe and Singapore: A Conceptual Study
Authors: Zhan Jie How
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With the heightened awareness of workplace learning and its impact on improving organizational performance and developing employee competence, governments and corporations around the world are forced to intensify their cooperation to establish national workplace development programmes to guide these corporations in fostering engaging and collaborative workplace learning cultures. This conceptual paper aims to conduct a comparative study of existing workplace development programmes for small and medium-sized enterprises (SMEs) in Europe and Singapore, focusing primarily on the Swedish Production Leap, Finnish TEKES Liideri Programme, and Singapore SkillsFuture SME Mentors Programme. The study carries out a systematic review of the three workplace development programmes to examine the roles of external mentors or coaches in influencing the design and implementation of workplace learning strategies and practices in SMEs. Organizational, personal and external factors that promote or inhibit effective workplace mentorship are also scrutinized, culminating in a critical comparison and evaluation of the strengths and weaknesses of the aforementioned programmes. Based on the findings from the review and analyses, a heuristic conceptual framework is developed to illustrate the complex interrelationships among external workplace development programmes, internal learning and development initiatives instituted by the organization’s higher management, and employees' continuous learning activities at the workplace. The framework also includes a set of guiding principles that can be used as the basis for internal mediation between the competing perspectives of mentors and mentees (employers and employees of the organization) regarding workplace learning conditions, practices and their intended impact on the organization. The conceptual study provides a theoretical blueprint for future empirical research on organizational workplace learning and the impact of government-initiated workplace development programmes.Keywords: employee competence, mentorship, organizational performance, workplace development programme, workplace learning culture
Procedia PDF Downloads 13520230 Purposes of Urdu Translations of the Meanings of Holy Quran
Authors: Muhammad Saleem
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The research paper entitled above would be a comprehensive and critical study of translations of the meanings of the Holy Qur’an. The discussion will deal with the targets & purposes of Urdu (National Language of Pakistan) translators of the meanings of the Holy Qur’an. There are more than 400 translations of the meanings of the Holy Qur’an in the Urdu Language. Muslims, non-Muslims and some organizations have made translations of the meanings of the Holy Qur’an to meet various targets. It is observed that all Urdu translators have not translated the Qur’an with a single objective and motivation; rather, some are biased and strive to discredit the Qur’an. Thus, they have made unauthentic and fabricated translations of the Qur’an. Some optimistically believe that they intend to do a service, whereas others pessimistically hold that they treacherously seek to further their rule. Some of them have been observed to be against Islam, starting their activities with spite, but after perceiving the truths of Islam and the miracle and greatness of the Holy Qur’an, they submitted to Islam, embracing it with pure hearts. Some translators made their translations of the meanings of the Holy Qur’an to serve Allah, and some of them have done their translations to earn only. All these translations vary from one to another due to style, trend, type, method and style. Some Urdu translations have been made to fulfill the lingual requirements. Some translations have been made by Muslim scholars to reduce the influence of Urdu translations of the meanings of the Holy Qur’an by Non-Muslims. The article deals with the various purposes of the translators of the meanings of the Holy Qur’an.Keywords: Qur'an, translation, urdu, language
Procedia PDF Downloads 2620229 A Novel Exploration/Exploitation Policy Accelerating Learning In Both Stationary And Non Stationary Environment Navigation Tasks
Authors: Wiem Zemzem, Moncef Tagina
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In this work, we are addressing the problem of an autonomous mobile robot navigating in a large, unknown and dynamic environment using reinforcement learning abilities. This problem is principally related to the exploration/exploitation dilemma, especially the need to find a solution letting the robot detect the environmental change and also learn in order to adapt to the new environmental form without ignoring knowledge already acquired. Firstly, a new action selection strategy, called ε-greedy-MPA (the ε-greedy policy favoring the most promising actions) is proposed. Unlike existing exploration/exploitation policies (EEPs) such as ε-greedy and Boltzmann, the new EEP doesn’t only rely on the information of the actual state but also uses those of the eventual next states. Secondly, as the environment is large, an exploration favoring least recently visited states is added to the proposed EEP in order to accelerate learning. Finally, various simulations with ball-catching problem have been conducted to evaluate the ε-greedy-MPA policy. The results of simulated experiments show that combining this policy with the Qlearning method is more effective and efficient compared with the ε-greedy policy in stationary environments and the utility-based reinforcement learning approach in non stationary environments.Keywords: autonomous mobile robot, exploration/ exploitation policy, large, dynamic environment, reinforcement learning
Procedia PDF Downloads 41120228 The Effect of Mobile Technology Use in Education: A Meta-Analysis Study
Authors: Şirin Küçük, Ayşe Kök, İsmail Şahin
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Mobile devices are very popular and useful tools for assisting people in daily life. With the advancement of mobile technologies, the issue of mobile learning has been widely investigated in education. Many researches consider that it is important to integrate pedagogical and technical strengths of mobile technology into learning environments. For this reason, the purpose of this research is to examine the effect of mobile technology use in education with meta-analysis method. Meta-analysis is a statistical technique which combines the findings of independent studies in a specific subject. In this respect, the articles will be examined by searching the databases for researches which are conducted between 2005 and 2014. It is expected that the results of this research will contribute to future research related to mobile technology use in education.Keywords: mobile learning, meta-analysis, mobile technology, education
Procedia PDF Downloads 71720227 Monocular Depth Estimation Benchmarking with Thermal Dataset
Authors: Ali Akyar, Osman Serdar Gedik
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Depth estimation is a challenging computer vision task that involves estimating the distance between objects in a scene and the camera. It predicts how far each pixel in the 2D image is from the capturing point. There are some important Monocular Depth Estimation (MDE) studies that are based on Vision Transformers (ViT). We benchmark three major studies. The first work aims to build a simple and powerful foundation model that deals with any images under any condition. The second work proposes a method by mixing multiple datasets during training and a robust training objective. The third work combines generalization performance and state-of-the-art results on specific datasets. Although there are studies with thermal images too, we wanted to benchmark these three non-thermal, state-of-the-art studies with a hybrid image dataset which is taken by Multi-Spectral Dynamic Imaging (MSX) technology. MSX technology produces detailed thermal images by bringing together the thermal and visual spectrums. Using this technology, our dataset images are not blur and poorly detailed as the normal thermal images. On the other hand, they are not taken at the perfect light conditions as RGB images. We compared three methods under test with our thermal dataset which was not done before. Additionally, we propose an image enhancement deep learning model for thermal data. This model helps extract the features required for monocular depth estimation. The experimental results demonstrate that, after using our proposed model, the performance of these three methods under test increased significantly for thermal image depth prediction.Keywords: monocular depth estimation, thermal dataset, benchmarking, vision transformers
Procedia PDF Downloads 2620226 Modifying Assessment Modes in the Science Classroom as a Solution to Examination Malpractice
Authors: Catherine Omole
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Examination malpractice includes acts that temper with collecting accurate results during the conduct of an examination, thereby giving undue advantage to a student over his colleagues. Even though examination malpractice has been a lingering problem, examinations may not be easy to do away with completely as it is an important feedback tool in the learning process with several other functions e.g for the purpose of selection, placement, certification and promotion. Examination malpractice has created a lot of problems such as a relying on a weak work force based on false assessment results. The question is why is this problem still persisting, despite measures that have been taken to curb this ugly trend over the years? This opinion paper has identified modifications that could help relieve the student of the examination stress and thus increase the student’s effort towards effective learning and discourage examination malpractice in the long run.Keywords: assessment, examination malpractice, learning, science classroom
Procedia PDF Downloads 25420225 Deciphering Orangutan Drawing Behavior Using Artificial Intelligence
Authors: Benjamin Beltzung, Marie Pelé, Julien P. Renoult, Cédric Sueur
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To this day, it is not known if drawing is specifically human behavior or if this behavior finds its origins in ancestor species. An interesting window to enlighten this question is to analyze the drawing behavior in genetically close to human species, such as non-human primate species. A good candidate for this approach is the orangutan, who shares 97% of our genes and exhibits multiple human-like behaviors. Focusing on figurative aspects may not be suitable for orangutans’ drawings, which may appear as scribbles but may have meaning. A manual feature selection would lead to an anthropocentric bias, as the features selected by humans may not match with those relevant for orangutans. In the present study, we used deep learning to analyze the drawings of a female orangutan named Molly († in 2011), who has produced 1,299 drawings in her last five years as part of a behavioral enrichment program at the Tama Zoo in Japan. We investigate multiple ways to decipher Molly’s drawings. First, we demonstrate the existence of differences between seasons by training a deep learning model to classify Molly’s drawings according to the seasons. Then, to understand and interpret these seasonal differences, we analyze how the information spreads within the network, from shallow to deep layers, where early layers encode simple local features and deep layers encode more complex and global information. More precisely, we investigate the impact of feature complexity on classification accuracy through features extraction fed to a Support Vector Machine. Last, we leverage style transfer to dissociate features associated with drawing style from those describing the representational content and analyze the relative importance of these two types of features in explaining seasonal variation. Content features were relevant for the classification, showing the presence of meaning in these non-figurative drawings and the ability of deep learning to decipher these differences. The style of the drawings was also relevant, as style features encoded enough information to have a classification better than random. The accuracy of style features was higher for deeper layers, demonstrating and highlighting the variation of style between seasons in Molly’s drawings. Through this study, we demonstrate how deep learning can help at finding meanings in non-figurative drawings and interpret these differences.Keywords: cognition, deep learning, drawing behavior, interpretability
Procedia PDF Downloads 15520224 Compare the Effectiveness of Web Based and Blended Learning on Paediatric Basic Life Support
Authors: Maria Janet, Anita David, P. Vijayasamundeeswarimaria
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Introduction: The main purpose of this study is to compare the effectiveness of web-based and blended learning on Paediatric Basic Life Support on competency among undergraduate nursing students in selected nursing colleges in Chennai. Materials and methods: A descriptive pre-test and post-test study design were used for this study. Samples of 100 Fourth year B.Sc., nursing students at Sri Ramachandra Faculty of Nursing SRIHER, Chennai, 100 Fourth year B.Sc., nursing students at Apollo College of Nursing, Chennai, were selected by purposive sampling technique. The instrument used for data collection was Knowledge Questionnaire on Paediatric Basic Life Support (PBLS). It consists of 29 questions on the general expansion of Basic Life Support and Cardiopulmonary Resuscitation, Prerequisites of Basic Life Support, and Knowledge on Paediatric Basic Life Support in which each question has four multiple choices answers, each right answer carrying one mark and no negative scoring. This questionnaire was formed with reference to AHA 2020 (American Heart Association) revised guidelines. Results: After the post-test, in the web-based learning group, 58.8% of the students had an inadequate level of objective performance score, while 41.1% of them had an adequate level of objective performance score. In the blended learning group, 26.5% of the students had an inadequate level of an objective performance score, and 73.4% of the students had an adequate level of an objective performance score. There was an association between the post-test level of knowledge and the demographic variables of undergraduate nursing students undergoing blended learning. The age was significant at a p-value of 0.01, and the performance of BLS before was significant at a p-value of 0.05. The results show that there was a significant positive correlation between knowledge and objective performance score of undergraduate nursing students undergoing web-based learning on paediatric basic life support.Keywords: basic life support, paediatric basic life support, web-based learning, blended learning
Procedia PDF Downloads 6520223 Strategies for Improving Teaching and Learning in Higher Institutions: Case Study of Enugu State University of Science and Technology, Nigeria
Authors: Gertrude Nkechi Okenwa
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Higher institutions, especially the universities that are saddled with the responsibilities of teaching, learning, research, publications and social services for the production of graduates that are worthy in learning and character, and the creation of up-to-date knowledge and innovations for the total socio-economic and even political development of a given nation. Therefore, the purpose of the study was to identify the teaching, learning techniques used in the Enugu State University of Science and Technology to ensure or ascertain students’ perception on these techniques. To guide the study, survey research method was used. The population for the study was made up of second and final year students which summed up to one hundred and twenty-six students in the faculty of education. Stratified random sampling technique was adopted. A sample size of sixty (60) students was drawn for the study. The instrument used for data collection was questionnaire. To analyze the data, mean and standard deviation were used to answers the research questions. The findings revealed that direct instruction and construction techniques are used in the university. On the whole, it was observed that the students perceived constructivist techniques to be more useful and effective than direct instruction technique. Based on the findings recommendations were made to include diversification of teaching techniques among others.Keywords: Strategies, Teaching and Learning, Constructive Technique, Direct Instructional Technique
Procedia PDF Downloads 53620222 General Mathematical Framework for Analysis of Cattle Farm System
Authors: Krzysztof Pomorski
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In the given work we present universal mathematical framework for modeling of cattle farm system that can set and validate various hypothesis that can be tested against experimental data. The presented work is preliminary but it is expected to be valid tool for future deeper analysis that can result in new class of prediction methods allowing early detection of cow dieseaes as well as cow performance. Therefore the presented work shall have its meaning in agriculture models and in machine learning as well. It also opens the possibilities for incorporation of certain class of biological models necessary in modeling of cow behavior and farm performance that might include the impact of environment on the farm system. Particular attention is paid to the model of coupled oscillators that it the basic building hypothesis that can construct the model showing certain periodic or quasiperiodic behavior.Keywords: coupled ordinary differential equations, cattle farm system, numerical methods, stochastic differential equations
Procedia PDF Downloads 13620221 Numerical Solutions of Fractional Order Epidemic Model
Authors: Sadia Arshad, Ayesha Sohail, Sana Javed, Khadija Maqbool, Salma Kanwal
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The dynamical study of the carriers play an essential role in the evolution and global transmission of infectious diseases and will be discussed in this study. To make this approach novel, we will consider the fractional order model which is generalization of integer order derivative to an arbitrary number. Since the integration involved is non local therefore this property of fractional operator is very useful to study epidemic model for infectious diseases. An extended numerical method (ODE solver) is implemented on the model equations and we will present the simulations of the model for different values of fractional order to study the effect of carriers on transmission dynamics. Global dynamics of fractional model are established by using the reproduction number.Keywords: Fractional differential equation, Numerical simulations, epidemic model, transmission dynamics
Procedia PDF Downloads 59020220 A Generative Adversarial Framework for Bounding Confounded Causal Effects
Authors: Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu
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Causal inference from observational data is receiving wide applications in many fields. However, unidentifiable situations, where causal effects cannot be uniquely computed from observational data, pose critical barriers to applying causal inference to complicated real applications. In this paper, we develop a bounding method for estimating the average causal effect (ACE) under unidentifiable situations due to hidden confounders. We propose to parameterize the unknown exogenous random variables and structural equations of a causal model using neural networks and implicit generative models. Then, with an adversarial learning framework, we search the parameter space to explicitly traverse causal models that agree with the given observational distribution and find those that minimize or maximize the ACE to obtain its lower and upper bounds. The proposed method does not make any assumption about the data generating process and the type of the variables. Experiments using both synthetic and real-world datasets show the effectiveness of the method.Keywords: average causal effect, hidden confounding, bound estimation, generative adversarial learning
Procedia PDF Downloads 18120219 Generation of Knowlege with Self-Learning Methods for Ophthalmic Data
Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder
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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods
Procedia PDF Downloads 25020218 Engaging Teacher Inquiry via New Media in Traditional and E-Learning Environments
Authors: Daniel A. Walzer
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As the options for course delivery and development expand, plenty of misconceptions still exist concerning e-learning and online course delivery. Classroom instructors often discuss pedagogy, methodologies, and best practices regarding teaching from a singular, traditional in-class perspective. As more professors integrate online, blended, and hybrid courses into their dossier, a clearly defined rubric for gauging online course delivery is essential. The transition from a traditional learning structure towards an updated distance-based format requires careful planning, evaluation, and revision. This paper examines how new media stimulates reflective practice and guided inquiry to improve pedagogy, engage interdisciplinary collaboration, and supply rich qualitative data for future research projects in media arts disciplines.Keywords: action research, inquiry, new media, reflection
Procedia PDF Downloads 30520217 Factors Impacting Technology Integration in EFL Classrooms: A Study of Qatari Independent Schools
Authors: Youmen Chaaban, Maha Ellili-Cherif
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The purpose of this study was to examine the effects of teachers’ individual characteristics and perceptions of environmental factors that impact their technology integration into their EFL (English as a Foreign Language) classrooms. To this end, a national survey examining EFL teachers’ perceptions was conducted at Qatari Independent schools. 263 EFL teachers responded to the survey which investigated several factors known to impact technology integration. These factors included technology availability and support, EFL teachers’ perceptions of importance, obstacles facing technology integration, competency with technology use, and formal technology preparation. The impact of these factors on teachers’ and students’ educational technology use was further measured. The analysis of the data included descriptive statistics and a chi-square analysis test in order to examine the relationship between these factors. The results revealed important cultural factors that impact teachers’ practices and attitudes towards technology in the Qatari context. EFL teachers were found to integrate technology most prominently for instructional delivery and preparation. The use of technology as a learning tool received less emphasis. Teachers further revealed consistent perceptions about obstacles to integration, high levels of confidence in using technology, and consistent beliefs about the importance of using technology as a learning tool. Further analyses of the factors impacting technology integration can assist with Qatar’s technology advancement and development efforts by indicating the areas of strength and areas where additional efforts are needed. The results will lay the foundation for conducting context-specific professional development suitable for the needs of EFL teachers in Qatari Independent Schools.Keywords: educational technology integration, Qatar, EFL, independent schools, ICT
Procedia PDF Downloads 37720216 Impact of Pedagogical Techniques on the Teaching of Sports Sciences
Authors: Muhammad Saleem
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Background: The teaching of sports sciences encompasses a broad spectrum of disciplines, including biomechanics, physiology, psychology, and coaching. Effective pedagogical techniques are crucial in imparting both theoretical knowledge and practical skills necessary for students to excel in the field. The impact of these techniques on students’ learning outcomes, engagement, and professional preparedness remains a vital area of study. Objective: This study aims to evaluate the effectiveness of various pedagogical techniques used in the teaching of sports sciences. It seeks to identify which methods most significantly enhance student learning, retention, engagement, and practical application of knowledge. Methods: A mixed-methods approach was employed, including both quantitative and qualitative analyses. The study involved a comparative analysis of traditional lecture-based teaching, experiential learning, problem-based learning (PBL), and technology-enhanced learning (TEL). Data were collected through surveys, interviews, and academic performance assessments from students enrolled in sports sciences programs at multiple universities. Statistical analysis was used to evaluate academic performance, while thematic analysis was applied to qualitative data to capture student experiences and perceptions. Results: The findings indicate that experiential learning and PBL significantly improve students' understanding and retention of complex sports science concepts compared to traditional lectures. TEL was found to enhance engagement and provide students with flexible learning opportunities, but its impact on deep learning varied depending on the quality of the digital resources. Overall, a combination of experiential learning, PBL, and TEL was identified as the most effective pedagogical approach, leading to higher student satisfaction and better preparedness for real-world applications. Conclusion: The study underscores the importance of adopting diverse and student-centered pedagogical techniques in the teaching of sports sciences. While traditional lectures remain useful for foundational knowledge, integrating experiential learning, PBL, and TEL can substantially improve student outcomes. These findings suggest that educators should consider a blended approach to pedagogy to maximize the effectiveness of sports science education.Keywords: sport sciences, pedagogical techniques, health and physical education, problem-based learning, student engagement
Procedia PDF Downloads 1120215 Identification of Biological Pathways Causative for Breast Cancer Using Unsupervised Machine Learning
Authors: Karthik Mittal
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This study performs an unsupervised machine learning analysis to find clusters of related SNPs which highlight biological pathways that are important for the biological mechanisms of breast cancer. Studying genetic variations in isolation is illogical because these genetic variations are known to modulate protein production and function; the downstream effects of these modifications on biological outcomes are highly interconnected. After extracting the SNPs and their effect on different types of breast cancer using the MRBase library, two unsupervised machine learning clustering algorithms were implemented on the genetic variants: a k-means clustering algorithm and a hierarchical clustering algorithm; furthermore, principal component analysis was executed to visually represent the data. These algorithms specifically used the SNP’s beta value on the three different types of breast cancer tested in this project (estrogen-receptor positive breast cancer, estrogen-receptor negative breast cancer, and breast cancer in general) to perform this clustering. Two significant genetic pathways validated the clustering produced by this project: the MAPK signaling pathway and the connection between the BRCA2 gene and the ESR1 gene. This study provides the first proof of concept showing the importance of unsupervised machine learning in interpreting GWAS summary statistics.Keywords: breast cancer, computational biology, unsupervised machine learning, k-means, PCA
Procedia PDF Downloads 13720214 Direct Torque Control of Induction Motor Employing Teaching Learning Based Optimization
Authors: Anam Gopi
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The undesired torque and flux ripple may occur in conventional direct torque control (DTC) induction motor drive. DTC can improve the system performance at low speeds by continuously tuning the regulator by adjusting the Kp, Ki values. In this Teaching Learning Based Optimization (TLBO) is proposed to adjust the parameters (Kp, Ki) of the speed controller in order to minimize torque ripple, flux ripple, and stator current distortion. The TLBO based PI controller has resulted is maintaining a constant speed of the motor irrespective of the load torque fluctuations.Keywords: teaching learning based optimization, direct torque control, PI controller
Procedia PDF Downloads 58020213 The Speech Act Responses of Students on the Teacher’s Request in the EFL Classroom
Authors: Agis Andriani
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To create an effective teaching condition, the teacher requests the students as the instruction to guide the them interactively in the learning activities in the classroom. This study involves 160 Indonesian students who study English in the university, as participants in the discourse completion test, and ten of them are interviewed. The result shows that when the students response the teacher’s request, it realizes assertives, directives, commisives, expressives, and declaratives. These indicate that the students are active, motivated, and responsive in the learning process, although in the certain condition these responses are to prevent their faces from the shyness of their silence in interaction. Therefore, it needs the teacher’s creativity to give the conducive atmosphere in order to support the students’ participation in learning English.Keywords: discourse completion test, effective teaching, request, teacher’s creativity
Procedia PDF Downloads 42620212 A Proposal for a Combustion Model Considering the Lewis Number and Its Evaluation
Authors: Fujio Akagi, Hiroaki Ito, Shin-Ichi Inage
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The aim of this study is to develop a combustion model that can be applied uniformly to laminar and turbulent premixed flames while considering the effect of the Lewis number (Le). The model considers the effect of Le on the transport equations of the reaction progress, which varies with the chemical species and temperature. The distribution of the reaction progress variable is approximated by a hyperbolic tangent function, while the other distribution of the reaction progress variable is estimated using the approximated distribution and transport equation of the reaction progress variable considering the Le. The validity of the model was evaluated under the conditions of propane with Le > 1 and methane with Le = 1 (equivalence ratios of 0.5 and 1). The estimated results were found to be in good agreement with those of previous studies under all conditions. A method of introducing a turbulence model into this model is also described. It was confirmed that conventional turbulence models can be expressed as an approximate theory of this model in a unified manner.Keywords: combustion model, laminar flame, Lewis number, turbulent flame
Procedia PDF Downloads 11420211 Innovation in Traditional Game: A Case Study of Trainee Teachers' Learning Experiences
Authors: Malathi Balakrishnan, Cheng Lee Ooi, Chander Vengadasalam
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The purpose of this study is to explore a case study of trainee teachers’ learning experience on innovating traditional games during the traditional game carnival. It explores issues arising from multiple case studies of trainee teachers learning experiences in innovating traditional games. A qualitative methodology was adopted through observations, semi-structured interviews and reflective journals’ content analysis of trainee teachers’ learning experiences creating and implementing innovative traditional games. Twelve groups of 36 trainee teachers who registered for Sports and Physical Education Management Course were the participants for this research during the traditional game carnival. Semi structured interviews were administrated after the trainee teachers learning experiences in creating innovative traditional games. Reflective journals were collected after carnival day and the content analyzed. Inductive data analysis was used to evaluate various data sources. All the collected data were then evaluated through the Nvivo data analysis process. Inductive reasoning was interpreted based on the Self Determination Theory (SDT). The findings showed that the trainee teachers had positive game participation experiences, game knowledge about traditional games and positive motivation to innovate the game. The data also revealed the influence of themes like cultural significance and creativity. It can be concluded from the findings that the organized game carnival, as a requirement of course work by the Institute of Teacher Training Malaysia, was able to enhance teacher trainers’ innovative thinking skills. The SDT, as a multidimensional approach to motivation, was utilized. Therefore, teacher trainers may have more learning experiences using the SDT.Keywords: learning experiences, innovation, traditional games, trainee teachers
Procedia PDF Downloads 32520210 The Establishment and Application of TRACE/FRAPTRAN Model for Kuosheng Nuclear Power Plant
Authors: S. W. Chen, W. K. Lin, J. R. Wang, C. Shih, H. T. Lin, H. C. Chang, W. Y. Li
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Kuosheng nuclear power plant (NPP) is a BWR/6 type NPP and located on the northern coast of Taiwan. First, Kuosheng NPP TRACE model were developed in this research. In order to assess the system response of Kuosheng NPP TRACE model, startup tests data were used to evaluate Kuosheng NPP TRACE model. Second, the over pressurization transient analysis of Kuosheng NPP TRACE model was performed. Besides, in order to confirm the mechanical property and integrity of fuel rods, FRAPTRAN analysis was also performed in this study.Keywords: TRACE, safety analysis, BWR/6, FRAPTRA
Procedia PDF Downloads 55720209 The Positive Effects of Processing Instruction on the Acquisition of French as a Second Language: An Eye-Tracking Study
Authors: Cecile Laval, Harriet Lowe
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Processing Instruction is a psycholinguistic pedagogical approach drawing insights from the Input Processing Model which establishes the initial innate strategies used by second language learners to connect form and meaning of linguistic features. With the ever-growing use of technology in Second Language Acquisition research, the present study uses eye-tracking to measure the effectiveness of Processing Instruction in the acquisition of French and its effects on learner’s cognitive strategies. The experiment was designed using a TOBII Pro-TX300 eye-tracker to measure participants’ default strategies when processing French linguistic input and any cognitive changes after receiving Processing Instruction treatment. Participants were drawn from lower intermediate adult learners of French at the University of Greenwich and randomly assigned to two groups. The study used a pre-test/post-test methodology. The pre-tests (one per linguistic item) were administered via the eye-tracker to both groups one week prior to instructional treatment. One group received full Processing Instruction treatment (explicit information on the grammatical item and on the processing strategies, and structured input activities) on the primary target linguistic feature (French past tense imperfective aspect). The second group received Processing Instruction treatment except the explicit information on the processing strategies. Three immediate post-tests on the three grammatical structures under investigation (French past tense imperfective aspect, French Subjunctive used for the expression of doubt, and the French causative construction with Faire) were administered with the eye-tracker. The eye-tracking data showed the positive change in learners’ processing of the French target features after instruction with improvement in the interpretation of the three linguistic features under investigation. 100% of participants in both groups made a statistically significant improvement (p=0.001) in the interpretation of the primary target feature (French past tense imperfective aspect) after treatment. 62.5% of participants made an improvement in the secondary target item (French Subjunctive used for the expression of doubt) and 37.5% of participants made an improvement in the cumulative target feature (French causative construction with Faire). Statistically there was no significant difference between the pre-test and post-test scores in the cumulative target feature; however, the variance approximately tripled between the pre-test and the post-test (3.9 pre-test and 9.6 post-test). This suggests that the treatment does not affect participants homogenously and implies a role for individual differences in the transfer-of-training effect of Processing Instruction. The use of eye-tracking provides an opportunity for the study of unconscious processing decisions made during moment-by-moment comprehension. The visual data from the eye-tracking demonstrates changes in participants’ processing strategies. Gaze plots from pre- and post-tests display participants fixation points changing from focusing on content words to focusing on the verb ending. This change in processing strategies can be clearly seen in the interpretation of sentences in both primary and secondary target features. This paper will present the research methodology, design and results of the experimental study using eye-tracking to investigate the primary effects and transfer-of-training effects of Processing Instruction. It will then provide evidence of the cognitive benefits of Processing Instruction in Second Language Acquisition and offer suggestion in second language teaching of grammar.Keywords: eye-tracking, language teaching, processing instruction, second language acquisition
Procedia PDF Downloads 275