Search results for: intergenerational learning
5809 The Context of Teaching and Learning Primary Science to Gifted Students: An Analysis of Australian Curriculum and New South Wales Science Syllabus
Authors: Rashedul Islam
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A firmly-validated aim of teaching science is to support student enthusiasm for science learning with an outspread interest in scientific issues in future life. This is in keeping with the recent development in Gifted and Talented Education statement which instructs that gifted students have a renewed interest and natural aptitude in science. Yet, the practice of science teaching leaves many students with the feeling that science is difficult and compared to other school subjects, students interest in science is declining at the final years of the primary school. As a curriculum guides the teaching-learning activities in school, where significant consequences may result from the context of the curricula and syllabi, are a major feature of certain educational jurisdictions in NSW, Australia. The purpose of this study was an exploration of the curriculum sets the context to identify how science education is practiced through primary schools in Sydney, Australia. This phenomenon was explored through document review from two publicly available documents namely: the NSW Science Syllabus K-6, and Australian Curriculum: Foundation - 10 Science. To analyse the data, this qualitative study applied themed content analysis at three different levels, i.e., first cycle coding, second cycle coding- pattern codes, and thematic analysis. Preliminary analysis revealed the phenomenon of teaching-learning practices drawn from eight themes under three phenomena aligned with teachers’ practices and gifted student’s learning characteristics based on Gagné’s Differentiated Model of Gifted and Talent (DMGT). From the results, it appears that, overall, the two documents are relatively well-placed in terms of identifying the context of teaching and learning primary science to gifted students. However, educators need to make themselves aware of the ways in which the curriculum needs to be adapted to meet gifted students learning needs in science. It explores the important phenomena of teaching-learning context to provide gifted students with optimal educational practices including inquiry-based learning, problem-solving, open-ended tasks, creativity in science, higher order thinking, integration, and challenges. The significance of such a study lies in its potential to schools and further research in the field of gifted education.Keywords: teaching primary science, gifted student learning, curriculum context, science syllabi, Australia
Procedia PDF Downloads 4135808 Social Mentoring: Towards Formal and Informal Deployment in the Structures of the Social and Solidarity Economy
Authors: Vanessa Casadella, Mourad Chouki, Agnès Ceccarelli, Sofiane Tahi
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Mentoring is positioned in an interpersonal and intergenerational perspective, serving the transmission of interpersonal skills and organizational culture. It echoes orientation, project, self-actualization, guidance, transmission, and filiation. It is available using a formal or informal approach. The formal dimension refers to a privileged relationship between a senior and a junior. Informal mentoring is unplanned and emerges naturally between two people who choose each other. However, it remains more difficult to understand. To study the link between formal and informal mentoring and to define the notion of “social” mentoring, we conducted a qualitative study of an exploratory nature with around ten SSE organizations located in the southeast region of Tunisia. The wealth of this territory has pushed residents to found SSE organizations with a view to creating jobs but also to preserving traditions and preserving nature. These organizations developed spontaneously to solve various local problems, such as the revitalization of deserted rural areas, environmental degradation, and the reskilling and professional reintegration of people marginalized in the labor market. This research, based on semi-structured interviews in order to obtain exhaustive and sensitive data, involves an interview guide with few questions mobilized to let the respondents, leaders of the different structures, express themselves freely. The guide includes questions on activities, methods of sharing knowledge, and difficulties in understanding between stakeholders. The interviews, lasting 30 to 60 minutes, were recorded using a dictaphone and then transcribed in full. The results are as follows: 1. We see two iterative mentoring loops. A first loop can be considered a type of formal mentoring. It highlights the support organized (in the form of training) by social enterprises with the aim of developing the autonomy, know-how, and interpersonal skills of members. A second loop concerns informal mentoring. This is non-formalized support provided by members or with other members of the entourage. This informal mentoring is mainly based on the observation of good practices and learning by doing. 2. We notice an intersection between the two loops. If the first loop is not done, the second will not take place. The knowledge acquired in the first loop is used to feed the second. 3. We note a form of reluctance on the part of some members to share their knowledge for reasons of competition. Ultimately, we retain the notion of “social” mentoring as a hybridization of formal and informal mentoring while dimensioning the “social” perspective by emphasizing the reciprocal character, solidarity, confidence, and trust between the mentor and the mentee.Keywords: social innovation, social mentoring, social and solidarity economy, informal mentoring
Procedia PDF Downloads 475807 Predictive Analytics of Student Performance Determinants
Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi
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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.Keywords: student performance, supervised machine learning, classification, cross-validation, prediction
Procedia PDF Downloads 1155806 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 2985805 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 3215804 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 1245803 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 1345802 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 4095801 Creating Inclusive Information Services: Librarians’ Design-Thinking Approach to Helping Students Succeed in the Digital Age
Authors: Yi Ding
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With the rapid development of educational technologies, higher education institutions are facing the challenge of creating an inclusive learning environment for students from diverse backgrounds. Academic libraries, the hubs of research, instruction, and innovation at higher educational institutions, are facing the same challenge. While academic librarians worldwide have been working hard to provide services for emerging information technology such as information literacy education, online learning support, and scholarly communication advocacy, the problem of digital exclusion remains a difficult one at higher education institutions. Information services provided by academic libraries can result in the digital exclusion of students from diverse backgrounds, such as students with various digital readiness levels, students with disabilities, as well as English-as-a-Second-Language learners. This research study shows how academic librarians can design digital learning objects that are cognizant of differences in learner traits and student profiles through the lens of design thinking. By demonstrating how the design process of digital learning objects can take into consideration users’ needs, experiences, and engagement with different technologies, this research study explains design principles of accessibility, connectivity, and scalability in creating inclusive digital learning objects as shown in various case studies. Equipped with the mindset and techniques to be mindful of diverse student learning traits and profiles when designing information services, academic libraries can improve the digital inclusion and ultimately student success at higher education institutions.Keywords: academic librarians, digital inclusion, information services, digital learning objects, student success
Procedia PDF Downloads 2065800 A Method of Representing Knowledge of Toolkits in a Pervasive Toolroom Maintenance System
Authors: A. Mohamed Mydeen, Pallapa Venkataram
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The learning process needs to be so pervasive to impart the quality in acquiring the knowledge about a subject by making use of the advancement in the field of information and communication systems. However, pervasive learning paradigms designed so far are system automation types and they lack in factual pervasive realm. Providing factual pervasive realm requires subtle ways of teaching and learning with system intelligence. Augmentation of intelligence with pervasive learning necessitates the most efficient way of representing knowledge for the system in order to give the right learning material to the learner. This paper presents a method of representing knowledge for Pervasive Toolroom Maintenance System (PTMS) in which a learner acquires sublime knowledge about the various kinds of tools kept in the toolroom and also helps for effective maintenance of the toolroom. First, we explicate the generic model of knowledge representation for PTMS. Second, we expound the knowledge representation for specific cases of toolkits in PTMS. We have also presented the conceptual view of knowledge representation using ontology for both generic and specific cases. Third, we have devised the relations for pervasive knowledge in PTMS. Finally, events are identified in PTMS which are then linked with pervasive data of toolkits based on relation formulated. The experimental environment and case studies show the accuracy and efficient knowledge representation of toolkits in PTMS.Keywords: knowledge representation, pervasive computing, agent technology, ECA rules
Procedia PDF Downloads 3235799 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 7145798 Collaborative Online International Learning with Different Learning Goals: A Second Language Curriculum Perspective
Authors: Andrew Nowlan
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During the Coronavirus pandemic, collaborative online international learning (COIL) emerged as an alternative to overseas sojourns. However, now that face-to-face classes have resumed and students are studying abroad, the rationale for doing COIL is not always clear amongst educators and students. Also, the logistics of COIL become increasingly complicated when participants involved in a potential collaboration have different second language (L2) learning goals. In this paper, the researcher will report on a study involving two bilingual, cross-cultural COIL courses between students at a university in Japan and those studying in North America, from April to December, 2022. The students in Japan were enrolled in an intercultural communication class in their L2 of English, while the students in Canada and the United States were studying intermediate Japanese as their L2. Based on a qualitative survey and journaling data received from 31 students in Japan, and employing a transcendental phenomenological research design, the researcher will highlight the students’ essence of experience during COIL. Essentially, students benefited from the experience through improved communicative competences and increased knowledge of the target culture, even when the L2 learning goals between institutions differed. Students also reported that the COIL experience was effective in preparation for actual study abroad, as opposed to a replacement for it, which challenges the existing literature. Both educators and administrators will be exposed to the perceptions of Japanese university students towards COIL, which could be generalized to other higher education contexts, including those in Southeast Asia. Readers will also be exposed to ideas for developing more effective pre-departure study abroad programs and domestic intercultural curriculum through COIL, even when L2 learning goals may differ between participants.Keywords: collaborative online international learning, study abroad, phenomenology, EdTech, intercultural communication
Procedia PDF Downloads 745797 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 2525796 Predicting Timely Delivery of Humanitarian Supplies Using Machine Learning Techniques
Authors: Mohammad Alshehri, Fahd Alfarsi
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Efficient supply chains play an essential role in delivering humanitarian supplies and directly impact the success of public aid initiatives globally. Predicting the delivery status of these essential supplies in a timely manner is crucial. Therefore, this study explores the application of various machine learning approaches to predict whether humanitarian deliveries will be made on time, using a comprehensive case-study dataset provided by one of the largest international supplying organisations. We employed several machine learning methods such as regression-based (e.g., logistics regression), tree-based (e.g., decision trees) and ensemble-based (e.g., AdaBoost, XGBoost, and Gradient Boosting) to develop our predictive model. Our findings demonstrate that ensemble algorithms achieved promising results, with F1 scores ranging from 0.90 to 0.98. These high accuracy levels indicate the robustness of ensemble-learning techniques in forecasting delivery status, potentially enabling more proactive and efficient supply chain management in global aid initiatives. The implications of this study suggest that integrating advanced predictive analytics can significantly enhance the reliability of supply chains, ensuring the timely delivery of critical commodities to those in need.Keywords: humanitarian aids, supply chains, machine learning, delivery status
Procedia PDF Downloads 125795 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 645794 Learning to Translate by Learning to Communicate to an Entailment Classifier
Authors: Szymon Rutkowski, Tomasz Korbak
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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning
Procedia PDF Downloads 1195793 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 5345792 The Effect of an Al Andalus Fused Curriculum Model on the Learning Outcomes of Elementary School Students
Authors: Sobhy Fathy A. Hashesh
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The study was carried out in the Elementary Classes of Andalus Private Schools, girls section using control and experimental groups formed by Random Assignment Strategy. The study aimed at investigating the effect of Al-Andalus Fused Curriculum (AFC) model of learning and the effect of separate subjects’ approach on the development of students’ conceptual learning and skills acquiring. The society of the study composed of Al-Andalus Private Schools, elementary school students, Girls Section (N=240), while the sample of the study composed of two randomly assigned groups (N=28) with one experimental group and one control group. The study followed the quantitative and qualitative approaches in collecting and analyzing data to investigate the study hypotheses. Results of the study revealed that there were significant statistical differences between students’ conceptual learning and skills acquiring for the favor of the experimental group. The study recommended applying this model on different educational variables and on other age groups to generate more data leading to more educational results for the favor of students’ learning outcomes.Keywords: AFC, STEAM, lego education, Al-Andalus fused curriculum, mechatronics
Procedia PDF Downloads 2095791 Students’ learning Effects in Physical Education between Sport Education Model with TPSR and Traditional Teaching Model with TPSR
Authors: Yi-Hsiang Pan, Chen-Hui Huang, Ching-Hsiang Chen, Wei-Ting Hsu
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The purposes of the study were to explore the students' learning effect of physical education curriculum between merging Teaching Personal and Social Responsibility (TPSR) with sport education model and TPSR with traditional teaching model, which these learning effects included sport self-efficacy, sport enthusiastic, group cohesion, responsibility and game performance. The participants include 3 high school physical education teachers and 6 physical education classes, 133 participants with experience group 75 students and control group 58 students, and each teacher taught an experimental group and a control group for 16 weeks. The research methods used questionnaire investigation, interview, focus group meeting. The research instruments included personal and social responsibility questionnaire, sport enthusiastic scale, group cohesion scale, sport self-efficacy scale and game performance assessment instrument. Multivariate Analysis of covariance and Repeated measure ANOVA were used to test difference of students' learning effects between merging TPSR with sport education model and TPSR with traditional teaching model. The findings of research were: 1) The sport education model with TPSR could improve students' learning effects, including sport self-efficacy, game performance, sport enthusiastic, group cohesion and responsibility. 2) The traditional teaching model with TPSR could improve students' learning effect, including sport self-efficacy, responsibility and game performance. 3) the sport education model with TPSR could improve more learning effects than traditional teaching model with TPSR, including sport self-efficacy, sport enthusiastic,responsibility and game performance. 4) Based on qualitative data about learning experience of teachers and students, sport education model with TPSR significant improve learning motivation, group interaction and game sense. The conclusions indicated sport education model with TPSR could improve more learning effects in physical education curriculum. On other hand, the curricular projects of hybrid TPSR-Sport Education model and TPSR-Traditional Teaching model are both good curricular projects of moral character education, which may be applied in school physical education.Keywords: character education, sport season, game performance, sport competence
Procedia PDF Downloads 4365790 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 3045789 An Empirical Evaluation of Performance of Machine Learning Techniques on Imbalanced Software Quality Data
Authors: Ruchika Malhotra, Megha Khanna
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The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.Keywords: change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics
Procedia PDF Downloads 4125788 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 1365787 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 5755786 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 4195785 Visualization-Based Feature Extraction for Classification in Real-Time Interaction
Authors: Ágoston Nagy
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This paper introduces a method of using unsupervised machine learning to visualize the feature space of a dataset in 2D, in order to find most characteristic segments in the set. After dimension reduction, users can select clusters by manual drawing. Selected clusters are recorded into a data model that is used for later predictions, based on realtime data. Predictions are made with supervised learning, using Gesture Recognition Toolkit. The paper introduces two example applications: a semantic audio organizer for analyzing incoming sounds, and a gesture database organizer where gestural data (recorded by a Leap motion) is visualized for further manipulation.Keywords: gesture recognition, machine learning, real-time interaction, visualization
Procedia PDF Downloads 3385784 Effectiveness of Reinforcement Learning (RL) for Autonomous Energy Management Solutions
Authors: Tesfaye Mengistu
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This thesis aims to investigate the effectiveness of Reinforcement Learning (RL) for Autonomous Energy Management solutions. The study explores the potential of Model Free RL approaches, such as Monte Carlo RL and Q-learning, to improve energy management by autonomously adjusting energy management strategies to maximize efficiency. The research investigates the implementation of RL algorithms for optimizing energy consumption in a single-agent environment. The focus is on developing a framework for the implementation of RL algorithms, highlighting the importance of RL for enabling autonomous systems to adapt quickly to changing conditions and make decisions based on previous experiences. Moreover, the paper proposes RL as a novel energy management solution to address nations' CO2 emission goals. Reinforcement learning algorithms are well-suited to solving problems with sequential decision-making patterns and can provide accurate and immediate outputs to ease the planning and decision-making process. This research provides insights into the challenges and opportunities of using RL for energy management solutions and recommends further studies to explore its full potential. In conclusion, this study provides valuable insights into how RL can be used to improve the efficiency of energy management systems and supports the use of RL as a promising approach for developing autonomous energy management solutions in residential buildings.Keywords: artificial intelligence, reinforcement learning, monte carlo, energy management, CO2 emission
Procedia PDF Downloads 735783 Comparison Learning Vocabulary Implicitly and Explicitly
Authors: Akram Hashemi
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This study provided an empirical evidence for learners of elementary level of language proficiency to investigate the potential role of contextualization in vocabulary learning. Prior to the main study, pilot study was performed to determine the reliability and validity of the researcher-made pretest and posttest. After manifesting the homogeneity of the participants, the participants (n = 90) were randomly assigned into three equal groups, i.e., two experimental groups and a control group. They were pretested by a vocabulary test, in order to test participants' pre-knowledge of vocabulary. Then, vocabulary instruction was provided through three methods of visual instruction, the use of context and the use of conventional techniques. At the end of the study, all participants took the same posttest in order to assess their vocabulary gain. The results of independent sample t-test indicated that there is a significant difference between learning vocabulary visually and learning vocabulary contextually. The results of paired sample t-test showed that different teaching strategies have significantly different impacts on learners’ vocabulary gains. Also, the contextual strategy was significantly more effective than visual strategy in improving students’ performance in vocabulary test.Keywords: vocabulary instruction, explicit instruction, implicit instruction, strategy
Procedia PDF Downloads 3245782 Estimating Gait Parameter from Digital RGB Camera Using Real Time AlphaPose Learning Architecture
Authors: Murad Almadani, Khalil Abu-Hantash, Xinyu Wang, Herbert Jelinek, Kinda Khalaf
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Gait analysis is used by healthcare professionals as a tool to gain a better understanding of the movement impairment and track progress. In most circumstances, monitoring patients in their real-life environments with low-cost equipment such as cameras and wearable sensors is more important. Inertial sensors, on the other hand, cannot provide enough information on angular dynamics. This research offers a method for tracking 2D joint coordinates using cutting-edge vision algorithms and a single RGB camera. We provide an end-to-end comprehensive deep learning pipeline for marker-less gait parameter estimation, which, to our knowledge, has never been done before. To make our pipeline function in real-time for real-world applications, we leverage the AlphaPose human posture prediction model and a deep learning transformer. We tested our approach on the well-known GPJATK dataset, which produces promising results.Keywords: gait analysis, human pose estimation, deep learning, real time gait estimation, AlphaPose, transformer
Procedia PDF Downloads 1115781 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 3255780 Computer Assisted Learning Module (CALM) for Consumer Electronics Servicing
Authors: Edicio M. Faller
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The use of technology in the delivery of teaching and learning is vital nowadays especially in education. Computer Assisted Learning Module (CALM) software is the use of computer in the delivery of instruction with a tailored fit program intended for a specific lesson or a set of topics. The CALM software developed in this study is intended to supplement the traditional teaching methods in technical-vocational (TECH-VOC) instruction specifically the Consumer Electronics Servicing course. There are three specific objectives of this study. First is to create a learning enhancement and review materials on the selected lessons. Second, is to computerize the end-of-chapter quizzes. Third, is to generate a computerized mock exam and summative assessment. In order to obtain the objectives of the study the researcher adopted the Agile Model where the development of the study undergoes iterative and incremental process of the Software Development Life Cycle. The study conducted an acceptance testing using a survey questionnaire to evaluate the CALM software. The results showed that CALM software was generally interpreted as very satisfactory. To further improve the CALM software it is recommended that the program be updated, enhanced and lastly, be converted from stand-alone to a client/server architecture.Keywords: computer assisted learning module, software development life cycle, computerized mock exam, consumer electronics servicing
Procedia PDF Downloads 383