Search results for: learning through movement

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

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Authors: Suhani Srivastava

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This research delves into the classification of orbital debris through machine learning (ML): it will categorize the intensity of the threat orbital debris poses through multiple ML models to gain an insight into effectively estimating the danger specific orbital debris can pose to future space missions. As the space industry expands, orbital debris becomes a growing concern in Low Earth Orbit (LEO) because it can potentially obfuscate space missions due to the increased orbital debris pollution. Moreover, detecting orbital debris and identifying its characteristics has become a major concern in Space Situational Awareness (SSA), and prior methods of solely utilizing physics can become inconvenient in the face of the growing issue. Thus, this research focuses on approaching orbital debris concerns through machine learning, an efficient and more convenient alternative, in detecting the potential threat certain orbital debris pose. Our findings found that the Logistic regression machine worked the best with a 98% accuracy and this research has provided insight into the accuracies of specific machine learning models when classifying orbital debris. Our work would help provide space shuttle manufacturers with guidelines about mitigating risks, and it would help in providing Aerospace Engineers facilities to identify the kinds of protection that should be incorporated into objects traveling in the LEO through the predictions our models provide.

Keywords: aerospace, orbital debris, machine learning, space, space situational awareness, nasa

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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 260

Authors: F. A. Thomas, M. Schrafl-Altermatt, R. Treier, S. Kaufmann

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Stroke is the main cause of adult disability. Especially upper limb function is affected in most patients. Recently, cooperative hand movements have been shown to be a promising type of upper limb training in stroke rehabilitation. In these movements, which are frequently found in activities of daily living (e.g. opening a bottle, winding up a blind), the force of one upper limb has to be equally counteracted by the other limb to successfully accomplish a task. The use of standardized and reliable clinical assessments is essential to evaluate the efficacy of therapy and the functional outcome of a patient. Many assessments for upper limb function or impairment are available. However, the evaluation of cooperative hand movement tasks are rarely included in those. Thus, the aim of this study was (i) to develop a novel clinical assessment (CASA - Cooperative Activity Stroke Assessment) for the evaluation of patients’ capacity to perform cooperative hand movements and (ii) to test its inter- and interrater reliability. Furthermore, CASA scores were compared to current gold standard assessments for upper extremity in stroke patients (i.e. Fugl-Meyer Assessment, Box & Blocks Test). The CASA consists of five cooperative activities of daily living including (1) opening a jar, (2) opening a bottle, (3) open and closing of a zip, (4) unscrew a nut and (5) opening a clipbox. Here, the goal is to accomplish the tasks as fast as possible. In addition to the quantitative rating (i.e. time) which is converted to a 7-point scale, also the quality of the movement is rated in a 4-point scale. To test the reliability of CASA, fifteen stroke subjects were tested within a week twice by the same two raters. Intra-and interrater reliability was calculated using the intraclass correlation coefficient (ICC) for total CASA score and single items. Furthermore, Pearson-correlation was used to compare the CASA scores to the scores of Fugl-Meyer upper limb assessment and the box and blocks test, which were assessed in every patient additionally to the CASA. ICC scores of the total CASA score indicated an excellent- and single items established a good to excellent inter- and interrater reliability. Furthermore, the CASA score was significantly correlated to the Fugl-Meyer and Box & Blocks score. The CASA provides a reliable assessment for cooperative hand movements which are crucial for many activities of daily living. Due to its non-costly setup, easy and fast implementation, we suggest it to be well suitable for clinical application. In conclusion, the CASA is a useful tool in assessing the functional status and therapy related recovery in cooperative hand movement capacity in stroke patients.

Keywords: activitites of daily living, clinical assessment, cooperative hand movements, reliability, stroke

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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

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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

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Authors: Prathik Ranka, Sridhar K, Vasanth Daniel, Mithun Shankar

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With growing global food needs and climate uncertainties, informed crop choices are critical for increasing agricultural productivity. Here we propose a machine learning-based crop recommendation system to help farmers in choosing the most proper crops according to their geographical regions and soil properties. We can deploy algorithms like Decision Trees, Random Forests and Support Vector Machines on a broad dataset that consists of climatic factors, soil characteristics and historical crop yields to predict the best choice of crops. The approach includes first preprocessing the data after assessing them for missing values, unlike in previous jobs where we used all the available information and then transformed because there was no way such a model could have worked with missing data, and normalizing as throughput that will be done over a network to get best results out of our machine learning division. The model effectiveness is measured through performance metrics like accuracy, precision and recall. The resultant app provides a farmer-friendly dashboard through which farmers can enter their local conditions and receive individualized crop suggestions.

Keywords: crop recommendation, precision agriculture, crop, machine learning

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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

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Authors: Sifan Guo, Xuesen Zheng

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Visitors as the vital research group have been mentioned in high frequency in the field of museum studies. With the rise of the New Museology Movement, new challenges in the museum appeared, ranging from how to eliminate the cliché class prejudices in museums to how to make visitor-oriented museums more welcome. In line with this new situation, to create a successful visiting experience is the focus of museums in today. National museums as tourist attractions always attract flooded attention, however the local museums may have the different situations. The residents could be one of the main visitors to the local museums how to attract them returned should be considered here. There are various people with different cultural, education and religion backgrounds, it is necessary to keep the balance of the education and entertainment to reach visitors’ expectations. Regarding these questions, a mixed methods research approach has been adopted: observations, tracking and questionnaires. Based on analysing some museums’ cases in the UK, it can be argued that: 1) Audiences’ accessibility support their options and judgments during the visiting. 2) Highly inclusive architecture and narrative expressions could encourage the visitors to proceed deeply understanding and alleviate conflicts. In addition, the main characteristics of the local museums and the interlinks between museums and urban renaissance will be clarified. The conclusion informs not only practical suggestions for reachable characteristic design, but also potential future research subjects.

Keywords: accessibility, challenging visitors, new museology movement, visiting experience

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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

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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

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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 307

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

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Authors: Jinshou Shi, Xiaozhou Zhou, Yingwei Zhou, Tuoyang Zhou, Ning Li, Chi Zhang, Zhanshuo Zhang, Ziang Chen

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In order to select the optimal interaction method for common computer click tasks, the click experiment test adopts the ISO 9241-9 task paradigm, using four common operations: mouse, trackball, touch, and eye control under visual feedback, auditory feedback, and no feedback. Through data analysis of various parameters of movement time, throughput, and accuracy, it is found that the movement time of touch-control is the shortest, the operation accuracy and throughput are higher than others, and the overall operation performance is the best. In addition, the motion time of the click operation with auditory feedback is significantly lower than the other two feedback methods in each operation mode experiment. In terms of the size of the click target, it is found that when the target is too small (less than 14px), the click performance of all aspects is reduced, so it is proposed that the design of the interface button should not be less than 28px. In this article, we discussed in detail the advantages and disadvantages of the operation and feedback methods, and the results of the discussion of the click operation can be applied to the design of the buttons in the interactive interface.

Keywords: cursor control performance, feedback, human computer interaction, throughput

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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

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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

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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 585

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

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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

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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

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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

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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

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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

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Authors: K. K. A. Bakhti, D. Mottet, J. Froger, I. Laffont

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Background: After a cerebrovascular accident (or stroke), many patients use excessive trunk movements to move their paretic hand towards a target (while the elbow is maintained flexed) even though they can use the upper-limb when the trunk is restrained. This phenomenon is labelled learned non-use and is known to be detrimental to neuroplasticity and recovery. Objective: The aim of this study is to quantify learned non-use of the paretic upper limb during a hand reaching task using 3D movement analysis. Methods: Thirty-four participants post supratentorial stroke were asked to reach a cone placed in front of them at 80% of their arm length. The reaching movement was repeated 5 times with the paretic hand, and then 5 times with the less-impaired hand. This sequence was first performed with the trunk free, then with the trunk restrained. Learned non-use of the upper-limb (LNUUL) was obtained from the difference of the amount of trunk compensation between the free trunk condition and the restrained trunk condition. Results: LNUUL was significantly higher for the paretic hand, with individual values ranging from 1% to 43%, and one-half of the patients with an LNUUL higher than 15%. Conclusions: Quantification of LNUUL can be used to objectively diagnose patients who need trunk rehabilitation. It can be also used for monitoring the rehabilitation progress. Quantification of LNUUL may guide upper-limb rehabilitation towards more optimal motor recovery avoiding maladaptive trunk compensation and its consequences on neuroplasticity.

Keywords: learned non-use, rehabilitation, stroke, upper limb

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Authors: Shayan Mohajer Hamidi

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Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

Procedia PDF Downloads 75

Authors: Ahmed Makhoukh

Abstract:

Quality assurance (QA) has recently become a common practice, which is endorsed by most Higher Education (HE) institutions worldwide, due to the pressure of internal and external forces. One of the aims of this quality movement is to make the contribution of university education to socio-economic development highly significant. This entails that graduates are currently required have a high-quality profile, i.e., to be competent and master the 21st-century skills needed in the labor market. This wave of change, mostly imposed by globalization, has the effect that university education should be learner-centered in order to satisfy the different needs of students and meet the expectations of other stakeholders. Such a shift of focus on the student learning outcomes has led HE institutions to reconsider their strategic planning, their mission, the curriculum, the pedagogical competence of the academic staff, among other elements. To ensure that the overall institutional performance is on the right way, a QA system should be established to assume this task of checking regularly the extent to which the set of standards of evaluation are strictly respected as expected. This operation of QA has the advantage of proving the accountability of the institution, gaining the trust of the public with transparency and enjoying an international recognition. This is the case of Doha Institute (DI) for Graduate Studies, in Qatar, the object of the present study. The significance of this contribution is to show that the conception of quality has changed in this digital age, and the need to integrate a department responsible for QA in every HE institution to ensure educational quality, enhance learners and achieve academic leadership. Thus, to undertake the issue of QA in DI for Graduate Studies, an elite university (in the academic sense) that focuses on a small and selected number of students, a qualitative method will be adopted in the description and analysis of the data (document analysis). In an attempt to investigate the extent to which QA is achieved in Doha Institute for Graduate Studies, three broad indicators will be evaluated (input, process and learning outcomes). This investigation will be carried out in line with the UK Quality Code for Higher Education represented by Quality Assurance Agency (QAA).

Keywords: accreditation, higher education, quality, quality assurance, standards

Procedia PDF Downloads 147

Authors: Ira Slabodar

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Autonomous learning in English as a Foreign Language (EFL) refers to the use of target language, learner collaboration and students’ responsibility for their learning. Teachers play a vital role of mediators and facilitators in self-regulated method. Thus, their perception of self-guided practices dictates their implementation of this approach. While research has predominantly focused on inadequate administration of autonomous learning in school mostly due to lack of appropriate teacher training, this study examined whether novice teachers who were exposed to extensive autonomous practices were likely to implement this method in their teaching. Twelve novice teachers were interviewed to examine their perception of learner autonomy and their administration of this method. It was found that three-thirds of the respondents experienced a gap between familiarity with autonomous learning and a favorable attitude to this approach and their deficient integration of self-directed learning. Although learner-related and institution-oriented factors played a role in this gap, it was mostly caused by the respondents’ not being genuinely autonomous. This may be due to indirect exposure rather than explicit introduction of the learner autonomy approach. The insights of this research may assist curriculum designers and heads of teacher training programs to rethink course composition to guarantee the transfer of methodologies into EFL classes.

Keywords: learner autonomy, teacher training, english as a foreign language (efl), genuinely autonomous teachers, explicit instruction, self-determination theory

Procedia PDF Downloads 58

Authors: Nolvi Francisco Baggio Filho, Roniele Belusso

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Many industrial processes require a precise linear motion. Usually, this movement is achieved with the use of rotary motors combined with electrical control systems and mechanical systems such as gears, pulleys and bearings. Other types of devices are based on linear motors, where the linear motion is obtained directly. The Linear Stepper Motor (MLP) is an excellent solution for industrial applications that require precise positioning and high speed. This study presents an MLP formed by a linear structure and static ferromagnetic material, and a mover structure in which three coils are mounted. Mechanical suspension systems allow a linear movement between static and mover parts, maintaining a constant air gap. The operating principle is based on the tendency of alignment of magnetic flux through the path of least reluctance. The force proportional to the intensity of the electric current and the speed proportional to the frequency of the excitation coils. The study of this device is still based on the use of a numerical and experimental analysis to verify the relationship among electric current applied and planar force developed. In addition, the magnetic field in the air gap region is also monitored.

Keywords: linear stepper motor, planar traction force, reluctance magnetic, industry applications

Procedia PDF Downloads 500

Authors: Mihail Calalb

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The aim of this research is to identify ways for achieving sustainable conceptual understanding within science lessons. For this purpose, a set of teaching and learning strategies, parts of the theory of visible teaching and learning (VTL), is studied. As a result, a new didactic approach named "learning by being" is proposed and its correlation with educational paradigms existing nowadays in science teaching domain is analysed. In the context of VTL the author describes the main strategies of "learning by being" such as guided self-scaffolding, structuring of information, and recurrent use of previous knowledge or help seeking. Due to the synergy effect of these learning strategies applied simultaneously in class, the impact factor of learning by being on cognitive achievement of students is up to 93 % (the benchmark level is equal to 40% when an experienced teacher applies permanently the same conventional strategy during two academic years). The key idea in "learning by being" is the assumption by the student of cognitive goals. From this perspective, the article discusses the role of student’s personal learning effort within several teaching strategies employed in VTL. The research results emphasize that three mandatory student – related moments are present in each constructivist teaching approach: a) students’ personal learning effort, b) student – teacher mutual feedback and c) metacognition. Thus, a successful educational strategy will target to achieve an involvement degree of students into the class process as high as possible in order to make them not only know the learning objectives but also to assume them. In this way, we come to the ownership of cognitive goals or students’ deep intrinsic motivation. A series of approaches are inherent to the students’ ownership of cognitive goals: independent research (with an impact factor on cognitive achievement equal to 83% according to the results of VTL); knowledge of success criteria (impact factor – 113%); ability to reveal similarities and patterns (impact factor – 132%). Although it is generally accepted that the school is a public service, nonetheless it does not belong to entertainment industry and in most of cases the education declared as student – centered actually hides the central role of the teacher. Even if there is a proliferation of constructivist concepts, mainly at the level of science education research, we have to underline that conventional or frontal teaching, would never disappear. Research results show that no modern method can replace an experienced teacher with strong pedagogical content knowledge. Such a teacher will inspire and motivate his/her students to love and learn physics. The teacher is precisely the condensation point for an efficient didactic strategy – be it constructivist or conventional. In this way, we could speak about "hybridized teaching" where both the student and the teacher have their share of responsibility. In conclusion, the core of "learning by being" approach is guided learning effort that corresponds to the notion of teacher–student harmonic oscillator, when both things – guidance from teacher and student’s effort – are equally important.

Keywords: conceptual understanding, learning by being, ownership of cognitive goals, science learning

Procedia PDF Downloads 167

Authors: Justine Jun

Abstract:

This study aims to reveal migrant women English instructors' workplace learning experiences in Canadian post-secondary institutions in Ontario. Although many scholars have conducted research studies on internationally educated teachers and their professional and employment challenges, few studies have recorded migrant women English language instructors’ professional learning and support experiences in post-secondary English language programs in Canada. This study employs a qualitative research paradigm. Mezirow’s Transformative Learning Theory is an essential lens for the researcher to explain, analyze, and interpret the research data. It is a collaborative research project. The researcher and participants cooperatively create photographic or other artwork data responding to the research questions. Photovoice and arts-informed data collection methodology are the main methods. Research participants engage in the study as co-researchers and inquire about their own workplace learning experiences, actively utilizing their critical self-reflective and dialogic skills. Co-researchers individually select the forms of artwork they prefer to engage with to represent their transformative workplace learning experiences about the Canadian workplace cultures that they underwent while working with colleagues and administrators in the workplace. Once the co-researchers generate their cultural artifacts as research data, they collaboratively interpret their artworks with the researcher and other volunteer co-researchers. Co-researchers jointly investigate the themes emerging from the artworks. They also interpret the meanings of their own and others’ workplace learning experiences embedded in the artworks through interactive one-on-one or group interviews. The following are the research questions that the migrant women English instructor participants examine and answer: (1) What have they learned about their workplace culture and how do they explain their learning experiences?; (2) How transformative have their learning experiences been at work?; (3) How have their colleagues and administrators influenced their transformative learning?; (4) What kind of support have they received? What supports have been valuable to them and what changes would they like to see?; (5) What have their learning experiences transformed?; (6) What has this arts-informed research process transformed? The study findings implicate English language instructor support currently practiced in post-secondary English language programs in Ontario, Canada, especially for migrant women English instructors. This research is a doctoral empirical study in progress. This research has the urgency to address the research problem that few studies have investigated migrant English instructors’ professional learning and support issues in the workplace, precisely that of English instructors working with adult learners in Canada. While appropriate social and professional support for migrant English instructors is required throughout the country, the present workplace realities in Ontario's English language programs need to be heard soon. For that purpose, the conceptualization of this study is crucial. It makes the investigation of under-represented instructors’ under-researched social phenomena, workplace learning and support, viable and rigorous. This paper demonstrates the robust theorization of English instructors’ workplace experiences using Mezirow’s Transformative Learning Theory in the English language teacher education field.

Keywords: English teacher education, professional learning, transformative learning theory, workplace learning

Procedia PDF Downloads 129