Search results for: unsupervised machine learning.
6329 A Multi-Agent Urban Traffic Simulator for Generating Autonomous Driving Training Data
Authors: Florin Leon
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This paper describes a simulator of traffic scenarios tailored to facilitate autonomous driving model training for urban environments. With the rising prominence of self-driving vehicles, the need for diverse datasets is very important. The proposed simulator provides a flexible framework that allows the generation of custom scenarios needed for the validation and enhancement of trajectory prediction algorithms. Its controlled yet dynamic environment addresses the challenges associated with real-world data acquisition and ensures adaptability to diverse driving scenarios. By providing an adaptable solution for scenario creation and algorithm testing, this tool proves to be a valuable resource for advancing autonomous driving technology that aims to ensure safe and efficient self-driving vehicles.Keywords: autonomous driving, car simulator, machine learning, model training, urban simulation environment
Procedia PDF Downloads 466328 Multi-Objectives Genetic Algorithm for Optimizing Machining Process Parameters
Authors: Dylan Santos De Pinho, Nabil Ouerhani
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Energy consumption of machine-tools is becoming critical for machine-tool builders and end-users because of economic, ecological and legislation-related reasons. Many machine-tool builders are seeking for solutions that allow the reduction of energy consumption of machine-tools while preserving the same productivity rate and the same quality of machined parts. In this paper, we present the first results of a project conducted jointly by academic and industrial partners to reduce the energy consumption of a Swiss-Type lathe. We employ genetic algorithms to find optimal machining parameters – the set of parameters that lead to the best trade-off between energy consumption, part quality and tool lifetime. Three main machining process parameters are considered in our optimization technique, namely depth of cut, spindle rotation speed and material feed rate. These machining process parameters have been identified as the most influential ones in the configuration of the Swiss-type machining process. A state-of-the-art multi-objective genetic algorithm has been used. The algorithm combines three fitness functions, which are objective functions that permit to evaluate a set of parameters against the three objectives: energy consumption, quality of the machined parts, and tool lifetime. In this paper, we focus on the investigation of the fitness function related to energy consumption. Four different energy consumption related fitness functions have been investigated and compared. The first fitness function refers to the Kienzle cutting force model. The second fitness function uses the Material Removal Rate (RMM) as an indicator of energy consumption. The two other fitness functions are non-deterministic, learning-based functions. One fitness function uses a simple Neural Network to learn the relation between the process parameters and the energy consumption from experimental data. Another fitness function uses Lasso regression to determine the same relation. The goal is, then, to find out which fitness functions predict best the energy consumption of a Swiss-Type machining process for the given set of machining process parameters. Once determined, these functions may be used for optimization purposes – determine the optimal machining process parameters leading to minimum energy consumption. The performance of the four fitness functions has been evaluated. The Tornos DT13 Swiss-Type Lathe has been used to carry out the experiments. A mechanical part including various Swiss-Type machining operations has been selected for the experiments. The evaluation process starts with generating a set of CNC (Computer Numerical Control) programs for machining the part at hand. Each CNC program considers a different set of machining process parameters. During the machining process, the power consumption of the spindle is measured. All collected data are assigned to the appropriate CNC program and thus to the set of machining process parameters. The evaluation approach consists in calculating the correlation between the normalized measured power consumption and the normalized power consumption prediction for each of the four fitness functions. The evaluation shows that the Lasso and Neural Network fitness functions have the highest correlation coefficient with 97%. The fitness function “Material Removal Rate” (MRR) has a correlation coefficient of 90%, whereas the Kienzle-based fitness function has a correlation coefficient of 80%.Keywords: adaptive machining, genetic algorithms, smart manufacturing, parameters optimization
Procedia PDF Downloads 1416327 Enabling Translanguaging in the EFL Classroom, Affordances of Learning and Reflections
Authors: Nada Alghali
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Translanguaging pedagogy suggests a new perspective in language education relating to multilingualism; multilingual learners have one linguistic repertoire and not two or more separate language systems (García and Wei, 2014). When learners translanguage, they are able to draw on all their language features in a flexible and integrated way (Otheguy, García, & Reid, 2015). In the Foreign Language Classroom, however, the tendency to use the target language only is still advocated as a pedagogy. This study attempts to enable learners in the English as a foreign language classroom to draw on their full linguistic repertoire through collaborative reading lessons. In observations prior to this study, in a classroom where English only policy prevails, learners still used their first language in group discussions yet were constrained at times by the teacher’s language policies. Through strategically enabling translanguaging in reading lessons (Celic and Seltzer, 2011), this study has revealed that learners showed creative ways of language use for learning and reflected positively on thisexperience. This case study enabled two groups in two different proficiency level classrooms who are learning English as a foreign language in their first year at University in Saudi Arabia. Learners in the two groups wereobserved over six weeks and wereasked to reflect their learning every week. The same learners were also interviewed at the end of translanguaging weeks after completing a modified model of the learning reflection (Ash and Clayton, 2009). This study positions translanguaging as collaborative and agentive within a sociocultural framework of learning, positioning translanguaging as a resource for learning as well as a process of learning. Translanguaging learning episodes are elicited from classroom observations, artefacts, interviews, reflections, and focus groups, where they are analysed qualitatively following the sociocultural discourse analysis (Fairclough &Wodak, 1997; Mercer, 2004). Initial outcomes suggest functions of translanguaging in collaborative reading tasks and recommendations for a collaborative translanguaging pedagogy approach in the EFL classroom.Keywords: translanguaging, EFL, sociocultural theory, discourse analysis
Procedia PDF Downloads 1706326 A Collaborative, Arts-Informed Action Research Investigation of Child-Led Assessment
Authors: Dragana Gnjatovic
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Assessment is a burning topic in education policy and practice due to measurement-driven neoliberal agendas of quality and standardisation of assessment practice through high stakes standardised testing systems that are now influencing early childhood education. This paper presents a collaborative, arts-informed action research project which places children at the centre of their learning, with assessment as an integral part of play-based learning processes. It aims to challenge traditional approaches to assessment that are often teacher-led and decontextualised from the processes of learning through exploring approaches where children's voices are central, and their creative arts expressions are used to assess learning and development. The theoretical framework draws on Vygotsky's sociocultural theory and Freire's critical pedagogy, which indicate the importance of socially constructed reality where knowledge is the result of collaboration between children and adults. This reality perceives children as competent agents of their own learning processes. An interpretive-constructivist and critical-transformative paradigm underpin collaborative action research in a three to five-year-old setting, where creative methods like storytelling, play, drama, drawing are used to assess children's learning. As data collection and analysis are still in process, this paper will present the methodology and some data vignettes, with the aim of stimulating discussion about innovation in assessment and contribution of the collaborative enquiry in the field of Early Childhood Education and Care.Keywords: assessment for learning, creative methodologies, collaborative action research, early childhood education and care
Procedia PDF Downloads 1276325 Green Thumb Engineering - Explainable Artificial Intelligence for Managing IoT Enabled Houseplants
Authors: Antti Nurminen, Avleen Malhi
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Significant progress in intelligent systems in combination with exceedingly wide application domains having machine learning as the core technology are usually opaque, non-intuitive, and commonly complex for human users. We use innovative IoT technology which monitors and analyzes moisture, humidity, luminosity and temperature levels to assist end users for optimization of environmental conditions for their houseplants. For plant health monitoring, we construct a system yielding the Normalized Difference Vegetation Index (NDVI), supported by visual validation by users. We run the system for a selected plant, basil, in varying environmental conditions to cater for typical home conditions, and bootstrap our AI with the acquired data. For end users, we implement a web based user interface which provides both instructions and explanations.Keywords: explainable artificial intelligence, intelligent agent, IoT, NDVI
Procedia PDF Downloads 1566324 Social Media Data Analysis for Personality Modelling and Learning Styles Prediction Using Educational Data Mining
Authors: Srushti Patil, Preethi Baligar, Gopalkrishna Joshi, Gururaj N. Bhadri
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In designing learning environments, the instructional strategies can be tailored to suit the learning style of an individual to ensure effective learning. In this study, the information shared on social media like Facebook is being used to predict learning style of a learner. Previous research studies have shown that Facebook data can be used to predict user personality. Users with a particular personality exhibit an inherent pattern in their digital footprint on Facebook. The proposed work aims to correlate the user's’ personality, predicted from Facebook data to the learning styles, predicted through questionnaires. For Millennial learners, Facebook has become a primary means for information sharing and interaction with peers. Thus, it can serve as a rich bed for research and direct the design of learning environments. The authors have conducted this study in an undergraduate freshman engineering course. Data from 320 freshmen Facebook users was collected. The same users also participated in the learning style and personality prediction survey. The Kolb’s Learning style questionnaires and Big 5 personality Inventory were adopted for the survey. The users have agreed to participate in this research and have signed individual consent forms. A specific page was created on Facebook to collect user data like personal details, status updates, comments, demographic characteristics and egocentric network parameters. This data was captured by an application created using Python program. The data captured from Facebook was subjected to text analysis process using the Linguistic Inquiry and Word Count dictionary. An analysis of the data collected from the questionnaires performed reveals individual student personality and learning style. The results obtained from analysis of Facebook, learning style and personality data were then fed into an automatic classifier that was trained by using the data mining techniques like Rule-based classifiers and Decision trees. This helps to predict the user personality and learning styles by analysing the common patterns. Rule-based classifiers applied for text analysis helps to categorize Facebook data into positive, negative and neutral. There were totally two models trained, one to predict the personality from Facebook data; another one to predict the learning styles from the personalities. The results show that the classifier model has high accuracy which makes the proposed method to be a reliable one for predicting the user personality and learning styles.Keywords: educational data mining, Facebook, learning styles, personality traits
Procedia PDF Downloads 2246323 Evaluating the Performance of Offensive Lineman in the National Football League
Authors: Nikhil Byanna, Abdolghani Ebrahimi, Diego Klabjan
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How does one objectively measure the performance of an individual offensive lineman in the NFL? The existing literature proposes various measures that rely on subjective assessments of game film, but has yet to develop an objective methodology to evaluate performance. Using a variety of statistics related to an offensive lineman’s performance, we develop a framework to objectively analyze the overall performance of an individual offensive lineman and determine specific linemen who are overvalued or undervalued relative to their salary. We identify eight players across the 2013-2014 and 2014-2015 NFL seasons that are considered to be overvalued or undervalued and corroborate the results with existing metrics that are based on subjective evaluation. To the best of our knowledge, the techniques set forth in this work have not been utilized in previous works to evaluate the performance of NFL players at any position, including offensive linemen.Keywords: offensive lineman, player performance, NFL, machine learning
Procedia PDF Downloads 1396322 Automatic Moment-Based Texture Segmentation
Authors: Tudor Barbu
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An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes
Procedia PDF Downloads 4126321 Winning the Future of Education in Africa through Project Base Learning: How the Implementation of PBL Pedagogy Can Transform Africa’s Educational System from Theory Base to Practical Base in School Curriculum
Authors: Bismark Agbemble
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This paper talks about how project-based learning (PBL) is being infused or implemented in the educational sphere of Africa. The paper navigates through the liminal aspects of PBL as a pedagogical approach to bridge the divide between theoretical knowledge and its application within school curriculums. Given that contextualized learning can be embodied, the abstract vehemently discusses that PBL creates an opportunity for students to work on projects that are of academic relevance in their local settings. It presents PBL’s growth of critical thinking, problem-solving, cooperation, and communications, which is vital in getting young citizens to prepare for the 21st-century revolution. In addition, the abstract stresses the possibility that PBL could become a stimulus to creativity and innovation wherein learning becomes motivated from within by intrinsic motivations. The paper advocates for a holistic approach that is based on teacher’s professional development with the provision of adequate infrastructural facilities and resource allocation, thus ensuring the success and sustainability of PBLs in African education systems. In the end, the paper positions this as a transformative educational methodology that has great potential in helping to shape an African generation that is prepared for a great future.Keywords: student centered pedagogy, constructivist learning theory, self-directed learning, active exploration, real world challenges, STEM, 21st century skills, curriculum design, classroom management, project base learning curriculum, global intelligence, social and communication skills, transferable skills, critical thinking, investigatable learning, life skills
Procedia PDF Downloads 486320 An Optimization of Machine Parameters for Modified Horizontal Boring Tool Using Taguchi Method
Authors: Thirasak Panyaphirawat, Pairoj Sapsmarnwong, Teeratas Pornyungyuen
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This paper presents the findings of an experimental investigation of important machining parameters for the horizontal boring tool modified to mouth with a horizontal lathe machine to bore an overlength workpiece. In order to verify a usability of a modified tool, design of experiment based on Taguchi method is performed. The parameters investigated are spindle speed, feed rate, depth of cut and length of workpiece. Taguchi L9 orthogonal array is selected for four factors three level parameters in order to minimize surface roughness (Ra and Rz) of S45C steel tubes. Signal to noise ratio analysis and analysis of variance (ANOVA) is performed to study an effect of said parameters and to optimize the machine setting for best surface finish. The controlled factors with most effect are depth of cut, spindle speed, length of workpiece, and feed rate in order. The confirmation test is performed to test the optimal setting obtained from Taguchi method and the result is satisfactory.Keywords: design of experiment, Taguchi design, optimization, analysis of variance, machining parameters, horizontal boring tool
Procedia PDF Downloads 4346319 Transformative Learning and the Development of Cultural Humility in Social Work Students
Authors: Ruilin Zhu, Katarzyna Olcoń, Rose M. Pulliam, Dorie J. Gilbert
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Cultural humility is increasingly important in social work literature, given its emphasis on mitigating power imbalances in helping relationships, particularly across cultural differences. Consequently, there is a need to understand whether and how cultural humility can be taught in social work education. Relying on ethnographic observations and reflective journals from a cultural immersion program, this study identified the learning process required to develop cultural humility: confusion and discomfort, re-moulding, and humility in action.Keywords: social work education, cultural humility, transformative learning theory, study abroad, ethnographic observations
Procedia PDF Downloads 1496318 Amazon and Its AI Features
Authors: Leen Sulaimani, Maryam Hafiz, Naba Ali, Roba Alsharif
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One of Amazon’s most crucial online systems is artificial intelligence. Amazon would not have a worldwide successful online store, an easy and secure way of payment, and other services if it weren’t for artificial intelligence and machine learning. Amazon uses AI to expand its operations and enhance them by upgrading the website daily; having a strong base of artificial intelligence in a worldwide successful business can improve marketing, decision-making, feedback, and more qualities. Aiming to have a rational AI system in one’s business should be the start of any process; that is why Amazon is fortunate that they keep taking care of the base of their business by using modern artificial intelligence, making sure that it is stable, reaching their organizational goals, and will continue to thrive more each and every day. Artificial intelligence is used daily in our current world and is still being amplified more each day to reach consumer satisfaction and company short and long-term goals.Keywords: artificial intelligence, Amazon, business, customer, decision making
Procedia PDF Downloads 986317 The Correspondence between Self-regulated Learning, Learning Efficiency and Frequency of ICT Use
Authors: Maria David, Tunde A. Tasko, Katalin Hejja-Nagy, Laszlo Dorner
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The authors have been concerned with research on learning since 1998. Recently, the focus of our interest is how prevalent use of information and communication technology (ICT) influences students' learning abilities, skills of self-regulated learning and learning efficiency. Nowadays, there are three dominant theories about the psychic effects of ICT use: According to social optimists, modern ICT devices have a positive effect on thinking. As to social pessimists, this effect is rather negative. And, regarding the views of biological optimists, the change is obvious, but these changes can fit into the mankind's evolved neurological system as did writing long ago. Mentality of 'digital natives' differ from that of elder people. They process information coming from the outside world in an other way, and different experiences result in different cerebral conformation. In this regard, researchers report about both positive and negative effects of ICT use. According to several studies, it has a positive effect on cognitive skills, intelligence, school efficiency, development of self-regulated learning, and self-esteem regarding learning. It is also proven, that computers improve skills of visual intelligence such as spacial orientation, iconic skills and visual attention. Among negative effects of frequent ICT use, researchers mention the decrease of critical thinking, as permanent flow of information does not give scope for deeper cognitive processing. Aims of our present study were to uncover developmental characteristics of self-regulated learning in different age groups and to study correlations of learning efficiency, the level of self-regulated learning and frequency of use of computers. Our subjects (N=1600) were primary and secondary school students and university students. We studied four age groups (age 10, 14, 18, 22), 400 subjects of each. We used the following methods: the research team developed a questionnaire for measuring level of self-regulated learning and a questionnaire for measuring ICT use, and we used documentary analysis to gain information about grade point average (GPA) and results of competence-measures. Finally, we used computer tasks to measure cognitive abilities. Data is currently under analysis, but as to our preliminary results, frequent use of computers results in shorter response time regarding every age groups. Our results show that an ordinary extent of ICT use tend to increase reading competence, and had a positive effect on students' abilities, though it didn't show relationship with school marks (GPA). As time passes, GPA gets worse along with the learning material getting more and more difficult. This phenomenon draws attention to the fact that students are unable to switch from guided to independent learning, so it is important to consciously develop skills of self-regulated learning.Keywords: digital natives, ICT, learning efficiency, reading competence, self-regulated learning
Procedia PDF Downloads 3536316 Envisioning The Future of Language Learning: Virtual Reality, Mobile Learning and Computer-Assisted Language Learning
Authors: Jasmin Cowin, Amany Alkhayat
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This paper will concentrate on a comparative analysis of both the advantages and limitations of using digital learning resources (DLRs). DLRs covered will be Virtual Reality (VR), Mobile Learning (M-learning) and Computer-Assisted Language Learning (CALL) together with their subset, Mobile Assisted Language Learning (MALL) in language education. In addition, best practices for language teaching and the application of established language teaching methodologies such as Communicative Language Teaching (CLT), the audio-lingual method, or community language learning will be explored. Education has changed dramatically since the eruption of the pandemic. Traditional face-to-face education was disrupted on a global scale. The rise of distance learning brought new digital tools to the forefront, especially web conferencing tools, digital storytelling apps, test authoring tools, and VR platforms. Language educators raced to vet, learn, and implement multiple technology resources suited for language acquisition. Yet, questions remain on how to harness new technologies, digital tools, and their ubiquitous availability while using established methods and methodologies in language learning paired with best teaching practices. In M-learning language, learners employ portable computing devices such as smartphones or tablets. CALL is a language teaching approach using computers and other technologies through presenting, reinforcing, and assessing language materials to be learned or to create environments where teachers and learners can meaningfully interact. In VR, a computer-generated simulation enables learner interaction with a 3D environment via screen, smartphone, or a head mounted display. Research supports that VR for language learning is effective in terms of exploration, communication, engagement, and motivation. Students are able to relate through role play activities, interact with 3D objects and activities such as field trips. VR lends itself to group language exercises in the classroom with target language practice in an immersive, virtual environment. Students, teachers, schools, language institutes, and institutions benefit from specialized support to help them acquire second language proficiency and content knowledge that builds on their cultural and linguistic assets. Through the purposeful application of different language methodologies and teaching approaches, language learners can not only make cultural and linguistic connections in DLRs but also practice grammar drills, play memory games or flourish in authentic settings.Keywords: language teaching methodologies, computer-assisted language learning, mobile learning, virtual reality
Procedia PDF Downloads 2276315 Design of Semi-Autonomous Street Cleaning Vehicle
Authors: Khouloud Safa Azoud, Süleyman Baştürk
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In the pursuit of cleaner and more sustainable urban environments, advanced technologies play a critical role in evolving sanitation systems. This paper presents two distinct advancements in automated cleaning machines designed to improve urban sanitation. The first advancement is a semi-automatic road surface cleaning machine that integrates human labor with solar energy to enhance environmental sustainability and adaptability, especially in regions with limited access to electricity. By reducing carbon emissions and increasing operational efficiency, this approach offers significant potential for urban sanitation enhancement. The second advancement is a multifunctional semi-automatic street cleaning machine equipped with a camera, Arduino programming, and GPS for an autonomous operation aimed at addressing cost barriers in developing countries. Prioritizing low energy consumption and cost-effectiveness, this machine provides versatile cleaning solutions adaptable to various environmental conditions. By integrating solar energy with autonomous operating systems and careful design, these developments represent substantial progress in sustainable urban sanitation, particularly in developing regions.Keywords: automated cleaning machines, solar energy integration, operational efficiency, urban sanitation systems
Procedia PDF Downloads 146314 Reinforcement Learning for Self Driving Racing Car Games
Authors: Adam Beaunoyer, Cory Beaunoyer, Mohammed Elmorsy, Hanan Saleh
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This research aims to create a reinforcement learning agent capable of racing in challenging simulated environments with a low collision count. We present a reinforcement learning agent that can navigate challenging tracks using both a Deep Q-Network (DQN) and a Soft Actor-Critic (SAC) method. A challenging track includes curves, jumps, and varying road widths throughout. Using open-source code on Github, the environment used in this research is based on the 1995 racing game WipeOut. The proposed reinforcement learning agent can navigate challenging tracks rapidly while maintaining low racing completion time and collision count. The results show that the SAC model outperforms the DQN model by a large margin. We also propose an alternative multiple-car model that can navigate the track without colliding with other vehicles on the track. The SAC model is the basis for the multiple-car model, where it can complete the laps quicker than the single-car model but has a higher collision rate with the track wall.Keywords: reinforcement learning, soft actor-critic, deep q-network, self-driving cars, artificial intelligence, gaming
Procedia PDF Downloads 366313 An Application of a Feedback Control System to Minimize Unforeseen Disruption in a Paper Manufacturing Industry in South Africa
Authors: Martha E. Ndeley
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Operation management is the key element within the manufacturing process. However, during this process, there are a number of unforeseen disruptions that causes the process to a standstill which are, machine breakdown, employees absenteeism, improper scheduling. When this happens, it forces the shop flow to a rescheduling process and these strategy reschedules only a limited part of the initial schedule to match up with the pre-schedule at some point with the objective to create a new schedule that is reliable which in the long run gets disrupted. In this work, we have developed feedback control system that minimizes any form of disruption before the impact becomes severe, the model was tested in a paper manufacturing industries and the results revealed that, if the disruption is minimized at the initial state, the impact becomes unnoticeable.Keywords: disruption, machine, absenteeism, scheduling
Procedia PDF Downloads 3016312 Learning Vocabulary with SkELL: Developing a Methodology with University Students in Japan Using Action Research
Authors: Henry R. Troy
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Corpora are becoming more prevalent in the language classroom, especially in the development of dictionaries and course materials. Nevertheless, corpora are still perceived by many educators as difficult to use directly in the classroom, a process which is also known as “data-driven learning” (DDL). Action research has been identified as a method by which DDL’s efficiency can be increased, but it is also an approach few studies on DDL have employed. Studies into the effectiveness of DDL in language education in Japan are also rare, and investigations focused more on student and teacher reactions rather than pre and post-test scores are rarer still. This study investigates the student and teacher reactions to the use of SkELL, a free online corpus designed to be user-friendly, for vocabulary learning at a university in Japan. Action research is utilized to refine the teaching methodology, with changes to the method based on student and teacher feedback received via surveys submitted after each of the four implementations of DDL. After some training, the students used tablets to study the target vocabulary autonomously in pairs and groups, with the teacher acting as facilitator. The results show that the students enjoyed using SkELL and felt it was effective for vocabulary learning, while the teaching methodology grew in efficiency throughout the course. These findings suggest that action research can be a successful method for increasing the efficacy of DDL in the language classroom, especially with teachers and students who are new to the practice.Keywords: action research, corpus linguistics, data-driven learning, vocabulary learning
Procedia PDF Downloads 2316311 Using Immersive Study Abroad Experiences to Strengthen Preservice Teachers’ Critical Reflection Skills on Future Classroom Practices
Authors: Meredith Jones, Susan Catapano, Carol McNulty
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Study abroad experiences create unique learning opportunities for preservice teachers to strengthen their reflective thinking practices through applied learning experiences. Not only do study abroad experiences provide opportunities for students to expand their cultural sensitivity, but incorporating applied learning experiences in study abroad trips creates unique opportunities for preservice teachers to engage in critical reflection on their teaching skills. Applied learning experiences are designed to nurture learning and growth through a reflective, experiential process outside the traditional classroom setting. As students participate in applied learning experiences, they engage in critical reflection independently, with their peers, and with university faculty. Critical reflection within applied learning contexts generates, deepens, and documents learning but must be intentionally designed to be effective. Grounded in Dewey’s model of reflection, this qualitative study examines longitudinal data from various study abroad cohorts from a particular university. Reflective data was collected during the study abroad trip, and follow up data on critical reflection of teaching practices were collected six months and a year after the trip. Dewey’s model of reflection requires preservice teachers to make sense of their experiences by reflecting on theoretical knowledge, experiences, and pedagogical knowledge. Guided reflection provides preservice teachers with a framework to respond to questions and ideas critical to the applied learning outcomes. Prompts are used to engage preservice teachers in reflecting on situations they have experienced and how they can be transferred to their teaching. Findings from this study noted that students with previous field experiences, or work in the field, engaged in more critical reflection on pedagogical knowledge throughout their applied learning experience. Preservice teachers with limited experiences in the field benefited from engaging in critical reflection prompted by university faculty during the applied learning experience. However, they were able to independently engage in critical reflection once they began work in the field through university field placements, internships, or student teaching. Finally, students who participated in study abroad applied learning experiences reported their critical reflection on their teaching practices, and cultural sensitivity enhanced their teaching and relationships with children once they formally entered the teaching profession.Keywords: applied learning experiences, critical reflection, cultural sensitivity, preservice teachers, teacher education
Procedia PDF Downloads 1306310 Effect of Key Parameters on Performances of an Adsorption Solar Cooling Machine
Authors: Allouache Nadia
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Solid adsorption cooling machines have been extensively studied recently. They constitute very attractive solutions recover important amount of industrial waste heat medium temperature and to use renewable energy sources such as solar energy. The development of the technology of these machines can be carried out by experimental studies and by mathematical modelisation. This last method allows saving time and money because it is suppler to use to simulate the variation of different parameters. The adsorption cooling machines consist essentially of an evaporator, a condenser and a reactor (object of this work) containing a porous medium, which is in our case the activated carbon reacting by adsorption with ammoniac. The principle can be described as follows: When the adsorbent (at temperature T) is in exclusive contact with vapour of adsorbate (at pressure P), an amount of adsorbate is trapped inside the micro-pores in an almost liquid state. This adsorbed mass m, is a function of T and P according to a divariant equilibrium m=f (T,P). Moreover, at constant pressure, m decreases as T increases, and at constant adsorbed mass P increases with T. This makes it possible to imagine an ideal refrigerating cycle consisting of a period of heating/desorption/condensation followed by a period of cooling/adsorption/evaporation. Effect of key parameters on the machine performances are analysed and discussed.Keywords: activated carbon-ammoniac pair, effect of key parameters, numerical modeling, solar cooling machine
Procedia PDF Downloads 2496309 Lifelong Education for Teachers: A Tool for Achieving Effective Teaching and Learning in Secondary Schools in Benue State, Nigeria
Authors: Adzongo Philomena Ibuh, Aloga O. Austin
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The purpose of the study was to examine lifelong education for teachers as a tool for achieving effective teaching and learning. Lifelong education enhances social inclusion, personal development, citizenship, employability, teaching and learning, community and the nation, and the challenges of lifelong education were also discussed. Descriptive survey design was adopted for the study. A simple random sampling technique was used to select 80 teachers as sample from a population of 105 senior secondary school teachers in Makurdi local government area of Benue state. A 20-item self designed questionnaire subjected to expert validation and reliability was used to collect data. The reliability Alpha coefficient of 0.87 was established using Crombach Alpha technique, mean scores and standard deviation were used to answer the 2 research questions while chi-square was used to analyze data for the 2 hypotheses. The findings of the study revealed that, lifelong education for teachers can be used to achieve as a tool for achieving effective teaching and learning, and the study recommended among others that government, organizations and individuals should in collaboration put lifelong education programmes for teachers on the priority list. The paper concluded that the strategic position of lifelong education for teachers towards enhanced teaching and learning makes it imperative for all hands to be on deck to support the programme financially and otherwise.Keywords: effective teaching and learning, lifelong education, teachers, tool
Procedia PDF Downloads 4696308 Learning to Recommend with Negative Ratings Based on Factorization Machine
Authors: Caihong Sun, Xizi Zhang
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Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.Keywords: factorization machines, feature engineering, negative ratings, recommendation systems
Procedia PDF Downloads 2386307 Use of Technology to Improve Students’ Attitude in Learning Mathematics of Non- Mathematics Undergraduate Students
Authors: Asia Majeed
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The learning of mathematics in science, engineering and social science programs can be enhanced through practical problem-solving techniques. The instructors can design their lessons with some strategies to improve students’ educational needs and accomplishments in mathematics classrooms. The use of technology in class problem solving and application sessions can enhance deep understanding of mathematics among students. As mathematician, we believe in subject specific and content-driven teaching methods. Through technology the relationship between the physical problems and the mathematical models can be analyzed. This paper is about selective use of technology in mathematics classrooms and helpful to others mathematics instructors who wishes to improve their traditional teaching techniques to improve students’ attitude in learning mathematics. These techniques corpus can be used in teaching large mathematics classes in science, technology, engineering, and social science.Keywords: attitude in learning mathematics, mathematics, non-mathematics undergraduate students, technology
Procedia PDF Downloads 2076306 Exploring How Online Applications Help Students to Learn Music Virtually: A Study in an Australian Music Academy
Authors: Ali Shah
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This paper outlines the case study experience of using a variety of online strategies in an Australian music academy context during covid times. The study aimed at exploring how online applications help students to learn music, specifically playing musical instruments, composing songs, and performing virtually. To explore this, music teachers’ perceptions and experiences regarding online learning, the teaching strategies they implemented, and the challenges they faced were examined. For the purpose of this study, a qualitative research structure was adopted through the use of three data collection tools. These methods included pre- and post-research individual interviews of teachers and students, analysis of their lesson plans, virtual classroom observations of the teachers followed by the researcher’sown reflections, post-observation discussions, and teachers’ reflective journals. The findings revealed that teachers had a theoretical understanding of virtual learning and recent musical application such as Flowkey, Skoove, and Piano marvel, which are benefits of e-learning. While teachers faced challenges in implementing strategies to teach keyboard/piano online, overall, both students and teachers felt the positive impact of online applications and strategies on their learning and felt that modern technology made it possible for anyone to take music lessons at home.Keywords: music, keyboard, piano, online learning, virtual learning
Procedia PDF Downloads 696305 Using Q-Learning to Auto-Tune PID Controller Gains for Online Quadcopter Altitude Stabilization
Authors: Y. Alrubyli
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Unmanned Arial Vehicles (UAVs), and more specifically, quadcopters need to be stable during their flights. Altitude stability is usually achieved by using a PID controller that is built into the flight controller software. Furthermore, the PID controller has gains that need to be tuned to reach optimal altitude stabilization during the quadcopter’s flight. For that, control system engineers need to tune those gains by using extensive modeling of the environment, which might change from one environment and condition to another. As quadcopters penetrate more sectors, from the military to the consumer sectors, they have been put into complex and challenging environments more than ever before. Hence, intelligent self-stabilizing quadcopters are needed to maneuver through those complex environments and situations. Here we show that by using online reinforcement learning with minimal background knowledge, the altitude stability of the quadcopter can be achieved using a model-free approach. We found that by using background knowledge instead of letting the online reinforcement learning algorithm wander for a while to tune the PID gains, altitude stabilization can be achieved faster. In addition, using this approach will accelerate development by avoiding extensive simulations before applying the PID gains to the real-world quadcopter. Our results demonstrate the possibility of using the trial and error approach of reinforcement learning combined with background knowledge to achieve faster quadcopter altitude stabilization in different environments and conditions.Keywords: reinforcement learning, Q-leanring, online learning, PID tuning, unmanned aerial vehicle, quadcopter
Procedia PDF Downloads 1646304 Using Historical Data for Stock Prediction
Authors: Sofia Stoica
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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.Keywords: finance, machine learning, opening price, stock market
Procedia PDF Downloads 1806303 Influence of Some Psychological Factors on the Learning Gains of Distance Learners in Mathematics in Ibadan, Nigeria
Authors: Adeola Adejumo, Oluwole David Adebayo, Muraina Kamilu Olanrewaju
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The purpose of this study was to investigate the influence of some psychological factors (i.e, school climate, parental involvement and classroom interaction) on the learning gains of university undergraduates in Mathematics in Ibadan, Nigeria. Three hundred undergraduates who are on open distance learning education programme in the University of Ibadan and thirty mathematics lecturers constituted the study’s sample. Both the independent and dependent variables were measured with relevant standardized instruments and the data obtained was analyzed using multiple regression statistical method. The instruments used were school climate scale, parental involvement scale and classroom interaction scale. Three research questions were answered in the study. The result showed that there was significant relationship between the three independent variables (school climate, parental involvement and classroom interaction) on the students’ learning gain in mathematics and that the independent variables both jointly and relatively contributed significantly to the prediction of students’ learning gain in mathematics. On the strength of these findings, the need to enhance the school climate, improve the parents’ involvement in the student’s education and encourage students’ classroom interaction were stressed and advocated.Keywords: school climate, parental involvement, ODL, learning gains, mathematics
Procedia PDF Downloads 4996302 A Formal Approach for Instructional Design Integrated with Data Visualization for Learning Analytics
Authors: Douglas A. Menezes, Isabel D. Nunes, Ulrich Schiel
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Most Virtual Learning Environments do not provide support mechanisms for the integrated planning, construction and follow-up of Instructional Design supported by Learning Analytic results. The present work aims to present an authoring tool that will be responsible for constructing the structure of an Instructional Design (ID), without the data being altered during the execution of the course. The visual interface aims to present the critical situations present in this ID, serving as a support tool for the course follow-up and possible improvements, which can be made during its execution or in the planning of a new edition of this course. The model for the ID is based on High-Level Petri Nets and the visualization forms are determined by the specific kind of the data generated by an e-course, a population of students generating sequentially dependent data.Keywords: educational data visualization, high-level petri nets, instructional design, learning analytics
Procedia PDF Downloads 2366301 Trends in Practical Research on Universal Design for Learning (UDL) in Japanese Elementary Schools
Authors: Zolzaya Badmaavanchig, Shoko Miyamoto
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In recent years, universal design for learning (hereinafter referred to as "UDL"), which aims to establish an inclusive education system and to make all children, regardless of their disabilities, experts in learning, has been attracting attention, and there have been some attempts to incorporate it into regular classrooms where children with developmental disabilities and those who show such tendencies are enrolled. The purpose of this study was to examine the effectiveness and challenges of implementing UDL in Japanese elementary schools based on the previous literature. As a method, we first searched for articles on UDL for learning and UDL in the classroom from 2010 to 2022. In addition, we selected practice studies that targeted children with special educational support needs and the classroom as a whole. In response to the extracted literature, this bridge examined the following five perspectives: (1) subjects and grades in which UDL was practiced, (2) methods to grasp the actual conditions of the children, (3) consideration for children with special needs during class, (4) form of class, and (5) effects of the practice. Based on the results, we would like to present issues related to future UDL efforts in Japanese elementary schools.Keywords: universal design for learning, regular elementary school class, children with special education needs, special educational support
Procedia PDF Downloads 536300 UKIYO-E: User Knowledge Improvement Based on Youth Oriented Entertainment, Art Appreciation Support by Interacting with Picture
Authors: Haruya Tamaki, Tsugunosuke Sakai, Ryuichi Yoshida, Ryohei Egusa, Shigenori Inagaki, Etsuji Yamaguchi, Fusako Kusunoki, Miki Namatame, Masanori Sugimoto, Hiroshi Mizoguchi
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Art appreciation is important as part of children education. Art appreciation can enrich sensibility and creativity. To enrich sensibility and creativity, the children have to learning knowledge of picture such as social and historical backgrounds and author intention. High learning effect can acquire by actively learning. In short, it is important that encourage learning of the knowledge about pictures actively. It is necessary that children feel like interest to encourage learning of the knowledge about pictures actively. In a general art museum, comments on pictures are done through writing. Thus, we expect that this method cannot arouse the interest of the children in pictures, because children feel like boring. In brief, learning about the picture information is difficult. Therefore, we are developing an art-appreciation support system that will encourage learning of the knowledge about pictures actively by children feel like interest. This system uses that Interacting with Pictures to learning of the knowledge about pictures. To Interacting with Pictures, children have to utterance by themselves. We expect that will encourage learning of the knowledge about pictures actively by Interacting with Pictures. To more actively learning, children can choose who talking with by information that location and movement of the children. This system must be able to acquire real-time knowledge of the location, movement, and voice of the children. We utilize the Microsoft’s Kinect v2 sensor and its library, namely, Kinect for Windows SDK and Speech Platform SDK v11 for this purpose. By using these sensor and library, we can determine the location, movement, and voice of the children. As the first step of this system, we developed ukiyo-e game that use ukiyo-e to appreciation object. Ukiyo-e is a traditional Japanese graphic art that has influenced the western society. Therefore, we believe that the ukiyo-e game will be appreciated. In this study, we applied talking to pictures to learn information about the pictures because we believe that learning information about the pictures by talking to the pictures is more interesting than commenting on the pictures using only texts. However, we cannot confirm if talking to the pictures is more interesting than commenting using texts only. Thus, we evaluated through EDA measurement whether the user develops an interest in the pictures while talking to them using voice recognition or by commenting on the pictures using texts only. Hence, we evaluated that children have interest to picture while talking to them using voice recognition through EDA measurement. In addition, we quantitatively evaluate that enjoyed this game or not and learning information about the pictures for primary schoolchildren. In this paper, we summarize these two evaluation results.Keywords: actively learning, art appreciation, EDA, Kinect V2
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