Search results for: rotation model of blended learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 22239

Search results for: rotation model of blended learning

22089 Efficient Fake News Detection Using Machine Learning and Deep Learning Approaches

Authors: Chaima Babi, Said Gadri

Abstract:

The rapid increase in fake news continues to grow at a very fast rate; this requires implementing efficient techniques that allow testing the re-liability of online content. For that, the current research strives to illuminate the fake news problem using deep learning DL and machine learning ML ap-proaches. We have developed the traditional LSTM (Long short-term memory), and the bidirectional BiLSTM model. A such process is to perform a training task on almost of samples of the dataset, validate the model on a subset called the test set to provide an unbiased evaluation of the final model fit on the training dataset, then compute the accuracy of detecting classifica-tion and comparing the results. For the programming stage, we used Tensor-Flow and Keras libraries on Python to support Graphical Processing Units (GPUs) that are being used for developing deep learning applications.

Keywords: machine learning, deep learning, natural language, fake news, Bi-LSTM, LSTM, multiclass classification

Procedia PDF Downloads 69
22088 Preparation of Wool Fiber/Keratin/PVA Film and Study on Their Structure and Properties

Authors: Min Wu, Shuming Shen, Xuhong Yang, Rencheng Tang

Abstract:

Every year, numerous organic wastes from fiber byproducts of the wool textile industry, poor quality raw wools not fit for spinning, horns, nails and feathers from butchery are disposed. These wastes are abundant in keratin which is a renewable material. Wool fiber/keratin/PVA composites with different proportions were prepared in this study, and the influence of the proportions on their structure and properties were studied, aiming to understand the potential application of keratin in the field of biomedicine, degradable wrapper, and cosmetics film, and provide a new way to reuse keratin wastes. The urea / sodium sulfide / sodium dodecyl sulfate (SDS) method was used to dissolve the wool. After filtration and dialysis, the wool keratin solution was achieved. Then the keratin solution and polyvinal (PVA) solution were blended in different proportions, and the wool fibers cut into a certain length were cast into the blended solution. Thereby, various wool fiber/keratin/PVA composite films with different proportions were formed through pouring the solution into a flat box and drying at room temperature. The surface morphology, molecular structure, and mechanical property of the composite films were studied. The results showed that, there are α-helix structure, β-sheet and random coil conformations in the pure keratin film, as well as in the wool fiber. Compared with wool fiber, the crystallinity of keratin decreased. PVA can obviously improve the mechanical property of the blended film. When the blended ratio of keratin and PVA is 20:80, the mechanical property of the blended film is greatly improved. The composite films with 8%-16% of wool fibers have better flexibility than those without wool fibers.

Keywords: composite film, keratin, mechanical property, morphological structure, PVA, wool fiber

Procedia PDF Downloads 273
22087 An Ontology for Smart Learning Environments in Music Education

Authors: Konstantinos Sofianos, Michail Stefanidakis

Abstract:

Nowadays, despite the great advances in technology, most educational frameworks lack a strong educational design basis. E-learning has become prevalent, but it faces various challenges such as student isolation and lack of quality in the learning process. An intelligent learning system provides a student with educational material according to their learning background and learning preferences. It records full information about the student, such as demographic information, learning styles, and academic performance. This information allows the system to be fully adapted to the student’s needs. In this paper, we propose a framework and an ontology for music education, consisting of the learner model and all elements of the learning process (learning objects, teaching methods, learning activities, assessment). This framework can be integrated into an intelligent learning system and used for music education in schools for the development of professional skills and beyond.

Keywords: intelligent learning systems, e-learning, music education, ontology, semantic web

Procedia PDF Downloads 126
22086 Classifying Students for E-Learning in Information Technology Course Using ANN

Authors: Sirilak Areerachakul, Nat Ployong, Supayothin Na Songkla

Abstract:

This research’s objective is to select the model with most accurate value by using Neural Network Technique as a way to filter potential students who enroll in IT course by electronic learning at Suan Suanadha Rajabhat University. It is designed to help students selecting the appropriate courses by themselves. The result showed that the most accurate model was 100 Folds Cross-validation which had 73.58% points of accuracy.

Keywords: artificial neural network, classification, students, e-learning

Procedia PDF Downloads 411
22085 The Development of Directed-Project Based Learning as Language Learning Model to Improve Students' English Achievement

Authors: Tri Pratiwi, Sufyarma Marsidin, Hermawati Syarif, Yahya

Abstract:

The 21st-century skills being highly promoted today are Creativity and Innovation, Critical Thinking and Problem Solving, Communication and Collaboration. Communication Skill is one of the essential skills that should be mastered by the students. To master Communication Skills, students must first master their Language Skills. Language Skills is one of the main supporting factors in improving Communication Skills of a person because by learning Language Skills students are considered capable of communicating well and correctly so that the message or how to deliver the message to the listener can be conveyed clearly and easily understood. However, it cannot be denied that English output or learning outcomes which are less optimal is the problem which is frequently found in the implementation of the learning process. This research aimed to improve students’ language skills by developing learning model in English subject for VIII graders of SMP N 1 Uram Jaya through Directed-Project Based Learning (DPjBL) implementation. This study is designed in Research and Development (R & D) using ADDIE model development. The researcher collected data through observation, questionnaire, interview, test, and documentation which were then analyzed qualitatively and quantitatively. The results showed that DPjBL is effective to use, it is seen from the difference in value between the pretest and posttest of the control class and the experimental class. From the results of a questionnaire filled in general, the students and teachers agreed to DPjBL learning model. This learning model can increase the students' English achievement.

Keywords: language skills, learning model, Directed-Project Based Learning (DPjBL), English achievement

Procedia PDF Downloads 157
22084 Analytical Modelling of the Moment-Rotation Behavior of Top and Seat Angle Connection with Stiffeners

Authors: Merve Sagiroglu

Abstract:

The earthquake-resistant steel structure design is required taking into account the behavior of beam-column connections besides the basic properties of the structure such as material and geometry. Beam-column connections play an important role in the behavior of frame systems. Taking into account the behaviour of connection in analysis and design of steel frames is important due to presenting the actual behavior of frames. So, the behavior of the connections should be well known. The most important force which transmitted by connections in the structural system is the moment. The rotational deformation is customarily expressed as a function of the moment in the connection. So, the moment-rotation curves are the best expression of behaviour of the beam-to-column connections. The designed connections form various moment-rotation curves according to the elements of connection and the shape of placement. The only way to achieve this curve is with real-scale experiments. The experiments of some connections have been carried out partially and are formed in the databank. It has been formed the models using this databank to express the behavior of connection. In this study, theoretical studies have been carried out to model a real behavior of the top and seat angles connections with angles. Two stiffeners in the top and seat angle to increase the stiffness of the connection, and two stiffeners in the beam web to prevent local buckling are used in this beam-to-column connection. Mathematical models have been performed using the database of the beam-to-column connection experiments previously by authors. Using the data of the tests, it has been aimed that analytical expressions have been developed to obtain the moment-rotation curve for the connection details whose test data are not available. The connection has been dimensioned in various shapes and the effect of the dimensions of the connection elements on the behavior has been examined.

Keywords: top and seat angle connection, stiffener, moment-rotation curves, analytical study

Procedia PDF Downloads 166
22083 Prediction of the Dark Matter Distribution and Fraction in Individual Galaxies Based Solely on Their Rotation Curves

Authors: Ramzi Suleiman

Abstract:

Recently, the author proposed an observationally-based relativity theory termed information relativity theory (IRT). The theory is simple and is based only on basic principles, with no prior axioms and no free parameters. For the case of a body of mass in uniform rectilinear motion relative to an observer, the theory transformations uncovered a matter-dark matter duality, which prescribes that the sum of the densities of the body's baryonic matter and dark matter, as measured by the observer, is equal to the body's matter density at rest. It was shown that the theory transformations were successful in predicting several important phenomena in small particle physics, quantum physics, and cosmology. This paper extends the theory transformations to the cases of rotating disks and spheres. The resulting transformations for a rotating disk are utilized to derive predictions of the radial distributions of matter and dark matter densities in rotationally supported galaxies based solely on their observed rotation curves. It is also shown that for galaxies with flattening curves, good approximations of the radial distributions of matter and dark matter and of the dark matter fraction could be obtained from one measurable scale radius. Test of the model on five galaxies, chosen randomly from the SPARC database, yielded impressive predictions. The rotation curves of all the investigated galaxies emerged as accurate traces of the predicted radial density distributions of their dark matter. This striking result raises an intriguing physical explanation of gravity in galaxies, according to which it is the proximal drag of the stars and gas in the galaxy by its rotating dark matter web. We conclude by alluding briefly to the application of the proposed model to stellar systems and black holes. This study also hints at the potential of the discovered matter-dark matter duality in fixing the standard model of elementary particles in a natural manner without the need for hypothesizing about supersymmetric particles.

Keywords: dark matter, galaxies rotation curves, SPARC, rotating disk

Procedia PDF Downloads 67
22082 Model Observability – A Monitoring Solution for Machine Learning Models

Authors: Amreth Chandrasehar

Abstract:

Machine Learning (ML) Models are developed and run in production to solve various use cases that help organizations to be more efficient and help drive the business. But this comes at a massive development cost and lost business opportunities. According to the Gartner report, 85% of data science projects fail, and one of the factors impacting this is not paying attention to Model Observability. Model Observability helps the developers and operators to pinpoint the model performance issues data drift and help identify root cause of issues. This paper focuses on providing insights into incorporating model observability in model development and operationalizing it in production.

Keywords: model observability, monitoring, drift detection, ML observability platform

Procedia PDF Downloads 91
22081 Self-Regulated Learning: A Required Skill for Web 2.0 Internet-Based Learning

Authors: Pieter Conradie, M. Marina Moller

Abstract:

Web 2.0 Internet-based technologies have intruded all aspects of human life. Presently, this phenomenon is especially evident in the educational context, with increased disruptive Web 2.0 technology infusions dramatically changing educational practice. The most prominent of these Web 2.0 intrusions can be identified as Massive Open Online Courses (Coursera, EdX), video and photo sharing sites (Youtube, Flickr, Instagram), and Web 2.0 online tools utilize to create Personal Learning Environments (PLEs) (Symbaloo (aggregator), Delicious (social bookmarking), PBWorks (collaboration), Google+ (social networks), Wordspress (blogs), Wikispaces (wiki)). These Web 2.0 technologies have supported the realignment from a teacher-based pedagogy (didactic presentation) to a learner-based pedagogy (problem-based learning, project-based learning, blended learning), allowing greater learner autonomy. No longer is the educator the source of knowledge. Instead the educator has become the facilitator and mediator of the learner, involved in developing learner competencies to support life-long learning (continuous learning) in the 21st century. In this study, the self-regulated learning skills of thirty first-year university learners were explored by utilizing the Online Self-regulated Learning Questionnaire. Implementing an action research method, an intervention was affected towards improving the self-regulation skill set of the participants. Statistical significant results were obtained with increased self-regulated learning proficiency, positively impacting learner performance. Goal setting, time management, environment structuring, help seeking, task (learning) strategies and self-evaluation skills were confirmed as determinants of improved learner success.

Keywords: andragogy, online self-regulated learning questionnaire, self-regulated learning, web 2.0

Procedia PDF Downloads 404
22080 Evaluating the Teaching and Learning Value of Tablets

Authors: Willem J. A. Louw

Abstract:

The wave of new advanced computing technology that has been developed during the recent past has significantly changed the way we communicate, collaborate and collect information. It has created a new technology environment and paradigm in which our children and students grow-up and this impacts on their learning. Research confirmed that Generation Y students have a preference for learning in the new technology environment. The challenge or question is: How do we adjust our teaching and learning to make the most of these changes. The complexity of effective and efficient teaching and learning must not be underestimated and changes must be preceded by proper objective research to prevent any haphazard developments that could do more harm than benefit. A blended learning approach has been used in the Forestry department for a few numbers of years including the use of electronic-peer assisted learning (e-pal) in a fixed-computer set-up within a learning management system environment. It was decided to extend the investigation and do some exploratory research by using a range of different Tablet devices. For this purpose, learning activities or assignments were designed to cover aspects of communication, collaboration and collection of information. The Moodle learning management system was used to present normal module information, to communicate with students and for feedback and data collection. Student feedback was collected by using an online questionnaire and informal discussions. The research project was implemented in 2013, 2014 and 2015 amongst first and third-year students doing a forestry three-year technical tertiary qualification in commercial plantation management. In general, more than 80% of the students alluded to that the device was very useful in their learning environment while the rest indicated that the devices were not very useful. More than ninety percent of the students acknowledged that they would like to continue using the devices for all of their modules whilst the rest alluded to functioning efficiently without the devices. Results indicated that information collection (access to resources) was rated the highest advantageous factor followed by communication and collaboration. The main general advantages of using Tablets were listed by the students as being mobility (portability), 24/7 access to learning material and information of any kind on a user friendly device in a Wi-Fi environment, fast computing process speeds, saving time, effort and airtime through skyping and e-mail, and use of various applications. Ownership of the device is a critical factor while the risk was identified as a major potential constraint. Significant differences were reported between the different types and quality of Tablets. The preferred types are those with a bigger screen and the ones with overall better functionality and quality features. Tablets significantly increase the collaboration, communication and information collection needs of the students. It does, however, not replace the need of a computer/laptop because of limited storage and computation capacity, small screen size and inefficient typing.

Keywords: tablets, teaching, blended learning, tablet quality

Procedia PDF Downloads 241
22079 Creating a Critical Digital Pedagogy Context: Challenges and Potential of Designing and Implementing a Blended Learning Intervention for Adult Refugees in Greece

Authors: Roula Kitsiou, Sofia Tsioli, Eleni Gana

Abstract:

The current sociopolitical realities (displacement, encampment, and resettlement) refugees experience in Greece are a quite complex issue. Their educational and social ‘integration’ is characterized by transition, insecurity, and constantly changing needs. Based on the current research data, technology and more specifically mobile phones are one of the most important resources for refugees, regardless of their levels of conventional literacy. The proposed paper discusses the challenges encountered during the design and implementation of the educational Action 16 ‘Language Education for Adult Refugees’. Action 16 is one of the 24 Actions of the Project PRESS (Provision of Refugee Education and Support Scheme), funded by the Hellenic Open University (2016-2017). Project PRESS had two main objectives: a) to address the educational and integration needs of refugees in transit, who currently reside in Greece, and b) implement research-based educational interventions in online and offline sites. In the present paper, the focus is on reflection and discussion about the challenges and the potential of integrating technology in language learning for a target-group with many specific needs, which have been recorded in field notes among other research tools (ethnographic data) used in the context of PRESS. Action 16, explores if and how technology enhanced language activities in real-time and place mediated through teachers, as well as an autonomous computer-mediated learning space (moodle platform and application) builds on and expands the linguistic, cultural and digital resources and repertoires of the students by creating collaborative face-to-face and digital learning spaces. A broader view on language as a dynamic puzzle of semiotic resources and processes based on the concept of translanguaging is adopted. Specifically, designing the blended learning environment we draw on the construct of translanguaging a) as a symbolic means to valorize students’ repertoires and practices, b) as a method to reach to specific applications of a target-language that the context brings forward (Greek useful to them), and c) as a means to expand refugees’ repertoires. This has led to the creation of a learning space where students' linguistic and cultural resources can find paths to expression. In this context, communication and learning are realized by mutually investing multiple aspects of the team members' identities as educational material designers, teachers, and students on the teaching and learning processes. Therefore, creativity, humour, code-switching, translation, transference etc. are all possible means that can be employed in order to promote multilingual communication and language learning towards raising intercultural awareness in a critical digital pedagogy context. The qualitative analysis includes critical reflection on the developed educational material, team-based reflexive discussions, teachers’ reports data, and photographs from the interventions. The endeavor to involve women and men with a refugee background into a blended learning experience was quite innovative especially for the Greek context. It reflects a pragmatist ethos of the choices made in order to respond to the here-and-now needs of the refugees, and finally it was a very challenging task that has led all actors involved into Action 16 to (re)negotiations of subjectivities and products in a creative and hopeful way.

Keywords: blended learning, integration, language education, refugees

Procedia PDF Downloads 117
22078 Prediction of Distillation Curve and Reid Vapor Pressure of Dual-Alcohol Gasoline Blends Using Artificial Neural Network for the Determination of Fuel Performance

Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

Abstract:

The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

Procedia PDF Downloads 87
22077 Breast Cancer Prediction Using Score-Level Fusion of Machine Learning and Deep Learning Models

Authors: Sam Khozama, Ali M. Mayya

Abstract:

Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

Procedia PDF Downloads 147
22076 Pushover Experiment of Traditional Dieh-Dou Timber Frame

Authors: Ren Zuo Wang

Abstract:

In this paper, in order to investigate the joint behaviors of the Dieh-Dou structure. A pushover experiment of Dieh-Dou Jia-Dong is implemented. NDI, LVDT and image measurement system are used to measure displacements of joints and deformations of Dieh-Dou Jia-Dong. In addition, joint rotation-moment relationships of column restoring force, purlin-supporting, Dou-Shu, Dou-Gong brackets, primary beam-Gua Tong, secondary beam-Gua Tong, Tertiary beam are builied. From Jia-Dong experiments, formulations of joint rotation are proposed.

Keywords: pushover experiment, Dieh-Dou timber frame, image measurement system, joint rotation-moment relationships

Procedia PDF Downloads 436
22075 Investigating the Dynamics of Knowledge Acquisition in Learning Using Differential Equations

Authors: Gilbert Makanda, Roelf Sypkens

Abstract:

A mathematical model for knowledge acquisition in teaching and learning is proposed. In this study we adopt the mathematical model that is normally used for disease modelling into teaching and learning. We derive mathematical conditions which facilitate knowledge acquisition. This study compares the effects of dropping out of the course at early stages with later stages of learning. The study also investigates effect of individual interaction and learning from other sources to facilitate learning. The study fits actual data to a general mathematical model using Matlab ODE45 and lsqnonlin to obtain a unique mathematical model that can be used to predict knowledge acquisition. The data used in this study was obtained from the tutorial test results for mathematics 2 students from the Central University of Technology, Free State, South Africa in the department of Mathematical and Physical Sciences. The study confirms already known results that increasing dropout rates and forgetting taught concepts reduce the population of knowledgeable students. Increasing teaching contacts and access to other learning materials facilitate knowledge acquisition. The effect of increasing dropout rates is more enhanced in the later stages of learning than earlier stages. The study opens up a new direction in further investigations in teaching and learning using differential equations.

Keywords: differential equations, knowledge acquisition, least squares nonlinear, dynamical systems

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22074 A Deep Reinforcement Learning-Based Secure Framework against Adversarial Attacks in Power System

Authors: Arshia Aflaki, Hadis Karimipour, Anik Islam

Abstract:

Generative Adversarial Attacks (GAAs) threaten critical sectors, ranging from fingerprint recognition to industrial control systems. Existing Deep Learning (DL) algorithms are not robust enough against this kind of cyber-attack. As one of the most critical industries in the world, the power grid is not an exception. In this study, a Deep Reinforcement Learning-based (DRL) framework assisting the DL model to improve the robustness of the model against generative adversarial attacks is proposed. Real-world smart grid stability data, as an IIoT dataset, test our method and improves the classification accuracy of a deep learning model from around 57 percent to 96 percent.

Keywords: generative adversarial attack, deep reinforcement learning, deep learning, IIoT, generative adversarial networks, power system

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22073 Enhancing Fall Detection Accuracy with a Transfer Learning-Aided Transformer Model Using Computer Vision

Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias

Abstract:

Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.

Keywords: healthcare, fall detection, transformer, transfer learning

Procedia PDF Downloads 117
22072 Exploring the Effect of Environmental Cues of Food Festival on Visitor Satisfaction

Authors: Tao Zhang

Abstract:

As the competition of all kinds of festival events becomes more and more fierce, more and more event organizers try to design a blended festivalscape by integrating multifaceted environmental cues in order to raise the service quality of festival events and then raise visitors’ satisfaction. As the main type of festival events, food festivals are popular in all over the world. The organizers’ of food festivals also try to mix food with multifaceted environmental cues (e.g., music, stage, light, dance) to design a blended festivalscape. However, until now little studies explore the environmental cues of food festivals and their relationship with visitors’ satisfaction. Therefore, the aim of this study is to ascertain the environmental cues of food festival and their relationship with visitors’ satisfaction by using the blended festivalscape theory. Using convenient sampling method, this study investigated 1,000 food festival visitors in Macau. Factor analysis showed there are mainly six environmental cues (i.e., food, atmosphere, program, staff, facility, and information). All six environmental cues are positively related with visitors’ satisfaction, while the most influential factors are food, atmosphere, and program. This study showed that festival event organizers’ should focus on the topic of their festival event, build festival atmosphere, and create interesting programs in order to design a blended festivalscape and then raise visitors’ satisfaction.

Keywords: environmental cue, event, festival, satisfaction

Procedia PDF Downloads 352
22071 The Incompressible Preference of Turbulence

Authors: Samuel David Dunstan

Abstract:

An elementary observation of a laminar cylindrical Poiseulle-Couette flow profile reveals no distinction in the parabolic streamwise profile from one without a cross-stream flow in whatever reference frame the observation is made. This is because the laminar flow is in solid-body rotation, and there is no intrinsic fluid rotation. Hence the main streamwise Poiseuille flow is unaffected. However, in turbulent (unsteady) cylindrical Poiseuille-Couette flow, the rotational reference frame must be considered, and any observation from an external inertial reference frame can give outright incorrect results. A common misconception in the study of fluid mechanics is the position of the observer does not matter. In this DNS (direct numerical simulation) study, firstly, turbulent flow in a pipe with axial rotation is established. Then in turbulent flow in the concentric pipe, with inner wall rotation, it is shown how the wall streak direction is oriented by the rotational reference frame. The Coriolis force here is not so fictitious after all!

Keywords: concentric pipe, rotational and inertial frames, frame invariance, wall streaks, flow orientation

Procedia PDF Downloads 73
22070 Using ROVs to Teach a Blended STEM Curriculum

Authors: Geoffrey A. Wright

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Over the past year we have developed and implemented a blended STEM curriculum based on ROV (Remotely Operated Vehicle) underwater technology with over 300 students in grades 2–9. This paper presents an overview of the curriculum, what we have learned from the development and implementation, with suggestions of how to build a similar statewide ROV program, and how we will continue and enhance the effort this next year with more than 300 additional students. The benefits of the program are the application and blending of STEM principles using inquiry based instruction, where students have shown to increase in STEM self-efficacy and interest.

Keywords: STEM, technology, engineering, ROV

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22069 Machine Learning Model Applied for SCM Processes to Efficiently Determine Its Impacts on the Environment

Authors: Elena Puica

Abstract:

This paper aims to investigate the impact of Supply Chain Management (SCM) on the environment by applying a Machine Learning model while pointing out the efficiency of the technology used. The Machine Learning model was used to derive the efficiency and optimization of technology used in SCM and the environmental impact of SCM processes. The model applied is a predictive classification model and was trained firstly to determine which stage of the SCM has more outputs and secondly to demonstrate the efficiency of using advanced technology in SCM instead of recuring to traditional SCM. The outputs are the emissions generated in the environment, the consumption from different steps in the life cycle, the resulting pollutants/wastes emitted, and all the releases to air, land, and water. This manuscript presents an innovative approach to applying advanced technology in SCM and simultaneously studies the efficiency of technology and the SCM's impact on the environment. Identifying the conceptual relationships between SCM practices and their impact on the environment is a new contribution to the research. The authors can take a forward step in developing recent studies in SCM and its effects on the environment by applying technology.

Keywords: machine-learning model in SCM, SCM processes, SCM and the environmental impact, technology in SCM

Procedia PDF Downloads 104
22068 Enhancing Teachers’ Professional Development Programmes by the Implementation of Flipped Learning Instruction: A Qualitative Study

Authors: Badriah Algarni

Abstract:

The pedagogy of ‘flipped learning’ is a form of blended instruction which is gaining widespread attention throughout the world. However, there is a lack of research concerning teachers’ professional development (TPD) in teachers who use flipping. The aim of this study was, therefore, to identify teachers’ perspectives on their experience of flipped PD. The study used a qualitative approach. Purposive sampling recruited nineteen teachers who participated in semi-structured, in-depth interviews. Thematic analysis was used to analyse the interview data. Overall, the teachers reported feeling more confident in their knowledge and skills after participating in flipped TPD. The analysis of the interview data revealed five overarching themes:1) increased engagement with the content; 2) better use of resources; 3) a social, collaborative environment; 4) exchange of practices and experiences; and 5) valuable online activities. These findings can encourage educators, policymakers, and trainers to consider flipped TPD as a form of PD to promote the building of teachers’ knowledge and stimulate reflective practices to improve teaching and learning practices.

Keywords: engagement, flipped learning, teachers’ professional development, collaboration

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22067 Investigating the Effect of the Flipped Classroom Using E-Learning on Language Proficiency, Learner's Autonomy, and Class Participation of English Language Learners

Authors: Michelle Siao-Cing Guo

Abstract:

Technology is widely adopted to assist instruction and learning across disciplines. Traditional teaching method fails to capture the attention of the generation of digital native and does not accommodate diverse needs of today’s learners. The innovation in technology allows new pedagogical approaches. One approach that converts the traditional learning classroom to a more flexible learning time and space is known as the flipped classroom. This new pedagogy extends and enhances learning and accommodates different learning styles. The flipped classroom employs technology to offer course materials online 24 hours/day and to promote active class learning. However, will Taiwanese students who are used to more traditional instructional methods embrace the flipped classroom using E-learning? Will the flipped approach have an effect on Taiwanese students’ English mastery and learning autonomy? The researcher compares a flipped classroom model using E-learning and the traditional-lecture model. A pre- and post-test and a questionnaire were utilized to examine the effect of the flipped classroom on Taiwanese college students. The test results showed that the flipped approach had a positive effect on learners’ English proficiency level, topical knowledge, and willingness to participate in class. The questionnaire also demonstrates the acceptance of the new teaching model.

Keywords: flipped classroom , E-learning, innovative teaching, technology

Procedia PDF Downloads 358
22066 A Model Towards Creating Positive Accounting Classroom Conditions That Supports Successful Learning at School

Authors: Vine Petzer, Mirna Nel

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An explanatory mixed method design was used to investigate accounting classroom conditions in the Further Education and Training (FET) Phase in South Africa. A descriptive survey research study with a heterogeneous group of learners and teachers was conducted in the first phase. In the qualitative phase, semi-structured individual interviews with learners and teachers, as well as observations in the accounting classroom, were employed to gain more in depth understanding of the learning conditions in the accounting classroom. The findings of the empirical research informed the development of a model for teachers in accounting, supporting them to use more effective teaching methods and create positive learning conditions for all learners to experience successful learning. A model towards creating positive Accounting classroom conditions that support successful learning was developed and recommended for education policy and decision-makers for use as a classroom intervention capacity building tool. The model identifies and delineates classroom practices that exert significant effect on learner attainment of quality education.

Keywords: accounting classroom conditions, positive education, successful learning, teaching accounting

Procedia PDF Downloads 133
22065 Engaging Students with Special Education Needs through Technology-Enhanced Interactive Activities in Class

Authors: Pauli P.Y. Lai

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Students with Special Education Needs (SEN) face many challenges in learning. Various challenges include difficulty in handwriting, slow understanding and assimilation, difficulty in paying attention during class, and lack of communication skills. To engage students with Special Education Needs in class with general students, Blackboard Collaborate is used as a teaching and learning tool to deliver a lecture with interactive activities. Blackboard Collaborate provides a good platform to create and enhance active, collaborative and interactive learning experience whereby the SEN students can easily interact with their general peers and the instructor by using the features of drawing on a virtual whiteboard, file sharing, classroom chatter, breakout room, hand-raising feature, polling, etc. By integrating a blended learning approach with Blackboard Collaborate, the students with Special Education Needs could engage in interactive activities with ease in class. Our research aims at exploring and discovering the use of Blackboard Collaborate for inclusive education based on a qualitative design with in-depth interviews. Being served in a general education environment, three university students with different kinds of learning disabilities have participated in our study. All participants agreed that functions provided by Blackboard Collaborate have enhanced their learning experiences and helped them learn better. Their academic performances also showed that SEN students could perform well with the help of technology. This research studies different aspects of using Blackboard Collaborate to create an inclusive learning environment for SEN students.

Keywords: blackboard collaborate, enhanced learning experience, inclusive education, special education needs

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22064 Affective (And Effective) Teaching and Learning: Higher Education Gets Social Again

Authors: Laura Zizka, Gaby Probst

Abstract:

The Covid-19 pandemic has affected the way Higher Education Institutions (HEIs) have given their courses. From emergency remote where all students and faculty were immediately confined to home teaching and learning, the continuing evolving sanitary situation obliged HEIs to adopt other methods of teaching and learning from blended courses that included both synchronous and asynchronous courses and activities to hy-flex models where some students were on campus while others followed the course simultaneously online. Each semester brought new challenges for HEIs and, subsequently, additional emotional reactions. This paper investigates the affective side of teaching and learning in various online modalities and its toll on students and faculty members over the past three semesters. The findings confirm that students and faculty who have more self-efficacy, flexibility, and resilience reported positive emotions and embraced the opportunities that these past semesters have offered. While HEIs have begun a new semester in an attempt to return to ‘normal’ face-to-face courses, this paper posits that there are lessons to be learned from these past three semesters. The opportunities that arose from the challenge of the pandemic should be considered when moving forward by focusing on a greater emphasis on the affective aspect of teaching and learning in HEIs worldwide.

Keywords: effective teaching and learning, higher education, engagement, interaction, motivation

Procedia PDF Downloads 105
22063 Competence on Learning Delivery Modes and Performance of Physical Education Teachers in Senior High Schools in Davao

Authors: Juvanie C. Lapesigue

Abstract:

Worldwide school closures result from a significant public health crisis that has affected the nation and the entire world. It has affected students, educators, educational organizations globally, and many other aspects of society. Academic institutions worldwide teach students using diverse approaches of various learning delivery modes. This paper investigates the competence and performance of physical education teachers using various learning delivery modes, including Distance learning, Blended Learning, and Homeschooling during online distance education. To identify the Gap between their age generation using various learning delivery that affects teachers' preparation for distance learning and evaluates how these modalities impact teachers’ competence and performance in the case of a pandemic. The respondents were the Senior High School teachers of the Department of Education who taught in Davao City before and during the pandemic. Purposive sampling was utilized on 61 Senior High School Teachers in Davao City Philippines. The result indicated that teaching performance based on pedagogy and assessment has significantly affected teaching performance in teaching physical education, particularly those Non-PE teachers teaching physical education subjects. It should be supplied with enhancement training workshops to help them be more successful in preparation in terms of teaching pedagogy and assessment in the following norm. Hence, a proposed unique training design for non-P.E. Teachers has been created to improve the teachers’ performance in terms of pedagogy and assessment in teaching P.E subjects in various learning delivery modes in the next normal.

Keywords: distance learning, learning delivery modes, P.E teachers, senior high school, teaching competence, teaching performance

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22062 The Magnetized Quantum Breathing in Cylindrical Dusty Plasma

Authors: A. Abdikian

Abstract:

A quantum breathing mode has been theatrically studied in quantum dusty plasma. By using linear quantum hydrodynamic model, not only the quantum dispersion relation of rotation mode but also void structure has been derived in the presence of an external magnetic field. Although the phase velocity of the magnetized quantum breathing mode is greater than that of unmagnetized quantum breathing mode, attenuation of the magnetized quantum breathing mode along radial distance seems to be slower than that of unmagnetized quantum breathing mode. Clearly, drawing the quantum breathing mode in the presence and absence of a magnetic field, we found that the magnetic field alters the distribution of dust particles and changes the radial and azimuthal velocities around the axis. Because the magnetic field rotates the dust particles and collects them, it could compensate the void structure.

Keywords: the linear quantum hydrodynamic model, the magnetized quantum breathing mode, the quantum dispersion relation of rotation mode, void structure

Procedia PDF Downloads 279
22061 A Comparison of Computational and Experimental Data to Investigate the Influence of the Tangential Velocity of Inner Rotating Wall on Axial Velocity Profile of Flow through Vertical Annular Pipe with Rotating Inner Surface

Authors: Abdusalam Sharf

Abstract:

In the oil and gas industries, one of the most important issues in drilling wells is understanding the behavior of a flow through an annulus gap in a vertical position, whose outer wall is stationary whilst the inner wall rotates. The main emphasis is placed on a comparison of experimental and computational investigations into the effects of the rotation speed of the inner pipe on the axial velocity profiles. The computational investigations were carried out by employing CFD software, and Gambit and Fluent. Three turbulence models were used: standard, RNG with enhanced wall treatment, and SST model. The profiles of the axial velocity had investigated at different rotation speeds of the inner pipe with three different volumetric flow rates. The comparison results showed that the calculations satisfactorily predict the qualitative features of the axial and swirl velocity profiles and the RNG model performs the best results.

Keywords: computational fluid dynamics (CFD), SST k−ω shear-stress transport (k−ω mode variant), RNG k–ε renormalisation group (k−ε mode variant), y+ dimensionless distance from wall

Procedia PDF Downloads 368
22060 Reinforcement Learning for Self Driving Racing Car Games

Authors: Adam Beaunoyer, Cory Beaunoyer, Mohammed Elmorsy, Hanan Saleh

Abstract:

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 29