Search results for: simulation learning

Authors: Farshad Badie

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The central focus of this article is on the fact that knowledge is constructed from an interaction between humans’ experiences and over their conceptions of constructed concepts. Logical characterisation of ‘human inductive learning over human’s constructed concepts’ within terminological systems and providing a logical background for theorising over the Human Concept Learning Problem (HCLP) in terminological systems are the main contributions of this research. This research connects with the topics ‘human learning’, ‘epistemology’, ‘cognitive modelling’, ‘knowledge representation’ and ‘ontological reasoning’.

Keywords: human concept learning, concept construction, knowledge construction, terminological systems

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Authors: Jatinder Kumar, Ajay Bansal

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Simulation of a photocatalytic reactor helps in understanding the complex behavior of the photocatalytic degradation. Simulation also aids the designing and optimization of the photocatalytic reactor. Lack of simulation strategies is a huge hindrance in the commercialization of the photocatalytic technology. With the increased performance of computational resources, and development of simulation software, computational fluid dynamics (CFD) is becoming an affordable engineering tool to simulate and optimize reactor designs. In the present paper, a CFD (Computational fluid dynamics) model for simulating the performance of an immobilized-titanium dioxide based annular photocatalytic reactor was developed. The computational model integrates hydrodynamics, species mass transport, and chemical reaction kinetics using a commercial CFD code Fluent 6.3.26. The CFD model was based on the intrinsic kinetic parameters determined experimentally in a perfectly mixed batch reactor. Rhodamine B, a complex organic compound, was selected as a test pollutant for photocatalytic degradation. It was observed that CFD could become a valuable tool to understand and improve the photocatalytic systems.

Keywords: simulation, computational fluid dynamics (CFD), annular photocatalytic reactor, titanium dioxide

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Authors: Ahmad FAROOQ, Xinfeng Zhang, Fahad Sabah, Raheem Sarwar

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In Traditional Chinese Medicine, tongue diagnosis is a vital inspection tool (TCM). In this study, we explore the potential of machine learning in tongue diagnosis. It begins with the cataloguing of the various classifications and characteristics of the human tongue. We infer 24 kinds of tongues from the material and coating of the tongue, and we identify 21 attributes of the tongue. The next step is to apply machine learning methods to the tongue dataset. We use the Weka machine learning platform to conduct the experiment for performance analysis. The 457 instances of the tongue dataset are used to test the performance of five different machine learning methods, including SVM, Random Forests, Decision Trees, and Naive Bayes. Based on accuracy and Area under the ROC Curve, the Support Vector Machine algorithm was shown to be the most effective for tongue diagnosis (AUC).

Keywords: medical imaging, image retrieval, machine learning, tongue

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method

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Authors: Motonobu Hattori

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In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudo patterns. Because, temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.

Keywords: catastrophic forgetting, dual-network, temporal sequences, hippocampal

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Authors: Marina Paula Carreira Rolim

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In order to have ELLs take responsibility for their own learning, it is important that they develop skills to work their studies strategically. The less they rely on the instructor as the content provider, the more they become active learners and have a higher sense of self-regulation and confidence in the learning process. This e-poster proposes a new teacher-student relationship that encourages learners to reflect, think critically, and act upon their realities. It also suggests the implementation of different autonomy-supportive teaching tools, such as portfolios, written journals, problem-solving activities, and strategy-based discussions in class. These teaching tools enable ELLs to develop awareness of learning strategies, learning styles, study plans, and available learning resources as means to foster their creative power of learning outside of classroom. In the role of a learning advisor, the teacher is no longer the content provider but a facilitator that introduces skills such as ‘elaborating’, ‘planning’, ‘monitoring’, and ‘evaluating’. The teacher acts as an educator and promotes the use of lifelong metacognitive skills to develop learner autonomy in the ESL/EFL context.

Keywords: autonomy, metacognitive skills, self-regulation, learning strategies, reflection

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

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2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: artificial intelligence, machine learning, deep learning, convolutional neural networks

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Authors: Martina Holenko Dlab, Natasa Hoic-Bozic, Ivica Boticki

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This paper presents technologically innovative and scalable mobile learning solution within the SCOLLAm project (“Opening up education through Seamless and COLLAborative mobile learning on tablet computers”). The main research method applied during the development of the SCOLLAm mobile learning system is design-based research. It assumes iterative refinement of the system guided by collaboration between researches and practitioners. Following the identification of requirements, a multiplatform mobile learning system SCOLLAm [in]Form was developed. Several experiments were designed and conducted in the first and second grade of elementary school. SCOLLAm [in]Form system was used to design learning activities for math classes during which students practice calculation. System refinements were based on experience and interaction data gathered during class observations. In addition to implemented improvements, the data were used to outline possible improvements and deficiencies of the system that should be addressed in the next phase of the SCOLLAm [in]Form development.

Keywords: adaptation, collaborative learning, educational technology, mobile learning, tablet computers

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Authors: Chih-Chun Wu

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Learning information and communication technologies (ICT) helps people survive in current society. For the internet generation also referred as digital natives, learning new technology is like breathing; however, for the elder generations also called digital immigrants, including parents and grandparents, learning new technology could be challenged and frustrated. While majority research focused on the effects of elders’ ICT learning, less attention was paid to the help that the elders got from their other family members while learning ICT. This study utilized the anonymous questionnaire to survey 3,749 undergraduates and demonstrated that families are great places for intergenerational technology learning to be carried out. Results from this study confirmed that in the family, the younger generation both helped set up technology products and educated the elder ones needed technology knowledge and skills. The family elder members in this study applied to those who lived under the same roof with relative relations. Results from this study revealed that 2,331 (62.2%) and 2,656 (70.8%) undergraduates revealed that they helped their family elder members set up and taught them how to use LINE respectively. In addition, 1,481 (49.1%) undergraduates helped their family elder members set up, and 2,222 (59.3%) taught them. When it came to Apps, 2,527 (67.4%) helped their family elder members download them, and 2,876 (76.7%) taught how to use them. As for search engine, 2,317 (61.8%) undergraduates taught their family elders. Furthermore, 3,118 (83.2%), 2,639 (70.4%) and 2,004 (53.7%) undergraduates illustrated that they taught their family elder members smartphones, computers and tablets respectively. Meanwhile, only 904 (24.2%) undergraduates taught their family elders how to make a doctor appointment online. This study suggests to making good use of intergenerational technology learning in the family, since it increases family elders’ technology capital, and thus strengthens our country’s human capital and competitiveness.

Keywords: intergenerational technology learning, adult technology learning, family technology learning, ICT learning

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Authors: Bella Llego

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This study aims to investigate the motivating and de-motivating factors that affect the learning ability of students attending the English Learning Center in Thailand. The subjects of this research were 20 students from the Hana Semiconductor Co., Limited. The data were collected by using questionnaire and analyzed using the SPSS program for the percentage, mean and standard deviation. The research results show that the main motivating factor in learning English at Hana Semiconductor Co., Ltd. is that it would help the employees to communicate with foreign customers and managers. Other reasons include the need to read and write e-mails, and reports in English, as well as to increase overall general knowledge. The main de-motivating factor is that there is a lot of vocabulary to remember when learning English. Another de-motivating factor is that when homework is given, the students have no time to complete the tasks required of them at the end of the working day.

Keywords: de-motivating, English learning center, motivating, student communicate

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Authors: Chariton Christou, David Cornwell

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Production Sharing Contract (PSC) is the type of contract that is being used widely in our time. The financial crisis made the governments tightfisted and they do not have the resources to participate in a development of a field. Therefore, more and more countries introduce the PSC. The companies have the power and the money to develop the field with their own way. The main problem is the transparency of oil and gas companies especially in the PSC and how this can be achieved. Many discussions have been made especially in the U.K. What we are suggesting is a dynamic financial simulation with the help of a flow meter. The flow meter will count the production of each field every day (it will be installed in a pipeline). The production will be the basic input of the simulation. It will count the profit, the costs and more according to the information of the flow meter. In addition it will include the terms of the contract and the costs that have been paid. By all these parameters the simulation will be able to present in real time the information of a field (taxes, employees, R-factor). By this simulation the company will share some information with the government but not all of them. The government will know the taxes that should be paid and what is the sharing percentage of it. All of the other information could be confidential for the company. Furthermore, oil company could control the R-factor by changing the production each day to maximize its sharing percentages and as a result of this the profit. This idea aims to change the way that governments 'control' oil companies and bring a transparency evolution in the industry. With the help of a simulation every country could be next to the company and have a better collaboration.

Keywords: production sharing contracts, transparency, simulation

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Authors: Jared Beard, Ali Baheri

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As autonomous systems become more prominent in society, ensuring their safe application becomes increasingly important. This is clearly demonstrated with autonomous cars traveling through a crowded city or robots traversing a warehouse with heavy equipment. Human environments can be complex, having high dimensional state and action spaces. This gives rise to two problems. One being that analytic solutions may not be possible. The other is that in simulation based approaches, searching the entirety of the problem space could be computationally intractable, ruling out formal methods. To overcome this, approximate solutions may seek to find failures or estimate their likelihood of occurrence. One such approach is adaptive stress testing (AST) which uses reinforcement learning to induce failures in the system. The premise of which is that a learned model can be used to help find new failure scenarios, making better use of simulations. In spite of these failures AST fails to find particularly sparse failures and can be inclined to find similar solutions to those found previously. To help overcome this, multi-fidelity learning can be used to alleviate this overuse of information. That is, information in lower fidelity can simulations can be used to build up samples less expensively, and more effectively cover the solution space to find a broader set of failures. Recent work in multi-fidelity learning has passed information bidirectionally using “knows what it knows” (KWIK) reinforcement learners to minimize the number of samples in high fidelity simulators (thereby reducing computation time and load). The contribution of this work, then, is development of the bidirectional multi-fidelity AST framework. Such an algorithm, uses multi-fidelity KWIK learners in an adversarial context to find failure modes. Thus far, a KWIK learner has been used to train an adversary in a grid world to prevent an agent from reaching its goal; thus demonstrating the utility of KWIK learners in an AST framework. The next step is implementation of the bidirectional multi-fidelity AST framework described. Testing will be conducted in a grid world containing an agent attempting to reach a goal position and adversary tasked with intercepting the agent as demonstrated previously. Fidelities will be modified by adjusting the size of a time-step, with higher-fidelity effectively allowing for more responsive closed loop feedback. Results will compare the single KWIK AST learner with the multi-fidelity algorithm with respect to number of samples, distinct failure modes found, and relative effect of learning after a number of trials.

Keywords: multi-fidelity reinforcement learning, multi-fidelity simulation, safety validation, falsification

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Authors: Madina Hamiane

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Modelling and simulation of an analogy function generator is presented based on a polynomial expansion model. The proposed function generator model is based on a 10th order polynomial approximation of any of the required functions. The polynomial approximations of these functions can then be implemented using basic CMOS circuit blocks. In this paper, a circuit model is proposed that can simultaneously generate many different mathematical functions. The circuit model is designed and simulated with HSPICE and its performance is demonstrated through the simulation of a number of non-linear functions.

Keywords: modelling and simulation, analog function generator, polynomial approximation, CMOS transistors

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Authors: S. Rawashdi, D. Bshouty

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This paper aimed at discussing how to urge middle and high school Arab students in Israel to be aware of the importance of and investing in learning mathematics. In the first phase of the study, three questionnaires were passed to two nine-grade classes, one on Awareness, one on Awakeness and one on Learning. One of the two classes was an outstanding class from a public school (PUBS) of 31 students, and the other a heterogeneous class from a private school (PRIS) with 31 students. The Learning questionnaire which was administrated to the Awareness and Awareness topics was passed to PRIS and the Awareness and Awareness Questionnaires were passed to the PUBS class After two months we passed the post-questionnaire to both classes to validate the long-term impact of the study. The findings of the study show that awakeness and awareness processes have an effect on the math learning process, on its context in students' daily lives and their growing interest in learning math.

Keywords: awakeness, awareness, learning mathematics, pupils

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Authors: W.Appamana, S. Jantasee, P. Siwarasak, T. Mueansichai, C. Kaewbuddee

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Heat transfer is important in chemical engineering field. We have to know how to predict rates of heat transfer in a variety of process situations. Therefore, heat transfer learning is one of the greatest challenges for undergraduate students in chemical engineering. To enhance student learning in classroom, active-learning method was proposed in a single classroom, using problems based on videos and creating video, think-pair-share and jigsaw technique. The result shows that active learning method can prevent copying of the solutions manual for students and improve average examination scores about 5% when comparing with students in traditional section. Overall, this project represents an effective type of class that motivates student-centric learning while enhancing self-motivation, creative thinking and critical analysis among students.

Keywords: active learning, student-created video, self-motivation, creative thinking

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Authors: Okoh Charity N.

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This study investigated the predictive power of preschoolers’ involvement in indoor and outdoor learning activities on their social learning skills in Niger state, Nigeria. Two research questions and two null hypotheses guided the study. Correlational research design was employed in the study. The population of the study consisted of 8,568 Nursery III preschoolers across the 549 preschools in the five Local Education Authorities in Niger State. A sample of 390 preschoolers drawn through multistage sampling procedure. Two instruments; Preschoolers’ Learning Activities Rating Scale (PLARS) and Preschoolers’ Social Learning Skills Rating Scale (PSLSRS) developed by the researcher were used for data collection. The reliability coefficients obtained for the PLARS and PSLSRS were 0.83 and 0.82, respectively. Data collected were analyzed using simple linear regression. Results showed that 37% of preschoolers’ social learning skills are predicted by their involvement in indoor learning activities, which is statistically significant (p < 0.05). It also shows that 11% of preschoolers’ social learning skills are predicted by their involvement in outdoor learning activities, which is statistically significant (p < 0.05). Therefore, it was recommended among others, that government and school administrators should employ qualified teachers who will stand as role models for preschoolers’ social skills development and provide indoor and outdoor activities and materials for preschoolers in schools.

Keywords: preschooler, social learning, indoor activities, outdoor activities

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Authors: Lin Li, Farshad Amini

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The flipped classroom has been introduced to promote collaborative learning and higher-order learning objectives. In contrast to the traditional classroom, the flipped classroom has students watch prerecorded lecture videos before coming to class and then “class becomes the place to work through problems, advance concepts, and engage in collaborative learning”. In this paper, the active flipped learning combines flipped classroom with active learning that is to establish an active flipped learning (AFL) model, aiming to promote active learning, stress deep learning, encourage student engagement and highlight data-driven personalized learning. Because students have watched the lecture prior to class, contact hours can be devoted to problem-solving and gain a deeper understanding of the subject matter. The instructor is able to provide students with a wide range of learner-centered opportunities in class for greater mentoring and collaboration, increasing the possibility to engage students. Currently, little is known about the extent to which AFL improves engineering students’ performance. This paper presents the preliminary study on the core course of sophomore students in Engineering Mechanics. A series of survey and interviews have been conducted to compare students’ learning engagement, empowerment, self-efficacy, and satisfaction with the AFL. It was found that the AFL model taking advantage of advanced technology is a convenient and professional avenue for engineering students to strengthen their academic confidence and self-efficacy in the Engineering Mechanics by actively participating in learning and fostering their deep understanding of engineering statics and dynamics

Keywords: active learning, engineering mechanics, flipped classroom, performance

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Authors: Elleuch Imen

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In this paper, it propose a new approach for learning Arabic as a foreign language via audio-visual translation, particularly subtitling. The approach consists of developing video sequences appropriate to different levels of learning (from A1 to C2) containing conversations, quizzes, games and others. Each video aims to achieve a specific objective, such as the correct pronunciation of Arabic words, the correct syntactic structuring of Arabic sentences, the recognition of the morphological characteristics of terms and the semantic understanding of statements. The subtitled videos obtained can be incorporated into different Arabic second language learning tools such as Moocs, websites, platforms, etc.

Keywords: arabic foreign language, learning, audio-visuel translation, subtitled videos

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Authors: Suratno

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Metacognition thinking skills should be developed early on in learning. The aim of research builds metacognition thinking skills through collaborative learning with self-evaluation. Approach to action research study involving 32 middle school students in Jember Indonesia. Indicators metacognition skills consist of planning, information management strategies, comprehension monitoring, and debugging strategies. Data were analyzed by t test and analysis of instructional videos. Results of the study here were significant differences in metacognition skills before and after the implementation of collaborative learning with self-evaluation. Analysis instructional video showing the difference artifacts of student learning activities to learning before and after implementation of collaborative learning with self-evaluation. Self-evaluation makes students familiar practice thinking skills metacognition.

Keywords: metacognition, collaborative, evaluation, thinking skills

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Authors: Razieh Arian, Hadi Adibi-Asl

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This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine

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Authors: Stephanie K. Douglas, Gordon R. Haley

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Organizations face increasing disruptions, changes, and uncertainties through the rapid shifts in the economy and business environment. A capacity for resilience is necessary for organizations to survive and thrive in such adverse conditions. Learning is an essential component of an organization's capability for building resilience. Strategic human resource management is a principal component of learning and organizational resilience. To achieve organizational resilience, human resource management strategies must support individual knowledge, skills, and ability development through organizational learning. This study aimed to contribute to the comprehensive knowledge of the relationship between strategic human resource management and organizational learning to build organizational resilience. The organizational learning dimensions of knowledge acquisition, knowledge distribution, knowledge interpretation, and organizational memory can be fostered through human resource management strategies and then aggregated to the organizational level to build resilience.

Keywords: human resource development, human resource management, organizational learning, organizational resilience

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Authors: Mohammed Ali

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In this paper, evaluation of flexible manufacturing system is made under different manufacturing strategies. The objective of this paper is to test the impact of pallets and routing flexibility on system performance operating at different sequencing rules, dispatching rules and at unbalanced load condition. A computer simulation model is developed to evaluate the effects of aforementioned manufacturing strategies on the make-span performance of flexible manufacturing system. The impact of number of pallets is shown with the different levels of routing flexibility. In this paper, the same manufacturing system is modeled under different combination of sequencing and dispatching rules. A series of simulation experiments are conducted and results analyzed. The result of the simulation shows that there is impact of pallets and routing flexibility on the performance of the system.

Keywords: flexibility, flexible manufacturing system, pallets, make-span, simulation

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Authors: Jan Stodt, Christoph Reich

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The usage of machine learning models for prediction is growing rapidly and proof that the intended requirements are met is essential. Audits are a proven method to determine whether requirements or guidelines are met. However, machine learning models have intrinsic characteristics, such as the quality of training data, that make it difficult to demonstrate the required behavior and make audits more challenging. This paper describes an ML audit framework that evaluates and reviews the risks of machine learning applications, the quality of the training data, and the machine learning model. We evaluate and demonstrate the functionality of the proposed framework by auditing an steel plate fault prediction model.

Keywords: audit, machine learning, assessment, metrics

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Authors: Horng-Jyh Chen, Yi-Fang Chen, Chien-Liang Lin

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In this paper, the authors try to investigate the determinants of behavioral intention of the blended e-learning course for senior students at the Active Ageing University in Taiwan. Due to lower proficiency in the use of computers and less experience on learning styles of the blended e-learning course for senior students will be expected quite different from those for most young students. After more than five weeks course for two years the questionnaire survey is executed to collect data for statistical analysis in order to understand the determinants of the behavioral intention for senior students. The object of this study is at one of the Active Ageing University in Taiwan total of 84 senior students in the blended e-learning for the ceramics teaching course. The research results show that only the perceived usefulness of the blended e-learning course has significant positive relationship with the behavioral intention.

Keywords: Active Aging University, blended e-learning, ceramics teaching course, behavioral intention

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Authors: Thi Chang Duyen Can

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Althoughthe COVID-19 epidemic is under control, online education technology in Vietnam will still thrive in the learner-centered trend. Most of the Vietnamese students are now ready to familiarize themselves with and access to online learning. Even in some cases, online learning, if combined with new tools, is far more effective and exciting for students than some traditional instruction. However, little research has been conducted to explore Vietnamese teachers’ difficulties in moderating learner-centered E-learning. Therefore, the study employed the mixed method (n=9) to (i) uncover the challenges faced by Vietnamese teachers in English language online classes using learner-centred approach and (ii) propose the recommendations to improve the quality of online training in universities.

Keywords: learner-centered e-learning, english language classes, teachers' challenges, online learning

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Authors: Raminder Kaur

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This paper considers the emerging area of integrating Virtual Reality (VR) technologies into the teaching of Visual Anthropology, Research Methods, and the Anthropology of Contemporary India in the University of Sussex. If deployed in a critical and self-reflexive manner, there are several advantages to VR-based immersive learning: (i) Based on data available for British schools, it has been noted that ‘Learning through experience can boost knowledge retention by up to 75%’. (ii) It can tutor students to learn with and from virtual worlds, devising new collaborative methods where suited. (iii) It can foster inclusive learning by aiding students with SEN and disabilities who may not be able to explore such areas in the physical world. (iv) It can inspire and instill confidence in students with anxieties about approaching new subjects, realms, or regions. (v) It augments our provision of ‘smart classrooms’ synchronised to the kinds of emerging immersive learning environments that students come from in schools.

Keywords: virtual reality, anthropology, immersive learning, university

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Authors: Glenn A. Palmer, Lorenzo Bowman, Juanita Johnson-Bailey

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The ubiquitous economic upheaval that has gripped the global environment in the past few years displaced many workers through unemployment or underemployment. Globally, this disruption has caused many adult workers to seek additional education or skills to remain competitive, and acquire the ability and options to find gainful employment. While many learners have availed themselves of some opportunities to be retrained and retooled at locations within their communities, others have explored those options through the online learning environment. This paper examines the empirical research that explores the various strategies that are used in the adult online learning community that could also foster transformative learning.

Keywords: online learning, transformational learning, adult education, economic crisis, unemployment

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Authors: Chaima Babi, Said Gadri

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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

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Authors: Rong Wang, Sandra Hasanefendic, Elizabeth von Hauff, Bart Bossink

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Technological learning and learning curve models have been continuously used to estimate the photovoltaics (PV) cost development over time for the climate mitigation targets. They can integrate a number of technological learning sources which influence the learning process. Yet the accuracy and realistic predictions for cost estimations of PV development are still difficult to achieve. This paper develops four hypothetical-alternative learning curve models by proposing different combinations of technological learning sources, including both local and global technology experience and the knowledge stock. This paper specifically focuses on the non-linear relationship between the costs and technological learning source and their dynamic interaction and uses the system dynamics approach to predict a more accurate PV cost estimation for future development. As the case study, the data from China is gathered and drawn to illustrate that the learning curve model that incorporates both the global and local experience is more accurate and realistic than the other three models for PV cost estimation. Further, absorbing and integrating the global experience into the local industry has a positive impact on PV cost reduction. Although the learning curve model incorporating knowledge stock is not realistic for current PV cost deployment in China, it still plays an effective positive role in future PV cost reduction.

Keywords: photovoltaic, system dynamics, technological learning, learning curve

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Authors: Tom O'Mahony

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This article considers the design of a student-centered learning environment in engineering education. The learning environment integrates a number of components, including project-based learning, collaborative learning, two-stage assignments, active learning lectures, and a flipped-classroom. Together these elements place the individual learner and their learning at the center of the environment by focusing on understanding, enhancing relevance, applying learning, obtaining rich feedback, making choices, and taking responsibility. The evolution of this environment from 2014 to the present day is outlined. The impact of this environment on learners and their learning is evaluated via student questionnaires that consist of both open and closed-ended questions. The closed questions indicate that students found the learning environment to be really interesting and enjoyable (rated as 4.7 on a 5 point scale) and encouraged students to adopt a deep approach towards studying the course materials (rated as 4.0 on a 5 point scale). A content analysis of the open-ended questions provides evidence that the project, active learning lectures, and flipped classroom all contribute to the success of this environment. Furthermore, this analysis indicates that the two-stage assessment process, in which feedback is provided between a draft and final assignment, is the key component and the dominant theme. A limitation of the study is the small class size (less than 20 learners per year), but, to some degree, this is compensated for by the longitudinal nature of the study.

Keywords: deep approaches, formative assessment, project-based learning, student-centered learning

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