Search results for: Problem based learning

Authors: Sherly Ferro Lensun

Abstract:

Strategies influence the language abilities of both male and female learners in the learning process. Therefore, learning strategies are one of the critical factors for improving language learning and are essential as part of the initial learning effort. In general, language learning strategies differ between boys and girls. Therefore, this research aims to obtain a model that investigates the relationship between the selection of learning strategies, their frequency of use, and the learner's gender. In addition, we found differences in strategy use and their impact on language ability between males and females. 137 students participated and completed the questionnaire. There were 48 males (35%) and 90 females (65.7%). It was clear that most of the Japanese learners were women. Findings show that most Japanese learners in North Sulawesi used cognitive and social strategies and methods of involving others in learning Japanese.

Keywords: Learning strategies, Japanese Language, Gender by Japanese Learners, North sulawesi.

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Authors: El Falaki Brahim, Khalidi Idrissi Mohammed, Bennani Samir

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E-learning is not restricted to the use of new technologies for the online content, but also induces the adoption of new approaches to improve the quality of education. This quality depends on the ability of these approaches (technical and pedagogical) to provide an adaptive learning environment. Thus, the environment should include features that convey intentions and meeting the educational needs of learners by providing a customized learning path to acquiring a competency concerned In our proposal, we believe that an individualized learning path requires knowledge of the learner. Therefore, it must pass through a personalization of diagnosis to identify precisely the competency gaps to fill, and reduce the cognitive load To personalize the diagnosis and pertinently measure the competency gap, we suggest implementing the formative assessment in the e-learning environment and we propose the introduction of a pre-regulation process in the area of formative assessment, involving its individualization and implementation in e-learning.

Keywords: Competency-Based-Approach, E-learning, Formative assessment, learner model, Modeling, pre-regulation process

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Authors: Hao He, Shaoqian Li

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In this paper, we study the cooperative communications where multiple cognitive radio (CR) transmit-receive pairs competitive maximize their own throughputs. In CR networks, the influences of primary users and the spectrum availability are usually different among CR users. Due to the existence of multiple relay nodes and the different spectrum availability, each CR transmit-receive pair should not only select the relay node but also choose the appropriate channel. For this distributed problem, we propose a game theoretic framework to formulate this problem and we apply a regret-matching learning algorithm which is leading to correlated equilibrium. We further formulate a modified regret-matching learning algorithm which is fully distributed and only use the local information of each CR transmit-receive pair. This modified algorithm is more practical and suitable for the cooperative communications in CR network. Simulation results show the algorithm convergence and the modified learning algorithm can achieve comparable performance to the original regretmatching learning algorithm.

Keywords: cognitive radio, cooperative communication, relay selection, channel choice, regret-matching learning, correlated equilibrium.

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Authors: Bahloul Amel

Abstract:

This study is an attempt to raise the awareness of the stakeholders and the authorities on the sensitivity of Algerian secondary school teachers of English as a Foreign Language about the students’ loss of English language skills learned during formal schooling with effort and at expense and the supposed measures to arrest that loss. Data was collected from secondary school teachers of EFL and analyzed quantitatively using a questionnaire containing open-ended and close-ended questions. The results advocate a consensus about the need for actions to be adopted to make assessment techniques outcome-oriented. Most of the participants were in favor of including curricular activities involving contextualized learning, problem-solving learning critical selfawareness, self and peer-assisted learning, use of computers and internet so as to make learners autonomous.

Keywords: Contextualized learning, EFL, Lifelong learning.

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Authors: Simon Thiel, Stavros Dalakakis, Dieter Roller

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This paper outlines the development of a learning retrieval agent. Task of this agent is to extract knowledge of the Active Semantic Network in respect to user-requests. Based on a reinforcement learning approach, the agent learns to interpret the user-s intention. Especially, the learning algorithm focuses on the retrieval of complex long distant relations. Increasing its learnt knowledge with every request-result-evaluation sequence, the agent enhances his capability in finding the intended information.

Keywords: Reinforcement learning, learning retrieval agent, search in semantic networks.

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Authors: Wang Zhanquan, Yang Zeping, Gu Chunhua, Zhu Fazhi, Guo Weibin

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Recently, Massive Open Online Courses (MOOCs) are becoming the new trend of education. There are many problems under the environment of Database Principle curriculum teaching process in MOOCs, such as teaching ideas and theories which are out of touch with the reality, how to carry out the technical teaching and interactive practice in the MOOCs environment, thus the methods of database course under the environment of MOOCs are proposed. There are three processes to deal with problem solving in the research, which are problems proposed, problems solved, and inductive analysis. The present research includes the design of teaching contents, teaching methods in classroom, flipped classroom teaching mode under the environment of MOOCs, learning flow method and large practice homework. The database designing ability is systematically improved based on the researching methods.

Keywords: Problem solving-driven, MOOCs, teaching art, learning flow.

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Authors: C. Rogerson, E. Scott

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The purpose of this paper is to consider the introduction of online courses to replace the current classroom-based staff training. The current training is practical, and must be completed before access to the financial computer system is authorized. The long term objective is to measure the efficacy, effectiveness and efficiency of the training, and to establish whether a transfer of knowledge back to the workplace has occurred. This paper begins with an overview explaining the importance of staff training in an evolving, competitive business environment and defines the problem facing this particular organization. A summary of the literature review is followed by a brief discussion of the research methodology and objective. The implementation of the alpha version of the online course is then described. This paper may be of interest to those seeking insights into, or new theory regarding, practical interventions of online learning in the real world.

Keywords: Computer-based courses, e-learning, online training, workplace training.

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Authors: Rana AlHajri, Salah Al-Sharhan, Ahmed Al-Hunaiyyan

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Mobile learning is a new learning landscape that offers opportunity for collaborative, personal, informal, and students’ centered learning environment. In implementing any learning system such as a mobile learning environment, learners’ expectations should be taken into consideration. However, there is a lack of studies on this aspect, particularly in the context of Kuwait higher education (HE) institutions. This study focused on how students perceive the use of mobile devices in learning. Although m-learning is considered as an effective educational tool in developed countries, it is not yet fully utilized in Kuwait. The study reports on the results of a survey conducted on 623 HE students in Kuwait to a better understand students' perceptions and opinions about the effectiveness of using mobile learning systems. An analysis of quantitative survey data is presented. The findings indicated that Kuwait HE students are very familiar with mobile devices and its applications. The results also reveal that students have positive perceptions of m-learning, and believe that video-based social media applications enhance the teaching and learning process.

Keywords: Higher education, mobile learning, social media, students’ perceptions.

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Authors: Keisuke Nakamura, Kiyoshi Akama, Hiroshi Mabuchi

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E-Learning systems are used by many learners and teachers. The developer is developing the e-Learning system. However, the developer cannot do system construction to satisfy all of users- demands. We discuss a method of constructing e-Learning systems where learners and teachers can design, try to use, and share extending system functions that they want to use; which may be nally added to the system by system managers.

Keywords: Clause-Rule-Model, database-access, e-Learning, Web-Application.

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Authors: P. Fazel

Abstract:

These days we face with so many advertisements in magazines, those mentioned coaching is pragmatic specialties which help people make change in their lives. Up to know Specialty coaches are not necessarily therapists, consultants or psychologist, thus they may not know psychological theories. The International Coach Federation identifies "facilitating learning and results" as one of its four core coach competencies, without understanding learning theories coaching practice hangs in theoretical abyss. Thus the aim of this article is investigating learning theories within coaching process. Therefore, I reviewed some cognitive and behavioral learning theories and analyzed their contribution with coaching process which has been introduced in mentor coaches and ICF certified coaches' papers and books. The result demonstrated that coaching profession is strongly grounded in learning theories, and it will be strengthened by the validation of theories and evidence-based research as we move forward. Thus, it needs more research in order to applying effective theoretical frameworks.

Keywords: Coaching, Learning theories. Cognitive learning theories, behavioral learning theories.

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Authors: Sirimanee Banjong

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This study aimed to 1) develop pre-service teachers’ leadership skills through camp-based learning, and 2) develop preservice teachers’ teamwork skills through camp-based learning. An applied research methodology was used. The target group was derived from a purposive selection. It involved 32 fourth-year students in Early Childhood Education Program enrolling a course entitled Seminar in Early Childhood Education provided during second semester of academic year 2013. The treatment was camp-based learning activities which applied a PDCA process including four stages: 1) plan, 2) do, 3) check, and 4) act. Research instruments were a learning camp program, a camp-based learning management plan, a 5-level assessment form for leadership skills and a 5-level assessment form for assessing teamwork skills. Data were analyzed using descriptive statistics. Results were: 1) pre-service teachers’ leadership skills yielded the before treatment average score at x= 3.4, S.D.=0.6 2and the after-treatment average score at x 4.29 , S.D.=0.66 pre-service teachers’ teamwork skills yielded the before-treatment average score at x=3.31, S.D.=0.60 and the after-treatment average score at x=4.42, S.D.=0.66 Both differences were statistically significant at the .05 level. Thus, the pre-service teachers’ leadership and teamwork skills were significantly improved through the camp-based learning approach.

Keywords: Learning camp, leadership skills, teamwork skills.

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Authors: M. Athar Hussain, M. Zafar Iqbal., M. Saeed Akhtar

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The fast growing accessibility and capability of emerging technologies have fashioned enormous possibilities of designing, developing and implementing innovative teaching methods in the classroom. The global technological scenario has paved the way to new pedagogies in teaching-learning process focusing on technology based learning environment and its impact on student achievement. The present experimental study was conducted to determine the effectiveness of technology based learning environment on student achievement in English as a foreign language. The sample of the study was 90 students of 10th grade of a public school located in Islamabad. A pretest- posttest equivalent group design was used to compare the achievement of the two groups. A Pretest and A posttest containing 50 items each from English textbook were developed and administered. The collected data were statistically analyzed. The results showed that there was a significant difference between the mean scores of Experimental group and the Control group. The performance of Experimental group was better on posttest scores that indicted that teaching through technology based learning environment enhanced the achievement level of the students. On the basis of the results, it was recommended that teaching and learning through information and communication technologies may be adopted to enhance the language learning capability of the students.

Keywords: English as a Foreign Language, Student Achievement, Technology Based Learning

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Authors: Ying Zhao

Abstract:

Keystroke authentication is a new access control system to identify legitimate users via their typing behavior. In this paper, machine learning techniques are adapted for keystroke authentication. Seven learning methods are used to build models to differentiate user keystroke patterns. The selected classification methods are Decision Tree, Naive Bayesian, Instance Based Learning, Decision Table, One Rule, Random Tree and K-star. Among these methods, three of them are studied in more details. The results show that machine learning is a feasible alternative for keystroke authentication. Compared to the conventional Nearest Neighbour method in the recent research, learning methods especially Decision Tree can be more accurate. In addition, the experiment results reveal that 3-Grams is more accurate than 2-Grams and 4-Grams for feature extraction. Also, combination of attributes tend to result higher accuracy.

Keywords: Keystroke Authentication, Pattern recognition, MachineLearning, Instance-based Learning, Bayesian, Decision Tree.

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Authors: Donald C. Lantu, Henndy Ginting, M. Yorga Permana, Dany M. A. Ramdlany

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We constructed a training program for top-talents of a Bank with Scharmer Theory-U as the model. In this training program, we implemented the action learning perspective, as it is claimed to be the most effective one currently available. In the process, participants were encouraged to be more involved, especially compared to traditional lecturing. The goal of this study is to assess the effectiveness of this particular training. The program consists of six days non-residential workshop within two months. Between each workshop, the participants were involved in the works of action learning group. They were challenged by dealing with the real problem related to their tasks at work. The participants of the program were 30 best talents who were chosen according to their yearly performance. Using paired difference statistical test in the behavioral assessment, we found that the training was not effective to increase participants’ leadership competencies. For the future development program, we suggested to modify the goals of the program toward the next stage of development.

Keywords: Action learning, behaviour, leadership development, Theory-U.

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Authors: Sameerchand Pudaruth, Avinash Mantaye

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E-learning refers to the specific kind of learning experienced within the domain of educational technology, which can be used in or out of the classroom. In this paper, we give an overview of an e-learning platform 'An Innovative Interactive and Online English Platform for Upper Primary Students' is an interactive web-based application which will serve as an aid to the primary school students in Mauritius. The objectives of this platform are to offer quality learning resources for the English subject at our primary level of education, encourage self-learning and hence promote e-learning. The platform developed consists of several interesting features, for example, the English Verb Conjugation tool, Negative Form tool, Interrogative Form tool and Close Test Generator. Thus, this learning platform will be useful at a time where our country is looking for an alternative to private tuition and also, looking forward to increase the pass rate.

Keywords: educational technology, e-learning, Mauritius.

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Authors: Tharwat N. Hijjawi

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Learning oral skills in an Arabic speaking environment is challenging. A blended course (material, activities, and individual/ group work tasks …) was implemented in a module of level B1 for undergraduate students of French as a foreign language in order to increase their opportunities to practice listening and speaking skills. This research investigates the influence of this modality on enhancing active learning and examines the effectiveness of provided strategies. Moreover, it aims at discovering how it allows teacher to flip the traditional classroom and create a learner-centered framework. Which approaches were integrated to motivate students and urge them to search, analyze, criticize, create and accomplish projects? What was the perception of students? This paper is based on the qualitative findings of a questionnaire and a focus group interview with learners. Despite the doubled time and effort both “teacher” and “student” needed, results revealed that the NTIC allowed a shift into a learning paradigm where learners were the “chiefs” of the process. Tasks and collaborative projects required higher intellectual capacities from them. Learners appreciated this experience and developed new life-long learning competencies at many levels: social, affective, ethical and cognitive. To conclude, they defined themselves as motivated young researchers, motivators and critical thinkers.

Keywords: Active learning, critical thinking, inverted classroom, learning paradigm, problem-based.

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Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. However, accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER benefiting from deep learning, especially CNN and VGG16. First, the data are pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning.

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Authors: Reem A. Alebaikan

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The emergence of blended learning has been influenced by the rapid changes in Higher Education within the last few years. However, there is a lack of studies that look into the future of blended learning in the Saudi context. The most likely explanation is that blended learning is relatively new and, with respect to learning in general, under-researched. This study addresses this gap and explores the views of lecturers and students towards the future of blended learning in Saudi Arabia. This study was informed by the interpretive paradigm that appears to be most appropriate to understand and interpret the perceptions of students and instructors towards a new learning environment. While globally there has been considerable research on the perceptions of e-learning and blended learning with its different models, there is plenty of space for further research specifically in the Arab region, and in Saudi Arabia where blended learning is now being introduced.

Keywords: blended learning, higher education.

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Authors: Alper Akın, İbrahim Aydoğdu

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This study presents a hybrid metaheuristic algorithm to obtain optimum designs for steel space buildings. The optimum design problem of three-dimensional steel frames is mathematically formulated according to provisions of LRFD-AISC (Load and Resistance factor design of American Institute of Steel Construction). Design constraints such as the strength requirements of structural members, the displacement limitations, the inter-story drift and the other structural constraints are derived from LRFD-AISC specification. In this study, a hybrid algorithm by using teachinglearning based optimization (TLBO) and harmony search (HS) algorithms is employed to solve the stated optimum design problem. These algorithms are two of the recent additions to metaheuristic techniques of numerical optimization and have been an efficient tool for solving discrete programming problems. Using these two algorithms in collaboration creates a more powerful tool and mitigates each other’s weaknesses. To demonstrate the powerful performance of presented hybrid algorithm, the optimum design of a large scale steel building is presented and the results are compared to the previously obtained results available in the literature.

Keywords: Optimum structural design, hybrid techniques, teaching-learning based optimization, harmony search algorithm, minimum weight, steel space frame.

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Authors: S. Babaie-Kafaki, R. Ghanbari, S.H. Nasseri, E. Ardil

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Bus networks design is an important problem in public transportation. The main step to this design, is determining the number of required terminals and their locations. This is an especial type of facility location problem, a large scale combinatorial optimization problem that requires a long time to be solved. The genetic algorithm (GA) is a search and optimization technique which works based on evolutionary principle of natural chromosomes. Specifically, the evolution of chromosomes due to the action of crossover, mutation and natural selection of chromosomes based on Darwin's survival-of-the-fittest principle, are all artificially simulated to constitute a robust search and optimization procedure. In this paper, we first state the problem as a mixed integer programming (MIP) problem. Then we design a new crossover and mutation for bus terminal location problem (BTLP). We tested the different parameters of genetic algorithm (for a sample problem) and obtained the optimal parameters for solving BTLP with numerical try and error.

Keywords: Bus networks, Genetic algorithm (GA), Locationproblem, Mixed integer programming (MIP).

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Authors: Eyup Yurt, Ahmet Kurnaz, Ismail Sahin

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The purpose of the study is to investigate the education faculty students’ attitudes towards e-learning according to different variables. In current study, the data were collected from 393 students of an education faculty in Turkey. In this study, theattitude towards e‐learning scale and the demographic information form were used to collect data. The collected data were analyzed by t-test, ANOVA and Pearson correlation coefficient. It was found that there is a significant difference in students’ tendency towards e-learning and avoidance from e-learning based on gender. Male students have more positive attitudes towards e-learning than female students. Also, the students who used the internet lesshave higher levels of avoidance from e-learning. Additionally, it is found that there is a positive and significant relationship between the number of personal mobile learning devices and tendency towards e-learning. On the other hand, there is a negative and significant relationship between the number of personal mobile learning devices and avoidance from e-learning. Also, suggestions were presented according to findings.

Keywords: Education faculty students, attitude towards e-learning, gender, daily Internet usage time, m-learning.

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Authors: Marios Poulos, Sozon Papavlasopoulos, V. S. Belesiotis

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In the proposed method for Web page-ranking, a novel theoretic model is introduced and tested by examples of order relationships among IP addresses. Ranking is induced using a convexity feature, which is learned according to these examples using a self-organizing procedure. We consider the problem of selforganizing learning from IP data to be represented by a semi-random convex polygon procedure, in which the vertices correspond to IP addresses. Based on recent developments in our regularization theory for convex polygons and corresponding Euclidean distance based methods for classification, we develop an algorithmic framework for learning ranking functions based on a Computational Geometric Theory. We show that our algorithm is generic, and present experimental results explaining the potential of our approach. In addition, we explain the generality of our approach by showing its possible use as a visualization tool for data obtained from diverse domains, such as Public Administration and Education.

Keywords: Computational Geometry, Education, e-Governance, Semantic Web.

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Authors: Ramin Javadzadeh, Emad Javadzadeh

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Locating the critical slip surface with the minimum factor of safety for a rock slope is a difficult problem. In recent years, some modern global optimization methods have been developed with success in treating various types of problems, but very few of such methods have been applied to rock mechanical problems. In this paper, use of hybrid model based on artificial immune system and cellular learning automata is proposed. The results show that the algorithm is an effective and efficient optimization method with a high level of confidence rate.

Keywords: CLA-AIS, failure surface, optimization methods, rock slope.

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Authors: R. Sharma, M. Gopal

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This paper presents a new problem solving approach that is able to generate optimal policy solution for finite-state stochastic sequential decision-making problems with high data efficiency. The proposed algorithm iteratively builds and improves an approximate Markov Decision Process (MDP) model along with cost-to-go value approximates by generating finite length trajectories through the state-space. The approach creates a synergy between an approximate evolving model and approximate cost-to-go values to produce a sequence of improving policies finally converging to the optimal policy through an intelligent and structured search of the policy space. The approach modifies the policy update step of the policy iteration so as to result in a speedy and stable convergence to the optimal policy. We apply the algorithm to a non-holonomic mobile robot control problem and compare its performance with other Reinforcement Learning (RL) approaches, e.g., a) Q-learning, b) Watkins Q(λ), c) SARSA(λ).

Keywords: Markov Decision Process (MDP), Mobile robot, Policy iteration, Simulation.

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Authors: Pimploi Tirastittam, Suppara Charoenpoom

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Nowadays the asynchronous learning has granted the permission to the anywhere and anything learning via the technology and E-media which give the learner more convenient. This research is about the design of the blended and online learning for the asynchronous learning of the process management subject in order to create the prototype of this subject asynchronous learning which will create the easiness and increase capability in the learning. The pattern of learning is the integration between the in-class learning and online learning via the internet. This research is mainly focused on the online learning and the online learning can be divided into 5 parts which are virtual classroom, online content, collaboration, assessment and reference material. After the system design was finished, it was evaluated and tested by 5 experts in blended learning design and 10 students which the user’s satisfaction level is good. The result is as good as the assumption so the system can be used in the process management subject for a real usage.

Keywords: Blended Learning, Asynchronous Learning, Design, Process Management.

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Authors: Seyed Habib A. Rahmati

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During last decades, developing multi-objective evolutionary algorithms for optimization problems has found considerable attention. Flexible job shop scheduling problem, as an important scheduling optimization problem, has found this attention too. However, most of the multi-objective algorithms that are developed for this problem use nonprofessional approaches. In another words, most of them combine their objectives and then solve multi-objective problem through single objective approaches. Of course, except some scarce researches that uses Pareto-based algorithms. Therefore, in this paper, a new Pareto-based algorithm called controlled elitism non-dominated sorting genetic algorithm (CENSGA) is proposed for the multi-objective FJSP (MOFJSP). Our considered objectives are makespan, critical machine work load, and total work load of machines. The proposed algorithm is also compared with one the best Pareto-based algorithms of the literature on some multi-objective criteria, statistically.

Keywords: Scheduling, Flexible job shop scheduling problem, controlled elitism non-dominated sorting genetic algorithm

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Authors: Chin-Cheh Yi, Pei-Wen Liao, Chin-Feng Huang, I-Hui Hwang

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With the proliferation of mobile computing technology, mobile learning (m-learning) will play a vital role in the rapidly growing electronic learning market. However, the acceptance of m-learning by individuals is critical to the successful implementation of m-learning systems. Thus, there is a need to research the factors that affect users- intention to use m-learning. Based on an updated information system (IS) success model, data collected from 350 respondents in Taiwan were tested against the research model using the structural equation modeling approach. The data collected by questionnaire were analyzed to check the validity of constructs. Then hypotheses describing the relationships between the identified constructs and users- satisfaction were formulated and tested.

Keywords: m-learning, information system success, users' satisfaction, perceived value.

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Classification, Bayesian network; structure learning, K2 algorithm, expert knowledge, surface water analysis.

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Authors: Nicholas Milburn, Yu Liang, Dalei Wu

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Athlete performance scoring within the climbing domain presents interesting challenges as the sport does not have an objective way to assign skill. Assessing skill levels within any sport is valuable as it can be used to mark progress while training, and it can help an athlete choose appropriate climbs to attempt. Machine learning-based methods are popular for complex problems like this. The dataset available was composed of dynamic force data recorded during climbing; however, this dataset came with challenges such as data scarcity, imbalance, and it was temporally heterogeneous. Investigated solutions to these challenges include data augmentation, temporal normalization, conversion of time series to the spectral domain, and cross validation strategies. The investigated solutions to the classification problem included light weight machine classifiers KNN and SVM as well as the deep learning with CNN. The best performing model had an 80% accuracy. In conclusion, there seems to be enough information within climbing force data to accurately categorize climbers by skill.

Keywords: Classification, climbing, data imbalance, data scarcity, machine learning, time sequence.

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Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: Intrusion prevention, network security, optimal policy, Q-learning.

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