Search results for: language learning model.

Authors: Aji P. Wibawa, Andrew Nafalski, Neil Murray, Wayan F. Mahmudy

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Parallel text alignment is proposed as a way of aligning bahasa Indonesia to words in Javanese. Since the one-to-one word translator does not have the facility to translate pragmatic aspects of Javanese, the parallel text alignment model described uses a phrase pair combination. The algorithm aligns the parallel text automatically from the beginning to the end of each sentence. Even though the results of the phrase pair combination outperform the previous algorithm, it is still inefficient. Recording all possible combinations consume more space in the database and time consuming. The original algorithm is modified by applying the edit distance coefficient to improve the data-storage efficiency. As a result, the data-storage consumption is 90% reduced as well as its learning period (42s).

Keywords: Parallel text alignment, phrase pair combination, edit distance coefficient, Javanese-Indonesian language.

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Authors: Sung-Hae Jun, Kyung-Whan Oh

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Statistical learning theory was developed by Vapnik. It is a learning theory based on Vapnik-Chervonenkis dimension. It also has been used in learning models as good analytical tools. In general, a learning theory has had several problems. Some of them are local optima and over-fitting problems. As well, statistical learning theory has same problems because the kernel type, kernel parameters, and regularization constant C are determined subjectively by the art of researchers. So, we propose an evolutionary statistical learning theory to settle the problems of original statistical learning theory. Combining evolutionary computing into statistical learning theory, our theory is constructed. We verify improved performances of an evolutionary statistical learning theory using data sets from KDD cup.

Keywords: Evolutionary computing, Local optima, Over-fitting, Statistical learning theory

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

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Artificial Intelligence (AI), specifically Reinforcement Learning (RL), has proven helpful in many control path planning technologies by maximizing and enhancing their performance, such as navigation systems. Since it learns from experience by interacting with the environment to determine the optimal policy, the optimal policy takes the best action in a particular state, accounting for the long-term rewards. Most navigation systems focus primarily on "arriving faster," overlooking safety and efficiency while estimating the optimum path, as safety and efficiency are essential factors when planning for a long-distance journey. This paper represents an RL control model that proposes a control mechanism for improving navigation systems. Also, the model could be applied to other control path planning applications because it is adjustable and can accept different properties and parameters. However, the navigation system application has been taken as a case and evaluation study for the proposed model. The model utilized a Q-learning algorithm for training and updating the policy. It allows the agent to analyze the quality of an action made in the environment to maximize rewards. The model gives the ability to update rewards regularly based on safety and efficiency assessments, allowing the policy to consider the desired safety and efficiency benefits while making decisions, which improves the quality of the decisions taken for path planning compared to the conventional RL approaches.

Keywords: Artificial intelligence, control system, navigation systems, reinforcement learning.

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Authors: Shinpei Ogata, Yoshitaka Aoki, Hirotaka Okuda, Saeko Matsuura

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A key to success of high quality software development is to define valid and feasible requirements specification. We have proposed a method of model-driven requirements analysis using Unified Modeling Language (UML). The main feature of our method is to automatically generate a Web user interface mock-up from UML requirements analysis model so that we can confirm validity of input/output data for each page and page transition on the system by directly operating the mock-up. This paper proposes a support method to check the validity of a data life cycle by using a model checking tool “UPPAAL" focusing on CRUD (Create, Read, Update and Delete). Exhaustive checking improves the quality of requirements analysis model which are validated by the customers through automatically generated mock-up. The effectiveness of our method is discussed by a case study of requirements modeling of two small projects which are a library management system and a supportive sales system for text books in a university.

Keywords: CRUD, Model Checking, Model Driven Development, Requirements Analysis, Unified Modeling Language, UPPAAL.

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Authors: Eleni Galiotou, Angela Ralli

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In this paper we propose a computational model for the representation and processing of morpho-phonological phenomena in a natural language, like Modern Greek. We aim at a unified treatment of inflection, compounding, and word-internal phonological changes, in a model that is used for both analysis and generation. After discussing certain difficulties cuase by well-known finitestate approaches, such as Koskenniemi-s two-level model [7] when applied to a computational treatment of compounding, we argue that a morphology-based model provides a more adequate account of word-internal phenomena. Contrary to the finite state approaches that cannot handle hierarchical word constituency in a satisfactory way, we propose a unification-based word grammar, as the nucleus of our strategy, which takes into consideration word representations that are based on affixation and [stem stem] or [stem word] compounds. In our formalism, feature-passing operations are formulated with the use of the unification device, and phonological rules modeling the correspondence between lexical and surface forms apply at morpheme boundaries. In the paper, examples from Modern Greek illustrate our approach. Morpheme structures, stress, and morphologically conditioned phoneme changes are analyzed and generated in a principled way.

Keywords: Morpho-Phonology, Natural Language Processing.

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Authors: Bahloul Amel

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The present study debates students’ perceptions of the use of technology in learning English as a Foreign Language. Its aim is to explore and understand students’ preparation and presentation of Posters, PowerPoint and Animated Videos by drawing attention to visual and oral elements. The data is collected through observations and semi-structured interviews and analyzed through phenomenological data analysis steps. The themes emerged from the data, visual learning satisfaction in using information and communication technology, providing structure to oral presentation, learning from peers’ presentations, draw attention to using Posters, PowerPoint and Animated Videos as each supports visual learning and organization of thoughts in oral presentations.

Keywords: Animated Videos, EFL, Posters, PowerPoint presentations, Visual Learning.

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Authors: Kathaleeya Chanda, Panupong Chanplin, Suppara Charoenpoom

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This purposes of the development of creative instruction model through digital media are to: 1) enable learners to learn from instruction media application; 2) help learners implementing instruction media correctly and appropriately; and 3) facilitate learners to apply technology for searching information and practicing skills to implement technology creatively. The sample group consists of 130 cases of secondary students studying in Bo Kluea School, Bo Kluea Nuea Sub-district, Bo Kluea District, Nan Province. The probability sampling was selected through the simple random sampling and the statistics used in this research are percentage, mean, standard deviation and one group pretest – posttest design. The findings are summarized as follows: The congruence index of instruction media for occupation and technology subjects is appropriate. By comparing between learning achievements before implementing the instruction media and learning achievements after implementing the instruction media, it is found that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. For the learning achievements from instruction media implementation, pretest mean is 16.24 while posttest mean is 26.28. Besides, pretest and posttest results are compared and differences of mean are tested, the test results show that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. This can be interpreted that the learners achieve better learning progress.

Keywords: Teaching learning model, digital media, creative instruction model, facilitate learners.

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Authors: Boyan Bontchev, Dessislava Vassileva

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Internet computer games turn to be more and more attractive within the context of technology enhanced learning. Educational games as quizzes and quests have gained significant success in appealing and motivating learners to study in a different way and provoke steadily increasing interest in new methods of application. Board games are specific group of games where figures are manipulated in competitive play mode with race conditions on a surface according predefined rules. The article represents a new, formalized model of traditional quizzes, puzzles and quests shown as multimedia board games which facilitates the construction process of such games. Authors provide different examples of quizzes and their models in order to demonstrate the model is quite general and does support not only quizzes, mazes and quests but also any set of teaching activities. The execution process of such models is explained and, as well, how they can be useful for creation and delivery of adaptive e-learning courseware.

Keywords: Quiz, board game, e-learning, adaptive.

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Authors: Christopher C. Anyadubalu

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This study investigated students- perception of self efficacy and anxiety in acquiring English language, and consequently examined the relationship existing among the independent variables, confounding variables and students- performances in the English language. The researcher tested the research hypotheses using a sample group of 318 respondents out of the population size of 400 students. The results obtained revealed that there was a significant moderate negative relationship between English language anxiety and performance in English language, but no significant relationship between self-efficacy and English language performance, among the middle-school students. There was a significant moderate negative relationship between English language anxiety and self-efficacy. It was discovered that general self-efficacy and English language anxiety represented a significantly more powerful set of predictors than the set of confounding variables. Thus, the study concluded that English language anxiety and general self-efficacy were significant predictors of English language performance among middle-school students in Satri Si Suriyothai School.

Keywords: Anxiety, English Language Anxiety, Performance inEnglish Language, Self Efficacy.

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Authors: Liliana Mâţă

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The focus of the study is to understand the factors of curriculum innovation from the perspective of Language teacher education. The overall aim of the study is to investigate Language educators- perceptions of factors of curriculum innovation. In the theoretical framework the main focus is on discussion about different curriculum approaches for language teacher education and limiting and facilitating factors of innovation. In order to achieve the aim of the study, an observational research is employed. The empirical basis of the study consists of questionnaire with sixty-three language teachers from eight Romanian higher education institutions. The findings reveal variation in Language teachers- conceptions of the dominant factors of curricular innovation.

Keywords: curriculum innovation, factors, Language teacher education

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Authors: A. T. Zaki

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The flipped classroom approach as a mode of blended learning was formally introduced to students of the English language modules at the British University in Egypt (BUE) at the start of the academic year 2015/2016. This paper aims to study the impact of the flipped classroom approach after three semesters of implementation. It will restrict itself to the examination of students’ achievement rates, student satisfaction, and how different student cohorts have benefited differently from the flipped practice. The paper concludes with recommendations of how the experience can be further developed.

Keywords: Achievement rates, developmental experience, Egypt, flipped classroom, higher education, student cohorts, student satisfaction.

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: Deep learning, data mining, gender predication, MOOCs.

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Authors: Leon Pan

Abstract:

The first programming course within post-secondary education has long been recognized as a challenging endeavor for both educators and students alike. Historically, these courses have exhibited high failure rates and a notable number of dropouts. Instructors often lament students' lack of effort on their coursework, and students often express frustration that the teaching methods employed are not effective. Drawing inspiration from the successful principles of Extreme Programming, this study introduces an approach—the Extremes-based teaching model—aimed at enhancing the teaching of introductory programming courses. To empirically determine the effectiveness of the model, a comparison was made between a section taught using the extreme-based model and another utilizing traditional teaching methods. Notably, the extreme-based teaching class required students to work collaboratively on projects, while also demanding continuous assessment and performance enhancement within groups. This paper details the application of the extreme-based model within the post-secondary online classroom context and presents the compelling results that emphasize its effectiveness in advancing the teaching and learning experiences. The extreme-based model led to a significant increase of 13.46 points in the weighted total average and a commendable 10% reduction in the failure rate.

Keywords: Extreme-based teaching model, innovative pedagogical methods, project-based learning, team-based learning.

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Authors: Ratima Damkham, Natasha Dejdumrong, Priyakorn Pusawiro

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This paper explored the solution in game design to help game designers in the educational game designing using digital educational game model canvas (DEGMC) and digital educational game form (DEGF) based on Outcome-based Education program. DEGMC and DEGF can help designers develop an overview of the game while designing and planning their own game. The way to clearly assess players’ ability from learning outcomes and support their game learning design is by using the tools. Designers can balance educational content and entertainment in designing a game by using the strategies of the Business Model Canvas and design the gameplay and players’ ability assessment from learning outcomes they need by referring to the Constructive Alignment. Furthermore, they can use their design plan in this research to write their Game Design Document (GDD). The success of the research was evaluated by four experts’ perspectives in the education and computer field. From the experiments, the canvas and form helped the game designers model their game according to the learning outcomes and analysis of their own game elements. This method can be a path to research an educational game design in the future.

Keywords: Constructive alignment, constructivist theory, educational game, outcome-based education.

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Authors: Agnès Garletti

Abstract:

Our research aims at helping the tutor on line to evaluate the student-s cognitive processes. The student is a learner in French as a Second Language who studies an on-line socio-cognitive scenario in written communication. In our method, these cognitive processes are defined. For that, the language abilities and learning tasks are associated to cognitive operation. Moreover, the found cognitive processes are named with specific terms. The result was to create an instrumental pattern to question the learner about the cognitive processes used to build an item of written comprehension. Our research follows the principles of the third historical generation of studies on the cognitive activity of the text comprehension. The strength of our instrumental pattern stands in the precision and the logical articulation of the questions to the learner. However, the learner-s answers can still be subjective but the precision of the instrument restricts it.

Keywords: Cognitive processes, Evaluation pattern, French as asecond language, Socio-cognitive scenario, Written comprehension.

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: Big data, bus headway prediction, machine learning, public transportation.

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Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

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Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: BERT, chatbot, cryptocurrency, deep learning.

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Authors: Marcio Leal, Marta Villamil

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Computacional recognition of sign languages aims to allow a greater social and digital inclusion of deaf people through interpretation of their language by computer. This article presents a model of recognition of two of global parameters from sign languages; hand configurations and hand movements. Hand motion is captured through an infrared technology and its joints are built into a virtual three-dimensional space. A Multilayer Perceptron Neural Network (MLP) was used to classify hand configurations and Dynamic Time Warping (DWT) recognizes hand motion. Beyond of the method of sign recognition, we provide a dataset of hand configurations and motion capture built with help of fluent professionals in sign languages. Despite this technology can be used to translate any sign from any signs dictionary, Brazilian Sign Language (Libras) was used as case study. Finally, the model presented in this paper achieved a recognition rate of 80.4%.

Keywords: Sign language recognition, computer vision, infrared, artificial neural network, dynamic time warping.

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Authors: Fei Ping Por, Soon Fook Fong

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The proposed Multimedia Pronunciation Learning Management System (MPLMS) in this study is a technology with profound potential for inducing improvement in pronunciation learning. The MPLMS optimizes the digitised phonetic symbols with the integration of text, sound and mouth movement video. The components are designed and developed in an online management system which turns the web to a dynamic user-centric collection of consistent and timely information for quality sustainable learning. The aim of this study is to design and develop the MPLMS which serves as an innovative tool to improve English pronunciation. This paper discusses the iterative methodology and the three-phase Alessi and Trollip model in the development of MPLMS. To align with the flexibility of the development of educational software, the iterative approach comprises plan, design, develop, evaluate and implement is followed. To ensure the instructional appropriateness of MPLMS, the instructional system design (ISD) model of Alessi and Trollip serves as a platform to guide the important instructional factors and process. It is expected that the results of future empirical research will support the efficacy of MPLMS and its place as the premier pronunciation learning system.

Keywords: Design, development, multimedia, pronunciation, learning management system

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Authors: Hirofumi Miyajima, Kazuya Kishida, Noritaka Shigei, Hiromi Miyajima

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Most of self-tuning fuzzy systems, which are automatically constructed from learning data, are based on the steepest descent method (SDM). However, this approach often requires a large convergence time and gets stuck into a shallow local minimum. One of its solutions is to use fuzzy rule modules with a small number of inputs such as DIRMs (Double-Input Rule Modules) and SIRMs (Single-Input Rule Modules). In this paper, we consider a (generalized) DIRMs model composed of double and single-input rule modules. Further, in order to reduce the redundant modules for the (generalized) DIRMs model, pruning and generative learning algorithms for the model are suggested. In order to show the effectiveness of them, numerical simulations for function approximation, Box-Jenkins and obstacle avoidance problems are performed.

Keywords: Box-Jenkins’s problem, Double-input rule module, Fuzzy inference model, Obstacle avoidance, Single-input rule module.

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Authors: C. Ardil

Abstract:

In this paper, we introduce an e-collaborative learning circles methodology which utilizes the information and communication technologies (ICTs) in e-educational processes. In e-collaborative learning circles methodology, the teachers and students announce their research projects on various mailing lists and discussion boards using available ICTs. The teachers & moderators and students who are already members of the e-forums, discuss the project proposals in their classrooms sent out by the potential global partner schools and return the requested feed back to the proposing school(s) about their level of the participation and contribution in the research. In general, an e-collaborative learning circle project is implemented with a small and diverse group (usually 8-10 participants) from around the world. The students meet regularly over a period of weeks/months through the ICTs during the ecollaborative learning process. When the project is completed, a project product (e-book / DVD) is prepared and sent to the circle members. In this research, when taking into account the interests and motivation of the participating students with the facilitating role of the teacher(s), the students in each circle do research to obtain new data and information, thus enabling them to have the opportunity to meet both different cultures and international understandings across the globe. However, while the participants communicate along with the members in the circle they also practice and develop their communication language skills. Finally, teachers and students find the possibility to develop their skills in using the ICTs as well.

Keywords: Distance Education, Online Learning, Web BasedLearning, Learning Circles, e-Collaborative Learning Circles

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Authors: Ava Dodd, Jonathan Adams

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The purpose of this study is to explore the characteristics of developing a machine learning application using synthetic data. The study is structured to develop the application for the purpose of deploying the computer vision model. The findings discuss the realities of attempting to develop a computer vision model for practical purpose, and detail the processes, tools and techniques that were used to meet accuracy requirements. The research reveals that synthetic data represent another variable that can be adjusted to improve the performance of a computer vision model. Further, a suite of tools and tuning recommendations are provided.

Keywords: computer vision, machine learning, synthetic data, YOLOv4

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Authors: Sobhy Fathy A. Hashesh

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This study aimed at investigating the effect of Andalus Knowledge Phases and Times (ANPT) model of learning and the effect of 'Intel Education Contribution in ANPT' on the development of students’ academic performance and emotional quotient. The society of the study composed of Andalus Private Schools, elementary school students (N=700), while the sample of the study composed of four randomly assigned groups (N=80) with one experimental group and one control group to study "ANPT" effect and the "Intel Contribution in ANPT" effect respectively. The study followed the quantitative and qualitative approaches in collecting and analyzing data to answer the study questions. Results of the study revealed that there were significant statistical differences between students’ academic performances and emotional quotients for the favor of the experimental groups. The study recommended applying this model on different educational variables and on other age groups to generate more data leading to more educational results for the favor of students’ learning outcomes.

Keywords: ANPT, Flipped Classroom, 5Es learning Model, Kagan structures.

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Authors: Wichuda Kunnu, Aungkana Sukwises

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Audio-lingual Method (ALM) is a teaching approach that is claimed that ineffective for teaching second/foreign languages. Because some linguists and second/foreign language teachers believe that ALM is a rote learning style. However, this study is done on a belief that ALM will be able to solve Thais’ English speaking problem. This paper aims to report the findings on teaching English speaking to adult learners with an “adapted ALM”, one distinction of which is to use Thai as the medium language of instruction. The participants are consisted of 9 adult learners. They were allowed to speak English more freely using both the materials presented in the class and their background knowledge of English. At the end of the course, they spoke English more fluently, more confidently, to the extent that they applied what they learnt both in and outside the class.

Keywords: Teaching English, Audio Lingual Method.

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Authors: Prashanth C.M., K. Chandrashekar Shet

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In recent past, the Unified Modeling Language (UML) has become the de facto industry standard for object-oriented modeling of the software systems. The syntax and semantics rich UML has encouraged industry to develop several supporting tools including those capable of generating deployable product (code) from the UML models. As a consequence, ensuring the correctness of the model/design has become challenging and extremely important task. In this paper, we present an approach for automatic verification of protocol model/design. As a case study, Session Initiation Protocol (SIP) design is verified for the property, “the CALLER will not converse with the CALLEE before the connection is established between them ". The SIP is modeled using UML statechart diagrams and the desired properties are expressed in temporal logic. Our prototype verifier “UML-SMV" is used to carry out the verification. We subjected an erroneous SIP model to the UML-SMV, the verifier could successfully detect the error (in 76.26ms) and generate the error trace.

Keywords: Unified Modeling Language, Statechart, Verification, Protocol Design, Model Checking.

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Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

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In this contribution a newly developed elearning environment is presented, which incorporates Intelligent Agents and Computational Intelligence Techniques. The new e-learning environment is constituted by three parts, the E-learning platform Front-End, the Student Questioner Reasoning and the Student Model Agent. These parts are distributed geographically in dispersed computer servers, with main focus on the design and development of these subsystems through the use of new and emerging technologies. These parts are interconnected in an interoperable way, using web services for the integration of the subsystems, in order to enhance the user modelling procedure and achieve the goals of the learning process.

Keywords: E-learning environments, intelligent agents, user modeling, Bayesian Networks, computational intelligence.

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Authors: Hy Dang, Bo Mei

Abstract:

The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: Classification, machine learning, time representation, stock prediction.

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Authors: Norazah Yusof, Andi Besse Firdausiah Mansur

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Social learning network analysis has drawn attention for most researcher on e-learning research domain. This is due to the fact that it has the capability to identify the behavior of student during their social interaction inside e-learning. Normally, the social network analysis (SNA) is treating the students' interaction merely as node and edge with less meaning. This paper focuses on providing an ontology structure of e-learning Moodle that can enrich the relationships among students, as well as between the students and the teacher. This ontology structure brings great benefit to the future development of e-learning system.

Keywords: Ontology, e-learning, © Learning Network, Moodle.

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Authors: Saule Mussabekova, Samal Abzhanova

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The Kazakh Language Fluency Test, based on the IELTS exam, was implemented in 2012 at Nazarbayev University in Astana, Kazakhstan. We would like to share our experience in developing this exam and some exam results with other language instructors. In this paper, we will cover all these peculiarities and their related issues. The Kazakh Language Fluency Test is a young exam. During its development, we faced many difficulties. One of the goals of the university and the country is to encourage fluency in the Kazakh language for all citizens of the Republic. Nazarbayev University has introduced a Kazakh language program to assist in achieving this goal. This policy is one-step in ensuring that NU students have a thorough understanding of the Kazakh language through a fluency test based on the International English Language Testing System (IELTS). The Kazakh Language Fluency Test exam aims to determine student’s knowledge of Kazakh language. The fact is that there are three types of students at Nazarbayev University: Kazakh-speaking heritage learners, Russian-speaking and English-speaking students. Unfortunately, we have Kazakh students who do not speak Kazakh. All students who finished school with Russian language instruction are given Kazakh Language Fluency Test in order to determine their Kazakh level. After the test exam, all students can choose appropriate Kazakh course: Basic Kazakh, Intermediate Kazakh and Upper-Intermediate Kazakh. The Kazakh Language Fluency Test consists of four parts: Listening, Reading, Writing and Speaking. They are taken on the same day in the abovementioned order.

Keywords: Diagnostic language test, Kazakh language, placement test, test result.

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Authors: Abdullah A. H. Alzahrani, Majd Zohri Yafi, Fawaz K. Alarfaj

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Unified Modelling Language (UML) is a software modelling language that is widely used and accepted. One significant drawback, of which, is that the language lacks formality. This makes carrying out any type of rigorous analysis difficult process. Many researchers attempt to introduce their approaches to formalise UML diagrams. However, it is always hard to decide what language and/or approach to use. Therefore, in this paper, we highlight some of the advantages and disadvantages of number of those approaches. We also try to compare different counterpart approaches. In addition, we draw some guidelines to help in choosing the suitable approach. Special concern is given to the formalisation of the static aspects of UML shown is class diagrams.

Keywords: UML formalisation, Object Constraints Language (OCL), Description Logic (DL), Z language.

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