Search results for: language arts

Authors: Safiah A. Madkhali

Abstract:

The grammatical relation object has not attracted the same attention in the literature as subject has. Where there is a clearly monotransitive verb such as kick, the criteria for identifying the grammatical relation may converge. However, the term object is also used to refer to phenomena that do not subsume all, or even most, of the recognized properties of the canonical object. Instances of such phenomena include non-canonical objects such as the ones in the so-called double-object construction i.e., the indirect object and the direct object as in (He bought his dog a new collar). In this paper, it is demonstrated how criteria of identifying the grammatical relation object that are found in the theoretical and typological literature can be applied to Arabic. Also, further language-specific criteria are here derived from the regularities of the canonical object in the language. The criteria established in this way are then applied to the non-canonical objects to demonstrate how far they conform to, or diverge from, the canonical object. Contrary to the claim that the direct object is more similar to the canonical object than is the indirect object, it was found that it is, in fact, the indirect object rather than the direct object that shares most of the aspects of the canonical object in monotransitive clauses.

Keywords: Canonical objects, double-object constructions, direct object, indirect object, non-canonical objects.

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Authors: Zainab M. Musa, Nordin M. A. Rahman, Julaily A. Jusoh

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Digital reference service is when a traditional library reference service is provided electronically. In most cases users do not get full satisfaction from using digital reference service due to variety of reasons. This paper discusses the formal specification of web services applications for digital reference services (WSDRS). WSDRS is an informal model that claims to reduce the problems of digital reference services in libraries. It uses web services technology to provide efficient digital way of satisfying users’ need in the reference section of libraries. Informal model is in natural language which is inconsistent and ambiguous that may cause difficulties to the developers of the system. In order to solve this problem we decided to convert the informal specifications into formal specifications. This is supposed to reduce the overall development time and cost. We use Z language to develop the formal model and verify it with Z/EVES theorem prover tool.

Keywords: Formal, specifications, web services, digital reference services.

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Authors: Sandra Valdez-Hernández

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Motivation is one of the most important factors when teaching language. Most institutions, at least in Mexico, pay low attention to the types of motivation students have when they are studying English; however, considering the motivation they have may lead to better understanding about their needs and purposes for learning English and the professors may understand and focus on their interests for making them persist in action through the course. This topic has been widely investigated in different countries, but more research needs to be done in Mexico to shed light on this area of potential impact. This quantitative study examines how students (n = 180) at a Rural University in Quintana Roo perceive their different types of motivation, intrinsic and extrinsic, instrumental, and integrative and the attitudes for the language. The findings reveal a high degree of intrinsic and instrumental motivation and provide insights into the perceived attitudes for learning English. Finding ways to persist in action may lead to better comprehending the reasons for learning English.

Keywords: Attitudes for motivation, types of motivation, Extrinsic and Intrinsic motivation, instrumental and integrative motivation.

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Authors: Rose Shayeghi, Pejman Hosseinioun

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The Multiple Intelligences theory characterizes human intelligence as a multifaceted entity that exists in all human beings with varying degrees. The most important contribution of this theory to the field of English Language Teaching (ELT) is its role in identifying individual differences and designing more learnercentered programs. The present study aims at investigating the relationship between different elements of multiple intelligence and grammar scores. To this end, 63 female Iranian EFL learner selected from among intermediate students participated in the study. The instruments employed were a Nelson English language test, Michigan Grammar Test, and Teele Inventory for Multiple Intelligences (TIMI). The results of Pearson Product-Moment Correlation revealed a significant positive correlation between grammatical accuracy and linguistic as well as interpersonal intelligence. The results of Stepwise Multiple Regression indicated that linguistic intelligence contributed to the prediction of grammatical accuracy.

Keywords: Multiple intelligence, grammar, ELT, EFL, TIMI.

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Authors: Ahmed Tawfik, Fausto Giunchiglia, Vincenzo Maltese

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Ontologies provide a common understanding of a specific domain of interest that can be communicated between people and used as background knowledge for automated reasoning in a wide range of applications. In this paper, we address the design of multilingual ontologies following well-defined knowledge engineering methodologies with the support of novel collaborative development approaches. In particular, we present a collaborative platform which allows ontologies to be developed incrementally in multiple languages. This is made possible via an appropriate mapping between language independent concepts and one lexicalization per language (or a lexical gap in case such lexicalization does not exist). The collaborative platform has been designed to support the development of the Universal Knowledge Core, a multilingual ontology currently in English, Italian, Chinese, Mongolian, Hindi and Bangladeshi. Its design follows a workflow-based development methodology that models resources as a set of collaborative objects and assigns customizable workflows to build and maintain each collaborative object in a community driven manner, with extensive support of modern web 2.0 social and collaborative features.

Keywords: Knowledge Diversity, Knowledge Representation, Ontology Development.

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Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: Artificial intelligence, depression detection, facial emotion recognition, natural language processing, mental disorder.

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Authors: László Lengyel, Tihamér Levendovszky, Gergely Mezei, Hassan Charaf

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Graph rewriting-based visual model processing is a widely used technique for model transformation. Visual model transformations often need to follow an algorithm that requires a strict control over the execution sequence of the transformation steps. Therefore, in Visual Model Processors (VMPs) the execution order of the transformation steps is crucial. This paper presents the visual control flow support of Visual Modeling and Transformation System (VMTS), which facilitates composing complex model transformations of simple transformation steps and executing them. The VMTS Visual Control Flow Language (VCFL) uses stereotyped activity diagrams to specify control flow structures and OCL constraints to choose between different control flow branches. This paper introduces VCFL, discusses its termination properties and provides an algorithm to support the termination analysis of VCFL transformations.

Keywords: Control Flow, Metamodel-Based Visual ModelTransformation, OCL, Termination Properties, UML.

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Authors: Othman O. Khalifa, Zakiah Hanim Ahmad, Teddy Surya Gunawan

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This paper presents a rule-based text- to- speech (TTS) Synthesis System for Standard Malay, namely SMaTTS. The proposed system using sinusoidal method and some pre- recorded wave files in generating speech for the system. The use of phone database significantly decreases the amount of computer memory space used, thus making the system very light and embeddable. The overall system was comprised of two phases the Natural Language Processing (NLP) that consisted of the high-level processing of text analysis, phonetic analysis, text normalization and morphophonemic module. The module was designed specially for SM to overcome few problems in defining the rules for SM orthography system before it can be passed to the DSP module. The second phase is the Digital Signal Processing (DSP) which operated on the low-level process of the speech waveform generation. A developed an intelligible and adequately natural sounding formant-based speech synthesis system with a light and user-friendly Graphical User Interface (GUI) is introduced. A Standard Malay Language (SM) phoneme set and an inclusive set of phone database have been constructed carefully for this phone-based speech synthesizer. By applying the generative phonology, a comprehensive letter-to-sound (LTS) rules and a pronunciation lexicon have been invented for SMaTTS. As for the evaluation tests, a set of Diagnostic Rhyme Test (DRT) word list was compiled and several experiments have been performed to evaluate the quality of the synthesized speech by analyzing the Mean Opinion Score (MOS) obtained. The overall performance of the system as well as the room for improvements was thoroughly discussed.

Keywords: Natural Language Processing, Text-To-Speech (TTS), Diphone, source filter, low-/ high- level synthesis.

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Authors: Tengku Mohd T. Sembok

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Documents retrieval in Information Retrieval Systems (IRS) is generally about understanding of information in the documents concern. The more the system able to understand the contents of documents the more effective will be the retrieval outcomes. But understanding of the contents is a very complex task. Conventional IRS apply algorithms that can only approximate the meaning of document contents through keywords approach using vector space model. Keywords may be unstemmed or stemmed. When keywords are stemmed and conflated in retrieving process, we are a step forwards in applying semantic technology in IRS. Word stemming is a process in morphological analysis under natural language processing, before syntactic and semantic analysis. We have developed algorithms for Malay and Arabic and incorporated stemming in our experimental systems in order to measure retrieval effectiveness. The results have shown that the retrieval effectiveness has increased when stemming is used in the systems.

Keywords: Information Retrieval, Natural Language Processing, Artificial Intelligence.

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Authors: M. Matash Borujerdi, S.M. Mirzababaei

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As computer network technology becomes increasingly complex, it becomes necessary to place greater requirements on the validity of developing standards and the resulting technology. Communication networks are based on large amounts of protocols. The validity of these protocols have to be proved either individually or in an integral fashion. One strategy for achieving this is to apply the growing field of formal methods. Formal methods research defines systems in high order logic so that automated reasoning can be applied for verification. In this research we represent and implement a formerly announced multicast protocol in Prolog language so that certain properties of the protocol can be verified. It is shown that by using this approach some minor faults in the protocol were found and repaired. Describing the protocol as facts and rules also have other benefits i.e. leads to a process-able knowledge. This knowledge can be transferred as ontology between systems in KQML format. Since the Prolog language can increase its knowledge base every time, this method can also be used to learn an intelligent network.

Keywords: Formal methods, MobiCast, Mobile Network, Multicast.

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Authors: H. Iranmanesh, M. Madadi

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Work Breakdown Structure (WBS) is one of the most vital planning processes of the project management since it is considered to be the fundamental of other processes like scheduling, controlling, assigning responsibilities, etc. In fact WBS or activity list is the heart of a project and omission of a simple task can lead to an irrecoverable result. There are some tools in order to generate a project WBS. One of the most powerful tools is mind mapping which is the basis of this article. Mind map is a method for thinking together and helps a project manager to stimulate the mind of project team members to generate project WBS. Here we try to generate a WBS of a sample project involving with the building construction using the aid of mind map and the artificial intelligence (AI) programming language. Since mind map structure can not represent data in a computerized way, we convert it to a semantic network which can be used by the computer and then extract the final WBS from the semantic network by the prolog programming language. This method will result a comprehensive WBS and decrease the probability of omitting project tasks.

Keywords: Expert System, Mind map, Semantic network, Work breakdown structure,

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Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: Public emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining.

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Authors: Miroslav Popelka, Jakub Nožička

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In this paper we deal with using Lego Mindstorms in simulation of robotic systems with respect to cost reduction. Lego Mindstorms kit contains broad variety of hardware components which are required to simulate, program and test the robotics systems in practice. Algorithm programming went in development environment supplied together with Lego kit as in programming language C# as well. Algorithm following the line, which we dealt with in this paper, uses theoretical findings from area of controlling circuits. PID controller has been chosen as controlling circuit whose individual components were experimentally adjusted for optimal motion of robot tracking the line. Data which are determined to process by algorithm are collected by sensors which scan the interface between black and white surfaces followed by robot. Based on discovered facts Lego Mindstorms can be considered for low-cost and capable kit to simulate real robotics systems.

Keywords: LEGO Mindstorms, PID controller, low-cost robotics systems, line follower, sensors, programming language C#, EV3 Home Edition Software.

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Authors: Thassanant Unnanantn, Suttipong Boonphadung

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This research study aimed to survey and analyze the attitudes of pre-service teachers’ the analytical thinking development based on Miller’s Model. The informants of this study were 22 third year teacher students majoring in Thai. The course where the instruction was conducted was English for Academic Purposes in Thai Language 2. The instrument of this research was an open-ended questionnaire with two dimensions of questions: academic and satisfaction dimensions. The investigation revealed the positive attitudes. In the academic dimension, the majority of 12 (54.54%), the highest percentage, reflected that the method of teaching analytical thinking and language simultaneously was their new knowledge and the similar percentage also belonged to text cohesion in writing. For the satisfaction, the highest frequency count was from 17 of them (77.27%) and this majority favored the openness or friendliness of the teacher.

Keywords: Analytical thinking development, Attitudes, Miller’s Model, Pre-service teachers.

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Authors: K. A. Navas, S. Archana Thampy, M. Sasikumar

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Medical image data hiding has strict constrains such as high imperceptibility, high capacity and high robustness. Achieving these three requirements simultaneously is highly cumbersome. Some works have been reported in the literature on data hiding, watermarking and stegnography which are suitable for telemedicine applications. None is reliable in all aspects. Electronic Patient Report (EPR) data hiding for telemedicine demand it blind and reversible. This paper proposes a novel approach to blind reversible data hiding based on integer wavelet transform. Experimental results shows that this scheme outperforms the prior arts in terms of zero BER (Bit Error Rate), higher PSNR (Peak Signal to Noise Ratio), and large EPR data embedding capacity with WPSNR (Weighted Peak Signal to Noise Ratio) around 53 dB, compared with the existing reversible data hiding schemes.

Keywords: Biomedical imaging, Data security, Datacommunication, Teleconferencing.

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Authors: Suwit Sadsunk

Abstract:

The study is about the designed and decorative fabric printing that derived from the Five-color porcelain (Benjarong). The researcher examined the pattern and creativity of the decorative design of the Five-color porcelain (Benjarong) by the artists in order to apply for contemporary arts so that young generation will acknowledge the importance of the Five-color porcelain (Benjarong). The research methodology is both quantitative and qualitative. The researcher conducted an in-depth interview with the operator of five-color porcelain (Benjarong) at Ampawa, Samutsongkram. The information from the interview can be useful and implemented for designing the fabric patterns. The researcher found that there were many formats and designs of the Five-color porcelain (Benjarong) from the past to the present. Its unique design can be applied for the fabric patterns and ready-to-wear clothes properly. After advertising and showing the work of the Five-color porcelain (Benjarong) publicly, there were more young people interested in the Five-color porcelain (Benjarong) than expected which exceeded the objective with positive attitudes towards the Five-color porcelain (Benjarong).

Keywords: Decorative fabric printing, Five-color porcelain (Benjarong).

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Authors: K. S. Jasmine, R. Vasantha

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Component-Based software engineering provides an opportunity for better quality and increased productivity in software development by using reusable software components [10]. One of the most critical aspects of the quality of a software system is its performance. The systematic application of software performance engineering techniques throughout the development process can help to identify design alternatives that preserve desirable qualities such as extensibility and reusability while meeting performance objectives [1]. In the present scenario, software engineering methodologies strongly focus on the functionality of the system, while applying a “fix- it-later" approach to software performance aspects [3]. As a result, lengthy fine-tunings, expensive extra hard ware, or even redesigns are necessary for the system to meet the performance requirements. In this paper, we propose design based, implementation independent, performance prediction approach to reduce the overhead associated in the later phases while developing a performance guaranteed software product with the help of Unified Modeling Language (UML).

Keywords: Software Reuse, Component-based development, Unified Modeling Language, Software performance, Software components, Performance engineering, Software engineering.

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Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as physiological vital signs, images and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful to influence the judgement of clinical sentiment in ICU clinical notes. This paper presents two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of a clinical transformer model that can reliably predict clinical sentiment for notes of COVID patients in ICU. We train the model on clinical notes for COVID-19 patients, ones not previously seen by Bio_ClinicalBERT or Bio_Discharge_Summary_BERT. The model which was based on Bio_ClinicalBERT achieves higher predictive accuracy than the one based on Bio_Discharge_Summary_BERT (Acc 93.33%, AUC 0.98, and Precision 0.96). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and Precision 0.92).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation.

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Authors: Bubaker F. Shareia

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Much of the literature on research design has focused on research conducted in developed, uni-cultural or primarily English speaking countries. Studies of qualitative case study research, the challenges, and prospects have been embedded in Western/Eurocentric society and social theories. Although there have been some theoretical studies, few empirical studies have been conducted to explore the nature of the challenges of qualitative case study in developing countries. These challenges include accessibility to organizations, conducting interviews in developing countries, accessing documents and observing official meetings, language and cultural challenges, the use of consent forms, issues affecting access to companies, respondent issues, and data analysis. The author, while conducting qualitative case study research in Libya, faced all these issues. The discussion in this paper examines these issues in order to make a contribution toward the literature in this area.

Keywords: Accounting, Libya, culture, language, developing countries, qualitative case study.

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Authors: Gemma García López

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The goal of this study is to analyze if search queries carried out in search engines such as Google, can offer emotional information about the user that performs them. Knowing the emotional state in which the Internet user is located can be a key to achieve the maximum personalization of content and the detection of worrying behaviors. For this, two studies were carried out using tools with advanced natural language processing techniques. The first study determines if a query can be classified as positive, negative or neutral, while the second study extracts emotional content from words and applies the categorical and dimensional models for the representation of emotions. In addition, we use search queries in Spanish and English to establish similarities and differences between two languages. The results revealed that text search queries performed by users on the Internet can be classified emotionally. This allows us to better understand the emotional state of the user at the time of the search, which could involve adapting the technology and personalizing the responses to different emotional states.

Keywords: Emotion classification, text search queries, emotional analysis, sentiment analysis in text, natural language processing.

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Authors: Sasitorn Chetanont

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The objectives of this study are to find out the approaches to promote healthy recreation activities for elderly tourists and develop Bang Nam Phueng Floating Market to be a health tourism attraction. The research methodology was to analyze internal and external situations according to MP-MF and the MCSTEPS principles. As for the results of this study the researcher found that the healthy recreational activities for elderly tourists could be divided in 7 groups; travelling Bang Nam Phueng Floating Market activity, homestay relaxation, arts center platform activity, healthy massage activity, paying homage to a Buddha image activity, herbal joss-stick home activity, making local desserts and food activity.

Keywords: Elderly tourists, recreational activities, Bang Nam Phueng Floating Market.

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Authors: Hsin-Yi Lien

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The study explored the role of metacognition in foreign language anxiety on a sample of 411 Taiwanese students of English as a Foreign Language. The reading strategy inventory was employed to evaluate the tertiary learners’ level of metacognitive awareness and a semi-structured background questionnaire was also used to examine the learners’ perceptions of their English proficiency and satisfaction of their current English learning. In addition, gender and academic level differences in employment of reading strategies were investigated. The results showed the frequency of reading strategy use increase slightly along with academic years and males and females actually employ different reading strategies. The EFL tertiary learners in the present study utilized cognitive strategies more frequently than metacognitive strategies or support strategies. Male students use metacognitive strategy more often while female students use cognitive and support strategy more frequently.

Keywords: Cognitive strategy, gender differences, metacognitive strategy, support strategy.

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Authors: Duangkamol Thitivesa

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This paper explores the use of project work in a content-based instruction in a Rajabhat University, Thailand. The use of project is to promote kinds of learning expected of student teachers as stated by Thailand Quality Framework: TQF. The kinds of learning are grouped into five domains: Ethical and moral development, knowledge, cognitive skill, interpersonal skills and responsibility, and analytical and communication skills. The content taught in class is used to lead the student teachers to relate their previously-acquired linguistic knowledge to meaningful realizations of the language system in passages of immediate relevance to their professional interests, teaching methods in particular. Two research questions are formulate to guide this study: 1) To what degree are the five domains of learning expected of student teachers after the use of project in a content class?, and 2) What is the academic achievement of the students’ writing skills, as part of the learning domains stated by TQF, against the 70% attainment target after the use of project to enhance the skill? The sample of the study comprised of 38 fourth-year English major students. The data was collected by means of a summative achievement test, student writing works, an observation checklist, and project diary. The scores in the summative achievement test were analyzed by mean score, standard deviation, and t-test. Project diary serves as students’ record of the language acquired during the project. List of structures and vocabulary noted in the diary has shown students’ ability to attend to, recognize, and focus on meaningful patterns of language forms.

Keywords: Thailand Quality Framework, Project Work, Writing skill.

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Authors: Thabet Slimani, Boutheina Ben Yaghlane, Khaled Mellouli

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In the last few years, the Semantic Web gained scientific acceptance as a means of relationships identification in knowledge base, widely known by semantic association. Query about complex relationships between entities is a strong requirement for many applications in analytical domains. In bioinformatics for example, it is critical to extract exchanges between proteins. Currently, the widely known result of such queries is to provide paths between connected entities from data graph. However, they do not always give good results while facing the user need by the best association or a set of limited best association, because they only consider all existing paths but ignore the path evaluation. In this paper, we present an approach for supporting association discovery queries. Our proposal includes (i) a query language PmSPRQL which provides a multiparadigm query expressions for association extraction and (ii) some quantification measures making easy the process of association ranking. The originality of our proposal is demonstrated by a performance evaluation of our approach on real world datasets.

Keywords: Association extraction, query Language, relationships, knowledge base, multi-paradigm query.

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: Deep neural models, natural language inference, recognizing textual entailment, sentence-to-sentence relation.

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Authors: Mehmet Baltacan

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In history, the relationship between Turks and Armenians was started when Turks entered Anatolia. Before, Armenian people lived in dominion of Persians, Macedonians, Selefkits, Romans, Sasanis, Byzantinians and Arabs. After Turks had entered Anatolia, Armenian people lived together with the people in the Ottoman Empire, and these two people’s living together made Armenians gain citizens’ rights in this empire. Armenian people were excused from the military services and some taxes. They got opportunities to promote in trade, craft, farming and administrative affairs. Firstly, the Ottoman Empire met with opera in 1720s via the embassy, and so with the help of Armenian artists, opera was introduced and developed. In this study, the development of terms related to the opera arts in the Ottoman Empire and the importance of Bosco and Naum theatres and the help and contributions of Armenian artists will be analyzed.

Keywords: Opera, Turkish opera, Armenian artists, Turkish-Armenian relations.

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Authors: Wala A. Bagunaid, Maram Meccawy, Arwa Allinjawi, Zilal Meccawy

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Continuous self-assessment becomes crucial in self-paced online learning environments. Students often depend on themselves to assess their progress; which is considered an essential requirement for any successful learning process. Today’s education institutions face major problems around student motivation and engagement. Thus, personalized e-learning systems aim to help and guide the students. Gamification provides an opportunity to help students for self-assessment and social comparison with other students through attempting to harness the motivational power of games and apply it to the learning environment. Furthermore, Open Social Student Modeling (OSSM) as considered as the latest user modeling technologies is believed to improve students’ self-assessment and to allow them to social comparison with other students. This research integrates OSSM approach and gamification concepts in order to provide self-assessment for English language learners at King Abdulaziz University (KAU). This is achieved through an interactive visual representation of their learning progress.

Keywords: E-learning system, gamification, motivation, social comparison, visualization.

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Authors: Yingqi Cui, Changran Huang, Raymond Lee

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In this paper, we proposed an AI Tutor using ontology and natural language process techniques to generate a computer science domain knowledge graph and answer users’ questions based on the knowledge graph. We define eight types of relation to extract relationships between entities according to the computer science domain text. The AI tutor is separated into two agents: learning agent and Question-Answer (QA) agent and developed on JADE (a multi-agent system) platform. The learning agent is responsible for reading text to extract information and generate a corresponding knowledge graph by defined patterns. The QA agent can understand the users’ questions and answer humans’ questions based on the knowledge graph generated by the learning agent.

Keywords: Artificial intelligence, natural language process, knowledge graph, agent, QA system.

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Authors: Stuart Palmer, Dale Holt

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This paper presents a large scale, quantitative investigation of the impact of discipline differences on the student experience of using an online learning environment (OLE). Based on a representative sample of 2526 respondents, a number of significant differences in the mean rating by broad discipline area of the importance of, and satisfaction with, a range of elements of an OLE were found. Broadly speaking, the Arts and Science and Technology discipline areas reported the lowest importance and satisfaction ratings for the OLE, while the Health and Behavioural Sciences area was the most satisfied with the OLE. A number of specific, systematic discipline differences are reported and discussed. Compared to the observed significant differences in mean importance ratings, there were fewer significant differences in mean satisfaction ratings, and those that were observed were less systematic than for importance ratings.

Keywords: Discipline difference, learning management system, online learning environment, student evaluation.

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Authors: Eugene Allevato

Abstract:

Developing a responsible personal worldview is central to sustainable development, but achieving quality education to promote transformative learning for sustainability is thus far, poorly understood. Most programs involving education for sustainable development rely on changing behavior, rather than attitudes. The emphasis is on the scientific and utilitarian aspect of sustainability with negligible importance on the intrinsic value of nature. Campus sustainability projects include building sustainable gardens and implementing energy-efficient upgrades, instead of focusing on educating for sustainable development through exploration of students’ values and beliefs. Even though green technology adoption maybe the right thing to do, most schools are not targeting the root cause of the environmental crisis; they are just providing palliative measures. This study explores the under-examined factors that lead to pro-environmental behavior by investigating the environmental perceptions of both college business students and personnel of green organizations. A mixed research approach of qualitative, based on structured interviews, and quantitative instruments was developed including 30 college-level students’ interviews and 40 green organization staff members involved in sustainable activities. The interviews were tape-recorded and transcribed for analysis. Categorization of the responses to the open‐ended questions was conducted with the purpose of identifying the main types of factors influencing attitudes and correlating with behaviors. Overall the findings of this study indicated a lack of appreciation for nature, and inability to understand interconnectedness and apply critical thinking. The results of the survey conducted on undergraduate students indicated that the responses of business and liberal arts students by independent t-test were significantly different, with a p‐value of 0.03. While liberal arts students showed an understanding of human interdependence with nature and its delicate balance, business students seemed to believe that humans were meant to rule over the rest of nature. This result was quite intriguing from the perspective that business students will be defining markets, influencing society, controlling and managing businesses that supposedly, in the face of climate change, shall implement sustainable activities. These alarming results led to the focus on green businesses in order to better understand their motivation to engage in sustainable activities. Additionally, a probit model revealed that childhood exposure to nature has a significantly positive impact in pro-environmental attitudes to most of the New Ecological Paradigm scales. Based on these findings, this paper discusses educators including Socrates, John Dewey and Paulo Freire in the implementation of eco-pedagogy and transformative learning following a curriculum with emphasis on critical and systems thinking, which are deemed to be key ingredients in quality education for sustainable development.

Keywords: Eco-pedagogy, environmental behavior, quality education for sustainable development, transformative learning.

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