Search results for: foreign language learning
2421 Teaching Linguistic Humour Research Theories: Egyptian Higher Education EFL Literature Classes
Authors: O. F. Elkommos
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“Humour studies” is an interdisciplinary research area that is relatively recent. It interests researchers from the disciplines of psychology, sociology, medicine, nursing, in the work place, gender studies, among others, and certainly teaching, language learning, linguistics, and literature. Linguistic theories of humour research are numerous; some of which are of interest to the present study. In spite of the fact that humour courses are now taught in universities around the world in the Egyptian context it is not included. The purpose of the present study is two-fold: to review the state of arts and to show how linguistic theories of humour can be possibly used as an art and craft of teaching and of learning in EFL literature classes. In the present study linguistic theories of humour were applied to selected literary texts to interpret humour as an intrinsic artistic communicative competence challenge. Humour in the area of linguistics was seen as a fifth component of communicative competence of the second language leaner. In literature it was studied as satire, irony, wit, or comedy. Linguistic theories of humour now describe its linguistic structure, mechanism, function, and linguistic deviance. Semantic Script Theory of Verbal Humor (SSTH), General Theory of Verbal Humor (GTVH), Audience Based Theory of Humor (ABTH), and their extensions and subcategories as well as the pragmatic perspective were employed in the analyses. This research analysed the linguistic semantic structure of humour, its mechanism, and how the audience reader (teacher or learner) becomes an interactive interpreter of the humour. This promotes humour competence together with the linguistic, social, cultural, and discourse communicative competence. Studying humour as part of the literary texts and the perception of its function in the work also brings its positive association in class for educational purposes. Humour is by default a provoking/laughter-generated device. Incongruity recognition, perception and resolving it, is a cognitive mastery. This cognitive process involves a humour experience that lightens up the classroom and the mind. It establishes connections necessary for the learning process. In this context the study examined selected narratives to exemplify the application of the theories. It is, therefore, recommended that the theories would be taught and applied to literary texts for a better understanding of the language. Students will then develop their language competence. Teachers in EFL/ESL classes will teach the theories, assist students apply them and interpret text and in the process will also use humour. This is thus easing students' acquisition of the second language, making the classroom an enjoyable, cheerful, self-assuring, and self-illuminating experience for both themselves and their students. It is further recommended that courses of humour research studies should become an integral part of higher education curricula in Egypt.
Keywords: ABTH, deviance, disjuncture, episodic, GTVH, humour competence, humour comprehension, humour in the classroom, humour in the literary texts, humour research linguistic theories, incongruity- resolution, isotopy-disjunction, jab line, longer text joke, narrative story line (macro-micro), punch line, six knowledge resource, SSTH, stacks, strands, teaching linguistics, teaching literature, TEFL, TESL.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13982420 Comparison of Machine Learning and Deep Learning Algorithms for Automatic Classification of 80 Different Pollen Species
Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinié
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Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. In this context, the automation of this task is urgent. In this work, we compare classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN and Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches.
Keywords: Image segmentation, stuck particles separation, Sobel operator, thresholding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1832419 A Method for Consensus Building between Teachers and Learners in a Value Co-Creative Learning Service
Authors: Ryota Sugino, Satoshi Mizoguchi, Koji Kimita, Keiichi Muramatsu, Tatsunori Matsui, Yoshiki Shimomura
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Improving added value and productivity of services entails improving both value-in-exchange and value-in-use. Value-in-use is realized by value co-creation, where providers and receivers create value together. In higher education services, value-in-use comes from learners achieving learning outcomes (e.g., knowledge and skills) that are consistent with their learning goals. To enhance the learning outcomes of a learner, it is necessary to enhance and utilize the abilities of the teacher along with the abilities of the learner. To do this, however, the learner and the teacher need to build a consensus about their respective roles. Teachers need to provide effective learning content; learners need to choose the appropriate learning strategies by using the learning content through consensus building. This makes consensus building an important factor in value co-creation. However, methods to build a consensus about their respective roles may not be clearly established, making such consensus difficult. In this paper, we propose some strategies for consensus building between a teacher and a learner in value co-creation. We focus on a teacher and learner co-design and propose an analysis method to clarify a collaborative design process to realize value co-creation. We then analyze some counseling data obtained from a university class. This counseling aimed to build a consensus for value-in-use, learning outcomes, and learning strategies between the teacher and the learner.Keywords: Consensus building, value co-creation, higher education, learning service.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17622418 Architecture from Teaching to Learning to Practice: Authentic learning Tasks in Developing Professional Competencies
Authors: N. Utaberta, B. Hassanpour, M. Surat, A. I. Che Ani, N.M. Tawil
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The concerns of education and practice of architecture do not necessarily overlap. Indeed the gap between them could be seen increasingly and less frequently bridged. We suggest that changing in architecture education and clarifying the relationship between these two can help to find and address the opportunities and unique positions to bridge this gulf.Keywords: Architecture education, Learning, Practice, Teaching
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16012417 A Dictionary Learning Method Based On EMD for Audio Sparse Representation
Authors: Yueming Wang, Zenghui Zhang, Rendong Ying, Peilin Liu
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Sparse representation has long been studied and several dictionary learning methods have been proposed. The dictionary learning methods are widely used because they are adaptive. In this paper, a new dictionary learning method for audio is proposed. Signals are at first decomposed into different degrees of Intrinsic Mode Functions (IMF) using Empirical Mode Decomposition (EMD) technique. Then these IMFs form a learned dictionary. To reduce the size of the dictionary, the K-means method is applied to the dictionary to generate a K-EMD dictionary. Compared to K-SVD algorithm, the K-EMD dictionary decomposes audio signals into structured components, thus the sparsity of the representation is increased by 34.4% and the SNR of the recovered audio signals is increased by 20.9%.
Keywords: Dictionary Learning, EMD, K-means Method, Sparse Representation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26182416 A Novel NIRS Index to Evaluate Brain Activity in Prefrontal Regions While Listening to First and Second Languages for Long Time Periods
Authors: Kensho Takahashi, Ko Watanabe, Takashi Kaburagi, Hiroshi Tanaka, Kajiro Watanabe, Yosuke Kurihara
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Near-infrared spectroscopy (NIRS) has been widely used as a non-invasive method to measure brain activity, but it is corrupted by baseline drift noise. Here we present a method to measure regional cerebral blood flow as a derivative of NIRS output. We investigate whether, when listening to languages, blood flow can reasonably localize and represent regional brain activity or not. The prefrontal blood flow distribution pattern when advanced second-language listeners listened to a second language (L2) was most similar to that when listening to their first language (L1) among the patterns of mean and standard deviation. In experiments with 25 healthy subjects, the maximum blood flow was localized to the left BA46 of advanced listeners. The blood flow presented is robust to baseline drift and stably localizes regional brain activity.
Keywords: NIRS, oxy-hemoglobin, baseline drift, blood flow, working memory, BA46, first language, second language.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22672415 Using Technology to Enhance the Student Assessment Experience
Authors: D. J. Smith, M. A. Qayyum
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The use of information tools is a common activity for students of any educational stage when they encounter online learning activities. Finding the relevant information for particular learning tasks is the topic of this paper as it investigates the use of information tools for a group of student participants. The paper describes and discusses the results with particular implications for use in higher education, and the findings suggest that improvement in assessment design and subsequent student learning may be achieved by structuring the purposefulness of information tools usage and online reading behaviors of university students.
Keywords: Information tools, assessment, online learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17132414 Improving the Quality of e-learning Courses in Higher Education through Student Satisfaction
Authors: Susana Lemos, Neuza Pedro
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Thepurpose of the research is to characterize the levels of satisfaction of the students in e-learning post-graduate courses, taking into account specific dimensions of the course which were considered as benchmarks for the quality of this type of online learning initiative, as well as the levels of satisfaction towards each specific indicator identified in each dimension. It was also an aim of this study to understand how thesedimensions relate to one another. Using a quantitative research approach in the collection and analysis of the data, the study involves the participation of the students who attended on e-learning course in 2010/2011. The conclusions of this study suggest that online students present relatively high levels of satisfaction, which points towards a positive experience during the course. It is possible to note that there is a correlation between the different dimensions studied, consequently leading to different improvement strategies. Ultimately, this investigation aims to contribute to the promotion of quality and the success of e-learning initiatives in Higher Education.Keywords: e-learning, higher education, quality, students satisfaction
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15882413 Use of Semantic Networks as Learning Material and Evaluation of the Approach by Students
Authors: Philippe A. Martin
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This article first summarizes reasons why current approaches supporting Open Learning and Distance Education need to be complemented by tools permitting lecturers, researchers and students to cooperatively organize the semantic content of Learning related materials (courses, discussions, etc.) into a fine-grained shared semantic network. This first part of the article also quickly describes the approach adopted to permit such a collaborative work. Then, examples of such semantic networks are presented. Finally, an evaluation of the approach by students is provided and analyzed.
Keywords: knowledge sharing, knowledge evaluation, e-learning
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15002412 Georgia Case: Tourism Expenses of International Visitors on the Basis of Growing Attractiveness
Authors: Nino Abesadze, Marine Mindorashvili, Nino Paresashvili
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At present actual tourism indicators cannot be calculated in Georgia, making it impossible to perform their quantitative analysis. Therefore, the study conducted by us is highly important from a theoretical as well as practical standpoint. The main purpose of the article is to make complex statistical analysis of tourist expenses of foreign visitors and to calculate statistical attractiveness indices of the tourism potential of Georgia. During the research, the method involving random and proportional selection has been applied. Computer software SPSS was used to compute statistical data for corresponding analysis. Corresponding methodology of tourism statistics was implemented according to international standards. Important information was collected and grouped from major Georgian airports, and a representative population of foreign visitors and a rule of selection of respondents were determined. The results show a trend of growth in tourist numbers and the share of tourists from post-soviet countries are constantly increasing. The level of satisfaction with tourist facilities and quality of service has improved, but still we have a problem of disparity between the service quality and the prices. The design of tourist expenses of foreign visitors is diverse; competitiveness of tourist products of Georgian tourist companies is higher. Attractiveness of popular cities of Georgia has increased by 43%.
Keywords: Tourist, expenses, indexes, statistics, analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9072411 Integrating Agents and Computational Intelligence Techniques in E-learning Environments
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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18642410 Automatically-generated Concept Maps as a Learning Tool
Authors: Xia Lin
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Concept maps can be generated manually or automatically. It is important to recognize differences of the two types of concept maps. The automatically generated concept maps are dynamic, interactive, and full of associations between the terms on the maps and the underlying documents. Through a specific concept mapping system, Visual Concept Explorer (VCE), this paper discusses how automatically generated concept maps are different from manually generated concept maps and how different applications and learning opportunities might be created with the automatically generated concept maps. The paper presents several examples of learning strategies that take advantages of the automatically generated concept maps for concept learning and exploration.Keywords: Concept maps, Dynamic concept representation, learning strategies, visual interface, Visual Concept Explorer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15022409 Stock Movement Prediction Using Price Factor and Deep Learning
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11282408 Optimizing Dialogue Strategy Learning Using Learning Automata
Authors: G. Kumaravelan, R. Sivakumar
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Modeling the behavior of the dialogue management in the design of a spoken dialogue system using statistical methodologies is currently a growing research area. This paper presents a work on developing an adaptive learning approach to optimize dialogue strategy. At the core of our system is a method formalizing dialogue management as a sequential decision making under uncertainty whose underlying probabilistic structure has a Markov Chain. Researchers have mostly focused on model-free algorithms for automating the design of dialogue management using machine learning techniques such as reinforcement learning. But in model-free algorithms there exist a dilemma in engaging the type of exploration versus exploitation. Hence we present a model-based online policy learning algorithm using interconnected learning automata for optimizing dialogue strategy. The proposed algorithm is capable of deriving an optimal policy that prescribes what action should be taken in various states of conversation so as to maximize the expected total reward to attain the goal and incorporates good exploration and exploitation in its updates to improve the naturalness of humancomputer interaction. We test the proposed approach using the most sophisticated evaluation framework PARADISE for accessing to the railway information system.Keywords: Dialogue management, Learning automata, Reinforcement learning, Spoken dialogue system
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15962407 Morphemic Analysis Awareness: A Boon or Bane on ESL Students’ Vocabulary Learning Strategy
Authors: Chandrakala Varatharajoo, Adelina Binti Asmawi, Nabeel Abdallah Mohammad Abedalaziz
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This study investigated the impact of inflectional and derivational morphemic analysis awareness on ESL secondary school students’ vocabulary learning strategy. The quasi-experimental study was conducted with 106 low proficiency secondary school students in two experimental groups (inflectional and derivational) and one control group. The students’ vocabulary acquisition was assessed through two measures: Morphemic Analysis Test and Vocabulary- Morphemic Test in the pretest and posttest before and after an intervention programme. Results of ANCOVA revealed that both the experimental groups achieved a significant score in Morphemic Analysis Test and Vocabulary-Morphemic Test. However, the inflectional group obtained a fairly higher score than the derivational group. Thus, the results indicated that ESL low proficiency secondary school students performed better on inflectional morphemic awareness as compared to derivatives. The results also showed that the awareness of inflectional morphology contributed more on the vocabulary acquisition. Importantly, learning inflectional morphology can help ESL low proficiency secondary school students to develop both morphemic awareness and vocabulary gain. Theoretically, these findings show that not all morphemes are equally useful to students for their language development. Practically, these findings indicate that morphological instruction should at least be included in remediation and instructional efforts with struggling learners across all grade levels, allowing them to focus on meaning within the word before they attempt the text in large for better comprehension. Also, by methodologically, by conducting individualized intervention and assessment this study provided fresh empirical evidence to support the existing literature on morphemic analysis awareness and vocabulary learning strategy. Thus, a major pedagogical implication of the study is that morphemic analysis awareness strategy is a definite boon for ESL secondary school students in learning English vocabulary.
Keywords: ESL, instruction, morphemic analysis, vocabulary.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28872406 Learning Process Enhancement for Robot Behaviors
Authors: Saeed Mohammed Baneamoon, Rosalina Abdul Salam, Abdullah Zawawi Hj. Talib
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Designing a simulated system and training it to optimize its tasks in simulated environment helps the designers to avoid problems that may appear when designing the system directly in real world. These problems are: time consuming, high cost, high errors percentage and low efficiency and accuracy of the system. The proposed system will investigate and improve the efficiency and accuracy of a simulated robot to choose correct behavior to perform its task. In this paper, machine learning, which uses genetic algorithm, is adopted. This type of machine learning is called genetic-based machine learning in which a distributed classifier system is used to improve the efficiency and accuracy of the robot. Consequently, it helps the robot to achieve optimal action.Keywords: Machine Learning, Genetic-Based MachineLearning, Learning Classifier System, Behaviors.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15192405 An Augmented-Reality Interactive Card Game for Teaching Elementary School Students
Authors: YuLung Wu, YuTien Wu, ShuMey Yu
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Game-based learning can enhance the learning motivation of students and provide a means for them to learn through playing games. This study used augmented reality technology to develop an interactive card game as a game-based teaching aid for delivering elementary school science course content with the aim of enhancing student learning processes and outcomes. Through playing the proposed card game, students can familiarize themselves with appearance, features, and foraging behaviors of insects. The system records the actions of students, enabling teachers to determine their students’ learning progress. In this study, 37 students participated in an assessment experiment and provided feedback through questionnaires. Their responses indicated that they were significantly more motivated to learn after playing the game, and their feedback was mostly positive.Keywords: Game-based learning, learning motivation, teaching aid, augmented reality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26522404 A Family of Distributions on Learnable Problems without Uniform Convergence
Authors: César Garza
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In supervised binary classification and regression problems, it is well-known that learnability is equivalent to uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.
Keywords: Statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3232403 The Use of a Tactical Simulator as a Learning Resource at the Norwegian Military Academy
Authors: O. Boe, A. Langaard Jensen
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The Norwegian Military Academy (Army) has been using a tactical simulator for the last two years. During this time there has been some discussion concerning how to use the simulator most efficiently and what type of learning one achieves by using the simulator. The problem that is addressed in this paper is how simulators can be used as a learning resource for students concerned with developing their military profession. The aim of this article is to create a wider consciousness regarding the use of a simulator while educating officers in a military profession. The article discusses the use of simulators from two different perspectives. The first perspective deals with using the simulator as a computer game, and the second perspective looks at the simulator as a socio-cultural artefact. Furthermore the article discusses four different ways the simulator can be looked upon as a useful learning resource when educating students of a military profession.Keywords: Learning, military, profession, simulator.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12082402 End-to-End Spanish-English Sequence Learning Translation Model
Authors: Vidhu Mitha Goutham, Ruma Mukherjee
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The low availability of well-trained, unlimited, dynamic-access models for specific languages makes it hard for corporate users to adopt quick translation techniques and incorporate them into product solutions. As translation tasks increasingly require a dynamic sequence learning curve; stable, cost-free opensource models are scarce. We survey and compare current translation techniques and propose a modified sequence to sequence model repurposed with attention techniques. Sequence learning using an encoder-decoder model is now paving the path for higher precision levels in translation. Using a Convolutional Neural Network (CNN) encoder and a Recurrent Neural Network (RNN) decoder background, we use Fairseq tools to produce an end-to-end bilingually trained Spanish-English machine translation model including source language detection. We acquire competitive results using a duo-lingo-corpus trained model to provide for prospective, ready-made plug-in use for compound sentences and document translations. Our model serves a decent system for large, organizational data translation needs. While acknowledging its shortcomings and future scope, it also identifies itself as a well-optimized deep neural network model and solution.
Keywords: Attention, encoder-decoder, Fairseq, Seq2Seq, Spanish, translation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4612401 Investigating the Dynamics of Knowledge Acquisition in Learning Using Differential Equations
Authors: Gilbert Makanda, Roelf Sypkens
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A mathematical model for knowledge acquisition in teaching and learning is proposed. In this study we adopt the mathematical model that is normally used for disease modelling into teaching and learning. We derive mathematical conditions which facilitate knowledge acquisition. This study compares the effects of dropping out of the course at early stages with later stages of learning. The study also investigates effect of individual interaction and learning from other sources to facilitate learning. The study fits actual data to a general mathematical model using Matlab ODE45 and lsqnonlin to obtain a unique mathematical model that can be used to predict knowledge acquisition. The data used in this study was obtained from the tutorial test results for mathematics 2 students from the Central University of Technology, Free State, South Africa in the department of Mathematical and Physical Sciences. The study confirms already known results that increasing dropout rates and forgetting taught concepts reduce the population of knowledgeable students. Increasing teaching contacts and access to other learning materials facilitate knowledge acquisition. The effect of increasing dropout rates is more enhanced in the later stages of learning than earlier stages. The study opens up a new direction in further investigations in teaching and learning using differential equations.Keywords: Differential equations, knowledge acquisition, least squares nonlinear, dynamical systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9022400 A Survey of Response Generation of Dialogue Systems
Authors: Yifan Fan, Xudong Luo, Pingping Lin
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An essential task in the field of artificial intelligence is to allow computers to interact with people through natural language. Therefore, researches such as virtual assistants and dialogue systems have received widespread attention from industry and academia. The response generation plays a crucial role in dialogue systems, so to push forward the research on this topic, this paper surveys various methods for response generation. We sort out these methods into three categories. First one includes finite state machine methods, framework methods, and instance methods. The second contains full-text indexing methods, ontology methods, vast knowledge base method, and some other methods. The third covers retrieval methods and generative methods. We also discuss some hybrid methods based knowledge and deep learning. We compare their disadvantages and advantages and point out in which ways these studies can be improved further. Our discussion covers some studies published in leading conferences such as IJCAI and AAAI in recent years.Keywords: Retrieval, generative, deep learning, response generation, knowledge.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11872399 Factors Affecting Happiness Learning of Students of Faculty of Management Science, Suan Sunandha Rajabhat University
Authors: Somtop Keawchuer
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The objectives of this research are to compare the satisfaction of students, towards the happiness learning, sorted by their personal profiles, and to figure out the factors that affect the students’ happiness learning. This paper used survey method to collect data from 362 students. The survey was mainly conducted in the Faculty of Management Science, Suan Sunandha Rajabhat University, including 3,443 students. The statistics used for interpreting the results included the frequencies, percentages, standard deviations and One-way ANOVA. The findings revealed that the students are aware and satisfaction that all the factors in 3 categories (knowledge, skill and attitude) influence the happiness learning at the highest levels. The comparison of the satisfaction levels of the students toward their happiness learning leads to the results that the students with different genders, ages, years of study, and majors of the study have the similar satisfaction at the high level.
Keywords: Happiness Learning, Satisfaction, Students.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 39312398 The Para-Universe of Collaborative Group Work in Today-s University Classrooms: Strategies to Help Ensure Success
Authors: Karen Armstrong
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Group work, projects and discussions are important components of teacher education courses whether they are face-toface, blended or exclusively online formats. This paper examines the varieties of tasks and challenges with this learning format in a face to face class teacher education class providing specific examples of both failure and success from both the student and instructor perspective. The discussion begins with a brief history of collaborative and cooperative learning, moves to an exploration of the promised benefits and then takes a look at some of the challenges which can arise specifically from the use of new technologies. The discussion concludes with guidelines and specific suggestions.Keywords: collaborative learning, cooperative computersupported collaborative learning (CSCL), e-learning, group dynamics
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15802397 The Effects of a Digital Dialogue Game on Higher Education Students’ Argumentation-Based Learning
Authors: Omid Noroozi
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Digital dialogue games have opened up opportunities for learning skills by engaging students in complex problem solving that mimic real world situations, without importing unwanted constraints and risks of the real world. Digital dialogue games can be motivating and engaging to students for fun, creative thinking, and learning. This study explored how undergraduate students engage with argumentative discourse activities which have been designed to intensify debate. A pre-test, post-test design was used with students who were assigned to groups of four and asked to debate a controversial topic with the aim of exploring various 'pros and cons' on the 'Genetically Modified Organisms (GMOs)'. Findings reveal that the Digital dialogue game can facilitate argumentation-based learning. The digital Dialogue game was also evaluated positively in terms of students’ satisfaction and learning experiences.Keywords: Argumentation, dialogue, digital game, learning, motivation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11892396 Exploring Self-Directed Learning Among Children
Authors: Mariani Md Nor, Y. Saeednia
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Self-directed learning (SDL) was developed initially for adult learning. Guglielmino constructed a scale to measure SDL. Recent researchers have applied this concept to children. Although there are sufficient theoretical evidences to present the possibility of applying this concept to children, empirical evidences were not provided. This study aimed to examine the quality of SDL and construct a scale to measure SDL among young children. A modified scale of Guglielmino-s scale was constructed and piloted with 183 subjects of age 9. Findings suggest that the qualities of SDL in young ages are apparently congruent with that of adults.Keywords: SDLR, Self-Directed Learning, Young Children.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20152395 Proposing Problem-Based Learning as an Effective Pedagogical Technique for Social Work Education
Authors: Christine K. Fulmer
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Social work education is competency based in nature. There is an expectation that graduates of social work programs throughout the world are to be prepared to practice at a level of competence, which is beneficial to both the well-being of individuals and community. Experiential learning is one way to prepare students for competent practice. The use of Problem-Based Learning (PBL) is a form experiential education that has been successful in a number of disciplines to bridge the gap between the theoretical concepts in the classroom to the real world. PBL aligns with the constructivist theoretical approach to learning, which emphasizes the integration of new knowledge with the beliefs students already hold. In addition, the basic tenants of PBL correspond well with the practice behaviors associated with social work practice including multi-disciplinary collaboration and critical thinking. This paper makes an argument for utilizing PBL in social work education.
Keywords: Constructivist theoretical approach, experiential learning, pedagogy, problem-based learning, social work education.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13192394 Fuzzy Rules Emulated Network Adaptive Controller with Unfixed Learning Rate for a Class of Unknown Discrete-time Nonlinear Systems
Authors: Chidentree Treesatayapun
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A direct adaptive controller for a class of unknown nonlinear discrete-time systems is presented in this article. The proposed controller is constructed by fuzzy rules emulated network (FREN). With its simple structure, the human knowledge about the plant is transferred to be if-then rules for setting the network. These adjustable parameters inside FREN are tuned by the learning mechanism with time varying step size or learning rate. The variation of learning rate is introduced by main theorem to improve the system performance and stabilization. Furthermore, the boundary of adjustable parameters is guaranteed through the on-line learning and membership functions properties. The validation of the theoretical findings is represented by some illustrated examples.
Keywords: Neuro-Fuzzy, learning algorithm, nonlinear discrete time.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14192393 Flipped Learning Application on the Development of Capabilities for Civil Engineering Education in Labs
Authors: Hector Barrios-Piña, Georgia García-Arellano, Salvador García-Rodríguez, Gerardo Bocanegra-García, Shashi Kant
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This work shows the methodology of application and the effectiveness of the Flipped Learning technique for Civil Engineering laboratory classes. It was experimented by some of the professors of the Department of Civil Engineering at Tecnológico de Monterrey while teaching their laboratory classes. A total of 28 videos were created. The videos primarily demonstrate instructions of the experimental practices other than the usage of tools and materials. The technique allowed the students to prepare for their classes in advance. A survey was conducted on the participating professors and students (semester of August-December 2019) to quantify the effectiveness of the Flipped Learning technique. The students reported it as an excellent way of improving their learning aptitude, including self-learning whereas, the professors felt it as an efficient technique for optimizing their class session, which also provided an extra slot for class-interaction. A comparison of grades was analyzed between the students of the traditional classes and with Flipped Learning. It did not distinguish the benefits of Flipped Learning. However, the positive responses from the students and the professors provide an impetus for continuing and promoting the Flipped Learning technique in future classes.
Keywords: Flipped learning, laboratory classes, educational innovation, civil engineering, higher education, competences.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7602392 Personalized Learning: An Analysis Using Item Response Theory
Authors: A. Yacob, N. Hj. Ali, M. H. Yusoff, M. Y. MohdSaman, W. M. A. F. W. Hamzah
Abstract:
Personalized learning becomes increasingly popular which not be restricted by time, place or any other barriers. This study proposes an analysis of Personalized Learning using Item Response Theory which considers course material difficulty and learner ability.The study investigates twenty undergraduate students at TATI University College, who are taking programming subject. By using the IRT,it was found that, finding the most appropriate problem levels to each student include high and low level test items together is not a problem. Thus, the student abilities can be asses more accurately and fairly. Learners who experience more anxiety will affect a heavier cognitive load and receive lower test scores.Instructors are encouraged to provide a supportive learning environment to enhance learning effectiveness because Cognitive Load Theory concerns the limited capacity of the brain to absorb new information.
Keywords: Analysis, Cognitive Load Theory, Item Response Theory, Learning, Motivation, Performance.
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