Search results for: Learning support
3235 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 2023234 Reducing the Imbalance Penalty through Artificial Intelligence Methods Geothermal Production Forecasting: A Case Study for Turkey
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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations, since the geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning and time series methods, the total generation of the power plants belonging to Zorlu Doğal Electricity Generation, which has a high installed capacity in terms of geothermal, was predicted for the first one-week and first two-weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.
Keywords: Machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2043233 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 17733232 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 16123231 Validation and Selection between Machine Learning Technique and Traditional Methods to Reduce Bullwhip Effects: a Data Mining Approach
Authors: Hamid R. S. Mojaveri, Seyed S. Mousavi, Mojtaba Heydar, Ahmad Aminian
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The aim of this paper is to present a methodology in three steps to forecast supply chain demand. In first step, various data mining techniques are applied in order to prepare data for entering into forecasting models. In second step, the modeling step, an artificial neural network and support vector machine is presented after defining Mean Absolute Percentage Error index for measuring error. The structure of artificial neural network is selected based on previous researchers' results and in this article the accuracy of network is increased by using sensitivity analysis. The best forecast for classical forecasting methods (Moving Average, Exponential Smoothing, and Exponential Smoothing with Trend) is resulted based on prepared data and this forecast is compared with result of support vector machine and proposed artificial neural network. The results show that artificial neural network can forecast more precisely in comparison with other methods. Finally, forecasting methods' stability is analyzed by using raw data and even the effectiveness of clustering analysis is measured.Keywords: Artificial Neural Networks (ANN), bullwhip effect, demand forecasting, Support Vector Machine (SVM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20103230 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 26283229 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 17223228 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 15973227 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 15083226 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 18803225 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 15133224 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 11553223 Leading, Teaching and Learning “in the Middle”: Experiences, Beliefs, and Values of Instructional Leaders, Teachers, and Students in Finland, Germany, and Canada
Authors: Brandy Yee, Dianne Yee
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Through the exploration of the lived experiences, beliefs and values of instructional leaders, teachers and students in Finland, Germany and Canada, we investigated the factors which contribute to developmentally responsive, intellectually engaging middle-level learning environments for early adolescents. Student-centred leadership dimensions, effective instructional practices and student agency were examined through the lens of current policy and research on middle-level learning environments emerging from the Canadian province of Manitoba. Consideration of these three research perspectives in the context of early adolescent learning, placed against an international backdrop, provided a previously undocumented perspective on leading, teaching and learning in the middle years. Aligning with a social constructivist, qualitative research paradigm, the study incorporated collective case study methodology, along with constructivist grounded theory methods of data analysis. Data were collected through semi-structured individual and focus group interviews and document review, as well as direct and participant observation. Three case study narratives were developed to share the rich stories of study participants, who had been selected using maximum variation and intensity sampling techniques. Interview transcript data were coded using processes from constructivist grounded theory. A cross-case analysis yielded a conceptual framework highlighting key factors that were found to be significant in the establishment of developmentally responsive, intellectually engaging middle-level learning environments. Seven core categories emerged from the cross-case analysis as common to all three countries. Within the visual conceptual framework (which depicts the interconnected nature of leading, teaching and learning in middle-level learning environments), these seven core categories were grouped into Essential Factors (student agency, voice and choice), Contextual Factors (instructional practices; school culture; engaging families and the community), Synergistic Factors (instructional leadership) and Cornerstone Factors (education as a fundamental cultural value; preservice, in-service and ongoing teacher development). In addition, sub-factors emerged from recurring codes in the data and identified specific characteristics and actions found in developmentally responsive, intellectually engaging middle-level learning environments. Although this study focused on 12 schools in Finland, Germany and Canada, it informs the practice of educators working with early adolescent learners in middle-level learning environments internationally. The authentic voices of early adolescent learners are the most important resource educators have to gauge if they are creating effective learning environments for their students. Ongoing professional dialogue and learning is essential to ensure teachers are supported in their work and develop the pedagogical practices needed to meet the needs of early adolescent learners. It is critical to balance consistency, coherence and dependability in the school environment with the necessary flexibility in order to support the unique learning needs of early adolescents. Educators must intentionally create a school culture that unites teachers, students and their families in support of a common purpose, as well as nurture positive relationships between the school and its community. A large, urban school district in Canada has implemented a school cohort-based model to begin to bring developmentally responsive, intellectually engaging middle-level learning environments to scale.
Keywords: Developmentally responsive learning environments, early adolescents, middle-level learning, middle years, instructional leadership, instructional practices, intellectually engaging learning environments, leadership dimensions, student agency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14923222 A Support System Applicable to Multiple APIs for Haptic VR Application Designers
Authors: Masaharu Isshiki, Kenji Murakami, Shun Ido
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This paper describes a proposed support system which enables applications designers to effectively create VR applications using multiple haptic APIs. When the VR designers create applications, it is often difficult to handle and understand many parameters and functions that have to be set in the application program using documentation manuals only. This complication may disrupt creative imagination and result in inefficient coding. So, we proposed the support application which improved the efficiency of VR applications development and provided the interactive components of confirmation of operations with haptic sense previously. In this paper, we describe improvements of our former proposed support application, which was applicable to multiple APIs and haptic devices, and evaluate the new application by having participants complete VR program. Results from a preliminary experiment suggest that our application facilitates creation of VR applications.Keywords: VR application, Support system, Haptic devices, Haptic APIs.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13463221 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 16113220 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 15293219 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 26633218 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 3553217 E-Education in Multicultural Setting: The Success of Mobile Learning
Authors: Subramaniam Chandran
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This paper explains how mobile learning assures sustainable e-education for multicultural group of students. This paper reports the impact of mobile learning on distance education in multicultural environment. The emergence of learning technologies through CD, internet, and mobile is increasingly adopted by distance institutes for quick delivery and cost-effective purposes. Their sustainability is conditioned by the structure of learners as well as the teaching community. The experimental study was conducted among the distant learners of Vinayaka Missions University located at Salem in India. Students were drawn from multicultural environment based on different languages, religions, class and communities. During the mobile learning sessions, the students, who are divided on language, religion, class and community, were dominated by play impulse rather than study anxiety or cultural inhibitions. This study confirmed that mobile learning improved the performance of the students despite their division based on region, language or culture. In other words, technology was able to transcend the relative deprivation in the multicultural groups. It also confirms sustainable e-education through mobile learning and cost-effective system of instruction. Mobile learning appropriates the self-motivation and play impulse of the young learners in providing sustainable e-education to multicultural social groups of students.
Keywords: E-Education, mobile learning, multiculturalism.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20503216 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 12173215 Development and Usability Evaluation of Platform Independent Mobile Learning Tool(M-LT)
Authors: Sahilu Wendeson Sahilu, Wan Fatimah Wan Ahmad, Nazleeni Samiha Haron
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Mobile learning (M-learning) integrates mobile devices and wireless computing technology to enhance the current conventional learning system. However, there are constraints which are affecting the implementation of platform and device independent M-learning. The main aim of this research is to fulfill the following main objectives: to develop platform independent mobile learning tool (M-LT) for structured programming course, and evaluate its effectiveness and usability using ADDIE instructional design model (ISD) as M-LT life cycle. J2ME (Java 2 micro edition) and XML (Extensible Markup Language) were used to develop platform independent M-LT. It has two modules lecture materials and quizzes. This study used Quasi experimental design to measure effectiveness of the tool. Meanwhile, questionnaire is used to evaluate the usability of the tool. Finally, the results show that the system was effective and also usability evaluation was positive.Keywords: ADDIE, Conventional learning, ISD, J2ME, Mlearning, Quasi Experiment, Wireless Technology, XML
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17193214 Negotiation Support for Value-based Decision in Construction
Authors: Christiono Utomo, Arazi Idrus, Isnanto, Annisa Nugraheni, Farida Rahmawati
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A Negotiation Support is required on a value-based decision to enable each stakeholder to evaluate and rank the solution alternatives before engaging into negotiation with the other stakeholders. This study demonstrates a process of negotiation support model for selection of a building system from value-based design perspective. The perspective is based on comparison of function and cost of a building system. Multi criteria decision techniques were applied to determine the relative value of the alternative solutions for performing the function. A satisfying option game theory are applied to the criteria of value-based decision which are LCC (life cycle cost) and function based FAST. The results demonstrate a negotiation process to select priorities of a building system. The support model can be extended to an automated negotiation by combining value based decision method, group decision and negotiation support.
Keywords: NSS, Value-based, Decision, Construction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17303213 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 9163212 Temporal Case-Based Reasoning System for Automatic Parking Complex
Authors: Alexander P. Eremeev, Ivan E. Kurilenko, Pavel R. Varshavskiy
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In this paper the problem of the application of temporal reasoning and case-based reasoning in intelligent decision support systems is considered. The method of case-based reasoning with temporal dependences for the solution of problems of real-time diagnostics and forecasting in intelligent decision support systems is described. This paper demonstrates how the temporal case-based reasoning system can be used in intelligent decision support systems of the car access control. This work was supported by RFBR.Keywords: Analogous reasoning, case-based reasoning, intelligent decision support systems, temporal reasoning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19793211 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 39413210 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 15893209 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 12003208 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 20273207 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 13333206 Future-Proofing the Workforce: A Case Study of Integrated Human Capability Frameworks to Support Business Success
Authors: P. Paliadelis, A. Jones, G. Campbell
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This paper discusses the development of co-designed capability frameworks for two large multinational organizations led by a university department. The aim was to create evidence-based, integrated capability frameworks that could define, identify, and measure human skill capabilities independent of specific work roles. The frameworks capture and cluster human skills required in the workplace and capture their application at various levels of mastery. Identified capability gaps inform targeted learning opportunities for workers to enhance their employability skills. The paper highlights the value of this evidence-based framework development process in capturing, defining, and assessing desired human-focused capabilities for organizational growth and success.
Keywords: Capability framework, human skills, work-integrated learning, credentialing, digital badging.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 47