Search results for: Learning Management System

Authors: Argaw T. Gurmu, Muhammad N. Mahmood

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The objective of this research is to identify the architecture and construction management students’ learning challenges of the building measurement. This research used the survey data obtained collected from the students who completed the building measurement unit. NVivo qualitative data analysis software was used to identify relevant themes. The analysis of the qualitative data revealed the major learning difficulties such as inadequacy of practice questions for the examination, inability to work as a team, lack of detailed understanding of the prerequisite units, insufficiency of the time allocated for tutorials and incompatibility of lecture and tutorial schedules. The output of this research can be used as a basis for improving the teaching and learning activities in construction measurement units.

Keywords: building measurement, construction management, learning challenges, evaluate survey

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Authors: Giovanni Gonzalez Araujo, Michael Kyrilov, Angelo Kyrilov

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STEAMplug is a web-based innovative educational platform which makes teaching easier and learning more effective. It requires no setup, eliminating the barriers to entry, allowing students to focus on their learning throughreal-world development environments. The student-centric tools enable easy collaboration between peers and teachers. Analyzing user interactions with the system enables us to predict student performance and identify at-risk students, allowing early instructor intervention.

Keywords: plagiarism detection, identifying at-Risk Students, education technology, e-learning system, collaborative development, learning and teaching with technology

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Authors: Salina Budin, Shaira Ismail

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Students learn effectively in a learning environment with a suitable teaching approach that matches their learning preferences. The main objective of the study is to examine the learning preferences amongst the students in the Science and Technology (S&T), and Social Science (SS) fields of study at the Universiti Teknologi Mara (UiTM), Pulau Pinang. The measurement instrument is based on the Dunn and Dunn Learning Styles which measure five elements of learning styles; environmental, sociological, emotional, physiological and psychological. Questionnaires are distributed amongst undergraduates in the Faculty of Mechanical Engineering and Faculty of Business Management. The respondents comprise of 131 diploma students of the Faculty of Mechanical Engineering and 111 degree students of the Faculty of Business Management. The results indicate that, both S&T and SS students share a similar learning preferences on the environmental aspect, emotional preferences, motivational level, learning responsibility, persistent level in learning and learning structure. Most of the S&T students are concluded as analytical learners and the majority of SS students are global learners. Both S&T and SS students are concluded as visual learners, preferred to be in an active mobility in a relaxing and enjoying mode with some light of refreshments during the learning process and exhibited reflective characteristics in learning. Obviously, the S&T students are considered as left brain dominant, whereas the SS students are right brain dominant. The findings highlighted that both categories of students exhibited similar learning preferences except on psychological preferences.

Keywords: learning preferences, Dunn and Dunn learning style, teaching approach, science and technology, social science

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Authors: Aloysius Hardoko, Susilo

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The root cause of the problem after the environmental damage due to coal mining activities defined as the province of East Kalimantan corridor masterplan economic activity accelerated the expansion of Indonesia's economic development (MP3EI) is the behavior of adults. Adult behavior can be changed through knowledge management and attitude. Based on the root of the problem, the objective of the research is to apply knowledge management and attitude based on holistic approach in learning andragogy as an effort to solve environmental problems after coal mining activities. Research methods to achieve the objective of using quantitative research with pretest postes group design. Knowledge management and attitudes based on a holistic approach in adult learning are applied through initial learning activities, core and case-based cover of environmental damage. The research instrument is a description of the case of environmental damage. The data analysis uses t-test to see the effect of knowledge management attitude based on holistic approach before and after adult learning. Location and sample of representative research of adults as many as 20 people in Kutai Kertanegara District, one of the districts in East Kalimantan province, which suffered the worst environmental damage. The conclusion of the research result is the application of knowledge management and attitude in adult learning influence to adult knowledge and attitude to overcome environmental problem post-coal mining activity.

Keywords: knowledge management and attitude, holistic approach, andragogy learning, environmental Issue

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Didiosky Benítez-Erice, Frederik Questier, Dalgys Pérez-Luján

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This paper aims to present two models around the production of students’ experiential knowledge in the teaching-learning process of higher education: the teacher-centered production model and the student-centered production model. From a range of knowledge management and experiential learning theories, the paper elaborates into the nature of students’ experiential knowledge and proposes further adjustments of existing second-generation knowledge management theories taking into account the particularities of higher education. Despite its theoretical nature the paper can be relevant for future studies that stress student-driven improvement and innovation at higher education institutions.

Keywords: experiential knowledge, higher education, knowledge management, teaching-learning process

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Authors: Ilir Rexhepi, Naim Ismajli

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Quality and quality management are key factors of success nowadays. Public sector and quality management in this sector contains many challenges and difficulties, most notably in a new country like Kosovo. This study analyses the process of implementation of quality management system in public administration institutions in this country. The main objective is to show how to set up a quality management system and how does the quality management system setup affect the overall public administration services in Kosovo. This study shows how the efficiency and effectiveness of public institution services/performance is rapidly improving through the establishment and functionalization of Quality Management System. The specific impact of established QMC within the organization has resulted with the identification of mission related processes within the entire system including input identification, the person in charge and the way of conversion to the output of each activity though the interference with other service processes within the system. By giving detailed analyses of all steps of implementation of the Quality Management System, its effect and consequences towards the overall public institution service performance, we try to go one step further, by showing it as a very good example or tool of other public institutions for improving their service performance. Interviews with employees, middle and high level managers including the quality manager and general secretaries are also part of analyses in this paper.

Keywords: quality, quality management system, efficiency, public administration institutions

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Authors: Nongyao Intasaso, Atchara Rattanama, Navarat Pewnual

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This research is survey research purposed to study the factor affected to knowledge management efficiency of personnel in Rajamangala University of Technology Srivijaya, and study the problem of knowledge management affected to knowledge development of personnel in the university. The tool used in this study is structures questioner standardize rating scale in 5 levels. The sample selected by purposive sampling and there are 137 participation calculated in 25% of population. The result found that factor affected to knowledge management efficiency in the university included (1) result from the organization factor found that the university provided project or activity that according to strategy and mission of knowledge management affected to knowledge management efficiency in highest level (x̅ = 4.30) (2) result from personnel factor found that the personnel are eager for knowledge and active to learning to develop themselves and work (Personal Mastery) affected to knowledge management efficiency in high level (x̅ = 3.75) (3) result from technological factor found that the organization brought multimedia learning aid to facilitate learning process affected to knowledge management efficiency in high level (x̅ = 3.70) and (4) the result from learning factor found that the personnel communicated and sharing knowledge and opinion based on acceptance to each other affected to knowledge management efficiency in high level (x̅ = 3.78). The problem of knowledge management in the university included the personnel do not change their work behavior, insufficient of collaboration, lack of acceptance in knowledge and experience to each other, and limited budget. The solutions to solve these problems are the university should be support sufficient budget, the university should follow up and evaluate organization development based on knowledge using, the university should provide the activity emphasize to personnel development and assign the committee to process and report knowledge management procedure.

Keywords: knowledge management, efficiency, personnel, learning process

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Authors: Stuti Modi, Aditi Kambli

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This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

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Authors: Kausik Halder, Nabendu Chaki, Ranjan Dasgupta

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We present a modelling framework that supports the engineering of early requirements specifications for design of learner centric dynamic Learning Management System. The framework is based on i* modelling tool and Means End Analysis, that adopts primitive concepts for modelling early requirements (such as actor, goal, and strategic dependency). We show how pedagogical and computational requirements for designing a learner centric Learning Management system can be adapted for the automatic early requirement engineering specifications. Finally, we presented a model on a Learner Quanta based adaptive Courseware. Our early requirement analysis shows that how means end analysis reveals gaps and inconsistencies in early requirements specifications that are by no means trivial to discover without the help of formal analysis tool.

Keywords: adaptive courseware, early requirement engineering, means end analysis, organizational modelling, requirement modelling

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Authors: Yen-Mei Lee

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Mobile learning (m-learning) has been applied in the education field not only because it is an alternative to web-based learning but also it possesses the ‘anytime, anywhere’ learning features. However, most studies focus on the technology-related issue, such as usability and functionality instead of addressing m-learning from the motivational perspective. Accordingly, the main purpose of the current paper is to integrate critical factors from different motivational theories and related findings to have a better understand the catalysts of an individual’s learning motivation toward m-learning. The main research question for this study is stated as follows: based on different motivational perspectives, what factors of applying mobile devices as medium can facilitate people’s learning motivations? Self-Determination Theory (SDT), Uses and Gratification Theory (UGT), Malone and Lepper’s taxonomy of intrinsic motivation theory, and different types of motivation concepts were discussed in the current paper. In line with the review of relevant studies, three motivating factors with five essential elements are proposed. The first key factor is autonomy. Learning on one’s own path and applying personalized format are two critical elements involved in the factor of autonomy. The second key factor is to apply a build-in instant feedback system during m-learning. The third factor is creating an interaction system, including communication and collaboration spaces. These three factors can enhance people’s learning motivations when applying mobile devices as medium toward learning. To sum up, in the currently proposed paper, with different motivational perspectives to discuss the m-learning is different from previous studies which are simply focused on the technical or functional design. Supported by different motivation theories, researchers can clearly understand how the mobile devices influence people’s leaning motivation. Moreover, instructional designers and educators can base on the proposed factors to build up their unique and efficient m-learning environments.

Keywords: autonomy, learning motivation, mobile learning (m-learning), motivational perspective

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Authors: Kaoutar Ben Azzou, Hanaa Talei

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Human resources is an important department in each organization as it manages the life cycle of employees from recruitment training to retirement or termination of contracts. The recruitment process starts with a job opening, followed by a selection of the best-fit candidates from all applicants. Matching the best profile for a job position requires a manual way of looking at many CVs, which requires hours of work that can sometimes lead to choosing not the best profile. The work presented in this paper aims at reducing the workload of HR personnel by automating the preliminary stages of the candidate screening process, thereby fostering a more streamlined recruitment workflow. This tool introduces an automated system designed to help with the recruitment process by scanning candidates' CVs, extracting pertinent features, and employing machine learning algorithms to decide the most fitting job profile for each candidate. Our work employs natural language processing (NLP) techniques to identify and extract key features from unstructured text extracted from a CV, such as education, work experience, and skills. Subsequently, the system utilizes these features to match candidates with job profiles, leveraging the power of classification algorithms.

Keywords: automated recruitment, candidate screening, machine learning, human resources management

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Authors: Maroonisha Maharajh

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Based on the Black Swan and Disruptive Innovation Theories, this study proposes an educational game based learning model within the context of the traditional classroom learning environment. In the proposed model, the perceived e-learning component is decomposed into accessibility, perceived quality and perceived usability within the traditional rural classroom environment. A sample of 92 respondents took part in this study. The results suggest that users’ continuance intention is determined by both economic and grassroots internet accessibility, which in turn is jointly determined by perceived usefulness, information quality, service quality, system quality, perceived ease of use and cognitive absorption of learning.

Keywords: blended learning, flipped classroom, e-learning, gaming

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Authors: Elson Szeto

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Over the past 15 years, digital technology has ubiquitously penetrated societies around the world. New values of e-learning are emerging in the preparation of future talents, while e-learning is a key driver of widening participation and knowledge transfer in Chinese higher education. As a vibrant, Chinese society in Asia, Hong Kong’s new generation university students, perhaps the digital natives, have been learning with e-learning since their basic education. They can acquire new knowledge with the use of different forms of e-learning as a generic competence. These students who embrace this competence further their study journeys in higher education. This project reviews the Government’s policy of Information Technology in Education which has largely put forward since 1998. So far, primary to secondary education has embraced advantages of e-learning capability to advance the learning of different subject knowledge. Yet, e-learning capacity in higher education is yet to be fully examined in Hong Kong. The study reported in this paper is a pilot investigation into e-learning capacity in Chinese higher education in the region. By conducting a qualitative case study of Hong Kong, the investigation focuses on (1) the institutional ICT settings in general; (2) the pedagogic responses to e-learning in specific; and (3) the university students’ satisfaction of e-learning. It is imperative to revisit the e-learning capacity for promoting effective learning amongst university students, supporting new knowledge acquisition and embracing new opportunities in the 21st century. As a pilot case study, data will be collected from individual interviews with the e-learning management team members of a university, teachers who use e-learning for teaching and students who attend courses comprised of e-learning components. The findings show the e-learning capacity of the university and the key components of leveraging e-learning capability as a university-wide learning settings. The findings will inform institutions’ senior management, enabling them to effectively enhance institutional e-learning capacity for effective learning and teaching and new knowledge acquisition. Policymakers will be aware of new potentials of e-learning for the preparation of future talents in this society at large.

Keywords: capability, e-learning, higher education, student learning

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Authors: Mahasa Zahirnia

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The purpose of this paper is to explore new and effective ways of optimizing satellite images using artificial intelligence, and the process of implementing reinforcement learning to enhance the quality of data captured within the image. In our implementation of Bellman's Reinforcement Learning equations, associated state diagrams, and multi-stage image processing, we were able to enhance image quality, detect and define objects. Reinforcement learning is the differentiator in the area of artificial intelligence, and Q-Learning relies on trial and error to achieve its goals. The reward system that is embedded in Q-Learning allows the agent to self-evaluate its performance and decide on the best possible course of action based on the current and future environment. Results show that within a simulated environment, built on the images that are commercially available, the rate of detection was 40-90%. Reinforcement learning through Q-Learning algorithm is not just desired but required design criteria for image optimization and enhancements. The proposed methods presented are a cost effective method of resolving uncertainty of the data because reinforcement learning finds ideal policies to manage the process using a smaller sample of images.

Keywords: Q-learning, image optimization, reinforcement learning, Markov decision process

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Authors: Md. Aminul Islam, Adel Merabet, Rachid Beguenane, Hussein Ibrahim

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This paper presents a simulation and mathematical model of stand-alone solar-wind-diesel based hybrid energy system (HES). A power management system is designed for multiple energy resources in a stand-alone hybrid energy system. Both Solar photovoltaic and wind energy conversion system consists of maximum power point tracking (MPPT), voltage regulation, and basic power electronic interfaces. An additional diesel generator is included to support and improve the reliability of stand-alone system when renewable energy sources are not available. A power management strategy is introduced to distribute the generated power among resistive load banks. The frequency regulation is developed with conventional phase locked loop (PLL) system. The power management algorithm was applied in Matlab®/Simulink® to simulate the results.

Keywords: solar photovoltaic, wind energy, diesel engine, hybrid energy system, power management, frequency and voltage regulation

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Authors: Itsaree Padphai, Jiranan Pakpeian, Suksun Niponchai

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This study is a descriptive research which aims to: 1) Compare the difference of knowledge before and after using the e-Learning program entitled “Basic Cardiopulmonary Resuscitation for Students in an Emergency Medical Technician Diploma Program”, and 2) Assess the students’ satisfaction after using the said program. This research is a kind of teaching and learning management supplemented with the e-Learning system; therefore, the purposively selected samples are 44 first-year and class-16 students of an emergency medical technician diploma program who attend the class in a second semester of academic year 2012 in Sirindhorn College of Public Health, Khon Kaen province. The research tools include 1) the questionnaire for general information of the respondents, 2) the knowledge tests before and after using the e-Learning program, and 3) an assessment of satisfaction in using the e-Learning program. The statistics used in data analysis percentage, include mean, standard deviation, and inferential statistics: paired t-test. 1. The general information of the respondents was mostly 37 females representing 84.09 percent. The average age was 19.5 years (standard deviation was 0.81), the maximum age was 21 years, and the minimum age was 19 years respectively. Students (35 subjects) admitted that they preferred the methods of teaching and learning by using the e-Learning systems. This was totally 79.95 percent. 2. A comparison on the difference of knowledge before and after using the e-Learning program showed that the mean before an application was 6.64 (standard deviation was 1.94) and after was 18.84 (standard deviation 1.03), which was higher than the knowledge of students before using the e-Learning program with the statistical significance (P value < 0.001). 3. For the satisfaction after using the e-Learning program, it was found that students’ satisfaction was at a very good level with the mean of 4.93 (standard deviation was 0.11).

Keywords: e-Learning, cardiopulmonary resuscitation, diploma program, Khon Kaen Province

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Authors: Bengi Sonyel, Kheder Kasem

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Nowadays technology is growing so fast. Everybody agrees that technology should be enhanced more in educational field in order to achieve maximum level of teaching and learning effectiveness. Collaborative learning is one of the most important subjects that have been discussed widely in the last 20 years. In this growing of technology and the widely spread of e-learning systems most of face-to-face processes are changing to be completely online base. Online collaborative learning considered one of the new feature that applied recently in some e-Learning systems but still there are much differences between face-to-face instance of collaborative learning and what really occur and happen in networked online environment.In this research we will compare face-to-face collaborative learning with online collaborative learning to define the key success for achieving course’s outcomes. We will also study the current teachers and students experience in today e-Learning systems, more specifically in online collaborative system and study them interaction to today’s technology that related to education. We will apply quantitative and qualitative research method in order to get accurate results. Finally we will gather all of our findings, analyze it and try to find the advantages and disadvantages as well as the current problems and possible solutions.

Keywords: collaborative learning, learning by doing, technology, teachers, learners experiences

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Authors: Willem J. A. Louw

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The wave of new advanced computing technology that has been developed during the recent past has significantly changed the way we communicate, collaborate and collect information. It has created a new technology environment and paradigm in which our children and students grow-up and this impacts on their learning. Research confirmed that Generation Y students have a preference for learning in the new technology environment. The challenge or question is: How do we adjust our teaching and learning to make the most of these changes. The complexity of effective and efficient teaching and learning must not be underestimated and changes must be preceded by proper objective research to prevent any haphazard developments that could do more harm than benefit. A blended learning approach has been used in the Forestry department for a few numbers of years including the use of electronic-peer assisted learning (e-pal) in a fixed-computer set-up within a learning management system environment. It was decided to extend the investigation and do some exploratory research by using a range of different Tablet devices. For this purpose, learning activities or assignments were designed to cover aspects of communication, collaboration and collection of information. The Moodle learning management system was used to present normal module information, to communicate with students and for feedback and data collection. Student feedback was collected by using an online questionnaire and informal discussions. The research project was implemented in 2013, 2014 and 2015 amongst first and third-year students doing a forestry three-year technical tertiary qualification in commercial plantation management. In general, more than 80% of the students alluded to that the device was very useful in their learning environment while the rest indicated that the devices were not very useful. More than ninety percent of the students acknowledged that they would like to continue using the devices for all of their modules whilst the rest alluded to functioning efficiently without the devices. Results indicated that information collection (access to resources) was rated the highest advantageous factor followed by communication and collaboration. The main general advantages of using Tablets were listed by the students as being mobility (portability), 24/7 access to learning material and information of any kind on a user friendly device in a Wi-Fi environment, fast computing process speeds, saving time, effort and airtime through skyping and e-mail, and use of various applications. Ownership of the device is a critical factor while the risk was identified as a major potential constraint. Significant differences were reported between the different types and quality of Tablets. The preferred types are those with a bigger screen and the ones with overall better functionality and quality features. Tablets significantly increase the collaboration, communication and information collection needs of the students. It does, however, not replace the need of a computer/laptop because of limited storage and computation capacity, small screen size and inefficient typing.

Keywords: tablets, teaching, blended learning, tablet quality

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Authors: Huie-Wen Lin

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This study integrated various teaching factors -based on the idea of a flipped classroom- in a financial management course. The study’s aim was to establish an effective teaching implementation strategy and evaluation mechanism with respect to learning outcomes, which can serve as a reference for the future modification of teaching methods. This study implemented a teaching method in five stages and estimated the learning efficiencies of 22 students (in the teaching scenario and over two semesters). Subsequently, data envelopment analysis (DEA) was used to compare, for each student, between the learning efficiencies before and after participation in the flipped classroom -in the first and second semesters, respectively- to identify the crucial external factors influencing learning efficiency. According to the results, the average overall student learning efficiency increased from 0.901 in the first semester to 0.967 in the second semester, which demonstrate that the flipped classroom approach can improve teaching effectiveness and learning outcomes. The results also revealed a difference in learning efficiency between male and female students.

Keywords: data envelopment analysis, flipped classroom, learning outcome, teaching and learning

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Authors: Larry Wang

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The aim of this paper is to demonstrate how an online homework system is integrated in teaching and learning mathematics and how it improves the student success rates in some gateway mathematics courses. WeBWork provided by the Mathematical Association of America is adopted as the online homework system. During the period of 2010-2015, the system was implemented in classes of precalculus, calculus, probability and statistics, discrete mathematics, linear algebra, and differential equations. As a result, the passing rates of the sections with WeBWork are well above other sections without WeBWork (about 7-10% higher). The paper also shows how the WeBWork system was used.

Keywords: gateway mathematics, online grading, pass rate, WeBWorK

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Authors: M. H. Imam, Imran A. Tasadduq, Abdul-Rahim Ahmad, Fahd M. Aldosari

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Learning outcomes of a course (CLOs) and the abilities at the time of graduation referred to as Student Outcomes (SOs) are required to be assessed for ABET accreditation. A question in an assessment must target a CLO as well as an SO and must represent a required level of competence. This paper presents the idea of an Expert System (ES) to select a proper question to satisfy ABET accreditation requirements. For ES implementation, seven attributes of a question are considered including the learning outcomes and Bloom’s Taxonomy level. A database contains all the data about a course including course content topics, course learning outcomes and the CLO-SO relationship matrix. The knowledge base of the presented ES contains a pool of questions each with tags of the specified attributes. Questions and the attributes represent expert opinions. With implicit rule base the inference engine finds the best possible question satisfying the required attributes. It is shown that the novel idea of such an ES can be implemented and applied to a course with success. An application example is presented to demonstrate the working of the proposed ES.

Keywords: expert system, student outcomes, course learning outcomes, question attributes

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Authors: Thanaphat Suwanaklang, Supaporn Suwannarongsri

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Presently, there are many industries in Thailand producing various products for both domestic distribution and export to foreign countries. Warehouse is one of the most important areas of business needing to store their products. Such businesses need to have a suitable warehouse management system for reducing the storage time and using the space as much as possible. This paper proposes the development of a web application for a warehouse management system. One of the ceramics factories in Thailand is conducted as a case study. By applying the ABC analysis, fixed location, commodity system, ECRS, and 7-waste theories and principles, the web application for the warehouse management system of the selected ceramics factory is developed to design the optimal storage area for groups of products and design the optimal routes of forklifts. From experimental results, it was found that the warehouse management system developed via the web application can reduce the travel distance of forklifts and the time of searching for storage area by 100% once compared with the conventional method. In addition, the entire storage area can be on-line and real-time monitored.

Keywords: warehouse management system, warehouse design method, logistics system, web application

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Authors: Stepan Grebeniuk, Ersi Hodo, Henri Ruotsalainen, Paul Tavolato

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Substation security plays an important role in the power delivery system. During the past years, there has been an increase in number of attacks on automation networks of the substations. In spite of that, there hasn’t been enough focus dedicated to the protection of such networks. Aiming to design a specialized anomaly detection system based on machine learning, in this paper we will discuss the IEC 60870-5-104 protocol that is used for communication between substation and control station and focus on the simulation of the substation traffic. Firstly, we will simulate the communication between substation slave and server. Secondly, we will compare the system's normal behavior and its behavior under the attack, in order to extract the right features which will be needed for building an anomaly detection system. Lastly, based on the features we will suggest the anomaly detection system for the asynchronous protocol IEC 60870-5-104.

Keywords: Anomaly detection, IEC-60870-5-104, Machine learning, Man-in-the-Middle attacks, Substation security

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Authors: Khaled Halimi, Hassina Seridi-Bouchelaghem

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The purpose of this paper is to describe how learning analytics approaches based on social semantic web techniques can be applied to enhance the lifelong learning experiences in a connectivist perspective. For this reason, a prototype of a system called SoLearn (Social Learning Environment) that supports this approach. We observed and studied literature related to lifelong learning systems, social semantic web and ontologies, connectivism theory, learning analytics approaches and reviewed implemented systems based on these fields to extract and draw conclusions about necessary features for enhancing the lifelong learning process. The semantic analytics of learning can be used for viewing, studying and analysing the massive data generated by learners, which helps them to understand through recommendations, charts and figures their learning and behaviour, and to detect where they have weaknesses or limitations. This paper emphasises that implementing a learning analytics approach based on social semantic web representations can enhance the learning process. From one hand, the analysis process leverages the meaning expressed by semantics presented in the ontology (relationships between concepts). From the other hand, the analysis process exploits the discovery of new knowledge by means of inferring mechanism of the semantic web.

Keywords: connectivism, learning analytics, lifelong learning, social semantic web

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Authors: Fuad M. Alkoot

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We aim at highlighting the benefits of classifier systems especially in supporting educational management decisions. The paper aims at using classifiers in an educational application where an outcome is predicted based on given input parameters that represent various conditions at the institute. We present a classifier system that is designed using a limited training set with data for only one semester. The achieved system is able to reach at previously known outcomes accurately. It is also tested on new input parameters representing variations of input conditions to see its prediction on the possible outcome value. Given the supervised expectation of the outcome for the new input we find the system is able to predict the correct outcome. Experiments were conducted on one semester data from two departments only, Switching and Mathematics. Future work on other departments with larger training sets and wider input variations will show additional benefits of classifier systems in supporting the management decisions at an educational institute.

Keywords: machine learning, pattern recognition, classifier design, educational management, outcome estimation

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Authors: A. Mohamed Mydeen, Pallapa Venkataram

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The learning process needs to be so pervasive to impart the quality in acquiring the knowledge about a subject by making use of the advancement in the field of information and communication systems. However, pervasive learning paradigms designed so far are system automation types and they lack in factual pervasive realm. Providing factual pervasive realm requires subtle ways of teaching and learning with system intelligence. Augmentation of intelligence with pervasive learning necessitates the most efficient way of representing knowledge for the system in order to give the right learning material to the learner. This paper presents a method of representing knowledge for Pervasive Toolroom Maintenance System (PTMS) in which a learner acquires sublime knowledge about the various kinds of tools kept in the toolroom and also helps for effective maintenance of the toolroom. First, we explicate the generic model of knowledge representation for PTMS. Second, we expound the knowledge representation for specific cases of toolkits in PTMS. We have also presented the conceptual view of knowledge representation using ontology for both generic and specific cases. Third, we have devised the relations for pervasive knowledge in PTMS. Finally, events are identified in PTMS which are then linked with pervasive data of toolkits based on relation formulated. The experimental environment and case studies show the accuracy and efficient knowledge representation of toolkits in PTMS.

Keywords: knowledge representation, pervasive computing, agent technology, ECA rules

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Authors: Omran Alharbi, Victor Lally

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The advantages of the adoption of new technology such as learning management systems (LMSs) in education and teaching methods have been widely recognised. This has led a large number of universities to integrate this type of technology into their daily learning and teaching activities in order to facilitate the education process for both learners and teachers. On the other hand, in some developing countries such as Saudi Arabia, educators have seldom used this technology. As a result, this study was conducted in order to investigate the factors that impede teachers’ use of technology (LMSs) in their teaching in Saudi Arabian institutions. This study used a qualitative approach. Eight participants were invited to take part in this study, and they were asked to give their opinions about the most significant factors that prevented them from integrating technology into their daily activities. The results revealed that a lack of LMS skills, interest in and knowledge about the LMS among teachers were the most significant factors impeding them from using technology in their lessons. The participants suggested that incentive training should be provided to reduce these challenges.

Keywords: LMS, factors, KSA, teachers

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Authors: Mafawez Alharbi, Mahdi Jemmali

Abstract:

E-learning is a developing area especially in education. E-learning can provide several benefits to learners. An intelligent system to collect all components satisfying user preferences is so important. This research presents an approach that it capable to personalize e-information and give the user their needs following their preferences. This proposal can make some knowledge after more evaluations made by the user. In addition, it can learn from the habit from the user. Finally, we show a walk-through to prove how intelligent process work.

Keywords: artificial intelligence, architecture, e-learning, software engineering, processing

Procedia PDF Downloads 158

Authors: Selvavinayagan Babiharan

Abstract:

This research aims to develop a deep learning platform to enhance mathematics education for secondary students in Sri Lanka. The platform will be designed to incorporate interactive and user-friendly features to engage students in active learning and promote their mathematical skills. The proposed platform will be developed using TensorFlow and Keras, two widely used deep learning frameworks. The system will be trained on a large dataset of math problems, which will be collected from Sri Lankan school curricula. The results of this research will contribute to the improvement of mathematics education in Sri Lanka and provide a valuable tool for teachers to enhance the learning experience of their students.

Keywords: information technology, education, machine learning, mathematics

Procedia PDF Downloads 52