Search results for: Azure Machine Learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8326

Search results for: Azure Machine Learning

6826 Teacher Education and the Impact of Higher Education Foreign Language Requirements on Students with Learning Disabilities

Authors: Joao Carlos Koch Junior, Risa Takashima

Abstract:

Learning disabilities have been extensively and increasingly studied in recent times. In spite of this, there is arguably a scarce number of studies addressing a key issue, which is the impact of foreign-language requirements on students with learning disabilities in higher education, and the lack of training or awareness of teachers regarding language learning disabilities. This study is an attempt to address this issue. An extensive review of the literature in multiple fields will be summarised. This, paired with a case-analysis of a university adopting a more inclusive approach towards special-needs students in its foreign-language programme, this presentation aims to establish a link between different studies and propose a number of suggestions to make language classrooms more inclusive.

Keywords: foreign language teaching, higher education, language teacher education, learning disabilities

Procedia PDF Downloads 438
6825 Effects of E-Learning Mode of Instruction and Conventional Mode of Instruction on Student’s Achievement in English Language in Senior Secondary Schools, Ibadan Municipal, Nigeria

Authors: Ibode Osa Felix

Abstract:

The use of e-Learning is presently intensified in the academic world following the outbreak of the Covid-19 pandemic in early 2020. Hitherto, e-learning had made its debut in teaching and learning many years ago when it emerged as an aspect of Computer Based Teaching, but never before has its patronage become so important and popular as currently obtains. Previous studies revealed that there is an ongoing debate among researchers on the efficacy of the E-learning mode of instruction over the traditional teaching method. Therefore, the study examined the effect of E-learning and Conventional Mode of Instruction on Students Achievement in the English Language. The study is a quasi-experimental study in which 230 students, from three public secondary schools, were selected through a simple random sampling technique. Three instruments were developed, namely, E-learning Instructional Guide (ELIG), Conventional Method of Instructional Guide (CMIG), and English Language Achievement Test (ELAT). The result revealed that students taught through the conventional method had better results than students taught online. The result also shows that girls taught with the conventional method of teaching performed better than boys in the English Language. The study, therefore, recommended that effort should be made by the educational authorities in Nigeria to provide internet facilities to enhance practices among learners and provide electricity to power e-learning equipment in the secondary schools. This will boost e-learning practices among teachers and students and consequently overtake conventional method of teaching in due course.

Keywords: e-learning, conventional method of teaching, achievement in english, electricity

Procedia PDF Downloads 163
6824 A Constructivist Approach and Tool for Autonomous Agent Bottom-up Sequential Learning

Authors: Jianyong Xue, Olivier L. Georgeon, Salima Hassas

Abstract:

During the initial phase of cognitive development, infants exhibit amazing abilities to generate novel behaviors in unfamiliar situations, and explore actively to learn the best while lacking extrinsic rewards from the environment. These abilities set them apart from even the most advanced autonomous robots. This work seeks to contribute to understand and replicate some of these abilities. We propose the Bottom-up hiErarchical sequential Learning algorithm with Constructivist pAradigm (BEL-CA) to design agents capable of learning autonomously and continuously through interactions. The algorithm implements no assumption about the semantics of input and output data. It does not rely upon a model of the world given a priori in the form of a set of states and transitions as well. Besides, we propose a toolkit to analyze the learning process at run time called GAIT (Generating and Analyzing Interaction Traces). We use GAIT to report and explain the detailed learning process and the structured behaviors that the agent has learned on each decision making. We report an experiment in which the agent learned to successfully interact with its environment and to avoid unfavorable interactions using regularities discovered through interaction.

Keywords: cognitive development, constructivist learning, hierarchical sequential learning, self-adaptation

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6823 Parallel Fuzzy Rough Support Vector Machine for Data Classification in Cloud Environment

Authors: Arindam Chaudhuri

Abstract:

Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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6822 An Exploratory Study: Mobile Learning as a Means of Promoting Sustainable Learning in the Saudi General Educational Schools via an Activity Theory Lens

Authors: Aiydh Aljeddani

Abstract:

Sustainable learning is an emerging concept that aims at enhancing sustainability literacy and competency in educational contexts. Mobile learning is one of the means increasingly used in sustainable development education nowadays. Studies which have explored this issue in the Saudi educational context so far are rare. Therefore, the current study attempted to explore the current situation of the usage of mobile learning in the Saudi elementary and secondary schools as a means of promoting sustainable learning. It also focused on how mobile learning has been implemented in those schools to promote sustainable learning and what factors have contributed to the success/failure of the implementation of mobile learning and possible ways to improve the current practice. An interpretive approach was followed in this study to gain a thorough understanding of the explored issue in the Saudi educational context using the activity theory as a lens to do so. A qualitative case study methodology in which semi-structured interviews, documents analysis and nominal group were used to gather the data for this study. Two hundred and twenty-nine participants representing several main stakeholders in the educational system took part in this study. Those included six general education schools, head teachers, teachers, students’ parents, educational supervisors, one curriculum designer and academic curriculum specialists. Through the lens of activity theory, the results of the study showed that there were contradictions in the current practice between the elements of the activity system and within each of its elements. Furthermore, several sociocultural factors have influenced both the division of labour and the community's members. These have acted as obstacles which have impeded the usage of mobile learning to promote sustainable learning in this context. It was found that shifting from the current practice to sustainable learning via the usage of mobile learning requires appropriate interrelationship between the different elements of the activity system. The study finally offers a number of recommendations to improve on the current practices and suggests areas for further studies.

Keywords: activity theory, mobile learning, sustainability competency, sustainability literacy, sustainable learning

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6821 Evaluating the Effectiveness of Animated Videos in Learning Economics

Authors: J. Chow

Abstract:

In laboratory settings, this study measured and reported the effects of undergraduate students watching animated videos on learning microeconomics as compared with the effectiveness of reading written texts. The study described an experiment on learning microeconomics in higher education using two different types of learning materials. It reported the effectiveness on microeconomics learning of watching animated videos and reading written texts. Undergraduate students in the university were randomly assigned to either a ‘video group’ or a ‘text group’ in the experiment. Previously-validated multiple-choice questions on fundamental concepts of microeconomics were administered. Both groups showed improvement between the pre-test and post-test. The experience of learning using text and video materials was also assessed. After controlling the student characteristics variables, the analyses showed that both types of materials showed comparable level of perceived learning experience. The effect size and statistical significance of these results supported the hypothesis that animated video is an effective alternative to text materials as a learning tool for students. The findings suggest that such animated videos may support teaching microeconomics in higher education.

Keywords: animated videos for education, laboratory experiment, microeconomics education, undergraduate economics education

Procedia PDF Downloads 137
6820 An Analysis of Instruction Checklist Based on Universal Design for Learning

Authors: Yong Wook Kim

Abstract:

The purpose of this study is to develop an instruction analysis checklist applicable to inclusive setting based on the Universal Design for Learning Guideline 2.0. To do this, two self-validation reviews, two expert validity reviews, and two usability evaluations were conducted based on the Universal Design for Learning Guideline 2.0. After validation and usability evaluation, a total of 36 items consisting of 4 items for each instruction was developed. In all questions, examples are presented for the purpose of reinforcing concrete. All the items were judged by the 3-point scale. The observation results were provided through a radial chart allowing SWOT analysis of the universal design for learning of teachers. The developed checklist provides a description of the principles and guidelines in the checklist itself as it requires a thorough understanding by the observer of the universal design for learning through prior education. Based on the results of the study, the instruction criteria, the specificity of the criteria, the number of questions, and the method of arrangement were discussed. As a future research, this study proposed the characteristics of application of universal design for learning for each subject, the comparison with the observation results through the self-report teaching tool, and the continual revision and supplementation of the lecture checklist.

Keywords: inclusion, universal design for learning, instruction analysis, instruction checklist

Procedia PDF Downloads 273
6819 Deriving Generic Transformation Matrices for Multi-Axis Milling Machine

Authors: Alan C. Lin, Tzu-Kuan Lin, Tsong Der Lin

Abstract:

This paper proposes a new method to find the equations of transformation matrix for the rotation angles of the two rotational axes and the coordinates of the three linear axes of an orthogonal multi-axis milling machine. This approach provides intuitive physical meanings for rotation angles of multi-axis machines, which can be used to evaluate the accuracy of the conversion from CL data to NC data.

Keywords: CAM, multi-axis milling machining, transformation matrix, rotation angles

Procedia PDF Downloads 468
6818 Investigating Learners’ Online Learning Experiences in a Blended-Learning School Environment

Authors: Abraham Ampong

Abstract:

BACKGROUND AND SIGNIFICANCE OF THE STUDY: The development of information technology and its influence today is inevitable in the world of education. The development of information technology and communication (ICT) has an impact on the use of teaching aids such as computers and the Internet, for example, E-learning. E-learning is a learning process attained through electronic means. But learning is not merely technology because learning is essentially more about the process of interaction between teacher, student, and source study. The main purpose of the study is to investigate learners’ online learning experiences in a blended learning approach, evaluate how learners’ experience of an online learning environment affects the blended learning approach and examine the future of online learning in a blended learning environment. Blended learning pedagogies have been recognized as a path to improve teacher’s instructional strategies for teaching using technology. Blended learning is perceived to have many advantages for teachers and students, including any-time learning, anywhere access, self-paced learning, inquiry-led learning and collaborative learning; this helps institutions to create desired instructional skills such as critical thinking in the process of learning. Blended learning as an approach to learning has gained momentum because of its widespread integration into educational organizations. METHODOLOGY: Based on the research objectives and questions of the study, the study will make use of the qualitative research approach. The rationale behind the selection of this research approach is that participants are able to make sense of their situations and appreciate their construction of knowledge and understanding because the methods focus on how people understand and interpret their experiences. A case study research design is adopted to explore the situation under investigation. The target population for the study will consist of selected students from selected universities. A simple random sampling technique will be used to select the targeted population. The data collection instrument that will be adopted for this study will be questions that will serve as an interview guide. An interview guide is a set of questions that an interviewer asks when interviewing respondents. Responses from the in-depth interview will be transcribed into word and analyzed under themes. Ethical issues to be catered for in this study include the right to privacy, voluntary participation, and no harm to participants, and confidentiality. INDICATORS OF THE MAJOR FINDINGS: It is suitable for the study to find out that online learning encourages timely feedback from teachers or that online learning tools are okay to use without issues. Most of the communication with the teacher can be done through emails and text messages. It is again suitable for sampled respondents to prefer online learning because there are few or no distractions. Learners can have access to technology to do other activities to support their learning”. There are, again, enough and enhanced learning materials available online. CONCLUSION: Unlike the previous research works focusing on the strengths and weaknesses of blended learning, the present study aims at the respective roles of its two modalities, as well as their interdependencies.

Keywords: online learning, blended learning, technologies, teaching methods

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6817 Effects of Ubiquitous 360° Learning Environment on Clinical Histotechnology Competence

Authors: Mari A. Virtanen, Elina Haavisto, Eeva Liikanen, Maria Kääriäinen

Abstract:

Rapid technological development and digitalization has affected also on higher education. During last twenty years multiple of electronic and mobile learning (e-learning, m-learning) platforms have been developed and have become prevalent in many universities and in the all fields of education. Ubiquitous learning (u-learning) is not that widely known or used. Ubiquitous learning environments (ULE) are the new era of computer-assisted learning. They are based on ubiquitous technology and computing that fuses the learner seamlessly into learning process by using sensing technology as tags, badges or barcodes and smart devices like smartphones and tablets. ULE combines real-life learning situations into virtual aspects and can be flexible used in anytime and anyplace. The aim of this study was to assess the effects of ubiquitous 360 o learning environment on higher education students’ clinical histotechnology competence. A quasi-experimental study design was used. 57 students in biomedical laboratory science degree program was assigned voluntarily to experiment (n=29) and to control group (n=28). Experimental group studied via ubiquitous 360o learning environment and control group via traditional web-based learning environment (WLE) in a 8-week educational intervention. Ubiquitous 360o learning environment (ULE) combined authentic learning environment (histotechnology laboratory), digital environment (virtual laboratory), virtual microscope, multimedia learning content, interactive communication tools, electronic library and quick response barcodes placed into authentic laboratory. Web-based learning environment contained equal content and components with the exception of the use of mobile device, interactive communication tools and quick response barcodes. Competence of clinical histotechnology was assessed by using knowledge test and self-report developed for this study. Data was collected electronically before and after clinical histotechnology course and analysed by using descriptive statistics. Differences among groups were identified by using Wilcoxon test and differences between groups by using Mann-Whitney U-test. Statistically significant differences among groups were identified in both groups (p<0.001). Competence scores in post-test were higher in both groups, than in pre-test. Differences between groups were very small and not statistically significant. In this study the learning environment have developed based on 360o technology and successfully implemented into higher education context. And students’ competence increases when ubiquitous learning environment were used. In the future, ULE can be used as a learning management system for any learning situation in health sciences. More studies are needed to show differences between ULE and WLE.

Keywords: competence, higher education, histotechnology, ubiquitous learning, u-learning, 360o

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6816 New Knowledge Co-Creation in Mobile Learning: A Classroom Action Research with Multiple Case Studies Using Mobile Instant Messaging

Authors: Genevieve Lim, Arthur Shelley, Dongcheol Heo

Abstract:

Abstract—Mobile technologies can enhance the learning process as it enables social engagement around concepts beyond the classroom and the curriculum. Early results in this ongoing research is showing that when learning interventions are designed specifically to generate new insights, mobile devices support regulated learning and encourage learners to collaborate, socialize and co-create new knowledge. As students navigate across the space and time boundaries, the fundamental social nature of learning transforms into mobile computer supported collaborative learning (mCSCL). The metacognitive interaction in mCSCL via mobile applications reflects the regulation of learning among the students. These metacognitive experiences whether self-, co- or shared-regulated are significant to the learning outcomes. Despite some insightful empirical studies, there has not yet been significant research that investigates the actual practice and processes of the new knowledge co-creation. This leads to question as to whether mobile learning provides a new channel to leverage learning? Alternatively, does mobile interaction create new types of learning experiences and how do these experiences co-create new knowledge. The purpose of this research is to explore these questions and seek evidence to support one or the other. This paper addresses these questions from the students’ perspective to understand how students interact when constructing knowledge in mCSCL and how students’ self-regulated learning (SRL) strategies support the co-creation of new knowledge in mCSCL. A pilot study has been conducted among international undergraduates to understand students’ perspective of mobile learning and concurrently develops a definition in an appropriate context. Using classroom action research (CAR) with multiple case studies, this study is being carried out in a private university in Thailand to narrow the research gaps in mCSCL and SRL. The findings will allow teachers to see the importance of social interaction for meaningful student engagement and envisage learning outcomes from a knowledge management perspective and what role mobile devices can play in these. The findings will signify important indicators for academics to rethink what is to be learned and how it should be learned. Ultimately, the study will bring new light into the co-creation of new knowledge in a social interactive learning environment and challenges teachers to embrace the 21st century of learning with mobile technologies to deepen and extend learning opportunities.

Keywords: mobile computer supported collaborative learning, mobile instant messaging, mobile learning, new knowledge co-creation, self-regulated learning

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6815 Innovative Approaches to Formal Education: Effect of Online Cooperative Learning Embedded Blended Learning on Student's Academic Achievement and Attitude

Authors: Mohsin Javed

Abstract:

School Education department is usually criticized for utilizing quite low or fewer academic days due to many reasons like extreme weather conditions, sudden holidays, summer vocations, pandemics and, terrorism etc. The purpose of the experimental study was to determine the efficacy of online cooperative learning (OCL) integrated in the rotation model of blended learning. The effects on academic achievement of students and students' attitude about OCL embedded learning were assessed. By using a posttest only control group design, sixty-two first-year students were randomly allocated to either the experimental (30) or control (32) group. The control group received face to face classes for six sessions per week, while the experimental group had three OCL and three formal sessions per week under rotation model. Students' perceptions of OCL were evaluated using a survey questionnaire. Data was analyzed by independent sample t test and one sample t test. According to findings, the intervention greatly improved the state of the dependent variables. The results demonstrate that OCL can be successfully implemented in formal education using a blended learning rotation approach. Higher secondary institutions are advised to use this model in situations like Covid 19, smog, unexpected holidays, instructor absence from class due to increased responsibilities, and summer vacations.

Keywords: blended learning, online cooperative learning, rotation model of blended learning, supplementing

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6814 Simulation Model for Evaluating the Impact of Adaptive E-Learning in the Agricultural Sector

Authors: Maria Nabakooza

Abstract:

Efficient agricultural production is very significant in attaining food sufficiency and security in the world. Many methods are employed by the farmers while attending to their gardens, from manual to mechanized, with Farmers range from subsistence to commercial depending on the motive. This creates a lacuna in the modes of operation in this field as different farmers will take different approaches. This has led to many e-Learning courses being introduced to address this gap. Many e-learning systems use advanced network technologies like Web services, grid computing to promote learning at any time and any place. Many of the existing systems have not inculcated the applicability of the modules in them, the tools to be used and further access whether they are the right tools for the right job. A thorough investigation into the applicability of adaptive eLearning in the agricultural sector has not been taken into account; enabling the assumption that eLearning is the right tool for boosting productivity in this sector. This study comes in to provide an insight and thorough analysis as to whether adaptive eLearning is the right tool for boosting agricultural productivity. The Simulation will adopt a system dynamics modeling approach as a way of examining causality and effect relationship. This study will provide teachers with an insight into which tools they should adopt in designing, and provide students the opportunities to achieve an orderly learning experience through adaptive navigating e-learning services.

Keywords: agriculture, adaptive, e-learning, technology

Procedia PDF Downloads 246
6813 Understanding Innovation, Mentorship, and Motivation in Teams, a Design-Centric Approach for Undergraduates

Authors: K. Z. Tang, K. Ameek, K. Kuang

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Rapid product development cycles and changing economic conditions compel businesses to find new ways to stay relevant and effective. One of the ways which many companies have adopted is to spur innovations within the various team-based units in the organization. It would be relevant and important to ensure our graduates are ready to excel in such evolving conditions within their professional eco-systems. However, it is not easy to understand the interplays of nurturing team innovation and improving students’ learning, in the context of engineering education. In this study, we seek to understand team innovation and explore ways to improve students’ performance and learning, via motivation and mentorship. Learning goals from a group of students are collected during a carefully designed two-week long summer programme to provide insights on the main themes, within the context of learning and working in a team.

Keywords: team innovation, mentorship, motivation, learning

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6812 Personality Based Adaptive E-Learning 3D Game

Authors: Yasith Nayana, Janani Manamperuma, Lalindi Amarasinghe, Sasanka Kodithuwakku

Abstract:

Educational games are popular among current e-learning systems. The approach to education through interactive media is expected to motivate students and encourage participation and engagement. ‘Kalayathra’ is an adaptive, player centered e-learning 3D game. The game identifies the player’s personality and adapt the gaming environment according to the player’s preference. Our platform measures the student’s performance and support learning through player assessment. Player experience is a good measure of the level of fun and education presented to players. To assess the level of playability we introduce an educational playability model. ‘Kalayathra’ is developed according to the GCE O/L syllabus and teaching guide in Sri Lankan education system. The game is capable of guiding players into the environment and aid them in tasks and activities depending on how much the player requires help.

Keywords: e-learning, games, adaptive, personality, gamification, player experience

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6811 Voting Representation in Social Networks Using Rough Set Techniques

Authors: Yasser F. Hassan

Abstract:

Social networking involves use of an online platform or website that enables people to communicate, usually for a social purpose, through a variety of services, most of which are web-based and offer opportunities for people to interact over the internet, e.g. via e-mail and ‘instant messaging’, by analyzing the voting behavior and ratings of judges in a popular comments in social networks. While most of the party literature omits the electorate, this paper presents a model where elites and parties are emergent consequences of the behavior and preferences of voters. The research in artificial intelligence and psychology has provided powerful illustrations of the way in which the emergence of intelligent behavior depends on the development of representational structure. As opposed to the classical voting system (one person – one decision – one vote) a new voting system is designed where agents with opposed preferences are endowed with a given number of votes to freely distribute them among some issues. The paper uses ideas from machine learning, artificial intelligence and soft computing to provide a model of the development of voting system response in a simulated agent. The modeled development process involves (simulated) processes of evolution, learning and representation development. The main value of the model is that it provides an illustration of how simple learning processes may lead to the formation of structure. We employ agent-based computer simulation to demonstrate the formation and interaction of coalitions that arise from individual voter preferences. We are interested in coordinating the local behavior of individual agents to provide an appropriate system-level behavior.

Keywords: voting system, rough sets, multi-agent, social networks, emergence, power indices

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6810 Gardening as a Contextual Scaffold for Learning: Connecting Community Wisdom for Science and Health Learning through Participatory Action Research

Authors: Kamal Prasad Acharya

Abstract:

The related literature suggests that teaching and learning science at the basic level community schools in Nepal is based on book recitation. Consequently, the achievement levels and the understanding of basic science concepts is much below the policy expectations. In this context, this study intended to gain perception in the implementation practices of school gardens ‘One Garden One School’ for science learning and to meet the target of sustainable development goals that connects community wisdom regarding school gardening activities (SGAs) for science learning. This Participatory Action Research (PAR) study was done at the action school located in Province 3, Chitwan of Federal Nepal, supported under the NORHED/Rupantaran project. The purpose of the study was to connect the community wisdom related to gardening activities as contextual scaffolds for science learning. For this, in-depth interviews and focus group discussions were applied to collect data which were analyzed using a thematic analysis. Basic level students, science teachers, and parents reported having wonderful experiences such as active and meaningful engagement in school gardening activities for science learning as well as science teachers’ motivation in activity-based science learning. Overall, teachers, students, and parents reported that the school gardening activities have been found to have had positive effects on students’ science learning as they develop basic scientific concepts by connecting community wisdom as a contextual scaffold. It is recommended that the establishment of a school garden is important for science learning in community schools throughout Nepal.

Keywords: contextual scaffold, community wisdom, science and health learning, school garden

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6809 The Impact of Using Microlearning to Enhance Students' Programming Skills and Learning Motivation

Authors: Ali Alqarni

Abstract:

This study aims to explore the impact of microlearning on the development of the programming skills as well as on the motivation for learning of first-year high schoolers in Jeddah. The sample consists of 78 students, distributed as 40 students in the control group, and 38 students in the treatment group. The quasi-experimental method, which is a type of quantitative method, was used in this study. In addition to the technological tools used to create and deliver the digital content, the study utilized two tools to collect the data: first, an observation card containing a list of programming skills, and second, a tool to measure the student's motivation for learning. The findings indicate that microlearning positively impacts programming skills and learning motivation for students. The study, then, recommends implementing and expanding the use of microlearning in educational contexts both in the general education level and the higher education level.

Keywords: educational technology, teaching strategies, online learning, microlearning

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6808 Exploring Utility and Intrinsic Value among UAE Arabic Teachers in Integrating M-Learning

Authors: Dina Tareq Ismail, Alexandria A. Proff

Abstract:

The United Arab Emirates (UAE) is a nation seeking to advance in all fields, particularly education. One area of focus for UAE 2021 agenda is to restructure UAE schools and universities by equipping them with highly developed technology. The agenda also advises educational institutions to prepare students with applicable and transferrable Information and Communication Technology (ICT) skills. Despite the emphasis on ICT and computer literacy skills, there exists limited empirical data on the use of M-Learning in the literature. This qualitative study explores the motivation of higher primary Arabic teachers in private schools toward implementing and integrating M-Learning apps in their classrooms. This research employs a phenomenological approach through the use of semistructured interviews with nine purposefully selected Arabic teachers. The data were analyzed using a content analysis via multiple stages of coding: open, axial, and thematic. Findings reveal three primary themes: (1) Arabic teachers with high levels of procedural knowledge in ICT are more motivated to implement M-Learning; (2) Arabic teachers' perceptions of self-efficacy influence their motivation toward implementation of M-Learning; (3) Arabic teachers implement M-Learning when they possess high utility and/or intrinsic value in these applications. These findings indicate a strong need for further training, equipping, and creating buy-in among Arabic teachers to enhance their ICT skills in implementing M-Learning. Further, given the limited availability of M-Learning apps designed for use in the Arabic language on the market, it is imperative that developers consider designing M-Learning tools that Arabic teachers, and Arabic-speaking students, can use and access more readily. This study contributes to closing the knowledge gap on teacher-motivation for implementing M-Learning in their classrooms in the UAE.

Keywords: ICT skills, m-learning, self-efficacy, teacher-motivation

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6807 Enhancing Critical Thinking through a Virtual Learning Environment

Authors: Diana Meeks

Abstract:

The use of a virtual learning environment (VLE), via the Second Life Platform has been a positive experience to enhance critical thinking, for executive graduate nursing practicum students. Due to the interest of faculty and students, the opportunity to immerse students via a virtual learning environment to enhance critical thinking related to the nurse executive role was explored. The College of Nursing realized the potential to enhance critical thinking and incorporated the Second Life, virtual learning environment platform into their graduate nursing program within their executive practicum course. The results from students and faculty regarding this experience have been positive. Students state the VLE platform has enhanced their critical thinking and interaction with peers. To date, course refinement incorporating a Second Life, virtual learning environment for the nurse executive practicum students continues. As a result, a designated subject matter expert has been designated for this course. The development and incorporation of the VLE approach will be presented.

Keywords: nursing, virtual learning environment, critical thinking, VLE

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6806 Analysis and Detection of Facial Expressions in Autism Spectrum Disorder People Using Machine Learning

Authors: Muhammad Maisam Abbas, Salman Tariq, Usama Riaz, Muhammad Tanveer, Humaira Abdul Ghafoor

Abstract:

Autism Spectrum Disorder (ASD) refers to a developmental disorder that impairs an individual's communication and interaction ability. Individuals feel difficult to read facial expressions while communicating or interacting. Facial Expression Recognition (FER) is a unique method of classifying basic human expressions, i.e., happiness, fear, surprise, sadness, disgust, neutral, and anger through static and dynamic sources. This paper conducts a comprehensive comparison and proposed optimal method for a continued research project—a system that can assist people who have Autism Spectrum Disorder (ASD) in recognizing facial expressions. Comparison has been conducted on three supervised learning algorithms EigenFace, FisherFace, and LBPH. The JAFFE, CK+, and TFEID (I&II) datasets have been used to train and test the algorithms. The results were then evaluated based on variance, standard deviation, and accuracy. The experiments showed that FisherFace has the highest accuracy for all datasets and is considered the best algorithm to be implemented in our system.

Keywords: autism spectrum disorder, ASD, EigenFace, facial expression recognition, FisherFace, local binary pattern histogram, LBPH

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6805 Using Deep Learning in Lyme Disease Diagnosis

Authors: Teja Koduru

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Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

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6804 A Framework for Rating Synchronous Video E-Learning Applications

Authors: Alex Vakaloudis, Juan Manuel Escano-Gonzalez

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Setting up a system to broadcast live lectures on the web is a procedure which on the surface does not require any serious technical skills mainly due to the facilities provided by popular learning management systems and their plugins. Nevertheless, producing a system of outstanding quality is a multidisciplinary and by no means a straightforward task. This complicatedness may be responsible for the delivery of an overall poor experience to the learners, and it calls for a formal rating framework that takes into account the diverse aspects of an architecture for synchronous video e-learning systems. We discuss the specifications of such a framework which at its final stage employs fuzzy logic technique to transform from qualitative to quantitative results.

Keywords: synchronous video, fuzzy logic, rating framework, e-learning

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6803 Students' Perception of Using Dental E-Models in an Inquiry-Based Curriculum

Authors: Yanqi Yang, Chongshan Liao, Cheuk Hin Ho, Susan Bridges

Abstract:

Aim: To investigate student’s perceptions of using e-models in an inquiry-based curriculum. Approach: 52 second-year dental students completed a pre- and post-test questionnaire relating to their perceptions of e-models and their use in inquiry-based learning. The pre-test occurred prior to any learning with e-models. The follow-up survey was conducted after one year's experience of using e-models. Results: There was no significant difference between the two sets of questionnaires regarding student’s perceptions of the usefulness of e-models and their willingness to use e-models in future inquiry-based learning. Most of the students preferred using both plaster models and e-models in tandem. Conclusion: Students did not change their attitude towards e-models and most of them agreed or were neutral that e-models are useful in inquiry-based learning. Whilst recognizing the utility of 3D models for learning, student's preference for combining these with solid models has implications for the development of haptic sensibility in an operative discipline.

Keywords: e-models, inquiry-based curriculum, education, questionnaire

Procedia PDF Downloads 420
6802 Cluster Analysis and Benchmarking for Performance Optimization of a Pyrochlore Processing Unit

Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

Abstract:

Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

Procedia PDF Downloads 138
6801 A Review on Parametric Optimization of Casting Processes Using Optimization Techniques

Authors: Bhrugesh Radadiya, Jaydeep Shah

Abstract:

In Indian foundry industry, there is a need of defect free casting with minimum production cost in short lead time. Casting defect is a very large issue in foundry shop which increases the rejection rate of casting and wastage of materials. The various parameters influences on casting process such as mold machine related parameters, green sand related parameters, cast metal related parameters, mold related parameters and shake out related parameters. The mold related parameters are most influences on casting defects in sand casting process. This paper review the casting produced by foundry with shrinkage and blow holes as a major defects was analyzed and identified that mold related parameters such as mold temperature, pouring temperature and runner size were not properly set in sand casting process. These parameters were optimized using different optimization techniques such as Taguchi method, Response surface methodology, Genetic algorithm and Teaching-learning based optimization algorithm. Finally, concluded that a Teaching-learning based optimization algorithm give better result than other optimization techniques.

Keywords: casting defects, genetic algorithm, parametric optimization, Taguchi method, TLBO algorithm

Procedia PDF Downloads 721
6800 A Multi-Agent Simulation of Serious Games to Predict Their Impact on E-Learning Processes

Authors: Ibtissem Daoudi, Raoudha Chebil, Wided Lejouad Chaari

Abstract:

Serious games constitute actually a recent and attractive way supposed to replace the classical boring courses. However, the choice of the adapted serious game to a specific learning environment remains a challenging task that makes teachers unwilling to adopt this concept. To fill this gap, we present, in this paper, a multi-agent-based simulator allowing to predict the impact of a serious game integration in a learning environment given several game and players characteristics. As results, the presented tool gives intensities of several emotional aspects characterizing learners reactions to the serious game adoption. The presented simulator is tested to predict the effect of basing a coding course on the serious game ”CodeCombat”. The obtained results are compared with feedbacks of using the same serious game in a real learning process.

Keywords: emotion, learning process, multi-agent simulation, serious games

Procedia PDF Downloads 392
6799 Extent of I.C.T Application in Record Management and Factors Hindering the Utilization of E-Learning in the Government Owned Universities in Enugu State, Nigeria

Authors: Roseline Unoma Chidobi

Abstract:

The purpose of this study is to identify the extent of Information Communication Technology (ICT) application in record management and some factors militating against the utilization of e-learning in the universities in Enugu state. The study was a survey research the quantitative data were collected through a 30 – item questionnaire title extent of ICT Application in Record management and militating Factors in the utilization of e-learning (EIARMMFUE). This was administered on a population of 603 respondents made up of university academic staff and senior administrative staff. The data were analyzed using mean, standard deviation and t-test statistics on a modified 4 point rating scale. Findings of the study revealed among others that ICT are not adequately applied in the management of records in the Universities in Nigeria. Factors like wrong notion or superstitious believe hinder the effective utilization of e – learning approach. The study recommended that the use of ICT in record management should be enhanced in order to achieve effective school management. All the factors militating against the effective utilization of e-learning approach should be addressed for the maximum realization of teaching and learning.

Keywords: e-learning, information communication, teaching, technology, tertiary institution

Procedia PDF Downloads 517
6798 Integrating Sustainable Development Goals in Teaching Mathematics Using Project Based Learning

Authors: S. Goel

Abstract:

In the current scenario, education should be realistic and nature-friendly. The earlier definition of education was restricted to the holistic development of the child which help them to increase their capacity and helps in social upliftment. But such definition gives a more individualistic aim of education. Due to that individualistic aim, we have become disconnected from nature. So, a school should be a place which provides students with an area to explore. They should get practical learning or learning from nature which is also propounded by Rousseau in the mid-eighteenth century. Integrating Sustainable development goals in the school curriculum will make it possible to connect the nature with the lives of the children in the classroom. Then, students will be more aware and sensitive towards their social and natural surroundings. The research attempts to examine the efficiency of project-based learning in mathematics to create awareness around sustainable development goals. The major finding of the research was that students are less aware of sustainable development goals, but when given time and an appropriate learning environment, students can be made aware of these goals. In this research, project-based learning was used to make students aware of sustainable development goals. Students were given pre test and post test which helped in analyzing their performance. After the intervention, post test result showed that mathematics projects can create an awareness of sustainable development goals.

Keywords: holistic development, natural learning, project based learning, sustainable development goals

Procedia PDF Downloads 173
6797 FLIME - Fast Low Light Image Enhancement for Real-Time Video

Authors: Vinay P., Srinivas K. S.

Abstract:

Low Light Image Enhancement is of utmost impor- tance in computer vision based tasks. Applications include vision systems for autonomous driving, night vision devices for defence systems, low light object detection tasks. Many of the existing deep learning methods are resource intensive during the inference step and take considerable time for processing. The algorithm should take considerably less than 41 milliseconds in order to process a real-time video feed with 24 frames per second and should be even less for a video with 30 or 60 frames per second. The paper presents a fast and efficient solution which has two main advantages, it has the potential to be used for a real-time video feed, and it can be used in low compute environments because of the lightweight nature. The proposed solution is a pipeline of three steps, the first one is the use of a simple function to map input RGB values to output RGB values, the second is to balance the colors and the final step is to adjust the contrast of the image. Hence a custom dataset is carefully prepared using images taken in low and bright lighting conditions. The preparation of the dataset, the proposed model, the processing time are discussed in detail and the quality of the enhanced images using different methods is shown.

Keywords: low light image enhancement, real-time video, computer vision, machine learning

Procedia PDF Downloads 188