Search results for: limit order book learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21213

Search results for: limit order book learning

20163 From Mathematics Project-Based Learning to Commercial Product Using Geometer’s Sketchpad (GSP)

Authors: Krongthong Khairiree

Abstract:

The purpose of this research study is to explore mathematics project-based learning approach and the use of technology in the context of school mathematics in Thailand. Data of the study were collected from 6 sample secondary schools and the students were 6-14 years old. Research findings show that through mathematics project-based learning approach and the use of GSP, students were able to make mathematics learning fun and challenging. Based on the students’ interviews they revealed that, with GSP, they were able to visualize and create graphical representations, which will enable them to develop their mathematical thinking skills, concepts and understanding. The students had fun in creating variety of graphs of functions which they can not do by drawing on graph paper. In addition, there are evidences to show the students’ abilities in connecting mathematics to real life outside the classroom and commercial products, such as weaving, patterning of broomstick, and ceramics design.

Keywords: mathematics, project-based learning, Geometer’s Sketchpad (GSP), commercial products

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20162 Teacher Education and the Impact of Higher Education Foreign Language Requirements on Students with Learning Disabilities

Authors: Joao Carlos Koch Junior, Risa Takashima

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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 448
20161 Machine Learning Techniques to Develop Traffic Accident Frequency Prediction Models

Authors: Rodrigo Aguiar, Adelino Ferreira

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Road traffic accidents are the leading cause of unnatural death and injuries worldwide, representing a significant problem of road safety. In this context, the use of artificial intelligence with advanced machine learning techniques has gained prominence as a promising approach to predict traffic accidents. This article investigates the application of machine learning algorithms to develop traffic accident frequency prediction models. Models are evaluated based on performance metrics, making it possible to do a comparative analysis with traditional prediction approaches. The results suggest that machine learning can provide a powerful tool for accident prediction, which will contribute to making more informed decisions regarding road safety.

Keywords: machine learning, artificial intelligence, frequency of accidents, road safety

Procedia PDF Downloads 87
20160 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

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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

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20159 Direct Electrical Communication of Redox Enzyme Based on 3-Dimensional Crosslinked Redox Enzyme/Carbon Nanotube on a Thiol-Modified Au Surface

Authors: A. K. M. Kafi, S. N. Nina, Mashitah M. Yusoff

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In this work, we have described a new 3-dimensional (3D) network of crosslinked Horseradish Peroxidase/Carbon Nanotube (HRP/CNT) on a thiol-modified Au surface in order to build up the effective electrical wiring of the enzyme units with the electrode. This was achieved by the electropolymerization of aniline-functionalized carbon nanotubes (CNTs) and 4-aminothiophenol -modified-HRP on a 4-aminothiophenol monolayer-modified Au electrode. The synthesized 3D HRP/CNT networks were characterized with cyclic voltammetry and amperometry, resulting the establishment direct electron transfer between the redox active unit of HRP and the Au surface. Electrochemical measurements reveal that the immobilized HRP exhibits high biological activity and stability and a quasi-reversible redox peak of the redox center of HRP was observed at about −0.355 and −0.275 V vs. Ag/AgCl. The electron transfer rate constant, KS and electron transfer co-efficient were found to be 0.57 s-1 and 0.42, respectively. Based on the electrocatalytic process by direct electrochemistry of HRP, a biosensor for detecting H2O2 was developed. The developed biosensor exhibits excellent electrocatalytic activity for the reduction of H2O2. The proposed biosensor modified with HRP/CNT 3D network displays a broader linear range and a lower detection limit for H2O2 determination. The linear range is from 1.0×10−7 to 1.2×10−4M with a detection limit of 2.2.0×10−8M at 3σ. Moreover, this biosensor exhibits very high sensitivity, good reproducibility and long-time stability. In summary, ease of fabrication, a low cost, fast response and high sensitivity are the main advantages of the new biosensor proposed in this study. These obvious advantages would really help for the real analytical applicability of the proposed biosensor.

Keywords: biosensor, nanomaterials, redox enzyme, thiol-modified Au surface

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20158 Analogy to Continental Divisions: An Attention-Grabbing Approach to Teach Taxonomic Hierarchy to Students

Authors: Sagheer Ahmad

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Teaching is a sacred profession whereby students are developed in their mental abilities to cope with the challenges of the remote world. Thinkers have developed plenty of interesting ways to make the learning process quick and absorbing for the students. However, third world countries are still lacking these remote facilities in the institutions, and therefore, teaching is totally dependent upon the skills of the teachers. Skillful teachers use self-devised and stimulating ideas to grab the attention of their students. Most of the time their ideas are based on local grounds with which the students are already familiar. This self-explanatory characteristic is the base of several local ideologies to disseminate scientific knowledge to new generations. Biology is such a subject which largely bases upon hypotheses, and teaching it in an interesting way is needful to create a friendly relationship between teacher and student, and to make a fantastic learning environment. Taxonomic classification if presented as it is, may not be attractive for the secondary school students who just start learning about biology at elementary levels. Presenting this hierarchy by exemplifying Kingdom, Phylum, Class, Order, family, genus and Species as comparatives of our division into continents, countries, cities, towns, villages, homes and finally individuals could be an attention-grabbing approach to make this concept get into bones of students. Similarly, many other interesting approaches have also been adopted to teach students in a fascinating way so that learning science subjects may not be boring for them. Discussing these appealing ways of teaching students can be a valuable stimulus to refine teaching methodologies about science, thereby promoting the concept of friendly learning.

Keywords: biology, innovative approaches, taxonomic classification, teaching

Procedia PDF Downloads 248
20157 A Constructivist Approach and Tool for Autonomous Agent Bottom-up Sequential Learning

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

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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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20156 Airfield Pavements Made of Reinforced Concrete: Dimensioning According to the Theory of Limit States and Eurocode

Authors: M. Linek, P. Nita

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In the previous airfield construction industry, pavements made of reinforced concrete have been used very rarely; however, the necessity to use this type of pavements in an emergency situations justifies the need reference to this issue. The paper concerns the problem of airfield pavement dimensioning made of reinforced concrete and the evaluation of selected dimensioning methods of reinforced concrete slabs intended for airfield pavements. Analysis of slabs dimensioning, according to classical method of limit states has been performed and it has been compared to results obtained in case of methods complying with Eurocode 2 guidelines. Basis of an analysis was a concrete slab of class C35/45 with reinforcement, located in tension zone. Steel bars of 16.0 mm have been used as slab reinforcement. According to comparative analysis of obtained results, conclusions were reached regarding application legitimacy of the discussed methods and their design advantages.

Keywords: rainforced concrete, cement concrete, airport pavements, dimensioning

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20155 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

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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

Procedia PDF Downloads 240
20154 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

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20153 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

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20152 Comparison of Machine Learning and Deep Learning Algorithms for Automatic Classification of 80 Different Pollen Species

Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. That is why the need for automation of this task is urgent. A lot of studies have investigated the subject using different standard image processing descriptors and sometimes hand-crafted ones.In this work, we make a comparative study between classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN, Autoencoders, Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches

Keywords: pollens identification, features extraction, pollens classification, automated palynology

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20151 The Democracy of Love and Suffering in the Erotic Epigrams of Meleager

Authors: Carlos A. Martins de Jesus

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The Greek anthology, first put together in the tenth century AD, gathers in two separate books a large number of epigrams devoted to love and its consequences, both of hetero (book V) and homosexual (book XII) nature. While some poets wrote epigrams of only one genre –that is the case of Strato (II cent. BC), the organizer of a wide-spread garland of homosexual epigrams –, several others composed within both categories, often using the same topics of love and suffering. Using Plato’s theorization of two different kinds of Eros (Symp. 180d-182a), the popular (pandemos) and the celestial (ouranios), homoerotic epigrammatic love is more often associated with the first one, while heterosexual poetry tends to be connected to a higher form of love. This paper focuses on the epigrammatic production of a single first-century BC poet, Meleager, aiming to look for the similarities and differences on singing both kinds of love. From Meleager, the Greek Anthology –a garland whose origins have been traced back to the poet’s garland itself– preserves more than sixty heterosexual and 48 homosexual epigrams, an important and unprecedented amount of poems that are able to trace a complete profile of his way of singing love. Meleager’s poetry deals with personal experience and emotions, frequently with love and the unhappiness that usually comes from it. Most times he describes himself not as an active and engaged lover, but as one struck by the beauty of a woman or boy, i.e., in a stage prior to erotic consummation. His epigrams represent the unreal and fantastic (literally speaking) world of the lover, in which the imagery and wordplays are used to convey emotion in the epigrams of both genres. Elsewhere Meleager surprises the reader by offering a surrealist or dreamlike landscape where everyday adventures are transcribed into elaborate metaphors for erotic feeling. For instance, in 12.81, the lovers are shipwrecked, and as soon as they have disembarked, they are promptly kidnapped by a figure who is both Eros and a beautiful boy. Particularly –and worth-to-know why significant – in the homosexual poems collected in Book XII, mythology also plays an important role, namely in the figure and the scene of Ganimedes’ kidnap by Zeus for his royal court (12. 70, 94). While mostly refusing the Hellenistic model of dramatic love epigram, in which a small everyday scene is portrayed –and 5. 182 is a clear exception to this almost rule –, Meleager actually focuses on the tumultuous inside of his (poetic) lovers, in the realm of a subject that feels love and pain far beyond his/her erotic preferences. In relation to loving and suffering –mostly suffering, it has to be said –, Meleager’s love is therefore completely democratic. There is no real place in his epigrams for the traditional association mentioned before between homoeroticism and a carnal-erotic-pornographic love, while the heterosexual one being more evenly and pure, so to speak.

Keywords: epigram, erotic epigram, Greek Anthology, Meleager

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20150 Machine Learning-Based Workflow for the Analysis of Project Portfolio

Authors: Jean Marie Tshimula, Atsushi Togashi

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We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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20149 Investigating Learners’ Online Learning Experiences in a Blended-Learning School Environment

Authors: Abraham Ampong

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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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20148 A Study on Performance Prediction in Early Design Stage of Apartment Housing Using Machine Learning

Authors: Seongjun Kim, Sanghoon Shim, Jinwooung Kim, Jaehwan Jung, Sung-Ah Kim

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As the development of information and communication technology, the convergence of machine learning of the ICT area and design is attempted. In this way, it is possible to grasp the correlation between various design elements, which was difficult to grasp, and to reflect this in the design result. In architecture, there is an attempt to predict the performance, which is difficult to grasp in the past, by finding the correlation among multiple factors mainly through machine learning. In architectural design area, some attempts to predict the performance affected by various factors have been tried. With machine learning, it is possible to quickly predict performance. The aim of this study is to propose a model that predicts performance according to the block arrangement of apartment housing through machine learning and the design alternative which satisfies the performance such as the daylight hours in the most similar form to the alternative proposed by the designer. Through this study, a designer can proceed with the design considering various design alternatives and accurate performances quickly from the early design stage.

Keywords: apartment housing, machine learning, multi-objective optimization, performance prediction

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20147 Effects of Ubiquitous 360° Learning Environment on Clinical Histotechnology Competence

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

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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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20146 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

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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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20145 The Role of Motivational Beliefs and Self-Regulated Learning Strategies in The Prediction of Mathematics Teacher Candidates' Technological Pedagogical And Content Knowledge (TPACK) Perceptions

Authors: Ahmet Erdoğan, Şahin Kesici, Mustafa Baloğlu

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Information technologies have lead to changes in the areas of communication, learning, and teaching. Besides offering many opportunities to the learners, these technologies have changed the teaching methods and beliefs of teachers. What the Technological Pedagogical Content Knowledge (TPACK) means to the teachers is considerably important to integrate technology successfully into teaching processes. It is necessary to understand how to plan and apply teacher training programs in order to balance students’ pedagogical and technological knowledge. Because of many inefficient teacher training programs, teachers have difficulties in relating technology, pedagogy and content knowledge each other. While providing an efficient training supported with technology, understanding the three main components (technology, pedagogy and content knowledge) and their relationship are very crucial. The purpose of this study is to determine whether motivational beliefs and self-regulated learning strategies are significant predictors of mathematics teacher candidates' TPACK perceptions. A hundred seventy five Turkish mathematics teachers candidates responded to the Motivated Strategies for Learning Questionnaire (MSLQ) and the Technological Pedagogical And Content Knowledge (TPACK) Scale. Of the group, 129 (73.7%) were women and 46 (26.3%) were men. Participants' ages ranged from 20 to 31 years with a mean of 23.04 years (SD = 2.001). In this study, a multiple linear regression analysis was used. In multiple linear regression analysis, the relationship between the predictor variables, mathematics teacher candidates' motivational beliefs, and self-regulated learning strategies, and the dependent variable, TPACK perceptions, were tested. It was determined that self-efficacy for learning and performance and intrinsic goal orientation are significant predictors of mathematics teacher candidates' TPACK perceptions. Additionally, mathematics teacher candidates' critical thinking, metacognitive self-regulation, organisation, time and study environment management, and help-seeking were found to be significant predictors for their TPACK perceptions.

Keywords: candidate mathematics teachers, motivational beliefs, self-regulated learning strategies, technological and pedagogical knowledge, content knowledge

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20144 Parental Engagement with Their Preschoolers’ Cognitive Development Prior to Their Kindergarten Admission: Sharjah-Based Case Study

Authors: Nada Mohammad Eljeshi

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In the United Arab Emirates (UAE), preschoolers can enroll in kindergarten after completing four years old by August 31 of their admission year. This study aims to better understand how Sharjah-based parents’ engagement with preschoolers contributes to their phonological awareness, literacy development, and print knowledge before their kindergarten admission considering cognitive development is addressed in the UAE national child care standards. More specifically, it will discuss the importance of cognitive development activities to preschoolers, the rationale behind defining the admission age to kindergarten and compare and benchmark the policy to other countries. To achieve this study's objectives, an online survey was conducted and distributed. Respondents were asked 13 dichotomous questions related to activities that promote the preschooler’s linguistics literacy and cognitive development. The results suggested parents’ emphasis on phonological awareness, followed by developing their print knowledge. However, the majority of the surveyed parents did not engage in literacy development with their preschoolers. On this basis, it is clear parents’ awareness should occur by introducing various activities such as book reading, that there is a need to introduce and encourage parents to various activities such as reading a printed book and drawings to keep up with their children's cognitive development. The survey results suggested an emphasis on phonological awareness, followed by developing their print knowledge. However, the majority of the surveyed parents did not engage in literacy development with their preschoolers. On this basis, parental awareness of the importance of preschoolers' cognitive development should be developed and engage the parents in understanding their preschooler’s cognitive development before entering kindergarten.

Keywords: preschoolers, cognitive development, parental engagement, Sharjah-based case study

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20143 Machine Learning Techniques in Seismic Risk Assessment of Structures

Authors: Farid Khosravikia, Patricia Clayton

Abstract:

The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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20142 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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20141 Deep-Learning Based Approach to Facial Emotion Recognition through Convolutional Neural Network

Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

Abstract:

Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. Accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER, benefiting from deep learning, especially CNN and VGG16. First, the data is pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning

Procedia PDF Downloads 93
20140 Teaching about Justice With Justice: How Using Experiential, Learner Centered Literacy Methodology Enhances Learning of Justice Related Competencies for Young Children

Authors: Bruna Azzari Puga, Richard Roe, Andre Pagani de Souza

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abstract outlines a proposed study to examine how and to what extent interactive, experiential, learner centered methodology develops learning of basic civic and democratic competencies among young children. It stems from the Literacy and Law course taught at Georgetown University Law Center in Washington, DC, since 1998. Law students, trained in best literacy practices and legal cases affecting literacy development, read “law related” children’s books and engage in interactive and extension activities with emerging readers. The law students write a monthly journal describing their experiences and a final paper: a conventional paper or a children’s book illuminating some aspect of literacy and law. This proposal is based on the recent adaptation of Literacy and Law to Brazil at Mackenzie Presbyterian University in São Paulo in three forms: first, a course similar to the US model, often conducted jointly online with Brazilian and US law students; second, a similar course that combines readings of children’s literature with activity based learning, with law students from a satellite Mackenzie campus, for young children from a vulnerable community near the city; and third, a course taught by law students at the main Mackenzie campus for 4th grade students at the Mackenzie elementary school, that is wholly activity and discourse based. The workings and outcomes of these courses are well documented by photographs, reports, lesson plans, and law student journals. The authors, faculty who teach the above courses at Mackenzie and Georgetown, observe that literacy, broadly defined as cognitive and expressive development through reading and discourse-based activities, can be influential in developing democratic civic skills, identifiable by explicit civic competencies. For example, children experience justice in the classroom through cooperation, creativity, diversity, fairness, systemic thinking, and appreciation for rules and their purposes. Moreover, the learning of civic skills as well as the literacy skills is enhanced through interactive, learner centered practices in which the learners experience literacy and civic development. This study will develop rubrics for individual and classroom teaching and supervision by examining 1) the children’s books and students diaries of participating law students and 2) the collection of photos and videos of classroom activities, and 3) faculty and supervisor observations and reports. These rubrics, and the lesson plans and activities which are employed to advance the higher levels of performance outcomes, will be useful in training and supervision and in further replication and promotion of this form of teaching and learning. Examples of outcomes include helping, cooperating and participating; appreciation of viewpoint diversity; knowledge and utilization of democratic processes, including due process, advocacy, individual and shared decision making, consensus building, and voting; establishing and valuing appropriate rules and a reasoned approach to conflict resolution. In conclusion, further development and replication of the learner centered literacy and law practices outlined here can lead to improved qualities of democratic teaching and learning supporting mutual respect, positivity, deep learning, and the common good – foundation qualities of a sustainable world.

Keywords: democracy, law, learner-centered, literacy

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20139 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 250
20138 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

Procedia PDF Downloads 281
20137 An ANN-Based Predictive Model for Diagnosis and Forecasting of Hypertension

Authors: Obe Olumide Olayinka, Victor Balanica, Eugen Neagoe

Abstract:

The effects of hypertension are often lethal thus its early detection and prevention is very important for everybody. In this paper, a neural network (NN) model was developed and trained based on a dataset of hypertension causative parameters in order to forecast the likelihood of occurrence of hypertension in patients. Our research goal was to analyze the potential of the presented NN to predict, for a period of time, the risk of hypertension or the risk of developing this disease for patients that are or not currently hypertensive. The results of the analysis for a given patient can support doctors in taking pro-active measures for averting the occurrence of hypertension such as recommendations regarding the patient behavior in order to lower his hypertension risk. Moreover, the paper envisages a set of three example scenarios in order to determine the age when the patient becomes hypertensive, i.e. determine the threshold for hypertensive age, to analyze what happens if the threshold hypertensive age is set to a certain age and the weight of the patient if being varied, and, to set the ideal weight for the patient and analyze what happens with the threshold of hypertensive age.

Keywords: neural network, hypertension, data set, training set, supervised learning

Procedia PDF Downloads 390
20136 Personality Based Adaptive E-Learning 3D Game

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

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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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20135 Forward Conditional Restricted Boltzmann Machines for the Generation of Music

Authors: Johan Loeckx, Joeri Bultheel

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Recently, the application of deep learning to music has gained popularity. Its true potential, however, has been largely unexplored. In this paper, a new idea for representing the dynamic behavior of music is proposed. A ”forward” conditional RBM takes into account not only preceding but also future samples during training. Though this may sound controversial at first sight, it will be shown that it makes sense from a musical and neuro-cognitive perspective. The model is applied to reconstruct music based upon the first notes and to improvise in the musical style of a composer. Different to expectations, reconstruction accuracy with respect to a regular CRBM with the same order, was not significantly improved. More research is needed to test the performance on unseen data.

Keywords: deep learning, restricted boltzmann machine, music generation, conditional restricted boltzmann machine (CRBM)

Procedia PDF Downloads 520
20134 The Impact of Using Microlearning to Enhance Students' Programming Skills and Learning Motivation

Authors: Ali Alqarni

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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

Procedia PDF Downloads 127