Search results for: learning style scale

Authors: Bruce Wrightsman

Abstract:

Traditionally, in architectural education, we develop studio projects with learning agendas that try to minimize conflict and reveal clear design objectives. Knowledge is gleaned only tacitly through confronting the reciprocity of site and form, space and light, structure and envelope. This institutional reality can limit student learning to the latent learning opportunities they will have to confront later in practice. One intent of academic design-build projects is to address the learning opportunities which one can discover in the messy grey areas of design. In this immersive experience, students confront the limitations of classroom learning and are exposed to challenges that demand collaborative practice. As a result, design-build has been widely adopted in an attempt to address perceived deficiencies in design education vis a vis the integration of building technology and construction. Hands-on learning is not a new topic, as espoused by John Dewey, who posits a debate between static and active learning in his book Democracy and Education. Dewey espouses the concept that individuals should become participants and not mere observers of what happens around them. Advocates of academic design-build programs suggest a direct link between Dewey’s speculation. These experiences provide irreplaceable life lessons: that real-world decisions have real-life consequences. The goal of the paper is not to confirm or refute the legitimacy and efficacy of online virtual learning. Rather, the paper aims to foster a deeper, honest discourse on the meaning of ‘making’ in architectural education and present projects that confronted the burdens of a global pandemic and developed unique teaching strategies that challenged design thinking as an observational and constructive effort to expand design student’s making skills and foster student agency.

Keywords: design/build, making, remote teaching, architectural curriculum

Procedia PDF Downloads 80

Authors: Ian Marc Gealon Cabugsa, Eleanor Pastrano Corcino, Gina Lapaza Montalan

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This study focused on the effect of Online Web-Learning (OWL) in the performance of the freshmen Civil Engineering Students of Ateneo de Davao University in their Chem 12 subject. The grades of the students that were required to use OWL were compared to students without OWL. The result of the study suggests promising result for the use of OWL in increasing the performance rate of students taking up Chem 12. Furthermore, there was a positive correlation between the final grade and OWL grade of the students that had OWL. While the majority of the students find OWL to be helpful in supporting their chemistry knowledge needs, most of them still prefer to learn using the traditional face-to-face instruction.

Keywords: chemistry education, enhanced performance, engineering chemistry, online web-based learning

Procedia PDF Downloads 374

Authors: Soo Hyung Kim

Abstract:

Two different learning approaches were suggested: focusing on factual knowledge or focusing on the embedded meaning in the statements. Each way of learning has positive effects on different question categories, where factual knowledge helps more with simple fact questions, and searching for meaning in given information helps learn causal relationship and the embedded meaning. To test this belief, two groups of learners (12 male and 39 female adults aged 18-37) watched a ten-minute long Youtube video about various factual events of American history, their meaning, and the causal relations of the events. The fact group was asked to focus on factual knowledge in the video, and the meaning group was asked to focus on the embedded meaning in the video. After watching the video, both groups took multiple-choice questions, which consisted of 10 questions asking the factual knowledge addressed in the video and 10 questions asking embedded meaning in the video, such as the causal relationship between historical events and the significance of the event. From ANCOVA analysis, it was found that the factual knowledge showed higher performance on the factual questions than the meaning group, although there was no group difference on the questions about the meaning between the two groups. The finding suggests that teacher instruction plays an important role in learners constructing a different type of knowledge in online learning.

Keywords: factual knowledge, instruction, meaning-based knowledge, online learning

Procedia PDF Downloads 134

Authors: Mohammad Abu-Shaira, Weishi Shi

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Adaptive learning, a commonly employed solution to drift, involves updating predictive models online during their operation to react to concept drifts, thereby serving as a critical component and natural extension for online learning systems that learn incrementally from each example. This paper introduces LSTM-SCCM “Long Short-Term Memory Stream Cruise Control Method”, a drift adaptation-as-a-service framework for online learning. LSTM-SCCM automates drift adaptation through prompt detection, drift magnitude quantification, dynamic hyperparameter tuning, performing shortterm optimization and model recalibration for immediate adjustments, and, when necessary, conducting long-term model recalibration to ensure deeper enhancements in model performance. LSTM-SCCM is incorporated into a suite of cutting-edge online regression models, assessing their performance across various types of concept drift using diverse datasets with varying characteristics. The findings demonstrate that LSTM-SCCM represents a notable advancement in both model performance and efficacy in handling concept drift occurrences. LSTM-SCCM stands out as the sole framework adept at effectively tackling concept drifts within regression scenarios. Its proactive approach to drift adaptation distinguishes it from conventional reactive methods, which typically rely on retraining after significant degradation to model performance caused by drifts. Additionally, LSTM-SCCM employs an in-memory approach combined with the Self-Adjusting Memory (SAM) architecture to enhance real-time processing and adaptability. The framework incorporates variable thresholding techniques and does not assume any particular data distribution, making it an ideal choice for managing high-dimensional datasets and efficiently handling large-scale data. Our experiments, which include abrupt, incremental, and gradual drifts across both low- and high-dimensional datasets with varying noise levels, and applied to four state-of-the-art online regression models, demonstrate that LSTM-SCCM is versatile and effective, rendering it a valuable solution for online regression models to address concept drift.

Keywords: automated drift detection and adaptation, concept drift, hyperparameters optimization, online and adaptive learning, regression

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Authors: Inkeri Jääskeläinen

Abstract:

The purpose of this study is to shed light on what is it like to study in apprenticeship training using Finnish as second language. This study examines the stories and experiences of apprenticeship students learning and studying Finnish as part of their vocational studies. Also, this pilot study examines the effects of learning to pronounce Finnish through body motions and gestures. Many foreign students choose apprenticeships and start vocational training too early, while their language skills in Finnish are still very weak. Both duties at work and school assignments require reasonably good general language skills (B1.1) and, especially at work, language skills are also a safety issue. At work students should be able to simultaneously learn Finnish and do vocational studies in a noisy, demanding, and stressing environment. Learning and understanding new things is very challenging under these circumstances and sometimes students get exhausted and experience a lot of stress - which makes learning even more difficult. Students are different from each other and so are their ways to learn. Thereafter, one of the most important features of apprenticeship training and second language learning is good understanding of adult learners and their needs. Kinaesthetic methods are an effective way to support adult students’ cognitive skills and make learning more relaxing and fun. Empirical findings show that language learning can indeed be supported physical ways, by body motions and gestures. The method used here, named TFFL (Touch and Feel Foreign Languages), was designed to support adult language learning, to correct or prevent language fossilization and to help the student to manage emotions. Finnish is considered as a difficult language to learn, mostly because it is so different from nearly all other languages. Many learners complain that they are lost or confused and there is a need to find a way to simultaneously learn the language and to handle negative emotion which come from Finnish language and the learning process itself. Due to the nature of Finnish language good pronunciation skills are needed just to understand the way the language work. Movements (body movements etc.) are a natural part of many cultures but not Finnish – In Finland students have traditionally been expected to stay still and that is not a natural way for many foreign students. However, kinaesthetic TFFL method proved out to be a useful way to help some L2 students to feel phonemes, rhythm and intonation, to improve their Finnish and, thereby, also to successfully complete their vocational studies.

Keywords: Finnish, fossilization, interference, kinaesthetic method

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Authors: Oscar E. Cariceo, Claudia V. Casal

Abstract:

Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

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Authors: Stephanie Watson, Fabrice Stephenson, Conrad Pilditch, Carolyn Lundquist

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Spatial data detailing both the distribution and density of functionally important marine species are needed to inform management decisions. Species distribution models (SDMs) have proven helpful in this regard; however, models often focus only on species occurrences derived from spatially expansive datasets and lack the resolution and detail required to inform regional management decisions. Boosted regression trees (BRT) were used to produce high-resolution SDMs (250 m) at two spatial scales predicting probability of occurrence, abundance (count per sample unit), density (count per km2) and uncertainty for seven coastal seafloor taxa that vary in habitat usage and distribution to examine prediction differences and implications for coastal management. We investigated if small scale regionally focussed models (82,000 km2) can provide improved predictions compared to data-rich national scale models (4.2 million km2). We explored the variability in predictions across model type (occurrence vs abundance) and model scale to determine if specific taxa models or model types are more robust to geographical variability. National scale occurrence models correlated well with broad-scale environmental predictors, resulting in higher AUC (Area under the receiver operating curve) and deviance explained scores; however, they tended to overpredict in the coastal environment and lacked spatially differentiated detail for some taxa. Regional models had lower overall performance, but for some taxa, spatial predictions were more differentiated at a localised ecological scale. National density models were often spatially refined and highlighted areas of ecological relevance producing more useful outputs than regional-scale models. The utility of a two-scale approach aids the selection of the most optimal combination of models to create a spatially informative density model, as results contrasted for specific taxa between model type and scale. However, it is vital that robust predictions of occurrence and abundance are generated as inputs for the combined density model as areas that do not spatially align between models can be discarded. This study demonstrates the variability in SDM outputs created over different geographical scales and highlights implications and opportunities for managers utilising these tools for regional conservation, particularly in data-limited environments.

Keywords: Benthic ecology, spatial modelling, multi-scalar modelling, marine conservation.

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Authors: Ummuhan Bas Aslan, Sehmus Aslan

Abstract:

Objective: Physical disability includes impairments, activity limitations, and participation restrictions. Individuals with physical disabilities have lower self-esteem compared non-disabled people. Self-esteem is widely accepted as a key indicator of emotional stability and adjustment to life demands. There is very limited study to investigate the effect of sports on self-esteem in physically disabled people. The aim of the present study was to evaluate of self-esteem in physically disabled adults who participated in sports. Methods: Fifty physically disabled adults who participated in sports aged between 18 to 35 years participated in the study. Self-esteem of the participants was assessed by Rosenberg Self-Esteem Scale. The scale is a 10-item measure of global self-esteem. The higher score on the scale indicates greater self-esteem. Scores between 15 and 25 are the normal range of and scores below 15 suggest low self-esteem. Results: Average age of participants was 25.18±6.20 years. 58% of the participants were 23 (46.0%) of the participants were wheelchair users, 8 (16.0%) were mobile with a walking aid and 19 (38.0%) were mobile without a walking aid. The length of physically disabled adults had been participating in their sports (basketball: 54%, athleticism: 32%, volleyball: 6%, cycling: 6%) was 4.94±3.86 years. The average Rosenberg Self-Esteem Scale score of the participants was 21.88 ±4.34. Conclusions: Our results suggest that physically disabled adults who participated in sports have the healthy level of self-esteem. Participating in sports could have positive effects on self-esteem in that physically, disabled people. There is needed future comparative studies on this topic.

Keywords: adult, physical disability, self-esteem, sport

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Authors: Mackenzie Leake, Liyu Xia, Kamil Rocki, Wayne Imaino

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In the Hierarchical Temporal Memory (HTM) paradigm the effect of overlap between inputs on the activation of columns in the spatial pooler is studied. Numerical results suggest that similar inputs are represented by similar sets of columns and dissimilar inputs are represented by dissimilar sets of columns. It is shown that the spatial pooler produces these results under certain conditions for the connectivity and proximal thresholds. Following the discussion of the initialization of parameters for the thresholds, corresponding qualitative arguments about the learning dynamics of the spatial pooler are discussed.

Keywords: hierarchical temporal memory, HTM, learning algorithms, machine learning, spatial pooler

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Authors: C. Salis, D. Zedda, M. F. Wilson

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The IDEA project was conceived for teachers who are interested in enhancing their capacity to effectively implement the use of specific technologies in their teaching practice. Participating teachers are coached and supported as they explore technologies applied to the educational context. They access tools such as the technological platform developed by our team. Among the platform functionalities, teachers access an instructional systems design (ISD) tool (learning designer) that was adapted to the needs of our project. The tool is accessible from computers or mobile devices and used in association with other technologies to create new, meaningful learning environments. The objective of an instructional systems design is to guarantee the quality and effectiveness of education and to enhance learning. This goal involves both teachers who want to become more efficient in transferring knowledge or skills and students as the final recipient of their teaching. The use of Blooms’s taxonomy enables teachers to classify the learning objectives into levels of complexity and specificity, thus making it possible to highlight the kind of knowledge teachers would like their students to reach. The fact that the instructional design features can be visualized through the IDEA platform is a guarantee for those who are looking for specific educational materials to be used in their lessons. Despite the benefits offered, a number of teachers are reluctant to use ISD because the preparatory work of having to thoroughly analyze the teaching/learning objectives, the planning of learning material, assessment activities, etc., is long and felt to be time-consuming. This drawback is minimized using a learning designer, as the tool facilitates to reuse of the didactic contents having a clear view of the processes of analysis, planning, and production of educational or testing materials uploaded on our platform. In this paper, we shall present the feedback of the teachers who used our tool in their didactic.

Keywords: educational benefits, educational quality, educational technology, ISD tool

Procedia PDF Downloads 188

Authors: Faizah Almalki, Simeon Gill, Steve G. Hayes, Lisa Taylor

Abstract:

A core element of cultural identity is the traditional costumes that provide insight into the heritage that has been acquired over time. This heritage is apparent in the use of colour, the styles and the functions of the clothing and it also reflects the skills of those who created the items and the time taken to produce them. Modern flat pattern drafting methods for making garment patterns are simple in comparison to the relatively laborious traditional approaches that would require personal interaction with the wearer throughout the production process. The current study reflects on the main elements of the pattern cutting system and how this has evolved in Saudi Arabia to affect the design of the Sawan garment. Analysis of the traditional methods for constructing Sawan garments was undertaken through observation of the practice and the garments and consulting documented guidance. This provided a foundation through which to explore how modern technology can be applied to improve the process. In this research, modern methods are proposed for producing traditional Saudi garments more efficiently while retaining elements of the conventional style and design. The current study has documented the vital aspects of Sawan garment style. The result showed that the method had been used to take the body measurements and pattern making was elementary and offered simple geometric shape and the Sawan garment is composed of four pieces. Consequently, this research allows for classical pattern shapes to be embedded in garments now worn in Saudi Arabia and for the continuation of cultural heritage.

Keywords: traditional Sawan garment technique, modern pattern cutting technique, the shape of the garment and software, Lectra Modaris

Procedia PDF Downloads 132

Authors: Inkeri Jaaskelainen

Abstract:

The purpose of this study is to shed light on what it is like to study in apprenticeship training using Finnish as a second language. This study examines the stories and experiences of apprenticeship students learning and studying Finnish as part of their vocational studies. Also, this pilot study examines the effects of learning to pronounce Finnish through body motions and gestures. Many foreign students choose apprenticeships and start vocational training too early, while their language skills in Finnish are still very weak. Both duties at work and school assignments require reasonably good general language skills (B1.1), and, especially at work, language skills are also a safety issue. At work, students should be able to simultaneously learn Finnish and do vocational studies in a noisy, demanding, and stressful environment. Learning and understanding new things is very challenging under these circumstances and sometimes students get exhausted and experience a lot of stress - which makes learning even more difficult. Students are different from each other and so are their ways to learn. Thereafter, one of the most important features of apprenticeship training and second language learning is a good understanding of adult learners and their needs. Kinaesthetic methods are an effective way to support adult students’ cognitive skills and make learning more relaxing and fun. Empirical findings show that language learning can indeed be supported in physical ways, by body motions and gestures. The method used here, named TFFL (Touch and Feel Foreign Languages), was designed to support adult language learning, to correct or prevent language fossilization, and to help the student to manage emotions. Finnish is considered as a difficult language to learn, mostly because it is so different from nearly all other languages. Many learners complain that they are lost or confused and there is a need to find a way to simultaneously learn the language and to handle negative emotion that comes from the Finnish language and the learning process itself. Due to the nature of the Finnish language, good pronunciation skills are needed just to understand the way the language work. Movements (body movements etc.) are a natural part of many cultures, but not Finnish. In Finland, students have traditionally been expected to stay still, and that is not a natural way for many foreign students. However, the kinaesthetic TFFL method proved out to be a useful way to help some L2 students to feel phonemes, rhythm, and intonation, to improve their Finnish, and, thereby, also to successfully complete their vocational studies.

Keywords: Finnish, fossilization, interference, kinaesthetic method

Procedia PDF Downloads 140

Authors: Danijela Vranješ, Nataša Vukajlović

Abstract:

Turning to learner-centered teaching instead of the teacher-centered approach brought a whole new perspective into the process of teaching and learning and set a new goal for improving the educational process itself. However, recently a tremendous decline in students’ performance on various standardized tests can be observed, above all on the PISA-test. The learner-centeredness on its own is not enough anymore: the students’ ability to think is deteriorating. Especially in foreign language learning, one can encounter a lot of learning by heart: whether it is grammar or vocabulary, teachers often seem to judge the students’ success merely on how well they can recall a specific word, phrase, or grammar rule, but they rarely aim to foster their ability to think. Convinced that foreign language teaching can do both, this research aims to discover how two different approaches to teaching foreign language foster the students’ ability to think as well as to what degree they help students get to the state-determined level of foreign language at the end of the semester as defined in the Common European Framework. For this purpose, two different curricula were developed: one is a traditional, learner-centered foreign language curriculum that aims at teaching the four competences as defined in the Common European Framework and serves as a control variable, whereas the second one has been enriched with various thinking routines and aims at teaching the foreign language as a means to communicate ideas and thoughts rather than reducing it to the four competences. Moreover, two types of tests were created for each approach, each based on the content taught during the semester. One aims to test the students’ competences as defined in the CER, and the other aims to test the ability of students to draw on the knowledge gained and come to their own conclusions based on the content taught during the semester. As it is an ongoing study, the results are yet to be interpreted.

Keywords: common european framework of reference, foreign language learning, foreign language teaching, testing and assignment

Procedia PDF Downloads 107

Authors: Yasmeen Coaxum

Abstract:

The year 2020 became synonymous with the words “Emergency Remote Teaching,” which was imposed upon educators during the COVID-19 pandemic. Consequently, teachers were compelled to find new and engaging ways to educate their students outside of the face-to-face classroom setting. Now online instruction has become more of the norm rather than a way to manage educational expectations during a crisis. Therefore, implementing a strategic way to create online environments for students to thrive, create, and fully engage in their learning process is essential. The Synchronous Online Flipped Learning Approach or SOFLA® is a distance learning model that most closely replicates actual classroom teaching. SOFLA® includes structured, interactive, multimodal activities in an eight-step learning cycle with both asynchronous and synchronous components that foster autonomous and interactive learning among today’s online learners. The results of a pilot study in an Intensive English Program at a university, using SOFLA® methodology to facilitate podcasting in an online learning environment will be shared. Previous findings on student-produced podcasting projects have shown that students felt they improved their pronunciation, vocabulary, and speaking skills. However, few if any studies have been conducted on using a structured online flipped learning approach to facilitate such projects. Therefore, the purpose of this study is to assess the effect of using the SOFLA® framework to enhance optimum engagement in the online environment while using podcasts as the primary tool of instruction. Through data from interviews, questionnaires, and the results of formative and summative assessments, this study also investigates the affective and academic impact this flipped learning method combined with podcasting has on the students in terms of speaking confidence and vocabulary retention, and production. The steps of SOFLA will be illustrated, a video demonstration of the Anchor podcasting app will be shown, and final student projects and questionnaire responses will be shared. The specific context is a 14-week advanced level conversation and listening class. Participants vary in age but are all adult language learners representing a diverse array of countries.

Keywords: mall online flipped learning, podcasting, productive vocabulary

Procedia PDF Downloads 176

Authors: Nattawadee Sinpattanawong

Abstract:

Oral presentation has been used mostly in business communication. The business presentation is carrying out through an audio and visual presentation material such as statistical documents, projectors, etc. Common examples of business presentation are intra-organization and sales presentations. The study aims at investigating functions, strategies and contents of assessors’ verbal feedback on presenters’ oral presentations and exploring presenters’ learning process and specific views and expectations concerning assessors’ verbal feedback related to the delivery of the oral presentation. This study is designed as a descriptive qualitative research; four master students and one teacher in English for Business and Industry Presentation Techniques class of public university will be selected. The researcher hopes that any understanding how assessors’ verbal feedback on oral presentations and learning process may illuminate issues for other people. The data from this research may help to expand and facilitate the readers’ understanding of assessors’ verbal feedback on oral presentations and learning process in their own situations. The research instruments include an audio recorder, video recorder and an interview. The students will be interviewing in order to ask for their views and expectations concerning assessors’ verbal feedback related to the delivery of the oral presentation. After finishing data collection, the data will be analyzed and transcribed. The findings of this study are significant because it can provide presenters knowledge to enhance their learning process and provide teachers knowledge about providing verbal feedback on student’s oral presentations on a business context.

Keywords: business context, learning process, oral presentation, verbal feedback

Procedia PDF Downloads 194

Authors: Olabamiji J. Onifade, Peter O. Ajayi, Paul O. Jegede

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This study aimed at investigating the preparedness of the undergraduate final year students of Computer Science as the next entrants into the workplace. It assessed their self-efficacy in computational tasks and examined the relationship between their self-efficacy and their learning experiences in Southwest Nigerian universities. The study employed a descriptive survey research design. The population of the study comprises all the final year students of Computer Science. A purposive sampling technique was adopted in selecting a representative sample of interest from the final year students of Computer Science. The Students’ Computational Task Self-Efficacy Questionnaire (SCTSEQ) was used to collect data. Mean, standard deviation, frequency, percentages, and linear regression were used for data analysis. The result obtained revealed that the final year students of Computer Science were averagely confident in performing computational tasks, and there is a significant relationship between the learning experiences of the students and their self-efficacy. The study recommends that the curriculum be improved upon to accommodate industry experts as lecturers in some of the courses, make provision for more practical sessions, and the learning experiences of the student be considered an important component in the undergraduate Computer Science curriculum development process.

Keywords: computer science, learning experiences, self-efficacy, students

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Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: crime prediction, machine learning, public safety, smart city

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Authors: Yuan-Hong Ho, Chiung-Ju Huang

Abstract:

This article presents a monitoring indicators system that predicts whether a local government in Taiwan is heading for fiscal distress and identifies a suitable fiscal policy that would allow the local government to achieve fiscal balance in the long run. This system is relevant to stockholders’ interest, simple for national audit bodies to use, and provides an early warning of fiscal distress that allows preventative action to be taken.

Keywords: fiscal health, fiscal distress, monitoring signals, 10-point scale

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Authors: M. Richichi

Abstract:

Evidencing the learning and developmental needs of students in specific educational institutions is central to determining the type of whole school pedagogical shift required. Initiating this transition by designing and implementing STEAM (Science, technology, engineering, art, and mathematics) project-based learning opportunities, in collaboration with industry, exposes teachers to new pedagogical and assessment practices. This experience instills confidence and a renewed sense of energy, which contributes to greater efficacy. Championing teachers in such learning environments leads to “bleeding” of inventive pedagogical understanding and skills as well as motivation. This contributes positively to collective teacher efficacy and the transition towards more cross-disciplinary initiatives and opportunities, and hence an innovative pedagogical shift. Evidence of skill and knowledge development in students, combined with greater confidence, work ethic and interest in STEAM areas, are further indicators of the success of the transitioning process.

Keywords: efficacy, pedagogy, transition, STEAM

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Authors: Mohammed Al Sulaimani, Hamad Al Manhi

Abstract:

With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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Authors: Vivian Khamis

Abstract:

Exposure to war and forced migration have been widely linked to child subsequent adaptation. What remains sparse is research spanning multiple risk and protective factors and examining their unique and relative implications to difficulties in mental health among refugee girls. This study investigated the mechanisms through which posttraumatic stress disorder (PTSD), emotion dysregulation , neuroticism, and behavioral and emotional disorders in Syrian refugee girls is impacted by exposure to war traumas, age, and other risk and protective factors such as coping styles, family relationships, and school environment. The sample consisted of 539 Syrian refugee girls who ranged in age from 7 to 18 years attending public schools in various governorates in Lebanon and Jordan. Two school counselors carried out the interviews with children at school. Results indicated that war trauma, older age, and a combination of negative copying style associated with conflict in the family could lead to an overall state of emotion dysregulation, neuroticism, behavioral and emotional disorders, and PTSD in refugee girls. On the other hand, lapse of time since resettlement in host country, positive copying style, cohesion, and expressiveness in the family would lead to more positive mental health status, including lower levels of emotion dysregulation, neuroticism, behavioral and emotional disorders, and PTSD . Enhanced understanding of the mechanistic role of risk and protective factors in contributing to difficulties in mental health in refugee girls may contribute to the development of effective interventions to target the psychological effects of the refugee experience.

Keywords: refugee girls, PTSD, emotion dysregulation, neuroticism, behavioral and emotional disorders

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Authors: Mo-Se Lee, Cheol-Hwi Ahn, Kee-Young Kwahk, Hyunchul Ahn

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Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN (Convolutional Neural Network), which is known as effective solution for recognizing and classifying images, has been popularly applied to classification and prediction problems in various fields. In this study, we try to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. In specific, we propose to apply CNN as the binary classifier that predicts stock market direction (up or down) by using a graph as its input. That is, our proposal is to build a machine learning algorithm that mimics a person who looks at the graph and predicts whether the trend will go up or down. Our proposed model consists of four steps. In the first step, it divides the dataset into 5 days, 10 days, 15 days, and 20 days. And then, it creates graphs for each interval in step 2. In the next step, CNN classifiers are trained using the graphs generated in the previous step. In step 4, it optimizes the hyper parameters of the trained model by using the validation dataset. To validate our model, we will apply it to the prediction of KOSPI200 for 1,986 days in eight years (from 2009 to 2016). The experimental dataset will include 14 technical indicators such as CCI, Momentum, ROC and daily closing price of KOSPI200 of Korean stock market.

Keywords: convolutional neural network, deep learning, Korean stock market, stock market prediction

Procedia PDF Downloads 425

Authors: Alissa Settembrino

Abstract:

Improvisation, one of the most expressive qualities of the performing arts, has allowed for entire compositions to be created through descargas. A topic relatively understudied, these combo-inspired jam sessions originated in Cuba and intrigued jazz musicians in the United States to experiment with their improvisation after the Cool Jazz era. Through the exploration of prominent improvisation-based Cuban dance styles, the crucial jazz musicians that contributed to the progression of the descarga movement and comparing such facets to that of jazz in the United States, this paper offers a critical comparative analysis to suggest how the descarga influenced American jazz. This paper specifically focuses on harmonic construction, form and rhythmic qualities, as well as how these recorded jam sessions started to change the way people listened to and enjoyed this style of music. Examining the harmonic intricacies of descargas offers the likelihood of having influenced the construction of the blues scale in American jazz. Since these recorded jam sessions originally stemmed from Cuban dance styles (the cumbia, guaracha, rumba, etc.), descarga compositions changed the way musicians structured their improvisation to meet recording guidelines as well as their audiences’ listening needs. The ways in which the descarga inspired harmonic and rhythmic change led to the movement’s influence on the jazz culture as it progressed from Cuba to New York during the 1950s. Exploring the descarga provides insight into a movement that is not commonly studied and encourages further discussion about how certain aspects of Latin American culture have influenced the United States socially and creatively.

Keywords: descarga, harmony, improvisation, jam session, jazz

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Authors: Zeineb Deymi-Gheriani

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In the last two decades, one can clearly observe a boom of interest for e-learning and web-supported programs. However, one can also notice that many of these programs focus on the accumulation and delivery of content generally as a business industry with no much concern for theoretical underpinnings. The existing research, at least in online English language teaching (ELT), has demonstrated a lack of an effective online teaching pedagogy anchored in a well-defined theoretical framework. Hence, this paper comes as an attempt to present constructivism as one of the theoretical bases for the design of an effective online language teaching pedagogy which is at the same time technologically intelligent and theoretically informed to help envision how education can best take advantage of the information and communication technology (ICT) tools. The present paper discusses the key principles underlying constructivism, its implications for online language teaching design, as well as its limitations that should be avoided in the e-learning instructional design. Although the paper is theoretical in nature, essentially based on an extensive literature survey on constructivism, it does have practical illustrations from an action research conducted by the author both as an e-tutor of English using Moodle online educational platform at the Virtual University of Tunis (VUT) from 2007 up to 2010 and as a face-to-face (F2F) English teaching practitioner in the Professional Certificate of English Language Teaching Training (PCELT) at AMIDEAST, Tunisia (April-May, 2013).

Keywords: active learning, constructivism, experiential learning, Piaget, Vygotsky

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Authors: Dohun Kim

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Technological innovations have stimulated flipped learning in many disciplines, including language teaching. It is a specific type of blended learning, which combines onsite (i.e. face-to-face) with online experiences to produce effective, efficient and flexible learning. Flipped learning literally ‘flips’ conventional teaching and learning activities upside down: it leverages technologies to deliver a lecture and direct instruction—other asynchronous activities as well—outside the classroom to reserve onsite time for interaction and activities in the upper cognitive realms: applying, analysing, evaluating and creating. Unlike the conventional flipped approaches, which focused on video lecture, followed by face-to-face or on-site session, new innovative methods incorporate various means and structures to serve the needs of different academic disciplines and classrooms. In the light of such innovations, this study adopted ‘student-engaged’ approaches to interpreter training and contrasts them with traditional classrooms. To this end, students were also encouraged to engage in asynchronous activities online, and innovative technologies, such as Telepresence, were employed. Based on the class implementation, a thorough examination was conducted to examine how we can structure and implement flipped classrooms for language and interpreting training while actively engaging learners. This study adopted a quantitative research method, while complementing it with a qualitative one. The key findings suggest that the significance of the instructor’s role does not dwindle, but his/her role changes to a moderator and a facilitator. Second, we can apply flipped learning to both theory- and practice-oriented modules. Third, students’ integration into the community of inquiry is of significant importance to foster active and higher-order learning. Fourth, cognitive presence and competence can be enhanced through strengthened and integrated teaching and social presences. Well-orchestrated teaching presence stimulates students to find out the problems and voices the convergences and divergences, while fluid social presence facilitates the exchanges of knowledge and the adjustment of solutions, which eventually contributes to consolidating cognitive presence—a key ingredient that enables the application and testing of the solutions and reflection thereon.

Keywords: blended learning, Community of Inquiry, flipped learning, interpreter training, student-centred learning

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Authors: Morakinyo Akintolu, Moeketsi Letseka

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In the year 2015, the United Nation member states, through the representative of all heads of states present, adopted the 17 Global goals known as the Sustainable Development Goals in their capacity to bring about social, economic, and cultural development to the world. Therefore, the need to accommodate equitable development one of the major goals is to achieve equitable and quality education for all to bring about international development. In this light, the study investigates the role of open distance learning in achieving sustainable development goals. Open distance learning comes as a second chance to individuals in disseminating educational content to students who missed the opportunity of attending the traditional school setting. Therefore, this study investigates if the SDGs reflect this type of learning (ODL) in creating Education for all according to the 2030 agenda by the United Nations. It further ascertains the role of ODL in achieving SDGs, the challenges encountered as well as the way forward.

Keywords: open distance learning, sustainable development goals, distance education, achieving, 2030 agenda

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Authors: M. Arunachalam, M. Pandey

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Nacre, a biological material that forms the inner-layer of sea shells can achieve high toughness and strength by way of staggered arrangement of strong tablets with soft and weak organic interface. Under applied loads the tablets slide over the adjacent tablets, thus generating inelastic deformation and toughness on macroscopic scale. A two dimensional finite element based homogenization methodology is adopted for obtaining the effective material properties of Nacre using a representative volume element (RVE) at finite deformations. In this work, the material behaviour for tablet and interface are assumed to be Isotropic elastic and Isotropic elastic-perfectly plastic with strain softening respectively. Numerical experiments such as uniaxial tension test along X, Y directions and simple shear test are performed on the RVE with uniform displacement and periodic constraints applied at the RVE boundaries to obtain the anisotropic homogenized response and maximum local stresses within each constituents of Nacre. Homogenized material model is then tested for macroscopic structure under three point bending condition and the results obtained are comparable with the results obtained for detailed microstructure based structure, thus homogenization provides a bridge between macroscopic scale and microscopic scale and homogenized material properties obtained from microstructural (RVE) analysis could be used in large scale structural analysis.

Keywords: finite element, homogenization, inelastic deformation, staggered arrangement

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Authors: Shael Brown, Reza Farivar

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Persistence diagrams capture valuable topological features of datasets that other methods cannot uncover. Still, their adoption in data pipelines has been limited due to the lack of publicly available tools in R (and python) for analyzing groups of them with machine learning and statistical inference. In an easy-to-use and scalable R package called TDApplied, we implement several applied analysis methods tailored to groups of persistence diagrams. The two main contributions of our package are comprehensiveness (most functions do not have implementations elsewhere) and speed (shown through benchmarking against other R packages). We demonstrate applications of the tools on simulated data to illustrate how easily practical analyses of any dataset can be enhanced with topological information.

Keywords: machine learning, persistence diagrams, R, statistical inference

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Authors: Slah Eddine Ben Fadhel

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Despite the development of new pedagogic methods, current teaching practices put more emphasis on the learning products than on the processes learners deploy. In school syllabi, for instance, very little time is devoted to both the explanation and analysis of strategies aimed at resolving problems by means of targeting students’ metacognitive procedures. Within a cognitive framework, teaching/learning contexts are conceived of in terms of cognitive, metacognitive and affective activities intended for the treatment of information. During these activities, learners come to develop an array of knowledge and strategies which can be subsumed within an active and constructive process. Through the investigation of strategies and metacognition concepts, the purpose is to reflect upon the modalities at the heart of the learning process and to demonstrate, similarly, the inherent significance of a cognitive approach to learning. The scope of this paper is predicated on a study where the population is a group of 76 primary school pupils who experienced difficulty with learning French. The population was divided into two groups: the first group was submitted during three months to a strategy-based training to learn French. All through this phase, the teachers centred class activities round making learners aware of the strategies the latter deployed and geared them towards appraising the steps these learners had themselves taken by means of a variety of tools, most prominent among which is the logbook. The second group was submitted to the usual learning context with no recourse whatsoever to any strategy-oriented tasks. The results of both groups point out the improvement of linguistic competences in the French language in the case of those pupils who were trained by means of strategic procedures. Furthermore, this improvement was noted in relation with the native language (Arabic), a fact that tends to highlight the importance of the interdisciplinary investigation of (meta-)cognitive strategies. These results show that strategic learning promotes in pupils the development of a better awareness of their own processes, which contributes to improving their general linguistic competences.

Keywords: constructive approach, cognitive strategies, metacognition, learning

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Authors: Omar Alshehri, Vic Lally

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This paper examined the attitudes of using social media tools to support learning at a university in Saudi Arabia. Moreover, it investigated the students’ current usage of these tools and examined the barriers they could face during the use of social media tools in the education process. Participants in this study were 42 university students. A web-based survey was used to collect data for this study. The results indicate that all of the students were familiar with social media and had used at least one type of social media for learning. It was found out that all students had very positive attitudes towards the use of social media and welcomed using these tools as a supplementary to the curriculum. However, the results indicated that the major barriers to using these tools in learning were distraction, opposing Islamic religious teachings, privacy issues, and cyberbullying. The study recommended that this study could be replicated at other Saudi universities to investigate factors and barriers that might affect Saudi students’ attitudes toward using social media to support learning.

Keywords: barriers to social media use, benefits of social media use, higher education, Saudi Arabia, social media

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