Search results for: quality of learning
14168 Re-Thinking Design/Build Curriculum in a Virtual World
Authors: Bruce Wrightsman
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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 8114167 Assessment of Online Web-Based Learning for Enhancing Student Grades in Chemistry
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 37514166 Adoption of International Financial Reporting Standards and Earnings Quality in Listed Deposit Money Banks in Nigeria
Authors: Shehu Usman Hassan
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Published accounting information in financial statements are required to provide various users - shareholders, employees, suppliers, creditors, financial analysts, stockbrokers and government agencies – with timely and reliable information useful for making prudent, effective and efficient decisions. The widespread failure in the financial information quality has created the need to improve the financial information quality and to strengthen the control of managers by setting up good firms structures. This paper investigates firm attributes from perspective of structure, monitoring, performance elements of listed deposit money banks in Nigeria. The study adopted correlational research design with balanced panel data of 14 banks as sample of the study using multiple regression as a tool of analysis. The result reveals that firms attributes (leverage, profitability, liquidity, bank size and bank growth) has as significant influence on earnings quality of listed deposit money banks in Nigeria after the adoption of IFRS, while the pre period shows that the selected firm attributes has no significant impact on earnings quality. It is therefore concluded that the adoption of IFRS is right and timely.Keywords: earnings quality, firm attributes, listed deposit money bank, Nigeria
Procedia PDF Downloads 51614165 The Good Form of a Sustainable Creative Learning City Based on “The Theory of a Good City Form“ by Kevin Lynch
Authors: Fatemeh Moosavi, Tumelo Franck Nkoshwane
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Peter Drucker the renowned management guru once said, “The best way to predict the future is to create it.” Mr. Drucker is also the man who placed human capital as the most vital resource of any institution. As such any institution bent on creating a better future, requires a competent human capital, one that is able to execute with efficiency and effectiveness the objective a society aspires to. Technology today is accelerating the rate at which many societies transition to knowledge based societies. In this accelerated paradigm, it is imperative that those in leadership establish a platform capable of sustaining the planned future; intellectual capital. The capitalist economy going into the future will not just be sustained by dollars and cents, but by individuals who possess the creativity to enterprise, innovate and create wealth from ideas. This calls for cities of the future, to have this premise at the heart of their future plan, if the objective of designing sustainable and liveable future cities will be realised. The knowledge economy, now transitioning to the creative economy, requires cities of the future to be ‘gardens’ of inspiration, to be places where knowledge, creativity, and innovation can thrive as these instruments are becoming critical assets for creating wealth in the new economic system. Developing nations must accept that learning is a lifelong process that requires keeping abreast with change and should invest in teaching people how to keep learning. The need to continuously update one’s knowledge, turn these cities into vibrant societies, where new ideas create knowledge and in turn enriches the quality of life of the residents. Cities of the future must have as one of their objectives, the ability to motivate their citizens to learn, share knowledge, evaluate the knowledge and use it to create wealth for a just society. The five functional factors suggested by Kevin Lynch;-vitality, meaning/sense, adaptability, access, control, and monitoring should form the basis on which policy makers and urban designers base their plans for future cities. The authors of this paper believe that developing nations “creative economy clusters”, cities where creative industries drive the need for constant new knowledge creating sustainable learning creative cities. Obviously the form, shape and size of these districts should be cognisant of the environmental, cultural and economic characteristics of each locale. Gaborone city in the republic of Botswana is presented as the case study for this paper.Keywords: learning city, sustainable creative city, creative industry, good city form
Procedia PDF Downloads 31114164 The Role of Instruction in Knowledge Construction in Online Learning
Authors: Soo Hyung Kim
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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 13614163 Next Generation Radiation Risk Assessment and Prediction Tools Generation Applying AI-Machine (Deep) Learning Algorithms
Authors: Selim M. Khan
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Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America
Procedia PDF Downloads 9814162 Kinaesthetic Method in Apprenticeship Training: Support for Finnish Learning in Vocational Education
Authors: Inkeri Jääskeläinen
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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
Procedia PDF Downloads 11014161 Machine Learning Techniques to Predict Cyberbullying and Improve Social Work Interventions
Authors: Oscar E. Cariceo, Claudia V. Casal
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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
Procedia PDF Downloads 17014160 Determinants of Infrastructure Provision in Ghana
Authors: Clifford Kwakwa Amoah, De-Graft Owusu-Manu, Prince Antwi-Afari
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Infrastructure is the lifeline for economic development of any country. Hence, obtaining infrastructure quality cannot be overemphasized. Nevertheless, challenges of infrastructure quality persist, and it is worse in developing countries despite the diverse study on the subject matter. Therefore, this study was formulated to identify the prevalent determinants of infrastructure quality using synthesis of extant literature (to identify key variables), and analysis of survey questionnaire of data collected by means of the inductive methodology approach, mean score ranking and descriptive statistics. The variables “partner with the private sector, growth stimulation and poverty reduction, and adherence to procurement core principles” were the most significant challenges that the government faces. Moreover, it would be of utmost concern to adopt some stringent measures to help improve and accelerate on the growth and development of the nation, thereby achieving the best quality required. This study is novel conducted to provide insight into some of the punitive measures, considered in ensuring that quality infrastructure is obtained in both developing (specifically) and developed economies. The research findings therefore provide some guidance for overcoming the accumulative challenges. Application of the stated findings will help bridge the gap of infrastructure challenges; this is because the study found strong empirical evidence that infrastructure plays a pivotal role in the productivity enhancement.Keywords: challenges, development, economic growth, government, infrastructure quality
Procedia PDF Downloads 14914159 [Keynote Talk]: From Clinical Practice to Academic Setup, 'Quality Circles' for Quality Outputs in Both
Authors: Vandita Mishra
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From the management of patients, reception, record, and assistants in a clinical practice; to the management of ongoing research, clinical cases and department profile in an academic setup, the healthcare provider has to deal with all of it. The victory lies in smooth running of the show in both the above situations with an apt solution of problems encountered and smooth management of crisis faced. Thus this paper amalgamates dental science with health administration by means of introduction of a concept for practice management and problem-solving called 'Quality Circles'. This concept uses various tools for problem solving given by experts from different fields. QC tools can be applied in both clinical and academic settings in dentistry for better productivity and for scientifically approaching the process of continuous improvement in both the categories. When approached through QC, our organization showed better patient outcomes and more patient satisfaction. Introduced in 1962 by Kaoru Ishikawa, this tool has been extensively applied in certain fields outside dentistry and healthcare. By exemplification of some clinical cases and virtual scenarios, the tools of Quality circles will be elaborated and discussed upon.Keywords: academics, dentistry, healthcare, quality
Procedia PDF Downloads 10314158 A Probabilistic View of the Spatial Pooler in Hierarchical Temporal Memory
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
Procedia PDF Downloads 34614157 Boost for Online Language Course through Peer Evaluation
Authors: Kirsi Korkealehto
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The purpose of this research was to investigate how the peer evaluation concept was perceived by language teachers developing online language courses. The online language courses in question were developed in language teacher teams within a nationwide KiVAKO-project funded by the Finnish Ministry of Education and Culture. The participants of the project were 86 language teachers of 26 higher education institutions in Finland. The KiVAKO-project aims to strengthen the language capital at higher education institutions by building a nationwide online language course offering on a shared platform. All higher education students can study the courses regardless of their home institutions. The project covers the following languages: Chinese, Estonian, Finnish Sign Language, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish on the levels CEFR A1-C1. The courses were piloted in the autumn term of 2019, and an online peer evaluation session was organised for all project participating teachers in spring 2020. The peer evaluation utilised the quality criteria for online implementation, which was developed earlier within the eAMK-project. The eAMK-project was also funded by the Finnish Ministry of Education and Culture with the aim to improve higher education institution teachers’ digital and pedagogical competences. In the online peer evaluation session, the teachers were divided into Zoom breakout rooms, in each of which two pilot courses were presented by their teachers dialogically. The other language teachers provided feedback on the course on the basis of the quality criteria. Thereafter good practices and ideas were gathered to an online document. The breakout rooms were facilitated by one teacher who was instructed and provided a slide-set prior to the online session. After the online peer evaluation sessions, the language teachers were asked to respond to an online questionnaire for feedback. The questionnaire included three multiple-choice questions using the Likert-scale rating and two open-ended questions. The online questionnaire was answered after the sessions immediately, the questionnaire link and the QR-code to it was on the last slide of the session, and it was responded at the site. The data comprise online questionnaire responses of the peer evaluation session and the researcher’s observations during the sessions. The data were analysed with a qualitative content analysis method with the help of Atlas.ti programme, and the Likert scale answers provided results per se. The observations were used as complementary data to support the primary data. The findings indicate that the working in the breakout rooms was successful, and the workshops proceeded smoothly. The workshops were perceived as beneficial in terms of improving the piloted courses and developing the participants’ own work as teachers. Further, the language teachers stated that the collegial discussions and sharing the ideas were fruitful. The aspects to improve the workshops were to give more time for free discussions and the opportunity to familiarize oneself with the quality criteria and the presented language courses beforehand. The quality criteria were considered to provide a suitable frame for self- and peer evaluations.Keywords: higher education, language learning, online learning, peer-evaluation
Procedia PDF Downloads 12814156 Kinaesthetic Method in Apprenticeship Training: Support for Finnish Learning in Vocational Education and Training
Authors: Inkeri Jaaskelainen
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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 14114155 Learning-by-Heart vs. Learning by Thinking: Fostering Thinking in Foreign Language Learning A Comparison of Two Approaches
Authors: Danijela Vranješ, Nataša Vukajlović
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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 11014154 Using the Synchronous Online Flipped Learning Approach to Facilitate Student Podcasting
Authors: Yasmeen Coaxum
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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 17914153 Investigation of Verbal Feedback and Learning Process for Oral Presentation
Authors: Nattawadee Sinpattanawong
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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 19514152 Leather Quality of Some Sudan Goats under Range Condition
Authors: Mohammed Alhadi Ebrahiem
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This study was designed to investigate the effect of breed and feeding level before slaughter on the skin\leather quality of the three main breeds of Sudan goats. Thirty (30) pieces of fresh skins from the three goat breeds (an average age 1-1.5 years) were chosen for the study purpose. For whole variations between the three breeds in two levels of feeding (poor and rich pastures) Complete Randomized Design (CRD) was used for data analysis. The results revealed that, leather weight (kg), elongation%, tensile strength (kg/cm2), cracking load (kg), thickness (mm), tear load (kg/cm) and chrome% findings were significantly affected (P≥0.05) by breed variation. Flexibility, moisture%, Ash% and fat % were not significantly affected (P ≥ 0.05) by breed. On the other hand, skin weight (kg), Cracking load (kg), Tear load (kg/cm) and Ash% were significantly affected (P≥0.05) by pasture quality. While Leather Elongation%, Tensile strength (kg/cm2), Thickness (mm), Flexibility, Moisture%, Fat % and Chrome% were not statistically (P ≥ 0.05) affected by pastures quality.Keywords: skin\leather quality, goats leather, natural pasture, Sudan
Procedia PDF Downloads 36014151 Evaluation of the Self-Efficacy and Learning Experiences of Final year Students of Computer Science of Southwest Nigerian Universities
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
Procedia PDF Downloads 14414150 An Application for Risk of Crime Prediction Using Machine Learning
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
Procedia PDF Downloads 11314149 Consumer Knowledge of Food Quality Assurance and Use of Food Labels in Trinidad, West Indies
Authors: Daryl Clement Knutt, Neela Badrie, Marsha Singh
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Quality assurance and product labelling are vital in the food and drink industry, as a tactical tool in a competitive environment. The food label is a principal marketing tool which also serves as a regulatory mechanism in the safeguarding of consumer well –being. The objective of this study was to evaluate the level of consumers’ use and understanding of food labeling information and knowledge pertaining to food quality assurance systems. The study population consisted of Trinidadian adults, who were over the age of 18 (n=384). Data collection was conducted via a self-administered questionnaire, which contained 31 questions, comprising of four sections: I. socio demographic information; II. food quality and quality assurance; III. use of Labeling information; and IV. laws and regulations. Sampling was conducted at six supermarkets, in five major regions of the country over a period of three weeks in 2014. The demographic profile of the shoppers revealed that majority was female (63.6%). The gender factor and those who were concerned about the nutrient content of their food, were predictive indicators of those who read food labels. Most (93.1%) read food labels before purchase, 15.4% ‘always’; 32.5% ‘most times’ and 45.2% ‘sometimes’. Some (42%) were often satisfied with the information presented on food labels, whilst 35.7% of consumers were unsatisfied. When the respondents were questioned on their familiarity with terms ‘food quality’ and ‘food quality assurance’, 21.3% of consumers replied positively - ‘I have heard the terms and know a lot’ whilst 37% were only ‘somewhat familiar’. Consumers were mainly knowledgeable of the International Standard of Organization (ISO) (51.5%) and Good Agricultural Practices GAP (38%) as quality tools. Participants ranked ‘nutritional information’ as the number one labeling element that should be better presented, followed by ‘allergy notes’ and ‘best before date’. Females were more inclined to read labels being the household shoppers. The shoppers would like better presentation of the food labelling information so as to guide their decision to purchase a product.Keywords: food labels, food quality, nutrition, marketing, Trinidad, Tobago
Procedia PDF Downloads 49314148 Using Science, Technology, Engineering, Art and Mathematics (STEAM) Project-Based Learning Programs to Transition towards Whole School Pedagogical Shift
Authors: M. Richichi
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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
Procedia PDF Downloads 13114147 A Comparative Analysis of Residential Quality of Public and Private Estates in Lagos
Authors: S. Akinde, Jubril Olatunbosun
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In recent years, most of the urban centers in Nigeria are fast experiencing housing problems such as unaffordable housing and environmental challenges, all of which determine the nature of housing quality. The population continues to increase and the demand for quality housing increases probably at the same rate. Several kinds of houses serve various purposes; the objectives of the low cost housing schemes as the name suggests is to make houses quality to both the middle and lower classes of people in Lagos. A casual look into the study area of Iba Low Cost Housing Estate and the Unity Low Cost Housing Estate, Ojo and Alimosho respectively in Lagos State have shown a huge demands for houses. The study area boasts of a large population all engaged in various commercial activities with income at various levels. It would be fair to say that these people are mainly of the middle class and lower class. This means the low cost housing scheme truly serves these purposes. A Low Cost Housing Scheme of Iba which is publicly owned and Low Cost Housing Scheme of Unity Estate (UE) is privately owned.Keywords: housing, residential quality, low cost housing scheme, public, private estates
Procedia PDF Downloads 56914146 Automated Feature Extraction and Object-Based Detection from High-Resolution Aerial Photos Based on Machine Learning and Artificial Intelligence
Authors: Mohammed Al Sulaimani, Hamad Al Manhi
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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
Procedia PDF Downloads 3414145 Stock Market Prediction Using Convolutional Neural Network That Learns from a Graph
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 42614144 Smart Textiles Integration for Monitoring Real-time Air Pollution
Authors: Akshay Dirisala
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Humans had developed a highly organized and efficient civilization to live in by improving the basic needs of humans like housing, transportation, and utilities. These developments have made a huge impact on major environmental factors. Air pollution is one prominent environmental factor that needs to be addressed to maintain a sustainable and healthier lifestyle. Textiles have always been at the forefront of helping humans shield from environmental conditions. With the growth in the field of electronic textiles, we now have the capability of monitoring the atmosphere in real time to understand and analyze the environment that a particular person is mostly spending their time at. Integrating textiles with the particulate matter sensors that measure air quality and pollutants that have a direct impact on human health will help to understand what type of air we are breathing. This research idea aims to develop a textile product and a process of collecting the pollutants through particulate matter sensors, which are equipped inside a smart textile product and store the data to develop a machine learning model to analyze the health conditions of the person wearing the garment and periodically notifying them not only will help to be cautious of airborne diseases but will help to regulate the diseases and could also help to take care of skin conditions.Keywords: air pollution, e-textiles, particulate matter sensors, environment, machine learning models
Procedia PDF Downloads 11514143 Online Language Learning and Teaching Pedagogy: Constructivism and Beyond
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
Procedia PDF Downloads 35214142 Flipped Learning in Interpreter Training: Technologies, Activities and Student Perceptions
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
Procedia PDF Downloads 19814141 Impact of Lifelong-Learning Mindset on Career Success of the Accounting and Finance Professionals
Authors: R. W. A. V. A. Wijenayake, P. M. R. N. Fernando, S. Nilesh, M. D. G. M. S. Diddeniya, M. Weligodapola, P. Shamila
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The study is designed to examine the impact of a lifelong learning mindset on the career success of accounting and finance professionals in the western province of Sri Lanka. The learning mindset impacts the career success of accounting and finance professionals. The main objective of this study is to identify how the lifelong-learning mindset impacts on the career success of accounting and finance professionals. The lifelong learning mindset is the desire to learn new things and curiosity, resilience, and strategic thinking are the selected constructs to measure the lifelong learning mindset. Career success refers to certain objectives and emotional measures of improvement in one’s work life. The related variables of career success are measured through the number of promotions that have been granted in his/her work life. Positivism is the research paradigm, and the deductive approach is involved as this study relies on testing an existing theory. To conduct the study, the accounting and finance professionals in the western province in Sri Lanka were selected because most reputed international and local companies and specifically, headquarters of most of the companies are in western province. The responses cannot be collected from the whole population. Therefore, this study used a simple random sampling method, and the sample size was 120. Therefore, to identify the impact, 5-point Likert scale is used to perform this quantitative data. Required data gathered through an online questionnaire and the final outputs of the study will offer certain important recommendations to several parties such as universities, undergraduates, companies, and the policymakers to improve, help mentally and financially and motivate the students and the employees to continue their studies without ceasing after completion of their degree.Keywords: career success, curiosity, lifelong learning mindset, resilience, strategic thinking
Procedia PDF Downloads 8814140 Australian Teachers and School Leaders’ Use of Differentiated Learning Experiences as Responsive Teaching for Students with ADHD
Authors: Kathy Gibbs
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There is a paucity of research in Australia about educators’ use of differentiated instruction (DI) to support the learning of students with ADHD. This study reports on small-scale, qualitative research using interviews with teachers and school leaders to identify how they use DI as an effective teaching instruction for students with ADHD. Findings showed that teachers and school leaders have a good understanding of ADHD; teachers use DI as an effective teaching practice to enhance learning for this student group and ensure the classroom environment is safe and secure. However, they do not adjust assessments for students with ADHD. School leaders are not clear on how teachers differentiate assessments or adapt to the classroom environment. These results highlight the need for further research at the teacher and teacher-educator level teachers to ensure teaching practices are effective in reducing unwanted behaviours that prevent students with ADHD from achieving their full academic potential.Keywords: teachers, differentiated instruction, ADHD, student learning, educators knowledge
Procedia PDF Downloads 5614139 TDApplied: An R Package for Machine Learning and Inference with Persistence Diagrams
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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