Search results for: content- and task-based learning

Authors: Karina Zaccari, Ernesto Cordeiro Marujo

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This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: machine learning, medical diagnosis, meningitis detection, pediatric research

Procedia PDF Downloads 150

Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

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Authors: Lynn Mcquarrie, Charlotte Enns

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The goal of this project was to develop a visually-based, signed language phonological awareness training program and to pilot the intervention with signing deaf children (ages 6 -10 years/ grades 1 - 4) who were beginning readers to assess the effects of systematic explicit American Sign Language (ASL) phonological instruction on both ASL vocabulary and English print vocabulary learning. Growing evidence that signing learners utilize visually-based signed language phonological knowledge (homologous to the sound-based phonological level of spoken language processing) when reading underscore the critical need for further research on the innovation of reading instructional practices for visual language learners. Multiple single-case studies using a multiple probe design across content (i.e., sign and print targets incorporating specific ASL phonological parameters – handshapes) was implemented to examine if a functional relationship existed between instruction and acquisition of these skills. The results indicated that for all cases, representing a variety of language abilities, the visually-based phonological teaching approach was exceptionally powerful in helping children to build their sign and print vocabularies. Although intervention/teaching studies have been essential in testing hypotheses about spoken language phonological processes supporting non-deaf children’s reading development, there are no parallel intervention/teaching studies exploring hypotheses about signed language phonological processes in supporting deaf children’s reading development. This study begins to provide the needed evidence to pursue innovative teaching strategies that incorporate the strengths of visual learners.

Keywords: American sign language phonological awareness, dual language strategies, vocabulary learning, word reading

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Authors: Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh

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Traffic congestion has become a severe worldwide problem, affecting everyday life, fuel consumption, time, and air pollution. The primary causes of these issues are inadequate transportation infrastructure, poor traffic signal management, and rising population. Traffic flow forecasting is one of the essential and effective methods in urban congestion and traffic management, which has attracted the attention of researchers. With the development of technology, undeniable progress has been achieved in existing methods. However, there is a possibility of improvement in the extraction of temporal and spatial features to determine the importance of traffic flow sequences and extraction features. In the proposed model, we implement the convolutional neural network (CNN) and long short-term memory (LSTM) deep learning models for mining nonlinear correlations and their effectiveness in increasing the accuracy of traffic flow prediction in the real dataset. According to the experiments, the results indicate that implementing Conv-LSTM networks increases the productivity and accuracy of deep learning models for traffic flow prediction.

Keywords: deep learning algorithms, intelligent transportation systems, spatiotemporal features, traffic flow prediction

Procedia PDF Downloads 171

Authors: Abdelmenen Abobghala, Mahmud Ahmed, Mohamed Alwaheshi, Anwar Fanan, Meftah Mehdawi, Ahmed Abuhatira

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This research aims to predict academic performance and identify weak points in students to aid teachers in understanding their learning needs. Both quantitative and qualitative methods are used to identify difficult test items and the factors causing difficulties. The study uses interventions like focus group discussions, interviews, and action plans developed by the students themselves. The research questions explore the predictability of final grades based on mock exams and assignments, the student's response to action plans, and the impact on learning performance. Ethical considerations are followed, respecting student privacy and maintaining anonymity. The research aims to enhance student engagement, motivation, and responsibility for learning.

Keywords: prediction, academic performance, weak points, understanding, learning, quantitative methods, qualitative methods, formative assessments, feedback, emotional responses, intervention, focus group discussion, interview, action plan, student engagement, motivation, responsibility, ethical considerations

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Authors: Debneil Saha Roy

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Weather forecasting is a complex topic and is well suited for analysis by deep learning approaches. With the wide availability of weather observation data nowadays, these approaches can be utilized to identify immediate comparisons between historical weather forecasts and current observations. This work explores the application of deep learning techniques to weather forecasting in order to accurately predict the weather over a given forecast hori­zon. Three deep neural networks are used in this study, namely, Multi-Layer Perceptron (MLP), Long Short Tunn Memory Network (LSTM) and a combination of Convolutional Neural Network (CNN) and LSTM. The predictive performance of these models is compared using two evaluation metrics. The results show that forecasting accuracy increases with an increase in the complexity of deep neural networks.

Keywords: convolutional neural network, deep learning, long short term memory, multi-layer perceptron

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Authors: H. Khomri, A. Bentellis

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Since century of the Development Activities extraction and a dispersed mineral processing Toxic metals and much more contaminated vast areas occupied by what they natural outcrops. New types of metalliferous habitats are so appeared. A species that is Lygeum spartum attracted our curiosity because apart from its valuable role in desertification, it is apparently able to exclude antimony and other metals can be. This species, green leaf blades which are provided as cattle feed, would be a good subject for phytoremediation of mineral soils. The study of absorption and translocation of chromium by the Lygeum spartum in the mining region of Djebel Hamimat and the interaction soil-plant, revealed that soils of this species living in this region are alkaline, calcareous majority in their fine texture medium and saline in their minority. They have normal levels of organic matter. They are moderately rich in nitrogen. They contain total chromium content reaches a maximum of 66,80 mg Kg^(-1) and a total absence of soluble chromium. The results of the analysis of variance of the difference between bare soils and soils appear Lygeum spartum made a significant difference only for the silt and organic matter. But for the other variables analyzed this difference is not significant. Thus, this plant has only one action on the amendment, only the levels of silt and organic matter in soils. The results of the multiple regression of the chromium content of the roots according to all soil variables studied did appear that among the studied variables included in the model, only the electrical conductivity and clay occur in the explanation of contents chromium in roots. The chromium content of the aerial parts analyzed by regression based on all studied soil variables allows us to see only the variables: electrical conductivity and content of chromium in the root portion involved in the explanation of the content chromium in the aerial part.

Keywords: absorption, translocation, analysis of variance, chrome, Lygeum spartum, multiple regression, the soil variables

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Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

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Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

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Authors: Malini Ganapathy, Sarjit Kaur

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Maximising learning with higher-order thinking skills with Information and Communications Technology (ICT) has been deep-rooted and emphasised in various developed countries such as the United Kingdom, the United States of America and Singapore. The transformation of the education curriculum in the Malaysia Education Development Plan (PPPM) 2013-2025 focuses on the concept of Higher Order Thinking (HOT) skills which aim to produce knowledgeable students who are critical and creative in their thinking and can compete at the international level. HOT skills encourage students to apply, analyse, evaluate and think creatively in and outside the classroom. In this regard, the National Education Blueprint (2013-2025) is grounded based on high-performing systems which promote a transformation of the Malaysian education system in line with the vision of Malaysia’s National Philosophy in achieving educational outcomes which are of world class status. This study was designed to investigate ESL students’ learning practices on the emphasis of promoting HOTs while using ICT in their curricula. Data were collected using a stratified random sampling where 100 participants were selected to take part in the study. These respondents were a group of undergraduate students who undertook ESL courses in a public university in Malaysia. A three-part questionnaire consisting of demographic information, students’ learning experience and ICT utilization practices was administered in the data collection process. Findings from this study provide several important insights on students’ learning experiences and ICT utilization in developing HOT skills.

Keywords: English as a second language students, critical and creative thinking, learning, information and communication technology and higher order thinking skills

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Authors: Sara Corvino

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The aim of this study is to explore the potential of inclusive learning and assessment strategies to foster students' engagement with historical debates surrounding the field of graphic design. The goal is to respond to the diversity of L4 Graphic Design students, at Nottingham Trent University, in a way that instead of 'lowering standards' can benefit everyone. This research tests, measures, and evaluates the impact of a specific intervention, an assessment task, to develop students' critical visual analysis skills and stimulate a deeper engagement with the subject matter. Within the action research approach, this work has followed a case study research method to understand students' views and perceptions of a specific project. The primary methods of data collection have been: anonymous electronic questionnaire and a paper-based anonymous critical incident questionnaire. NTU College of Business Law and Social Sciences Research Ethics Committee granted the Ethical approval for this research in November 2019. Other methods used to evaluate the impact of this assessment task have been Evasys's report and students' performance. In line with the constructivist paradigm, this study embraces an interpretative and contextualized analysis of the collected data within the triangulation analytical framework. The evaluation of both qualitative and quantitative data demonstrates that active learning strategies and the disruption of thinking patterns can foster greater students' engagement and can lead to meaningful learning.

Keywords: active learning, assessment for learning, graphic design, higher education, student engagement

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Authors: P. Halder, A. Zaman

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It is estimated that heart disease accounts for one in ten deaths worldwide. United States deaths due to heart disease are among the leading causes of death according to the World Health Organization. Cardiovascular diseases (CVDs) account for one in four U.S. deaths, according to the Centers for Disease Control and Prevention (CDC). According to statistics, women are more likely than men to die from heart disease as a result of strokes. A 50% increase in men's mortality was reported by the World Health Organization in 2009. The consequences of cardiovascular disease are severe. The causes of heart disease include diabetes, high blood pressure, high cholesterol, abnormal pulse rates, etc. Machine learning (ML) can be used to make predictions and decisions in the healthcare industry. Thus, scientists have turned to modern technologies like Machine Learning and Data Mining to predict diseases. The disease prediction is based on four algorithms. Compared to other boosts, the Ada boost is much more accurate.

Keywords: heart disease, cardiovascular disease, coronary artery disease, feature selection, random forest, AdaBoost, SVM, decision tree

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Authors: Elvin Karaaslan Klose

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Museums are important sites of informal, often semi-structured and self-paced learning. Challenged by digital alternatives and increased expectations from their visitors, museums have to adapt to the digital age by enriching their collection and educational content with additional options for interactivity. One such option lies in the concept of the electronic book, which can be used either on dedicated devices or downloaded by visitors before entering the exhibition area. These electronic books serve as an alternative or supplement to the classic audio guide and provide visitors with information about artifacts as well as background stories and factoids about the subjects of the exhibition. Bringing such interactive elements into the museum experience has been shown to increase information retention and enjoyment among young aged visitors and adults. This article aims to bring together both theoretical frameworks and practical examples of how interactive media in the form of electronic books can be used to enhance the experience of the museum visitor.

Keywords: electronic books, interactive media, arts education, museum education

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Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction

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Authors: Fu-Chi Chuang, Yu-Liang, Chang, Wen-Der Wang

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Our environment has been contaminated by many artificial chemicals, such as plastics, pesticides. Many of them have hormone-like activity and are classified as 'environmental hormone (also named endocrine disruptors)'. These chemicals interfere with or mimic hormones have adverse effects that persist into adulthood. Environmental education is an important way to teach students to become engaged in real-world issues that transcend classroom walls. Elementary education is the first stage to perform environmental education and it is an important component to help students develop adequate environmental knowledge, attitudes, and behavior. However, elementary teachers' knowledge plays a critical role in this mission. Therefore, we use a questionnaire to survey the knowledge of environmental hormone of elementary school teachers and their learning motivation of the environmental hormone-regarding knowledge. We collected 218 questionnaires from Taiwanese elementary teachers and the results indicate around 73% of elementary teachers do not have enough knowledge about environmental hormones. Our results also reveal the in-service elementary teachers’ learning motivation of environmental hormones knowledge is positively enhanced once they realized their insufficient cognitive ability of environmental hormones. We believe our study will provide the powerful reference for Ministry of Education to set up the policy of environmental education to enrich all citizens sufficient knowledge of the effects of the environmental hormone on organisms, and further to enhance our correct environmental behaviors.

Keywords: elementary teacher, environmental hormones, learning motivation, questionnaire

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Authors: A. Mohammed, A. M. Umar, S. H. Adamu

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The study was conducted to evaluate the growth performance and nutrients utilization using 20 entire males of Sahelian goats fed Rumen content (fore-stomach digest) and poultry litter waste (PLW) at various levels of inclusion. The experimental animals were randomly allocated to diet A (Control), B (10% each of FSD and PLW), C (6.67%PLW and 13.33 FSD) and D(13.33% PLW and 6.67% FDS) at the rate of five animals per treatment. After 90 days of feeding trial, It was observed that Diets D had best feed intake and body weight gain which might be due to the good palatability of PLW and less odour of FSD in the diet. Diet C had the least feed cost then followed by diet B and while diet A(control) was more expensive than other treatments. There was the significant difference (P<0.05) between the treatments in the cost of daily feed consumption. Treatment A had the highest value while treatment C recorded the lowest cost of daily feed consumption. There was no significant difference (P > 0.05) between all treatments in terms of Cost of feed kg/ live weight gain, where treatment B had the highest value while the lowest obtained in treatment D. However, it is recommended that more research trial should be carried out to ascertain the true value of incorporating poultry litter waste and fore-stomach digest.

Keywords: poultry litter, rumen content, weight gain, economics

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Authors: Ilona Buchem, Carolin Gellner

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Over the last few years, the call for the support of senior learners in the development of their digital literacy has become prevalent, mainly due to the progression towards ageing societies paired with advances in digitalisation in all spheres of life, including e-health and electronic patient record (EPA). While major research efforts in supporting senior learners in developing digital literacy have been invested so far in e-learning focusing on knowledge acquisition and cognitive tasks, little research exists in learning models which target virtual mentoring and coaching with the help of pedagogical agents and address the social dimensions of learning. Research from studies with students in the context of formal education has already provided methods for designing intelligent virtual agents in support of personalised learning. However, this research has mostly focused on cognitive skills and has not yet been applied to the context of mentoring/coaching of senior learners, who have different characteristics and learn in different contexts. In this paper, we describe how insights from previous research can be used to develop an intelligent virtual learning coach (agent) for senior learners with a focus on building the social relationship between the agent and the learner and the key task of the agent to socialize learners to the larger context of digital literacy with a focus on electronic health records. Following current approaches to mentoring and coaching, the agent is designed not to enhance and monitor the cognitive performance of the learner but to serve as a trusted friend and advisor, whose role is to provide one-to-one guidance and support sharing of experiences among learners (peers). Based on literature review and synopsis of research on virtual agents and current coaching/mentoring models under consideration of the specific characteristics and requirements of senior learners, we describe the design framework which was applied to design an intelligent virtual learning coach as part of the e-learning system for digital literacy of senior learners in the ePA-Coach project founded by the German Ministry of Education and Research. This paper also presents the results from the evaluation study, which compared the use of the first prototype of the virtual learning coach designed according to the design framework with a voice narration in a multimedia learning environment with senior learners. The focus of the study was to validate the agent design in the context of the persona effect (Lester et al., 1997). Since the persona effect is related to the hypothesis that animated agents are perceived as more socially engaging, the study evaluated possible impacts of agent coaching in comparison with voice coaching on motivation, engagement, experience, and digital literacy.

Keywords: virtual learning coach, virtual mentor, pedagogical agent, senior learners, digital literacy, electronic health records

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Authors: Sachin Nagargoje

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Complete labeled data is often difficult to obtain in a practical scenario. Even if one manages to obtain the data, the quality of the data is always in question. In shopping vertical, offers are the input data, which is given by advertiser with or without a good quality of information. In this paper, an author investigated the possibility of using a very simple Semi-supervised learning approach to increase the recall of unhealthy offers (has badly written Offer Title or partial product details) in shopping vertical domain. The author found that the semisupervised learning method had improved the recall in the Smart Phone category by 30% on A=B testing on 10% traffic and increased the YoY (Year over Year) number of impressions per month by 33% at production. This also made a significant increase in Revenue, but that cannot be publicly disclosed.

Keywords: semi-supervised learning, clustering, recall, coverage

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Authors: Eunice H. Li

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This e-poster explores some of the issues that are linked to Open Educational Resources (OER). It describes how OER is explained by experts in the field and relates its value in attaining and using knowledge. ‘Open', 'open pedagogy', self-direction, freedom, and autonomy are the main issues identified for the discussion. All of these issues make essential contributions to OER in one way or another. Nevertheless, there are seemingly areas of contentions with regard to applying these concepts in teaching and learning practices. For this e-Poster, it is the teaching-learning aspects of OER that it is primarily concerned with. The basis for the discussion comes from a 2013 critique of OER presented by Jeremy Knox of the University of Edinburgh, tutor of the MSc in Digital Education Programme. This discussion is also supported by the analysis of other research work and papers in this area. The general view on OER is that it is a useful tool for the advancement of learner-centred models of education, but in whatever context, pedagogy cannot be diminished and overlooked. It should take into consideration how to deal with the issues identified above in order to allow learners to gain full benefit from OER.

Keywords: open, pedagogy, e-learning technologies, autonomy, knowledge

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Authors: Eric Agrie Ambele

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The norms and models for learning pronunciation in relation to the teaching and learning of English pronunciation are key issues nowadays in English Language Teaching in ESL contexts. This paper discusses these issues based on a study on the attitudes of some Francophone university students in Cameroon towards three English accents spoken in Cameroon: Cameroon Francophone English (CamFE), Cameroon English (CamE), and Hyperlectal Cameroon English (near standard British English). With the desire to know more about the treatment that these English accents receive among these students, an aspect that had hitherto received little attention in the literature, a language attitude questionnaire, and the matched-guise technique was used to investigate this phenomenon. Two methods of data analysis were employed: (1) the percentage count procedure, and (2) the semantic differential scale. The findings reveal that the participants’ attitudes towards the selected accents vary in degree. Though Hyperlectal CamE emerged first, CamE second and CamFE third, no accent, on average, received a negative evaluation. It can be deduced from this findings that, first, CamE is gaining more and more recognition and can stand as an autonomous accent; second, that the participants all rated Hyperlectal CamE higher than CamE implies that they would be less motivated in a context where CamE is the learning model. By implication, in the teaching of English pronunciation to francophone learners learning English in Cameroon, Hyperlectal Cameroon English should be the model.

Keywords: teaching pronunciation, English accents, Francophone learners, attitudes

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Authors: Daniel Asiamah Ameyaw

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This research attempts to investigate how lecturer evaluation makes a difference in enhancing higher education teaching and learning processes. The research questions to guide this research work states first as, “What are the perspectives on the difference made by evaluating academic teachers in order to enhance higher education teaching and learning processes?” and second, “What are the implications of the findings for Policy and Practice?” Data for this research was collected mainly through interviewing and partly documents review. Data analysis was conducted under the framework of grounded theory. The findings showed that for individual lecturer level, lecturer evaluation provides a continuous improvement of teaching strategies, and serves as source of data for research on teaching. At the individual student level, it enhances students learning process; serving as source of information for course selection by students; and by making students feel recognised in the educational process. At the institutional level, it noted that lecturer evaluation is useful in personnel and management decision making; it assures stakeholders of quality teaching and learning by setting up standards for lecturers; and it enables institutions to identify skill requirement and needs as a basis for organising workshops. Lecturer evaluation is useful at national level in terms of guaranteeing the competencies of graduates who then provide the needed manpower requirement of the nation. Besides, it mentioned that resource allocation to higher educational institution is based largely on quality of the programmes being run by the institution. The researcher concluded, that the findings have implications for policy and practice, therefore, higher education managers are expected to ensure that policy is implemented as planned by policy-makers so that the objectives can successfully be achieved.

Keywords: academic quality, higher education, lecturer evaluation, teaching and learning processes

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Authors: Azusa Katsumata

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Where there is collaboration between universities and companies in the educational context, companies seek ‘knowledge’ from universities and provide a ‘place of practice’ to them. Several universities have introduced activities aimed at the mutual enlightenment of a diversity of people in career education. However, several programs emphasize on delivering results, and on practicing the prepared materials as planned. Few programs focus on unexpected failures and setbacks. This way of learning is important in career education so that classmates can help each other, overcome difficulties, draw out each other’s strengths, and learn from them. Seijo University in Tokyo offered Tokyo Tourism, a Project-Based Learning course, as a first-year career education course until 2016. In cooperation with a travel agency, students participate in planning actual tourism products for foreigners visiting Japan, undertake tours serving as guides. This paper aims to study the 'learning platform' created by a series of processes such as the fieldwork, planning tours, the presentation, selling the tourism products, and guiding the tourists. We conducted a questionnaire to measure the development of work-related skills in class. From the results of the questionnaire, we can see, in the example of this class, that students demonstrated an increased desire to be pro-active and an improved motivation to learn. Students have not, however, acquired policy or business skills. This is appropriate for first-year careers education, but we need to consider how this can be incorporated into future courses. In the questionnaire filled out by the students after the class, the following results were found. Planning and implementing travel products while learning from each other, and helping the teams has led to improvements in the student workforce. This course is a collaborative project between Japanese universities and the 2020 Tokyo Olympics and Paralympic Games committee.

Keywords: university career education, platform of learning, project-based learning, collaboration between university and company

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Authors: Hassnen M. Jafer, W. Atherton, F. Ruddock, E. Loffill

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This study represents the results of an experimental work using two types of fly ashes as a cement replacement in soft soil stabilisation. The fly ashes (FA1 and FA2) used in this study are by-products resulting from an incineration processes between 800 and 1200 ˚C. The stabilised soil in this study was an intermediate plasticity silty clayey soil with medium organic matter content. The experimental works were initially conducted on soil treated with different percentages of FA1 (0, 3, 6, 9, 12, and 15%) to identify the optimum FA1 content. Then FA1 was chemically activated by FA2 which has high alkalinity by blending the optimum content of FA1 with different portions of FA2. The improvement levels were evaluated dependent on the results obtained from consistency limits and compaction tests along with the results of unconfined compressive strength (UCS) tests which were conducted on specimens of soil treated with FA1 and FA2 and exposed to different periods of curing (zero, 7, 14, and 28 days). The results indicated that the FA1 and FA2 used in this study effectively improved the physical and geotechnical properties of the soft soil where the index of plasticity (IP) was decreased significantly from 21 to 13.17 with 12% of FA1; however, there was a slight increase in IP with the use of FA2. Meanwhile, 12% of FA1 was identified as the optimum percentage improving the UCS of stabilised soil significantly. Furthermore, FA2 was found effective as a chemical activator to FA1 where the UCS was improved significantly after using FA2.

Keywords: fly ashes, soft soil stabilisation, waste materials, unconfined compressive strength

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Authors: A. Schuchter, M. Promegger

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The outbreak of the COVID-19 pandemic has shown us that online education is so much more than just a cool feature for teachers – it is an essential part of modern teaching. In online math teaching, it is common to use tools to share screens, compute and calculate mathematical examples, while the students can watch the process. On the other hand, flipped classroom models are on the rise, with their focus on how students can gather knowledge by watching videos and on the teacher’s use of technological tools for information transfer. This paper proposes a co-educational teaching approach for coding and engineering subjects with the help of drone-building to spark interest in technology and create a platform for knowledge transfer. The project combines aspects from mathematics (matrices, vectors, shaders, trigonometry), physics (force, pressure and rotation) and coding (computational thinking, block-based programming, JavaScript and Python) and makes use of collaborative-shared 3D Modeling with clara.io, where students create mathematics knowhow. The instructor follows a problem-based learning approach and encourages their students to find solutions in their own time and in their own way, which will help them develop new skills intuitively and boost logically structured thinking. The collaborative aspect of working in groups will help the students develop communication skills as well as structural and computational thinking. Students are not just listeners as in traditional classroom settings, but play an active part in creating content together by compiling a Handbook of Knowledge (called “open book”) with examples and solutions. Before students start calculating, they have to write down all their ideas and working steps in full sentences so other students can easily follow their train of thought. Therefore, students will learn to formulate goals, solve problems, and create a ready-to use product with the help of “reverse engineering”, cross-referencing and creative thinking. The work on drones gives the students the opportunity to create a real-life application with a practical purpose, while going through all stages of product development.

Keywords: flipped classroom, co-creational education, coding, making, drones, co-education, ARCS-model, problem-based learning

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Authors: Feng Xu, Zhaozhi Liu, Junhua Xu, Xiaolong Tang, Dunwen Zuo

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Chemical vapor deposition (CVD) diamond coated cutting tool has excellent cutting performance, it is the most ideal tool for the processing of nonferrous metals and alloys, composites, nonmetallic materials and other difficult-to-machine materials efficiently and accurately. Depositing CVD diamond coating on the cemented carbide with high cobalt content can improve its toughness and strength, therefore, it is very important to research on the preparation technology and cutting properties of CVD diamond coated cemented carbide cutting tool with high cobalt content. The preparation technology of boron-doped diamond (BDD) coating has been studied and the coated drills were prepared. BDD coating were deposited on the drills by using the optimized parameters and the SEM results show that there are no cracks or collapses in the coating. Cutting tests with the prepared drills against the silumin and aluminum base printed circuit board (PCB) have been studied. The results show that the wear amount of the coated drill is small and the machined surface has a better precision. The coating does not come off during the test, which shows good adhesion and cutting performance of the drill.

Keywords: cemented carbide with high cobalt content, CVD boron-doped diamond, cutting test, drill

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Authors: Walid Cherif

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Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: data mining, knowledge discovery, machine learning, similarity measurement, supervised classification

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Authors: Hari Sharan Pandit

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Mathematics teaching in Nepal has been centralized and guided by the notion of transfer of knowledge and skills from teachers to students. The overemphasis on an algorithm-centric approach of mathematics teaching and the focus on ‘rote–learning’ as the ultimate way of solving mathematical problems since the early years of schooling have been creating severe problems in school-level mathematics in Nepal. In this context, the author argues that students should learn real-world mathematical problems through various interesting, creative and collaborative, as well as artistic and alternative ways of knowing. The collaboration-incorporated pedagogy is an distinct pedagogical approach that offers a better alternative as an integrated and interdisciplinary approach to learning that encourages students to think more broadly and critically about real-world problems. The paper, as a summarized report of action research designed, developed and implemented by the author, focuses on the needs and usefulness of collaboration-incorporated pedagogy in the Nepali context to make mathematics teaching more meaningful for producing creative and critical citizens. This paper is useful for mathematics teachers, teacher educators and researchers who argue on arts integration in mathematics teaching.

Keywords: algorithm-centric, rote-learning, collaboration - incorporated pedagogy, action research

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Authors: N. P. D. Tran, H. Q. D. Nguyen, M. C. Yang

Abstract:

In this study, contact lenses were prepared through the polymerization of tris-(trimethyl-silyl-propyl-methacrylate) (TRIS), N,N-dimethylacrylamide (DMA), N-vinylpyrrolidone (NVP), and cross-linked with ethylene glycol dimethylacrylate (EGDMA). The equilibrium water content (EWC), oxygen permeability (Dk), light transmittance, and in vitro cytotoxicity of TRIS-DMA-NVP with various ratios were measured. The results showed that the EWC increased while the Dk decreased with the increase of NVP content. For the sample with 25 wt% NVP, the EWC attained 53% whereas the Dk decreased to 46 barrers. All these lenses exhibited light transmittance over than 95%. In addition, all these lenses exhibited no inhibition to the growth of L292 fibroblasts. Thus, this study showed that TRIS-DMA-NVP can be applicable for making contact lens.

Keywords: DMA, TRIS, NVP, silicone hydrogel, contact lens

Procedia PDF Downloads 322

Authors: Susan Dodd

Abstract:

This presentation details the methodology for teachers to identify and support a population of students who have historically been overlooked in regards to their educational needs. The twice exceptional (2e) student is a learner who is considered gifted and also has a learning disability, as defined by the Individuals with Disabilities Education Act (IDEA). Many of these students remain underserved throughout their educational careers because their exceptionalities may mask each other, resulting in a special population of students who are not achieving to their fullest potential. There are three common scenarios that may make the identification of a 2e student challenging. First, the student may have been identified as gifted, and her disability may go unnoticed. She could also be considered an under-achiever, or she may be able to compensate for her disability under the school works becomes more challenging. In the second scenario, the student may be identified as having a learning disability and is only receiving remedial services where his giftedness will not be highlighted. His overall IQ scores may be misleading because they were impacted by his learning disability. In the third scenario, the student is able to compensate for her ability well enough to maintain average scores, and she goes undetected as both gifted and learning disabled. Research in the area identifies the complexity involved in identifying 2e students, and how multiple forms of assessment are required. It is important for teachers to be aware of the common characteristics exhibited by many 2e students, so these learners can be identified and appropriately served. Once 2e students have been identified, teachers are then challenged to meet the varying needs of these exceptional learners. Strength-based teaching entails simultaneously providing gifted instruction as well as individualized accommodations for those students. Research in this field has yielded strategies that have proven helpful for teaching 2e students, as well as other students who may be struggling academically. Differentiated instruction, while necessary in all classrooms, is especially important for 2e students, as is encouragement for academic success. Teachers who take the time to really know their students will have a better understanding of each student’s strengths and areas for growth, and therefore tailor instruction to extend the intellectual capacities for optimal achievement. Teachers should also understand that some learning activities can prove very frustrating to students, and these activities can be modified based on individual student needs. Because 2e students can often become discouraged by their learning challenges, it is especially important for teachers to assist students in recognizing their own strengths and maintaining motivation for learning. Although research on the needs of 2e students has spanned across two decades, this population remains underserved in many educational institutions. Teacher awareness of the identification of and the support strategies for 2e students is critical for their success.

Keywords: gifted, learning disability, special needs, twice exceptional

Procedia PDF Downloads 179

Authors: Adisorn Bansong, Walai Isarankura Na Ayudhaya, Aumporn Makanong

Abstract:

A Development of an Instructional Model for Health Education was the aim to develop and study the effectiveness of an instructional model for health education to enhance self-regulation and learning achievement of lower secondary school students. It was the Quasi-Experimental Designs, used a Single-group Interrupted Time-series Designs, conducted by 2 phases: 1. To develop an instructional model based on Social Cognitive Theory and Strategic Life Planning. 2. To trial and evaluate effectiveness of an instructional model. The results as the following: i. An Instructional Model for Health Education consists of five main components: a) Attention b) Forethought c) Tactic Planning d) Execution and e) Reflection. ii. After an Instructional Model for Health Education has used for a semester trial, found the 4.07 percent of sample’s Self-Regulation higher and learning achievement on post-test were significantly higher than pre-test at .05 levels (p = .033, .000).

Keywords: social cognitive theory, strategic life planning, self-regulation, learning achievement

Procedia PDF Downloads 465

Authors: Yee-May Chan

Abstract:

In recent decades, it is observed that social work agencies have participated actively, and thus, have gradually been more influential in social work education in Hong Kong. The neo-liberal welfare ideologies and changing funding mode have transformed the landscape in social work practice and have also had a major influence on the fieldwork environment in Hong Kong. The aim of this research is to explore the educational role of social work agencies and examine in particular whether they are able to enhance or hinder critical reflective learning in fieldwork. In-depth interviews with 15 frontline social workers and managers in different social work agencies were conducted to collect their views and experience in helping social work students in fieldwork. The overall findings revealed that under the current social welfare context most social workers consider that the most important role of social work agencies in fieldwork is to help students prepare to fit-in the practice requirements and work within agencies’ boundary. The fit-for-purpose and down-to-earth view of fieldwork practice is seen as prevalent among most social workers. This narrow perception of agency’s role seems to be more favourable to competence-based approaches. In contrast, though critical reflection has been seen as important in addressing the changing needs of service users, the role of enhancing critical reflective learning has not been clearly expected or understood by most agency workers. The notion of critical reflection, if considered, has been narrowly perceived in fieldwork learning. The findings suggest that the importance of critical reflection is found to be subordinate to that of practice competence. The lack of critical reflection in the field is somehow embedded in the competence-based social work practice. In general, social work students’ critical reflection has not been adequately supported or enhanced in fieldwork agencies, nor critical reflective practice has been encouraged in fieldwork process. To address this situation, the role of social work agencies in fieldwork should be re-examined. To maximise critical reflective learning in the field, critical reflection as an avowed objective in fieldwork learning should be clearly stated. Concrete suggestions are made to help fieldwork agencies become more prepared to critical reflective learning. It is expected that the research can help social work communities to reflect upon the current realities of fieldwork context and to identify ways to strengthen agencies’ capacities to enhance critical reflective learning and practice of social work students.

Keywords: competence-based social work, critical reflective learning, fieldwork agencies, neo-liberal welfare

Procedia PDF Downloads 321