Search results for: batch machine learning
5971 Sense Environmental Hormones in Elementary School Teachers and Their in Service Learning Motivation
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
Procedia PDF Downloads 3135970 ePA-Coach: Design of the Intelligent Virtual Learning Coach for Senior Learners in Support of Digital Literacy in the Context of Electronic Patient Record
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
Procedia PDF Downloads 1175969 An Embarrassingly Simple Semi-supervised Approach to Increase Recall in Online Shopping Domain to Match Structured Data with Unstructured Data
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
Procedia PDF Downloads 1225968 Learning from Dendrites: Improving the Point Neuron Model
Authors: Alexander Vandesompele, Joni Dambre
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The diversity in dendritic arborization, as first illustrated by Santiago Ramon y Cajal, has always suggested a role for dendrites in the functionality of neurons. In the past decades, thanks to new recording techniques and optical stimulation methods, it has become clear that dendrites are not merely passive electrical components. They are observed to integrate inputs in a non-linear fashion and actively participate in computations. Regardless, in simulations of neural networks dendritic structure and functionality are often overlooked. Especially in a machine learning context, when designing artificial neural networks, point neuron models such as the leaky-integrate-and-fire (LIF) model are dominant. These models mimic the integration of inputs at the neuron soma, and ignore the existence of dendrites. In this work, the LIF point neuron model is extended with a simple form of dendritic computation. This gives the LIF neuron increased capacity to discriminate spatiotemporal input sequences, a dendritic functionality as observed in another study. Simulations of the spiking neurons are performed using the Bindsnet framework. In the common LIF model, incoming synapses are independent. Here, we introduce a dependency between incoming synapses such that the post-synaptic impact of a spike is not only determined by the weight of the synapse, but also by the activity of other synapses. This is a form of short term plasticity where synapses are potentiated or depressed by the preceding activity of neighbouring synapses. This is a straightforward way to prevent inputs from simply summing linearly at the soma. To implement this, each pair of synapses on a neuron is assigned a variable,representing the synaptic relation. This variable determines the magnitude ofthe short term plasticity. These variables can be chosen randomly or, more interestingly, can be learned using a form of Hebbian learning. We use Spike-Time-Dependent-Plasticity (STDP), commonly used to learn synaptic strength magnitudes. If all neurons in a layer receive the same input, they tend to learn the same through STDP. Adding inhibitory connections between the neurons creates a winner-take-all (WTA) network. This causes the different neurons to learn different input sequences. To illustrate the impact of the proposed dendritic mechanism, even without learning, we attach five input neurons to two output neurons. One output neuron isa regular LIF neuron, the other output neuron is a LIF neuron with dendritic relationships. Then, the five input neurons are allowed to fire in a particular order. The membrane potentials are reset and subsequently the five input neurons are fired in the reversed order. As the regular LIF neuron linearly integrates its inputs at the soma, the membrane potential response to both sequences is similar in magnitude. In the other output neuron, due to the dendritic mechanism, the membrane potential response is different for both sequences. Hence, the dendritic mechanism improves the neuron’s capacity for discriminating spa-tiotemporal sequences. Dendritic computations improve LIF neurons even if the relationships between synapses are established randomly. Ideally however, a learning rule is used to improve the dendritic relationships based on input data. It is possible to learn synaptic strength with STDP, to make a neuron more sensitive to its input. Similarly, it is possible to learn dendritic relationships with STDP, to make the neuron more sensitive to spatiotemporal input sequences. Feeding structured data to a WTA network with dendritic computation leads to a significantly higher number of discriminated input patterns. Without the dendritic computation, output neurons are less specific and may, for instance, be activated by a sequence in reverse order.Keywords: dendritic computation, spiking neural networks, point neuron model
Procedia PDF Downloads 1335967 Open Educational Resources (OER): Deciding upon Openness
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
Procedia PDF Downloads 4005966 Francophone University Students' Attitudes Towards English Accents in Cameroon
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
Procedia PDF Downloads 1975965 Enhancing Higher Education Teaching and Learning Processes: Examining How Lecturer Evaluation Make a Difference
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
Procedia PDF Downloads 1435964 [Keynote Talk]: Study of Cooperative Career Education between Universities and Companies
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
Procedia PDF Downloads 1615963 Role of Yeast-Based Bioadditive on Controlling Lignin Inhibition in Anaerobic Digestion Process
Authors: Ogemdi Chinwendu Anika, Anna Strzelecka, Yadira Bajón-Fernández, Raffaella Villa
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Anaerobic digestion (AD) has been used since time in memorial to take care of organic wastes in the environment, especially for sewage and wastewater treatments. Recently, the rising demand/need to increase renewable energy from organic matter has caused the AD substrates spectrum to expand and include a wider variety of organic materials such as agricultural residues and farm manure which is annually generated at around 140 billion metric tons globally. The problem, however, is that agricultural wastes are composed of materials that are heterogeneous and too difficult to degrade -particularly lignin, that make up about 0–40% of the total lignocellulose content. This study aimed to evaluate the impact of varying concentrations of lignin on biogas yields and their subsequent response to a commercial yeast-based bioadditive in batch anaerobic digesters. The experiments were carried out in batches for a retention time of 56 days with different lignin concentrations (200 mg, 300 mg, 400 mg, 500 mg, and 600 mg) treated to different conditions to first determine the concentration of the bioadditive that was most optimal for overall process improvement and yields increase. The batch experiments were set up using 130 mL bottles with a working volume of 60mL, maintained at 38°C in an incubator shaker (150rpm). Digestate obtained from a local plant operating at mesophilic conditions was used as the starting inoculum, and commercial kraft lignin was used as feedstock. Biogas measurements were carried out using the displacement method and were corrected to standard temperature and pressure using standard gas equations. Furthermore, the modified Gompertz equation model was used to non-linearly regress the resulting data to estimate gas production potential, production rates, and the duration of lag phases as indicatives of degrees of lignin inhibition. The results showed that lignin had a strong inhibitory effect on the AD process, and the higher the lignin concentration, the more the inhibition. Also, the modelling showed that the rates of gas production were influenced by the concentrations of the lignin substrate added to the system – the higher the lignin concentrations in mg (0, 200, 300, 400, 500, and 600) the lower the respective rate of gas production in ml/gVS.day (3.3, 2.2, 2.3, 1.6, 1.3, and 1.1), although the 300 mg increased by 0.1 ml/gVS.day over that of the 200 mg. The impact of the yeast-based bioaddition on the rate of production was most significant in the 400 mg and 500 mg as the rate was improved by 0.1 ml/gVS.day and 0.2 ml/gVS.day respectively. This indicates that agricultural residues with higher lignin content may be more responsive to inhibition alleviation by yeast-based bioadditive; therefore, further study on its application to the AD of agricultural residues of high lignin content will be the next step in this research.Keywords: anaerobic digestion, renewable energy, lignin valorisation, biogas
Procedia PDF Downloads 915962 Minimizing Learning Difficulties in Teaching Mathematics
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
Procedia PDF Downloads 135961 Investigation of Boll Properties on Cotton Picker Machine Performance
Authors: Shahram Nowrouzieh, Abbas Rezaei Asl, Mohamad Ali Jafari
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Cotton, as a strategic crop, plays an important role in providing human food and clothing need, because of its oil, protein, and fiber. Iran has been one of the largest cotton producers in the world in the past, but unfortunately, for economic reasons, its production is reduced now. One of the ways to reduce the cost of cotton production is to expand the mechanization of cotton harvesting. Iranian farmers do not accept the function of cotton harvesters. One reason for this lack of acceptance of cotton harvesting machines is the number of field losses on these machines. So, the majority of cotton fields are harvested by hand. Although the correct setting of the harvesting machine is very important in the cotton losses, the morphological properties of the cotton plant also affect the performance of cotton harvesters. In this study, the effect of some cotton morphological properties such as the height of the cotton plant, number, and length of sympodial and monopodial branches, boll dimensions, boll weight, number of carpels and bracts angle were evaluated on the performance of cotton picker. In this research, the efficiency of John Deere 9920 spindle Cotton picker is investigated on five different Iranian cotton cultivars. The results indicate that there was a significant difference between the five cultivars in terms of machine harvest efficiency. Golestan cultivar showed the best cotton harvester performance with an average of 87.6% of total harvestable seed cotton and Khorshid cultivar had the least cotton harvester performance. The principal component analysis showed that, at 50.76% probability, the cotton picker efficiency is affected by the bracts angle positively and by boll dimensions, the number of carpels and the height of cotton plants negatively. The seed cotton remains (in the plant and on the ground) after harvester in PCA scatter plot were in the same zone with boll dimensions and several carpels.Keywords: cotton, bract, harvester, carpel
Procedia PDF Downloads 1355960 Differentiated Instruction for All Learners: Strategies for Full Inclusion
Authors: Susan Dodd
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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 1795959 An Experimental Study of Self-Regulated Learning with High School Gifted Pupils
Authors: Prakash Singh
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Research studies affirm the view that gifted pupils are endowed with unique personality traits, enabling them to study at higher levels of thinking, at a faster pace, and with a greater degree of autonomy than their average counterparts. The focus of this study was whether high school gifted pupils are capable of studying an advanced level curriculum on their own by employing self-regulated learning (SRL) strategies. To be self-regulated, pupils are required to be metacognitively, motivationally, and behaviourally active participants in their own learning processes so that they are able to initiate and direct their personal curriculum efforts to acquire cognitive skills and knowledge, instead of being solely reliant on their teachers. Researchers working with gifted populations concede that limited studies have been conducted thus far to examine gifted pupils’ expertise in using SRL strategies to assume ownership of their learning. In order to conduct this investigation, an enriched module in Accounting for specifically gifted grade eleven pupils was developed, incorporating advanced level content, and use was made of the Post-test-Only Control Group Design to accomplish this research objective. The results emanating from this empirical study strongly suggest that SRL strategies can be employed to overcome a narrow, rigid approach that limits the education of gifted pupils in the regular classroom of the high school. SRL can meaningfully offer an alternative way to implement an advanced level curriculum for the gifted in the mainstream of education. This can be achieved despite the limitations of differentiation in the regular classroom.Keywords: advanced level curriculum, high school gifted pupils, self-regulated learning, teachers’ professional competencies
Procedia PDF Downloads 4025958 Development of an Instructional Model for Health Education Based On Social Cognitive Theory and Strategic Life Planning to Enhance Self-Regulation and Learning Achievement of Lower Secondary School Students
Authors: Adisorn Bansong, Walai Isarankura Na Ayudhaya, Aumporn Makanong
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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 4655957 Enhancing Critical Reflective Practice in Fieldwork Education: An Exploratory Study of the Role of Social Work Agencies in the Welfare Context of Hong Kong
Authors: Yee-May Chan
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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 3215956 Leveraging Reasoning through Discourse: A Case Study in Secondary Mathematics Classrooms
Authors: Cory A. Bennett
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Teaching and learning through the use of discourse support students’ conceptual understanding by attending to key concepts and relationships. One discourse structure used in primary classrooms is number talks wherein students mentally calculate, discuss, and reason about the appropriateness and efficiency of their strategies. In the secondary mathematics classroom, the mathematics understudy does not often lend itself to mental calculations yet learning to reason, and articulate reasoning, is central to learning mathematics. This qualitative case study discusses how one secondary school in the Middle East adapted the number talk protocol for secondary mathematics classrooms. Several challenges in implementing ‘reasoning talks’ became apparent including shifting current discourse protocols and practices to a more student-centric model, accurately recording and probing student thinking, and specifically attending to reasoning rather than computations.Keywords: discourse, reasoning, secondary mathematics, teacher development
Procedia PDF Downloads 1875955 Machine Translation Analysis of Chinese Dish Names
Authors: Xinyu Zhang, Olga Torres-Hostench
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This article presents a comparative study evaluating and comparing the quality of machine translation (MT) output of Chinese gastronomy nomenclature. Chinese gastronomic culture is experiencing an increased international acknowledgment nowadays. The nomenclature of Chinese gastronomy not only reflects a specific aspect of culture, but it is related to other areas of society such as philosophy, traditional medicine, etc. Chinese dish names are composed of several types of cultural references, such as ingredients, colors, flavors, culinary techniques, cooking utensils, toponyms, anthroponyms, metaphors, historical tales, among others. These cultural references act as one of the biggest difficulties in translation, in which the use of translation techniques is usually required. Regarding the lack of Chinese food-related translation studies, especially in Chinese-Spanish translation, and the current massive use of MT, the quality of the MT output of Chinese dish names is questioned. Fifty Chinese dish names with different types of cultural components were selected in order to complete this study. First, all of these dish names were translated by three different MT tools (Google Translate, Baidu Translate and Bing Translator). Second, a questionnaire was designed and completed by 12 Chinese online users (Chinese graduates of a Hispanic Philology major) in order to find out user preferences regarding the collected MT output. Finally, human translation techniques were observed and analyzed to identify what translation techniques would be observed more often in the preferred MT proposals. The result reveals that the MT output of the Chinese gastronomy nomenclature is not of high quality. It would be recommended not to trust the MT in occasions like restaurant menus, TV culinary shows, etc. However, the MT output could be used as an aid for tourists to have a general idea of a dish (the main ingredients, for example). Literal translation turned out to be the most observed technique, followed by borrowing, generalization and adaptation, while amplification, particularization and transposition were infrequently observed. Possibly because that the MT engines at present are limited to relate equivalent terms and offer literal translations without taking into account the whole context meaning of the dish name, which is essential to the application of those less observed techniques. This could give insight into the post-editing of the Chinese dish name translation. By observing and analyzing translation techniques in the proposals of the machine translators, the post-editors could better decide which techniques to apply in each case so as to correct mistakes and improve the quality of the translation.Keywords: Chinese dish names, cultural references, machine translation, translation techniques
Procedia PDF Downloads 1375954 Development of Web-Based Iceberg Detection Using Deep Learning
Authors: A. Kavya Sri, K. Sai Vineela, R. Vanitha, S. Rohith
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Large pieces of ice that break from the glaciers are known as icebergs. The threat that icebergs pose to navigation, production of offshore oil and gas services, and underwater pipelines makes their detection crucial. In this project, an automated iceberg tracking method using deep learning techniques and satellite images of icebergs is to be developed. With a temporal resolution of 12 days and a spatial resolution of 20 m, Sentinel-1 (SAR) images can be used to track iceberg drift over the Southern Ocean. In contrast to multispectral images, SAR images are used for analysis in meteorological conditions. This project develops a web-based graphical user interface to detect and track icebergs using sentinel-1 images. To track the movement of the icebergs by using temporal images based on their latitude and longitude values and by comparing the center and area of all detected icebergs. Testing the accuracy is done by precision and recall measures.Keywords: synthetic aperture radar (SAR), icebergs, deep learning, spatial resolution, temporal resolution
Procedia PDF Downloads 915953 Applying Program Theory-Driven Approach to Design and Evaluate a Teacher Professional Development Program
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Japanese Scholar Manabu Sato has been advocating the Learning Community, which changed Japanese fundamental education during the last three decades. It was also called a “Quiet Revolution.” Manabu Sato criticized that traditional education only focused on individual competition, exams, teacher-centered instruction, and memorization. The students lacked leaning motivation. Therefore, Manabu Sato proclaimed that learning should be a sustainable process of “constantly weaving the relationship and the meanings” by having dialogues with learning materials, with peers, and with oneself. For a long time, secondary school education in Taiwan has been focused on exams and emphasized reciting and memorizing. The incident of “giving up learning” happened to some students. Manabu Sato’s learning community program has been implemented very successfully in Japan. It is worth exploring if learning community can resolve the issue of “Escape from learning” phenomenon among secondary school students in Taiwan. This study was the first year of a two-year project. This project applied a program theory-driven approach to evaluating the impact of teachers’ professional development interventions on students’ learning by using a mix of methods, qualitative inquiry, and quasi-experimental design. The current study was to show the results of using the method of theory-driven approach to program planning to design and evaluate a teachers’ professional development program (TPDP). The Manabu Sato’s learning community theory was applied to structure all components of a 54-hour workshop. The participants consisted of seven secondary school science teachers from two schools. The research procedure was comprised of: 1) Defining the problem and assessing participants’ needs; 2) Selecting the Theoretical Framework; 3) Determining theory-based goals and objectives; 4) Designing the TPDP intervention; 5) Implementing the TPDP intervention; 6) Evaluating the TPDP intervention. Data was collected from a number of different sources, including TPDP checklist, activity responses of workshop, LC subject matter test, teachers’ e-portfolio, course design documents, and teachers’ belief survey. The major findings indicated that program design was suitable to participants. More than 70% of the participants were satisfied with program implementation. They revealed that TPDP was beneficial to their instruction and promoted their professional capacities. However, due to heavy teaching loadings during the project some participants were unable to attend all workshops. To resolve this problem, the author provided options to them by watching DVD or reading articles offered by the research team. This study also established a communication platform for participants to share their thoughts and learning experiences. The TPDP had marked impacts on participants’ teaching beliefs. They believe that learning should be a sustainable process of “constantly weaving the relationship and the meanings” by having dialogues with learning materials, with peers, and with oneself. Having learned from TPDP, they applied a “learner-centered” approach and instructional strategies to design their courses, such as learning by doing, collaborative learning, and reflective learning. To conclude, participants’ beliefs, knowledge, and skills were promoted by the program instructions.Keywords: program theory-driven approach, learning community, teacher professional development program, program evaluation
Procedia PDF Downloads 3085952 Discrimination and Classification of Vestibular Neuritis Using Combined Fisher and Support Vector Machine Model
Authors: Amine Ben Slama, Aymen Mouelhi, Sondes Manoubi, Chiraz Mbarek, Hedi Trabelsi, Mounir Sayadi, Farhat Fnaiech
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Vertigo is a sensation of feeling off balance; the cause of this symptom is very difficult to interpret and needs a complementary exam. Generally, vertigo is caused by an ear problem. Some of the most common causes include: benign paroxysmal positional vertigo (BPPV), Meniere's disease and vestibular neuritis (VN). In clinical practice, different tests of videonystagmographic (VNG) technique are used to detect the presence of vestibular neuritis (VN). The topographical diagnosis of this disease presents a large diversity in its characteristics that confirm a mixture of problems for usual etiological analysis methods. In this study, a vestibular neuritis analysis method is proposed with videonystagmography (VNG) applications using an estimation of pupil movements in the case of an uncontrolled motion to obtain an efficient and reliable diagnosis results. First, an estimation of the pupil displacement vectors using with Hough Transform (HT) is performed to approximate the location of pupil region. Then, temporal and frequency features are computed from the rotation angle variation of the pupil motion. Finally, optimized features are selected using Fisher criterion evaluation for discrimination and classification of the VN disease.Experimental results are analyzed using two categories: normal and pathologic. By classifying the reduced features using the Support Vector Machine (SVM), 94% is achieved as classification accuracy. Compared to recent studies, the proposed expert system is extremely helpful and highly effective to resolve the problem of VNG analysis and provide an accurate diagnostic for medical devices.Keywords: nystagmus, vestibular neuritis, videonystagmographic system, VNG, Fisher criterion, support vector machine, SVM
Procedia PDF Downloads 1365951 Developing a Virtual Reality System to Assist in Anatomy Teaching and Evaluating the Effectiveness of That System
Authors: Tarek Abdelkader, Suresh Selvaraj, Prasad Iyer, Yong Mun Hin, Hajmath Begum, P. Gopalakrishnakone
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Nowadays, more and more educational institutes, as well as students, rely on 3D anatomy programs as an important tool that helps students correlate the actual locations of anatomical structures in a 3D dimension. Lately, virtual reality (VR) is gaining more favor from the younger generations due to its higher interactive mode. As a result, using virtual reality as a gamified learning platform for anatomy became the current goal. We present a model where a Virtual Human Anatomy Program (VHAP) was developed to assist with the anatomy learning experience of students. The anatomy module has been built, mostly, from real patient CT scans. Segmentation and surface rendering were used to create the 3D model by direct segmentation of CT scans for each organ individually and exporting that model as a 3D file. After acquiring the 3D files for all needed organs, all the files were introduced into a Virtual Reality environment as a complete body anatomy model. In this ongoing experiment, students from different Allied Health orientations are testing the VHAP. Specifically, the cardiovascular system has been selected as the focus system of study since all of our students finished learning about it in the 1st trimester. The initial results suggest that the VHAP system is adding value to the learning process of our students, encouraging them to get more involved and to ask more questions. Involved students comments show that they are excited about the VHAP system with comments about its interactivity as well as the ability to use it solo as a self-learning aid in combination with the lectures. Some students also experienced minor side effects like dizziness.Keywords: 3D construction, health sciences, teaching pedagogy, virtual reality
Procedia PDF Downloads 1575950 From “Learning to Read” to “Reading to Learn”
Authors: Lucélia Alcântara
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Reading has been seen as a passive skill by many people for a long time. However, when one comes to study it deeply and in a such a way that the act of reading equals acquiring knowledge through living an experience that belongs to him/her, passive definitely becomes active. Material development with a focus on reading has to consider much more than reading strategies. The following questions are asked: Is the material appropriate to the students’ reality? Does it make students think and state their points of view? With that in mind a lesson has been developed to illustrate theory becoming practice. Knowledge, criticality, intercultural experience and social interaction. That is what reading is for.Keywords: reading, culture, material development, learning
Procedia PDF Downloads 5345949 Imputing Missing Data in Electronic Health Records: A Comparison of Linear and Non-Linear Imputation Models
Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand
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Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models on two different realworld electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.Keywords: EHR, machine learning, imputation, laboratory variables, algorithmic bias
Procedia PDF Downloads 855948 A Review of End-of-Term Oral Tests for English-Majored Students of HCMC Open University
Authors: Khoa K. Doan
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Assessment plays an essential role in teaching and learning English as it aims to measure the learning outcomes. Designing appropriate test types and procedures for four skills, especially productive skills, is a very challenging task for teachers of English. The assessment scheme is supposed to provide precise measures and fair opportunities for students to demonstrate what they can do with their language skills. This involves content domains, measurement techniques, administrative feasibility, target populations, and potential sources of testing bias. Based on these elements, a review of end-of-term speaking tests for English-majored students at Ho Chi Minh City Open University (Viet Nam) was undertaken for the purpose of analyzing the strengths and limitations of the testing tool for the speaking assessment. It helped to identify what could be done to facilitate the process of teaching and learning in that context.Keywords: assessment, oral tests, speaking, testing
Procedia PDF Downloads 3205947 Classification of Computer Generated Images from Photographic Images Using Convolutional Neural Networks
Authors: Chaitanya Chawla, Divya Panwar, Gurneesh Singh Anand, M. P. S Bhatia
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This paper presents a deep-learning mechanism for classifying computer generated images and photographic images. The proposed method accounts for a convolutional layer capable of automatically learning correlation between neighbouring pixels. In the current form, Convolutional Neural Network (CNN) will learn features based on an image's content instead of the structural features of the image. The layer is particularly designed to subdue an image's content and robustly learn the sensor pattern noise features (usually inherited from image processing in a camera) as well as the statistical properties of images. The paper was assessed on latest natural and computer generated images, and it was concluded that it performs better than the current state of the art methods.Keywords: image forensics, computer graphics, classification, deep learning, convolutional neural networks
Procedia PDF Downloads 3375946 Scenario-Based Learning Using Virtual Optometrist Applications
Authors: J. S. M. Yang, G. E. T. Chua
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Diploma in Optometry (OPT) course is a three-year program offered by Ngee Ann Polytechnic (NP) to train students to provide primary eye care. Students are equipped with foundational conceptual knowledge and practical skills in the first three semesters before clinical modules in fourth to six semesters. In the clinical modules, students typically have difficulties in integrating the acquired knowledge and skills from the past semesters to perform general eye examinations on public patients at NP Optometry Centre (NPOC). To help the students overcome the challenge, a web-based game Virtual Optometrist (VO) was developed to help students apply their skills and knowledge through scenario-based learning. It consisted of two interfaces, Optical Practice Counter (OPC) and Optometric Consultation Room (OCR), to provide two simulated settings for authentic learning experiences. In OPC, students would recommend and provide appropriate frame and lens selection based on virtual patient’s case history. In OCR, students would diagnose and manage virtual patients with common ocular conditions. Simulated scenarios provided real-world clinical situations that required contextual application of integrated knowledge from relevant modules. The stages in OPC and OCR are of increasing complexity to align to expected students’ clinical competency as they progress to more senior semesters. This prevented gameplay fatigue as VO was used over the semesters to achieve different learning outcomes. Numerous feedback opportunities were provided to students based on their decisions to allow individualized learning to take place. The game-based learning element in VO was achieved through the scoreboard and leader board to enhance students' motivation to perform. Scores were based on the speed and accuracy of students’ responses to the questions posed in the simulated scenarios, preparing the students to perform accurately and effectively under time pressure in a realistic optometric environment. Learning analytics was generated in VO’s backend office based on students’ responses, offering real-time data on distinctive and observable learners’ behavior to monitor students’ engagement and learning progress. The backend office allowed versatility to add, edit, and delete scenarios for different intended learning outcomes. Likert Scale was used to measure students’ learning experience with VO for OPT Year 2 and 3 students. The survey results highlighted the learning benefits of implementing VO in the different modules, such as enhancing recall and reinforcement of clinical knowledge for contextual application to develop higher-order thinking skills, increasing efficiency in clinical decision-making, facilitating learning through immediate feedback and second attempts, providing exposure to common and significant ocular conditions, and training effective communication skills. The results showed that VO has been useful in reinforcing optometry students’ learning and supporting the development of higher-order thinking, increasing efficiency in clinical decision-making, and allowing students to learn from their mistakes with immediate feedback and second attempts. VO also exposed the students to diverse ocular conditions through simulated real-world clinical scenarios, which may otherwise not be encountered in NPOC, and promoted effective communication skills.Keywords: authentic learning, game-based learning, scenario-based learning, simulated clinical scenarios
Procedia PDF Downloads 1175945 Feasibility Study of Measurement of Turning Based-Surfaces Using Perthometer, Optical Profiler and Confocal Sensor
Authors: Khavieya Anandhan, Soundarapandian Santhanakrishnan, Vijayaraghavan Laxmanan
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In general, measurement of surfaces is carried out by using traditional methods such as contact type stylus instruments. This prevalent approach is challenged by using non-contact instruments such as optical profiler, co-ordinate measuring machine, laser triangulation sensors, machine vision system, etc. Recently, confocal sensor is trying to be used in the surface metrology field. This sensor, such as a confocal sensor, is explored in this study to determine the surface roughness value for various turned surfaces. Turning is a crucial machining process to manufacture products such as grooves, tapered domes, threads, tapers, etc. The roughness value of turned surfaces are in the range of range 0.4-12.5 µm, were taken for analysis. Three instruments were used, namely, perthometer, optical profiler, and confocal sensor. Among these, in fact, a confocal sensor is least explored, despite its good resolution about 5 nm. Thus, such a high-precision sensor was used in this study to explore the possibility of measuring turned surfaces. Further, using this data, measurement uncertainty was also studied.Keywords: confocal sensor, optical profiler, surface roughness, turned surfaces
Procedia PDF Downloads 1345944 Neural Style Transfer Using Deep Learning
Authors: Shaik Jilani Basha, Inavolu Avinash, Alla Venu Sai Reddy, Bitragunta Taraka Ramu
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We can use the neural style transfer technique to build a picture with the same "content" as the beginning image but the "style" of the picture we've chosen. Neural style transfer is a technique for merging the style of one image into another while retaining its original information. The only change is how the image is formatted to give it an additional artistic sense. The content image depicts the plan or drawing, as well as the colors of the drawing or paintings used to portray the style. It is a computer vision programme that learns and processes images through deep convolutional neural networks. To implement software, we used to train deep learning models with the train data, and whenever a user takes an image and a styled image, the output will be as the style gets transferred to the original image, and it will be shown as the output.Keywords: neural networks, computer vision, deep learning, convolutional neural networks
Procedia PDF Downloads 955943 Gaia (Earth) Education Philosophy – A Journey Back to the Future
Authors: Darius Singh
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This study adopts a research, develop, and deploy methodology to create a state-of-the-art forest preschool environment using technology and the Gaia (Earth) Education Philosophy as design support. The new philosophy adopts an ancient Greek terminology, “Gaia,” meaning “Mother Earth”, and it take its principle to model everything with the oldest living and breathing entity that it know – Earth. This includes using nature and biomimicry-based principles in building design, environments, curricula, teaching, learning, values and outcomes for children. The study highlights the potential effectiveness of the Gaia (Earth) Education Philosophy as a means of designing Earth-inspired environments for children’s learning. The discuss the strengths of biomimicry-based design principles and propose a curriculum that emphasizes natural outcomes for early childhood learning. Theoretical implications of the study are that the Gaia (Earth) Education Philosophy could serve as a strong foundation for educating young learners.it present a unique approach that promotes connections with Earth-principles and lessons that can contribute to the development of social and environmental consciousness among children and help educate generations to come into a stable and balanced future.Keywords: earth science, nature education, sustainability, gaia, forest school, nature, inspirational teaching and learning
Procedia PDF Downloads 655942 Computer Aided Analysis of Breast Based Diagnostic Problems from Mammograms Using Image Processing and Deep Learning Methods
Authors: Ali Berkan Ural
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This paper presents the analysis, evaluation, and pre-diagnosis of early stage breast based diagnostic problems (breast cancer, nodulesorlumps) by Computer Aided Diagnosing (CAD) system from mammogram radiological images. According to the statistics, the time factor is crucial to discover the disease in the patient (especially in women) as possible as early and fast. In the study, a new algorithm is developed using advanced image processing and deep learning method to detect and classify the problem at earlystagewithmoreaccuracy. This system first works with image processing methods (Image acquisition, Noiseremoval, Region Growing Segmentation, Morphological Operations, Breast BorderExtraction, Advanced Segmentation, ObtainingRegion Of Interests (ROIs), etc.) and segments the area of interest of the breast and then analyzes these partly obtained area for cancer detection/lumps in order to diagnosis the disease. After segmentation, with using the Spectrogramimages, 5 different deep learning based methods (specified Convolutional Neural Network (CNN) basedAlexNet, ResNet50, VGG16, DenseNet, Xception) are applied to classify the breast based problems.Keywords: computer aided diagnosis, breast cancer, region growing, segmentation, deep learning
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