Search results for: concept-based learning

Authors: Madhuri S. Ghate, Rahul P. Chavhan, Shriya S. Nahar

Abstract:

Learning objective: •To describe Magnetic Resonance Imaging (MRI) imaging appearances of typical and atypical uterine fibroids with emphasis on differentiating it from other similar conditions. •To classify uterine fibroids according to International Federation of Gynecology and Obstetrics (FIGO) Sub-classifications system and emphasis on its clinical significance. •To show cases with atypical imaging appearances atypical fibroids Material and methods: MRI of Pelvis had been performed in symptomatic women of child bearing age group on 1.5T and 3T MRI using T1, T2, STIR, FAT SAT, DWI sequences. Contrast was administered when degeneration was suspected. Imaging appearances of Atypical fibroids and various degenerations in fibroids were studied. Fibroids were classified using FIGO Sub-classification system. Its impact on surgical decision making and clinical outcome were also studied qualitatively. Results: Intramural fibroids were most common (14 patients), subserosal 7 patients, submucosal 5 patients . 6 patients were having multiple fibroids. 7 were having atypical fibroids. (1 hyaline degeneration, 1 cystic degeneration, 1 fatty, 1 necrosis and hemorrhage, 1 red degeneration, 1 calcification, 1 unusual large bilobed growth). Fibroids were classified using FIGO system. In uterus conservative surgeries, the lesser was the degree of myometrial invasion of fibroid, better was the fertility outcome. Conclusion: Relationship of fibroid with mucosal and serosal layers is important in the management of symptomatic fibroid cases. Risk to fertility involved in uterus conservative surgeries in women of child bearing age group depends on the extent of myometrial invasion of fibroids. FIGO system provides better insight into the degree of myometrial invasion. Knowledge about the atypical appearances of fibroids is important to avoid diagnostic confusion and untoward treatment.

Keywords: degeneration, FIGO sub-classification, MRI pelvis, uterine fibroids

Procedia PDF Downloads 88

Authors: Fernanda Goulart, Rita de Cássia Barbirato

Abstract:

Task-based language teaching has received attention among researchers as it has been pointed out with the potential to provide more significant opportunities for using the target language and therefore generate successful language acquisition. Nevertheless, in the Brazilian context, few studies have analyzed the potential of tasks in English language acquisition. There is also a need for textbooks to meet the needs of Brazilian students. This work is part of doctoral research in its initial phase. It aims to demonstrate and discuss thematic textbook samples on tasks designed to be applied among high school and undergraduate students in a public technological educational context in São Paulo State, Brazil. It is a qualitative study. The data collection process for course design and textbook development initially included a survey administered to 159 students. Questions related to students’ English background knowledge, main learning interests, and needs. Most students reported difficulties communicating in English and showed a strong interest in a communicative English course. The theme “Cultural diversity” was chosen among other options provided. The textbook was then designed and comprised nine task cycles divided into four sequences. Cycles were composed of pre-tasks, tasks, and post-tasks. The main findings of this first phase of the research revealed that designing a task-based textbook is not easy and requires the necessary steps and lots of effort to meet students’ language needs. Several revisions were needed before the conclusion of the final version of the textbook. The material will be further applied in a three-month English course. In this presentation, we hope to contribute to discussions in research on task-based teaching. Also, we intend to support teachers with their knowledge of tasks and thematic material development in this field.

Keywords: task-based language teaching, language acquisition, English language teaching, task cycles

Procedia PDF Downloads 78

Authors: Sharda Kumari, Saiman Shetty

Abstract:

Autonomous trucking is just one of the numerous significant shifts impacting fleet management services. The Society of Automotive Engineers (SAE) has defined six levels of vehicle automation that have been adopted internationally, including by the United States Department of Transportation. On public highways in the United States, organizations are testing driverless vehicles with at least Level 4 automation which indicates that a human is present in the vehicle and can disable automation, which is usually done while the trucks are not engaged in highway driving. However, completely driverless vehicles are presently being tested in the state of California. While autonomous trucking can increase safety, decrease trucking costs, provide solutions to trucker shortages, and improve efficiencies, logistics, too, requires advancements to keep up with trucking innovations. Given that artificial intelligence, machine learning, and automated procedures enable people to do their duties in other sectors with fewer resources, CRM (Customer Relationship Management) can be applied to the autonomous trucking business to provide the same level of efficiency. In a society witnessing significant digital disruptions, fleet management is likewise being transformed by technology. Utilizing strategic alliances to enhance core services is an effective technique for capitalizing on innovations and delivering enhanced services. Utilizing analytics on CRM systems improves cost control of fuel strategy, fleet maintenance, driver behavior, route planning, road safety compliance, and capacity utilization. Integration of autonomous trucks with automated fleet management, yard/terminal management, and customer service is possible, thus having significant power to redraw the lines between the public and private spheres in autonomous trucking logistics.

Keywords: autonomous vehicles, customer relationship management, customer experience, autonomous trucking, digital transformation

Procedia PDF Downloads 107

Authors: Ruby Jean Hornsby

Abstract:

In our rapidly advancing techno-moral world, human-robot relationships are increasingly becoming a part of intimate human life. Indeed, social robots - that is, autonomous or semi-autonomous embodied artificial agents that generally possess human or animal-like qualities (such as responding to environmental stimuli, communicating, learning, performing human tasks, and making autonomous decisions) - have been designed to function as human friends. In light of such advances, immediate philosophical scrutiny is imperative in order to examine the extent to which human-robot interactions constitute genuine friendship and therefore contribute towards the good human life. Aristotle's conception of friendship is philosophically illuminating and sufficiently broad in scope to guide such analysis. On his account, it is necessary (though not sufficient) that for a friendship to exist between two agents - A and B - both agents must have a mutual love for one another. Aristotle claims that A loves B if: Condition 1: A desires those apparent good (qua pleasant, useful, or virtuous) properties attributable to B, and Condition 2: A has goodwill (wishes what is best) for B. This paper argues that human-robot interaction can (and does) successfully meet both conditions; as such, it demonstrates that robots and humans can reciprocally love one another. It will argue for this position by first justifying the claim that a human can desire apparent good features attributable to a robot (i.e., by taking them to be pleasant and/or useful) and outlining how it is that a human can wish a robot well in light of that robot's (quasi-) interests. Next, the paper will argue that a robot can (quasi-)desire certain properties that are attributable to a human before elucidating how it is possible for a robot to act in the interests of a human. Accordingly, this paper will conclude that it is already the case that humans can formulate relationships with robots that involve reciprocated love. This is significant because it suggests that social robots are candidates for human friendship and can therefore contribute toward flourishing human futures.

Keywords: ancient philosophy, friendship, inter-disciplinary applied ethics, love, social robotics

Procedia PDF Downloads 100

Authors: Mitansha, Suzanne Wilkinson, Regan Potangaroa

Abstract:

The built environment is designed, maintained, operated, and decommissioned by construction organisations, which play a significant role in providing physical resources and rebuilding infrastructures during major crises and disasters. It is evident that enhancing the resilience of construction organisations allows better responding ability and speedy recovery from disasters and acts as a boon for the nation in the face of significant disruptions. As individuals are the integral component of any organisation, hence, individual resilience is considered a critical aspect, which may boost organisational resilience of construction sector. It has been observed that individual resilience is indirectly supported by organisation’s citizenship behaviour, job performance, and career success. Not only this, it also tends to hold a directly proportional relation with job satisfaction, physical and emotional well-being affected by organisation’s work culture, whereas the resilience of organisation increases as a result of positive adaption, growth and collective learning of the employees as an entity. Moreover, indicators like Situation awareness in staff and crisis related issues, effective vulnerability management, organisational leadership and culture ensured by approachable, encouraging and people-oriented leaders, are prominent for achieving organisational resilience. It, thus, becomes perceptible that both, organisational and individual resiliencies have the potential to influence each other. Consequently, it arises a major question that how these characteristics are associated and tend to behave with respect to each other The study, thus, aims to explore the overlapping dimensions of organisational and individual resilience to determine the impact boundaries. The research methodology of the paper would be based on systematic literature review specifically focused on the resilience of construction industry. This would provide a direct comparison of characteristics influencing individual and organisational resilience and will present the most significant indicators of individual resilience, that can eventually help to enhance the resilience of construction organisations amidst any disaster or crisis.

Keywords: construction industry, individual resilience, organizational resilience, overlapping dimension

Procedia PDF Downloads 100

Authors: Lena Shulyakovskaya

Abstract:

Every year, schools aim to develop and adopt new technology and pedagogy as a way to equip today's students with the needed 21st Century skills. However, the field of primary and secondary education may not be as open to embracing change in reality. Despite the drive to reform and innovation, the field of education in Canada is still very much steeped in tradition and uses many of the practices that came into effect over 50 years ago. Among those are employment and retention practices. Millennials are the youngest generation of professionals entering the workplace at this time and the ones leaving their jobs within just a few years. Almost half of new teachers leave Canadian schools within their first five years on the job. This paper discusses one of the contributing factors that lead Canadian millennial teachers to either leave or stay in the profession - standardized education system. Using an exploratory case study approach, in-depth interviews with former and current millennial teachers were conducted to learn about their experiences within the K-12 system. Among the findings were the young teachers' concerns about the constant changes to teaching practices and technological implementations that claimed to advance teaching and learning, and yet in reality only disguised and reiterated the same traditional, outdated, and standardized practices that already existed. Furthermore, while many millennial teachers aspired to be innovative with their curriculum and teaching practices, they felt trapped and helpless in the hands of school leaders who were very reluctant to change. While many new program ideas and technological advancements are being made openly available to teachers on a regular basis, it is important to consider the education field as a whole and how it plays into the teachers' ability to realistically implement changes. By the year 2025, millennials will make up approximately 75% of the North American workforce. It is important to examine generational differences among teachers and understand how millennial teachers may be shaping the future of primary and secondary schools, either by staying or leaving the profession.

Keywords: 21st century skills, millennials, teacher attrition, tradition

Procedia PDF Downloads 226

Authors: Gaurav Kumar Sinha

Abstract:

In an era marked by increasing concerns about energy sustainability, this research endeavors to address the pressing challenge of energy consumption in buildings and industries. This study delves into the transformative potential of AWS services in optimizing energy efficiency. The research is founded on the recognition that effective management of energy consumption is imperative for both environmental conservation and economic viability. Buildings and industries account for a substantial portion of global energy use, making it crucial to develop advanced techniques for analysis and reduction. This study sets out to explore the integration of AWS services with big data analytics to provide innovative solutions for energy consumption analysis. Leveraging AWS's cloud computing capabilities, scalable infrastructure, and data analytics tools, the research aims to develop efficient methods for collecting, processing, and analyzing energy data from diverse sources. The core focus is on creating predictive models and real-time monitoring systems that enable proactive energy management. By harnessing AWS's machine learning and data analytics capabilities, the research seeks to identify patterns, anomalies, and optimization opportunities within energy consumption data. Furthermore, this study aims to propose actionable recommendations for reducing energy consumption in buildings and industries. By combining AWS services with metrics-driven insights, the research strives to facilitate the implementation of energy-efficient practices, ultimately leading to reduced carbon emissions and cost savings. The integration of AWS services not only enhances the analytical capabilities but also offers scalable solutions that can be customized for different building and industrial contexts. The research also recognizes the potential for AWS-powered solutions to promote sustainable practices and support environmental stewardship.

Keywords: energy consumption analysis, big data analytics, AWS services, energy efficiency

Procedia PDF Downloads 63

Authors: Bahadır Erişti

Abstract:

Values are the behavioral procedures of society based communication and interaction process that includes social and cultural backgrounds. The policy of learning and teaching in higher education is oriented towards constructing knowledge and skills, based on theorist framework of cognitive and psychomotor aspects. This approach makes people not to develop generosity, empathy, affection, solidarity, justice, equality and so on. But the sensorial gains of education system provide the integrity of society interaction. This situation carries out the necessity of values education’s in higher education. The current study aims to consider values education from the viewpoint of students in higher education. Within the framework of the current study, an open ended survey based scenario of higher education students was conducted with the students’ social, cognitive, affective and moral developments. In line with this purpose, the following situations of the higher education system were addressed based on the higher education students’ viewpoint: The views of higher education students’ regarding values that are tried to be gained at the higher education system; The higher education students’ suggestions regarding values education at the higher education system; The views of the higher education students’ regarding values that are imposed at the higher education system. In this study, descriptive qualitative research method was used. The study group of the research is composed of 20 higher education postgraduate students at Curriculum and Instruction Department of Educational Sciences at Anadolu University. An open-ended survey was applied for the purpose of collecting qualitative data. As a result of the study, value preferences, value judgments and value systems of the higher education students were constructed on prioritizes based on social, cultural and economic backgrounds and statues. Multi-dimensional process of value education in higher education need to be constructed on higher education-community-cultural background cooperation. Thus, the act of judgement upon values between higher education students based on the survey seems to be inherent in the system of education itself. The present study highlights the students’ value priorities and importance of values in higher education. If the purpose of the higher education system gains on values, it is possible to enable society to promote humanity.

Keywords: higher education, value, values education, values in higher education

Procedia PDF Downloads 337

Authors: Carlos Alberto Ríos Reyes, Andrés Felipe Mejía Durán, Oscar Mauricio Castellanos Alarcón

Abstract:

There is no doubt of great importance to make it known that planet Earth is an entity in constant change and transformation; processes such as construction and destruction are part of the evolution of the territory. Geoeducation workshops represent a significant contribution to the search for educational projects focused on teaching relevant geoscience topics to make natural threats known in schools through recreational and didactic activities. This initiative represents an educational alternative that must be developed with the participation of primary and secondary schools, universities, and local communities. The methodology is based on several phases, which include: diagnosis to know the best teaching method for basic concepts and establish a starting point for the topics to be taught, as well as to identify areas and concepts that need to be reinforced and/or deepened; design of activities that involve all students regardless of their ability or level; use of accessible materials and experimentation to support clear and concise explanations for all students; adaptation of the teaching-learning process to individual needs; sensitization about natural threats; and evaluation and feedback. It is expected to offer a series of activities and materials as a significant contribution to the search for educational projects focused on teaching relevant geoscientific topics such as natural threats associated with earthquakes, volcanic eruptions, floods, landslides, etc. The major findings of this study are the pedagogical strategies that primary and secondary school teachers can appropriate to face the challenge of transferring geological knowledge and to advise decision-makers and citizens on the importance of geosciences for daily life. We conclude that the knowledge of the natural threats to our planet is very important to contribute to mitigating their risk.

Keywords: workshops, geoeducation, curriculum, geosciences, natural threats

Procedia PDF Downloads 64

Authors: G. Ravindranath, S. Savitha

Abstract:

This paper presents heat transfer analysis of single horizontal bare tube and heat transfer analysis of staggered arrangement of bare tube bundles bare tube bundles in gas-solid (air-solid) fluidized bed and predictions are done by using Artificial Neural Network (ANN) based on experimental data. Fluidized bed provide nearly isothermal environment with high heat transfer rate to submerged objects i.e. due to through mixing and large contact area between the gas and the particle, a fully fluidized bed has little temperature variation and gas leaves at a temperature which is close to that of the bed. Measurement of average heat transfer coefficient was made by local thermal simulation technique in a cold bubbling air-fluidized bed of size 0.305 m. x 0.305 m. Studies were conducted for single horizontal Bare Tube of length 305mm and 28.6mm outer diameter and for bare tube bundles of staggered arrangement using beds of large (average particle diameter greater than 1 mm) particle (raagi and mustard). Within the range of experimental conditions influence of bed particle diameter ( Dp), Fluidizing Velocity (U) were studied, which are significant parameters affecting heat transfer. Artificial Neural Networks (ANNs) have been receiving an increasing attention for simulating engineering systems due to some interesting characteristics such as learning capability, fault tolerance, and non-linearity. Here, feed-forward architecture and trained by back-propagation technique is adopted to predict heat transfer analysis found from experimental results. The ANN is designed to suit the present system which has 3 inputs and 2 out puts. The network predictions are found to be in very good agreement with the experimental observed values of bare heat transfer coefficient (hb) and nusselt number of bare tube (Nub).

Keywords: fluidized bed, large particles, particle diameter, ANN

Procedia PDF Downloads 364

Authors: Stephanie Liu Lu

Abstract:

With the proliferation of artificial intelligence tools in the field of education, it is crucial to explore their impact on language learning outcomes. This paper examines the use of AI tools, such as ChatGPT, in practical writing within business Chinese teaching to investigate how AI can enhance practical writing skills and teaching effectiveness. The study involved third and fourth-year university students majoring in accounting and finance from a university in Hong Kong within the context of a business correspondence writing class. Students were randomly assigned to a control group, who completed business letter writing independently, and an experimental group, who completed the writing with the assistance of AI. In the latter, the AI-assisted business letters were initially drafted by the students issuing commands and interacting with the AI tool, followed by the students' revisions of the draft. The paper assesses the performance of both groups in terms of grammatical expression, communicative effect, and situational awareness. Additionally, the study collected dialogue texts from interactions between students and the AI tool to explore factors that affect text generation and the potential impact of AI on enhancing students' communicative and identity awareness. By collecting and comparing textual performances, it was found that students assisted by AI showed better situational awareness, as well as more skilled organization and grammar. However, the research also revealed that AI-generated articles frequently lacked a proper balance of identity and writing purpose due to limitations in students' communicative awareness and expression during the instruction and interaction process. Furthermore, the revision of drafts also tested the students' linguistic foundation, logical thinking abilities, and practical workplace experience. Therefore, integrating AI tools and related teaching into the curriculum is key to the future of business Chinese teaching.

Keywords: AI-assistance, business Chinese, textual analysis, language education

Procedia PDF Downloads 54

Authors: Parinyaporn Thanaboonpuang, Siridej Sujiva, Shotiga Pasiphul

Abstract:

The higher education reform that integration of nursing programmes into the higher education system. Learning outcomes represent one of the essential building blocks for transparency within higher education systems and qualifications. The purpose of this study is to develop a toolkit of undergraduate nursing student’desirable characteristics assessment on Thai Qualifications Framework for Higher education and to test psychometric property for this instrument. This toolkit seeks to improve on the Computer Multimedia test. There are three skills to be examined: Cognitive skill, Responsibility and Interpersonal Skill, and Information Technology Skill. The study was conduct in 4 phases. In Phase 1. Based on developed a measurement model and Computer Multimedia test. Phase 2 two round focus group were conducted, to determine the content validity of measurement model and the toolkit. In Phase 3, data were collected using a multistage random sampling of 1,156 senior undergraduate nursing student were recruited to test psychometric property. In Phase 4 data analysis was conducted by descriptive statistics, item analysis, inter-rater reliability, exploratory factor analysis and confirmatory factor analysis. The resulting TNDC consists of 74 items across the following four domains: Cognitive skill, Interpersonal Skill, Responsibility and Information Technology Skill. The value of Cronbach’ s alpha for the four domains were .781, 807, .831, and .865, respectively. The final model in confirmatory factor analysis fit quite well with empirical data. The TNDC was found to be appropriate, both theoretically and statistically. Due to these results, it is recommended that the toolkit could be used in future studies for Nursing Program in Thailand.

Keywords: toolkit, nursing student’ desirable characteristics, Thai qualifications framework

Procedia PDF Downloads 535

Authors: Osvaldo N. Oliveira Jr.

Abstract:

The control of molecular architecture inherent in some experimental methods to produce nanostructured films has had great impact on devices of various types, including sensors and biosensors. The self-assembly monolayers (SAMs) and the electrostatic layer-by-layer (LbL) techniques, for example, are now routinely used to produce tailored architectures for biosensing where biomolecules are immobilized with long-lasting preserved activity. Enzymes, antigens, antibodies, peptides and many other molecules serve as the molecular recognition elements for detecting an equally wide variety of analytes. The principles of detection are also varied, including electrochemical methods, fluorescence spectroscopy and impedance spectroscopy. In this presentation an overview will be provided of biosensors made with nanostructured films to detect antibodies associated with tropical diseases and HIV, in addition to detection of analytes of medical interest such as cholesterol and triglycerides. Because large amounts of data are generated in the biosensing experiments, use has been made of computational and statistical methods to optimize performance. Multidimensional projection techniques such as Sammon´s mapping have been shown more efficient than traditional multivariate statistical analysis in identifying small concentrations of anti-HIV antibodies and for distinguishing between blood serum samples of animals infected with two tropical diseases, namely Chagas´ disease and Leishmaniasis. Optimization of biosensing may include a combination of another information visualization method, the Parallel Coordinate technique, with artificial intelligence methods in order to identify the most suitable frequencies for reaching higher sensitivity using impedance spectroscopy. Also discussed will be the possible convergence of technologies, through which machine learning and other computational methods may be used to treat data from biosensors within an expert system for clinical diagnosis.

Keywords: clinical diagnosis, information visualization, nanostructured films, layer-by-layer technique

Procedia PDF Downloads 334

Authors: Indira Makhazhan, Azamat Taigarayev, Perizat Yerlan, Batyrbay Gulbike, Samal Abzhanova

Abstract:

Aitys is a competitional performance of two or more poets creating instantly the lyrics of music concerning the social issues accompanied with the traditional instrument dombra. It is an unique music genre, because it is not practical to create music and lyrics spontaneous in anywhere else. This research study tends to approach to this particular music genre Aitys and identify its significance not only in the sense of the Kazakh cultural heritage, but also from the perspective of personal development as the improvisational , oratory, public performance skills within the ability to think critically over the social problems and represent them in convenient to public form. Through conducting this research, this paper aims to reveal the importance and beneficence of aitys in terms of both prevalence of cultural heritage and its function in personal development of the singer. In order to answer to the research question, we conducted a survey and an in-depth interview with the students of Nazarbayev University. In the survey it was asked to answer the general questions about aitys and its importance, whereas in the interview part, we asked their opinion on the importance of aitys in improving the personal skills. The results of findings was more surprising than it was expected. They agreed that the aitys lessons, workshops and concerts have high outcomes in terms improvements of improvisational, oratory, and leadership skills. Students of NU as a representors of young generation have shown a great interest in aitys, and even more interested in the topics/social issues, where the poets have to defend their usually controversial position. To conclude, the research study has focused on the importance of the aitys in personal development of different leadership skills. The given research lead us to think about the aitys as a part of cognitive musicology, where within the learning of music it represents the process of cognition as well.

Keywords: aitys, cultural heritage, Kazakh language, musicology, personal development

Procedia PDF Downloads 354

Authors: Abderrahim Elmoataz

Abstract:

More and more contemporary applications involve data in the form of functions defined on irregular and topologically complicated domains (images, meshs, points clouds, networks, etc). Such data are not organized as familiar digital signals and images sampled on regular lattices. However, they can be conveniently represented as graphs where each vertex represents measured data and each edge represents a relationship (connectivity or certain affinities or interaction) between two vertices. Processing and analyzing these types of data is a major challenge for both image and machine learning communities. Hence, it is very important to transfer to graphs and networks many of the mathematical tools which were initially developed on usual Euclidean spaces and proven to be efficient for many inverse problems and applications dealing with usual image and signal domains. Historically, the main tools for the study of graphs or networks come from combinatorial and graph theory. In recent years there has been an increasing interest in the investigation of one of the major mathematical tools for signal and image analysis, which are Partial Differential Equations (PDEs) variational methods on graphs. The normalized p-laplacian operator has been recently introduced to model a stochastic game called tug-of-war-game with noise. Part interest of this class of operators arises from the fact that it includes, as particular case, the infinity Laplacian, the mean curvature operator and the traditionnal Laplacian operators which was extensiveley used to models and to solve problems in image processing. The purpose of this paper is to introduce and to study a new class of normalized p-Laplacian on graphs. The introduction is based on the extension of p-harmonious function introduced in as discrete approximation for both infinity Laplacian and p-Laplacian equations. Finally, we propose to use these operators as a framework for solving many inverse problems in image processing.

Keywords: normalized p-laplacian, image processing, stochastic game, inverse problems

Procedia PDF Downloads 511

Authors: Sadeq Al Yaari, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaari

Abstract:

Background & aims: Reading is a receptive skill whose importance could involve abilities' variance from linguistic standard. Several evidences support the hypothesis stating that the more you read the better you write, with a different impact for speech language therapists (SLTs) who use audio-visual aids and computer-assisted language instruction (CALI) and those who do not. Methods: Here we made use of audio-visual aids and CALI for teaching reading skill to a group of 40 students of special needs of both sexes (range between 8 and 18 years old) at al-Malādh school for teaching students of special needs in Dhamar (Yemen) while another group of the same number is taught using ordinary teaching methods. Pre-and-posttests have been administered at the beginning and the end of the semester (Before and after teaching the reading course). The purpose was to understand the differences between the levels of the students of special needs to see to what extent audio-visual aids and CALI are useful for them. The two groups were taught by the same instructor under the same circumstances in the same school. Both quantitative and qualitative procedures were used to analyze the data. Results: The overall findings revealed that audio-visual aids and CALI are very useful for teaching reading to students of special needs and this can be seen in the scores of the treatment group’s subjects (7.0%, in post-test vs.2.5% in pre-test). In comparison to the scores of the second group’s subjects (where audio-visual aids and CALI were not used) (2.2% in both pre-and-posttests), the first group subjects have overcome reading tasks and this can be observed in their performance in the posttest. Compared with males, females’ performance was better (1466 scores (7.3%) vs. 1371 scores (6.8%). Qualitative and statistical analyses showed that such comprehension is absolutely due to the use of audio-visual aids and CALI and nothing else. These outcomes confirm the evidence of the significance of using audio-visual aids and CALI as effective means for teaching receptive skills in general and reading skill in particular.

Keywords: reading, receptive skills, audio-visual aids, CALI, students, special needs, SLTs

Procedia PDF Downloads 47

Authors: Ting Shen, Spyros Konstantopoulos

Abstract:

During the past three decades, class size effects have been a focal debate in education. The idea of having smaller class is enormously popular among parents, teachers and policy makers. The rationale of its popularity is that small classroom could provide a better learning environment in which there would be more teacher-pupil interaction and more individualized instruction. This early stage benefits would also have a long-term positive effect. It is a common belief that reducing class size may result in increases in student achievement. However, the empirical evidence about class-size effects from experimental or quasi-experimental studies has been mixed overall. This study sheds more light on whether class size reduction impacts reading achievement in eight European countries: Bulgaria, Germany, Hungary, Italy, Lithuania, Romania, Slovakia, and Slovenia. We examine class size effects on reading achievement using national probability samples of fourth graders. All eight European countries had participated in the Progress in International Reading Literacy Study (PIRLS) in 2001, 2006 and 2011. Methodologically, the quasi-experimental method of instrumental variables (IV) has been utilized to facilitate causal inference of class size effects. Overall, the results indicate that class size effects on reading achievement are not significant across countries and years. However, class size effects are evident in Romania where reducing class size increases reading achievement. In contrast, in Germany, increasing class size seems to increase reading achievement. In future work, it would be valuable to evaluate differential class size effects for minority or economically disadvantaged student groups or low- and high-achievers. Replication studies with different samples and in various settings would also be informative. Future research should continue examining class size effects in different age groups and countries using rich international databases.

Keywords: class size, reading achievement, instrumental variables, PIRLS

Procedia PDF Downloads 289

Authors: Abdullah Al Farwan, Ya Zhang

Abstract:

In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

Procedia PDF Downloads 165

Authors: L. Sun, C. Hardacre, A. Garforth, N. Zhang

Abstract:

Higher Education (HE) degrees in the UK are attractive for international students. The recognized reputation of the HE and the world-leading researchers in some areas in the UK imply that the HE degree from the UK might be a passport to a successful career for abroad students. However, it is a challenge to inspire outstanding students applying for the universities in the UK. The incentives should be country-specific for undergraduates and postgraduates. The potential obstacles to stop students applying for the study in the UK mainly lie in these aspects: different HE systems between the UK and other countries, such as China; less information for the application procedures; worries for the study in English for those non-native speakers; and expensive international tuition fees. The hybrid incentives have been proposed by the efforts from the institutions, stuffs, and students themselves. For example, excellent students from top universities would join us based on the abroad exchange programs or ‘2+2 programme’ with discount tuition. They are potential PhD candidates in the further study in the UK. Diversity promotions are implemented to share information and answer queries for potential students and their guardians. Face to face presentations, workshops, and seminars deliver chances for students to admire teaching and learning in the UK, and give students direct answers for their confusions. WeChat official account and Twitter as the online information platform are set up to post messages of recruitment, the guidance for the application procedures, and international collaboration in teaching and research as well. Students who are studying in the UK and the alumni would share their experiences in the study and lives in the UK and their careers after obtaining the HE degree would play as a positive stimulus to our potential students. Short term modules in the UK with exchangeable credits in summer holidays would give abroad students firsthand experiences of the study in the reputable schools with excellent academics, different cultures and the network with international students. Successful cases at the University of Manchester illustrated the effectiveness of these presented methodologies.

Keywords: abroad students, degree study, high education, hybrid incentives

Procedia PDF Downloads 164

Authors: Alicia Greenbank, Efrat Bengio

Abstract:

The aim of this research was to examine the efficacy of the first course in Israel, whose objective is to train student teachers in the special education department to work cooperatively with parents of children with special needs. Studies often highlight the importance of cooperation between teachers and parents of students with special needs. Israel’s Special Education Law defines parents as complete partners, and the Ministry of Education encourages and even requires that partnership be present. Yet this partnership is difficult to achieve many kindergarten teachers, and teachers have a lot of difficulties establishing and managing a pattern of cooperation with their students’ parents. Often we see different perspectives on the child's development and needs, distrust, lack of appreciation, and communication difficulties on both sides – parents & teachers. The course describes a method of instilling the need for cooperation at an early stage of teacher training-in the teacher training program. 22 students in the special education program for early childhood education in the fourth year of learning took part in the course. The fourth-year is the experiential training year and the first time that students have worked in a school. The course consisted of 14 sessions. Seven parents of students with different disabilities participated at 6 of the sessions. The changes in the students' attitudes towards partnership and their ability to manage this partnership were carried out by examining the reports written by the students before the meetings with the parents and the reflections they wrote after each meeting with the parents and at the end of the course. Three themes emerged from the narrative analysis, corresponding to the three preconditions for joint activities with parents — Approach, Attitude, Appropriate Atmosphere, according to the Four A’s Model. The findings showed that a course combining meetings with parents of children with special needs offers many benefits for teacher training. The course raised student awareness of the question partnership, changed students’ approaches and attitudes towards the parents, stressed the importance of partnership, and provided students with tools for working with parents through the school. Based on the findings of this study, courses in this format can be applied in order to cooperate between teachers and parents, for example, parents of gifted children with special needs.

Keywords: Partnership with parents in special education, parents of children with disabilities, parents of children with special needs, parents’ involvement in special education

Procedia PDF Downloads 187

Authors: Peifang Hsieh

Abstract:

The prevention of child abuse has aroused serious concerns in Taiwan because of the disparity between the increasing amount of reported child abuse cases that doubled over the past decade and the scarcity of social workers. New Taipei city, with the most population in Taiwan and over 70% of its 4 million citizens are migrant families in which the needs of children can be easily neglected due to insufficient support from relatives and communities, sees urgency for a social support system, by preemptively identifying and outreaching high-risk families of child abuse, so as to offer timely assistance and preventive measure to safeguard the welfare of the children. Big data analysis is the inspiration. As it was clear that high-risk families of child abuse have certain characteristics in common, New Taipei city decides to consolidate detailed background information data from departments of social affairs, education, labor, and health (for example considering status of parents’ employment, health, and if they are imprisoned, fugitives or under substance abuse), to cross-reference for accurate and prompt identification of the high-risk families in need. 'The Service Center for High-Risk Families' (SCHF) was established to integrate data cross-departmentally. By utilizing the machine learning 'random forest method' to build a risk prediction model which can early detect families that may very likely to have child abuse occurrence, the SCHF marks high-risk families red, yellow, or green to indicate the urgency for intervention, so as to those families concerned can be provided timely services. The accuracy and recall rates of the above model were 80% and 65%. This prediction model can not only improve the child abuse prevention process by helping social workers differentiate the risk level of newly reported cases, which may further reduce their major workload significantly but also can be referenced for future policy-making.

Keywords: child abuse, high-risk families, big data analysis, risk prediction model

Procedia PDF Downloads 133

Authors: Mohamad Khairi Haji Othman, Mohd Zailani Mohd Yusoff, Rozalina Khalid

Abstract:

The inculcation of noble values in teaching and learning is very important, especially to build students with good characters and values. Therefore, the purpose of this research is to identify the challenges of implementing the inculcation of noble values in teaching in primary schools. This study was conducted at four North Zone Peninsular Malaysia schools. This study was used a qualitative approach in the form of case studies. The qualitative approach aims at gaining meaning and a deep understanding of the phenomenon studied from the perspectives of the study participants and not intended to make the generalization. The sample in this study consists of eight teachers who teach in four types of schools that have been chosen purposively. The method of data collection is through semi-structured interviews used in this study. The comparative method is continuously used in this study to analyze the primary data collected. The study found that the main challenges faced by teachers were students' problems and class control so that teachers felt difficult to the inculcation of noble values in teaching. In addition, the language challenge is difficult for students to understand. Similarly, peers are also challenging because students are more easily influenced by friends rather than listening to teachers' instructions. The last challenge was the influence of technology and mass media electronic more widespread. The findings suggest that teachers need to innovate in order to assist the school in inculcating religious and moral education towards the students. The school through guidance and counseling teachers can also plan some activities that are appropriate to the student's present condition. Through this study, teachers and the school should work together to develop the values of students in line with the needs of the National Education Philosophy that wishes to produce intelligent, emotional, spiritual, intellectual and social human capital.

Keywords: challenges, implementation, inculcation, noble values

Procedia PDF Downloads 183

Authors: Shivahari Revathi Venkateswaran

Abstract:

Segmenting customers plays a significant role in churn prediction. It helps the marketing team with proactive and reactive customer retention. For the reactive retention, the retention team reaches out to customers who already showed intent to disconnect by giving some special offers. When coming to proactive retention, the marketing team uses churn prediction model, which ranks each customer from rank 1 to 100, where 1 being more risk to churn/disconnect (high ranks have high propensity to churn). The churn prediction model is built by using XGBoost model. However, with the churn rank, the marketing team can only reach out to the customers based on their individual ranks. To profile different groups of customers and to frame different marketing strategies for targeted groups of customers are not possible with the churn ranks. For this, the customers must be grouped in different segments based on their profiles, like demographics and other non-controllable attributes. This helps the marketing team to frame different offer groups for the targeted audience and prevent them from disconnecting (proactive retention). For segmentation, machine learning approaches like k-mean clustering will not form unique customer segments that have customers with same attributes. This paper finds an alternate approach to find all the combination of unique segments that can be formed from the user attributes and then finds the segments who have uplift (churn rate higher than the baseline churn rate). For this, search algorithms like fast search and recursive search are used. Further, for each segment, all customers can be targeted using individual churn ranks from the churn prediction model. Finally, a UI (User Interface) is developed for the marketing team to interactively search for the meaningful segments that are formed and target the right set of audience for future marketing campaigns and prevent them from disconnecting.

Keywords: churn prediction modeling, XGBoost model, uplift segments, proactive marketing, search algorithms, retention, k-mean clustering

Procedia PDF Downloads 70

Authors: Ali̇ Bayram, Semih Dalkilic, Remzi Yigiter

Abstract:

N-methyl-D-aspartate (NMDA) receptor is a subtype of glutamate receptor and plays a pivotal role in learning, memory, neuronal plasticity, neurotoxicity and synaptic mechanisms. Animal experiments were suggested that glutamate-induced excitotoxic injuriy and NMDA receptor blockage lead to amnesia and other neurodegenerative diseases including Alzheimer’s disease (AD), Huntington’s disease, amyotrophic lateral sclerosis. Aim of this study is to investigate association between NMDA receptor coding gene GRIN2B expression level and Alzheimer disease. The study was approved by the local ethics committees, and it was conducted according to the principles of the Declaration of Helsinki and guidelines for the Good Clinical Practice. Peripheral blood was collected 50 patients who diagnosed AD and 49 healthy control individuals. Total RNA was isolated with RNeasy midi kit (Qiagen) according to manufacturer’s instructions. After checked RNA quality and quantity with spectrophotometer, GRIN2B expression levels were detected by quantitative real time PCR (QRT-PCR). Statistical analyses were performed, variance between two groups were compared with Mann Whitney U test in GraphpadInstat algorithm with 95 % confidence interval and p < 0.05. After statistical analyses, we have determined that GRIN2B expression levels were down regulated in AD patients group with respect to control group. But expression level of this gene in each group was showed high variability. İn this study, we have determined that NMDA receptor coding gene GRIN2B expression level was down regulated in AD patients when compared with healthy control individuals. According to our results, we have speculated that GRIN2B expression level was associated with AD. But it is necessary to validate these results with bigger sample size.

Keywords: Alzheimer’s disease, N-methyl-d-aspartate receptor, NR2B, GRIN2B, mRNA expression, RT-PCR

Procedia PDF Downloads 393

Authors: Cajethan U. Ugwuoke

Abstract:

Agriculture is taught in secondary schools to develop skills in students which will empower them to contribute to national economic development. Unfortunately, our educational system emphasizes the application of conventional teaching methods in delivering instructions, which fails to produce students competent enough to carry out agricultural production. This study was therefore aimed at examining the application of digital technologies as tools for transformative instructional delivery. Four specific purposes, research questions and hypotheses guided the study. The study adopted a descriptive survey research design where 80 subjects representing 64 teachers of agriculture and 16 principals in the Udenu local government area of Enugu State, Nigeria, participated in the study. A structured questionnaire was used to collect data. The assumption of normality was ascertained by subjecting the data collected to a normality test. Data collected were later subjected to mean, Pearson product-moment correlation, ANOVA and t-test to answer the research questions and test the hypotheses at a 5% significant level. The result shows that the application of digital technologies helps to reduce learners’ boredom (3.52.75), improves learners’ performance (3.63.51), and is used as a visual aid for learners (3.56.61), among others. There was a positive, strong and significant relationship between the application of digital technologies and effective instructional delivery (+.895, p=.001<.05, F=17.73), competency of teachers to the application of digital technologies and effective instructional delivery (+998, p=.001<0.5, F=16263.45), and frequency of the application of digital technologies and effective instructional delivery (+.999, p=.001<.05, F=31436.14). There was no evidence of autocorrelation and multicollinearity in the regression models between the application of digital technologies and effective instructional delivery (2.03, Tolerance=1.00, VIF=1.00), competency of teachers in the application of digital technologies and effective instructional delivery (2.38, Tolerance=1.00, VIF=1.00) and frequency of the application of digital technologies and effective instructional delivery (2.00, Tolerance=1.00, VIF=1.00). Digital technologies should be therefore applied in teaching to facilitate effective instructional delivery in agriculture.

Keywords: agricultural science, digital technologies, instructional delivery, learning

Procedia PDF Downloads 70

Authors: Amir Shahab Shahabi, Mohsen Hasirian

Abstract:

Modern societies, marked by expansive Internet connectivity and the rise of e-commerce, are now integrated with digital platforms at an unprecedented level. The efficiency, speed, and accessibility of e-commerce have garnered a substantial consumer base. Against this backdrop, electronic banking has undergone rapid proliferation within the realm of online activities. However, this growth has inadvertently given rise to an environment conducive to illicit activities, notably electronic payment fraud, posing a formidable challenge to the domain of electronic banking. A pivotal role in upholding the integrity of electronic commerce and business transactions is played by electronic fraud detection, particularly in the context of credit cards which underscores the imperative of comprehensive research in this field. To this end, our study introduces an Attentional Bi-Stream Sequence Learner (AttBiSeL) framework that leverages attention mechanisms and recurrent networks. By incorporating bidirectional recurrent layers, specifically bidirectional Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) layers, the proposed model adeptly extracts past and future transaction sequences while accounting for the temporal flow of information in both directions. Moreover, the integration of an attention mechanism accentuates specific transactions to varying degrees, as manifested in the output of the recurrent networks. The effectiveness of the proposed approach in automatic credit card fraud classification is evaluated on the European Cardholders' Fraud Dataset. Empirical results validate that the hybrid architectural paradigm presented in this study yields enhanced accuracy compared to previous studies.

Keywords: credit card fraud, deep learning, attention mechanism, recurrent neural networks

Procedia PDF Downloads 7

Authors: Guolong Zhong, Venkatesh Chennam Vijay, Ilias Oraifige

Abstract:

In the last 20 years, Knowledge Based Engineering (KBE) has shown its advantages in product development in different engineering areas such as automation, mechanical, civil and aerospace engineering in terms of digital design automation and cost reduction by automating repetitive design tasks through capturing, integrating, utilising and reusing the existing knowledge required in various aspects of the product design. However, in primary design stages, the descriptive information of a product is discrete and unorganized while knowledge is in various forms instead of pure data. Thus, it is crucial to have an integrated product model which can represent the entire product information and its associated knowledge at the beginning of the product design. One of the shortcomings of the existing product models is a lack of required knowledge representation in various aspects of product design and its mapping to an interoperable schema. To overcome the limitation of the existing product model and methodologies, two key factors are considered. First, the product model must have well-defined classes that can represent the entire product information and its associated knowledge. Second, the product model needs to be represented in an interoperable schema to ensure a steady data exchange between different product modelling platforms and CAD software. This paper introduced a method to provide a general product model as a generative representation of a product, which consists of the geometry information and non-geometry information, through a product modelling framework. The proposed method for capturing the knowledge from the designers through a knowledge file provides a simple and efficient way of collecting and transferring knowledge. Further, the knowledge schema provides a clear view and format on the data that needed to be gathered in order to achieve a unified knowledge exchange between different platforms. This study used a game-based platform to make product modelling environment accessible for non-engineers. Further the paper goes on to test use case based on the proposed game-based product modelling environment to validate the effectiveness among non-engineers.

Keywords: game-based learning, knowledge based engineering, product modelling, design automation

Procedia PDF Downloads 153

Authors: Aschalew Cherie Workneh, K. S. Hari Prasad, Chandra Shekhar Prasad Ojha

Abstract:

Due to the increase in water scarcity, the crop water stress index (CWSI) is receiving significant attention these days, especially in arid and semiarid regions, for quantifying water stress and effective irrigation scheduling. Nowadays, machine learning techniques such as neural networks are being widely used to determine CWSI. In the present study, the performance of two artificial neural networks, namely, Self-Organizing Maps (SOM) and Feed Forward-Back Propagation Artificial Neural Networks (FF-BP-ANN), are compared while determining the CWSI of rice crop. Irrigation field experiments with varying degrees of irrigation were conducted at the irrigation field laboratory of the Indian Institute of Technology, Roorkee, during the growing season of the rice crop. The CWSI of rice was computed empirically by measuring key meteorological variables (relative humidity, air temperature, wind speed, and canopy temperature) and crop parameters (crop height and root depth). The empirically computed CWSI was compared with SOM and FF-BP-ANN predicted CWSI. The upper and lower CWSI baselines are computed using multiple regression analysis. The regression analysis showed that the lower CWSI baseline for rice is a function of crop height (h), air vapor pressure deficit (AVPD), and wind speed (u), whereas the upper CWSI baseline is a function of crop height (h) and wind speed (u). The performance of SOM and FF-BP-ANN were compared by computing Nash-Sutcliffe efficiency (NSE), index of agreement (d), root mean squared error (RMSE), and coefficient of correlation (R²). It is found that FF-BP-ANN performs better than SOM while predicting the CWSI of rice crops.

Keywords: artificial neural networks; crop water stress index; canopy temperature, prediction capability

Procedia PDF Downloads 116

Authors: Dmytro Zubov, Francesco Volponi

Abstract:

In this paper, D-Wave quantum computing Ising model is used for the forecasting of positive extremes of daily mean air temperature. Forecast models are designed with two to five qubits, which represent 2-, 3-, 4-, and 5-day historical data respectively. Ising model’s real-valued weights and dimensionless coefficients are calculated using daily mean air temperatures from 119 places around the world, as well as sea level (Aburatsu, Japan). In comparison with current methods, this approach is better suited to predict heat wave values because it does not require the estimation of a probability distribution from scarce observations. Proposed forecast quantum computing algorithm is simulated based on traditional computer architecture and combinatorial optimization of Ising model parameters for the Ronald Reagan Washington National Airport dataset with 1-day lead-time on learning sample (1975-2010 yr). Analysis of the forecast accuracy (ratio of successful predictions to total number of predictions) on the validation sample (2011-2014 yr) shows that Ising model with three qubits has 100 % accuracy, which is quite significant as compared to other methods. However, number of identified heat waves is small (only one out of nineteen in this case). Other models with 2, 4, and 5 qubits have 20 %, 3.8 %, and 3.8 % accuracy respectively. Presented three-qubit forecast model is applied for prediction of heat waves at other five locations: Aurel Vlaicu, Romania – accuracy is 28.6 %; Bratislava, Slovakia – accuracy is 21.7 %; Brussels, Belgium – accuracy is 33.3 %; Sofia, Bulgaria – accuracy is 50 %; Akhisar, Turkey – accuracy is 21.4 %. These predictions are not ideal, but not zeros. They can be used independently or together with other predictions generated by different method(s). The loss of human life, as well as environmental, economic, and material damage, from extreme air temperatures could be reduced if some of heat waves are predicted. Even a small success rate implies a large socio-economic benefit.

Keywords: heat wave, D-wave, forecast, Ising model, quantum computing

Procedia PDF Downloads 495

Authors: J. Van der Walt, N. A. Plastow, M. Unger

Abstract:

Gross and fine motor skill difficulties among children affect their ability to learn and progress in school. Research indicates that children in low socio-economic areas are at a higher risk of motor skill difficulties, while therapy resources are limited. The Hopscotch motor skill programme is a well-researched accessible in-school intervention developed by occupational and physiotherapists through complex intervention development. The development stage of the complex intervention development model firstly included a prevalence study in a low-resourced area in the West Coast of South Africa, indicating a high prevalence with significant motor skill difficulties among pre-school children at 14.5% with fine motor skill difficulties at 24.6%. A scoping review identifies motor skill interventions for pre-school children and a proposed a framework of fundamental concepts to consider when developing a motor skill intervention. a Delphi-study considered the framework and encouraged collaboration between therapists and educators to make the programme accessible, resource and cost effective, specifically geared towards a rural, low resourced area. The results from the Delphi study, together with the proposed framework from the scoping review was used to develop the Hopscotch programme, adopting a task-shifting approach. The eight-week small-group programme is facilitated by teachers with the support of therapists. The programme aims to improve the motor skills of pre-school aged children with motor skill difficulties to promote academic readiness through obstacle courses, ball skill games and fine motor games and crafts. A randomised controlled trial is planned as a next stage to determine the preliminary effect of the programme on the motor and early academic skills of pre-school children.

Keywords: accesible learning, motor skill intervention, school readiness, task shifting

Procedia PDF Downloads 194