Search results for: evolving learning

Authors: Nigel P. Coutts, Stellina Z. Sim

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Research suggests that the pedagogy we utilize when teaching mathematics contributes to a negative attitude towards the discipline. Worried by this, we have explored teaching mathematics for understanding, fluency, and confidence. We investigated strategies to engage students with the beauty of mathematics, moving them beyond mimicry and memorization. The result is an integrated pedagogy and curriculum arrangement which combines concept-based mathematics with Number Talks, Visible Thinking Routines, and Teaching for Understanding. Our qualitative research shows that students self-report greater self-confidence and heightened engagement with mathematical thinking. Teacher reflections on student learning echo this finding. As a result of this, we advocate for teacher training in the implementation of a concept-based curriculum supplemented with Number Talk strategies.

Keywords: mathematical thinking, teaching for understanding, student confidence, concept-based learning, engagement

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Authors: Bethany Wood

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The world pandemic led to a change in the way social media was used by audiences, with young people spending more hours on the platform due to lockdown. Reports by Ofcom have demonstrated that the internet is the second most popular platform for accessing news after television in the UK with social media and the internet ranked as the most popular platform to access news for those aged between 16-24. These statistics are unsurprising considering that at the time of writing, 98 percent of Generation Z (Gen Z) owned a smartphone and the subsequent ease and accessibility of social media. Technology is constantly developing and with this, its importance is becoming more prevalent with each generation: the Baby Boomers (1946-1964) consider it something useful whereas millennials (1981-1997) believe it a necessity for day to day living. Gen Z, otherwise known as the digital native, have grown up with this technology at their fingertips and social media is a norm. It helps form their identity, their affiliations and opens gateways for them to engage with news in a new way. It is a common misconception that Gen Z do not consume news, they are simply doing so in a different way to their predecessors. Using a sample of 800 18-20 year olds whilst utilising Generational theory, Actor Network Theory and the Social Shaping of Technology, this research provides a critical analyse regarding how Gen Z’s news consumption and engagement habits are developing along with technology to sculpture the future format of news and its distribution. From that perspective, allied with the empirical approach, it is possible to provide research orientated advice for the industry and even help to redefine traditional concepts of journalism.

Keywords: journalism, generation z, digital, social media

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Authors: Mounir Kehal, Adel Al Araifi

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The post-globalisation epoch has placed businesses everywhere in new and different competitive situations where knowledgeable, effective and efficient behaviour has come to provide the competitive and comparative edge. Enterprises have turned to explicit- and even conceptualising on tacit- Knowledge Management to elaborate a systematic approach to develop and sustain the Intellectual Capital needed to succeed. To be able to do that, you have to be able to visualize your organization as consisting of nothing but knowledge and knowledge flows, whilst being presented in a graphical and visual framework, referred to as automated organizational cartography. Hence, creating the ability of further actively classifying existing organizational content evolving from and within data feeds, in an algorithmic manner, potentially giving insightful schemes and dynamics by which organizational know-how is visualised. It is discussed and elaborated on most recent and applicable definitions and classifications of knowledge management, representing a wide range of views from mechanistic (systematic, data driven) to a more socially (psychologically, cognitive/metadata driven) orientated. More elaborate continuum models, for knowledge acquisition and reasoning purposes, are being used for effectively representing the domain of information that an end user may contain in their decision making process for utilization of available organizational intellectual resources (i.e. Autocart). In this paper we present likewise an empirical research study conducted previously to try and explore knowledge diffusion in a specialist knowledge domain.

Keywords: knowledge management, knowledge maps, knowledge diffusion, organizational cartography

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Authors: Mamadou Dione, Eric Matzner-lober, Philippe Alexandre

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The Energy Transition Act defined by the French State has precise implications on Renewable Energies, in particular on its remuneration mechanism. Until then, a purchase obligation contract permitted the sale of wind-generated electricity at a fixed rate. Tomorrow, it will be necessary to sell this electricity on the Market (at variable rates) before obtaining additional compensation intended to reduce the risk. This sale on the market requires to announce in advance (about 48 hours before) the production that will be delivered on the network, so to be able to predict (in the short term) this production. The fundamental problem remains the variability of the Wind accentuated by the geographical situation. The objective of the project is to provide, every day, short-term forecasts (48-hour horizon) of wind production using weather data. The predictions of the GFS model and those of the ECMWF model are used as explanatory variables. The variable to be predicted is the production of a wind farm. We do two approaches: a direct approach that predicts wind generation directly from weather data, and an integrated approach that estimâtes wind from weather data and converts it into wind power by power curves. We used machine learning techniques to predict this production. The models tested are random forests, CART + Bagging, CART + Boosting, SVM (Support Vector Machine). The application is made on a wind farm of 22MW (11 wind turbines) of the Compagnie du Vent (that became Engie Green France). Our results are very conclusive compared to the literature.

Keywords: forecast aggregation, machine learning, spatio-temporal dynamics modeling, wind power forcast

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Authors: Bichi Muktar Sani

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The philosophy of Physical and Health Education is to develop academic and professional competency which will enable individuals earn a living and render unique services to the society and also provide good basis of knowledge and experience that characterize an educated and fully developed person through physical activities. With the increase of sedentary activities such as watching television, playing videogames, increased computer technology, automation and reduction of high school Physical and Health Education schedules, young people are most likely to become overweight, and less fit. Physical Education is a systematic instruction in sports, training, practice, gymnastics, exercises, and hygiene given as part of a school or college program. Physical and Health Education is the study, practice, and appreciation of the art and science of human movement. Physical and Health Education is course in the curricula that utilizes the learning in the cognitive, affective, and psychomotor domains in a lay or movement exploration setting. The paper made some recommendations on the way forward.

Keywords: issues, challenges, physical education, school

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Authors: Yuxi Zhu, Zhenqian Chen

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It is of great interest to investigate the thermal properties of non-precious metal catalysts for Proton exchange membrane fuel cell (PEMFC) based on the thermal management requirements. Due to the low symmetry of materials, to accurately obtain the thermal conductivity of materials, it is necessary to obtain the second and third order force constants by combining density functional theory and machine learning interatomic potential. To be specific, the interatomic force constants are obtained by moment tensor potential (MTP), which is trained by the computational trajectory of Ab initio molecular dynamics (AIMD) at 50, 300, 600, and 900 K for 1 ps each, with a time step of 1 fs in the AIMD computation. And then the thermal conductivity can be obtained by solving the Boltzmann transport equation. In this paper, the thermal transport properties of single metal atom catalysts are studied for the first time to our best knowledge by machine-learning interatomic potential (MLIP). Results show that the single metal atom catalysts exhibit anisotropic thermal conductivities and partially exhibit good thermal conductivity. The average lattice thermal conductivities of G-FeN₄, G-CoN₄ and G-NiN₄ at 300 K are 88.61 W/mK, 205.32 W/mK and 210.57 W/mK, respectively. While other single metal atom catalysts show low thermal conductivity due to their low phonon lifetime. The results also show that low-frequency phonons (0-10 THz) dominate thermal transport properties. The results provide theoretical insights into the application of single metal atom catalysts in thermal management.

Keywords: proton exchange membrane fuel cell, single metal atom catalysts, density functional theory, thermal conductivity, machine-learning interatomic potential

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Authors: Hualter Oliveira Barbosa, Raquel Feitosa do Vale Cunha, Erika Muniz dos Santos, Fernanda Belmira Souza, Fabio Sousa, Luis Henrique Pascareli, Franciney de Oliveira Lima, Ana Cláudia Reis da Silva, Christiane Moreira de Almeida

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Software development is intrinsic human-based knowledge-intensive. Due to globalization, software development has become a complex challenge and we usually face barriers related to knowledge management, team building, costly testing processes, especially in distributed settings. For this reason, several approaches have been proposed to minimize barriers caused by geographic distance. In this paper, we present as we use experimental studies to improve our knowledge management process using the Wiki system. According to the results, it was possible to identify learning preferences from our software projects leader team, organize and improve the learning experience of our Wiki and; facilitate collaboration by newcomers to improve Wiki with new contents available in the Wiki.

Keywords: mobile product, knowledge transfer, knowledge management process, wiki, GSD

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Authors: Svetlana Polskaya

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The study deals with the issue of using the Content and Language Integrated Learning (CLIL) concept when teaching Master Program students majoring in neuromarketing and entrepreneurship. Present-day employers expect young graduates to conduct professional communication with their English-speaking peers and demonstrate proper knowledge of the industry’s terminology and jargon. The idea of applying CLIL was the result of the above-mentioned students possessing high proficiency in English, thus, not requiring any further knowledge of the English language in terms of traditional grammar or lexis. Due to this situation, a CLIL-type program was devised, allowing learners to acquire new knowledge of entrepreneurship and neuromarketing spheres combined with simultaneous honing their English language practical usage. The case study analyzes CLIL application within this particular program as well as the experience accumulated in the process.

Keywords: CLIL, entrepreneurship, neuromarketing, foreign language acquisition, proficiency level

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Authors: Dachuan Shi, M. Hecht, Y. Ye

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With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

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Authors: Natcha Wattanaprapa, Alongkorn Taengtong, Phachaya Chaiwchan

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This study investigates and promotes the distribution of community enterprise products of Samut Songkhram province by using e-commerce web technology to help distribute the products. This study also aims to develop the information system to be able to operate on multiple platforms and promote the easy usability on smartphones to increase the efficiency and promote the distribution of community enterprise products of Samut Songkhram province in three areas including Baan Saraphi learning center, the learning center of Bang Noi Floating market as well as Bang Nang Li learning center. The main structure consists of spreading the knowledge regarding the tourist attraction in the area of community enterprise, e-commerce system of community enterprise products, and Chatbot. The researcher developed the system into an application form using the software package to create and manage the content on the internet. Connect management system (CMS) word press was used for managing web pages. Add-on CMS word press was used for creating the system of Chatbot, and the database of PHP My Admin was used as the database management system. The evaluation by the experts and users in 5 aspects, including the system efficiency, the accuracy in the operation of the system, the convenience and ease of use of the system, the design, and the promotion of product distribution in Samut Songkhram province by using questionnaires revealed that the result of evaluation in the promotion of product distribution in Samut Songkhram province was the highest with the mean of 4.20. When evaluating the efficiency of the developed system, it was found that the result of system efficiency was the highest level with a mean of 4.10.

Keywords: community enterprise, digital commerce, promotion of product distribution, Samut Songkhram province

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Authors: M. Dimitri, M. Ricci, F. Bigi, M. Romiti, A. Corvi

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Tissue engineering has reached a significant milestone with the integration of 3D printing for the creation of complex bioconstructs equipped with vascular networks, crucial for cell maintenance and growth. This study aims to demonstrate the effectiveness of a portable microperfusion system designed to adapt dynamically to the evolving conditions of cell growth within 3D-printed bioconstructs. The microperfusion system was developed to provide a constant and controlled flow of nutrients and oxygen through the integrated vessels in the bioconstruct, replicating in vivo physiological conditions. Through a series of preliminary experiments, we evaluated the system's ability to maintain a favorable environment for cell proliferation and differentiation. Measurements of cell density and viability were performed to monitor the health and functionality of the tissue over time. Preliminary results indicate that the portable microperfusion system not only supports but optimizes cell growth, effectively adapting to changes in metabolic needs during the bioconstruct maturation process. This research opens perspectives in tissue engineering, demonstrating that a portable microperfusion system can be successfully integrated into 3D-printed bioconstructs, promoting sustainable and uniform cell growth. The implications of this study are far-reaching, with potential applications in regenerative medicine and pharmacological research, providing a platform for the development of functional and complex tissues.

Keywords: biofabrication, microfluidic perfusion system, 4D bioprinting

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Authors: Shantanu Vyas, Neerja Meena

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Facial infiltrating lipomatosis is a rare lipomatous lesion, first described by Slavin in 1983. It is a benign pseudotumor pathology. It corresponds to a non-encapsulated collection of mature adipocytes infiltrating the local tissue and hyperplasia of underlying bone leading to a craniofacial deformity. Very few cases have been reported in the literature. We report the case of a 19-year-old female patient, who was consulted for a swelling of the right hemiface progressively evolving since birth. Physical examination revealed facial asymmetry. On palpation, the mass was soft, painless, not compressible, not pulsatile, not fluctuating. In view of the asymptomatic nature and slow progression of the lesion, a lipomatous tumour, namely lipoma, was suggested. CT scan image shows a hyperplastic subcutaneous fat on the right hemiface. On the right jugal and temporal areas, there is a subcutaneous formation of fatty density, poorly limited, with no detectable peripheral capsule. It merges with the adjacent fat. In the bone window, there was a hyperplasia of underlying bone. Facial lipomatosis infiltration of the face is a benign pseudotumor pathology. As a result, it can be confused with other disorders, in particular, hemifacial hyperplasia. Combination of physical and radiological findings can establish the diagnosis. Surgical treatment is done for cosmetic purposes.

Keywords: cosmetic correction and facial assemetry, aesthetic results, facial infiltration, surgery

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Authors: Azusa Katsumata

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Several universities in Japan 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 excursion focusing Various Problems of Society, as second year career education course, Students will learn about contraception, infertility, homeless people, LGBT, and they will discuss based on the excursion. This paper aims to study the ‘learning platform’ created by a series of processes such as the excursion, the discussion, and the presentation. In this course, students looked back on their lives and imagined the future in concrete terms, performing tasks in groups. The students came across a range of values through lectures and conversations, thereby developing feelings of self-efficacy. We conducted a questionnaire to measure the development of career in class. From the results of the questionnaire, we can see, in the example of this class, that students respected diversity and understood the importance of uncertainty and discontinuity. Whereas the students developed career awareness, they actually did not come across that scene and would do so only in the future when it became necessary. In this class, students consciously considered social problems, but did not develop the practical skills necessary to deal with these. This is appropriate for one of project, but we need to consider how this can be incorporated into future courses. University constitutes only a single period in life-long career formation. Thus, further research may be indicated to determine whether the positive effects of career education at university continue to contribute to individual careers going forward.

Keywords: career education of university, excursion, learning platform, problems of society

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Authors: Michael Louis Sunaris, Robby Yussac Tallar

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The concept of sustainable river is evolving in Indonesia today. Many rivers condition in Indonesia have decreased by quality and quantity. The degradation of this condition is caused by rapid land use change as a result of increased population growth and human activity. It brings the degradation of the existing watersheds including some types of land use that an important factor in determining the status of river sustainability. Therefore, an evaluation method is required to determine the sustainability status of waterbody within watershed. The purpose of this study is to analyze various types of land use in determining the status of river sustainability. This study takes the watersheds of Citarum Upstream as a study area. The results of the analysis prove the index of sustainability status of the river that changes from good to bad or average in the rivers in the study area. The rapid and uncontrolled changes of land use especially in the upper watersheds area are the main causes that happened over time. It was indicated that the cumulative runoff coefficients were increased significantly. These situations indicated that the damage of watersheds has an impact on the water surplus or deficit problem yearly. Therefore, the rivers in Indonesia should be protected and conserved. The sustainability index of the rivers is an index to indicate the condition of watersheds by defining status of rivers in order to achieve sustainable water resource management.

Keywords: land use change, runoff coefficient, a simple index, sustainable river

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Authors: E. Maoz

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Background: As a teaching method, project-based learning is strongly linked to developing students’ critical thinking skills. It combines creative independent thinking, team work, and disciplinary subject-field integration. In the 'Introduction to Nursing Research Methods' course (year 3, Generic Track), project based learning is used to teach the topic of 'Evidence-Based Nursing'. This topic examines a clinical care issue encountered by students in the field. At the end of their project, students present proposals for managing the said issue. Proposals are the product of independent integrative thinking integrating a wide range of factors influencing the issue’s management. Method: Papers by 27 groups of students (165 students) were content analyzed to identify which themes emerged from the students' recommendations for managing the clinical issue. Findings: Five main themes emerged—current management approach; adapting procedures in line with current recent research recommendations; training for change (veteran nursing staff, beginner students, patients, significant others); analysis of 'economic benefit vs. patient benefit'; multidisciplinary team engagement in implementing change in practice. Two surprising themes also emerged: advertising and marketing using new technologies, which reflects how the new generation thinks. Summary and Recommendations: Among the main challenges in nursing education is training nursing graduates to think independently, integratively, and critically. Combining PBL with classical teaching methods stimulates students cognitively while opening new vistas with implications on all levels of the profession: management, research, education, and practice. Advanced students can successfully grasp and interpret the current state of clinical practice. They are competent and open to leading change and able to consider the diverse factors and interconnections that characterize the nurse's work.

Keywords: evidence based nursing, critical thinking skills, project based learning, students education

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Authors: Roslina Ibrahim, Azizah Jaafar, Khalili Khalil

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Educational games (EG) are regarded as a promising teaching and learning tool for the new generation. Growing number of studies and literatures can be found in EG studies. Both academic researchers and commercial developers come out with various educational games prototypes and titles. Despite that, acceptance of educational games still lacks among the students. It is important to understanding students’ perceptions of EG, since they are the main stakeholder of the technology. Thus, this study seeks to understand perceptions of undergraduates’ students using a framework originated from user acceptance theory. The framework consists of six constructs with twenty-eight items. Data collection was done on 180 undergraduate students of Universiti Teknologi Malaysia, Kuala Lumpur using self-developed online EG called ROBO-C. Data analysis was done using descriptive, factor analysis and correlations. Performance expectancy, effort expectancy, attitude, and enjoyment factors were found significantly correlated with the intention to use EG. This study provides more understanding towards the use of educational games among students.

Keywords: educational games, perceptions, acceptance, UTAUT

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Authors: Bliss Singhal

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Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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Authors: Paula Andrea Segura Delgado, Martha Helena Ramírez-Bahena

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Research on how the brain learns has a transcendental application in the educational context. It is crucial for teacher training to understand the nature of brain changes and their direct influence on learning processes. This communication is based on a literature review focused on neuroscience, neuroeducation, and the impact of digital technology on the human brain. Information was gathered from both English and Spanish language sources, using online journals, books and reports. The general objective was to analyze the role of neuroscience knowledge in enriching our understanding of the learning process. In fact, the authors have focused on the impact of digital technology on the human brain as well as its influence in the field of education..Neuroscience knowledge can contribute significantly to improving the training of educators and therefore educational practices. Education as an instrument of change and school as an agent of socialization, it is necessary to understand what it aims to transform: the human brain. Understanding the functioning of the human brain has important repercussions on education: this elucidates cognitive skills, psychological processes and elements that influence the learning process (memory, executive functions, emotions and the circadian cycle); helps identify psychological and neurological deficits that can impede learning processes (dyslexia, autism, hyperactivity); It allows creating environments that promote brain development and contribute to the advancement of brain capabilities in alignment with the stages of neurobiological development. The digital age presents diverse opportunities to every social environment. The frequent use of digital technology (DT) has had a significant and abrupt impact on both the cognitive abilities and physico-chemical properties of the brain, significantly influencing educational processes. Hence, educational community, with the insights from advances in neuroscience, aspire to identify the positive and negative effects of digital technology on the human brain. This knowledge helps ensure the alignment of teacher training and practices with these findings. The knowledge of neuroscience enables teachers to develop teaching methods that are aligned with the way the brain works. For example, neuroscience research has shown that digital technology is having a significant impact on the human brain (addition, anxiety, high levels of dopamine, circadian cycle disorder, decrease in attention, memory, concentration, problems with their social relationships). Therefore, it is important to understand the nature of these changes, their impact on the learning process, and how educators should effectively adapt their approaches based on these brain's changes.

Keywords: digital technology, learn process, neuroscience knowledge, neuroeducation, training proffesors

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Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

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In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

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Authors: Phalaunnnaphat Siriwongs

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The classroom of the 21st century is an ever changing forum for new and innovative thoughts and ideas. With increasing technology and opportunity, students have rapid access to information that only decades ago would have taken weeks to obtain. Unfortunately, new techniques and technology are not the cure for the fundamental problems that have plagued the classroom ever since education was established. Class size has been an issue long debated in academia. While it is difficult to pin point an exact number, it is clear that in this case more does not mean better. By looking into the success and pitfalls of classroom size the true advantages of smaller classes will become clear. Previously, one class was comprised of 50 students. Being seventeen and eighteen- year- old students, sometimes it was quite difficult for them to stay focused. To help them understand and gain much knowledge, a researcher introduced “The Theory of Multiple Intelligence” and this, in fact, enabled students to learn according to their own learning preferences no matter how they were being taught. In this lesson, the researcher designed a cycle of learning activities involving all intelligences so that everyone had equal opportunities to learn.

Keywords: multiple intelligences, role play, performance assessment, formative assessment

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Authors: Derya Yucel, Nigar Angın, Dürdane Mart, Meltem Turkeri, Volkan Catalkaya, Celal Yucel

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Chickpea (Cicer arietinum L.) with high protein content is a vital food, especially in under-developed and developing countries for the people who do not consume enough meat due to low-income level. The objective of the proposed study is to evaluate growing, yield and yield components of chickpea genotypes under Mediterranean condition so determine tolerance of chickpea genotypes against drought and heat stress. For this purpose, a total of 34 chickpea genotypes were used as material. The experiment was conducted according to factorial randomized complete block design with 3 reps at the Eastern Mediterranean Research Institute, Adana, TURKEY for 2014-15 growing season under three different growing conditions (Winter sowing, irrigated-late sowing and non-irrigated- late sowing). According to results of this experiment, vegetative period, flowering time, poding time, maturity time, plant height, height of first pod, seed yield and 100 seed weight were ranged between 68.33 to 78.77 days, 94.22 to 85.00 days, 94.11 to 106.44 days, 198.56 to 214.44 days, 37.18 to 64.89 cm, 18.33 to 34.83 cm, 417.1 to 1746.4 kg/ha and 14.02 to 45.02 g, respectively. Among the chickpea genotypes, the Aksu, Arda, Çakır, F4 09 (X 05 TH 21-16189), FLIP 03-108 were least affected by drought and heat stress. Therefore, these genotypes can be used as sources of drought and heat tolerance in further breeding programme for evolving the drought and heat tolerant genotypes in chickpea.

Keywords: chickpea, drought stress, heat stress, yield

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Authors: Cristina-Maria Păcurar

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The paper presents an original Python-based application that outlines the advantages of combining some elementary notions of mathematics with the study of a programming language. The application support refers to some of the first lessons of analytic geometry, meaning conics and quadrics and their reduction to a standard form, as well as some related notions. The chosen programming language is Python, not only for its closer to an everyday language syntax – and therefore, enhanced readability – but also for its highly reusable code, which is of utmost importance for a mathematician that is accustomed to exploit already known and used problems to solve new ones. The purpose of this paper is, on one hand, to support the idea that one of the most appropriate means to initiate one into programming is throughout mathematics, and reciprocal, one of the most facile and handy ways to assimilate some basic knowledge in the study of mathematics is to apply them in a personal project. On the other hand, besides being a mean of learning both programming and analytic geometry, the application subject to this paper is itself a useful tool for it can be seen as an independent original Python package for analytic geometry.

Keywords: analytic geometry, conics, python, quadrics

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Authors: Ana Paula Soares, Alexandrina Lages, Helena Oliveira, Francisco-Javier Gutiérrez-Domínguez, Marisa Lousada

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From an early age, exposure to a spoken language allows us to implicitly capture the structure underlying the succession of the speech sounds in that language and to segment it into meaningful units (words). Statistical learning (SL), i.e., the ability to pick up patterns in the sensory environment even without intention or consciousness of doing it, is thus assumed to play a central role in the acquisition of the rule-governed aspects of language and possibly to lie behind the language difficulties exhibited by children with development language disorder (DLD). The research conducted so far has, however, led to inconsistent results, which might stem from the behavioral tasks used to test SL. In a classic SL experiment, participants are first exposed to a continuous stream (e.g., syllables) in which, unbeknownst to the participants, stimuli are grouped into triplets that always appear together in the stream (e.g., ‘tokibu’, ‘tipolu’), with no pauses between each other (e.g., ‘tokibutipolugopilatokibu’) and without any information regarding the task or the stimuli. Following exposure, SL is assessed by asking participants to discriminate between triplets previously presented (‘tokibu’) from new sequences never presented together during exposure (‘kipopi’), i.e., to perform a two-alternative-forced-choice (2-AFC) task. Despite the widespread use of the 2-AFC to test SL, it has come under increasing criticism as it is an offline post-learning task that only assesses the result of the learning that had occurred during the previous exposure phase and that might be affected by other factors beyond the computation of regularities embedded in the input, typically the likelihood two syllables occurring together, a statistic known as transitional probability (TP). One solution to overcome these limitations is to assess SL as exposure to the stream unfolds using online techniques such as event-related potentials (ERP) that is highly sensitive to the time-course of the learning in the brain. Here we collected ERPs to examine the neurofunctional correlates of SL in preschool children with DLD, and chronological-age typical language development (TLD) controls who were exposed to an auditory stream in which eight three-syllable nonsense words, four of which presenting high-TPs and the other four low-TPs, to further analyze whether the ability of DLD and TLD children to extract-word-like units from the steam was modulated by words’ predictability. Moreover, to ascertain if the previous knowledge of the to-be-learned-regularities affected the neural responses to high- and low-TP words, children performed the auditory SL task, firstly, under implicit, and, subsequently, under explicit conditions. Although behavioral evidence of SL was not obtained in either group, the neural responses elicited during the exposure phases of the SL tasks differentiated children with DLD from children with TLD. Specifically, the results indicated that only children from the TDL group showed neural evidence of SL, particularly in the SL task performed under explicit conditions, firstly, for the low-TP, and, subsequently, for the high-TP ‘words’. Taken together, these findings support the view that children with DLD showed deficits in the extraction of the regularities embedded in the auditory input which might underlie the language difficulties.

Keywords: development language disorder, statistical learning, transitional probabilities, word segmentation

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Authors: Marie Bountrogianni, Leonora Zefi, Krystle Phirangee, Naza Djafarova

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Faculty development is critical for any institution as it impacts students’ learning experiences and faculty performance with regards to course delivery. With that in mind, The Chang School at Ryerson University embarked on an initiative to develop a comprehensive, relevant faculty development program for online faculty and instructors. Teaching Adult Learners Online (TALO) is a professional development program designed to build capacity among online teaching faculty to enhance communication/facilitation skills for online instruction and establish a Community of Practice to allow for opportunities for online faculty to network and exchange ideas and experiences. TALO is comprised of four online modules and each module provides three hours of learning materials. The topics focus on online teaching and learning experience, principles and practices, opportunities and challenges in online assessments as well as course design and development. TALO offers a unique experience for online instructors who are placed in the role of a student and an instructor through interactivities involving discussions, hands-on assignments, peer mentoring while experimenting with technological tools available for their online teaching. Through exchanges and informal peer mentoring, a small interdisciplinary community of practice has started to take shape. Successful participants have to meet four requirements for completion: i) participate actively in online discussions and activities, ii) develop a communication plan for the course they are teaching, iii) design one learning activity/or media component, iv) design one online learning module. This study adopted a mixed methods exploratory sequential design. For the qualitative phase of this study, a thorough literature review was conducted on what constitutes effective faculty development programs. Based on that review, the design team identified desired competencies for online teaching/facilitation and course design. Once the competencies were identified, a focus group interview with The Chang School teaching community was conducted as a needs assessment and to validate the competencies. In the quantitative phase, questionnaires were distributed to instructors and faculty after the program was launched to continue ongoing evaluation and revisions, in hopes of further improving the program to meet the teaching community’s needs. Four faculty members participated in a one-hour focus group interview. Major findings from the focus group interview revealed that for the training program, faculty wanted i) to better engage students online, ii) to enhance their online teaching with specific strategies, iii) to explore different ways to assess students online. 91 faculty members completed the questionnaire in which findings indicated that: i) the majority of faculty stated that they gained the necessary skills to demonstrate instructor presence through communication and use of technological tools provided, ii) increased faculty confidence with course management strategies, iii) learning from peers is most effective – the Community of Practice is strengthened and valued even more as program alumni become facilitators. Although this professional development program is not mandatory for online instructors, since its launch in Fall 2014, over 152 online instructors have successfully completed the program. A Community of Practice emerged as a result of the program and participants continue to exchange thoughts and ideas about online teaching and learning.

Keywords: community of practice, customized, faculty development, inclusive design

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Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers

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Authors: Pedro Esteban

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Today’s electrical networks, including microgrids, are evolving into smart grids. The smart grid concept brings the idea that the power comes from various sources (continuous or intermittent), in various forms (AC or DC, high, medium or low voltage, etc.), and it must be integrated into the electric power system in a smart way to guarantee a continuous and reliable supply that complies with power quality and energy efficiency standards and grid code requirements. This idea brings questions for the different players like how the required power will be generated, what kind of power will be more suitable, how to store exceeding levels for short or long-term usage, and how to combine and distribute all the different generation power sources in an efficient way. To address these issues, there has been lots of development in recent years on the field of on-grid and off-grid hybrid power systems (HPS). These systems usually combine one or more modes of electricity generation together with energy storage to ensure optimal supply reliability and high level of energy security. Hybrid power systems combine power generation and energy storage technologies together with real-time energy management and innovative power quality and energy efficiency improvement functionalities. These systems help customers achieve targets for clean energy generation, they add flexibility to the electrical grid, and they optimize the installation by improving its power quality and energy efficiency.

Keywords: microgrids, hybrid power systems, energy storage, power quality improvement

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Authors: Asimina Paparrigopoulou, John Pavlopoulos, Maria Konstantinidou

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Dating papyri accurately is crucial not only to editing their texts but also for our understanding of palaeography and the history of writing, ancient scholarship, material culture, networks in antiquity, etc. Most ancient manuscripts offer little evidence regarding the time of their production, forcing papyrologists to date them on palaeographical grounds, a method often criticized for its subjectivity. By experimenting with data obtained from the Collaborative Database of Dateable Greek Bookhands and the PapPal online collections of objectively dated Greek papyri, this study shows that deep learning dating models, pre-trained on generic images, can achieve accurate chronological estimates for a test subset (67,97% accuracy for book hands and 55,25% for documents). To compare the estimates of these models with those of humans, experts were asked to complete a questionnaire with samples of literary and documentary hands that had to be sorted chronologically by century. The same samples were dated by the models in question. The results are presented and analysed.

Keywords: image classification, papyri images, dating

Procedia PDF Downloads 78

Authors: Annelien A. Van Rooyen, Carol S. Binnekade, Deon Scott, Christina C. Shuttleworth

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Society expects professional accountants to uphold fundamental principles of professional competence, confidentiality, and ethical behavior. Their work needs to be trusted by the public, clients and other stakeholders. However, self-interest, intimidation and even ignorance could create conditions in which accounting practitioners and their staff may act contradictory to these principles. Similarly, plagiarism and cheating occur regularly at higher education institutions, where students claim ignorance of these actions and the accompanying consequences. Teaching students ethical skills in a distance-learning environment where interaction between students and instructors is limited is a challenge for academics. This also applies to instructors who teach accounting subjects to potential professional accountants. The researchers wanted to understand the concerns of accounting practitioners regarding recently qualified accounting students’ understanding of ethics and the resulting influence on their conduct. A mixed method approach was used to obtain feedback from numerous accounting practitioners in South Africa. The research questions focused mainly on ethical conduct in the workplace and the influence of social media on the behavior of graduates. The findings of the research suggested, inter alia, that accounting practitioners are of the opinion that the ethical conduct of graduates starts at home, but higher education institutions play a pivotal role in providing students with an understanding of ethics in the workplace, including the role of social media. The paper concludes with recommendations on how academics in higher education institutions need to address these challenges.

Keywords: accounting profession, distance learning, ethics, workplace

Procedia PDF Downloads 204

Authors: Violetta Cataldo, Renata Savy, Simona Sbranna

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Background: Foreign Language Learning (FLL) is characterised by prosodic transfer phenomena regarding pitch accents placement, intonation patterns, and pitch range excursion from the learners’ mother tongue to their Foreign Language (FL) which suggests that the gradual development of general linguistic competence in FL does not imply an equally correspondent improvement of the prosodic competence. Topic: The present study aims to monitor the development of prosodic competence of learners of Italian and German throughout the FLL process. The primary object of this study is to investigate the intonational features and the f₀ range excursion of Italian and German from a cross-linguistic perspective; analyses of native speakers’ productions point out the differences between this pair of languages and provide models for the Target Language (TL). A following crosscheck compares the L2 productions in Italian and German by non-native speakers to the Target Language models, in order to verify the occurrence of prosodic interference phenomena, i.e., type, degree, and modalities. Methodology: The subjects of the research are university students belonging to two groups: Italian native speakers learning German as FL and German native speakers learning Italian as FL. Both of them have been divided into three subgroups according to the FL proficiency level (beginners, intermediate, advanced). The dataset consists of wh-questions placed in situational contexts uttered in both speakers’ L1 and FL. Using a phonetic approach, analyses have considered three domains of intonational contours (Initial Profile, Nuclear Accent, and Terminal Contour) and two dimensions of the f₀ range parameter (span and level), which provide a basis for comparison between L1 and L2 productions. Findings: Results highlight a strong presence of prosodic transfer phenomena affecting L2 productions in the majority of both Italian and German learners, irrespective of their FL proficiency level; the transfer concerns all the three domains of the contour taken into account, although with different modalities and characteristics. Currently, L2 productions of German learners show a pitch span compression on the domain of the Terminal Contour compared to their L1 towards the TL; furthermore, German learners tend to use lower pitch range values in deviation from their L1 when improving their general linguistic competence in Italian FL proficiency level. Results regarding pitch range span and level in L2 productions by Italian learners are still in progress. At present, they show a similar tendency to expand the pitch span and to raise the pitch level, which also reveals a deviation from the L1 possibly in the direction of German TL. Conclusion: Intonational features seem to be 'resistant' parameters to which learners appear not to be particularly sensitive. By contrast, they show a certain sensitiveness to FL pitch range dimensions. Making clear which the most resistant and the most sensitive parameters are when learning FL prosody could lay groundwork for the development of prosodic trainings thanks to which learners could finally acquire a clear and natural pronunciation and intonation.

Keywords: foreign language learning, German, Italian, L2 prosody, pitch range, transfer

Procedia PDF Downloads 286

Authors: Nirmani Wijenayake, Louise Lutze-Mann, Lucy Jo, John Wilson, Vivian Yeung, Dean Lovett, Kim Snepvangers

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Sessional academic staff at universities have the most influence and impact on student learning, engagement, and experience as they have the most direct contact with undergraduate students. A blended technology-enhanced program was created for the development and support of sessional staff to ensure adequate training is provided to deliver quality educational outcomes for the students. This program combines innovative mixed media educational modules, a peer-driven support forum, and face-to-face workshops to provide a comprehensive training and support package for staff. Additionally, the program encourages the development of learning communities and peer mentoring among the sessional staff to enhance their support system. In 2018, the program was piloted on 100 sessional staff in the School of Biotechnology and Biomolecular Sciences to evaluate the effectiveness of this model. As part of the program, rotoscope animations were developed to showcase ‘typical’ interactions between staff and students. These were designed around communication, confidence building, consistency in grading, feedback, diversity awareness, and mental health and wellbeing. When surveyed, 86% of sessional staff found these animations to be helpful in their teaching. An online platform (Moodle) was set up to disseminate educational resources and teaching tips, to host a discussion forum for peer-to-peer communication and to increase critical thinking and problem-solving skills through scenario-based lessons. The learning analytics from these lessons were essential in identifying difficulties faced by sessional staff to further develop supporting workshops to improve outcomes related to teaching. The face-to-face professional development workshops were run by expert guest speakers on topics such as cultural diversity, stress and anxiety, LGBTIQ and student engagement. All the attendees of the workshops found them to be useful and 88% said they felt these workshops increase interaction with their peers and built a sense of community. The final component of the program was to use an adaptive e-learning platform to gather feedback from the students on sessional staff teaching twice during the semester. The initial feedback provides sessional staff with enough time to reflect on their teaching and adjust their performance if necessary, to improve the student experience. The feedback from students and the sessional staff on this model has been extremely positive. The training equips the sessional staff with knowledge and insights which can provide students with an exceptional learning environment. This program is designed in a flexible and scalable manner so that other faculties or institutions could adapt components for their own training. It is anticipated that the training and support would help to build the next generation of educators who will directly impact the educational experience of students.

Keywords: designing effective instruction, enhancing student learning, implementing effective strategies, professional development

Procedia PDF Downloads 128