Search results for: artificial teacher

Authors: Nathaniel Carpenter

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Web-enabled systems for supporting youth mental health management in Australia are pioneering in their field; however, with their success, these systems are experiencing exponential growth in demand which is straining an already stretched service. Supporting youth mental is critical as the lack of support is associated with significant and lasting negative consequences. To meet this growing demand, and provide critical support, investigations are needed on evaluating and improving existing online support services. Improvements should focus on developing frameworks capable of augmenting and scaling service provisions. There are few investigations informing best-practice frameworks when implementing e-mental health support systems for youth mental health; there are fewer which implement machine learning or artificially intelligent systems to facilitate the delivering of services. This investigation will use a case study methodology to highlight the design features which are important for systems to enable young people to self-manage their mental health. The investigation will also highlight the current information system challenges, to include challenges associated with service quality, provisioning, and scaling. This work will propose methods of meeting these challenges through improved design, service augmentation and automation, service quality, and through artificially intelligent inspired solutions. The results of this study will inform a framework for supporting youth mental health with intelligent and scalable web-enabled technologies to support an ever-growing user base.

Keywords: artificial intelligence, information systems, machine learning, youth mental health

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Authors: Styliani Soulioti, Helen Fiddler

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The aim of this study was to investigate the approaches used by physiotherapists in the education of patients with chronic low back pain (cLBP) and the rationale that underpins their choice of approach. Therapeutic patient education (TPE) is considered to be an important aspect of modern physiotherapy practice, as it helps patients achieve better self-management and a better understanding of their problem. Previous studies have explored this subject, but the reasoning behind the choices physiotherapists make as educators has not been widely explored, thus making it difficult to understand areas that could be addressed in order to improve the application of TPE.A qualitative study design, guided by a constructivist epistemology was used in this research project. Semi-structured interviews were used to collect data from 7 physiotherapists. Inductive coding and thematic analysis were used, which allowed key themes to emerge. Data analysis revealed two overarching themes: 1) patient-centred versus therapist-centred educational approaches, and 2) behaviourist versus constructivist educational approaches. Physiotherapists appear to use a patient-centred-approach when they explore patients’ beliefs about cLBP and treatment expectations. However, treatment planning and goal-setting were guided by a therapist-centred approach, as physiotherapists appear to take on the role of the instructor/expert, whereas patients were viewed as students. Using a constructivist approach, physiotherapists aimed to provide guidance to patients by combining their professional knowledge with the patients’ individual knowledge, to help the patient better understand their problem, reflect upon it and find a possible solution. However, educating patients about scientific facts concerning cLBP followed a behaviourist approach, as an instructor/student relationship was observed and the learning content was predetermined and transmitted in a one-way manner. The results of this study suggest that a lack of consistency appears to exist in the educational approaches used by physiotherapists. Although patient-centeredness and constructivism appear to be the aims set by physiotherapists in order to optimise the education they provide, a student-teacher relationship appears to dominate when it comes to goal-setting and delivering scientific information.

Keywords: chronic low back pain, educational approaches, health education, patient education

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Authors: Abdulkader Helwan

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Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

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Authors: Daudi S. Simbeye, Mbazingwa E. Mkiramweni

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Plant diseases have the potential to drastically diminish the quantity and quality of agricultural products. Guava (Psidium guajava), sometimes known as the apple of the tropics, is one of the most widely cultivated fruits in tropical regions. Monitoring plant health and diagnosing illnesses is an essential matter for sustainable agriculture, requiring the inspection of visually evident patterns on plant leaves and fruits. Due to minor variations in the symptoms of various guava illnesses, a professional opinion is required for disease diagnosis. Due to improper pesticide application by farmers, erroneous diagnoses may result in economic losses. This study proposes a method that uses artificial intelligence (AI) to detect and classify the most widespread guava plant by comparing images of its leaves and fruits to datasets. ESP32 CAM is responsible for data collection, which includes images of guava leaves and fruits. By comparing the datasets, these image formats are used as datasets to help in the diagnosis of plant diseases through the leaves and fruits, which is vital for the development of an effective automated agricultural system. The system test yielded the most accurate identification findings (99 percent accuracy in differentiating four guava fruit diseases (Canker, Mummification, Dot, and Rust) from healthy fruit). The proposed model has been interfaced with a mobile application to be used by smartphones to make a quick and responsible judgment, which can help the farmers instantly detect and prevent future production losses by enabling them to take precautions beforehand.

Keywords: early identification, guava plants, fruit diseases, deep learning

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Authors: Juhi Faridi, Mohd. Ajmal Kafeel

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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems

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Authors: Joanna Estkowska

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Sensory integration methods are very useful and improve daily functioning autistic and mentally disabled children. Autism is a neurobiological disorder that impairs one's ability to communicate with and relate to others as well as their sensory system. Children with autism, even highly functioning kids, can find it difficult to process language with surrounding noise or smells. They are hypersensitive to things we can ignore such as sight, sounds and touch. Adolescents with highly functioning autism or Asperger Syndrome can study Science and Math but the social aspect is difficult for them. Nature science is an area of study that attracts many of these kids. It is a systematic field in which the children can focus on a small aspect. If you follow these rules you can come up with an expected result. Sensory integration program and systematic classroom observation are quantitative methods of measuring classroom functioning and behaviors from direct observations. These methods specify both the events and behaviors that are to be observed and how they are to be recorded. Our students with and without autism attended the lessons in the classroom of nature science in the school and in the laboratory of University of Science and Technology in Bydgoszcz. The aim of this study is investigation the effects of sensory integration methods in teaching to students with autism. They were observed during experimental lessons in the classroom and in the laboratory. Their physical characteristics, sensory dysfunction, and behavior in class were taken into consideration by comparing their similarities and differences. In the chemistry classroom, every autistic student is paired with a mentor from their school. In the laboratory, the children are expected to wear goggles, gloves and a lab coat. The chemistry classes in the laboratory were held for four hours with a lunch break, and according to the assistants, the children were engaged the whole time. In classroom of nature science, the students are encouraged to use the interactive exhibition of chemical, physical and mathematical models constructed by the author of this paper. Our students with and without autism attended the lessons in those laboratories. The teacher's goals are: to assist the child in inhibiting and modulating sensory information and support the child in processing a response to sensory stimulation.

Keywords: autism spectrum disorder, science education, sensory integration techniques, student with special educational needs

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Authors: Nuri Balta, Ali Eryilmaz

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High-quality teachers are the key to improve student learning. Without a professional development of the teachers, the improvement of student success is difficult and incomplete. This study offers an in-service training course model for professional development of teachers (PD) entitled "teachers teaching teachers" (TTT). The basic premise of the PD program, designed for this study, was primarily aimed to increase the subject matter knowledge of high school physics teachers. The TTT course (the three hour long workshops), organized for this study, lasted for seven weeks with seventeen teachers took part in the TTT program at different amounts. In this study, the effect of the TTT program on teachers’ knowledge improvement was searched through the modern physics unit (MPU). The participating teachers taught the unit to one of their grade ten classes earlier, and they taught another equivalent class two months later. They were observed in their classes both before and after TTT program. The teachers were divided into placebo and the treatment groups. The aim of Solomon four-group design is an attempt to eliminate the possible effect of pre-test. However, in this study the similar design was used to eliminate the effect of pre teaching. The placebo group teachers taught their both classes as regular and the treatment group teachers had TTT program between the two teachings. The class observation results showed that the TTT program increased teachers’ knowledge and skills in teaching MPU. Further, participating in the TTT program caused teachers to teach the MPU in accordance with the requirements of the curriculum. In order to see any change in participating teachers’ success, an achievement test was applied to them. A large effect size (dCohen=.93) was calculated for the effect of TTT program on treatment group teachers’ achievement. The results suggest that staff developers should consider including topics, attractive to teachers, in-service training programs (a) to help teachers’ practice teaching the new topics (b) to increase the participation rate. During the conduction of the TTT courses, it was observed that teachers could not end some discussions and explain some concepts. It is now clear that teachers need support, especially when discussing counterintuitive concepts such as modern physics concepts. For this reason it is recommended that content focused PD programs be conducted at the helm of a scholarly coach.

Keywords: high school physics, in-service training course, modern physics unit, teacher professional development

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Authors: John Gibbs, Benjamin Flanders, Dylan Pozorski, Weixuan Liu

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Weight Painting–adjusting the influence a skeletal joint has on a given vertex in a character mesh–is an arduous and time con- suming part of the 3D animation pipeline. This process generally requires a trained technical animator and many hours of work to complete. Our skiNNer plug-in, which works within Autodesk’s Maya 3D animation software, uses Machine Learning and data pro- cessing techniques to create a deep neural network model that can accomplish the weight painting task in seconds rather than hours for bipedal quasi-humanoid character meshes. In order to create a properly trained network, a number of challenges were overcome, including curating an appropriately large data library, managing an arbitrary 3D mesh size, handling arbitrary skeletal architectures, accounting for extreme numeric values (most data points are near 0 or 1 for weight maps), and constructing an appropriate neural network model that can properly capture the high frequency alter- ation between high weight values (near 1.0) and low weight values (near 0.0). The arrived at neural network model is a cross between a traditional CNN, deep residual network, and fully dense network. The resultant network captures the unusually hard-edged features of a weight map matrix, and produces excellent results on many bipedal models.

Keywords: 3d animation, animation, character, rigging, skinning, weight painting, machine learning, artificial intelligence, neural network, deep neural network

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Authors: Per Blomqvist

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This study is part of a larger research project on creativity and writing cultures in upper secondary schools in Sweden, with the purpose of exploring how formative assessment practices can be developed to better support students' writing of subject-specific texts. The purpose of the study is to shed light on how writing has changed over time in the subjects of Social Studies and Swedish, especially regarding changes in the formative assessment practice in relation to students opportunities to take part in creative writing processes that can develop their subject specific-writing. Theoretically, the study is based on concepts and models concerning creativity, writing instructions and formative assessment, especially regarding scaffolding in relation to the development of students' subject-specific writing. The empirical data consists of video recordings of teacher groups' conversations from five upper secondary schools in Sweden, compromising a total of twenty teachers. The conversations were conducted as so-called collective remembering interviews, a method to stimulate the participants' memory through social interaction, and focused on addressing issues on how writing assessment has changed over time. Topic analysis was used to analyze the conversations in order to identify common descriptions and expressions among the teachers in each group. The result highlights two different assessment practices that are described as giving students different opportunities to take part in creative writing processes to develop their writing of subject-specific texts. One of the assessment practices is characterized by teachers focusing on explaining to the students what the grading criteria mean and showing sample texts that correspond to a certain grade. The teachers describe that this assessment practice has led to a formalized, instrumental and product-oriented writing culture that has negative consequences for the student's development of their subject-specific writing, which often lacks independent reasoning, own conclusions and understanding of concepts. The other assessment practice is characterized by students examining text qualities and discussing a variety of sample texts to understand what different texts require. These teachers describe the assessment practice as an exploratory work that leads to more creative writing processes where the students gradually deepen their understanding of subject-specific texts and develop their writing.

Keywords: teaching for creativity, writing processes, formative assessment, subject-specific writing

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Authors: Silvia Boschetti, Jakub Binter, Robin Kopecký, Lenka PříPlatová, Jaroslav Flegr

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A strict dichotomy was present between religion and science, but recently, cognitive science focusses on the impact of supernatural beliefs on cognitive processes such as pattern recognition. It has been hypothesized that cognitive and perceptual processes have been under evolutionary pressures that ensured amplified perception of patterns, especially when in stressful and harsh conditions. The pattern detection in religious and non-religious individuals after induction of negative, anxious mood shall constitute a cornerstone of the general role of anxiety, cognitive bias, leading towards or against the by-product hypothesis, one of the main theories on the evolutionary studies of religion. The apophenia (tendencies to perceive connection and meaning on unrelated events) and perception of visual patterns (or pateidolia) are of utmost interest. To capture the impact of culture and upbringing, a comparative study of two European countries, the Czech Republic (low organized religion participation, high esoteric belief) and Italy (high organized religion participation, low esoteric belief), are currently in the data collection phase. Outcomes will be presented at the conference. A battery of standardized questionnaires followed by pattern recognition tasks (the patterns involve color, shape, and are of artificial and natural origin) using an experimental method involving the conditioning of (controlled, laboratory-induced) stress is taking place. We hypothesize to find a difference between organized religious belief and personal (esoteric) belief that will be alike in both of the cultural environments.

Keywords: culture, esoteric belief, pattern perception, religiosity

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Authors: Fatima Muhammad Shitu

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In language learning, Second language learners like their native speaker counter parts, commit errors in their attempt to achieve competence in the target language. The realm of Collocation has to do with meaning relation between lexical items. In all human language, there is a kind of ‘natural order’ in which words are arranged or relate to one another in sentences so much so that when a word occurs in a given context, the related or naturally co -occurring word will automatically come to the mind. It becomes an error, therefore, if students inappropriately pair or arrange such ‘naturally’ co – occurring lexical items in a text. It has been observed that most of the second language learners in this research group commit collocational errors. A study of this kind is very significant as it gives insight into the kinds of errors committed by learners. This will help the language teacher to be able to identify the sources and causes of such errors as well as correct them thereby guiding, helping and leading the learners towards achieving some level of competence in the language. The aim of the study is to understand the nature of these errors as stumbling blocks to effective essay writing. The objective of the study is to identify the errors, analyse their structural compositions so as to determine whether there are similarities between students in this regard and to find out whether there are patterns to these kinds of errors which will enable the researcher to understand their sources and causes. As a descriptive research, the researcher samples some nine hundred essays collected from three hundred undergraduate learners of English as a second language in the Federal College of Education, Kano, North- West Nigeria, i.e. three essays per each student. The essays which were given on three different lecture times were of similar thematic preoccupations (i.e. same topics) and length (i.e. same number of words). The essays were written during the lecture hour at three different lecture occasions. The errors were identified in a systematic manner whereby errors so identified were recorded only once even if they occur severally in students’ essays. The data was collated using percentages in which the identified number of occurrences were converted accordingly in percentages. The findings from the study indicates that there are similarities as well as regular and repeated errors which provided a pattern. Based on the pattern identified, the conclusion is that students’ collocational errors are attributable to poor teaching and learning which resulted in wrong generalisation of rules.

Keywords: collocations, errors, second language learning, ESL students

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Authors: Salah Hadjout, Mohamed Zouidi

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In Algeria, several works carried out in recent years have shown the importance of fusarium head blight in durum wheat. Indeed, this disease is caused by a complex of Fusarium genus pathogens. The research carried out reports that F. culmorum is the main species infecting cereals. These informations motivated our interest in the field evaluation of the behavior of some durum wheat genotypes (parental varieties and lines) with regard to fusarium head blight, mainly caused by four F. culmorum isolates. Our research work focused on following the evolution of symptom development throughout the grain filling, after artificial inoculation of ears by Fusarium isolates in order to establish a first image on the differences in genotype behavior to fusarium haed blight. Field disease assessment criteria are: disease assessment using a grading scale, thousand grain weight measurement and AUDPC. The results obtained revealed that the varieties and lines resulting from crosses had a quite different level of sensitivity to F. culmorum species and no genotype showed complete resistance in our culture conditions. Among the material tested, some lines showed higher resistance than their parents. The results also show a slight behavioral variability also linked to the aggressiveness of the Fusarium species studied in this work. Our results open very important research perspectives on fusarium head blight, in particular the search for toxins produced by Fusarium species.

Keywords: fusarium head blight, durum wheat, Fusarium culmorum, field disease assessment criteria, Algeria

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Authors: Ahmet Kurnaz, Eyup Yurt, Ümit Çiftci

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In this study, too, an attempt was made to reveal the place and effects of information technologies on the lives and education of gifted children based on the views of gifted. To this end, the effects of information technologies on gifted are general skills, technology use, academic and social skills, and cooperative and personal skills were investigated. These skills were explored depending on whether or not gifted had their own computers, had internet connection at home, or how often they use the internet, average time period they spent at the computer, how often they played computer games and their use of social media. The study was conducted using the screening model with a quantitative approach. The sample of the study consisted of 129 gifted attending 5-12th classes in 12 provinces in different regions of Turkey. 64 of the participants were female while 65 were male. The research data were collected using the using computer of gifted and information technologies (UCIT) questionnaire which was developed by the researchers and given its final form after receiving expert view. As a result of the study, it was found that UCIT use improved foreign language speaking skills of gifted, enabled them to get to know and understand different cultures, and made use of computer and information technologies while they study. At the end of the study these result were obtained: Gifted have positive idea using computer and communication technology. There are differences whether using the internet about the ideas UCIT. But there are not differences whether having computer, inhabited city, grade level, having internet at home, daily and weekly internet usage durations, playing the computer and internet game, having Facebook and Twitter account about the UCIT. UCIT contribute to the development of gifted vocabulary, allows knowing and understand different cultures, developing foreign language speaking skills, gifted do not give up computer when they do their homework, improve their reading, listening, understanding and writing skills in a foreign language. Gifted children want to have transition to the use of tablets in education. They think UCIT facilitates doing their homework, contributes learning more information in a shorter time. They'd like to use computer-assisted instruction programs at courses. They think they will be more successful in the future if their computer skills are good. But gifted students prefer teacher instead of teaching with computers and they said that learning can be run from home without going to school.

Keywords: gifted, using computer, communication technology, information technologies

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Authors: Boukhalfa Djemouai, Belkadi Souhila, Safsaf Boubakeur

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To increase the profitability of the national herd so that it can meet the needs of the population, Algeria has proceeded to the introduction of new reproductive biotechnologies, including artificial insemination on natural heat, by induction and heat synchronization. This biotechnology uses the male way for the creation and dissemination of genetic progress. The study has focused on 30 goat kids and bucks local breed aged between 03 and 24 months, divided into 03 groups 03-06 months[Grp 1; n=9], 07-10 months [Grp 2; n=13] and 11-24 months [Grp 3; n=8], in order to determine the influence of age on testicular evolution by measurements of testis and scrotum, and the epididymis sperm parameters evaluation. These parameters are influenced by age variations (sperm and spermocytogram). The examined parameters have focused on testicular weight (grams), the scrotal circumference (cm), mass mobility (%), vitality rate (%), sperm concentration (x 109), and percentage of abnormal spermatozoa (%). The ANOVA reveals a significance effect of age on parameters: testis weight, scrotal circumference, sperm concentration, motility varying between high (p < 0.01) to very high significance (p < 0.001), while in viability and abnormalities no significance was observed between all groups. The value of these parameters increased significantly until the age of 02 years, while that of sperm abnormalities has increased in Grp2. The histological study of testicular development shows that the genetic spermatozoa function characterized by cell proliferation, which is more and more intense starting from the age of 05 months and can be considered as an age of puberty in the local breed goat Arbia and increases with animal age.

Keywords: kids and bucks, epididymis sperm, testicular measurements, Arbia breed

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Authors: Abimbola Akintounde

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Supporting the social and emotional needs of young adolescents has become an emergent concern for schools around the world. Yet educators remain in a dilemma regarding the optimum approach for integrating social and emotional learning (SEL) into their content area instruction. The purpose of this study was to explore the perception of secondary students regarding their schoolwide SEL interventions. Twenty-four International Baccalaureate students in a final year mathematics course at an American Public Secondary School near Washington D. C. were randomly selected for participation in this study via an online electronic survey. The participants in this study used Likert-scale items to rate the effectiveness of the socio-emotional and character development programs being implemented at their schools. Respondents also ranked their preferred mode of delivery of social and emotional support programs. About 71% of the teenagers surveyed preferred SEL support rendered via interactive team-building activities and games, 42% of the high school students in the study ranked focus group discussions as their preferred format for SEL interventions, while only 13% of the respondents in the study regarded lectures and presentations as their preferred mode of SEL delivery. About one-fourth of the study participants agreed that explicit instruction was critical to enhancing students’ wellness, 79% agreed that SEL programs should foster less teacher talk, while 88% of the students indicated that student engagement was critical to their mental health. Eighty percent of the teenagers surveyed decried that the focus of their school-wide social and emotional programs was poorly prioritized. About two-thirds of the students agreed that social justice and equity issues should be embedded in their schools’ advisory programs. More than half of the respondents agitated for strategies for managing stress and their school workload. About 54% of the respondents also clamored for SEL programs that reinforce emotion regulation and coping strategies for anxiety. Based on the findings of this study, recommendations were proffered for best practices in the design and implementation of effective learner-friendly social and emotional development interventions.

Keywords: SEL, math anxiety, student support, emotion regulation, social awareness, self awareness, self management, relationship building

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Authors: Carla Idely Palencia-Aguilar

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Mining in Colombia represents around 2% of the GDP (USD 8 billion in 2018), with main productions represented by coal, nickel, gold, silver, emeralds, iron, limestone, gypsum, among others. Sand and Gravel had been decreasing its participation of the GDP with a reduction of 33.2 million m3 in 2015, to 27.4 in 2016, 22.7 in 2017 and 15.8 in 2018, with a consumption of approximately 3 tons/inhabitant. However, with the new government policies it is expected to increase in the following years. Mining causes temporary environmental impacts, once restoration and rehabilitation takes place, social, environmental and economic benefits are higher than the initial state. A way to demonstrate how the mining interventions had contributed to improve the characteristics of the region after sand and gravel mining, the NDVI (Normalized Difference Vegetation Index) from MODIS and ASTER were employed. The histograms show not only increments of vegetation in the area (8 times higher), but also topographies similar to the ones before the intervention, according to the application for sustainable development selected: either agriculture, forestry, cattle raising, artificial wetlands or do nothing. The decision was based upon a Multicriteria analysis for optimal land use, with three main variables: geostatistics, evapotranspiration and groundwater characteristics. The use of remote sensing, meteorological stations, piezometers, sunphotometers, geoelectric analysis among others; provide the information required for the multicriteria decision. For cattle raising and agricultural applications (where various crops were implemented), conservation of products were tested by means of nanotechnology. The results showed a duration of 2 years with no chemicals added for preservation and concentration of vitamins of the tested products.

Keywords: ASTER, Geostatistics, MODIS, Multicriteria

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Authors: L. Spitaleri, C. M. A. Gangemi, R. Purrello, G. Nicotra, G. Trusso Sfrazzetto, G. Casella, M. Casarin, A. Gulino

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Hybrid molecular–nanoparticle materials, obtained with a bottom-up approach, are suitable for the fabrication of functional nanostructures showing structural control and well-defined properties, i.e., optical, electronic or catalytic properties, in the perspective of applications in different fields of nanotechnology. Gold nanoparticles (Au NPs) exhibit important chemical, electronic and optical properties due to their size, shape and electronic structures. In fact, Au NPs containing no more than 30-40 atoms are only luminescent because they can be considered as large molecules with discrete energy levels, while nano-sized Au NPs only show the surface plasmon resonance. Hence, it appears that gold nanoparticles can alternatively be luminescent or plasmonic, and this represents a severe constraint for their use as an optical material. The aim of this work was the fabrication of nanoscale assembly of Au NPs covalently anchored to each other by means of novel bi-functional porphyrin molecules that work as bridges between different gold nanoparticles. This functional architecture shows a strong surface plasmon due to the Au nanoparticles and a strong luminescence signal coming from porphyrin molecules, thus, behaving like an artificial organized plasmonic and fluorescent network. The self-assembly geometry of this porphyrin on the Au NPs was studied by investigation of the conformational properties of the porphyrin derivative at the DFT level. The morphology, electronic structure and optical properties of the conjugated Au NPs – porphyrin system were investigated by TEM, XPS, UV–vis and Luminescence. The present nanostructures can be used for plasmon-enhanced fluorescence, photocatalysis, nonlinear optics, etc., under atmospheric conditions since our system is not reactive to air nor water and does not need to be stored in a vacuum or inert gas.

Keywords: gold nanoparticle, porphyrin, surface plasmon resonance, luminescence, nanostructures

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Authors: R. O. Osaseri, A. R. Usiobaifo

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The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

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Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, this project proposes AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project presents the best-in-school techniques used to preserve the data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptographic techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures and identifies potential correction/mitigation measures.

Keywords: data privacy, artificial intelligence (AI), healthcare AI, data sharing, healthcare organizations (HCOs)

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Authors: Qasim Munye, Juned Islam, Haseeb Qureshi, Syed Jung

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Lung nodules are commonly identified in computed tomography (CT) scans by experienced radiologists at a relatively late stage. Early diagnosis can greatly increase survival. We propose using a pix2pix conditional generative adversarial network to generate realistic images simulating early-stage lung nodule growth. We have applied deep images prior to 2341 slices from 895 computed tomography (CT) scans from the Lung Image Database Consortium (LIDC) dataset to generate pseudo-healthy medical images. From these images, 819 were chosen to train a pix2pix network. We observed that for most of the images, the pix2pix network was able to generate images where the nodule increased in size and intensity across epochs. To evaluate the images, 400 generated images were chosen at random and shown to a medical student beside their corresponding original image. Of these 400 generated images, 384 were defined as satisfactory - meaning they resembled a nodule and were visually similar to the corresponding image. We believe that this generated dataset could be used as training data for neural networks to detect lung nodules at an early stage or to improve the accuracy of such networks. This is particularly significant as datasets containing the growth of early-stage nodules are scarce. This project shows that the combination of deep image prior and generative models could potentially open the door to creating larger datasets than currently possible and has the potential to increase the accuracy of medical classification tasks.

Keywords: medical technology, artificial intelligence, radiology, lung cancer

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Authors: Li-Hua Luu, Alexis Doghmane, Abbas Farhat, Mohammad Sanayei, Pierre Philippe, Pablo Cuellar

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Suction buckets are promising innovative foundations for offshore wind turbines. They generally feature the shape of an inverted bucket and rely on a suction system as a driving agent for their installation into the seabed. Water is pumped out of the buckets that are initially placed to rest on the seabed, creating a net pressure difference across the lid that generates a seepage flow, lowers the soil resistance below the foundation skirt, and drives them effectively into the seabed. The stability of the suction mechanism as well as the possibility of a piping failure (i.e., localized fluidization within the internal soil plug) during their installation are some of the key questions that remain open. The present work deals with an experimental study of localized fluidization by suction within a fixed bucket partially embedded into a submerged artificial soil made of spherical beads. The transient process, from the onset of granular motion until reaching a stationary regime for the fluidization at the embedded bucket wall, is recorded using the combined optical techniques of planar laser-induced fluorescence and refractive index matching. To conduct a systematic study of the piping threshold for the seepage flow, we vary the beads size, the suction pressure, and the initial depth for the bucket. This experimental modelling, by dealing with erosion-related phenomena from a micromechanical perspective, shall provide qualitative scenarios for the local processes at work which are missing in the offshore practice so far.

Keywords: fluidization, micromechanical approach, offshore foundations, suction bucket

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Authors: Muhammad Anjum Aqueel, Zaighum Abbas, Mubasshir Sohail, Muhammad Abubakar, Hafiz Khurram Shurjeel, Abu Bakar Muhammad Raza, Muhammad Afzal, Sami Ullah

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Keeping in view the increasing demand, queen of Apis mellifera L. (Hymenoptera: Apidae) was reared artificially in this experiment at varying diets including royal jelly. Larval duration, pupal duration, weight, and size of pupae were evaluated at different diets including royal jelly. Queen larvae were raised by Doo Little grafting method. Four different diets were mixed with royal jelly and applied to larvae. Fructose, sugar, yeast, and honey were provided to rearing queen larvae along with same amount of royal jelly. Larval and pupal duration were longest (6.15 and 7.5 days, respectively) at yeast and shortest on honey (5.05 and 7.02 days, respectively). Heavier and bigger pupae were recorded on yeast (168.14 mg and 1.76 cm, respectively) followed by diets having sugar and honey. Due to production of heavier and bigger pupae, yeast was considered as best artificial diet for the growing queen larvae. So, in the second part of experiment, different amounts of yeast were provided to growing larvae along with fixed amount (0.5 g) of royal jelly. Survival rates of the larvae and queen bee were 70% and 40% in the 4-g food, 86.7% and 53.3% in the 6-g food, and 76.7% and 50% in the 8-g food. Weight of adult queen bee (1.459±0.191 g) and the number of ovarioles (41.7±21.3) were highest at 8 g of food. Results of this study are helpful for bee-keepers in producing fitter queen bees.

Keywords: apis melifera l, dietary effect, survival and development, honey bee queen

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Authors: Zonglin Yang, Tatsuya Akiyama, Kerry S. Williamson, Michael J. Franklin, Thiruvarangan Ramaraj

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Pseudomonas aeruginosa is an opportunistic pathogen that forms surface-associated microbial communities (biofilms) on artificial implant devices and on human tissue. Biofilm infections are difficult to treat with antibiotics, in part, because the bacteria in biofilms are physiologically heterogeneous. One measure of biological heterogeneity in a population of cells is to quantify the cellular concentrations of ribosomes, which can be probed with fluorescently labeled nucleic acids. The fluorescent signal intensity following fluorescence in situ hybridization (FISH) analysis correlates to the cellular level of ribosomes. The goals here are to provide computationally and statistically robust approaches to automatically quantify cellular heterogeneity in biofilms from a large library of epifluorescent microscopy FISH images. In this work, the initial steps were developed toward these goals by developing an automated biofilm detection approach for use with FISH images. The approach allows rapid identification of biofilm regions from FISH images that are counterstained with fluorescent dyes. This methodology provides advances over other computational methods, allowing subtraction of spurious signals and non-biological fluorescent substrata. This method will be a robust and user-friendly approach which will enable users to semi-automatically detect biofilm boundaries and extract intensity values from fluorescent images for quantitative analysis of biofilm heterogeneity.

Keywords: image informatics, Pseudomonas aeruginosa, biofilm, FISH, computer vision, data visualization

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Authors: Sabli, Eddy Rismunandar, Akhirudin, Nana Halim, Zulfikar, Nining Dwirosanti, Wila Ningsih, Pipih Siti Sofiah, Danik Dania Asadayanti, Dewi Eka Arini Algozi, Gita Mahardika Pamuji, Ajun, Mangasa Aritonang, Nanang Rukmana, Arief Rachman Wonodhipo, Victor Imanuel Nahumury, Lili Husada, Wawan Saepul Irwan, Al Mukhlas Fikri

Abstract:

Covid-19 pandemic has widely impacted the lives. An adaptive strategy must be quickly formulated to maintain the quality of education, especially by vocational school which technical skill competencies are highly needed. This study aimed to evaluate the effectiveness of e-training on the attitude and skill competencies of vocational high school teachers in Indonesia. A total of 720 Indonesian vocational high school teachers with various programs, including hospitality, administration, online business and marketing, culinary arts, fashion, cashier, tourism, haircut, and accounting participated e-training for a month. The training used electronic learning management system to provide materials (modules, presentation slides, and tutorial videos), tasks, and evaluations. Tutorial class was carried out by video conference meeting. Attitude and skill competencies were evaluated before and after the training. Meanwhile, the teachers also gave satisfactory feedback on the quality of the organizer and tutors. Data analysis used paired sample t-test and Anova with Tukey’s post hoc test. The results showed that e-training significantly increased the score of attitude and skill competencies of the teachers (p <0,05). Moreover, the remarkable increase was found among hospitality (57,5%), cashier (50,1%), and online business and marketing (48,7%) teachers. However, the effect among fashion, tourism and haircut teachers was less obvious. In addition, the satisfactory score on the quality of the organizer and tutors were 88,9 (very good), and 93,5 (excellence), respectively. The study concludes that a well-organized e-training could increase the attitude and skill competencies of Indonesian vocational high school teachers during Covid-19 pandemic.

Keywords: E-training, skill, teacher, vocational high school

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Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li

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With the widespread popularity of mobile devices and the development of artificial intelligence (AI), deep learning (DL) has been extensively applied in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace; a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Moreover, using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. We conducted an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace has a more robust performance than FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.

Keywords: mobile computing, deep learning apps, sensitive information, static analysis

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Authors: Raoul Ouambo Tobou, Alexis Kuitche, Marcel Edoun

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The FWM (Finite Window Method) is a new numerical meshfree technique for solving problems defined either in terms of PDEs (Partial Differential Equation) or by a set of conservation/equilibrium laws. The principle behind the FWM is that in such problem each element of the concerned domain is interacting with its neighbors and will always try to adapt to keep in equilibrium with respect to those neighbors. This leads to a very simple and robust problem solving scheme, well suited for transfer problems. In this work, we have applied the FWM to an unsteady scalar convection-diffusion equation. Despite its simplicity, it is well known that convection-diffusion problems can be challenging to be solved numerically, especially when convection is highly dominant. This has led researchers to set the scalar convection-diffusion equation as a benchmark one used to analyze and derive the required conditions or artifacts needed to numerically solve problems where convection and diffusion occur simultaneously. We have shown here that the standard FWM can be used to solve convection-diffusion equations in a robust manner as no adjustments (Upwinding or Artificial Diffusion addition) were required to obtain good results even for high Peclet numbers and coarse space and time steps. A comparison was performed between the FWM scheme and both a first order implicit Finite Volume Scheme (Upwind scheme) and a third order implicit Finite Volume Scheme (QUICK Scheme). The results of the comparison was that for equal space and time grid spacing, the FWM yields a much better precision than the used Finite Volume schemes, all having similar computational cost and conditioning number.

Keywords: Finite Window Method, Convection-Diffusion, Numerical Technique, Convergence

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Authors: Abhinav Chaturvedi, Joohi Chaturvedi, Renu Chaturvedi

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With rapid urbanization and growth of population, more buildings are require to be constructed to meet the increasing demand of the shelter. 80 % of the world population is living in developing countries, but the adequate energy supplied to only 30% of it. In India situation get little more difficult as majority of the villages of India are still deprived of energy. 1/3 of the Indian household does not have energy supply. So there is big gap between energy demand and supply. Moreover India is producing around 65 % of the energy from Non – Renewable sources and 25 % of the Energy is imported in the form of oil and gas and only 10% of the total, is generated from other sources like solar power, wind power etc. Present modern structures are big energy consumers as they are consuming 40 % of the total energy in providing comfort conditions to the users, in from of heating and cooling,5 % in Building Construction, 20 % in transportation and 20 % in industrial process and 10 % in other processes. If we minimize this Heating and Cooling and lighting load of the building we can conserve huge amount of energy for the future. In history, buildings do not have artificial systems of cooling or heating. These buildings, especially in Hadoti Region which have Semi Arid Climatic conditions, are provided with Solar Passive Design Techniques that is the reason of comfort inside the buildings. So if we use some appropriate elements of these heritage structures, in our present age building design we can find some certain solution to energy crises. Present paper describes Various Solar Passive design techniques used in past, and the same could be used in present to reduce the consumption of energy.

Keywords: energy conservation, Hadoti region, solar passive design techniques , semi - arid climatic condition

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Authors: Wai Ha Leung

Abstract:

Mother tongue language (MTL) curriculum is core to school education in most countries/regions' school curriculum. Through mother tongue language learning, students are expected to enhance their understanding of the nation's culture and foster the sense of cultural and ethnic identity. However, MTL education in Hong Kong is complicated by the colonial history. This study examines Hong Kong Chinese language teachers' perceptions of MTL education, and the implication on MTL curriculum development. The questionnaire was administrated to 97 teachers, and interviews were carried out on 17 teachers. Usually, MTL is both the tool with which knowledge and skills are taught and learned and the vehicle for students to learn about the traditions of the countries' literature and culture. In Hong Kong, 95% of the population is of Chinese descent. Traditionally, education in China was a mixture of philosophy, history, politics and literacy. Chinese as an MTL subject in pre-colonial Hong Kong has always been assigned the mission of developing students' cultural identity in addition to the development of linguistic proficiency. During the colonial period, the Chinese Language curriculum shifted to be more language skills based with less emphasis on Chinese culture and moral education. After the sovereignty of Hong Kong was returned to China in 1997, although a new curriculum was implemented in 2002, teaching and learning in school as well as public examinations seem to be remaining language skills oriented instead of culturally based. This deviation from the trend of both Chinese traditional education and global mother tongue language education makes some Chinese language teachers feel confused. In addition, there is comment that in general Hong Kong students' Chinese language proficiency is becoming weaker and weaker in recent years. Thus, effectiveness of the skills oriented language curriculum has come under question. How a language teacher views the aims and objectives of the language subject he or she is teaching has a direct effect on the curriculum delivery and pedagogies used. It is, therefore, important to investigate what is the language teachers' perception of MTL education, and whether the current school curriculum can meet the teachers' expectation as well as achieve the aims of MTL education. Given this context, this study explored the views of Hong Kong Chinese language teachers on MTL education. The data indicate that teachers showed a strong resentment towards the current curriculum. Results may have implications on mother tongue language curriculum development.

Keywords: Chinese language education, curriculum development, mother tongue language education, teachers' perception

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Authors: Roselyn Alejandro-Ymana

Abstract:

The study was an attempt to assess the MTAP Saturday Class Program along its eight components namely, modules, instructional materials, scheduling, trainer-teachers, supervisory support, administrative support, financial support and educational facilities, the results of which served as bases in developing policy guidelines to enhance the MTAP Saturday Class Program. Using a descriptive development method of research, this study involved the participation of twenty-eight (28) schools with MTAP Saturday Class Program in the Division of Dasmarinas City where twenty-eight school heads, one hundred twenty-five (125) teacher-trainer, one hundred twenty-five (125) pupil program participants, and their corresponding one hundred twenty-five (125) parents were purposively drawn to constitute the study’s respondent. A self-made validated survey questionnaire together with Pre and Post-Test Assessment Test in Mathematics for pupils participating in the program, and an unstructured interview guide was used to gather the data needed in the study. Data obtained from the instruments administered was organized and analyzed through the use of statistical tools that included the Mean, Weighted Mean, Relative Frequency, Standard Deviation, F-Test or One-Way ANOVA and the T-Test. Results of the study revealed that all the eight domains involved in the MTAP Saturday Class Program were practiced with the areas of 'trainer-teachers', 'educational facilities', and 'supervisory support' identified as the program’s strongest components while the areas of 'financial support', 'modules' and 'scheduling' as being the weakest program’s components. Moreover, the study revealed based on F-Test, that there was a significant difference in the assessment made by the respondents in each of the eight (8) domains. It was found out that the parents deviated significantly from the assessment of either the school heads or the teachers on the indicators of the program. There is much to be desired when it comes to the quality of the implementation of the MTAP Saturday Class Program. With most of the indicators of each component of the program, having received overall average ratings that were at least 0.5 point away from the ideal rating 5 for total quality, school heads, teachers, and supervisors need to work harder for total quality of the implementation of the MTAP Saturday Class Program in the division.

Keywords: mathematics achievement, MTAP program, policy guidelines, program assessment

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Authors: Sima Modirkhamene, Arezoo Khezri

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The purpose of the present investigation was to probe the main motivational strategies Iranian school vs. institute teachers use in virtual and in-person classes to motivate students in learning the English language. Yet another purpose was to understand teachers’ perceptions about any modifications in their use of motivational strategies before and during/after the pandemic. For the purpose of this investigation, a total of 63 EFL teachers (35 female, 28 male) were conveniently sampled from schools and institutes in the cities of Mahabad and Sardasht. Moreover, for the interview phase of the study, 20 percent (n=16) of the sample was selected conveniently. The required data was gathered through a modified questionnaire (Cheng & Dornyei, 2007) consisting of 42 items and a set of semi-structured interviews. The outcomes of a set of non-parametric Mann-Whitney U tests demonstrated that presenting tasks properly in online classes and familiarizing learners with L2- related values in in-person classes came out as the most influential source of motivational strategies practiced by EFL school teachers. Additionally, it was found that proper teacher behavior(showing enthusiasm) in both in-person and virtual classes and presenting tasks properly in in-person classes were overwhelmingly endorsed by EFL institute teachers. The study also portrayed no statistically significant mean difference between school and institute EFL teachers’ overall use of motivational strategies in virtual and in-person classes. The interview results indicated that the strategies of designing tasks through technological aids, provision of videos, gamification techniques, assigning projects, and delivering formative online feedback were held in high regard during/after the pandemic due to the high reliance of teaching on the Internet connection. Meanwhile, the research has indicated that the spread of COVID-19 was the main reason for teachers’ modifications in motivational strategies, in response to the crisis of the pandemic, all educational contexts at all levels resorted to online education as a result their strategies were adapted to the new situation. The findings brought to light through this investigation provided initial evidence of the unintended consequences of the pandemic on teachers’ strategic choices. Therefore, to deliver a better education for the future, the study suggests more concentration on the quality of teaching as well as reframing the status quo of teaching .

Keywords: virtual teaching, motivational teaching strategies, teaching context, online education

Procedia PDF Downloads 49