Search results for: learning from history

Authors: Nathenal Thomas Lambamo

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Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

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Authors: Saed Khawaldeh, Mohamed Elsharnouby, Alaa Eddin Alchalabi, Usama Pervaiz, Tajwar Aleef, Vu Hoang Minh

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Taxonomic classification has a wide-range of applications such as finding out more about the evolutionary history of organisms that can be done by making a comparison between species living now and species that lived in the past. This comparison can be made using different kinds of extracted species’ data which include DNA sequences. Compared to the estimated number of the organisms that nature harbours, humanity does not have a thorough comprehension of which specific species they all belong to, in spite of the significant development of science and scientific knowledge over many years. One of the methods that can be applied to extract information out of the study of organisms in this regard is to use the DNA sequence of a living organism as a marker, thus making it available to classify it into a taxonomy. The classification of living organisms can be done in many machine learning techniques including Neural Networks (NNs). In this study, DNA sequences classification is performed using Convolutional Neural Networks (CNNs) which is a special type of NNs.

Keywords: deep networks, convolutional neural networks, taxonomic classification, DNA sequences classification

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Authors: Thuy T. T. Tran, Hamish Coates, Sophie Arkoudis

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Evaluation instruments of teaching are abundant; however, these do not prompt any enhancement in the quality of teaching, not least because these instruments are framed only by teacher-centered conceptions of teaching. There is a need for more sophisticated teaching evaluation measures that focus on student learning and multi-stakeholder involvement. This study aims to develop such an evaluation instrument for Vietnamese higher education. The study uses several kinds of methods. The instrument was initially drafted through in-depth review of research, paying close attention to Vietnamese higher education. Draft evaluation instruments were produced and reviewed by 34 experts. The outcomes of this qualitative and quantitative data reveal an instrument that highlights the value of a multisource student-centered approach, and the rich integration of contextual and cultural traits where Confucian values are emphasized. The validation affirms that evaluating teaching in such way will facilitate the continuous learning growth of all stakeholders involved.

Keywords: multi stakeholders, quality teaching, student learning, teaching evaluation

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Authors: Ananya Mitra Pramanik, Anjali Agrawal

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The objective of this paper is to trace the origin and evolution of clothing in the Indian Subcontinent. The paper seeks to understand the need for mankind to shed his natural state and adopt clothing as an inseparable accessory for his body. It explores the various theories of the origin of clothing. The known journey of clothing of this region started from the Indus Valley Civilisation which dates back to 2500 BC. Due to the weather conditions of the region, few actual samples have survived, and most of the knowledge of textiles is derived from the sculptures and other remains from this era. The understanding of textiles of the period after the Indus Valley Civilisation (2500-1500 BC) till the Mauryan and the Sunga Period (321-72 BC) comes from literary sources, e.g., Vedas, Smritis, the eminent Indian epics of the Ramayana and the Mahabharata, forest books, etc. Textile production was one of the most important economic activities of this region. It was next only to agriculture. While attempting to trace the history of clothing the paper draws the evolution of Indian traditional fashion through the change of rulers of this region and the development of the modern Indian traditional dress, i.e., sari, salwar kamiz, dhoti, etc. The major aims of the study are to define the different time periods chronologically and to inspect the major changes in textile fashion, manufacturing, and materials that took place. This study is based on secondary research. It is founded on data taken primarily from books and journals. Not much of visuals are added in the paper as actual fabric references are near nonexistent. It gives a brief history of the ancient textiles of India from the time frame of 2500 BC-8th C AD.

Keywords: evolution, history, origin, textiles

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Authors: Niall J. English

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Under- and post-graduate training can benefit from a more active learning style, and most particularly so in engineering. Despite this, outreach to young children in primary and secondary schools is less-developed in terms of its documented effectiveness, especially given new emphasis placed within the third level and advanced research program’s on Education and Public Engagement (EPE). Bearing this in mind, outreach and school visits form the basis to ascertain how active learning, careers stimulus and EPE initiatives for young children can inform the university sector, helping to improve future engineering-teaching standards, and enhancing both quality and practicalities of the teaching-and-learning experience. Indeed, engineering-education EPE/outreach work has been demonstrated to lead to several tangible benefits and improved outcomes, such as greater engagement and interest with science/engineering for school-children, careers awareness, enabling teachers with strong contributions to technical knowledge of engineering subjects, and providing development of general professional skills for engineering, e.g., communication and teamwork. This intervention involved active learning in ‘buzz’ groups for young children of concepts in gas engineering, observing their peer interactions to develop university-level lessons on activity learning. In addition, at the secondary level, careers-outreach efforts have led to statistical determinations of motivations towards engineering education and training, which aids in the redesign of engineering curricula for more active learning.

Keywords: outreach, education and public engagement, careers, peer interactions

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Authors: Alex Lundy

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As the suburban landscape has evolved over time, it has been slowly stripped down to the absolute bare essentials of housing. This has resulted in the loss of core elements of the built environment which previously supported community no longer being present in most neighborhoods. As a result, this work will explore how current and past designers have successfully introduced these concepts in similar settings, in an effort to re-implement them into the contemporary subdivision. Ultimately, this will result in a reimagining suburban design through elements like identity, adaptability, place, and social spaces to improve community interaction and cohesion. Overall, this thesis asserts that contemporary subdivisions don’t support the growing need for community in daily life and should be improved through the implementation of historical neighborhood design and select modern urban concepts to better suit living needs.

Keywords: suburbia, community, social connection, identity, adaptability, neighborhood, place, unity, leasure, social ties, third place, learning from history

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Authors: M. Duran Toksari, Berrin Ucarkus

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In this paper, we propose two algorithms to optimally solve makespan and total completion time scheduling problems with learning effect and job dependent delivery times in a single machine environment. The delivery time is the extra time to eliminate adverse effect between the main processing and delivery to the customer. In this paper, we introduce the job dependent delivery times for some single machine scheduling problems with position dependent learning effect, which are makespan are total completion. The results with respect to two algorithms proposed for solving of the each problem are compared with LINGO solutions for 50-jobs, 100-jobs and 150-jobs problems. The proposed algorithms can find the same results in shorter time.

Keywords: delivery Times, learning effect, makespan, scheduling, total completion time

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Authors: Masud Karim, Md. Solaiman Mia, Saifuddin Md. Tareeq, Md. Hasanuzzaman

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Autism Spectrum Disorder (ASD) is a neurodevelopment disorder. Such disorder is found in childhood life. Children with ASD have less capabilities in communication and social skills. Therapies are used to develop communication and social skills. Recently researchers have been trying to use robots in such therapies. In this paper, we have presented social skill learning test cases for children with ASD. Autism conditions are measured in 30 children in a special school. Among them, twelve children are selected who have equal ASD conditions. Then six children participated in training with humans, and another six children participated in training with robots. The learning session continued for one week and three hours each day. We have taken an assessment test before the learning sessions. After completing the learning sessions, we have taken another assessment test. We have found better performances from children who have participated in robotic sessions rather than the children who have participated in human sessions.

Keywords: children with ASD, NAO robot, human-robot interaction, social skills

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Authors: Kafi Razzaq Ahmed

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Speaking fluently in a second language requires vocabulary, grammar, and pronunciation skills. Teaching the English language entails teaching pronunciation. In professional literature, there have been a lot of attempts to integrate technology into improving the pronunciation of learners. The technique is also neglected in Kurdish contexts, Salahaddin University – Erbil included. Thus, the main aim of the research is to point out the efficiency of using video materials for both language teachers and learners within and beyond classroom learning and teaching environments to enhance student's pronunciation. To collect practical data, a research project has been designed. In subsequent research, a posttest will be administered after each lesson to 100 first-year students at Salahaddin University-Erbil English departments. All students will be taught the same material using different methods, one based on video materials and the other based on the traditional approach to teaching pronunciation. Finally, the results of both tests will be analyzed (also knowing the attitudes of both the teachers and the students about both lessons) to indicate the impact of using video in the process of teaching and learning pronunciation.

Keywords: video, pronunciation, teaching, learning

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Authors: S. J. Ha, S. J. Baik, T. O. Kim, S. W. Han

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For computing the seismic responses of structures, current seismic design provisions permit response history analyses (RHA) that can be used without limitations in height, seismic design category, and building irregularity. In order to obtain accurate seismic responses using RHA, it is important to use adequate input ground motions. Current seismic design provisions provide criteria for selecting ground motions. In this study, the accurate and computationally efficient algorithm is proposed for accurately selecting ground motions that satisfy the requirements specified in current seismic design provisions. The accuracy of the proposed algorithm is verified using single-degree-of-freedom systems with various natural periods and yield strengths. This study shows that the mean seismic responses obtained from RHA with seven and ten ground motions selected using the proposed algorithm produce errors within 20% and 13%, respectively.

Keywords: algorithm, ground motion, response history analysis, selection

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Authors: Natalie Frandsen

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Pursuing post-secondary education is a milestone for many Canadian youths. This transition involves many changes and opportunities for growth. However, this may also be a period where challenges arise. Perhaps not surprisingly, mental health challenges for post-secondary students are common. This poses difficulties for students and instructors. Common mental-health-related symptoms (e.g., low motivation, fatigue, inability to concentrate) can affect academic performance, and instructors may need to provide accommodations for these students without the necessary expertise. ‘Distance education’ has been growing and gaining momentum in Canada for three decades. As a consequence of the COVID-19 pandemic, post-secondary institutions have been required to deliver courses using ‘remote’ methods (i.e., various online delivery modalities). The learning challenges and subsequent academic performance issues experienced by students with mental-health-related disabilities studying online are not well understood. However, we can postulate potential factors drawing from learning theories, the relationship between mental-health-related symptoms and academic performance, and learning design. Identifying barriers and opportunities to academic performance is an essential step in ensuring that students with mental-health-related disabilities are able to achieve their academic goals. Completing post-secondary education provides graduates with more employment opportunities. It is imperative that our post-secondary institutions take a holistic view of learning by providing learning and mental health support while reducing structural barriers. Health-promoting universities and colleges infuse health into their daily operations and academic mandates. Acknowledged in this Charter is the notion that all sectors must take an active role in favour of health, social justice, and equity for all. Drawing from mental health promotion and Universal Design for Learning (UDL) frameworks, relevant adult learning concepts, and critical digital pedagogy, considerations for mental-health-promoting, online learning community development will be summarized. The education sector has the opportunity to create and foster equitable and mental health-promoting learning environments. This is of particular importance during a global pandemic when the mental health of students is being disproportionately impacted.

Keywords: academic performance, community, mental health promotion, online learning

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Authors: Fariha Asif

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The Saudi EFL learners face a number of problems in EFL learning, anxiety is the most potent one among those. It means that its resolution can lead to better language skills in Saudi students. That’s why, the study is carried out and is considered to be of interest to the Saudi language learners, educators and the policy makers because of the potentially negative impact that anxiety has on English language learning. The purpose of the study is to explore the factors that cause language anxiety in the Saudi EFL learners while learning speaking skills and the influence it casts on communication in the target language. The investigation of the anxiety-producing factors that arise while learning to communicate in the target language will hopefully broaden the insight into the issue of language anxiety and will help language teachers in making the classroom environment less stressful. The study seeks to answer the questions such as what are the psycholinguistic factors that cause language anxiety among ESL/EFL learners in learning and speaking English Language, especially in the context of the Saudi students. What are the socio-cultural factors that cause language anxiety among Saudi EFL learners in learning and speaking English Language? How is anxiety manifested in the language learning of the Saudi EFL learners? And which strategies can be used to successfully cope with language anxiety? The scope of the study is limited to the college and university English Teachers and subject specialists (males and females) in public sectors colleges and universities in Saudi Arabia. Some of the key findings of the study are:, Anxiety plays an important role in English as foreign language learning for the Saudi EFL learners. Some teachers believe that anxiety bears negatives effects for the learners, while some others think that anxiety serves a positive outcome for the learners by giving them an extra bit of motivation to do their best in English language learning. Language teachers seem to have consensus that L1 interference is one of the major factors that cause anxiety among the Saudi EFL learners. Most of the Saudi EFL learners are found to have fear of making mistakes. They don’t take initiative and opt to keep quiet and don’t respond fearing that they would make mistakes and this would ruin their image in front of their peers. Discouraging classroom environment is also counted as one of the major anxiety causing factors. The teachers, who don’t encourage learners positively, make them anxious and they start avoiding class participation. It is also found that English language teachers have their important role to minimize the negative effects of anxiety in the classes. The teachers’ positive encouragement can do wonders in this regard. A positive, motivating and encouraging class environment is essential to produce desired results in English language learning for the Saudi EFL learners.

Keywords: factors, psychology, speaking, EFL

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Authors: Krishang Surapaneni

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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

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Authors: Iman I. Salama, Samia M. Sami, Somaia I. Salama, Zeinab N. Said, Thanaa M. Rabah, Aida M. Abdel-Mohsin

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This is a national community-based project to evaluate the effectiveness of HBV vaccination program in prevention of infection. HBV markers were tested in the sera of 3600 vaccinated children. Infected children were followed up for 1 year. Prevalence of HBV infection was 0.39 % (0.28% positive for anti-HBc, 0.03% positive for HBsAg and 0.08% positive for both). One year later, 50% of positive anti-HBc children turned negative with sustained positivity for positive HBsAg cases. HBV infection was significantly higher at age above 9 years (0.6%) compared to 0.2% at age 3-9 years and 0% at younger age (P < 0.05). Logistic analysis revealed that predictors for HBV infection were history of blood transfusion, regular medical injection, and family history of either HBV infection or drug abuse (adjusted odds ratios 6.2, 5.6, 7.6 & 19.1 respectively). HBV vaccination program produced adequate protection. Adherence to infection control measures and safe blood transfusion are recommended.

Keywords: HBV infection, HBV vaccine, children, Egypt

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Authors: Dulanjali Ranasinghe, Isuru Supasan, Kaushalya Premachandra, Ranjan Dissanayake, Ajith Rajapaksha, Eustace Fernando

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Proteomics studies of organisms are considered to be significantly information-rich compared to their genomic counterparts because proteomes of organisms represent the expressed state of all proteins of an organism at a given time. In modern top-down and bottom-up proteomics workflows, the primary analysis methods employed are gel–based methods such as two-dimensional (2D) electrophoresis and mass spectrometry based methods. Machine learning (ML) and artificial intelligence (AI) have been used increasingly in modern biological data analyses. In particular, the fields of genomics, DNA sequencing, and bioinformatics have seen an incremental trend in the usage of ML and AI techniques in recent years. The use of aforesaid techniques in the field of proteomics studies is only beginning to be materialised now. Although there is a wealth of information available in the scientific literature pertaining to proteomics workflows, no comprehensive review addresses various aspects of the combined use of proteomics and machine learning. The objective of this review is to provide a comprehensive outlook on the application of machine learning into the known proteomics workflows in order to extract more meaningful information that could be useful in a plethora of applications such as medicine, agriculture, and biotechnology.

Keywords: proteomics, machine learning, gel-based proteomics, mass spectrometry

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Authors: Qura-tul-aain Khair

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Purpose- The purpose of this paper is to empirically examining the strength of association of responsive market orientation and proactive market orientation with new product performance and exploring the possible moderating role of organizational learning based on contingency theory. Design/methodology/approach- Data for this study was collected from FMCG manufacturing industry and services industry, where customers are in contact frequently and responses are recorded on continuous basis. Sample was collected through convenience sampling. The data collected from different marketing department and sales personnel were analysed using SPSS 16 version. Findings- The paper finds that responsive market orientation is more strongly associated with new product performance. The moderator, organizational learning, plays it significant role on the relationship between responsive market orientation and new product performance. Research limitations/implications- this paper has taken sample from just FMCG industry and service industry, more work can be done regarding how different-markets require different market orientation behaviours. Originality/value- This paper will be useful for foreign business looking for investing and expanding in Pakistan, they can find opportunity to get sustained competitive advantage through exploring the proactive side of market orientation and importance of organizational learning.

Keywords: organizational learning, proactive market orientation, responsive market orientation, new product performance

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Authors: Shairn Hollis-Turner

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The changing demands of workplace practice in the field of business information and administration have placed considerable pressure on educators to prepare students for the world of work. In this paper, we argue that appropriate forms of work-integrated learning (WIL) could enhance learning experiences in higher education and support educators to meet industry needs for changing times. The study aims to enhance business information and administration education from a practice perspective. The guiding research question is: How can a systematic understanding of work-integrated learning practices enhance learning experiences in higher education? The research design comprised comparative case studies across three countries and was framed by Activity Theory. Analysis of the findings highlighted the similarities across WIL systems for higher education practices and the differences within the activity systems. The findings showed similarities in program practice, content, placement, and in the struggles of students to find placements. The findings also showed misalignments between WIL preparation, delivery, and future focus of WIL at these institutions. The findings suggest that employment requirements vary across countries and that systems could be improved to meet the demands of workplace practice for changing times for the benefit of students’ learning and employability.

Keywords: business administration, business information, knowledge, post graduate diploma

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Authors: S. Vijayakumar, S. B. Rathna Kumar, Navnath D Jagadale

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Learning and teaching are the challenges ahead in the education of the students with hearing impairment using sign language (SHISL). Either the students or teachers face difficulties in the process of learning/teaching. Communication is one of the main barriers while teaching SHISL. Further, the courses of study or the subjects are limited to SHISL at least in countries like India. Students with hearing impairment mainly opt for sign language as a communication mode. Subjects like physics, chemistry, advanced mathematics etc. are not available in the curriculum for the SHISL since their content and ideas are complex. In India, exemption for language papers is being given for the students with hearing impairment. It may give opportunity to them to secure secondary/ higher secondary qualifications. It is a known fact that students with hearing impairment are facing difficulty in their future carrier. They secure neither a higher study nor a good employment opportunity. Vocational training in various trades will land them in few jobs with few bucks in pocket. However, not all of them are blessed with higher positions in government or private sectors in competitive fields or where the technical knowledge is required. E learning with sign language instructions can be used for teaching languages and science subjects. Computer Based Instruction (CBI), Computer Based Training (CBT), and Computer Assisted Instruction (CAI) are now part-and-parcel of Modern Education. It will also include signed video clip corresponding to the topic. Learning language subjects will improve the understanding of concepts in different subjects. Learning other science subjects like their hearing counterparts will enable the SHISL to go higher in studies and increase their height to pluck a fruit of the tree of employment.

Keywords: students with hearing impairment using sign language, hearing impairment, language subjects, science subjects, e-learning

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Authors: Narupot Putwattana

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Changes in global situation such as environmental and economic crisis brought the new perspective for science education called integrative biology. STEM has been increasingly mentioned for several educational researches as the approach which combines the concept in Science (S), Technology (T), Engineering (E) and Mathematics (M) to apply in teaching and learning process so as to strengthen the 21st-century skills such as creativity and critical thinking. Recent studies demonstrated STEM as the pedagogy which described the engineering process along with the science classroom activities. So far, pedagogical contents for STEM explaining the content in biology have been scarce. A qualitative literature review was conducted so as to gather the articles based on electronic databases (google scholar). STEM education, engineering design, teaching and learning of biology were used as main keywords to find out researches involving with the application of STEM in biology teaching and learning process. All articles were analyzed to obtain appropriate teaching and learning model that unify the core concept of biology. The synthesized model comprised of engineering design, inquiry-based learning, biological prototype and biologically-inspired design (BID). STEM content and context integration were used as the theoretical framework to create the integrative biology instructional model for STEM education. Several disciplines contents such as biology, engineering, and technology were regarded for inquiry-based learning to build biological prototype. Direct and indirect integrations were used to provide the knowledge into the biology related STEM strategy. Meanwhile, engineering design and BID showed the occupational context for engineer and biologist. Technological and mathematical aspects were required to be inspected in terms of co-teaching method. Lastly, other variables such as critical thinking and problem-solving skills should be more considered in the further researches.

Keywords: biomimicry, engineering approach, STEM education, teaching and learning model

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Authors: Aloysius Hardoko, Susilo

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The root cause of environmental damage post coal mining activities as determined by the province of East Kalimantan as a corridor of economic activity masterplan acceleration of economic development expansion (MP3EI) is the behavior of adults. Adult behavior can be changed through knowledge management and attitude. Based on the root of the problem, the objective of the research is to apply knowledge management and attitude based on holistic approach in learning andragogy as an effort to solve environmental problems after coal mining activities. Research methods to achieve the objective of using quantitative research with pretest posttest group design. Knowledge management and attitudes based on a holistic approach in adult learning are applied through initial learning activities, core and case-based cover of environmental damage. The research instrument is a description of the case of environmental damage. The data analysis uses t-test to see the effect of knowledge management attitude based on holistic approach before and after adult learning. Location and sample of representative research of adults as many as 20 people in Kutai Kertanegara District, one of the districts in East Kalimantan province, which suffered the worst environmental damage. The conclusion of the research result is the application of knowledge management and attitude in adult learning influence to adult knowledge and attitude to overcome environmental problem post coal mining activity.

Keywords: knowledge management and attitude, holistic approach, andragogy learning, environmental damage

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Authors: Timothy Wale Olaosebikan

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The adverse effect of the Covid-19 outbreak and lock-downs on the world economy has coursed a major disrupt in mostly all sectors. The educational sector is not exempted from this disruption as it is one of the most affected sectors in the world. Similarly, most developing countries are still struggling to adopt/ adapt with the 21st-century advancement of technology, which includes e-learning/ e-education. Furthermore, one is left to wonder of the possibility of these countries surviving this disruption on their various educational systems that may no longer be business as usual after the Covid Pandemic era. This study evaluates the e-learning process of educational systems, especially in developing countries. The collection of data for the study was effected through the use of questionnaires with sampling drawn by stratified random sampling. The data was analyzed using descriptive and inferential statistics. The findings of the study show that about 30% of developing countries have fully adopted the e-learning system, about 45% of these countries are still struggling to upgrade while about 25% of these countries are yet to adopt the e-learning system of education. The study concludes that the sudden closure of educational institutions around the world during the Covid Pandemic period should facilitate a teaching pedagogy of e-learning and virtual delivery of courses and programmes in these developing countries. If this approach can be fully adopted, schools might have to grapple with the initial teething problems, given the sudden transition just in order to preserve the welfare of students. While progress should be made to transit as the case may be, lectures and seminars can be delivered through the web conferencing site-zoom. Interestingly, this can be done on a mobile phone. The demands of this approach would equally allow lecturers to make major changes to their work habits, uploading their teaching materials online, and get to grips with what online lecturing entails. Consequently, the study recommends that leaders of developing countries, regulatory authorities, and heads of educational institutions must adopt e-learning into their educational system. Also, e-learning should be adopted into the educational curriculum of students, especially from elementary school up to tertiary level. Total compliance to the e-learning system must be ensured on the part of both the institutions, stake holders, lecturers, tutors, and students. Finally, collaborations with developed countries and effective funding for e-learning integration must form the heart of their cardinal mission.

Keywords: Covid pandemic, developing countries, educational system, e-learning

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: M. M. Sadeghi, S. Vahdani

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Masonry dome structures had been widely used for covering large spans in the past. The seismic assessment of these historical structures is very complicated due to the nonlinear behavior of the material, their rigidness, and special stability configuration. The assessment method based on energy balance concept, as well as the standard pushover analysis, is used to evaluate the effectiveness of these methods in the case of masonry dome structures. The Soltanieh dome building is used as an example to which two methods are applied. The performance points are given from superimposing the capacity, and demand curves in Acceleration Displacement Response Spectra (ADRS) and energy coordination are compared with the nonlinear time history analysis as the exact result. The results show a good agreement between the dynamic analysis and the energy balance method, but standard pushover method does not provide an acceptable estimation.

Keywords: energy balance method, pushover analysis, time history analysis, masonry dome

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Authors: Shan-Ken Chien

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This research aims to share the application of the Music and Narrative Curriculum developed through a college community service-learning course to a special education classroom in a local secondary school. The development of the Music and Narrative Curriculum stems from the music appreciation courses that the author has taught at the university. The curriculum structure consists of three instructional phases, each with three core literacy. This study will show the implementation of an eighteen-week general music education course, including classroom training on the university campus and four intervention music lessons in a special education classroom. Students who participated in the Music and Narrative Curriculum came from two different parts. One is twenty-five college students enrolling in Music Literacy and Community Service-Learning, and the other one is nine junior high school students with intellectual disabilities (ID) in a special education classroom. This study measures two parts. One is the effectiveness of the Music and Narrative Curriculum in applying four interventions in music lessons in a special education classroom, and the other is measuring college students' service-learning experiences and growth outcomes.

Keywords: college service-learning, general music education, music literacy, narrative skills, students with special needs

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Authors: Tharwat N. Hijjawi

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Learning oral skills in an Arabic speaking environment is challenging. A blended course (material, activities, and individual/ group work tasks …) was implemented in a module of level B1 for undergraduate students of French as a foreign language in order to increase their opportunities to practice listening and speaking skills. This research investigates the influence of this modality on enhancing active learning and examines the effectiveness of provided strategies. Moreover, it aims at discovering how it allows teacher to flip the traditional classroom and create a learner-centered framework. Which approaches were integrated to motivate students and urge them to search, analyze, criticize, create and accomplish projects? What was the perception of students? This paper is based on the qualitative findings of a questionnaire and a focus group interview with learners. Despite the doubled time and effort both “teacher” and “student” needed, results revealed that the NTIC allowed a shift into a learning paradigm where learners were the “chiefs” of the process. Tasks and collaborative projects required higher intellectual capacities from them. Learners appreciated this experience and developed new life-long learning competencies at many levels: social, affective, ethical and cognitive. To conclude, they defined themselves as motivated young researchers, motivators and critical thinkers.

Keywords: active learning, critical thinking, inverted classroom, learning paradigm, problem-based

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Authors: Efleda Preclaro Tolentino

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Research indicates that an educator’s belief system is reflected in the way they structure the learning environment. Their values and belief system have the potential to positively impact school readiness through an understanding of children’s development and the creation of a stable, motivating environment. Based on the premise that the social environment influences the development of social skills, knowledge construct, and shared values of young children, this study examined verbal and nonverbal exchanges between early childhood teachers and their preschool students within the context of remote learning. Using the qualitative method of data collection, the study determined the nature of interactions between preschoolers and their teachers within a remote learning environment at a preschool in Southeast Asia that utilized the Mother Tongue-based Multilingual Education (MTBMLE) Approach. From the lens of sociocultural theory, the study investigated preschoolers’ use of literacies to convey meaning and to interact within a remote learning environment. Using a Strengths Perspective, the study revealed the creativity and resourcefulness of preschoolers in expressing themselves through trans-literacies that were made possible by the use of online mode of learning within cultural and subcultural norms. The study likewise examined how social skills acquired by young children were transmitted (verbally or nonverbally) in their interactions with peers during Zoom meetings. By examining the dynamics of social exchanges between teachers and children, the findings of the study underscore the importance of providing support for preschool students as they apply acquired values and shared practices within a remote learning environment. The potential of distance learning in the early years will be explored, specifically in supporting young children’s language and literacy development. At the same time, the study examines the role of teachers as cultivators of trans-literacies. The teachers’ skillful use of technology in facilitating young children’s learning, as well as in supporting interactions with families, will be examined. The findings of this study will explore the potential of distance learning in early childhood education to establish continuity in learning, supporting young children’s social and emotional transitions, and nurturing trans-literacies that transcend prevailing definitions of learning contexts. The implications of teachers and parents working collaboratively to support student learning will be examined. The importance of preparing teachers to be resourceful, adaptable, and innovative to ensure that learning takes place across a variety of modes and settings will be discussed.

Keywords: transliteracy, preschoolers, remote learning, strengths perspective

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Authors: Peeyush Verma, Anil Kumar, Anju Rawlley, Chanchal Mehra

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India's school-going population is largely served by an educational system that is, in most rural parts, stuck with methods that emphasize rote learning, endless examinations, and monotonous classroom activities. Rural government schools are generally seen as having poor infrastructure, poor support system and low motivation for teaching as well as learning. It was experienced during the survey of this project that there is lesser motivation of rural boys and girls to attend their schools and still less likely chances to study science, tabooed as “difficult”. An experiment was conducted with the help of Rural Knowledge Network Project through Department of Science and Technology, Govt of India in five remote villages of Sehore District in Madhya Pradesh (India) during 2012-2015. These schools are located about 50-70 Km away from Bhopal, the capital of Madhya Pradesh and can distinctively qualify as average rural schools. Three tier methodology was adapted to unfold the experiment. In first tier randomly selected boys and girls from these schools were taken to a daylong visit to the Regional Science Centre located in Bhopal. In second tier, randomly selected half of those who visited earlier were again taken to the Science Centre to make models of Science. And in third tier, all the boys and girls studying science were exposed to video lectures and study material through web. The results have shown an interesting face towards learning science among youths in rural schools through peer learning or incremental learning. The students who had little or no interest in learning science became good learners and queries started pouring in from the neighbourhood village as well as a few parents requested to take their wards in the project to learn science. The paper presented is a case study of the experiment conducted in five rural schools of Sehore District. It reflects upon the methodology of developing awareness and interest among students and finally engaging them in popularising science through peer-to-peer learning using incremental learning elements. The students, who had a poor perception about science initially, had changed their attitude towards learning science during the project period. The results of this case, however, cannot be generalised unless replicated in the same setting elsewhere.

Keywords: popularisation of science, science temper, incremental learning, peer-to-peer learning

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Authors: Joshua Osondu

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This research explores how Artificial Intelligence (AI) can be utilized as a policy response to address teaching and learning (TL) issues in education in Ghana. The dual (AI and human) instructor model is used as a theoretical framework to examine how AI can be employed to improve teaching and learning processes and to equip learners with the necessary skills in the emerging AI society. A qualitative research design was employed to assess the impact of AI on various TL issues, such as teacher workloads, a lack of qualified educators, low academic performance, unequal access to education and educational resources, a lack of participation in learning, and poor access and participation based on gender, place of origin, and disability. The study concludes that AI can be an effective policy response to TL issues in Ghana, as it has the potential to increase students’ participation in learning, increase access to quality education, reduce teacher workloads, and provide more personalized instruction. The findings of this study are significant for filling in the gaps in AI research in Ghana and other developing countries and for motivating the government and educational institutions to implement AI in TL, as this would ensure quality, access, and participation in education and help Ghana industrialize.

Keywords: artificial intelligence, teacher, learner, students, policy response

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Authors: Raja Rodziah Binti Raja Zainal Hassan

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The development of Malaysian political cinema is rapidly taking shape in the local film industry. The paper focuses on the production of independent political documentary by two Malaysian filmmakers, Amir Muhammad and Fahmi Reza. Revolutionary cinema can be understood by utilizing the Third Cinema Theory in order to analyse the meaning and its impact on the audience. The issue surrounding the political cinema in Malaysia is the question of national identity. The implementation of racial or ethnic based politics has resulted in hostility within Malaysia’s multiracial society. Amir Muhammad and Fahmi Reza revisit the Malaysian political history through their films in order to understand the reasons behind the hostility and conflict.

Keywords: Political cinema, third cinema theory, revolutionary cinema, national identity, racial or ethnic politics

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Authors: Christine K. Ormsbee, Jeremy S. Robinson

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Teacher quality is important for United States universities. It impacts student achievement, program and degree progress, and even retention. While course instructors are still the primary designers and deliverers of instruction in U.S. higher education classrooms, students have become better and more vocal consumers of instruction. They are capable of identifying what instructors do that facilitates their learning or, conversely, what instructors do that makes learning more difficult. Instructors can use students as resources as they design and implement their courses. Students have become more aware of their own learning preferences and processes and can articulate those. While it is not necessarily possible or likely that an instructor can address the widely varying differences in learning preferences represented by a large class of students, it is possible for them to employ general instructional supports that help students understand clearly the instructor's study expectations, identify critical content, efficiently commit content to memory, and develop new skills. Those learning supports include reading guides, test study guides, and other instructor-developed tasks that organize learning for students, hold them accountable for the content, and prepare them to use that material in simulated and real situations. When U.S. university teaching and learning support staff work with instructors to help them identify areas of their teaching to improve, a key part of that assistance includes talking to the instructor member's students. Students are asked to explain what the instructor does that helps them learn, what the instructor does that impedes their learning, and what they wish the instructor would do. Not surprisingly, students are very specific in what they see as helpful learning supports for them. Moreover, they also identify impediments to their success, viewing those as the instructor creating unnecessary barriers to learning. A qualitative survey was developed to provide undergraduate students the opportunity to identify instructor behaviors and/or practices that they thought helped students learn and those behaviors and practices that were perceived as hindrances to student success. That information is used to help instructors implement more student-focused learning supports that facilitate student achievement. In this session, data shared from the survey will focus on supportive instructor behaviors identified by undergraduate students in an institution located in the southwest United States and those behaviors that students perceive as creating unnecessary barriers to their academic success.

Keywords: effective teaching, pedagogy, student engagement, instructional design

Procedia PDF Downloads 85