Search results for: remote learning

Authors: Lokes Parvatha Kumaran S., Sakthi Jay Mahenthar C., Sathyaprakash P., Jayakumar V., Shobanadevi A.

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With the evolution of technology, the need to solve complex computational problems like machine learning and deep learning has shot up. But even the most powerful classical supercomputers find it difficult to execute these tasks. With the recent development of quantum computing, researchers and tech-giants strive for new quantum circuits for machine learning tasks, as present works on Quantum Machine Learning (QML) ensure less memory consumption and reduced model parameters. But it is strenuous to simulate classical deep learning models on existing quantum computing platforms due to the inflexibility of deep quantum circuits. As a consequence, it is essential to design viable quantum algorithms for QML for noisy intermediate-scale quantum (NISQ) devices. The proposed work aims to explore Variational Quantum Circuits (VQC) for Deep Reinforcement Learning by remodeling the experience replay and target network into a representation of VQC. In addition, to reduce the number of model parameters, quantum information encoding schemes are used to achieve better results than the classical neural networks. VQCs are employed to approximate the deep Q-value function for decision-making and policy-selection reinforcement learning with experience replay and the target network.

Keywords: quantum computing, quantum machine learning, variational quantum circuit, deep reinforcement learning, quantum information encoding scheme

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Authors: Elham Shirvani–Ghadikolaei, Seyed Mahdi Sajjadi

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State of the art technology has the tremendous impact on our life, in this situation education system have been influenced as well as. In this paper, tried to compare two space of learning text and hypertext with each other, and some challenges of using hypertext in religious education. Regarding the fact that, hypertext is an undeniable part of learning in this world and it has highly beneficial for the education process from class to office and home. In this paper tried to solve this question: the consequences and challenges of applying hypertext in religious education. Also, the consequences of this survey demonstrate the role of curriculum designer and planner of education to solve this problem.

Keywords: Hyper-textual, learning, religious education, learning text

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Authors: Afaf Alharbi, Qianni Zhang

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The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper introduces a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple-instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation of an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.

Keywords: attention multiple instance learning, MIL and transfer learning, histopathological slides, cancer tissue classification

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Authors: Susan Lewis

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The assessment of learning outcomes at the program level has attracted much international interest from the perspectives of quality assurance and ongoing curricular redesign and renewal. This paper examines program-level learning outcomes in the field of music and technology, an area of study that has seen an explosion in program development over the past fifteen years. The Audio Engineering Society (AES) maintains an online directory of educational institutions worldwide, yielding the most comprehensive inventory of programs and courses in music and technology. The inventory includes courses, programs, and degrees in music and technology, music and computer science, music production, and the music industry. This paper focuses on published student learning outcomes for undergraduate degrees in music and technology and analyses commonalities at institutions in North America, the United Kingdom, and Europe. The results of a survey of student learning outcomes at twenty institutions indicates a focus on three distinct student learning outcomes: (1) cross-disciplinary knowledge in the fields of music and technology; (2) the practical application of training through the professional industry; and (3) the acquisition of skills in communication and collaboration. The paper then analyses assessment mechanisms for tracking student learning and achievement of learning outcomes at these institutions. The results indicate highly variable assessment practices. Conclusions offer recommendations for enhancing assessment techniques and better communicating learning outcomes to students.

Keywords: quality assurance, student learning; learning outcomes, music and technology

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Authors: Petros Roussos

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The present study focused on students' statistical reasoning related to Null Hypothesis Statistical Testing and p-values. Its objective was to test the hypothesis that neither the place (classroom, at a distance, online) nor the medium that actually supports the learning (ICT, internet, books) has an effect on understanding of statistical concepts. In addition, it was expected that students' attitudes towards statistics would not predict understanding of statistical concepts. The sample consisted of 385 undergraduate and postgraduate students from six state and private universities (five in Greece and one in Cyprus). Students were administered two questionnaires: a) the Greek version of the Survey of Attitudes Toward Statistics, and b) a short instrument which measures students' understanding of statistical significance and p-values. Results suggest that attitudes towards statistics do not predict students' understanding of statistical concepts, whereas the medium did not have an effect.

Keywords: attitudes towards statistics, blended learning, e-learning, statistical reasoning

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Authors: Golovchun Aleftina, Dabyltayeva Raikhan

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Nowadays, in the world of widely developing cross-cultural interactions and rapidly changing demands of the global labor market, foreign language teaching and learning has taken a special role not only in school education but also in everyday life. Cognitive Lingua-Cultural Methodology of Foreign Language Teaching originated in Kazakhstan brings a communicative approach to the forefront in foreign language teaching that gives raise a variety of techniques to make the language learning a real communication. One of these techniques is Computer Assisted Language Learning. In our article, we aim to: demonstrate what learning benefits students are likely to get by teachers having implemented computer-based technologies into foreign language teaching process; prove that technology-based classroom serves as the best tool for interactive and efficient language learning; give examples of classroom sufficient organization with computer-based activities.

Keywords: computer assisted language learning, learning benefits, foreign language teaching process, implementation, communicative approach

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Authors: Hector Barrios-Piña, Georgia García-Arellano, Salvador García-Rodríguez, Gerardo Bocanegra-García, Shashi Kant

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This work shows the methodology of application and the effectiveness of the Flipped Learning technique for Civil Engineering laboratory classes. It was experimented by some of the professors of the Department of Civil Engineering at Tecnológico de Monterrey while teaching their laboratory classes. A total of 28 videos were created. The videos primarily demonstrate instructions of the experimental practices other than the usage of tools and materials. The technique allowed the students to prepare for their classes in advance. A survey was conducted on the participating professors and students (semester of August-December 2019) to quantify the effectiveness of the Flipped Learning technique. The students reported it as an excellent way of improving their learning aptitude, including self-learning whereas, the professors felt it as an efficient technique for optimizing their class session, which also provided an extra slot for class-interaction. A comparison of grades was analyzed between the students of the traditional classes and with Flipped Learning. It did not distinguish the benefits of Flipped Learning. However, the positive responses from the students and the professors provide an impetus for continuing and promoting the Flipped Learning technique in future classes.

Keywords: flipped learning, laboratory classes, civil engineering, competences development

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Authors: Fani Firmahandari

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The development learning module physics based on guided inquiry approach on model cooperative learning type STAD (Student Team Achievement Division) in the main subject of temperature and heat. The research development aimed to produce physics learning module based on guided cooperative learning type STAD (Student Team Achievement Division) in the main subject of temperature and heat to the student in X class. The research method used Research and Development approach. The development procedure of this module includes potential problems, data collection to meet the need, product design, and feasibility of this module. The impact of learning can be seen or observed clearly when the learning process takes place, the teachers or the students already implemented measures cooperative learning model type STAD, so that the learning process goes well, the interaction of teachers and students, students with student looks good, besides that students can interact and work together in group.

Keywords: cooperative learning type STAD (student team achievement division), development, inquiry, interaction students

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Authors: M. H. Yee, J. Md Yunos, W. Othman, R. Hassan, T. K. Tee, M. M. Mohamad

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The generation of an idea that goes through several phases is affected by individual factors, interests, preferences and motivation. The purpose of this research was to analyze the difference in difficulties of generating ideas according to individual learning styles. A total of 375 technical students from four technical universities in Malaysia were randomly selected as samples. The Kolb Learning Styles Inventory and a set of developed questionnaires were used in this research. The results showed that the most dominant learning style is among technical students is Doer. A total of 319 (85.1%) technical students faced difficulties in solving individual assignments. Most of the problem faced by technical students is the difficulty of generating ideas for solving individual assignments. There was no significant difference in difficulties of generating ideas according to students’ learning styles. Therefore, students need to learn higher order thinking skills enabling students to generate ideas and consequently complete assignments.

Keywords: difference, difficulties, generating idea, learning styles, Kolb Learning Styles Inventory

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Authors: Du T. Tran, Quyen T. L. Hoang

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The role of language learning strategies in second language acquisition has received increased attention across several disciplines in recent years. Language learning strategies have been shown to occur in many studies over the passing years with the aim of improving the efficiency of language learning. Following previous studies, this study endeavors to scrutinize language learning strategies employed by the students at Vo Minh Duc high school and the effect of motivation on students’ learning strategy choices. The responses are examined quantitatively and qualitatively to enhance their validity and reliability. Data are collected from 342 students’ responses to the questionnaire, interviews with ten teachers and fifteen students, and classroom observations. The findings reveal that students’ motivation has an enormous impact on the choice of language learning strategies. The results simultaneously show that students use many language learning strategies to enhance their communicative competence, but the most frequently used ones are cognitive and affective ones. Significant correlations among types of learning strategies and the influence of motivation on the choices of language learning strategies were consistent with previous studies. The study’s results are expected to be beneficial to teachers of English and students in terms of narrowing the gap between the students' language learning strategies and their teaching methodologies preferences and sketching out the best strategies to enhance students’ speaking skills. The implications of these findings and the importance of viewing learners holistically are discussed, and recommendations are made for ongoing research.

Keywords: learning strategies, speaking skills, memorization strategies, cognitive strategies, affective strategies

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Authors: C. Maphosa, Ndileleni Mudzielwana, Lufuno Phillip Netshifhefhe

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In line with established mission and vision, a university articulates its focus and purpose of existence. The conduct of business in a university should be for the furtherance of the mission and vision. Teaching and learning should play a pivotal role in driving the purpose of a university. In this paper, the researchers examine how service learning could be significant in driving the purpose of a rural-based university whose focus is to promote rural development. The importance of institutions’ vision and mission statement is explored and the vision and mission of the said university examined closely. The concept rural development and the contribution of a university in its promotion is discussed. Service learning as a teaching and learning approach is examined and its significance in driving the purpose of a rural-based university explained.

Keywords: relevance, differentiation, purpose, teaching, learning

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Authors: Hy Dang, Bo Mei

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The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: classification, machine learning, time representation, stock prediction

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Authors: Diego Tancara, Raul Coto, Ariel Norambuena, Hoseein T. Dinani, Felipe Fanchini

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Quantum machine learning is a growing research field that aims to perform machine learning tasks assisted by a quantum computer. Kernel-based quantum machine learning models are paradigmatic examples where the kernel involves quantum states, and the Gram matrix is calculated from the overlapping between these states. With the kernel at hand, a regular machine learning model is used for the learning process. In this paper we investigate the quantum support vector machine and quantum kernel ridge models to predict the degree of non-Markovianity of a quantum system. We perform digital quantum simulation of amplitude damping and phase damping channels to create our quantum dataset. We elaborate on different kernel functions to map the data and kernel circuits to compute the overlapping between quantum states. We observe a good performance of the models.

Keywords: quantum, machine learning, kernel, non-markovianity

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Authors: Zhuang Hou, Xiaolei Cao

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The general public and medical professionals recognized the importance of accurately measuring and storing blood oxygen levels and heart rate during the COVID-19 pandemic. The demand for accurate contactless devices was motivated by the need for cross-infection reduction and the shortage of conventional oximeters, partially due to the global supply chain issue. This paper evaluated a contactless mini program HealthyPai’s heart rate (HR) and oxygen saturation (SpO2) measurements compared with other wearable devices. In the HR study of 185 samples (81 in the laboratory environment, 104 in the real-life environment), the mean absolute error (MAE) ± standard deviation was 1.4827 ± 1.7452 in the lab, 6.9231 ± 5.6426 in the real-life setting. In the SpO2 study of 24 samples, the MAE ± standard deviation of the measurement was 1.0375 ± 0.7745. Our results validated that HealthyPai utilizing the Integrated Image Deep Learning Solution (IIDLS) framework, can accurately measure HR and SpO2, providing the test quality at least comparable to other FDA-approved wearable devices in the market and surpassing the consumer-grade and research-grade wearable standards.

Keywords: remote photoplethysmography, heart rate, oxygen saturation, contactless measurement, mini program

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Authors: Jennifer Buz, Alvin Spivey

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The most common greenhouse gas emitted through human activities, carbon dioxide (CO2), is naturally consumed by plants during photosynthesis. This process is actively being monetized by companies wishing to offset their carbon dioxide emissions. For example, companies are now able to purchase protections for vegetated land due-to-be clear cut or purchase barren land for reforestation. Therefore, by actively preventing the destruction/decay of plant matter or by introducing more plant matter (reforestation), a company can theoretically offset some of their emissions. One of the biggest issues in the carbon credit market is validating and verifying carbon offsets. There is a need for a system that can accurately and frequently ensure that the areas sold for carbon credits have the vegetation mass (and therefore for carbon offset capability) they claim. Traditional techniques for measuring vegetation mass and determining health are costly and require many person-hours. Orbital Sidekick offers an alternative approach that accurately quantifies carbon mass and assesses vegetation health through satellite hyperspectral imagery, a technique which enables us to remotely identify material composition (including plant species) and condition (e.g., health and growth stage). How much carbon a plant is capable of storing ultimately is tied to many factors, including material density (primarily species-dependent), plant size, and health (trees that are actively decaying are not effectively storing carbon). All of these factors are capable of being observed through satellite hyperspectral imagery. This abstract focuses on speciation. To build a species classification model, we matched pixels in our remote sensing imagery to plants on the ground for which we know the species. To accomplish this, we collaborated with the researchers at the Teakettle Experimental Forest. Our remote sensing data comes from our airborne “Kato” sensor, which flew over the study area and acquired hyperspectral imagery (400-2500 nm, 472 bands) at ~0.5 m/pixel resolution. Coverage of the entire teakettle experimental forest required capturing dozens of individual hyperspectral images. In order to combine these images into a mosaic, we accounted for potential variations of atmospheric conditions throughout the data collection. To do this, we ran an open source atmospheric correction routine called ISOFIT1 (Imaging Spectrometer Optiman FITting), which converted all of our remote sensing data from radiance to reflectance. A database of reflectance spectra for each of the tree species within the study area was acquired using the Teakettle stem map and the geo-referenced hyperspectral images. We found that a wide variety of machine learning classifiers were able to identify the species within our images with high (>95%) accuracy. For the most robust quantification of carbon mass and the best assessment of the health of a vegetated area, speciation is critical. Through the use of high resolution hyperspectral data, ground-truth databases, and complex analytical techniques, we are able to determine the species present within a pixel to a high degree of accuracy. These species identifications will feed directly into our carbon mass model.

Keywords: hyperspectral, satellite, carbon, imagery, python, machine learning, speciation

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Authors: Rosemary E. Huntriss, Lucy Jones

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Obesity and excess weight continue to be significant health problems in England. Traditional weight management programmes offer face-to-face support or group education. Remote care is recognised as a viable means of support; however, its effectiveness has not previously been evaluated in a tier 3 weight management setting. This service evaluation explored the effectiveness of online coaching, telephone support, and face-to-face support as optional management strategies within a tier 3 weight management programme. Outcome data were collected for adults with a BMI ≥ 45 or ≥ 40 with complex comorbidity who were referred to a Tier 3 weight management programme from January 2018 and had been discharged before October 2018. Following an initial 45-minute consultation with a specialist weight management dietitian, patients were offered a choice of follow-up support in the form of online coaching supported by an app (8 x 15 minutes coaching), face-to-face or telephone appointments (4 x 30 minutes). All patients were invited to a final 30-minute face-to-face assessment. The planned intervention time was between 12 and 24 weeks. Patients were offered access to adjunct face-to-face or telephone psychological support. One hundred and thirty-nine patients were referred into the programme from January 2018 and discharged before October 2018. One hundred and twenty-four patients (89%) attended their initial assessment. Out of those who attended their initial assessment, 110 patients (88.0%) completed more than half of the programme and 77 patients (61.6%) completed all sessions. The average length of the completed programme (all sessions) was 17.2 (SD 4.2) weeks. Eighty-five (68.5%) patients were coached online, 28 (22.6%) patients were supported face-to-face support, and 11 (8.9%) chose telephone support. Two patients changed from online coaching to face-to-face support due to personal preference and were included in the face-to-face group for analysis. For those with data available (n=106), average weight loss across the programme was 4.85 (SD 3.49)%; average weight loss was 4.70 (SD 3.19)% for online coaching, 4.83 (SD 4.13)% for face-to-face support, and 6.28 (SD 4.15)% for telephone support. There was no significant difference between weight loss achieved with face-to-face vs. online coaching (4.83 (SD 4.13)% vs 4.70 (SD 3.19) (p=0.87) or face-to-face vs. remote support (online coaching and telephone support combined) (4.83 (SD 4.13)% vs 4.85 (SD 3.30)%) (p=0.98). Remote support has been shown to be as effective as face-to-face support provided by a dietitian in the short-term within a tier 3 weight management setting. The completion rates were high compared with another tier 3 weight management services suggesting that offering remote support as an option may improve completion rates within a weight management service.

Keywords: dietitian, digital health, obesity, weight management

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Authors: César Garza

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In supervised binary classification and regression problems, it is well-known that learnability is equivalent to a uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.

Keywords: statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization

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Authors: Molly Pui Man Wong

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In this study, a blended and interactive e-learning Courseware that our team developed will be introduced, and our team’s experiences on how the e-learning Courseware and the flipped classroom benefit student learning in bioethics in the medical program will be shared. This study is a continuation of the previously established study, which provides a summary of the well-developed e-learning Courseware in a blended learning approach and an update on its efficiency and efficacy. First, a collection of animated videos capturing selected topics of bioethics and related ethical issues and dilemma will be introduced. Next, a selection of problem-based learning videos (“simulated doctor-patient role play”) with pop-up questions and discussions will be further discussed. Our recent findings demonstrated that these activities launched by the Courseware strongly engaged students in bioethics education and enhanced students’ critical thinking and creativity, which were consistent with the previous data in the preliminary studies. Moreover, the educational benefits of the online art exhibition, art jamming, and competition will be discussed, through which students could express bioethics through arts and enrich their learning in medical research in an interactive, fun, and entertaining way, strengthening their interests in bioethics. Furthermore, online survey questionnaires and focus group interviews were conducted. Consistent with the preliminary studies, our results indicated that implementing the e-learning Courseware with a flipped classroom in bioethics education enhanced both active learning and student engagement. In conclusion, our Courseware not only reinforces education in art, bioethics, and medicine but also benefits students in understanding and critical thinking in socio-ethical issues and serves as a valuable learning tool in bioethics teaching and learning.

Keywords: bioethics, courseware, e-learning, flipped classroom

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Authors: Ahlam Alnatour

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Background: To our knowledge, there is lack of studies that describe the experience of studying health promotion courses using an interactive approach, and compare students’ and teachers perceptions about this method of teaching. The purpose of this study is to provide a comparison between student and teacher experiences and perspectives in learning health promotion course using interactive learning. Design: A descriptive qualitative design was used to provide an in-depth description and understanding of students’ and teachers experiences and perceptions of learning health promotion courses using an interactive learning. Study Participants: About 14 fourteen students (seven male, seven female) and eight teachers at governmental university in northern Jordan participated in this study. Data Analysis: Conventional content analysis approach was used for participants’ scripts to gain an in-depth description for both students' and teacher’s experiences. Results: The main themes emerged from the data analysis describing the students’ and teachers perceptions of the interactive health promotion class: teachers’ and students positive experience in adopting interactive learning, advantages and benefits of interactive teaching, barriers to interactive teaching, and suggestions for improvement. Conclusion: Both teachers and students reflected positive attitudes toward interactive learning. Interactive learning helped to engage in learning process physically and cognitively. Interactive learning enhanced learning process, promote student attention, enhanced final performance, and satisfied teachers and students accordingly. Interactive learning approach should be adopted in teaching graduate and undergraduate courses using updated and contemporary strategies. Nursing scholars and educators should be motivated to integrate interactive learning in teaching different nursing courses.

Keywords: interactive learning, nursing, health promotion, qualitative study

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Authors: Y. Kavanagh, N. O'Hara, R. Palmer, P. Lowe, D. Rafferty

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Physical Physics is a physics education methodology for games programfmes that integrates physical activity with movement tracking and modelling. It significantly enhances the learning experience and it is effective in illustrating how physics is core in games design and programming, while allowing students to be active participants and take ownership of the learning process. It has been successfully piloted with undergraduate students studying Games Development.

Keywords: activity, enhanced learning, game development, physics

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Authors: YuLung Wu, YuTien Wu, ShuMey Yu

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Game-based learning can enhance the learning motivation of students and provide a means for them to learn through playing games. This study used augmented reality technology to develop an interactive card game as a game-based teaching aid for delivering elementary school science course content with the aim of enhancing student learning processes and outcomes. Through playing the proposed card game, students can familiarize themselves with appearance, features, and foraging behaviors of insects. The system records the actions of students, enabling teachers to determine their students’ learning progress. In this study, 37 students participated in an assessment experiment and provided feedback through questionnaires. Their responses indicated that they were significantly more motivated to learn after playing the game, and their feedback was mostly positive.

Keywords: game-based learning, learning motivation, teaching aid, augmented reality

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Authors: Sakchai Rachniyom

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Owing to the ASEAN community will formally take place in the few months; therefore, Thais should realize about the importance of English language. Since, it is regarded as a working language in the community. To promote Science students’ English proficiency, teacher should be able to teach in English language appropriately and effectively. The purposes of the quasi – experimental research are (1) to measure the learning achievement, (2) to evaluate students’ satisfaction on the teaching and learning and (3) to study the consequences of co – teaching method in order comprehend the learning achievement and improvement. The participants were 40 general science students teacher. Two types of research instruments were included; (1) an achievement test, and (2) a questionnaire. This research was conducted for 1 semester. The statistics used in this research were arithmetic mean and standard deviation. The findings of the study revealed that students’ achievement score was significantly increased at statistical level .05 and the students satisfied the teaching and learning at the highest level . The students’ involvement and teachers’ support were promoted. It was also reported students’ learning was improved by co – teaching method.

Keywords: co – teaching method, learning science in english, teacher, education

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Authors: Nadir Ali Mugheri

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This study has explored the perceptions of English language teachers (ELT) regarding use of technology in learning English as a second language (L2) at Universities in Pakistan. In this regard, 200 ELT teachers from 80 leading universities were selected through a judgmental sampling method. Results established that most of the teachers supported integration and incorporation of technology in the language classroom so as to teach L2 in an effective and efficient way. This study unearthed that the teachers termed the use of technology in learning English as a second language (ESL) as a positive step towards enhancing the learning capabilities and improving the personal traits of the students or learners. Findings suggest that the integration of technology in the language learning makes the learners within the classroom active and enthusiastic, and the teachers need to be equipped with the latest knowledge of mobile assisted language learning (MALL) and computer assisted language learning (CALL) so that they may ensure use of this innovative technology in their teaching practices. Results also indicated that the technology has proved itself a stimulus for improving language in the ELT milieu. The use of technology helps teachers develop themselves professionally. This study discovered that there are many determinants that make teaching and learning within the classroom efficacious, while the use of technology is one of them. Data was collected through qualitative design in order to get a complete depiction. Semi-structured interviews were conducted and analyzed through thematic analysis.

Keywords: english language teaching, computer assisted language learning, use of technology, thematic analysis

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Authors: Stanle Madonsela

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For learning to take place effectively, learners have to use language. Language becomes a critical tool by which to communicate, to express feelings, desires and thoughts, and most of all to learn. However, each individual’s capacity to use language is unique. In multilingual countries, classrooms usually comprise learners from different language backgrounds, and therefore the language used for teaching and learning requires rethinking. Interaction in the classroom, if done in a language that is understood by the learners, could maximise the outcomes of learning. This paper explores the extent to which the use of a single code becomes a source of anxiety to learners in multilingual classrooms in South African schools. It contends that a multilingual approach in the learning process should be explored in order to promote learner autonomy in the learning process.

Keywords: anxiety, classroom, foreign language teaching, multilingual

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Authors: Ashutosh Mishra, Nikhil Goyal

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A 3D facial emotion recognition model based on deep learning is proposed in this paper. Two convolution layers and a pooling layer are employed in the deep learning architecture. After the convolution process, the pooling is finished. The probabilities for various classes of human faces are calculated using the sigmoid activation function. To verify the efficiency of deep learning-based systems, a set of faces. The Kaggle dataset is used to verify the accuracy of a deep learning-based face recognition model. The model's accuracy is about 65 percent, which is lower than that of other facial expression recognition techniques. Despite significant gains in representation precision due to the nonlinearity of profound image representations.

Keywords: facial recognition, computational intelligence, convolutional neural network, depth map

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Authors: May George

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Inference plays an important role in the learning process and it can lead to a rapid acquisition of a second language. When learning a non-native language, i.e., a critical language like Arabic, the students depend on the teacher’s support most of the time to learn new concepts. The students focus on memorizing the new vocabulary and stress on learning all the grammatical rules. Hence, the students became mechanical and cannot produce the language easily. As a result, they are unable to predict the meaning of words in the context by relying heavily on the teacher, in that they cannot link their prior knowledge or even identify the meaning of the words without the support of the teacher. This study explores how the teacher guides students learning during the inference process and what are the processes of learning that can direct student’s inference.

Keywords: inference, reading, Arabic, language acquisition

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Authors: Neha Devi, P. K. Joshi

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Fire fuel map is one of the most critical factors for planning and managing the fire hazard and risk. One of the most significant forms of global disturbance, impacting community dynamics, biogeochemical cycles and local and regional climate across a wide range of ecosystems ranging from boreal forests to tropical rainforest is wildfire Assessment of fire danger is a function of forest type, fuelwood stock volume, moisture content, degree of senescence and fire management strategy adopted in the ground. Remote sensing has potential of reduction the uncertainty in mapping fuels. Hyperspectral remote sensing is emerging to be a very promising technology for wildfire fuels characterization. Fine spectral information also facilitates mapping of biophysical and chemical information that is directly related to the quality of forest fire fuels including above ground live biomass, canopy moisture, etc. We used Hyperion imagery acquired in February, 2016 and analysed four fuel characteristics using Hyperion sensor data on-board EO-1 satellite, acquired over the Shiwalik Himalayas covering the area of Champawat, Uttarakhand state. The main objective of this study was to present an overview of methodologies for mapping fuel properties using hyperspectral remote sensing data. Fuel characteristics analysed include fuel biomass, fuel moisture, and fuel condition and fuel type. Fuel moisture and fuel biomass were assessed through the expression of the liquid water bands. Fuel condition and type was assessed using green vegetation, non-photosynthetic vegetation and soil as Endmember for spectral mixture analysis. Linear Spectral Unmixing, a partial spectral unmixing algorithm, was used to identify the spectral abundance of green vegetation, non-photosynthetic vegetation and soil.

Keywords: forest fire fuel, Hyperion, hyperspectral, linear spectral unmixing, spectral mixture analysis

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Authors: Fatima Achouri, Zakaria Smahi

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Bir El Djir is an important coastal township in Oran department, located at 450 Km far away from Algiers on northwest of Algeria. In this coastal area, the urban sprawl is one of the main problems that reduce the limited highly fertile land. So, using the remote sensing and GIS technologies have shown their great capabilities to solve many earth resources issues. The aim of this study is to produce land use and cover map for the studied area at varied periods to monitor possible changes that may occurred, particularly in the urban areas and subsequently predict likely changes. For this, two spatial images SPOT and Landsat satellites from 1987 and 2014 respectively were used to assess the changes of urban expansion and encroachment during this period with photo-interpretation and GIS approach. The results revealed that the town of Bir El Djir has shown a highest growth rate in the period 1987-2014 which is 521.1 hectares in terms of area. These expansions largely concern the new real estate constructions falling within the social and promotional housing programs launched by the government. Indeed, during the last census period (1998 -2008), the population of this town has almost doubled from 73 029 to 152 151 inhabitants with an average annual growth of 5.2%. This also significant population growth is causing an accelerated urban expansion of the periphery which causing its conurbation with the towns of Oran in the West side. The most urban expansion is characterized by the new construction in the form of spontaneous or peripheral precarious habitat, but also unstructured slums settled especially in the southeastern part of town.

Keywords: urban expansion, remote sensing, photo-interpretation, spatial dynamics

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Authors: K. M. Wong

Abstract:

Engineering education is crucial to technological innovation and advancement worldwide by generating young talents who are able to integrate scientific principles and design practical solutions for real-world problems. Graduates of engineering curriculums are expected to demonstrate an extensive set of learning outcomes as required in international accreditation agreements for engineering academic qualifications, such as the Washington Accord and the Sydney Accord. On the other hand, students have different learning preferences of receiving, processing and internalizing knowledge and skills. If the learning environment is advantageous to the learning styles of the students, there is a higher chance that the students can achieve the intended learning outcomes. With proper identification of the learning styles of the students, corresponding teaching strategies can then be developed for more effective learning. This research was an investigation of learning styles of tertiary students studying higher diploma programmes in Hong Kong. Data from over 200 students in engineering programmes were collected and analysed to identify the learning characteristics of students. A small-scale longitudinal study was then started to gather academic results of the students throughout their two-year engineering studies. Preliminary results suggested that the sample students were reflective, sensing, visual, and sequential learners. Observations from the analysed data not only provided valuable information for teachers to design more effective teaching strategies, but also provided data for further analysis with the students’ academic results. The results generated from the longitudinal study shed light on areas of improvement for more effective engineering curriculum design for better teaching and learning.

Keywords: learning styles, learning characteristics, engineering education, vocational education, Hong Kong

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Authors: Elena Castillo-López, Raúl Pereda, Julio Manuel de Luis, Rubén Pérez, Felipe Piña

Abstract:

Sediments are an important source of accumulation of toxic contaminants within the aquatic environment. Bioassays are a powerful tool for the study of sediments in relation to their toxicity, but they can be expensive. This article presents a methodology to estimate the main physical property of intertidal sediments in coastal zones: heavy metals concentration. This study, which was developed in the Bay of Santander (Spain), applies classical and robust statistic to CASI-2 hyperspectral images to estimate heavy metals presence and ecotoxicity (TOC). Simultaneous fieldwork (radiometric and chemical sampling) allowed an appropriate atmospheric correction to CASI-2 images.

Keywords: remote sensing, intertidal sediment, airborne sensors, heavy metals, eTOCoxicity, robust statistic, estimation

Procedia PDF Downloads 421