Search results for: guided digital learning

Authors: Jie Liu, Xudong Luo, Pingping Lin, Yifan Fan

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Facebook, Twitter, Weibo, and other social media and significant e-commerce sites generate a massive amount of online texts, which can be used to analyse people’s opinions or sentiments for better decision-making. So, sentiment analysis, especially fine-grained sentiment analysis, is a very active research topic. In this paper, we survey various methods for fine-grained sentiment analysis, including traditional sentiment lexicon-based methods, machine learning-based methods, and deep learning-based methods in aspect/target/attribute-based sentiment analysis tasks. Besides, we discuss their advantages and problems worthy of careful studies in the future.

Keywords: sentiment analysis, fine-grained, machine learning, deep learning

Procedia PDF Downloads 233

Authors: Abdulmajeed Almansour

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Learning a foreign language with the assistant of technological tools has become an interest of learners and educators. Increased use of smartphones among undergraduate students has made them popular for not only social communication but also for entertainment and educational purposes. Smartphones have provided remarkable advantages in language learning process. Learning vocabulary is an important part of learning a language. The use of smartphone applications for English vocabulary learning provides an opportunity for learners to improve vocabulary knowledge beyond the classroom wall anytime anywhere. Recently, various smartphone applications were created specifically for vocabulary learning. This paper aims to explore the use of smartphone application Memrise designed for vocabulary learning to enhance academic vocabulary among undergraduate students. It examines whether the use of a Memrise smartphone application designed course enhances the academic vocabulary learning among ESL learners. The research paradigm used in this paper followed a mixed research model combining quantitative and qualitative research. The study included two hundred undergraduate students randomly assigned to the experimental and controlled group during the first academic year at the Faculty of English Language, Imam University. The research instruments included an attitudinal questionnaire and an English vocabulary pre-test administered to students at the beginning of the semester whereas post-test and semi-structured interviews administered at the end of the semester. The findings of the attitudinal questionnaire revealed a positive attitude towards using smartphones in learning vocabulary. The post-test scores showed a significant difference in the experimental group performance. The results from the semi-structure interviews showed that there were positive attitudes towards Memrise smartphone application. The students found the application enjoyable, convenient and efficient learning tool. From the study, the use of the Memrise application is seen to have long-term and motivational benefits to students. For this reason, there is a need for further research to identify the long-term optimal effects of learning a language using smartphone applications.

Keywords: second language vocabulary learning, academic vocabulary, mobile learning technologies, smartphone applications

Procedia PDF Downloads 144

Authors: Ahmad Khachan, Ahmet Ozmen

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This study aims to introduce a mobile bite-sized learning concept, a mobile application with social networks motivation factors that will encourage students to practice critical thinking, improve analytical skills and learn knowledge sharing. We do not aim to propose another e-learning or distance learning based tool like Moodle and Edmodo; instead, we introduce a mobile learning tool called Interactive M-learning Application. The tool reconstructs and strengthens the bonds between educators and learners and provides a foundation for integrating mobile devices in education. The application allows learners to stay connected all the time, share ideas, ask questions and learn from each other. It is built on Android since the Android has the largest platform share in the world and is dominating the market with 74.45% share in 2018. We have chosen Google-Firebase server for hosting because of flexibility, ease of hosting and real time update capabilities. The proposed m-learning tool was offered to four groups of university students in different majors. An improvement in the relation between the students, the teachers and the academic institution was obvious. Student’s performance got much better added to better analytical and critical skills advancement and moreover a willingness to adopt mobile learning in class. We have also compared our app with another tool in the same class for clarity and reliability of the results. The student’s mobile devices were used in this experimental study for diversity of devices and platform versions.

Keywords: education, engineering, interactive software, undergraduate education

Procedia PDF Downloads 133

Authors: G. Valentis, Q. Berthelot

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Nowadays the trend to develop ever more intelligent and autonomous systems often takes its inspiration in the living beings on Earth. Some simple isolated systems are able, once brought together, to form a strong and reliable system. When trying to adapt the idea to man-made systems it is not possible to include in their program everything the system may encounter during its life cycle. It is, thus, necessary to make the system able to take decisions based on other criteria such as its past experience, i.e. to make the system learn on its own. However, at some point the acquired knowledge depends also on environment. So the question is: if system environment is modified, how could the system respond to it quickly and appropriately enough? Here, starting from reinforcement learning to rate its decisions, and using adaptive learning algorithms for gain and loss reward, the system is made able to respond to changing environment and to adapt its knowledge as time passes. Application is made to a robot finding an exit in a labyrinth.

Keywords: reinforcement learning, neural network, autonomous systems, adaptive learning, changing environment

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Authors: Khader I. Alkhouri

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This paper explores the emerging intersection of artificial intelligence (AI) and subconscious research, examining how AI technologies may revolutionize our understanding of the human mind. We review key AI techniques being applied to decode subconscious processes, discuss potential applications and breakthroughs, and consider the ethical implications and societal impacts of this rapidly advancing field. By leveraging AI's powerful pattern recognition and data analysis capabilities, researchers aim to gain unprecedented insights into implicit memory, unconscious bias, and automatic behaviors. While promising, this research also raises important questions about cognitive privacy and the responsible development of these technologies.

Keywords: artificial intelligence, machine learning, neuroethics, psychological research, subconscious

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Authors: Anshul, Rajni Kalia, Sachin Kumar

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Introduction: The costoclavicular approach, a modification to the infraclavicular approach, has been described for anesthesia for upper limb surgeries. Material And Methods: In this randomized and single-blind study, fourty patients undergoing emergency/elective upper limb surgery were allocated to two groups. Group C and S received ultrasound-guided Costoclavicular block and Supraclavicular block, respectively, with 20 ml 0.5 % ropivacaine with 8 mg dexamethasone under strict asepsis. The primary outcome assessed was the total duration of sensory and motor block in the postoperative period. Secondary outcomes were to compare the time taken to perform the procedure, block characteristics in terms of onset of motor and sensory blockade, the efficacy of analgesia with respect to the time of administration of the first rescue analgesic dose with both the blocks and note the side effects pertaining to either of the blocks. Results: The mean total duration of sensory and motor blockade was longer in group C vs. group S (p=0.002 and 0.024, respectively). The mean duration to perform a block in group S was more than in group C (p=0.012). The mean onset of sensory and motor Blockade Time in group S was more than in group C (p<0.001 and <0.001, respectively). The mean duration to perform a block in group S was more than in group C (p=0.012). Conclusion: The costoclavicular approach is better than supraclavicular in terms of rapid execution, faster onset of sensory-motor blockade, prolonged postoperative analgesia and similar PONV and safety profile.

Keywords: costoclavicular, supraclavicular, ropivacaine, dexamethasone

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Authors: Eyup Bayram Guzel

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There have been growing awareness that technology offers unique and promising advantages by offering up-to-data educational materials in promoting teaching and learning materials, new strategies for building enhanced communication environment for people with disabilities and specifically for this study concentrated on the students with deafness and hearing impairments. Creating e-learning environment where teachers and students work in collaboration to develop better educational outcomes is the foremost reason of conducting this research. This study examined the perspectives of special education teachers’ regarding an application of e-learning software called Multimedia Builder on the students with deafness and hearing impairments. Initial and follow up interviews were conducted with 15 special education teachers around the scope of qualitative case study. Grounded approach has been used to analyse and interpret the data. The research results revealed that application of Multimedia Builder software were influential on reading, sign language, vocabulary improvements, computer and ICT usage developments and on audio-visual learning achievements for the advantages of students with deafness and hearing impairments. The implications of the study encouraged the ways of using e-learning tools and strategies to promote unique and comprehensive learning experiences for the targeted students and their teachers.

Keywords: e-learning, special education, deafness and hearing impairment, computer-ICT usage.

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Authors: Azzeddine Atibi, Khadija El Kababi, Salim Ahmed, Mohamed Radid

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Teaching and learning occupy a significant position globally, as the sustainable development of all sectors is intrinsically linked to the improvement of the educational system. The COVID-19 pandemic demonstrated that the integration of Information and Communication Technology (ICT) in the learning process is not optional but essential, and that proficiency in computer tools is an asset that will enhance pedagogy and ensure the continuity of learning under any circumstances. The objective of our study is to evaluate the impact of introducing computer tools on the quality of learning and the realization of conceptual change in learners. To this end, a learning situation was meticulously prepared, targeting first-year baccalaureate students in experimental sciences at a public high school, "Khadija Oum Almouminin," focusing on the chapter on glycemia regulation in the Moroccan Life and Earth Sciences (LES) curriculum. The learning situation was implemented with a pilot group that utilized computer tools and a control group that studied the same chapter without using ICT. The analysis and comparison of the results allowed us to verify the research question posed and to propose perspectives to ensure conceptual change in learners.

Keywords: information and communication technology, conceptual change, continuity of learning, life and earth sciences, glycemia regulation

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Authors: Ahmed Al-Adaileh

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Renewable energy sources, domestic storage systems, controllable loads and machine learning technologies will be key components of future smart homes management systems. An energy management scheme that uses a Deep Learning (DL) approach to support the smart home management systems, which consist of a standalone photovoltaic system, storage unit, heating ventilation air-conditioning system and a set of conventional and smart appliances, is presented. The objective of the proposed scheme is to apply DL-based machine learning to predict various running parameters within a smart home's environment to achieve maximum comfort levels for occupants, reduced electricity bills, and less dependency on the public grid. The problem is using Reinforcement learning, where decisions are taken based on applying the Continuous-time Markov Decision Process. The main contribution of this research is the proposed framework that applies DL to enhance the system's supervised dataset to offer unlimited chances to effectively support smart home systems. A case study involving a set of conventional and smart appliances with dedicated processing units in an inhabited building can demonstrate the validity of the proposed framework. A visualization graph can show "before" and "after" results.

Keywords: smart homes systems, machine learning, deep learning, Markov Decision Process

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Authors: John Tarus, Zhendong Niu, Bakhti Khadidja

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In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving the problem of information overload in e-commerce domains and providing accurate recommendations, e-learning recommender systems on the other hand still face some issues arising from differences in learner characteristics such as learning style, skill level and study level. Conventional recommendation techniques such as collaborative filtering and content-based deal with only two types of entities namely users and items with their ratings. These conventional recommender systems do not take into account the learner characteristics in their recommendation process. Therefore, conventional recommendation techniques cannot make accurate and personalized recommendations in e-learning environment. In this paper, we propose a recommendation technique combining collaborative filtering and ontology to recommend personalized learning materials to online learners. Ontology is used to incorporate the learner characteristics into the recommendation process alongside the ratings while collaborate filtering predicts ratings and generate recommendations. Furthermore, ontological knowledge is used by the recommender system at the initial stages in the absence of ratings to alleviate the cold-start problem. Evaluation results show that our proposed recommendation technique outperforms collaborative filtering on its own in terms of personalization and recommendation accuracy.

Keywords: collaborative filtering, e-learning, ontology, recommender system

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Authors: A. Van Staden, A. Tolmie, E. Vorster

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Research confirms the multifaceted nature of spelling development and underscores the importance of both cognitive and linguistic skills that affect sound spelling development such as working and long-term memory, phonological and orthographic awareness, mental orthographic images, semantic knowledge and morphological awareness. This has clear implications for many South African English second language spellers (L2) who attempt to become proficient spellers. Since English has an opaque orthography, with irregular spelling patterns and insufficient sound/grapheme correspondences, L2 spellers can neither rely, nor draw on the phonological awareness skills of their first language (for example Sesotho and many other African languages), to assist them to spell the majority of English words. Epistemologically, this research is informed by social constructivism. In addition the researchers also hypothesized that the principles of the Overlapping Waves Theory was an appropriate lens through which to investigate whether L2 spellers could significantly improve their spelling skills via the implementation of an alternative route to spelling development, namely the orthographic route, and more specifically via the application of visual imagery. Post-test results confirmed the results of previous research that argues for the interactive nature of different cognitive and linguistic systems such as working memory and its subsystems and long-term memory, as learners were systematically guided to store visual orthographic images of words in their long-term lexicons. Moreover, the results have shown that L2 spellers in the experimental group (n = 9) significantly outperformed L2 spellers (n = 9) in the control group whose intervention involved phonological awareness (and coding) including the teaching of spelling rules. Consequently, L2 learners in the experimental group significantly improved in all the post-test measures included in this investigation, namely the four sub-tests of short-term memory; as well as two spelling measures (i.e. diagnostic and standardized measures). Against this background, the findings of this study look promising and have shown that, within a social-constructivist learning environment, learners can be systematically guided to apply higher-order thinking processes such as visual imagery to successfully store and retrieve mental images of spelling words from their output lexicons. Moreover, results from the present study could play an important role in directing research into this under-researched aspect of L2 literacy development within the South African education context.

Keywords: English second language spellers, phonological and orthographic coding, social constructivism, visual imagery as spelling strategy

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Authors: Thomas Abbey

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This paper is part of an ongoing research addressing the experience of language learners in developing a sense of language ownership in their second language. For the majority of language learners, the main goal of learning a second or foreign language is to develop proficiency in the target language. Language proficiency comprises numerous intersecting competency skills ranging from causally listening to speaking using certain registers. This autoethnography analyzes lived experiences related to transitioning from learning a language in a classroom to being in an environment where the researcher's second language is the primary means of communication. Focused on lived experiences, the purpose of this research is to provide an insight into the experiences of language learners entering new environments and needing to navigate life within another language. Through reflections, this paper offers a critical account of experience traveling to Baku, Azerbaijan as a Russian language learner. The analysis for this paper focuses on the development of a sense of language ownership.

Keywords: autoethnography, language learning, language ownership, transformative learning

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Authors: Farha Sattar, Laurence Tamatea, Muhammad Nawaz

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Drones, the Unmanned Aerial Vehicles are playing an important role in real-world problem-solving. With the new advancements in technology, drones are becoming available, affordable and user- friendly. Use of drones in education is opening new trends in teaching and learning practices in an innovative and engaging way. Drones vary in types and sizes and possess various characteristics and capabilities which enhance their potential to be used in education from basic to advanced and challenging learning activities which are suitable for primary, middle and high school level. This research aims to provide an insight to explore different types of drones and their compatibility to be used in teaching different subjects at various levels. Research focuses on integrating the drone technology along with Australian curriculum content knowledge to reinforce the understanding of the fundamental concepts and helps to develop the critical thinking and reasoning in the learning process.

Keywords: critical thinking, drone technology, drone types, innovative learning

Procedia PDF Downloads 291

Authors: Anne C. Richer-De-Forges, Dominique Arrouays, Songchao Chen, Mercedes Roman Dobarco

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Most of the digital soil mapping (DSM) products rely on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs. However, many other observations (often qualitative, nominal, or ordinal) could be used as proxies of lab measurements or as input data for ML of PTF predictions. DSM and ML are briefly described with some examples taken from the literature. Then, we explore the potential of an ordinal qualitative variable, i.e., the hand-feel soil texture (HFST) estimating the mineral particle distribution (PSD): % of clay (0-2µm), silt (2-50µm) and sand (50-2000µm) in 15 classes. The PSD can also be measured by lab measurements (LAST) to determine the exact proportion of these particle-sizes. However, due to cost constraints, HFST are much more numerous and spatially dense than LAST. Soil texture (ST) is a very important soil parameter to map as it is controlling many of the soil properties and functions. Therefore, comes an essential question: is it possible to use HFST as a proxy of LAST for calibration and/or validation of DSM predictions of ST? To answer this question, the first step is to compare HFST with LAST on a representative set where both information are available. This comparison was made on ca 17,400 samples representative of a French region (34,000 km2). The accuracy of HFST was assessed, and each HFST class was characterized by a probability distribution function (PDF) of its LAST values. This enables to randomly replace HFST observations by LAST values while respecting the PDF previously calculated and results in a very large increase of observations available for the calibration or validation of PTF and ML predictions. Some preliminary results are shown. First, the comparison between HFST classes and LAST analyses showed that accuracies could be considered very good when compared to other studies. The causes of some inconsistencies were explored and most of them were well explained by other soil characteristics. Then we show some examples applying these relationships and the increase of data to several issues related to DSM. The first issue is: do the PDF functions that were established enable to use HSFT class observations to improve the LAST soil texture prediction? For this objective, we replaced all HFST for topsoil by values from the PDF 100 time replicates). Results were promising for the PTF we tested (a PTF predicting soil water holding capacity). For the question related to the ML prediction of LAST soil texture on the region, we did the same kind of replacement, but we implemented a 10-fold cross-validation using points where we had LAST values. We obtained only preliminary results but they were rather promising. Then we show another example illustrating the potential of using HFST as validation data. As in numerous countries, the HFST observations are very numerous; these promising results pave the way to an important improvement of DSM products in all the countries of the world.

Keywords: digital soil mapping, improvement of digital soil mapping predictions, potential of using hand-feel soil texture, soil texture prediction

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Authors: Felix Brito

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With the growth of online learning, several higher education institutions have attempted to incorporate technology in their curriculum. Successful technology implementation projects really on technology infrastructure and on the acceptance of education professionals towards innovation. This research study is aimed at illustrating the relevance of the human component in technology implementation projects in higher education by describing the Learning Management System implementation project executed by instructional designers working for a higher education institution in the southeast region of the United States. An analysis of the Transformative Leadership Theory, the Technology Acceptance Model, and the Diffusion of Innovation Process provide the support for a solid understanding of this issue and address recommendations for future technology implementation projects in higher education institutions.

Keywords: diffusion of innovation process, instructional design, leadership, learning management systems, online learning, technology acceptance model, transformative leadership theory

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Authors: O. F. Elkommos

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Teaching English as a Second Language (TESL) has become a very rich area of research. Practitioners or teachers of English as a foreign or a second language are now promoting both collaborative learning and collaborative teaching. Students learning a language collaboratively and cooperatively are learning in a better environment of team work where they learn from each other. Further, teaching English collaboratively also creates an enriching environment that is also very enriching to students’ and teachers’ experiences of learning and teaching. Moreover, action research stems from actual teacher concerns and students’ needs. Reflection in turn, on the experience of the material taught and the delivery of material is becoming an integral part of the teaching and learning experience self- evaluation and self-development. In this case, the concern of the research field in the area of TESL will be the development of teaching delivery, material and quality of learning. In the present research, the TESL module taught to year two students in the Faculty of Arts and Humanities, British University in Egypt (BUE) will be evaluated reflexively by the students and teachers. The module was taught to students in two different specialisms. It was taught and delivered through collaborative teaching and was evaluated by both teachers and students as very successful and enjoyable. The reflections of both teachers and students as well as student results confirm that it was a success.

Keywords: action research, addressing differentiation, collaborative teaching, reflective teaching and learning, reflexive learning, reflexive teaching, self-development, self-evaluation, TESL

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Authors: Reza Khani, Ziba Hosseini

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This study was an attempt to investigate the difference between learners of Iranian Kurdish–Persian bilingual language and Persian monolinguals, regarding language strategy use (LLS). The participants of the study were 120 monolingual Persian and 120 bilingual Kurdish studying English as a foreign language (EFL). Data were collected using strategy inventory for language learning SILL. The results show bilingual reported higher use of language learning strategies in all categories of SILL except memory strategies.

Keywords: language learning, memory, monolingual, comparative study

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Authors: Hafizul Rasdi

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This study was conducted to find out the perceptions of Islamic Education teachers on the implementation of 21st century learning practices in Kuching, Sarawak. This study uses the field method. Eight respondents were selected based on the interviews and focus group discussions conducted among teachers in four primary school in Kuching, Sarawak. This study is focused to find out the perceptions of Islamic Education teachers on the implementation of 21st century learning as well as the importance of 21st century learning in the subject of Islamic Education. Data were collected using library research, semi-structured interview transcripts and focus group discussions. Data analysis methods used was descriptive analysis. The findings of the study have shown that Islamic Education teachers in primary school in Kuching, Sarawak agreed on the implementation of 21st Century Learning Practices in Islamic Education subject. The finding also show that the application of 21st Century Learning Practices in the subject of Islamic Education can help improve students mastery of the subject.

Keywords: perceptions, Islamic education, 21st century learning practices, teachers

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Authors: Rachel M. Lørum, Henrik Eriksson, Frida Smith

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Purpose: In recent years, the use of benchmarks for the improvement of healthcare has become increasingly common. There has been an increasing interest in why improvement initiatives so often fail to eliminate the problems they aspire to solve. Benchmarking comes with its fair share of challenges and problems, such as capturing the dynamics and complexities of the care environments, among others. In this study, we demonstrate how learning-oriented, voluntary benchmarks in the complex environment of public healthcare could be designed. Findings: Our four most important findings were the following: first, important organizational learning (OL) regarding the complexity of the service and implications on how to design a benchmark for learning and improvement occurred during the process. Second, participation by a wide range of professionals and stakeholders was crucial for capturing the complexity of people and organizations and increasing the quality of the template. Third, the continuous dialogue between all organizations involved was an important tool for ongoing organizational learning throughout the process. The last important finding was the impact of the facilitator’s role through supporting progress, coordination, and dialogue. Design: We chose participatory design as the research design. Data were derived from written materials such as e-mails, protocols, observational notes, and reflection notes collected during a period of 1.5 years. Originality: Our main contributions are the identification of important strategies, initiatives, and actors to involve when designing voluntary benchmarks for learning and improvement.

Keywords: organizational learning, quality improvement, learning-oriented benchmark, healthcare, patient safety

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Authors: N. Ipiña, R. Basagoiti, O. Jimenez, I. Arriaran

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Higher education students are increasingly enrolling in online courses, they are, at the same time, generating data about their learning process in the courses. Data collected in those technology enhanced learning spaces can be used to identify patterns and therefore, offer recommendations/personalized courses to future online students. Moreover, recommendations are considered key aspects for personalization in online learning. Taking into account the above mentioned context, the aim of this paper is to explore the perception of higher education students and teachers towards receiving recommendations in online courses. The study was carried out with 322 students and 10 teachers from two different faculties (Engineering and Education) from Mondragon University. Online questionnaires and face to face interviews were used to gather data from the participants. Results from the questionnaires show that most of the students would like to receive recommendations in their online courses as a guide in their learning process. Findings from the interviews also show that teachers see recommendations useful for their students’ learning process. However, teachers believe that specific pedagogical training is required. Conclusions can also be drawn as regards the importance of personalization in technology enhanced learning. These findings have significant implications for those who train online teachers due to the fact that pedagogy should be the driven force and further training on the topic could be required. Therefore, further research is needed to better understand the impact of recommendations on online students’ learning process and draw some conclusion on pedagogical concerns.

Keywords: higher education, perceptions, recommendations, online courses

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Authors: Lisbeth Amhag

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The aim of the study is to describe and analyze the design of mobile teaching for students collaborative learning in distance higher education with a focus on mobile technologies as online webinars (web-based seminars or conferencing) by using laptops, smart phones, or tablets. These multimedia tools can provide face-to-face interactions, recorded flipped classroom videos and parallel chat communications. The data collection consists of interviews with 22 students and observations of online face-to-face webinars, as well two surveys. Theoretically, the study joins the research tradition of Computer Supported Collaborative learning, CSCL, as well as Computer Self-Efficacy, CSE concerned with individuals’ media and information literacy. Important conclusions from the study demonstrated mobile interactions increased student centered learning. As the students were appreciating the working methods, they became more engaged and motivated. The mobile technology using among student also contributes to increased flexibility between space and place, as well as media and information literacy.

Keywords: computer self-efficacy, computer supported collaborative learning, distance and open learning, educational design and technologies, media and information literacy, mobile learning

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Authors: Aishrith Rao

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COVID 19 is a pandemic which has resulted in thousands of deaths around the world and a huge impact on the global economy. Testing is a huge issue as the test kits have limited availability and are expensive to manufacture. Using deep learning methods on radiology images in the detection of the coronavirus as these images contain information about the spread of the virus in the lungs is extremely economical and time-saving as it can be used in areas with a lack of testing facilities. This paper focuses on binary classification and multi-class classification of COVID 19 and other diseases such as pneumonia, tuberculosis, etc. Different deep learning methods such as VGG-19, COVID-Net, ResNET+ SVM, Deep CNN, DarkCovidnet, etc., have been used, and their accuracy has been compared using the Chest X-Ray dataset.

Keywords: deep learning, computer vision, radiology, COVID-19, ResNet, VGG-19, deep neural networks

Procedia PDF Downloads 139

Authors: Blanco T. F., Fernández-López A.

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Nowadays, education, motivated by the new demands of the 21st century, acquires a dimension that converts the skills that new generations may need into a huge and uncertain set of knowledge too broad to be entirety covered. Within this set, and as tools to reach them, we find Learning and Knowledge Technologies (LKT). Thus, in order to prepare students for an everchanging society in which the technological boom involves everything, it is essential to develop digital competence. Nevertheless LKT seems not to have found their place in the educational system. This work is aimed to go a step further in the research of the most appropriate procedures and resources for technological integration in the classroom. The main objective of this exploratory study is to analyze the didactic suitability (epistemic, cognitive, affective, interactional, mediational and ecological) for teaching and learning processes of mathematics with robotics and 3D printing. The analysis carried out is drawn from a STEAM (Science, Technology, Engineering, Art and Mathematics) project that has the Pilgrimage way to Santiago de Compostela as a common thread. The sample is made up of 25 Primary Education students (10 and 11 years old). A qualitative design research methodology has been followed, the sessions have been distributed according to the type of technology applied. Robotics has been focused towards learning two-dimensional mathematical notions while 3D design and printing have been oriented towards three-dimensional concepts. The data collection instruments used are evaluation rubrics, recordings, field notebooks and participant observation. Indicators of didactic suitability proposed by Godino (2013) have been used for the analysis of the data. In general, the results show a medium-high level of didactic suitability. Above these, a high mediational and cognitive suitability stands out, which led to a better understanding of the positions and relationships of three-dimensional bodies in space and the concept of angle. With regard to the other indicators of the didactic suitability, it should be noted that the interactional suitability would require more attention and the affective suitability a deeper study. In conclusion, the research has revealed great expectations around the combination of teaching-learning processes of mathematics and LKT. Although there is still a long way to go in terms of the provision of means and teacher training.

Keywords: 3D printing, didactic suitability, educational design, robotics

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Authors: Richard Ayobayowa Foyewa

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This work examined the application of ICT in the teaching and learning of English language in Nigerian secondary schools. The definition of ICT was given briefly before areas in which the ICT could be applied in teaching and learning of English language were observed. Teachers’ attitudes towards the use of the computer and Internet facilities were also observed. The conclusion drawn was that ICT is very relevant in the teaching and learning of English language in Nigerian secondary schools. It was therefore recommended that teachers who are not computer literate should go for the training without further delay; government should always employ English language teachers who are computer literates. Government should make fund available in schools for the training and re-training of English language teachers in various computer programmes and in making internet facilities available in secondary schools.

Keywords: ICT, Nigerian secondary schools, teaching and learning of English

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Authors: Ibraheem Husain, Abul Kalam Najmi, Karishma Chester

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First-in-human (FIH) studies are a critical step in clinical development of any molecule that has shown therapeutic promise in preclinical evaluations, since preclinical research and safety studies into clinical development is a crucial step for successful development of monoclonal antibodies for guidance in pharmaceutical industry for the treatment of human diseases. Therefore, comparison between USFDA and nine pharmacologically guided approaches (PGA) (simple allometry, maximum life span potential, brain weight, rule of exponent (ROE), two species methods and one species methods) were made to determine maximum recommended starting dose (MRSD) for first in human clinical trials using four drugs namely Denosumab, Bevacizumab, Anakinra and Omalizumab. In our study, the predicted pharmacokinetic (pk) parameters and the estimated first-in-human dose of antibodies were compared with the observed human values. The study indicated that the clearance and volume of distribution of antibodies can be predicted with reasonable accuracy in human and a good estimate of first human dose can be obtained from the predicted human clearance and volume of distribution. A pictorial method evaluation chart was also developed based on fold errors for simultaneous evaluation of various methods.

Keywords: clinical pharmacology (CPH), clinical research (CRE), clinical trials (CTR), maximum recommended starting dose (MRSD), clearance and volume of distribution

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Authors: Xulu Yao, Moi Hoon Yap, Yanlong Zhang

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As a branch of artificial neural network, deep learning is widely used in the field of image recognition, but the lack of its dataset leads to imperfect model learning. By analysing the data scale requirements of deep learning and aiming at the application in GUI generation, it is found that the collection of GUI dataset is a time-consuming and labor-consuming project, which is difficult to meet the needs of current deep learning network. To solve this problem, this paper proposes a semi-supervised deep learning model that relies on the original small-scale datasets to produce a large number of reliable data sets. By combining the cyclic neural network with the generated countermeasure network, the cyclic neural network can learn the sequence relationship and characteristics of data, make the generated countermeasure network generate reasonable data, and then expand the Rico dataset. Relying on the network structure, the characteristics of collected data can be well analysed, and a large number of reasonable data can be generated according to these characteristics. After data processing, a reliable dataset for model training can be formed, which alleviates the problem of dataset shortage in deep learning.

Keywords: GUI, deep learning, GAN, data augmentation

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Authors: Ahmad Almohana

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Technology has led to rapid changes in the world, and most importantly to education, particularly in the 21st century. Technology has enhanced teachers’ potential and has resulted in the provision of greater interaction and choices for learners. In addition, technology is helping to improve individuals’ learning experiences and building their capacity to read, listen, speak, search, analyse, memorise and encode languages, as well as bringing learners together and creating a sense of greater involvement. This paper has been organised in the following way: the first section provides a review of the literature related to the implementation of CALL (computer assisted learning language), and it explains CALL and its phases, as well as attempting to highlight and analyse Warschauer’s article. The second section is an attempt to describe the move from CALL to mobilised systems of edutainment, which challenge existing forms of teaching and learning. It also addresses the role of the teacher and the curriculum content, and how this is affected by the computerisation of learning that is taking place. Finally, an empirical study has been conducted to collect data from teachers in Saudi Arabia using quantitive and qualitative method tools. Connections are made between the area of study and the personal experience of the researcher carrying out the study with a methodological reflection on the challenges faced by the teachers of this same system. The major findings were that it is worth spelling out here that despite the circumstances in which students and lecturers are currently working, the participants revealed themselves to be highly intelligent and articulate individuals who were constrained from revealing this criticality and creativity by the system of learning and teaching operant in most schools.

Keywords: CALL, computer assisted learning language, EFL, English as a foreign language, ELT, English language teaching, ETL, enhanced technology learning, MALL, mobile assisted learning language

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Authors: Atiwit Sinyoo, Sekh Thanprasertsuk, Sithiporn Agthong, Pasakorn Watanatada, Shaun Peter Qureshi, Saknan Bongsebandhu-Phubhakdi

Abstract:

Background: Since the SARS-CoV-2 virus became extensively disseminated throughout the world, online learning has become one of the most hotly debated topics in educational reform. While some studies have already shown the advantage of online learning, there are still questions concerning how online learning affects students’ learning behavior and academic achievement when each student learns in a different way. Hence, we aimed to develop a guide for preclinical medical students to avoid drawbacks and get benefits from online learning that possibly a double-edged sword. Methods: We used a multiple-choice questionnaire to evaluate the learning behavior of second-year Thai medical students in the neuroscience course. All traditional face-to-face lecture classes were video-recorded and promptly posted to the online learning platform throughout this course. Students could pick and choose whatever classes they wanted to attend, and they may use online learning as often as they wished. Academic performance was evaluated as summative score, spot exam score and pre-post-test improvement. Results: More frequently students used online learning platform, the less they attended lecture classes (P = 0.035). High proactive online learners (High PO) who were irregular attendee (IrA) had significantly lower summative scores (P = 0.026), spot exam score (P = 0.012) and pre-post-test improvement (P = 0.036). In the meanwhile, conditional attendees (CoA) who only attended classes with attendance check had significantly higher summative score (P = 0.025) and spot exam score (P = 0.001) if they were in the High PO group. Conclusions: The benefit and drawbacks edges of using an online learning platform were demonstrated in our research. Based on this double-edged sword effect, we believe that online learning is a valuable learning strategy, but students must carefully plan their study schedule to gain the “benefit edge” meanwhile avoiding its “drawback edge”.

Keywords: academic performance, assessment, attendance, online learning, preclinical medical students

Procedia PDF Downloads 139

Authors: Susan Lee

Abstract:

Situated learning principles are adopted in the design of the module, professional communication, in its iteration of tasks and assignments to create a learning environment that simulates workplace reality. The success of situated learning is met when students are able to transfer and apply their skills beyond the classroom, in their personal life, and workplace. The learning process should help students recognize the relevance and opportunities for application. In the module’s learning component on negotiation, cases are created based on scenarios inspired by industry practices. The cases simulate scenarios that students on the course may encounter when they enter the workforce when they take on executive roles in the real estate sector. Engaging in the cases has enhanced students’ learning experience as they apply interpersonal communication skills in negotiation contexts of executives. Through the process of case analysis, role-playing, and peer feedback, students are placed in an experiential learning space to think and act in a deliberate manner not only as students but as professionals they will graduate to be. The immersive skills practices enable students to continuously apply a range of verbal and non-verbal communication skills purposefully as they stage their negotiations. The theme in students' feedback resonates with their awareness of the authentic and workplace experiences offered through visceral role-playing. Students also note relevant opportunities for the future transfer of the skills acquired. This indicates that students recognize the possibility of encountering similar negotiation episodes in the real world and realize they possess the negotiation tools and communication skills to deliberately apply them when these opportunities arise outside the classroom.

Keywords: deliberate practice, interpersonal communication skills, role-play, situated learning

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Authors: Sebastian Oportus, Fabrizio Alvarez

Abstract:

3D digitalization of heritage objects is widely used nowadays. However, the most advanced 3D scanners in the market that capture topology and texture at the same time, and are specifically made for this purpose, don’t deliver the accuracy that is needed for scientific research. In the last three years, we have developed a method that combines the use of Metrologic grade laser scans, that allows us to work with a high accuracy topology up to 15 times more precise and combine this mesh with a texture obtained from high definition photogrammetry with up to 100 times more pixel concentrations. The result is an accurate digitalization that promotes heritage preservation, scientific study, high detail reproduction, and digital restoration, among others. In Chile, we have already performed 478 digitalizations of high-value heritage pieces and compared the results with up to five different digitalization methods; the results obtained show a considerable better dimensional accuracy and texture resolution. We know the importance of high precision and resolution for academics and museology; that’s why our proposal is to set a worldwide standard using this open source methodology.

Keywords: 3D digitalization, digital heritage, heritage preservation, digital restauration, heritage reproduction

Procedia PDF Downloads 166