Search results for: deep learning based FER

Authors: Alessandro Marano

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The author describes the use of deep plane face lifting and platysmaplasty to treat sagging neck with minimal scars. Series of case study. The author uses a selective deep plane face lift with a minimal access scar that not extend behind the ear lobe, neck liposuction and platysmaplasty to restore the sagging neck; the scars are minimal and no require drainage post-op. The deep plane face lifting can achieve a good result restoring vertical vectors in aging and sagging face, neck district can be treated without cutting the skin behind the ear lobe combining the SMAS vertical suspension and platysmaplasty; surgery can be performed in local anesthesia with sedation in day surgery and fast recovery. Restoring neck sagging without extend scars behind ear lobe is possible in selected patients, procedure is fast, safe, no drainage required, patients are satisfied and healing time is fast and comfortable.

Keywords: face lifting, aesthetic, face, neck, platysmaplasty, deep plane

Procedia PDF Downloads 94

Authors: Joshefina Bengoechea Fernandez, Alex Bell

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In its 2021 guidance for policy makers, the UNESCO has proposed 4 areas where AI can be applied in educational settings: These are: 1) Education management and delivery; 2) Learning and assessment; 3) Empowering teachers and facilitating teaching, and 4) Providing lifelong learning possibilities (UNESCO, 2021). Like with wblockchain technologies, AI will automate the management of educational institutions. These include, but are not limited to admissions, timetables, attendance, and homework monitoring. Furthermore, AI will be used to select relevant learning content across learning platforms for each student, based on his or her personalized needs. A problem educators face is the “one-size-fits-all” approach that does not work with a diverse student population. The purpose of this paper is to illustrate if the implementation of Technology is the solution to the Problems faced in Higher Education. The paper builds upon a constructivist approach, combining a literature review and research on key publications and academic reports.

Keywords: artificial intelligence, learning platforms, students personalised needs, life- long learning, privacy, ethics

Procedia PDF Downloads 97

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

Procedia PDF Downloads 368

Authors: Shahira Mahmoud Yacout

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Writing is an essential skill in many vocational, academic environments, and notably workplaces, yet many students perceive writing as being something tiring and boring or maybe a “waste of time”. Studies in the field of foreign languages related this fact might be due to the lack of connection between what is learned in the university and what students come to encounter in real life situations”. Arabic learners felt they needed more language exposure to the context of their future professions. With this idea in mind, Scenario based learning (SBL) is reported to be an educational approach to motivate, engage and stimulate students’ interest and to achieve the desired writing learning outcomes. In addition, researchers suggested Scenario based learning (SBL)as an instructional approach that develops and enhances students skills through developing higher order thinking skills and active learning. It is a subset of problem-based learning and case-based learning. The approach focuses on authentic rhetorical framing reflecting writing tasks in real life situations. It works successfully when used to simulate real-world practices, providing context that reflects the types of situations professionals respond to in writing. It was claimed that using realistic scenarios customized to the course’s learning objectives as it bridged the gap for students between theory and application. Within this context, it is thought that scenario-based learning is an important approach to enhance the learners’ writing skills and to reflect meaningful learning within authentic contexts. As an Arabicforeign language instructor, it was noticed that students find difficulties in adapting writing styles to authentic writing contexts and addressing different audiences and purposes. This idea is supported by studieswho claimed that AFL students faced difficulties with transferring writing skills to situations outside of the classroom context. In addition, it was observed that some of the Arabic textbooks for teaching Arabic as a foreign language lacked topics that initiated higher order thinking skills and stimulated the learners to understand the setting, and created messages appropriate to different audiences, context, and purposes. The goals of this study are to 1)provide a rational for using scenario-based learning approach to improveAFL learners in writing skills, 2) demonstrate how to design/ implement a scenario-based learning technique aligned with the writing course objectives,3) demonstrate samples of scenario-based approach implemented in AFL writing class, and 4)emphasis the role of peer-review along with the instructor’s feedback, in the process of developing the writing skill. Finally, this presentation highlighted and emphasized the importance of using the scenario-based learning approach in writing as a means to mirror students’ real-life situations and engage them in planning, monitoring, and problem solving. This approach helped in making writing an enjoyable experience and clearly useful to students’ future professional careers.

Keywords: meaningful learning, real life contexts, scenario based learning, writing skill

Procedia PDF Downloads 91

Authors: Yahya Almurtadha, Mukhtar Ghaleb, Ahmed M. Shamsan Saleh

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The world witnessed a fierce attack from the Covid-19 virus, which affected public life socially, economically, healthily and psychologically. The world's governments tried to confront the pandemic by imposing a number of precautionary measures such as general closure, curfews and social distancing. Scientists have also made strenuous efforts to develop an effective vaccine to train the immune system to develop antibodies to combat the virus, thus reducing its symptoms and limiting its spread. Artificial intelligence, along with researchers and medical authorities, has accelerated the vaccine development process through big data processing and simulation. On the other hand, one of the most important negatives of the impact of Covid 19 was the state of anxiety and fear due to the blowout of rumors through social media, which prompted governments to try to reassure the public with the available means. This study aims to proposed using Sentiment Analysis (AKA Opinion Mining) and deep learning as efficient artificial intelligence techniques to work on retrieving the tweets of the public from Twitter and then analyze it automatically to extract their opinions, expression and feelings, negatively or positively, about the symptoms they may feel after vaccination. Sentiment analysis is characterized by its ability to access what the public post in social media within a record time and at a lower cost than traditional means such as questionnaires and interviews, not to mention the accuracy of the information as it comes from what the public expresses voluntarily.

Keywords: deep learning, opinion mining, natural language processing, sentiment analysis

Procedia PDF Downloads 165

Authors: Sophia Shi

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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

Procedia PDF Downloads 125

Authors: Nassim Dennouni, Yvan Peter, Luigi Lancieri, Zohra Slama

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The objective of this article is to make a bibliographic study on the recommendation of mobile learning activities that are used as part of the field trip scenarios. Indeed, the recommendation systems are widely used in the context of mobility because they can be used to provide learning activities. These systems should take into account the history of visits and teacher pedagogy to provide adaptive learning according to the instantaneous position of the learner. To achieve this objective, we review the existing literature on field trip scenarios to recommend mobile learning activities.

Keywords: mobile learning, field trip, mobile learning activities, collaborative filtering, recommendation system, point of interest, ACO algorithm

Procedia PDF Downloads 440

Authors: Guezouli Larbi, Belkacem Soundes

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The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.

Keywords: text detection, CNN, PZM, deep learning

Procedia PDF Downloads 78

Authors: Chen-Ya Juan

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Problem-Based Learning uses vague questions to guide student thinking and enhance their self-learning and collaboration. Most teachers implement PBL in a physical classroom, where teachers can monitor and evaluate students’ learning progress and guide them to search resources for answers. However, the prevalence of the Covid-19 in the world had changed from physical teaching to distance teaching. This instruction used many cases and applied Problem-Based Learning combined on the distance teaching via the internet for college students. This study involved an experimental group with PBL and a control group without PBL. The teacher divided all students in PBL class into eight groups, and 7~8 students in each group. The teacher assigned different cases for each group of the PBL class. Three stages of instruction were developed, including background knowledge of Learning, case analysis, and solving problems for each case. This study used a quantitative research method, a two-sample t-test, to find a significant difference in groups with PBL and without PBL. Findings indicated that PBL incased the average score of special education knowledge. The average score was improved by 20.46% in the PBL group and 15.4% without PBL. Results didn’t show significant differences (0.589>0.05) in special education professional knowledge. However, the feedback of the PBL students implied learning more about the application, problem-solving skills, and critical thinking. PBL students were more likely to apply professional knowledge on the actual case, find questions, resources, and answers. Most of them understood the importance of collaboration, working as a team, and communicating with other team members. The suggestions of this study included that (a) different web-based teaching instruments influenced student’s Learning; (b) it is difficult to monitor online PBL progress; (c) online PBL should be implemented flexible and multi-oriented; (d) although PBL did not show a significant difference on the group with PBL and without PBL, it did increase student’s problem-solving skills and critical thinking.

Keywords: problem-based learning, college students, distance learning, case analysis, problem-solving

Procedia PDF Downloads 125

Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

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Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

Procedia PDF Downloads 158

Authors: Kherafa Abdennasser

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The application of Information and Communication Technologies (ICT) to the training area led to the creation of this new reality called E-learning. That last one is described like the marriage of multi- media (sound, image and text) and of the internet (diffusion on line, interactivity). Distance learning became an important totality for training and that last pass in particular by the setup of a distance learning platform. In our memory, we will use an open source platform named Dokeos for the management of a distance training of GPS called e-GPS. The learner is followed in all his training. In this system, trainers and learners communicate individually or in group, the administrator setup and make sure of this system maintenance.

Keywords: ICT, E-learning, learning plate-forme, Dokeos, GPS

Procedia PDF Downloads 473

Authors: Omar Masaud Almrhag, Frage Lhadi Abookleesh

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Different types of food like banana, potato and chicken affect the quality of oil during deep fat frying. The changes in the quality of oil were evaluated and compared. Four different types of edible oils, namely, corn oil, soybean, canola, and palm oil were used for deep fat frying at 180°C ± 5°C for 5 h/d for six consecutive days. A potato was sliced into 7-8 cm length wedges and chicken was cut into uniform pieces of 100 g each. The parameters used to assess the quality of oil were total polar compound (TPC), iodine value (IV), specific extinction E1% at 233 nm and 269 nm, fatty acid composition (FAC), free fatty acids (FFA), viscosity (cp) and changes in the thermal properties. Results showed that, TPC, IV, FAC, Viscosity (cp) and FFA composition changed significantly with time (P< 0.05) and type of food. Significant differences (P< 0.05) were noted for the used parameters during frying of the above mentioned three products.

Keywords: frying potato, chicken, frying deterioration, quality of oil

Procedia PDF Downloads 414

Authors: Daniela Velichová

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Plenty of ideas on how to adopt active learning methods in education are available nowadays. Mathematics is a subject where the active involvement of students is required in particular in order to achieve desirable results regarding sustainable knowledge and deep understanding. The present article is based on the outcomes of an Erasmus+ project DrIVE-MATH, that was aimed at developing a novel and integrated framework to teach maths classes in engineering courses at the university level. It is fundamental for students from the early years of their academic life to have agile minds. They must be prepared to adapt to their future working environments, where enterprises’ views are always evolving, where all collaborate in teams, and relations between peers are thought for the well-being of the whole - workers and company profit. This reality imposes new requirements on higher education in terms of adaptation of different pedagogical methods, such as project-based and active-learning methods used within the course curricula. Active learning methodologies are regarded as an effective way to prepare students to meet the challenges posed by enterprises and to help them in building critical thinking, analytic reasoning, and insight to the solved complex problems from different perspectives. Fostering learning-by-doing activities in the pedagogical process can help students to achieve learning independence, as they could acquire deeper conceptual understanding by experimenting with the abstract concept in a more interesting, useful, and meaningful way. Clear information about learning outcomes and goals might help students to take more responsibility for their learning results. Active learning methods implemented by the project team members in their teaching practice, eduScrum and Jigsaw in particular, proved to provide better scientific and soft skills support to students than classical teaching methods. EduScrum method enables teachers to generate a working environment that stimulates students' working habits and self-initiative as they become aware of their responsibilities within the team, their own acquired knowledge, and their abilities to solve problems independently, though in collaboration with other team members. This method enhances collaborative learning, as students are working in teams towards a common goal - knowledge acquisition, while they are interacting with each other and evaluated individually. Teams consisting of 4-5 students work together on a list of problems - sprint; each member is responsible for solving one of them, while the group leader – a master, is responsible for the whole team. A similar principle is behind the Jigsaw technique, where the classroom activity makes students dependent on each other to succeed. Students are divided into groups, and assignments are split into pieces, which need to be assembled by the whole group to complete the (Jigsaw) puzzle. In this paper, analysis of students’ perceptions concerning the achievement of deeper conceptual understanding in mathematics and the development of soft skills, such as self-motivation, critical thinking, flexibility, leadership, responsibility, teamwork, negotiation, and conflict management, is presented. Some new challenges are discussed as brought by introducing active learning methods in the basic mathematics courses. A few examples of sprints developed and used in teaching basic maths courses at technical universities are presented in addition.

Keywords: active learning methods, collaborative learning, conceptual understanding, eduScrum, Jigsaw, soft skills

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Authors: Kishore Kumar R., Kaustav Sengupta, Shalini Sood Sehgal, Poornima Santhanam

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Fashion is a human expression that is constantly changing. One of the prime factors that consistently influences fashion is the change in colour preferences. The role of colour in our everyday lives is very significant. It subconsciously explains a lot about one’s mindset and mood. Analyzing the colours by extracting them from the outfit images is a critical study to examine the individual’s/consumer behaviour. Several research works have been carried out on extracting colours from images, but to the best of our knowledge, there were no studies that extract colours to specific apparel and identify colour patterns geographically. This paper proposes a framework for accurately extracting colours from T-shirt images and predicting dominant colours geographically. The proposed method consists of two stages: first, a U-Net deep learning model is adopted to segment the T-shirts from the images. Second, the colours are extracted only from the T-shirt segments. The proposed method employs the iMaterialist (Fashion) 2019 dataset for the semantic segmentation task. The proposed framework also includes a mechanism for gathering data and analyzing India’s general colour preferences. From this research, it was observed that black and grey are the dominant colour in different regions of India. The proposed method can be adapted to study fashion’s evolving colour preferences.

Keywords: colour analysis in t-shirts, convolutional neural network, encoder-decoder, k-means clustering, semantic segmentation, U-Net model

Procedia PDF Downloads 105

Authors: Mária Csernoch, Piroska Biró

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The legends about “user-friendly” and “easy-to-use” birotical tools (computer-related office tools) have been spreading and misleading end-users. This approach has led us to the extremely high number of incorrect documents, causing serious financial losses in the creating, modifying, and retrieving processes. Our research proved that there are at least two sources of this underachievement: (1) The lack of the definition of the correctly edited, formatted documents. Consequently, end-users do not know whether their methods and results are correct or not. They are not aware of their ignorance. They are so ignorant that their ignorance does not allow them to realize their lack of knowledge. (2) The end-users’ problem-solving methods. We have found that in non-traditional programming environments end-users apply, almost exclusively, surface approach metacognitive methods to carry out their computer related activities, which are proved less effective than deep approach methods. Based on these findings we have developed deep approach methods which are based on and adapted from traditional programming languages. In this study, we focus on the most popular type of birotical documents, the text-based documents. We have provided the definition of the correctly edited text, and based on this definition, adapted the debugging method known in programming. According to the method, before the realization of text editing, a thorough debugging of already existing texts and the categorization of errors are carried out. With this method in advance to real text editing users learn the requirements of text-based documents and also of the correctly formatted text. The method has been proved much more effective than the previously applied surface approach methods. The advantages of the method are that the real text handling requires much less human and computer sources than clicking aimlessly in the GUI (Graphical User Interface), and the data retrieval is much more effective than from error-prone documents.

Keywords: deep approach metacognitive methods, error-prone birotical documents, financial losses, human and computer resources

Procedia PDF Downloads 377

Authors: Ming-Jen Huang, Chun-Fang Huang, Chiching Wei

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With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Keywords: document processing, framework, formal definition, machine learning

Procedia PDF Downloads 206

Authors: Nidhal K. Azawi, John M. Gauch

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Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

Procedia PDF Downloads 247

Authors: Erhan Eroğlu

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This paper presents a new method called Mentor and Mentee Based Learning. This new method is becoming more and more common especially at workplaces. This study is significant as it clearly underlines how it works well. Education has always aimed at equipping people with the necessary knowledge and information. For many decades it went on teachers’ talk and chalk methods. In the second half of the nineteenth century educators felt the need for some changes in delivery systems. Some new terms like self- discovery, learner engagement, student centered learning, hands on learning have become more and more popular for such a long time. However, some educators believe that there is much room for better learning methods in many fields as they think the learners still cannot fulfill their potential capacities. Thus, new systems and methods are still being developed and applied at education centers and work places. One of the latest methods is assigning some mentors for the newly recruited employees and training them within a mentor and mentee program which allows both parties to see their strengths and weaknesses and the areas which can be improved. This paper aims at finding out the perceptions of the mentors and mentees on the programs they are offered at their workplaces and suggests some betterment alternatives. The study has been conducted via a qualitative method whereby some interviews have been done with both mentors and mentees separately and together. Results show that it is a great way to train inexperienced one and also to refresh the older ones. Some points to be improved have also been underlined. The paper shows that education is not a one way path to follow.

Keywords: learning, mentor, mentee, training

Procedia PDF Downloads 225

Authors: Aibek Kukpayev, Dhawal Shah

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Combustion of sour fuels containing high amount of sulfur leads to the formation of sulfur oxides, which adversely harm the environment and has a negative impact on human health. Considering this, several legislations have been imposed to bring down the sulfur content in fuel to less than 10 ppm. In recent years, novel deep eutectic solvents (DESs) have been developed to achieve deep desulfurization, particularly to extract thiophenic compounds from liquid fuels. These novel DESs, considered as analogous to ionic liquids are green, eco-friendly, inexpensive, and sustainable. We herein, using molecular dynamic simulation, analyze the interactions of metal-based DESs with model oil consisting of thiophenic compounds. The DES used consists of polyethylene glycol (PEG-200) as a hydrogen bond donor, choline chloride (ChCl) or tetrabutyl ammonium chloride (TBAC) as a hydrogen bond acceptor, and cobalt chloride (CoCl₂) as metal salt. In particular, the combination of ChCl: PEG-200:CoCl₂ at a ratio 1:2:1 and the combination of TBAC:PEG-200:CoCl₂ at a ratio 1:2:0.25 were simulated, separately, with model oil consisting of octane and thiophenes at 25ᵒC and 1 bar. The results of molecular dynamics simulations were analyzed in terms of interaction energies between different components. The simulations revealed a stronger interaction between DESs/thiophenes as compared with octane/thiophenes, suggestive of an efficient desulfurization process. In addition, our analysis suggests that the choice of hydrogen bond acceptor strongly influences the efficiency of the desulfurization process. Taken together, the results also show the importance of the metal ion, although present in small amount, in the process, and the role of the polymer in desulfurization of the model fuel.

Keywords: deep eutectic solvents, desulfurization, molecular dynamics simulations, thiophenes

Procedia PDF Downloads 139

Authors: Shan Jiang, Xinyu Tang

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Game-based learning is an emerging pedagogy to make the learning experience more effective, enjoyable, and fun. However, most games used in classroom settings have been overly simplistic. This paper presents a case study on a Python-based online game designed to improve the effectiveness in both teaching and research in higher education. The proposed game system not only creates a fun and enjoyable experience for students to learn various topics in programming but also improves the effectiveness of teaching in several aspects, including material presentation, helping students to recognize the importance of the subjects, and linking theoretical concepts to practice. The proposed game system also serves as an information cyber-infrastructure that automatically collects and stores data from players. The data could be useful in research areas including human-computer interaction, decision making, opinion mining, and artificial intelligence. They further provide other possibilities beyond these areas due to the customizable nature of the game.

Keywords: game-based learning, programming, research-teaching integration, Hearthstone

Procedia PDF Downloads 157

Authors: Rafia Rafique, Arifa Khadim

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This research investigates the moderating role of job satisfaction between organizational learning and work performance among nurses. Correlation research design was used. Non-probability purposive sampling technique was utilized to recruit a sample of 110 nurses from public hospitals situated in the city of Lahore. The construct of organizational learning was measured using subscale of Integrated Scale for Measuring Organizational Learning. Job satisfaction was measured with the help of Job Satisfaction Survey. Performance of employees (task performance, contextual performance and counterproductive work behavior) was assessed by Individual Work Performance Questionnaire. Job satisfaction negatively moderates the relationship between organizational learning and counterproductive work behavior. Education has a significant positive relationship with organizational learning. Age, current hospital experience, marital satisfaction and salary of the nurses have positive relationship while number of children has significant negative relationship with counterproductive work behavior. These outcomes can be insightful in understanding the dynamics involved in work performance. Based on the result of this study relevant solutions can be proposed to improve the work performance of nurses.

Keywords: counterproductive work behavior, nurses, organizational learning, work performance

Procedia PDF Downloads 436

Authors: Nikolina Ribarić

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E-learning is most commonly defined as a set of applications and processes, such as Web-based learning, computer-based learning, virtual classrooms, and digital collaboration, that enable access to instructional content through a variety of electronic media. The main goal of an e-learning system is learning, and the way to evaluate the impact of an e-learning system is by examining whether students learn effectively with the help of that system. Testmoz is a program for online preparation of knowledge evaluation assignments. The program provides teachers with computer support during the design of assignments and evaluating them. Students can review and solve assignments and also check the correctness of their solutions. Research into the increase of motivation by the practice of providing teaching content by applying online tests prepared in the Testmoz program was carried out with students of the 8th grade of Ljubo Babić Primary School in Jastrebarsko. The students took the tests in their free time, from home, for an unlimited number of times. SPSS was used to process the data obtained by the research instruments. The results of the research showed that students preferred to practice teaching content and achieved better educational results in chemistry when they had access to online tests for repetition and practicing in relation to subject content which was checked after repetition and practicing in "the classical way" -i.e., solving assignments in a workbook or writing assignments in worksheets.

Keywords: chemistry class, e-learning, motivation, Testmoz

Procedia PDF Downloads 155

Authors: Mohamed Bendahmane, Brahim Elfalaki, Mohammed Benattou

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One of the major sources of learners' professional difficulties is their heterogeneity. Whether on cognitive, social, cultural or emotional level, learners being part of the same group have many differences. These differences do not allow to apply the same learning process at all learners. Thus, an optimal learning path for one, is not necessarily the same for the other. We present in this paper a model-oriented service to offer to each learner a personalized learning path to acquire the targeted skills.

Keywords: learning path, web service, trace analysis, personalization

Procedia PDF Downloads 346

Authors: Omran Alharbi

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It is difficult to find an aspect of our modern lives that has been untouched by mobile technology. Indeed, the use of mobile learning in Saudi Arabia may enhance students’ learning and increase overall educational standards. However, within tertiary education, the success of e-learning implementation depends on the degree to which students and educators accept mobile learning and are willing to utilise it. Therefore, this research targeted the factors that influence Hail University instructors’ intentions to use mobile learning. An online survey was completed by eighty instructors and it was found that their use of mobile learning was heavily predicted by performance experience, effort expectancy, social influence, and facilitating conditions; the multiple regression analysis revealed that 67% of the variation was accounted for by these variables. From these variables, effort expectancy was shown to be the strongest predictor of intention to use e-learning for instructors.

Keywords: acceptance, faculty member, mobile learning, KSA

Procedia PDF Downloads 148

Authors: Giorgi Gaganidze, Eter Kharaishvili

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The atypical crisis has created new challenges in the education system. Globally, including in Georgia, traditional methods of managing the education system have appeared particularly vulnerable. In addition, new opportunities for the introduction of innovative management of learning processes have emerged. The aim of the research is to identify the main challenges in the field of education management in the distance learning process in Georgia and to develop recommendations on the opportunities for the introduction of innovative management. The paper substantiates the relevance of the research, in particular, it notes that in Georgia, as in many countries, distance learning in higher education institutions became particularly crucial during the Covid-19 pandemic. What is more, theoretical and practical aspects of distance learning are less proven, and a number of problems have been identified in the field of education management in Georgia. The article justifies the need to study the challenges of distance learning for the formation of a sustainable education management system. Within the bibliographic research, there are grouped the opinions of researchers on the modern problems of distance learning and education management in the article. Based on scientific papers, the expectations formed about distance learning are studied, and the main focus is on the existing problems of education management during the atypical crisis. The article discusses the forms and opportunities of distance learning in different countries, evaluates different approaches and challenges to distance learning, and justifies the role of education management in effective distance learning. The paper uses various theoretical-methodological tools of research, including desk research on the research topic; Data selection-grouping, problem identification is carried out by analysis, synthesis, sampling, induction, and other methods;SWOT analysis is used to assess the strengths, weaknesses, opportunities, and threats of distance education and management; The level of student satisfaction with distance learning is determined through the Population-based / Census-based approach; The results of the research are processed by SPSS program. Quantitative research and semi-structured interviews with relevant focus groups were conducted to identify working directions for innovative management of distance learning and education. Research has shown that the demand for distance education is growing in Georgia, but the need to introduce innovative education management remains a particular challenge. Conclusions have been made on the introduction of innovative education management, and the relevant recommendations have been developed.

Keywords: distance learning, management challenges, education management, innovative management

Procedia PDF Downloads 122

Authors: Marina Vicario, Amadeo Argüelles, Pilar Gómez, Carlos Hernández

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In this paper, the Computer Research Network of the National Polytechnic Institute of Mexico proposes a paradigmatic model for the inference of cognitive patterns in digital learning systems. This model leads to metadata architecture useful for analysis and prediction in online learning systems; especially on MOOc's architectures. The model is in the design phase and expects to be tested through an institutional of courses project which is going to develop for the MOOc.

Keywords: cognitive footprints, learning analytics, predictive learning, digital learning, educational computing, educational informatics

Procedia PDF Downloads 471

Authors: Atuhurra Jesse, N'guessan Yves-Roland Douha, Pabitra Lenka

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The detection of diseases within plants has attracted a lot of attention from computer vision enthusiasts. Despite the progress made to detect diseases in many plants, there remains a research gap to train image classifiers to detect the cacao swollen shoot virus disease or CSSVD for short, pertinent to cacao plants. This gap has mainly been due to the unavailability of high quality labeled training data. Moreover, institutions have been hesitant to share their data related to CSSVD. To fill these gaps, image classifiers to detect CSSVD-infected cacao plants are presented in this study. The classifiers are based on VGG16, ResNet50 and Vision Transformer (ViT). The image classifiers are evaluated on a recently released and publicly accessible KaraAgroAI Cocoa dataset. The best performing image classifier, based on ResNet50, achieves 95.39\% precision, 93.75\% recall, 94.34\% F1-score and 94\% accuracy on only 20 epochs. There is a +9.75\% improvement in recall when compared to previous works. These results indicate that the image classifiers learn to identify cacao plants infected with CSSVD.

Keywords: CSSVD, image classification, ResNet50, vision transformer, KaraAgroAI cocoa dataset

Procedia PDF Downloads 94

Authors: Maria Janet, Anita David, P. Vijayasamundeeswarimaria

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Introduction: The main purpose of this study is to compare the effectiveness of web-based and blended learning on Paediatric Basic Life Support on competency among undergraduate nursing students in selected nursing colleges in Chennai. Materials and methods: A descriptive pre-test and post-test study design were used for this study. Samples of 100 Fourth year B.Sc., nursing students at Sri Ramachandra Faculty of Nursing SRIHER, Chennai, 100 Fourth year B.Sc., nursing students at Apollo College of Nursing, Chennai, were selected by purposive sampling technique. The instrument used for data collection was Knowledge Questionnaire on Paediatric Basic Life Support (PBLS). It consists of 29 questions on the general expansion of Basic Life Support and Cardiopulmonary Resuscitation, Prerequisites of Basic Life Support, and Knowledge on Paediatric Basic Life Support in which each question has four multiple choices answers, each right answer carrying one mark and no negative scoring. This questionnaire was formed with reference to AHA 2020 (American Heart Association) revised guidelines. Results: After the post-test, in the web-based learning group, 58.8% of the students had an inadequate level of objective performance score, while 41.1% of them had an adequate level of objective performance score. In the blended learning group, 26.5% of the students had an inadequate level of an objective performance score, and 73.4% of the students had an adequate level of an objective performance score. There was an association between the post-test level of knowledge and the demographic variables of undergraduate nursing students undergoing blended learning. The age was significant at a p-value of 0.01, and the performance of BLS before was significant at a p-value of 0.05. The results show that there was a significant positive correlation between knowledge and objective performance score of undergraduate nursing students undergoing web-based learning on paediatric basic life support.

Keywords: basic life support, paediatric basic life support, web-based learning, blended learning

Procedia PDF Downloads 65

Authors: Wiem Ben Khalifa, Dalila Souilem, Mahmoud Neji

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The evolutions of Social Web and Semantic Web lead us to ask ourselves about the way of supporting the personalization of learning by means of intelligent filtering of educational resources published in the digital networks. We recommend personalized courses of learning articulated around a first educational course defined upstream. Resuming the context and the stakes in the personalization, we also suggest anchoring the personalization of learning in a community of interest within a group of learners enrolled in the same training. This reflection is supported by the display of an active and semantic system of learning dedicated to the constitution of personalized to measure courses and in the due time.

Keywords: Semantic Web, semantic system, ontology, evaluation, e-learning

Procedia PDF Downloads 326

Authors: Sitthichai Laisema, Panita Wannapiroon

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This study is a research and development which is intended to: 1) design ubiquitous collaborative learning activities with virtual teams using CPS processes to develop creative thinking and collaboration skills, and 2) assess the suitability of the ubiquitous collaborative learning activities. Its methods are divided into 2 phases. Phase 1 is the design of ubiquitous collaborative learning activities with virtual teams using CPS processes, phase 2 is the assessment of the suitability of the learning activities. The samples used in this study are 5 professionals in the field of learning activity design, ubiquitous learning, information technology, creative thinking, and collaboration skills. The results showed that ubiquitous collaborative learning activities with virtual teams using CPS processes to develop creative thinking and collaboration skills consist of 3 main steps which are: 1) preparation before learning, 2) learning activities processing and 3) performance appraisal. The result of the learning activities suitability assessment from the professionals is in the highest level.

Keywords: ubiquitous learning, collaborative learning, virtual team, creative problem solving

Procedia PDF Downloads 506