Search results for: learning object
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8124

Search results for: learning object

7794 Heightening Pre-Service Teachers’ Attitude towards Learning and Metacognitive Learning through Information and Communication Technology: Pre-Service Science Teachers’ Perspective

Authors: Abiodun Ezekiel Adesina, Ijeoma Ginikanwa Akubugwo

Abstract:

Information and Communication Technology, ICT can heighten pre-service teachers’ attitudes toward learning and metacognitive learning; however, there is a dearth of literature on the perception of the pre-service teachers on heightening their attitude toward learning and metacognitive learning. Thus, this study investigates the perception of pre-service science teachers on heightening their attitude towards learning and metacognitive learning through ICT. Two research questions and four hypotheses guided the research. A mixed methods research was adopted for the study in concurrent triangulation type of integrating qualitative and quantitative approaches to the study. The cluster random sampling technique was adopted to select 250 pre-service science teachers in Oyo township. Two self-constructed instruments: Heightening Pre-service Science Teachers’ Attitude towards Learning and Metacognitive Learning through Information and Communication Technology Scale (HPALMIS, r=.73), and an unstructured interview were used for data collection. Thematic analysis, frequency counts and percentages, t-tests, and analysis of variance were used for data analysis. The perception level of the pre-service science teachers on heightening their attitude towards learning and metacognitive learning through ICT is above average, with the majority perceiving that ICT can enhance their thinking about their learning. The perception was significant (mean=92.68, SD=10.86, df=249, t=134.91, p<.05). The perception was significantly differentiated by gender (t=2.10, df= 248, p<.05) in favour of the female pre-service teachers and based on the first time of ICTs use (F(5,244)= 9.586, p<.05). Lecturers of science and science related courses should therefore imbibe the use of ICTs in heightening pre-service teachers’ attitude towards learning and metacognitive learning. Government should organize workshops, seminars, lectures, and symposia along with professional bodies for the science education lecturers to keep abreast of the trending ICT.

Keywords: pre-service teachers’ attitude towards learning, metacognitive learning, ICT, pre-service teachers’ perspectives

Procedia PDF Downloads 94
7793 Omni-Modeler: Dynamic Learning for Pedestrian Redetection

Authors: Michael Karnes, Alper Yilmaz

Abstract:

This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.

Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition

Procedia PDF Downloads 73
7792 Fostering Enriched Teaching and Learning Experience Using Effective Cyber-Physical Learning Environment

Authors: Shubhakar K., Nachamma S., Judy T., Jacob S. C., Melvin Lee, Kenneth Lo

Abstract:

In recent years, technological advancements have ushered in a new era of education characterized by the integration of technology-enabled devices and online tools. The cyber-physical learning environment (CPLE) is a prime example of this evolution, merging remote cyber participants with in-class learners through immersive technology, interactive digital whiteboards, and online communication platforms like Zoom and MS Teams. This approach transforms the teaching and learning experience into a more seamless, immersive, and inclusive one. This paper outlines the design principles and key features of CPLE that support both teaching and group-based activities. We also explore the key characteristics and potential impact of such environments on educational practices. By analyzing user feedback, we evaluate how technology enhances teaching and learning in a cyber-physical setting, its impact on learning outcomes, user-friendliness, and areas for further enhancement to optimize the teaching and learning environment.

Keywords: cyber-physical class, hybrid teaching, online learning, remote learning, technology enabled learning

Procedia PDF Downloads 28
7791 Materials and Techniques of Anonymous Egyptian Polychrome Cartonnage Mummy Mask: A Multiple Analytical Study

Authors: Hanaa A. Al-Gaoudi, Hassan Ebeid

Abstract:

The research investigates the materials and processes used in the manufacturing of an Egyptian polychrome cartonnage mummy mask with the aim of dating this object and establishing trade patterns of certain materials that were used and available at the time of ancient Egypt. This anonymous-source object was held in the basement storage of the Egyptian Museum in Cairo (EMC) and has never been on display. Furthermore, there is no information available regarding its owner, provenance, date, and even the time of its possession by the museum. Moreover, the object is in a very poor condition where almost two-thirds of the mask was bent and has never received any previous conservation treatment. This research has utilized well-established multi-analytical methods to identify the considerable diversity of materials that have been used in the manufacturing of this object. These methods include Computed Tomography Scan (CT scan) to acquire detailed pictures of the inside physical structure and condition of the bended layers. Dino-Lite portable digital microscope, scanning electron microscopy with energy dispersive X-ray spectrometer (SEM-EDX), and the non-invasive imaging technique of multispectral imaging (MSI) to obtain information about the physical characteristics and condition of the painted layers and to examine the microstructure of the materials. Portable XRF Spectrometer (PXRF) and X-Ray powder diffraction (XRD) to identify mineral phases and the bulk element composition in the gilded layer, ground, and pigments; Fourier-transform infrared (FTIR) to identify organic compounds and their molecular characterization; accelerator mass spectrometry (AMS 14C) to date the object. Preliminary results suggest that there are no human remains inside the object, and the textile support is linen fibres with tabby weave 1/1 and these fibres are in a very bad condition. Several pigments have been identified, such as Egyptian blue, Magnetite, Egyptian green frit, Hematite, Calcite, and Cinnabar; moreover, the gilded layers are pure gold and the binding media in the pigments is Arabic gum and animal glue in the textile support layer.

Keywords: analytical methods, Egyptian museum, mummy mask, pigments, textile

Procedia PDF Downloads 121
7790 Avatar Creation for E-Learning

Authors: M. Najib Osman, Hanafizan Hussain, Sri Kusuma Wati Mohd Daud

Abstract:

Avatar was used as user’s symbol of identity in online communications such as Facebook, Twitter, online game, and portal community between unknown people. The development of this symbol is the use of animated character or avatar, which can engage learners in a way that draws them into the e-Learning experience. Immersive learning is one of the most effective learning techniques, and animated characters can help create an immersive environment. E-learning is an ideal learning environment using modern means of information technology, through the effective integration of information technology and the curriculum to achieve, a new learning style which can fully reflect the main role of the students to reform the traditional teaching structure thoroughly. Essential in any e-learning is the degree of interactivity for the learner, and whether the learner is able to study at any time, or whether there is a need for the learner to be online or in a classroom with other learners at the same time (synchronous learning). Ideally, e-learning should engage the learners, allowing them to interact with the course materials, obtaining feedback on their progress and assistance whenever it is required. However, the degree of interactivity in e-learning depends on how the course has been developed and is dependent on the software used for its development, and the way the material is delivered to the learner. Therefore, users’ accessibility that allows access to information at any time and places and their positive attitude towards e-learning such as having interacting with a good teacher and the creation of a more natural and friendly environment for e-learning should be enhanced. This is to motivate their learning enthusiasm and it has been the responsibility of educators to incorporate new technology into their ways of teaching.

Keywords: avatar, e-learning, higher education, students' perception

Procedia PDF Downloads 408
7789 Using Deep Learning Real-Time Object Detection Convolution Neural Networks for Fast Fruit Recognition in the Tree

Authors: K. Bresilla, L. Manfrini, B. Morandi, A. Boini, G. Perulli, L. C. Grappadelli

Abstract:

Image/video processing for fruit in the tree using hard-coded feature extraction algorithms have shown high accuracy during recent years. While accurate, these approaches even with high-end hardware are computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks (CNNs), specifically an algorithm (YOLO - You Only Look Once) with 24+2 convolution layers. Using deep-learning techniques eliminated the need for hard-code specific features for specific fruit shapes, color and/or other attributes. This CNN is trained on more than 5000 images of apple and pear fruits on 960 cores GPU (Graphical Processing Unit). Testing set showed an accuracy of 90%. After this, trained data were transferred to an embedded device (Raspberry Pi gen.3) with camera for more portability. Based on correlation between number of visible fruits or detected fruits on one frame and the real number of fruits on one tree, a model was created to accommodate this error rate. Speed of processing and detection of the whole platform was higher than 40 frames per second. This speed is fast enough for any grasping/harvesting robotic arm or other real-time applications.

Keywords: artificial intelligence, computer vision, deep learning, fruit recognition, harvesting robot, precision agriculture

Procedia PDF Downloads 414
7788 Adaptive E-Learning System Using Fuzzy Logic and Concept Map

Authors: Mesfer Al Duhayyim, Paul Newbury

Abstract:

This paper proposes an effective adaptive e-learning system that uses a coloured concept map to show the learner's knowledge level for each concept in the chosen subject area. A Fuzzy logic system is used to evaluate the learner's knowledge level for each concept in the domain, and produce a ranked concept list of learning materials to address weaknesses in the learner’s understanding. This system obtains information on the learner's understanding of concepts by an initial pre-test before the system is used for learning and a post-test after using the learning system. A Fuzzy logic system is used to produce a weighted concept map during the learning process. The aim of this research is to prove that such a proposed novel adapted e-learning system will enhance learner's performance and understanding. In addition, this research aims to increase participants' overall understanding of their learning level by providing a coloured concept map of understanding followed by a ranked concepts list of learning materials.

Keywords: adaptive e-learning system, coloured concept map, fuzzy logic, ranked concept list

Procedia PDF Downloads 288
7787 The Effectiveness of Lesson Study via Learning Communities in Increasing Instructional Self-Efficacy of Beginning Special Educators

Authors: David D. Hampton

Abstract:

Lesson study is used as an instructional technique to promote both student and faculty learning. However, little is known about the usefulness of learning communities in supporting results of lesson study on the self-efficacy and development for tenure-track faculty. This study investigated the impact of participation in a lesson study learning community on 34 new faculty members at a mid-size Midwestern University, specifically regarding implementing lesson study evaluations by new faculty on their reported self-efficacy. Results indicate that participation in a lesson study learning community significantly increased faculty members’ lesson study self-efficacy as well as grant and manuscript production over one academic year. Suggestions for future lesson study around faculty learning communities are discussed.

Keywords: lesson study, learning community, lesson study self-efficacy, new faculty

Procedia PDF Downloads 145
7786 The AI Arena: A Framework for Distributed Multi-Agent Reinforcement Learning

Authors: Edward W. Staley, Corban G. Rivera, Ashley J. Llorens

Abstract:

Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains. An emerging landscape of development environments is making powerful RL techniques more accessible for a growing community of researchers. However, most existing frameworks do not directly address the problem of learning in complex operating environments, such as dense urban settings or defense-related scenarios, that incorporate distributed, heterogeneous teams of agents. To help enable AI research for this important class of applications, we introduce the AI Arena: a scalable framework with flexible abstractions for distributed multi-agent reinforcement learning. The AI Arena extends the OpenAI Gym interface to allow greater flexibility in learning control policies across multiple agents with heterogeneous learning strategies and localized views of the environment. To illustrate the utility of our framework, we present experimental results that demonstrate performance gains due to a distributed multi-agent learning approach over commonly-used RL techniques in several different learning environments.

Keywords: reinforcement learning, multi-agent, deep learning, artificial intelligence

Procedia PDF Downloads 152
7785 Classification Based on Deep Neural Cellular Automata Model

Authors: Yasser F. Hassan

Abstract:

Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: cellular automata, neural cellular automata, deep learning, classification

Procedia PDF Downloads 191
7784 The Effects of Integrating Knowledge Management and e-Learning: Productive Work and Learning Coverage

Authors: Ashraf Ibrahim Awad

Abstract:

It is important to formulate suitable learning environments ca-pable to be customized according to value perceptions of the university. In this paper, light is shed on the concepts of integration between knowledge management (KM), and e-learning (EL) in the higher education sector of the economy in Abu Dhabi Emirate, United Arab Emirates (UAE). A discussion on and how KM and EL can be integrated and leveraged for effective education and training is presented. The results are derived from the literature and interviews with 16 of the academics in eight universities in the Emirate. The conclusion is that KM and EL have much to offer each other, but this is not yet reflected at the implementation level, and their boundaries are not always clear. Interviews have shown that both concepts perceived to be closely related and, responsibilities for these initiatives are practiced by different departments or units.

Keywords: knowledge management, e-learning, learning integration, universities, UAE

Procedia PDF Downloads 503
7783 Learning Preference in Nursing Students at Boromarajonani College of Nursing Chon Buri

Authors: B. Wattanakul, G. Ngamwongwan, S. Ngamkham

Abstract:

Exposure to different learning experiences contributes to changing in learning style. Addressing students’ learning preference could help teachers provide different learning activities that encourage the student to learn effectively. Purpose: The purpose of this descriptive study was to describe learning styles of nursing students at Boromarajonani College of Nursing Chon Buri. Sample: The purposive sample was 463 nursing students who were enrolled in a nursing program at different academic levels. The 16-item VARK questionnaire with 4 multiple choices was administered at one time data collection. Choices have consisted with modalities of Visual, Aural, Read/write, and Kinesthetic measured by VARK. Results: Majority of learning preference of students at different levels was visual and read/write learning preference. Almost 67% of students have a multimodal preference, which is visual learning preference associated with read/write or kinesthetic preference. At different academic levels, multimodalities are greater than single preference. Over 30% of students have one dominant learning preference, including visual preference, read/write preference and kinesthetic preference. Analysis of Variance (ANOVA) with Bonferroni adjustment revealed a significant difference between students based on their academic level (p < 0.001). Learning style of the first-grade nursing students differed from the second-grade nursing students (p < 0.001). While learning style of nursing students in the second-grade has significantly varied from the 1st, 3rd, and 4th grade (p < 0.001), learning preference of the 3rd grade has significantly differed from the 4th grade of nursing students (p > 0.05). Conclusions: Nursing students have varied learning styles based on their different academic levels. Learning preference is not fixed attributes. This should help nursing teachers assess the types of changes in students’ learning preferences while developing teaching plans to optimize students’ learning environment and achieve the needs of the courses and help students develop learning preference to meet the need of the course.

Keywords: learning preference, VARK, learning style, nursing

Procedia PDF Downloads 353
7782 Hybrid Feature Selection Method for Sentiment Classification of Movie Reviews

Authors: Vishnu Goyal, Basant Agarwal

Abstract:

Sentiment analysis research provides methods for identifying the people’s opinion written in blogs, reviews, social networking websites etc. Sentiment analysis is to understand what opinion people have about any given entity, object or thing. Sentiment analysis research can be broadly categorised into three types of approaches i.e. semantic orientation, machine learning and lexicon based approaches. Feature selection methods improve the performance of the machine learning algorithms by eliminating the irrelevant features. Information gain feature selection method has been considered best method for sentiment analysis; however, it has the drawback of selection of threshold. Therefore, in this paper, we propose a hybrid feature selection methods comprising of information gain and proposed feature selection method. Initially, features are selected using Information Gain (IG) and further more noisy features are eliminated using the proposed feature selection method. Experimental results show the efficiency of the proposed feature selection methods.

Keywords: feature selection, sentiment analysis, hybrid feature selection

Procedia PDF Downloads 333
7781 A Research Agenda for Learner Models for Adaptive Educational Digital Learning Environments

Authors: Felix Böck

Abstract:

Nowadays, data about learners and their digital activities are collected, which could help educational institutions to better understand learning processes, improve them and be able to provide better learning assistance. In this research project, custom knowledge- and data-driven recommendation algorithms will be used to offer students in higher education integrated learning assistance. The pre-requisite for this is a learner model that is as comprehensive as possible, which should first be created and then kept up-to-date largely automatically for being able to individualize and personalize the learning experience. In order to create such a learner model, a roadmap is presented that describes the individual phases up to the creation and evaluation of the finished model. The methodological process for the research project is disclosed, and the research question of how learners can be supported in their learning with personalized, customized learning recommendations is explored.

Keywords: research agenda, user model, learner model, higher education, adaptive educational digital learning environments, personalized learning paths, recommendation system, adaptation, personalization

Procedia PDF Downloads 9
7780 Evaluating the Effectiveness of Digital Game-Based Learning on Educational Outcomes of Students with Special Needs in an Inclusive Classroom

Authors: Shafaq Rubab

Abstract:

The inclusion of special needs students in a classroom is prevailing gradually in developing countries. Digital game-based learning is one the most effective instructional methodology for special needs students. Digital game-based learning facilitates special needs students who actually face challenges and obstacles in their learning processes. This study aimed to evaluate the effectiveness of digital game-based learning on the educational progress of special needs students in developing countries. The quasi-experimental research was conducted by using purposively selected sample size of eight special needs students. Results of both experimental and control group showed that performance of the experimental group students was better than the control group students and there was a significant difference between both groups’ results. This research strongly recommended that digital game-based learning can help special needs students in an inclusive classroom. It also revealed that special needs students can learn efficiently by using pedagogically sound learning games and game-based learning helps a lot for the self-paced fast-track learning system.

Keywords: inclusive education, special needs, digital game-based learning, fast-track learning

Procedia PDF Downloads 289
7779 The Differences in Skill Performance Between Online and Conventional Learning Among Nursing Students

Authors: Nurul Nadrah

Abstract:

As a result of the COVID-19 pandemic, a movement control order was implemented, leading to the adoption of online learning as a substitute for conventional classroom instruction. Thus, this study aims to determine the differences in skill performance between online learning and conventional methods among nursing students. We employed a quasi-experimental design with purposive sampling, involving a total of 59 nursing students, and used online learning as the intervention. As a result, the study found there was a significant difference in student skill performance between online learning and conventional methods. As a conclusion, in times of hardship, it is necessary to implement alternative pedagogical approaches, especially in critical fields like nursing, to ensure the uninterrupted progression of educational programs. This study suggests that online learning can be effectively employed as a means of imparting knowledge to nursing students during their training.

Keywords: nursing education, online learning, skill performance, conventional learning method

Procedia PDF Downloads 39
7778 A Design of the Infrastructure and Computer Network for Distance Education, Online Learning via New Media, E-Learning and Blended Learning

Authors: Sumitra Nuanmeesri

Abstract:

The research focus on study, analyze and design the model of the infrastructure and computer networks for distance education, online learning via new media, e-learning and blended learning. The collected information from study and analyze process that information was evaluated by the index of item objective congruence (IOC) by 9 specialists to design model. The results of evaluate the model with the mean and standard deviation by the sample of 9 specialists value is 3.85. The results showed that the infrastructure and computer networks are designed to be appropriate to a great extent appropriate to a great extent.

Keywords: blended learning, new media, infrastructure and computer network, tele-education, online learning

Procedia PDF Downloads 400
7777 Analyzing Corporate Employee Preferences for E-Learning Platforms: A Survey-Based Approach to Knowledge Updation

Authors: Sandhyarani Mahananda

Abstract:

This study investigates the preferences of corporate employees for knowledge updates on the e-learning platform. The researchers explore the factors influencing their platform choices through a survey administered to employees across diverse industries and job roles. The survey examines preferences for specific platforms (e.g., Coursera, Udemy, LinkedIn Learning). It assesses the importance of content relevance, platform usability, mobile accessibility, and integration with workplace learning management systems. Preliminary findings indicate a preference for platforms that offer curated, job-relevant content, personalized learning paths, and seamless integration with employer-provided learning resources. This research provides valuable insights for organizations seeking to optimize their investment in e-learning and enhance employee knowledge development.

Keywords: corporate training, e-learning platforms, employee preferences, knowledge updation, professional development

Procedia PDF Downloads 17
7776 The Application of ICT in E-Assessment and E-Learning in Language Learning and Teaching

Authors: Seyyed Hassan Seyyedrezaei

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The advent of computer and ICT thereafter has introduced many irrevocable changes in learning and teaching. There is substantially growing need for the use of IT and ICT in language learning and teaching. In other words, the integration of Information Technology (IT) into online teaching is of vital importance for education and assessment. Considering the fact that the image of education is undergone drastic changes by the advent of technology, education systems and teachers move beyond the walls of traditional classes and methods in order to join with other educational centers to revitalize education. Given the advent of distance learning, online courses and virtual universities, e-assessment has taken a prominent place in effective teaching and meeting the learners' educational needs. The purpose of this paper is twofold: first, scrutinizing e-learning, it discusses how and why e-assessment is becoming widely used by educationalists and administrators worldwide. As a second purpose, a couple of effective strategies for online assessment will be enumerated.

Keywords: e-assessment, e learning, ICT, online assessment

Procedia PDF Downloads 565
7775 Students’ Perceptions of Using Wiki Technology to Enhance Language Learning

Authors: Hani Mustafa, Cristina Gonzalez Ruiz, Estelle Bech

Abstract:

The growing influence of digital technologies has made learning and interaction more accessible, resulting in effective collaboration if properly managed. Technology enabled learning has become an important conduit for learning, including collaborative learning. The use of wiki technology, for example, has opened a new learning platform that enables the integration of social, linguistic, and cognitive processes of language learning. It encourages students to collaborate in the construction, analysis, and understanding of knowledge. But to what extent is the use of wikis effective in promoting collaborative learning among students. In addition, how do students perceive this technology in enhancing their language learning? In this study, students were be given a wiki project to complete collaboratively with their group members. Students had to write collaboratively to produce and present a seven-day travel plan in which they had to describe places to visit and things to do to explore the best historical and cultural aspects of the country. The study involves students learning French, Malay, and Spanish as a foreign language. In completing this wiki project, students will move from passive learning of language to real engagement with classmates, requiring them to collaborate and negotiate effectively with one another. The objective of the study is to ascertain to what extent does wiki technology helped in promoting collaborative learning and improving language skills from students’ perception. It is found that while there was improvement in students language skills, the overall experience was less positive due to unfamiliarity with a new learning tool.

Keywords: collaborative learning, foreign language, wiki, teaching

Procedia PDF Downloads 135
7774 Curriculum-Based Multi-Agent Reinforcement Learning for Robotic Navigation

Authors: Hyeongbok Kim, Lingling Zhao, Xiaohong Su

Abstract:

Deep reinforcement learning has been applied to address various problems in robotics, such as autonomous driving and unmanned aerial vehicle. However, because of the sparse reward penalty for a collision with obstacles during the navigation mission, the agent fails to learn the optimal policy or requires a long time for convergence. Therefore, using obstacles and enemy agents, in this paper, we present a curriculum-based boost learning method to effectively train compound skills during multi-agent reinforcement learning. First, to enable the agents to solve challenging tasks, we gradually increased learning difficulties by adjusting reward shaping instead of constructing different learning environments. Then, in a benchmark environment with static obstacles and moving enemy agents, the experimental results showed that the proposed curriculum learning strategy enhanced cooperative navigation and compound collision avoidance skills in uncertain environments while improving learning efficiency.

Keywords: curriculum learning, hard exploration, multi-agent reinforcement learning, robotic navigation, sparse reward

Procedia PDF Downloads 87
7773 E-Learning in Primary Science: Teachers versus Students

Authors: Winnie Wing Mui So, Yu Chen

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This study investigated primary school teachers’ and students’ perceptions of science learning in an e-learning environment. This study used a multiple case study design and involved eight science teachers and their students from four Hong Kong primary schools. The science topics taught included ‘season and weather’ ‘force and movement’, ‘solar and lunar eclipse’ and ‘living things and habitats’. Data were collected through lesson observations, interviews with teachers, and interviews with students. Results revealed some differences between the teachers’ and the students’ perceptions regarding the usefulness of e-learning resources, the organization of student-centred activities, and the impact on engagement and interactions in lessons. The findings have implications for the more effective creation of e-learning environments for science teaching and learning in primary schools.

Keywords: e-learning, science education, teacher' and students' perceptions, primary schools

Procedia PDF Downloads 197
7772 Spatio-Temporal Assessment of Urban Growth and Land Use Change in Islamabad Using Object-Based Classification Method

Authors: Rabia Shabbir, Sheikh Saeed Ahmad, Amna Butt

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Rapid land use changes have taken place in Islamabad, the capital city of Pakistan, over the past decades due to accelerated urbanization and industrialization. In this study, land use changes in the metropolitan area of Islamabad was observed by the combined use of GIS and satellite remote sensing for a time period of 15 years. High-resolution Google Earth images were downloaded from 2000-2015, and object-based classification method was used for accurate classification using eCognition software. The information regarding urban settlements, industrial area, barren land, agricultural area, vegetation, water, and transportation infrastructure was extracted. The results showed that the city experienced a spatial expansion, rapid urban growth, land use change and expanding transportation infrastructure. The study concluded the integration of GIS and remote sensing as an effective approach for analyzing the spatial pattern of urban growth and land use change.

Keywords: land use change, urban growth, Islamabad, object-based classification, Google Earth, remote sensing, GIS

Procedia PDF Downloads 147
7771 Digi-Buddy: A Smart Cane with Artificial Intelligence and Real-Time Assistance

Authors: Amaladhithyan Krishnamoorthy, Ruvaitha Banu

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Vision is considered as the most important sense in humans, without which leading a normal can be often difficult. There are many existing smart canes for visually impaired with obstacle detection using ultrasonic transducer to help them navigate. Though the basic smart cane increases the safety of the users, it does not help in filling the void of visual loss. This paper introduces the concept of Digi-Buddy which is an evolved smart cane for visually impaired. The cane consists for several modules, apart from the basic obstacle detection features; the Digi-Buddy assists the user by capturing video/images and streams them to the server using a wide-angled camera, which then detects the objects using Deep Convolutional Neural Network. In addition to determining what the particular image/object is, the distance of the object is assessed by the ultrasonic transducer. The sound generation application, modelled with the help of Natural Language Processing is used to convert the processed images/object into audio. The object detected is signified by its name which is transmitted to the user with the help of Bluetooth hear phones. The object detection is extended to facial recognition which maps the faces of the person the user meets in the database of face images and alerts the user about the person. One of other crucial function consists of an automatic-intimation-alarm which is triggered when the user is in an emergency. If the user recovers within a set time, a button is provisioned in the cane to stop the alarm. Else an automatic intimation is sent to friends and family about the whereabouts of the user using GPS. In addition to safety and security by the existing smart canes, the proposed concept devices to be implemented as a prototype helping visually-impaired visualize their surroundings through audio more in an amicable way.

Keywords: artificial intelligence, facial recognition, natural language processing, internet of things

Procedia PDF Downloads 349
7770 Learning Model Applied to Cope with Professional Knowledge Gaps in Final Project of Information System Students

Authors: Ilana Lavy, Rami Rashkovits

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In this study, we describe Information Systems students' learning model which was applied by students in order to cope with professional knowledge gaps in the context of their final project. The students needed to implement a software system according to specifications and design they have made beforehand. They had to select certain technologies and use them. Most of them decided to use programming environments that were learned during their academic studies. The students had to cope with various levels of knowledge gaps. For that matter they used learning strategies that were organized by us as a learning model which includes two phases each suitable for different learning tasks. We analyze the learning model, describing advantages and shortcomings as perceived by the students, and provide excerpts to support our findings.

Keywords: knowledge gaps, independent learner skills, self-regulated learning, final project

Procedia PDF Downloads 474
7769 An Accurate Computation of 2D Zernike Moments via Fast Fourier Transform

Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez

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Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.

Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments

Procedia PDF Downloads 260
7768 A Review on Artificial Neural Networks in Image Processing

Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

Procedia PDF Downloads 401
7767 A Bibliometric Analysis of Research on E-learning in Physics Education: Trends, Patterns, and Future Directions

Authors: Siti Nurjanah, Supahar

Abstract:

E-learning has become an increasingly popular mode of instruction, particularly in the field of physics education, where it offers opportunities for interactive and engaging learning experiences. This research aims to analyze the trends of research that investigated e-learning in physics education. Data was extracted from Scopus's database using the keywords "physics" and "e-learning". Of the 380 articles obtained based on the search criteria, a trend analysis of the research was carried out with the help of RStudio using the biblioshiny package and VosViewer software. Analysis showed that publications on this topic have increased significantly from 2014 to 2021. The publication was dominated by researchers from the United States. The main journal that publishes articles on this topic is Proceedings Frontiers in Education Conference fie. The most widely cited articles generally focus on the effectiveness of Moodle for physics learning. Overall, this research provides an in-depth understanding of the trends and key findings of research related to e-learning in physics.

Keywords: bibliometric analysis, physics education, biblioshiny, E-learning

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7766 Audio-Visual Co-Data Processing Pipeline

Authors: Rita Chattopadhyay, Vivek Anand Thoutam

Abstract:

Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

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7765 Learning for the Future: Flipping English Language Learning Classrooms for Future

Authors: Natarajan Hema, Tamilarasan Karunakaran

Abstract:

Technology is remodeling the process of teaching and learning. An inflection point is faced where technological interventions are rewiring learning process in formal classrooms. Employment depends on dynamic learning capability. Transforming the functionalities of teaching-learning-assessment through innovation is needed to modify the roles of teacher to enabler and learner to the dynamic learner. This makeover is vital for English language teaching where English is acquired as a skill, exercised as ability and get stabilized as a competence. This reshaping could be achieved through providing autonomy to participants of learning. This paper explores parameters and components aiding such a transformation. The differentiated responsibilities and other critical learning support systems are projected as viable options. New age teaching practices are studied for feasibilities to aid transformation and being put forth an inter-operable teaching-learning system for a learner-centric ELT classrooms. LOTUS model developed by the authors is also studied for its inclusiveness to promote skill acquisition.

Keywords: ELT methodology, communicative competence, skill acquisition , new age teaching

Procedia PDF Downloads 352