Search results for: reflective learning approach

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

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

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

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Authors: Abe Degale D., Cheng Jian

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When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

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Authors: Konstantinos Sofianos, Michail Stefanidakis

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Nowadays, despite the great advances in technology, most educational frameworks lack a strong educational design basis. E-learning has become prevalent, but it faces various challenges such as student isolation and lack of quality in the learning process. An intelligent learning system provides a student with educational material according to their learning background and learning preferences. It records full information about the student, such as demographic information, learning styles, and academic performance. This information allows the system to be fully adapted to the student’s needs. In this paper, we propose a framework and an ontology for music education, consisting of the learner model and all elements of the learning process (learning objects, teaching methods, learning activities, assessment). This framework can be integrated into an intelligent learning system and used for music education in schools for the development of professional skills and beyond.

Keywords: intelligent learning systems, e-learning, music education, ontology, semantic web

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Authors: Dalia Hanna, Alexander Ferworn

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This research provides detailed proposed training modules for the public safety teams and, specifically, SAR teams responsible for search and rescue operations related to finding lost persons with dementia. Finding a lost person alive is the goal of this training. Time matters if a lost person is to be found alive. Finding lost people living with dementia is quite challenging, as they are unaware they are lost and will not seek help. Even a small contribution to SAR operations could contribute to saving a life. SAR operations will always require expert professional and human volunteers. However, we can reduce their time, save lives, and reduce costs by providing practical training that is based on real-life scenarios. The content for the proposed training is based on the research work done by the researcher in this area. This research has demonstrated that, based on utilizing drones, the algorithmic approach could support a successful search outcome. Understanding the behavior of the lost person, learning where they may be found, predicting their survivability, and automating the search are all contributions of this work, founded in theory and demonstrated in practice. In crisis management, human behavior constitutes a vital aspect in responding to the crisis; the speed and efficiency of the response often get affected by the difficulty of the context of the operation. Therefore, training in this area plays a significant role in preparing the crisis manager to manage the emotional aspects that lead to decision-making in these critical situations. Since it is crucial to gain high-level strategic choices and the ability to apply crisis management procedures, simulation exercises become central in training crisis managers to gain the needed skills to respond critically to these events. The training will enhance the responders’ ability to make decisions and anticipate possible consequences of their actions through flexible and revolutionary reasoning in responding to the crisis efficiently and quickly. As adult learners, search and rescue teams will be approaching training and learning by taking responsibility of the learning process, appreciate flexible learning and as contributors to the teaching and learning happening during that training. These are all characteristics of adult learning theories. The learner self-reflects, gathers information, collaborates with others and is self-directed. One of the learning strategies associated with adult learning is effective elaboration. It helps learners to remember information in the long term and use it in situations where it might be appropriate. It is also a strategy that can be taught easily and used with learners of different ages. Designers must design reflective activities to improve the student’s intrapersonal awareness.

Keywords: training, OER, dementia, drones, search and rescue, adult learning, UDL, instructional design

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Authors: Afaf Alharbi, Qianni Zhang

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

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

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Authors: Azeddine El-Hassouny, Chandrashekhar Meshram, Geraldin Nanfack

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In recent years, learning from data with noisy labels (Label Noise) has been a major concern in supervised learning. This problem has become even more worrying in Deep Learning, where the generalization capabilities have been questioned lately. Indeed, deep learning requires a large amount of data that is generally collected by search engines, which frequently return data with unreliable labels. In this paper, we investigate the Label Noise in Deep Learning using variational inference. Our contributions are : (1) exploiting Label Noise concept where the true labels are learnt using reparameterization variational inference, while observed labels are learnt discriminatively. (2) the noise transition matrix is learnt during the training without any particular process, neither heuristic nor preliminary phases. The theoretical results shows how true label distribution can be learned by variational inference in any discriminate neural network, and the effectiveness of our approach is proved in several target datasets, such as MNIST and CIFAR32.

Keywords: label noise, deep learning, discrete latent variable, variational inference, MNIST, CIFAR32

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Authors: Hassan M. H. Mustafa

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This piece of research addresses an interesting comparative analytical study. Which considers two concepts of diverse algorithmic computational intelligence approaches related tightly with Neural and Non-Neural Systems. The first algorithmic intelligent approach concerned with observed obtained practical results after three neural animal systems’ activities. Namely, they are Pavlov’s, and Thorndike’s experimental work. Besides a mouse’s trial during its movement inside figure of eight (8) maze, to reach an optimal solution for reconstruction problem. Conversely, second algorithmic intelligent approach originated from observed activities’ results for Non-Neural Ant Colony System (ACS). These results obtained after reaching an optimal solution while solving Traveling Sales-man Problem (TSP). Interestingly, the effect of increasing number of agents (either neurons or ants) on learning performance shown to be similar for both introduced systems. Finally, performance of both intelligent learning paradigms shown to be in agreement with learning convergence process searching for least mean square error LMS algorithm. While its application for training some Artificial Neural Network (ANN) models. Accordingly, adopted ANN modeling is a relevant and realistic tool to investigate observations and analyze performance for both selected computational intelligence (biological behavioral learning) systems.

Keywords: artificial neural network modeling, animal learning, ant colony system, traveling salesman problem, computational biology

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Authors: Najith Duminda Galmangoda Guruge, Nadeeka Rathnayake, Vinodani Wimalasena, Dinesha Wijesooriya

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Investing in Early Learning can improve children’ interests for education and makes them ready for school. Children in economically disadvantaged communities may have reduced readiness for schools. Health Promotion approach enables communities including disadvantaged to control over their health. Mothers of children under the age five in ‘Alapathwewa’ community (n=40) were selected as the sample with the aim to promote early learning of children to improve their school readiness. Mothers in ‘Morakeewa’ community (n=40) were the control. Interventions were for a period of 2 years and children of these mothers were followed up to school entry. Importance of early learning and possibility of providing quality learning environments for children at a low cost was discussed with mothers in an experimental setting by facilitators. Mothers were enabled to make age-appropriate baby rooms which provide learning opportunities. Collective community playhouses and play areas were developed by mothers to provide opportunities for children to interact and learn with each other. Mothers started discussing with each other and sharing experiences. The progress was monitored by mothers at regular intervals. Data regarding school competencies of children were obtained from school teachers. School teachers measured thirteen competencies of children on a scale of ‘very good, good, moderate and weak’. All children in the experimental group were in ‘very good’ level in two competencies, ‘communicate friendly with others’ and ‘express ideas well’. Children in the experimental group reported a significantly higher achievement of all thirteen competencies (p < .05) than children in control. Providing quality early learning environments for children even in economically disadvantaged settings makes them ready for schools. Through a Health Promotion approach, early learning experiences for children can be provided at a low cost.

Keywords: disadvantaged, early learning, economically, health promotion

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Authors: Thomas Yeboah, Gifty Akouko Sarpong

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Every learner has a specific learning style that helps him/her to study best. This means that any learning method (e-learning method or traditional face-to-face method) a learner chooses should address the learning style of the learner. Therefore, the main purpose of this research is to investigate whether learners’ grade achievement in e-learning environment is improved for learners with a particular learning style. In this research, purposive sampling technique was employed for selecting the sample size of three hundred and twenty (320) students studying a course UGRC 140 Science and Technology in our Lives at Christian Service University College. Data were analyzed by using, percentages, T -test, and one-way ANOVA. A thorough analysis was done on the data collected and the results revealed that learners with the Assimilator learning style and the converger learning style obtained higher grade achievement than both diverger learning style and accommodative learning style. Again, the results also revealed that accommodative learning style was not good enough for e-learning method.

Keywords: e-learning, learning style, grade achievement, accomodative, divergent, convergent, assimilative

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

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

Keywords: relevance, differentiation, purpose, teaching, learning

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Authors: Jawairia Rasheed

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Modern robots are often used for search and rescue purpose. One of the key areas of interest in such cases is learning complex environments. One of the key methodologies for robots in such cases is reinforcement learning. In reinforcement learning robots learn to move the path to reach the goal while avoiding obstacles. Q-learning, one of the most advancement of reinforcement learning is used for making the robots to learn the path. Robots learn by interacting with the environment to reach the goal. In this paper simulation model of bee-like robots is implemented in NETLOGO. In the start the learning rate was less and it increased with the passage of time. The bees successfully learned to reach the goal while avoiding obstacles through Q-learning technique.

Keywords: reinforlearning of bee like robots for reaching the goalcement learning for randomly placed obstacles, obstacle avoidance through q-learning, q-learning for obstacle avoidance,

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Authors: Jacqueline P. Davies

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Introduction: Student nurses must develop skills in observation, communication and reflection as well as public health knowledge from their first year of training. This paper will explain a method developed for students to collect their own findings about public health in urban areas. These areas are both rich in the history of old public health that informs the content of many traditional public health walks, but are also locations where new public health concerns about chronic disease are concentrated. The learning method explained in this paper enables students to collect their own data and write original work as first year students. Examples of their findings will be given. Methodology: In small groups, health care students are instructed to walk in neighbourhoods near to the hospitals they will soon attend as apprentice nurses. On their walks, they wander slowly, engage in conversations, and enter places open to the public. As they drift, they observe with all five senses in the real three dimensional world to collect data for their reflective accounts of old and new public health. They are encouraged to stop for refreshments and taste, as well as look, hear, smell, and touch while on their walk. They reflect as a group and later develop an individual reflective account in which they write up their deep reflections about what they observed on their walk. In preparation for their walk, they are encouraged to look at studies of quality of Life and other neighbourhood statistics as well as undertaking a risk assessment for their walk. Findings: Reflecting on their walks, students apply theoretical concepts around social determinants of health and health inequalities to develop their understanding of communities in the neighbourhoods visited. They write about the treasured historical architecture made of stone, bronze and marble which have outlived those who built them; but also how the streets are used now. The students develop their observations into thematic analyses such as: what we drink as illustrated by the empty coke can tossed into a now disused drinking fountain; the shift in home-life balance illustrated by streets where families once lived over the shop which are now walked by commuters weaving around each other as they talk on their mobile phones; and security on the street, with CCTV cameras placed at regular intervals, signs warning trespasses and barbed wire; but little evidence of local people watching the street. Conclusion: In evaluations of their first year, students have reported the health walk as one of their best experiences. The innovative approach was commended by the UK governing body of nurse education and it received a quality award from the nurse education funding body. This approach to education allows students to develop skills in the real world and write original work.

Keywords: education, innovation, nursing, urban

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Authors: Degale Desta, Cheng Jian

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The most important factor in identifying a person is their face. Even identical twins have their own distinct faces. As a result, identification and face recognition are needed to tell one person from another. A face recognition system is a verification tool used to establish a person's identity using biometrics. Nowadays, face recognition is a common technique used in a variety of applications, including home security systems, criminal identification, and phone unlock systems. This system is more secure because it only requires a facial image instead of other dependencies like a key or card. Face detection and face identification are the two phases that typically make up a human recognition system.The idea behind designing and creating a face recognition system using deep learning with Azure ML Python's OpenCV is explained in this paper. Face recognition is a task that can be accomplished using deep learning, and given the accuracy of this method, it appears to be a suitable approach. To show how accurate the suggested face recognition system is, experimental results are given in 98.46% accuracy using Fast-RCNN Performance of algorithms under different training conditions.

Keywords: deep learning, face recognition, identification, fast-RCNN

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Authors: Eunice Tan

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The purpose of this presentation is to look at an alternative to the approach and methodologies of working with special needs. The strength-based approach to education embodies a paradigm shift. It is a strategy to move away from a deficit-based methodology which inadvertently may lead to an extensive list of things that the child cannot do or is unable to do. Today, many parents of individuals with special needs are focused on the child’s deficits rather than on his or her strengths. Even when parents Recognise and identify their child’s strengths to be valuable and wish to develop their abilities, they face the challenge that there are insufficient programs committed to supporting the development and improvement of such abilities. What is a strength-based approach in education? A strength-based approach in education focuses on students' positive qualities and contributions to class instead of the skills and abilities they may not have. Many schools are focused on the child’s special educational needs rather than the whole child. Parents interviewed have said that they have to engage external tutors to help hone in on their child’s interests and strengths.

Keywords: differential learning needs, special needs, instructional style, talents

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Authors: J. H. Low, S. H. Hew, C. O. Wong

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This paper proposes an innovative approach to represent the pictogram Chinese characters. The advantage of this representation is using an extraordinary to represent the pictogram Chinese character. This extraordinary representation is created accordingly to the original pictogram Chinese characters revolution. The purpose of this innovative creation is to assistant the learner learning Chinese as second language (SCL) in Chinese language learning specifically on memorize Chinese characters. Commonly, the SCL will give up and frustrate easily while memorize the Chinese characters by rote. So, our innovative representation is able to help on memorize the Chinese character by the help of visually storytelling. This innovative representation enhances the Chinese language learning experience of SCL.

Keywords: Chinese e-learning, innovative Chinese character representation, knowledge management, language learning

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Authors: Shahbaz Ahmed

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This study is conducted to demonstrate the knowledge of intentional learning and incidental learning. Hypothesis of this experiment is intentional learning is better than incidental learning, participants were demonstrated and were asked to learn the 10 nonsense syllables in a specific sequence from the colored cards in the end they were asked to recall the background color of each card instead of nonsense syllables. Independent variables of the experiment are the colored cards containing nonsense syllables which are to be memorized by the participants, dependent variables are the number of correct responses made by the participant. The findings of the experiment concluded that intentional learning is better than incidental learning, hence hypothesis is proved.

Keywords: intentional learning, incidental learning, non-sense syllable cards, score sheets

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Authors: B. El Fadil, R. Najar

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STEM education is promoted by many scholars and curricula around the world, but it is not yet well established in the province of Quebec in Canada. In addition, effective instructional STEM activities and design methods are required to ensure that students and teachers' needs are being met. One potential method is the Engineering Design Process (EDP), a methodology that emphasizes the importance of creativity and collaboration in problem-solving strategies. This article reports on a case study that focused on using the EDP to develop instructional materials by means of making a technological artifact to teach mathematical variables and functions at the secondary level. The five iterative stages of the EDP (design, make, test, infer, and iterate) were integrated into the development of the course materials. Data was collected from different sources: pre- and post-questionnaires, as well as a working document dealing with pupils' understanding based on designing, making, testing, and simulating. Twenty-four grade seven (13 years old) students in Northern Quebec participated in the study. The findings of this study indicate that STEM activities have a positive impact not only on students' engagement in classroom activities but also on learning new mathematical concepts. Furthermore, STEM-focused activities have a significant effect on problem-solving skills development in an interdisciplinary approach. Based on the study's results, we can conclude, inter alia, that teachers should integrate STEM activities into their teaching practices to increase learning outcomes and attach more importance to STEM-focused activities to develop students' reflective thinking and hands-on skills.

Keywords: engineering design process, motivation, stem, integration, variables, functions

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Authors: Ahasanul Haque, Abdullah Sarwar, Khaliq Ahmed

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Networking is important among students to achieve better understanding. Social networking plays an important role in the education. Realizing its huge potential, various organizations, including institutions of higher learning have moved to the area of social networks to interact with their students especially through Facebook. Therefore, measuring the effectiveness of Facebook as a learning tool has become an area of interest to academicians and researchers. Therefore, this study tried to integrate and propose new theoretical and empirical evidences by linking the western idea of adopting Facebook as an alternative learning platform from a Malaysian perspective. This study, thus, aimed to fill a gap by being among the pioneering research that tries to study the effectiveness of adopting Facebook as a learning platform across other cultural settings, namely Malaysia. Structural equation modelling was employed for data analysis and hypothesis testing. This study findings have provided some insights that would likely affect students’ awareness towards using Facebook as an alternative learning platform in the Malaysian higher learning institutions. At the end, future direction is proposed.

Keywords: Learning Management Tool, social networking, education, Malaysia

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Authors: Nicholas V. Scott, Jack McCarthy

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Military, law enforcement, and counter terrorism organizations are often tasked with target detection and image characterization of scenes containing explosive materials in various types of environments where light scattering intensity is high. Mitigation of this photonic noise using classical digital filtration and signal processing can be difficult. This is partially due to the lack of robust image processing methods for photonic noise removal, which strongly influence high resolution target detection and machine learning-based pattern recognition. Such analysis is crucial to the delivery of reliable intelligence. Polarization filters are a possible method for ambient glare reduction by allowing only certain modes of the electromagnetic field to be captured, providing strong scene contrast. An experiment was carried out utilizing a polarization lens attached to a hyperspectral imagery camera for the purpose of exploring the degree to which an imaged polarized scene of potassium, phosphorus, and nitrogen mixture allows for improved target detection and image segmentation. Preliminary imagery results based on the application of machine learning algorithms, including competitive leaky learning and distance metric analysis, to polarized hyperspectral imagery, suggest that polarization filters provide a slight advantage in image segmentation. The results of this work have implications for understanding the presence of explosive material in dry, desert areas where reflective glare is a significant impediment to scene characterization.

Keywords: explosive material, hyperspectral imagery, image segmentation, machine learning, polarization

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Authors: Sylvia Tumelo Nthutang, Nehemiah Mavetera

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Educational institutions are under pressure from their competitors. Regulators and community groups need educational institutions to adopt appropriate business and organizational practices. Globally, educational institutions are now using e-learning as the best teaching and learning approach. E-learning is becoming the center of attention to the learning institutions, educational systems and software inventors. North-West University (NWU) is currently using eFundi, a Learning Management System (LMS). LMS are all information systems and procedures that adds value to students learning and support the learning material in text or any multimedia files. With various e-learning tools, students would be able to access all the materials related to the course in electronic copies. The study was tasked with identifying the e-learning components at the NWU, Mafikeng campus. Quantitative research methodology was considered in data collection and descriptive statistics for data analysis. The Activity Theory (AT) was used as a theory to guide the study. AT outlines the limitations amongst e-learning at the macro-organizational level (plan, guiding principle, campus-wide solutions) and micro-organization (daily functioning practice, collaborative transformation, specific adaptation). On a technological environment, AT gives people an opportunity to change from concentrating on computers as an area of concern but also understand that technology is part of human activities. The findings have identified the university’s current IT tools and knowledge on e-learning elements. It was recommended that university should consider buying computer resources that consumes less power and practice e-learning effectively.

Keywords: e-learning, information and communication technology (ICT), teaching, virtual learning environment

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Authors: Sini George

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Active learning pedagogies are valued for their success in increasing 21st-century learners’ engagement, developing transferable skills like critical thinking or quantitative reasoning, and creating deeper and more lasting educational gains. 'Blended learning' is an active learning pedagogical approach in which direct instruction moves from the group learning space to the individual learning space, and the resulting group space is transformed into a dynamic, interactive learning environment where the educator guides students as they apply concepts and engage creatively in the subject matter. This project aimed to develop a blended learning instructional approach to teaching concepts around pharmaceutical calculations to year 1 pharmacy students. The wrong dose, strength or frequency of a medication accounts for almost a third of medication errors in the NHS therefore, progression to year 2 requires a 70% pass in this calculation test, in addition to the standard progression requirements. Many students were struggling to achieve this requirement in the past. It was also challenging to teach these concepts to students of a large class (> 130) with mixed mathematical abilities, especially within a traditional didactic lecture format. Therefore, short screencasts with voice-over of the lecturer were provided in advance of a total of four teaching sessions (two hours/session), incorporating core content of each session and talking through how they approached the calculations to model metacognition. Links to the screencasts were posted on the learning management. Viewership counts were used to determine that the students were indeed accessing and watching the screencasts on schedule. In the classroom, students had to apply the knowledge learned beforehand to a series of increasingly difficult set of questions. Students were then asked to create a question in group settings (two students/group) and to discuss the questions created by their peers in their groups to promote deep conceptual learning. Students were also given time for question-and-answer period to seek clarifications on the concepts covered. Student response to this instructional approach and their test grades were collected. After collecting and organizing the data, statistical analysis was carried out to calculate binomial statistics for the two data sets: the test grade for students who received blended learning instruction and the test grades for students who received instruction in a standard lecture format in class, to compare the effectiveness of each type of instruction. Student response and their performance data on the assessment indicate that the learning of content in the blended learning instructional approach led to higher levels of student engagement, satisfaction, and more substantial learning gains. The blended learning approach enabled each student to learn how to do calculations at their own pace freeing class time for interactive application of this knowledge. Although time-consuming for an instructor to implement, the findings of this research demonstrate that the blended learning instructional approach improves student academic outcomes and represents a valuable method to incorporate active learning methodologies while still maintaining broad content coverage. Satisfaction with this approach was high, and we are currently developing more pharmacy content for delivery in this format.

Keywords: active learning, blended learning, deep conceptual learning, instructional approach, metacognition, pharmaceutical calculations

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Authors: Engin Eyceyurt, Josko Zec

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The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: drive test, LTE, machine learning, uplink throughput prediction

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Authors: Motahareh Fadaei

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Wireless sensor networks that are used to monitor a special environment, are formed from a large number of sensor nodes. The role of these sensors is to sense special parameters from ambient and to make connection. In these networks, the most important challenge is the management of energy usage. Clustering is one of the methods that are broadly used to face this challenge. In this paper, a distributed clustering protocol based on learning automata is proposed for underwater wireless sensor networks. The proposed algorithm that is called LA-Clustering forms clusters in the same energy level, based on the energy level of nodes and the connection radius regardless of size and the structure of sensor network. The proposed approach is simulated and is compared with some other protocols with considering some metrics such as network lifetime, number of alive nodes, and number of transmitted data. The simulation results demonstrate the efficiency of the proposed approach.

Keywords: clustering, energy consumption‎, learning automata, underwater sensor networks

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Authors: H. S. Saini, K. Vijayalakshmi, Rishi Sayal

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Network-based education has been growing rapidly in size and quality. Knowledge clustering becomes more important in personalized information retrieval for web-learning. A personalized-Learning service after the learners’ knowledge has been classified with clustering. Through automatic analysis of learners’ behaviors, their partition with similar data level and interests may be discovered so as to produce learners with contents that best match educational needs for collaborative learning. We present a specific mining tool and a recommender engine that we have integrated in the online learning in order to help the teacher to carry out the whole e-learning process. We propose to use sequential pattern mining algorithms to discover the most used path by the students and from this information can recommend links to the new students automatically meanwhile they browse in the course. We have Developed a specific author tool in order to help the teacher to apply all the data mining process. We tend to report on many experiments with real knowledge so as to indicate the quality of using both clustering and sequential pattern mining algorithms together for discovering personalized e-learning systems.

Keywords: e-learning, cluster, personalization, sequence, pattern

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Authors: Jodie Lee, Lorena Chan, Esther Tong

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Hong Kong students face a unique learning environment. Starting from the 2010/2011 school year, The Education Bureau (EDB) of the Government of the Hong Kong Special Administrative Region implemented the fine-tuned Medium of Instruction (MOI) arrangements for secondary schools. Since then, secondary schools in Hong Kong have been given the flexibility to decide the most appropriate MOI arrangements for their schools and under the new academic structure for senior secondary education, particularly on the compulsory part of the mathematics curriculum. In 2019, Hong Kong Diploma of Secondary Education Examination (HKDSE), over 40% of school day candidates attempted the Mathematics Compulsory Part examination in the Chinese version while the rest took the English version. Moreover, only 14.38% of candidates sat for one of the extended Mathematics modules. This results in a serious of intricate issues to students’ learning in post-secondary education programmes. It is worth to note that when students further pursue to an higher education in Hong Kong or even oversea, they may facing substantial difficulties in transiting learning from learning mathematics in their mother tongue in Chinese-medium instruction (CMI) secondary schools to an English-medium learning environment. Some students understood the mathematics concepts were found to fail to fulfill the course requirements at college or university due to their learning experience in secondary study at CMI. They are particularly weak in comprehending the mathematics questions when they are doing their assessment or attempting the test/examination. A government funded project was conducted with the aims of providing integrated learning context and language support to students with a lower level of numeracy and/or with CMI learning experience. By introducing this “integrated concept + language mapping approach”, students can cope with the learning challenges in the compulsory English-medium mathematics and statistics subjects in their tertiary education. Ultimately, in the hope that students can enhance their mathematical ability, analytical skills, and numerical sense for their lifelong learning. The “Concept + Language Mapping “(CLM) approach was adopted and tried out in the bridging courses for students with a lower level of numeracy and/or with CMI learning experiences. At the beginning of each class, a pre-test was conducted, and class time was then devoted to introducing the concepts by CLM approach. For each concept, the key thematic items and their different semantic relations are presented using graphics and animations via the CLM approach. At the end of each class, a post-test was conducted. Quantitative data analysis was performed to study the effect on students’ learning via the CLM approach. Stakeholders' feedbacks were collected to estimate the effectiveness of the CLM approach in facilitating both content and language learning. The results based on both students’ and lecturers’ feedback indicated positive outcomes on adopting the CLM approach to enhance the mathematical ability and analytical skills of CMI students.

Keywords: mathematics, Concept+Language Mapping, level of numeracy, medium of instruction

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Authors: Vera G. Dianova, Lori P. Montross, Charles M. Burke

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In the digital age, the widespread and frequently excessive use of mobile phones amongst university students is recognized as a significant distractor which interferes with their ability to enter a deep state of concentration during studies and diminishes their prospects of experiencing the enjoyable and instrumental state of flow, as defined and described by psychologist M. Csikszentmihalyi. This study has targeted 50 university students with the aim of teaching them to cultivate their ability to engage in deep work and to attain the state of flow, fostering more effective and enjoyable learning experiences. Prior to the start of the intervention, all participating students completed a comprehensive survey based on a variety of validated scales assessing their inclination toward lifelong learning, frequency of flow experiences during study, frustration tolerance, sense of agency, as well as their love of learning and daily time devoted to non-academic mobile phone activities. Several days after this initial assessment, students received a 90-minute lecture on the principles of flow and deep work, accompanied by a critical discourse on the detrimental effects of excessive mobile phone usage. They were encouraged to practice deep work and strive for frequent flow states throughout the semester. Subsequently, students submitted weekly surveys, including the 10-item CORE Dispositional Flow Scale, a 3-item agency scale and furthermore disclosed their average daily hours spent on non-academic mobile phone usage. As a final step, at the end of the semester students engaged in reflective report writing, sharing their experiences and evaluating the intervention's effectiveness. They considered alterations in their love of learning, reflected on the implications of their mobile phone usage, contemplated improvements in their tolerance for boredom and perseverance in complex tasks, and pondered the concept of lifelong learning. Additionally, students assessed whether they actively took steps towards managing their recreational phone usage and towards improving their commitment to becoming lifelong learners. Employing a mixed-methods approach our study offers insights into the dynamics of concentration, flow, mobile phone usage and attitudes towards learning among undergraduate and graduate university students. The findings of this study aim to promote profound contemplation, on the part of both students and instructors, on the rapidly evolving digital-age higher education environment. In an era defined by digital and AI advancements, the ability to concentrate, to experience the state of flow, and to love learning has never been more crucial. This study underscores the significance of addressing mobile phone distractions and providing strategies for cultivating deep concentration. The insights gained can guide educators in shaping effective learning strategies for the digital age. By nurturing a love for learning and encouraging lifelong learning, educational institutions can better prepare students for a rapidly changing labor market, where adaptability and continuous learning are paramount for success in a dynamic career landscape.

Keywords: deep work, flow, higher education, lifelong learning, love of learning

Procedia PDF Downloads 47

Authors: Airy Huang, Fuji Foo, Aries Prasetya Wibowo

Abstract:

In recent years, the focus of Natural Language Processing (NLP) development has been gradually shifting from the semantics-based approach to deep learning one, which performs faster with fewer resources. Although it performs well in many applications, the deep learning approach, due to the lack of semantics understanding, has difficulties in noticing and expressing a novel business case with a pre-defined scope. In order to meet the requirements of specific robotic services, deep learning approach is very labor-intensive and time consuming. It is very difficult to improve the capabilities of conversational AI in a short time, and it is even more difficult to self-learn from experiences to deliver the same service in a better way. In this paper, we present an adaptive conversational AI algorithm that combines both semantic knowledge and deep learning to address this issue by learning new business cases through conversations. After self-learning from experience, the robot adapts to the business cases originally out of scope. The idea is to build new or extended robotic services in a systematic and fast-training manner with self-configured programs and constructed dialog flows. For every cycle in which a chat bot (conversational AI) delivers a given set of business cases, it is trapped to self-measure its performance and rethink every unknown dialog flows to improve the service by retraining with those new business cases. If the training process reaches a bottleneck and incurs some difficulties, human personnel will be informed of further instructions. He or she may retrain the chat bot with newly configured programs, or new dialog flows for new services. One approach employs semantics analysis to learn the dialogues for new business cases and then establish the necessary ontology for the new service. With the newly learned programs, it completes the understanding of the reaction behavior and finally uses dialog flows to connect all the understanding results and programs, achieving the goal of self-learning process. We have developed a chat bot service mounted on a kiosk, with a camera for facial recognition and a directional microphone array for voice capture. The chat bot serves as a concierge with polite conversation for visitors. As a proof of concept. We have demonstrated to complete 90% of reception services with limited self-learning capability.

Keywords: conversational AI, chatbot, dialog management, semantic analysis

Procedia PDF Downloads 111

Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: cyber security, intrusion prevention, optimal policy, Q-learning

Procedia PDF Downloads 207

Authors: Rachael Olubukola Afolabi

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Immersive technologies known as X Reality or Cross Reality that include virtual reality augmented reality, and mixed reality have pervaded into the education system at different levels from elementary school to adult learning. Instructors, instructional designers, and learning experience specialists continue to find new ways to engage students in the learning process using technology. While the progression of web technologies has enhanced digital learning experiences, analytics on learning outcomes continue to be explored to determine the relevance of these technologies in learning. Digital learning has evolved from web 1.0 (static) to 4.0 (dynamic and interactive), and this evolution of technologies has also advanced teaching methods and approaches. This paper explores how these technologies are being utilized in learning and the results that educators and learners have identified as effective learning opportunities and approaches.

Keywords: immersive technologoes, virtual reality, augmented reality, technology in learning

Procedia PDF Downloads 119

Authors: Kyria Rebeca Finardi

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The study discusses the role of foreign languages in general and of English in particular in the process of internationalization of higher education (IHE), defined as the intentional integration of an international, intercultural or global dimension in the purpose, function or offer of higher education. The study is bibliographical and offers a brief outline of the current political, economic and educational scenarios in Brazil, before discussing some possibilities and challenges for the development of multilingualism and IHE there. The theoretical background includes a review of Brazilian language and internationalization policies. The review and discussion concludes that the use of the Content and Language Integrated Learning (CLIL) approach and the Intercomprehension approach to foreign language teaching/learning are relevant alternatives to foster multilingualism in that context.

Keywords: Brazil, higher education, internationalization, multilingualism

Procedia PDF Downloads 127