Search results for: quest based learning

Authors: Kashika P. H.

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The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty.

Keywords: Amazon rekognition, API, deep learning, computer vision, face detection, text detection

Procedia PDF Downloads 97

Authors: Derssie Mebratu

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As a large variety of micro services, web services, social graphic applications, and media applications are continuously developed, it is substantially vital to design and build a reliable, efficient, and faster memory tiering system. Despite limited design, implementation, and deployment in the last few years, several techniques are currently developed to improve a memory tiering system in a cloud. Some of these techniques are to develop an optimal scanning frequency; improve and track pages movement; identify pages that recently accessed; store pages across each tiering, and then identify pages as a hot, warm, and cold so that hot pages can store in the first tiering Dynamic Random Access Memory (DRAM) and warm pages store in the second tiering Compute Express Link(CXL) and cold pages store in the third tiering Non-Volatile Memory (NVM). Apart from the current proposal and implementation, we also develop a new technique based on a machine learning algorithm in that the throughput produced 25% improved performance compared to the performance produced by the baseline as well as the latency produced 95% improved performance compared to the performance produced by the baseline.

Keywords: machine learning, bayesian optimization, memory tiering, CXL, DRAM

Procedia PDF Downloads 87

Authors: Saman Khairani

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Assessment is a pivotal component of the teaching and learning process, serving as a critical tool for evaluating student progress, diagnosing learning needs, and informing instructional decisions. In the context of English Language Teaching (ELT), effective assessment practices are essential to promote meaningful learning experiences and foster continuous improvement in language proficiency. This paper delves into various assessment strategies, explores associated challenges, and highlights best practices for assessing student learning in ELT. The paper begins by examining the diverse forms of assessment, including formative assessments that provide timely feedback during the learning process and summative assessments that evaluate overall achievement. Additionally, alternative methods such as portfolios, self-assessment, and peer assessment play a significant role in capturing various aspects of language learning. Aligning assessments with learning objectives is crucial. Educators must ensure that assessment tasks reflect the desired language skills, communicative competence, and cultural awareness. Validity, reliability, and fairness are essential considerations in assessment design. Challenges in assessing language skills—such as speaking, listening, reading, and writing—are discussed, along with practical solutions. Constructive feedback, tailored to individual learners, guides their language development. In conclusion, this paper synthesizes research findings and practical insights, equipping ELT practitioners with the knowledge and tools necessary to design, implement, and evaluate effective assessment practices. By fostering meaningful learning experiences, educators contribute significantly to learners’ language proficiency and overall success.

Keywords: ELT, formative, summative, fairness, validity, reliability

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Authors: Pedro Martinez-Santos, Víctor Gómez-Escalonilla, Silvia Díaz-Alcaide, Esperanza Montero, Miguel Martín-Loeches

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Groundwater monitoring networks are critical in evaluating the vulnerability of groundwater resources to depletion and contamination, both in space and time. Groundwater monitoring networks typically grow over decades, often in organic fashion, with relatively little overall planning. The groundwater monitoring networks in the Madrid area, Spain, were reviewed for the purpose of identifying gaps and opportunities for improvement. Spatial analysis reveals the presence of various monitoring networks belonging to different institutions, with several hundred observation wells in an area of approximately 4000 km2. This represents several thousand individual data entries, some going back to the early 1970s. Major issues included overlap between the networks, unknown screen depth/vertical distribution for many observation boreholes, uneven time series, uneven monitored species, and potentially suboptimal locations. Results also reveal there is sufficient information to carry out a spatial and temporal analysis of groundwater vulnerability based on machine learning applications. These can contribute to improve the overall planning of monitoring networks’ expansion into the future.

Keywords: groundwater monitoring, observation networks, machine learning, madrid

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Authors: Wen-Wei Chiang

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In this study, the researcher developed a scale for use in measuring the degree to which high school students experience a state of flow. The researcher then verified its reliability and validity in an actual classroom setting. The ultimate objective was to identify feasible methods by which to promote the experience of a flow state among high school students engaged in the study of science. The nine indices identified in this study to assess the engagement of high school students focus primarily on the study of science-related topics; however, the principles on which they are based are applicable to a wide range of learning situations. Teachers must outline the goals of each lesson clearly and provide unambiguous feedback. They must also look for ways to make the lessons more fun and appealing.

Keywords: flow experience, positive psychology, questionnaire, science learning

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Authors: Rohit Mittal, Bright Keswani, Amit Mithal

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This paper provides a sense about the application of computational intelligence techniques used to develop computer games, especially car racing. For the deep sense and knowledge of artificial intelligence, this paper is divided into various sections that is optimization, imitation, innovation and combining approach of optimization and imitation. This paper is mainly concerned with combining approach which tells different aspects of using fitness measures and supervised learning techniques used to imitate aspects of behavior. The main achievement of this paper is based on modelling player behaviour and evolving new game content such as racing tracks as single car racing on single track.

Keywords: evolution algorithm, genetic, optimization, imitation, racing, innovation, gaming

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Authors: Adil Ishag

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Diglossia emerges in a situation where two distinctive varieties of a language are used alongside within a certain community. In this case, one is considered as a high or standard variety and the second one as a low or colloquial variety. Arabic is an extreme example of a highly diglossic language. This diglossity is due to the fact that Arabic is one of the most spoken languages and spread over 22 Countries in two continents as a mother tongue, and it is also widely spoken in many other Islamic countries as a second language or simply the language of Quran. The geographical variation between the countries where the language is spoken and the duality of the classical Arabic and daily spoken dialects in the Arab world on the other hand; makes the Arabic language one of the most diglossic languages. This paper tries to investigate this phenomena and its relation to learning Arabic as a first and second language.

Keywords: Arabic language, diglossia, first and second language, language learning

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Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

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In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning

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Authors: Kasun P. Wijayaratna, Lauren Gardner, Taha Hossein Rashidi

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Undergraduate students entering university across the last 2 to 3 years tend to be born during the middle years of the 1990s. This generation of students has been exposed to the internet and the desire and dependency on technology since childhood. Brains develop based on environmental influences and technology has wired this generation of student to be attuned to sophisticated complex visual imagery, indicating visual forms of learning may be more effective than the traditional lecture or discussion formats. Furthermore, post-millennials perspectives on career are not focused solely on stability and income but are strongly driven by interest, entrepreneurship and innovation. Accordingly, it is important for educators to acknowledge the generational shift and tailor the delivery of learning material to meet the expectations of the students and the needs of industry. In the context of transport engineering, effectively teaching undergraduate students the basic principles of transport planning, traffic engineering and highway design is fundamental to the progression of the profession from a practice and research perspective. Recent developments in technology have transformed the discipline as practitioners and researchers move away from the traditional “pen and paper” approach to methods involving the use of computer programs and simulation. Further, enhanced accessibility of technology for students has changed the way they understand and learn material being delivered at tertiary education institutions. As a consequence, blended learning approaches, which aim to integrate face to face teaching with flexible self-paced learning resources, have become prevalent to provide scalable education that satisfies the expectations of students. This research study involved the development of a series of ‘Blended Learning’ initiatives implemented within an introductory transport planning and geometric design course, CVEN2401: Sustainable Transport and Highway Engineering, taught at the University of New South Wales, Australia. CVEN2401 was modified by conducting interactive polling exercises during lectures, including weekly online quizzes, offering a series of supplementary learning videos, and implementing a realistic design project that students needed to complete using modelling software that is widely used in practice. These activities and resources were aimed to improve the learning environment for a large class size in excess of 450 students and to ensure that practical industry valued skills were introduced. The case study compared the 2016 and 2017 student cohorts based on their performance across assessment tasks as well as their reception to the material revealed through student feedback surveys. The initiatives were well received with a number of students commenting on the ability to complete self-paced learning and an appreciation of the exposure to a realistic design project. From an educator’s perspective, blending the course made it feasible to interact and engage with students. Personalised learning opportunities were made available whilst delivering a considerable volume of complex content essential for all undergraduate Civil and Environmental Engineering students. Overall, this case study highlights the value of blended learning initiatives, especially in the context of large class size university courses.

Keywords: blended learning, highway design, teaching, transport planning

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Authors: Andreas Johansson

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Conceptual understanding needs to be grounded on observation of physical phenomena, experiences or metaphors. Observation of physical phenomena using demonstration experiments has a long tradition within physics education and students need to develop mental models to relate the observations to concepts from scientific theories. This study investigates how live and video experiments involving an acoustic trap to visualize particle-field interaction, field properties and particle properties can help develop students' mental models and how they can be used differently to realize their potential as teaching tools. Initially, they were treated as analogs and the lesson designs were kept identical. With a design-based approach, the experimental and video designs, as well as best practices for a respective teaching tool, were then developed in iterations. Variation theory was used as a theoretical framework to analyze the planned respective realized pattern of variation and invariance in order to explain learning outcomes as measured by a pre-posttest consisting of conceptual multiple-choice questions inspired by the Force Concept Inventory and the Force and Motion Conceptual Evaluation. Interviews with students and teachers were used to inform the design of experiments and videos in each iteration. The lesson designs and the live and video experiments has been developed to help teachers improve student learning and make school physics more interesting by involving experimental setups that usually are out of reach and to bridge the gap between what happens in classrooms and in science research. As students’ conceptual knowledge also rises their interest in physics the aim is to increase their chances of pursuing careers within science, technology, engineering or mathematics.

Keywords: acoustic trap, design-based research, experiments, variation theory

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Authors: Ambeck Celyne Tebid, Harry S. Rampa

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The South African Education system recognises the need for all learners including those experiencing learning difficulties, to have access to a single unified system of education. For teachers to be pedagogically responsive to an increasingly diverse learner population without appropriate support has been proven to be unrealistic. As such, this has considerably hampered interest amongst teachers, especially those at the foundation phase to work within an Inclusive Education (IE) and training system. This qualitative study aimed at investigating foundation phase teachers’ experiences of school-based support teams (SBSTs) in two Full-Service (inclusive schools) and one Mainstream public primary school in the Gauteng province of South Africa; with particular emphasis on finding ways to supporting them, since teachers claimed they were not empowered in their initial training to teach learners experiencing learning difficulties. Hence, SBSTs were created at school levels to fill this gap thereby, supporting teaching and learning by identifying and addressing learners’, teachers’ and schools’ needs. With the notion that IE may be failing because of systemic reasons, this study uses Bronfenbrenner’s (1979) ecosystemic as well as Piaget’s (1980) maturational theory to examine the nature of support and experiences amongst teachers taking individual and systemic factors into consideration. Data was collected using in-depth, face-to-face interviews, document analysis and observation with 6 foundation phase teachers drawn from 3 different schools, 3 SBST coordinators, and 3 school principals. Data was analysed using the phenomenological data analysis method. Amongst the findings of the study is that South African full- service and mainstream schools have functional SBSTs which render formal and informal support to the teachers; this support varies in quality depending on the socio-economic status of the relevant community where the schools are situated. This paper, however, argues that what foundation phase teachers settled for as ‘support’ is flawed; as well as how they perceive the SBST and its role is problematic. The paper conclude by recommending that, the SBST should consider other approaches at foundation phase teacher support such as, empowering teachers with continuous practical experiences on how to deal with real classroom scenarios, as well as ensuring that all support, be it on academic or non-academic issues should be provided within a learning community framework where the teacher, family, SBST and where necessary, community organisations should harness their skills towards a common goal.

Keywords: foundation phase, full- service schools, inclusive education, learning difficulties, school-based support teams, teacher support

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Authors: Tahir Mehmood, Mumtaz Akhter

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The global need for conflict management is greater now in the early 21st century than ever before. According to UNESCO, half of the world’s 195 countries will have to expand their stock of educationist significantly, some by tens of thousands, if the goal development targets are desired to achieve. Socioeconomic inequities, political instability, demographic changes and crises such as the HIV/AIDs epidemic have engendered huge shortfalls in teacher supply and low teacher quality in many developing countries. Education serves as back bone in development process. Open learning and distance education programs are serving as pivotal part of development process. It is now clear that ‘bricks and mortar’ approaches to expanding teacher education may not be adequate if the current and projected shortfalls in teacher supply and low teacher quality are to be properly addressed. The study is designed to measure the perceptions of teaching learning community about conflict management with special reference to open and distance learning. It was descriptive study which targeted teachers, students, community members and experts. Data analysis was carried out by using statistical techniques served by SPSS. Findings reflected that audience perceives open and distance learning as change agent and as development tool. It is noticed that target audience has driven prominent performance by using facility of open and distance learning.

Keywords: conflict management, open and distance learning, teachers, students

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Authors: Olubukola Olumuyiwa Tokede, Dominic D. Ahiaga-Dagbui, John Morrison

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The project environment in construction has been widely criticised for its inability to learn from experience effectively. As each project is bespoke, learning is ephemeral, as it is often confined within its bounds and seldom assimilated with others that are being delivered in the project environment. To engender learning across construction projects, collaborative contractual arrangements, such as alliancing and partnering, have been embraced to aid the transferability of lessons across projects. These cooperative arrangements, however, tend to be costly, and hence construction organisations could revert to less expensive traditional procurement approaches after successful collaborative project delivery. This research, therefore, seeks to assess the lessons-learned in a post-alliance contractual framework. Using a case-study approach, we examine the experiences of a public sector authority who engaged a project facilitator to foster learning during the delivery of a significant piece of critical infrastructure. It was found that the facilitator enabled optimal learning outcomes in post-alliance contractual frameworks by attenuating the otherwise adversarial relationship between clients and contractors. Further research will seek to assess the effectiveness of different knowledge-brokering agencies in construction projects.

Keywords: facilitation, knowledge-brokering, learning, projects

Procedia PDF Downloads 126

Authors: Liliana O. Martínez, Juan E. González, Manuel Ramírez-Aranda, Ana Cervantes-Herrera

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In this work, the use of a collection of mathematical challenges and puzzles aimed at students who are starting in algebra is proposed. The selected challenges and puzzles are intended to arouse students' interest in this area of mathematics, in addition to facilitating the teaching-learning process through challenges such as riddles, crossword puzzles, and board games, all in everyday situations that allow them to build themselves the learning. For this, it is proposed to carry out a "Math Rally: algebra" divided into four sections: mathematical reasoning, a hierarchy of operations, fractions, and algebraic equations.

Keywords: algebra, algebraic challenge, algebraic puzzle, math rally

Procedia PDF Downloads 150

Authors: Ling Qi, Matloob Khushi, Josiah Poon

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This paper introduces a pre-trained Masked Candlestick Model (MCM) for trading time-series data. The pre-trained model is based on three core designs. First, we convert trading price data at each data point as a set of normalized elements and produce embeddings of each element. Second, we generate a masked sequence of such embedded elements as inputs for self-supervised learning. Third, we use the encoder mechanism from the transformer to train the inputs. The masked model learns the contextual relations among the sequence of embedded elements, which can aid downstream classification tasks. To evaluate the performance of the pre-trained model, we fine-tune MCM for three different downstream classification tasks to predict future price trends. The fine-tuned models achieved better accuracy rates for all three tasks than the baseline models. To better analyze the effectiveness of MCM, we test the same architecture for three currency pairs, namely EUR/GBP, AUD/USD, and EUR/JPY. The experimentation results demonstrate MCM’s effectiveness on all three currency pairs and indicate the MCM’s capability for signal extraction from trading data.

Keywords: masked language model, transformer, time series prediction, trading prediction, embedding, transfer learning, self-supervised learning

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Authors: Siyao Zhu, Yifang Xu

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After natural and man-made disasters, robots can bypass the danger, expedite the search, and acquire unprecedented situational awareness to design rescue plans. The hands-free requirement from the first responders excludes the use of tedious manual control and operation. In unknown, unstructured, and obstructed environments, natural-language-based supervision is not amenable for first responders to formulate, and is difficult for robots to understand. Brain-computer interface is a promising option to overcome the limitations. This study aims to test the feasibility of using electroencephalography (EEG) signals to decode human intentions and detect the level of consensus on robot-provided information. EEG signals were classified using machine-learning and deep-learning methods to discriminate search intentions and agreement perceptions. The results show that the average classification accuracy for intention recognition and consensus assessment is 67% and 72%, respectively, proving the potential of incorporating recognizable users’ bioelectrical responses into advanced robot-assisted systems for emergency response.

Keywords: consensus assessment, electroencephalogram, emergency response, human-robot collaboration, intention recognition, search and rescue

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Authors: J. Miranda, D. Chavarría-Barrientos, M. Ramírez-Cadena, M. E. Macías, P. Ponce, J. Noguez, R. Pérez-Rodríguez, P. K. Wright, A. Molina

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Higher education methods need to evolve because the new generations of students are learning in different ways. One way is by adopting emergent technologies, new learning methods and promoting the maker movement. As a result, Tecnologico de Monterrey is developing Open Innovation Laboratories as an immediate response to educational challenges of the world. This paper presents an Open Innovation Laboratory for Rapid Realization of Sensing, Smart and Sustainable Products (S³ Products). The Open Innovation Laboratory is composed of a set of specific resources where students and teachers use them to provide solutions to current problems of priority sectors through the development of a new generation of products. This new generation of products considers the concepts Sensing, Smart, and Sustainable. The Open Innovation Laboratory has been implemented in different courses in the context of New Product Development (NPD) and Integrated Manufacturing Systems (IMS) at Tecnologico de Monterrey. The implementation consists of adapting this Open Innovation Laboratory within the course’s syllabus in combination with the implementation of specific methodologies for product development, learning methods (Active Learning and Blended Learning using Massive Open Online Courses MOOCs) and rapid product realization platforms. Using the concepts proposed it is possible to demonstrate that students can propose innovative and sustainable products, and demonstrate how the learning process could be improved using technological resources applied in the higher educational sector. Finally, examples of innovative S³ products developed at Tecnologico de Monterrey are presented.

Keywords: active learning, blended learning, maker movement, new product development, open innovation laboratory

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Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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Authors: Abdulmutallib U. Baraya, Aishatu M. Chadi, Zainab A. Aliyu, Agatha Samson

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Learning Resources is the field of study that investigates the process of analyzing, designing, developing, implementing, and evaluating learning materials, learners, and the learning process in order to improve teaching and learning in university-level education essential for empowering students and various sectors of Nigeria’s economy to succeed in a fast-changing global economy. Innovation in the information age of the 21st century is the use of educational technologies in the classroom for instructional delivery, it involves the use of appropriate educational technologies like smart boards, computers, projectors and other projected materials to facilitate learning and improve performance. The study examined learning resources as determinants for improving the teaching and learning process in Abubakar Tafawa Balewa University (ATBU), Bauchi, Bauchi state of Nigeria. Three objectives, three research questions and three null hypotheses guided the study. The study adopted a Survey research design. The population of the study was 880 lecturers. A sample of 260 was obtained using the research advisor table for determining sampling, and 250 from the sample was proportionately selected from the seven faculties. The instrument used for data collection was a structured questionnaire. The instrument was subjected to validation by two experts. The reliability of the instrument stood at 0.81, which is reliable. The researchers, assisted by six research assistants, distributed and collected the questionnaire with a 75% return rate. Data were analyzed using mean and standard deviation to answer the research questions, whereas simple linear regression was used to test the null hypotheses at a 0.05 level of significance. The findings revealed that physical facilities and digital technology tools significantly improved the teaching and learning process. Also, consumables, supplies and equipment do not significantly improve the teaching and learning process in the faculties. It was recommended that lecturers in the various faculties should strengthen and sustain the use of digital technology tools, and there is a need to strive and continue to properly maintain the available physical facilities. Also, the university management should, as a matter of priority, continue to adequately fund and upgrade equipment, consumables and supplies frequently to enhance the effectiveness of the teaching and learning process.

Keywords: education, facilities, learning-resources, technology-tools

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Authors: Jürgen Keil, Frank Walther

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This article presents two innovative solutions for vertical vibration mitigation barriers including experimental and numerical investigations on the completed barriers. There is a continuing growth of exposure to noise and vibration in people´s daily lives due to the quest for more mobility and flexibility. In previous times neglected, immissions caused by vibrations can lead, for example, to secondary noise or damage in the adjacent buildings. Also people can feel very affected by vibrations. But unlike in new construction, in existing infrastructure and buildings action can be taken almost only on the transmission path of those vibrations. In the following two solutions were shown how vibrations on the transmission path can be mitigated. These are the jet grouting method and a new installation method (patent pending) by means of a prefabricated hollow box which is filled with vibration reducing mats and driven down to depth, are presented. The essential results of the numerical and experimental investigations on the completed wave barriers are included as well. This article is based on the results of a field test with the participation of Keller Holding, which was executed in the context of the European research project RIVAS (Railway Induced Vibration Abatement Solutions), and on a thesis done at the Technical University of Dresden with the involvement of BAUGRUND DRESDEN Ingenieurgesellschaft mbH and the Keller Holding GmbH.

Keywords: jet grouting, rail way lines, vertical vibration mitigation, vibration reducing mats

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Authors: Liu Yi Hui

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The COVID-19 pandemic in 2020 has globally affected all aspects of life, with social distancing and quarantine orders causing turmoil and learning in community colleges being temporarily paused. In fact, this is the first time that adult education has faced such a severe challenge. It forces researchers to reflect on the impact of pandemics on adult education and ways to respond. Distance learning appears to be one of the pedagogical tools capable of dealing with interpersonal isolation and social distancing caused by the pandemic. This research aims to examine whether the impact of social distancing during COVID-19 will lead to increased acceptance of technology and, subsequently, an increase in adults ’ willingness to participate in distance learning. The hypothesis that social distancing and the desire to participate in distance learning affects learners’ tendency to accept technology is investigated. Teachers ’ participation in distance education and acceptance of technology are used as adjustment variables with the relationship to “social distancing,” “participation in distance learning,” and “acceptance of technology” of learners. A questionnaire survey was conducted over a period of twelve months for teachers and learners at all community colleges in Taiwan who enrolled in a basic unit course. Community colleges were separated using multi-stage cluster sampling, with their locations being metropolitan, non-urban, south, and east as criteria. Using the G*power software, 660 samples were selected and analyzed. The results show that through appropriate pedagogical strategies or teachers ’ own acceptance of technology, adult learners’ willingness to participate in distance learning could be influenced. A diverse model of participation can be developed, improving adult education institutions’ ability to plan curricula to be flexible to avoid the risk associated with epidemic diseases.

Keywords: social distancing, adult learning, community colleges, technology acceptance model

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Authors: Kawai Nobuaki

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This paper describes the design and implementation of web system for continuable and viable collaboration. This study proposes the improvement of the system based on a result of a certain practice. As contemporary higher education information environments transform, this study highlights the significance of university identity and college identity that are formed continuously through independent activities of the students. Based on these discussions, the present study proposes a practical media environment design which facilitates the processes of organizational identity formation based on a continuous and cyclical model. Even if users change by this system, the communication system continues operation and cooperation. The activity becomes the archive and produces new activity. Based on the result, this study elaborates a plan with a re-design by a system from the viewpoint of second-order cybernetics. Systems theory is a theoretical foundation for our study.

Keywords: collaborative work, learning management system, second-order cybernetics, systems theory, user generated contents, viable system model

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Authors: Kavita Bodke

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Structural health monitoring (SHM) is experiencing growth, necessitating the development of distinct methodologies to address its expanding scope effectively. In this study, we developed automatic structure damage identification, which incorporates three unique types of a building’s structural integrity. The first pertains to the presence of fractures within the structure, the second relates to the issue of dampness within the structure, and the third involves corrosion inside the structure. This study employs image classification techniques to discern between intact and impaired structures within structural data. The aim of this research is to find automatic damage detection with the probability of each damage class being present in one image. Based on this probability, we know which class has a higher probability or is more affected than the other classes. Utilizing photographs captured by a mobile camera serves as the input for an image classification system. Image classification was employed in our study to perform multi-class and multi-label classification. The objective was to categorize structural data based on the presence of cracks, moisture, and corrosion. In the context of multi-class image classification, our study employed three distinct methodologies: Random Forest, Multilayer Perceptron, and CNN. For the task of multi-label image classification, the models employed were Rasnet, Xceptionet, and Inception.

Keywords: SHM, CNN, deep learning, multi-class classification, multi-label classification

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Authors: Hamed Zolfaghari, Mojtaba Kord

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After feasibility study the design phase is started and the rest of other phases are highly dependent on this phase. forecasting the duration of design phase could do a miracle and would save a lot of time. This study provides a fast and accurate Machine learning (ML) and optimization framework, which allows a quick duration estimation of project design phase, hence improving operational efficiency and competitiveness of a design construction company. 3 data sets of three years composed of daily time spent for different design projects are used to train and validate the ML models to perform multiple projects. Our study concluded that Artificial Neural Network (ANN) performed an accuracy of 0.94.

Keywords: time estimation, machine learning, Artificial neural network, project design phase

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Authors: Isiya Shinkafi Salihu

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Open education resources (OER) are open learning materials in different formats, course content and context to support learning globally. This study investigated the level of awareness of Hospitality and Tourism OER among students in the Department of Tourism and Hotel Management in a University. Specifically, it investigated students’ awareness, use and accessibility of OER in learning. The research design method used was the quantitative approach, using an online questionnaire. The thesis research shows that respondents frequently use OER but with little knowledge of the content and context of the material. Most of the respondents’ have little knowledge about the concept even though they use it. Information and communication technologies are tools for information gathering, social networking and knowledge sharing and transfer. OER are open education materials accessible online such as curriculum, maps, course materials, and videos that users create, adapt, reuse for learning and research. Few of the respondents that used OER in learning faced some challenges such as high cost of data, poor connectivity and lack of proper guidance. The results suggest a lack of awareness of OER among students in the faculty of tourism and the need for support from the teachers in the utilization of OER. The thesis also reveals that some of the international students are accessing the internet as beginners in their studies which require guidance. The research, however, recommends that further studies should be conducted to other faculties.

Keywords: creative commons, open education resources, open licenses, information and communication technology

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Authors: B. K. Manjunatha Goud, Aruna Chanu Oinam

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The undergraduate medical curriculum is oriented towards training the students to undertake the responsibilities of a physician. During the training period, adequate emphasis is placed on inculcating logical and scientific habits of thought; clarity of expression and independence of judgment; and ability to collect and analyze information and to correlate them. At Ras Al Khaimah Medical and Health Sciences University (RAKMHSU), Biochemistry a basic medical science subject is taught in the 1st year of 5 years medical course with vertical interdisciplinary interaction with all subjects, which needs to be taught and learned adequately by the students to be related to clinical case or clinical problem in medicine and future diagnostics so that they can practice confidently and skillfully in the community. Based on these facts study was done to know the extent of usage of library resources by the students and the impact of study materials on their preparation for examination. It was a comparative cross sectional study included 100 and 80 1st and 2nd-year students who had successfully completed Biochemistry course. The purpose of the study was explained to all students [participants]. Information was collected on a pre-designed, pre-tested and self-administered questionnaire. The questionnaire was validated by the senior faculties and pre tested on students who were not involved in the study. The study results showed that 80.30% and 93.15% of 1st and 2nd year students have the clear idea of course outline given in course handout or study guide. We also found a statistically significant number of students agreed that they were benefited from the practical session and writing notes in the class hour. A high percentage of students [50% and 62.02%] disagreed that that reading only the handouts is enough for their examination as compared to other students. The study also showed that only 35% and 41% of students visited the library on daily basis for the learning process, around 65% of students were using lecture notes and text books as a tool for learning and to understand the subject and 45% and 53% of students used the library resources (recommended text books) compared to online sources before the examinations. The results presented here show that students perceived that e-learning resources like power point presentations along with text book reading using SQ4R technique had made a positive impact on various aspects of their learning in Biochemistry. The use of library by students has overall positive impact on learning process especially in medical field enhances the outcome, and medical students are better equipped to treat the patient. But it’s also true that use of library use has been in decline which will impact the knowledge aspects and outcome. In conclusion, a student has to be taught how to use the library as learning tool apart from lecture handouts.

Keywords: medical education, learning resources, study guide, biochemistry

Procedia PDF Downloads 173

Authors: Jane Ebele Iloanya

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The introduction of the learning outcome approach in contemporary curriculum design and instruction, has brought student–centered education to the fore. In teacher –centered teaching and learning, the teacher transfers knowledge to the students, who are always at the receiving end. The teacher is assumed to know it all and hardly trusts the knowledge of the students. Teacher-centered education places emphasis on the supremacy of the teacher over the students who should ideally, be able to dialogue with the teacher. The paper seeks to examine the issue of democratisation of the teaching and learning process in Institutions of Higher Learning in Botswana. Botswana is a landlocked country in Southern Africa, with a total population of about two million people. In 1977, Botswana’s First National Policy on Education was unveiled. This came eleven years after the country gained independence from Great Britain. The philosophy which informed the 1977 Education Policy was “Social Harmony”. The philosophy of social harmony has four main principles: Unity, Development, Democracy and Self- Reliance. These principles were meant to permeate all aspects of lives of the people of Botswana, including, the issue of how teaching and learning is conducted in Botswana’s institutions of higher learning. This paper will examine the practicalisation of the principle of democracy in teaching and learning at higher education level in Botswana. It will in particular, discuss the issue of students’ participation and engagement in the teaching and learning process. The following questions will be addressed: 1.Are students involved in planning the curriculum? 2.How engaged are the students in the teaching and learning process? 3.How democratic are the teachers in terms of students’ rights and privileges? A mixed–method approach will be adopted in this study. Questionnaires will be distributed to the students to elicit their views on the practicalisation of the principle of democracy at the higher education level. Semi-structured interview questions will be administered in order to collect information from the lecturers on the issue of democratisation of teaching and learning at the higher education level in Botswana. In addition, relevant and related literature will be reviewed to augment collected data. The study will focus on three tertiary institutions in Gaborone, the capital city of Botswana. Currently, there are ten tertiary institutions in Gaborone; both privately and government owned. The outcome of this study will add to the existing body of knowledge on the issue of the practicalisation of democracy at the higher education level in Botswana. This research is therefore relevant in helping to find out if democratisation of teaching and learning has been realised in Botswana’s Institutions of higher learning. It is important to examine Botswana’s national policy on education in this way to ascertain if it has been effective in giving the country’s education system that democratic element, which is essential for a student-centered approach to the teaching and learning process.

Keywords: democratisation, higher education, learning, teaching

Procedia PDF Downloads 295

Authors: Faiza Belbachir, Thibault Schienhinski

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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.

Keywords: Tripadvisor, opinion detection, SentiWordNet, trust score

Procedia PDF Downloads 188

Authors: Geeta Goyal

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Teaching-learning of English as a second language is a challenge for the learner as well as the teacher. Whereas a student may find it hard and get demotivated while communicating in a language other than mother tongue, a teacher, too, finds it difficult to integrate necessary teaching material in lesson plans to maximize the outcome. Studies reveal that task-based teaching can be useful in diverse contexts in a second language classroom as it helps in creating opportunities for language exposure as per learners' interest and capability levels, which boosts their confidence and learning efficiency. The present study has analysed the impact of various activities carried out in a heterogenous group of second language learners at tertiary level in a semi-urban area in Haryana state of India. Language tasks were specifically planned with a focus on engaging groups of twenty-five students for a period of three weeks. These included language games such as spell-well, cross-naught besides other communicative and interactive tasks like mock-interviews, role plays, sharing experiences, storytelling, simulations, scene-enact, video-clipping, etc. Tools in form of handouts and cue cards were also used as per requirement. This experiment was conducted for ten groups of students taking bachelor’s courses in different streams of humanities, commerce, and sciences. Participants were continuously supervised, monitored, and guided by the respective teacher. Feedback was collected from the students through classroom observations, interviews, and questionnaires. Students' responses revealed that they felt comfortable and got plenty of opportunities to communicate freely without being afraid of making mistakes. It was observed that even slow/timid/shy learners got involved by getting an experience of English language usage in friendly environment. Moreover, it helped the teacher in establishing a trusting relationship with students and encouraged them to do the same with their classmates. The analysis of the data revealed that majority of students demonstrated improvement in their interest and enthusiasm in the class. The study revealed that task-based teaching was an effective method to improve the teaching-learning process under the given conditions.

Keywords: communication skills, English, second language, task-based teaching

Procedia PDF Downloads 78