Search results for: autonomous learning system

Authors: Aisha Noour, Nick Hubbard

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Learner motivation is considered an important premise for the Blended e-Learning (BL) method. BL is an effective learning method in multiple domains, which opens several opportunities for its participants to engage in the learning environment. This research explores the learners’ perspective of BL according to the Self-Determination Theory (SDT). It identifies the opportunities and challenges for using the BL in Logistics Education (LE) in Egyptian Higher Education (HE). SDT is approached from different perspectives within the relationship between Intrinsic Motivation (IM), Extrinsic Motivation (EM) and Amotivation (AM). A self-administered face-to-face questionnaire was used to collect data from learners who were geographically widely spread around three colleges of International Transport and Logistics (CILTs) at the Arab Academy for Science, Technology and Maritime Transport (AAST&MT) in Egypt. Six hundred and sixteen undergraduates responded to a questionnaire survey. Respondents were drawn from three branches in Greater Cairo, Alexandria, and Port Said. The data analysis used was SPSS 22 and AMOS 18.

Keywords: intrinsic motivation, extrinsic motivation, amotivation, blended e-learning, Self Determination Theory

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Authors: Yigal Rosen, Garrett Jaeger, Michelle Newstadt, Ilia Rushkin, Sara Bakken

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All children are capable of advancing their creative thinking skills and engaging in creative play. Creative play puts children in charge of exploring ideas, relationships, spaces and problems. Supported by The LEGO Foundation, the creative thinking formative assessment is designed to provide valid, reliable and informative measurement to support the development of creative skills while children are engaged in Learning through Play. In this paper we provide an overview of the assessment framework underpinned the assessment of creative thinking and report the results from the 2022 pilot study demonstrating promising evidence on the ability to measure creative skills in a conceptually and ecologically valid way to inform the development of creative skills.

Keywords: creativity, creative thinking, assessment, learning through play, creative play, learning progressions

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Authors: Jolanta Jonak

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All students demonstrate various learning preferences and learning styles that range from visual, auditory to kinesthetic preferences. These learning preferences are further impacted by individual cognitive profiles hat characterizes itself in linguistic strengths, logical- special, inter-or intra- personal, just to name a few. Students from culturally and linguistically diverse backgrounds (CLD) have an increased risk of being misunderstood by many school systems and even medical personnel. Students with disability, specifically Autism, are faced with another layer of learning differences. Research indicates that large numbers of students are not provided the type of education and types of supports they need in order to be successful in an academic environment. Multiple research findings indicate that significant numbers of school staff self-reports that they do not feel adequately prepared to work with students with disability and different learing profiles. It is very important for the school staff to be educated about different learning needs of students with autism spectrum disorders. Having the knowledge, school staff can avoid unnecessary referrals for office referrals and avoid inaccurate decisions about restrictive learning environments. This presentation will illustrate the cognitive differences in students with autism, how to recognize them, and how to support them through Differentiated Instruction. One way to ensure successful education for students with disability is by providing Differentiated Instruction (DI). DI is quickly gaining its popularity in the Unites States as a scientific- research based instructional approach for all students. This form of support ensures that regardless of the students’ learning preferences and cognitive learning profiles, they have an opportunity to learn through approaches that are suitable to their needs. It is extremely important for the school staff, especially school psychologists who often are the first experts to be consulted by educators, to be educated about differences due to learning preference styles and differentiation needs.

Keywords: special education, autism, differentiation, differences, differentiated instruction

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Authors: Routsukol Sunalai

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This research was to study the relationship between the organizational culture like bureaucratic system, and patronage system in government hospitals with hospital accreditation and its impact on the quality of service in the government hospital accredited. Qualitative research was applied in this study by in-depth interviews with samples containing 20 public welfare service providers, i.e. doctors, nurses and practical nurses and 20 service recipients in the units of study. It was found that the bureaucracy still existed and was evidenced by the structure of the line of command; work systems, clear cut duty divisions, procedures and plans, and the patronage system hindered the quality of service in the government hospitals under the process of development and accreditation. The administrators should encourage and support the creation of a learning process in the organization for self-improvement and work development.

Keywords: hospital in Dusit Area, organization culture, the quality of service, economics and financial engineering

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Authors: Jurijs Salijevs, Katrina Bolocko

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The integration of artificial intelligence and neural networks has significantly changed full-body imaging and high-resolution 3D mapping systems, and this paper reviews research in these areas. With an emphasis on their use in the early identification of melanoma and other disorders, the goal is to give a wide perspective on the current status and potential future of these medical imaging technologies. Authors also examine methodologies such as machine learning and deep learning, seeking to identify efficient procedures that enhance diagnostic capabilities through the analysis of 3D body scans. This work aims to encourage further research and technological development to harness the full potential of AI in disease diagnosis.

Keywords: artificial intelligence, neural networks, 3D scan, body scan, 3D mapping system, healthcare

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Authors: Eunice Gan Ghee Wu, Marcus Goh Tian Xi, Alicia Chua Si Wen, Helen Bound, Lee Liang Ying, Albert Lee

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The Map of Dialogical Inquiry provides a conceptual basis of learning processes. According to the Map, dialogical inquiry motivates complex thinking, dialogue, reflection, and learner agency. For instance, classrooms that incorporated dialogical inquiry enabled learners to construct more meaning in their learning, to engage in self-reflection, and to challenge their ideas with different perspectives. While the Map contributes to the psychology of learning, its qualitative approach makes it hard to track and compare learning processes over time for both teachers and learners. Qualitative approach typically relies on open-ended responses, which can be time-consuming and resource-intensive. With these concerns, the present research aimed to develop and validate a quantifiable measure for the Map. Specifically, the Map of Dialogical Inquiry reflects the eight different learning processes and perspectives employed during a learner’s experience. With a focus on interpersonal and emotional learning processes, the purpose of the present study is to construct and validate a scale to measure the “Relating” aspect of learning. According to the Map, the Relating aspect of learning contains four conceptual components: using intuition and empathy, seeking personal meaning, building relationships and meaning with others, and likes stories and metaphors. All components have been shown to benefit learning in past research. This research began with a literature review with the goal of identifying relevant scales in the literature. These scales were used as a basis for item development, guided by the four conceptual dimensions in the “Relating” aspect of learning, resulting in a pool of 47 preliminary items. Then, all items were administered to 200 American participants via an online survey along with other scales of learning. Dimensionality, reliability, and validity of the “Relating” scale was assessed. Data were submitted to a confirmatory factor analysis (CFA), revealing four distinct components and items. Items with lower factor loadings were removed in an iterative manner, resulting in 34 items in the final scale. CFA also revealed that the “Relating” scale was a four-factor model, following its four distinct components as described in the Map of Dialogical Inquiry. In sum, this research was able to develop a quantitative scale for the “Relating” aspect of the Map of Dialogical Inquiry. By representing learning as numbers, users, such as educators and learners, can better track, evaluate, and compare learning processes over time in an efficient manner. More broadly, this scale may also be used as a learning tool in lifelong learning.

Keywords: lifelong learning, scale development, dialogical inquiry, relating, social and emotional learning, socio-affective intuition, empathy, narrative identity, perspective taking, self-disclosure

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Authors: Salahaeddine Sbai

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Air quality analysis using machine learning models is a method employed to assess and predict air pollution levels. This approach leverages the capabilities of machine learning algorithms to analyze vast amounts of air quality data and extract valuable insights. By training these models on historical air quality data, they can learn patterns and relationships between various factors such as weather conditions, pollutant emissions, and geographical features. The trained models can then be used to predict air quality levels in real-time or forecast future pollution levels. This application of machine learning in air quality analysis enables policymakers, environmental agencies, and the general public to make informed decisions regarding health, environmental impact, and mitigation strategies. By understanding the factors influencing air quality, interventions can be implemented to reduce pollution levels, mitigate health risks, and enhance overall air quality management. Climate change is having significant impacts on Morocco, affecting various aspects of the country's environment, economy, and society. In this study, we use some machine learning models under python environment to predict and analysis air quality change over North of Morocco to evaluate the climate change impact on agriculture.

Keywords: air quality, machine learning models, pollution, pollutant emissions

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Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

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Authors: Thapanee Seechaliao

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This research paper presents guiding on how to design social media into higher education courses. The research methodology used a survey approach. The research instrument was a questionnaire about guiding on how to design social media into higher education courses. Thirty-one lecturers completed the questionnaire. The data were scored by frequency and percentage. The research results were the lecturers’ opinions concerning the designing social media into higher education courses as follows: 1) Lecturers deem that the most suitable learning theory is Collaborative Learning. 2) Lecturers consider that the most important learning and innovation Skill in the 21st century is communication and collaboration skills. 3) Lecturers think that the most suitable evaluation technique is authentic assessment. 4) Lecturers consider that the most appropriate portion used as blended learning should be 70% in the classroom setting and 30% online.

Keywords: instructional design, social media, courses, higher education

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Authors: D. A. Carnegie

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Whilst there is a movement towards increased digital augmentation in order to facilitate effective tertiary learning, this must come with an awareness of the limitations of such an approach. Learning is best achieved in an environment that includes their learning peers where difficulties can be shared and learning enabled. Policy that advocates for digital technology in place of a physical classroom is dangerous and is often driven by financial concerns rather than pedagogical ones. In this paper, a mostly digital-less form of teaching is presented – one that has proven to be extremely effective. Implicit is anecdotal evidence that student prefer the old overhead transparencies to PowerPoint presentations. Varying and reinforcing assessment, facilitation of effective note-taking, and just actively engaging with students is at the core of a good tertiary education experience. Digital techniques can augment and complement, but not replace these core personal teaching requirements.

Keywords: engineering education, active classroom engagement, effective note taking, reinforcing assessment

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Authors: Jihen Bennaceur, Wissem Zouaghi, Ali Mabrouk

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The major aim of cyber threat intelligence (CTI) is to provide sophisticated knowledge about cybersecurity threats to ensure internal and external safeguards against modern cyberattacks. Inaccurate, incomplete, outdated, and invaluable threat intelligence is the main problem. Therefore, data analysis based on AI algorithms is one of the emergent solutions to overcome the threat of information-sharing issues. In this paper, we propose a supervised machine learning-based algorithm to improve threat information sharing by providing a sophisticated classification of cyber threats and data. Extensive simulations investigate the accuracy, precision, recall, f1-score, and support overall to validate the designed algorithm and to compare it with several supervised machine learning algorithms.

Keywords: threat information sharing, supervised learning, data classification, performance evaluation

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Authors: Deawan Rakin Ahamed Remal, Sinthia Chowdhury, Sharun Akter Khushbu, Sheak Rashed Haider Noori

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Native Speech to text synthesis has its own leverage for the purpose of mankind. The extensive nature of art to speaking different accents is common but the purpose of communication between two different accent types of people is quite difficult. This problem will be motivated by the extraction of the wrong perception of language meaning. Thus, many existing automatic speech recognition has been placed to detect text. Overall study of this paper mentions a review of NSTTR (Native Speech Text to Text Recognition) synthesis compared with Text to Text recognition. Review has exposed many text to text recognition systems that are at a very early stage to comply with the system by native speech recognition. Many discussions started about the progression of chatbots, linguistic theory another is rule based approach. In the Recent years Deep learning is an overwhelming chapter for text to text learning to detect language nature. To the best of our knowledge, In the sub continent a huge number of people speak in Bangla language but they have different accents in different regions therefore study has been elaborate contradictory discussion achievement of existing works and findings of future needs in Bangla language acoustic accent.

Keywords: TTR, NSTTR, text to text recognition, deep learning, natural language processing

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Authors: Tayaa Karima, Bouaziz Amina

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Today's world is knowledge-based; everything we do is somehow connected with technology which it has a remarkable influence on socio-cultural and economic developments, including educational settings. This type of technology is supported in many teaching/learning setting where the medium of instruction is through computer technology, and particularly involving digital technologies. There has been much debate over the use of computers and the internet in foreign language teaching for more than two decades. Various studies highlights that the integration of Information Communications Technology (ICT) in foreign language teaching will have positive effects on both the teachers and students to help them be aware of the modernized world and meet the current demands of the globalised world. Information and communication technology has been gradually integrated in foreign learning environment as a platform for providing learners with learning opportunities. Thus, the impact of ICT on language teaching and learning has been acknowledged globally, this is because of the fundamental role that it plays in the enhancement of teaching and learning quality, modify the pedagogical practice, and motivate learners. Due to ICT related developments, many Maghreb countries regard ICT as a tool for changes and innovations in education. Therefore, the ministry of education attempted to set up computer laboratories and provide internet connection in the schools. Investment in ICT for educational innovations and improvement purposes has been continuing the need of teacher who will employ it in the classroom as vital role of the curriculum. ICT does not have an educational value in itself, but it becomes precious when teachers use it in learning and teaching process. This paper examines the impacts of ICT on teacher development rather than on teaching quality and highlights some challenges facing using ICT in the language learning/teaching.

Keywords: information communications technology (ICT), integration, foreign language teaching, teacher development, learning opportunity

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Authors: R Palson Kennedy, P.Kiran Sai

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This article introduces machine learning (ML) researchers to the hurdles that geoscience problems present, as well as the opportunities for improvement in both ML and geosciences. This article presents a review from the data life cycle perspective to meet that need. Numerous facets of geosciences present unique difficulties for the study of intelligent systems. Geosciences data is notoriously difficult to analyze since it is frequently unpredictable, intermittent, sparse, multi-resolution, and multi-scale. The first half addresses data science’s essential concepts and theoretical underpinnings, while the second section contains key themes and sharing experiences from current publications focused on each stage of the data life cycle. Finally, themes such as open science, smart data, and team science are considered.

Keywords: Data science, intelligent system, machine learning, big data, data life cycle, recent development, geo science

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Authors: Catherine Thompson, Maryam Jalali, Peter Hills

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The allocation of visual attention is critical when driving and anything that limits attention will have a detrimental impact on safety. Engaging in a secondary task reduces the amount of attention directed to the road because drivers allocate resources towards this task, leaving fewer resources to process driving-relevant information. Yet the dangers associated with a secondary task do not end when the driver returns their attention to the road. Instead, the attentional settings adopted to complete a secondary task may persist to the road, affecting attention, and therefore affecting driver performance. This 'attentional inertia' effect was investigated in the current work. Forty drivers searched for hazards in driving video clips while their eye-movements were recorded. At varying intervals they were instructed to attend to a secondary task displayed on a tablet situated to their left-hand side. The secondary task consisted of three separate computer games that induced horizontal, vertical, and random eye movements. Visual search and hazard detection in the driving clips were compared across the three conditions of the secondary task. Results showed that the layout of information in the secondary task, and therefore the allocation of attention in this task, had an impact on subsequent search in the driving clips. Vertically presented information reduced the wide horizontal spread of search usually associated with accurate driving and had a negative influence on the detection of hazards. The findings show the additional dangers of engaging in a secondary task while driving. The attentional inertia effect has significant implications for semi-autonomous and autonomous vehicles in which drivers have greater opportunity to direct their attention away from the driving task.

Keywords: attention, eye-movements, hazard perception, visual search

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Authors: Erva Akin

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– The use of copyrighted material for machine learning purposes is a challenging issue in the field of artificial intelligence (AI). While machine learning algorithms require large amounts of data to train and improve their accuracy and creativity, the use of copyrighted material without permission from the authors may infringe on their intellectual property rights. In order to overcome copyright legal hurdle against the data sharing, access and re-use of data, the use of copyrighted material for machine learning purposes may be considered permissible under certain circumstances. For example, if the copyright holder has given permission to use the data through a licensing agreement, then the use for machine learning purposes may be lawful. It is also argued that copying for non-expressive purposes that do not involve conveying expressive elements to the public, such as automated data extraction, should not be seen as infringing. The focus of such ‘copy-reliant technologies’ is on understanding language rules, styles, and syntax and no creative ideas are being used. However, the non-expressive use defense is within the framework of the fair use doctrine, which allows the use of copyrighted material for research or educational purposes. The questions arise because the fair use doctrine is not available in EU law, instead, the InfoSoc Directive provides for a rigid system of exclusive rights with a list of exceptions and limitations. One could only argue that non-expressive uses of copyrighted material for machine learning purposes do not constitute a ‘reproduction’ in the first place. Nevertheless, the use of machine learning with copyrighted material is difficult because EU copyright law applies to the mere use of the works. Two solutions can be proposed to address the problem of copyright clearance for AI training data. The first is to introduce a broad exception for text and data mining, either mandatorily or for commercial and scientific purposes, or to permit the reproduction of works for non-expressive purposes. The second is that copyright laws should permit the reproduction of works for non-expressive purposes, which opens the door to discussions regarding the transposition of the fair use principle from the US into EU law. Both solutions aim to provide more space for AI developers to operate and encourage greater freedom, which could lead to more rapid innovation in the field. The Data Governance Act presents a significant opportunity to advance these debates. Finally, issues concerning the balance of general public interests and legitimate private interests in machine learning training data must be addressed. In my opinion, it is crucial that robot-creation output should fall into the public domain. Machines depend on human creativity, innovation, and expression. To encourage technological advancement and innovation, freedom of expression and business operation must be prioritised.

Keywords: artificial intelligence, copyright, data governance, machine learning

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Authors: Sharapat Sharapat

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English language is perceived as cultural capital in many non-native English-speaking countries, and minority groups in these social contexts seem to invest in the language to be empowered and reposition themselves from the imbalanced power relation with the dominant group. This study is devoted to explore how English learning influence minority Kazakh students’ identity (re)construction at Chinese universities from the scope of ‘imagined community, investment, and identity’ theory of Norton (2013). To this end the three research questions were designed as follows: 1) Kazakh minority students’ English learning experiences at Chinese universities; 2) Kazakh minority students’ views about benefits and opportunities of English learning; 3) the influence of English learning on Kazakh minority students’ identity (re)construction. The study employs an interview-based qualitative research method by interviewing nine Kazakh minority students in universities in Xinjiang and other inland cities in China. The findings suggest that through English learning, some students have reconstructed multiple identities as multicultural and global identities, which created ‘a third space’ to break limits of their ethnic and national identities and confused identity as someone in-between. Meanwhile, most minority students were empowered by the English language to resist inferior or marginalized positions and reconstruct imagined elite identity. However, English learning disempowered students who have little previous English education in school and placed them on unequal footing with other students, which further escalated the educational inequities.

Keywords: minority in China, identity construction, multilingual education, language empowerment

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Authors: Gloria Chen

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When offering conventional level-appropriate ESL classes for adults is not feasible, a multilevel adult ESL class can be formed to benefit those who need to learn English for daily function. This paper examines the rationale, the process, the contents, and the outcomes of a multilevel ESL class for adults. The action research discusses a variety of assessments, lesson plans, teaching strategies that facilitate lifelong language learning. In small towns where adult ESL learners are only a handful, often advanced students and inexperienced students have to be placed in one class. Such class might not be viewed as desirable, but with on-going assessments, careful lesson plans, and purposeful strategies, a multilevel ESL class for adults can overcome the obstacles and help learners to reach a higher level of English proficiency. This research explores some hand-on strategies, such as group rotating, cooperative learning, and modifying textbook contents for practical purpose, and evaluate their effectiveness. The data collected in this research include Needs Assessment (beginning of class term), Mid-term Self-Assessment (5 months into class term), End-of-term Student Reflection (10 months into class), and End-of-term Assessment from the Instructor (10 months into class). A descriptive analysis of the data explains the practice of this particular learning community, and reveal the areas for improvement and enrichment. This research answers the following questions: (1) How do the assessments positively help both learners and instructors? (2) How do the learning strategies prepare students to become independent, life-long English learners? (3) How do materials, grouping, and class schedule enhance the learning? The result of the research contributes to the field of teaching and learning in language, not limited in English, by (a) examining strategies of conducting a multilevel adult class, (b) involving adult language learners with various backgrounds and learning styles for reflection and feedback, and (c) improving teaching and learning strategies upon research methods and results. One unique feature of this research is how students can work together with the instructor to form a learning community, seeking and exploring resources available to them, to become lifelong language learners.

Keywords: adult language learning, assessment, multilevel, teaching strategies

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Authors: Farhad Ghasemi

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Along with transforming the international system into a complex and chaotic system, the fundamental question arises: how can deterrence be reconstructed conceptually and theoretically in this system model? The deterrence system is much more complex today than it was seven decades ago. This article suggests that the perception of deterrence as a linear system is a fundamental mistake because it does not consider the new dynamics of the international system, including network power dynamics. The author aims to improve this point by focusing on complexity and chaos theories, especially their nonlinearity and cascading failure principles. This article proposes that the perception of deterrence as a linear system is a fundamental mistake, as the new dynamics of the surrounding international system do not take into account. The author recognizes deterrence as a nonlinear system and introduces it as a concept in strategic studies.

Keywords: complexity, international system, deterrence, linear deterrence, nonlinear deterrence

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Authors: Jérôme de Reffye, Marc Antoni

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Following the development of the ERTMS system, we think it is interesting to develop another software-based track circuit system which would fit secondary railway lines with an easy-to-work implementation and a low sensitivity to rail-wheel impedance variations. We called this track circuit 'Track Railway by Automatic Circuits.' To be internationally implemented, this system must not have any mechanical component and must be compatible with existing track circuit systems. For example, the system is independent from the French 'Joints Isolants Collés' that isolate track sections from one another, and it is equally independent from component used in Germany called 'Counting Axles,' in French 'compteur d’essieux.' This track circuit is fully interoperable. Such universality is obtained by replacing the train detection mechanical system with a space-time filtering of train position. The various track sections are defined by the frequency of a continuous signal. The set of frequencies related to the track sections is a set of orthogonal functions in a Hilbert Space. Thus the failure probability of track sections separation is precisely calculated on the basis of signal-to-noise ratio. SNR is a function of the level of traction current conducted by rails. This is the reason why we developed a very powerful algorithm to reject noise and jamming to obtain an SNR compatible with the precision required for the track circuit and SIL 4 level. The SIL 4 level is thus reachable by an adjustment of the set of orthogonal functions. Our major contributions to railway engineering signalling science are i) Train space localization is precisely defined by a calibration system. The operation bypasses the GSM-R radio system of the ERTMS system. Moreover, the track circuit is naturally protected against radio-type jammers. After the calibration operation, the track circuit is autonomous. ii) A mathematical topology adapted to train space localization by following the train through a linear time filtering of the received signal. Track sections are numerically defined and can be modified with a software update. The system was numerically simulated, and results were beyond our expectations. We achieved a precision of one meter. Rail-ground and rail-wheel impedance sensitivity analysis gave excellent results. Results are now complete and ready to be published. This work was initialised as a research project of the French Railways developed by the Pi-Ramses Company under SNCF contract and required five years to obtain the results. This track circuit is already at Level 3 of the ERTMS system, and it will be much cheaper to implement and to work. The traffic regulation is based on variable length track sections. As the traffic growths, the maximum speed is reduced, and the track section lengths are decreasing. It is possible if the elementary track section is correctly defined for the minimum speed and if every track section is able to emit with variable frequencies.

Keywords: track section, track circuits, space-time crossing, adaptive track section, automatic railway signalling

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Authors: Grace D. Severo, Lopita U. Jung

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This study aimed to determine the educational philosophies and teaching styles of the college faculty of the University of Perpetual Help System DALTA in the campuses of Las-Piñas, Molino, and Calamba, south of Metro Manila. It sought to determine the relationships of educational philosophy and teaching styles of the college faculty vis-à-vis the university system’s educational philosophies and teaching style preferences. A hundred and five faculty members from the Colleges of Education, Arts and Sciences responded to the survey during the academic year 2014-2015. The Philosophy of Adult Education Inventory measured the faculty’s preferred educational philosophies. The Principles of Adult Learning Scale measured the faculty’s teaching style preference. Findings show that there is a similarity between the university system and the faculty members in using the progressive educational philosophy, however both contrasted in the preferred teaching style. Majority of the faculty held progressive educational philosophy but their preference for teacher-centered teaching style did not match. This implies that the majority are certain of having progressive educational philosophy but are not utilizing the learner-centered teaching styles; a high degree of support and commitment to practice a progressive and humanist philosophical orientation in education; and a high degree of support on teacher-centered teaching style promotion from the institution can strengthen a high degree of commitment for the faculty to enunciate their values and practice through these educational philosophies and teaching styles.

Keywords: educational philosophies, teaching styles, philosophy of adult education inventory, principles of adult learning scale

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Authors: Elvira Wahyuni

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This study is a classroom action research. The general objective of this study was to find out students’ speaking ability through teaching English by using video and to find out the effectiveness of using video in teaching English to improve students’ speaking ability. The subjects of this study were 34 of the first-year students of SMAN 12 Pekanbaru who were learning English as a foreign language (EFL). Students were given pre-test before the treatment and post-test after the treatment. Quantitative data was collected by using speaking test requiring the students to respond to the recorded questions. Qualitative data was collected through observation sheets and field notes. The research finding reveals that there is a significant improvement of the students’ speaking ability through the use of video in speaking class. The qualitative data gave a description and additional information about the learning process done by the students. The research findings indicate that the use of video in teaching and learning is good in increasing learning outcome.

Keywords: English teaching, fun learning, speaking ability, video

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Yong Wook Kim

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The diversity of students in regular classrooms is increasing due to expand inclusive education and increase multicultural students in South Korea. In this diverse classroom environment, the universal design for learning (UDL) has been proposed as a way to meet both the educational need and social expectation of student achievement. UDL offers a variety of practical teaching methods, one of which is a differentiating instruction. The differentiating instruction has been pointed out resource limitation, organizational resistance, and lacks easy-to-implement framework. However, through the framework provided by the UDL, differentiating instruction is able to be flexible in their implementation. In practice, the UDL and differentiating instruction are complementary, but there is still a lack of research that suggests specific implementation methods that apply both concepts at the same time. This study was conducted to investigate the effects of differentiating instruction strategies according to learner characteristics (readiness, interest, learning profile), components of differentiating instruction (content, process, performance, learning environment), especially UDL principles (representation, behavior and expression, participation) existed in differentiating instruction, and implementation of UDL-based differentiating instruction through the Planning for All Learner (PAL) and UDL Lesson Plan Cycle. It is meaningful that such a series of studies can enhance the possibility of more concrete and realistic UDL-based teaching and learning strategies in the classroom, especially in inclusive settings.

Keywords: universal design for learning, differentiating instruction, UDL lesson plan, PAL

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Authors: Laura Zizka, Gaby Probst

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The Covid-19 pandemic has affected the way Higher Education Institutions (HEIs) have given their courses. From emergency remote where all students and faculty were immediately confined to home teaching and learning, the continuing evolving sanitary situation obliged HEIs to adopt other methods of teaching and learning from blended courses that included both synchronous and asynchronous courses and activities to hy-flex models where some students were on campus while others followed the course simultaneously online. Each semester brought new challenges for HEIs and, subsequently, additional emotional reactions. This paper investigates the affective side of teaching and learning in various online modalities and its toll on students and faculty members over the past three semesters. The findings confirm that students and faculty who have more self-efficacy, flexibility, and resilience reported positive emotions and embraced the opportunities that these past semesters have offered. While HEIs have begun a new semester in an attempt to return to ‘normal’ face-to-face courses, this paper posits that there are lessons to be learned from these past three semesters. The opportunities that arose from the challenge of the pandemic should be considered when moving forward by focusing on a greater emphasis on the affective aspect of teaching and learning in HEIs worldwide.

Keywords: effective teaching and learning, higher education, engagement, interaction, motivation

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Authors: Shoeb A. Adeel, Shashant Anand, Vivek Paul, Dinesh, Suraj, Roshan

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The paper presents a study of micro air vehicles (MAVs) with wingspans of 20 Cm with two different airfoil configurations. MAVs have vast potential applications in both military and civilian areas. These MAVs are fully autonomous and supply real-time data. The paper focuses on two different designs of the MAVs one being N22 airfoil and the other a flat plate with similar dimension. As designed, the MAV would fly in a low Reynolds-number regime at airspeeds of 15 & 20 m/sec. Propulsion would be provided by an electric motor with an advanced lithium. Because of the close coupling between vehicle elements, system integration would be a significant challenge, requiring tight packaging and multifunction components to meet mass limitations and Centre of Gravity (C.G) balancing. These MAVs are feasible and within a couple of years of technology development in key areas including sensors, propulsion, Aerodynamics, and packaging these would be easily available to the users at affordable prices. The paper finally compares the flight performance of the two configurations.

Keywords: airfoil, CFD, MAV, flight performance, endurance, climb, lift, drag

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Authors: Wen-Chao Tang, Tang-Yi Liu, Ming Gao, Gang Xu, Hua-Yuan Yang

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This study developed a method for teaching acupuncture manipulation in small groups optimized with the theory of motor learning. Sixty acupuncture students and their teacher participated in our research. Motion videos were recorded of their manipulations using the lifting-thrusting method. These videos were analyzed using Simi Motion software to acquire the movement parameters of the thumb tip. The parameter velocity curves along Y axis was used to generate small teaching groups clustered by a self-organized map (SOM) and K-means. Ten groups were generated. All the targeted instruction based on the comparative results groups as well as the videos of teacher and student was provided to the members of each group respectively. According to the theory and research of motor learning, the factors or technologies such as video instruction, observational learning, external focus and summary feedback were integrated into this teaching method. Such efforts were desired to improve and enhance the effectiveness of current acupuncture teaching methods in limited classroom teaching time and extracurricular training.

Keywords: acupuncture, group teaching, video instruction, observational learning, external focus, summary feedback

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Authors: Jenjira Chinnawong, Phusit Phukamchanoad

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The objective of this study is to explore the guidelines for the development of community classroom for research and academic services in Ranong province. By interviewing leaders involved in the development of learning resources, research, and community services, it was found that the leaders' perceptions in the development of learning resources, research, and community services in Ranong, was at the highest level. They perceived at every step on policies of community classroom implementation, research, and community services in Ranong. Leaders' perceptions were at the moderate level in terms of analysis of problems related to procedures of community classroom management, research and community services in Ranong especially in the planning and implementation of the examination, improvement, and development of learning sources to be in good condition and ready to serve the visitors. Their participation in the development of community classroom, research, and community services in Ranong was at a high level, particularly in the participation in monitoring and evaluation of the development of learning resources as well as in reporting on the result of the development of learning resources. The most important thing in the development of community classroom, research and community services in Ranong is the necessity to integrate the three principles of knowledge building in teaching, research and academic services in order to create the identity of the local and community classroom for those who are interested to visit to learn more about the useful knowledge. As a result, community classroom, research, and community services were well-known both inside and outside the university.

Keywords: community classroom, learning resources, development, participation

Procedia PDF Downloads 136

Authors: Michael McMahon

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The use of media (video/animation/graphics) has long been used by athletes, coaches, and sports scientists to analyse and improve performance in technical skills and team tactics. Sports educators are increasingly open to the use of technology to support coach and learner development. However, an overreliance is a concern., This paper is part of a larger Ph.D. study looking into these new challenges for Sports Educators. Most notably, how to exploit the deep-learning potential of Digital Media among expert learners, how to instruct sports educators to create effective media content that fosters deep learning, and finally, how to make the process manageable and cost-effective. Central to the study is Richard Mayers Cognitive Theory of Multimedia Learning. Mayers Multimedia Learning Theory proposes twelve principles that shape the design and organization of multimedia presentations to improve learning and reduce cognitive load. For example, the Prior Knowledge principle suggests and highlights different learning outcomes for Novice and Non-Novice learners, respectively. Little research, however, is available to support this principle in modified domains (e.g., sports tactics and strategy). As a foundation for further research, this paper compares and contrasts a range of contemporary multimedia sports coaching content and assesses how they perform as learning tools for Strategic and Tactical Play Acquisition among elite sports practitioners. The stress tests applied are guided by Mayers's twelve Multimedia Learning Principles. The focus is on the elite athletes and whether current coaching digital media content does foster improved sports learning among this cohort. The sport of Gaelic Football was selected as it has high strategic and tactical play content, a wide range of Practitioner skill levels (Novice to Elite), and also a significant volume of Multimedia Coaching Content available for analysis. It is hoped the resulting data will help identify and inform the future instructional content design and delivery for Sports Practitioners and help promote best design practices optimal for different levels of expertise.

Keywords: multimedia learning, e-learning, design for learning, ICT

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Authors: Ruthanne Tobin

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The shift to a personalized learning (PL) curriculum in Canada represents an innovative approach to teaching and learning that is also evident in various initiatives across the 32-nation OECD. The premise behind PL is that empowering individual learners to have more input into how they access and construct knowledge, and express their understanding of it, will result in more meaningful school experiences and academic success. In this paper presentation, the author reports on a document analysis of the new curriculum in the province of British Columbia. Three theoretical frameworks are used to analyze the new curriculum. Framework 1 focuses on five dominant aspects (FDA) of PL at the classroom level. Framework 2 focuses on conceptualizing and enacting personalized learning (CEPL) within three spheres of influence. Framework 3 focuses on the integration of three types of knowledge (content, technological, and pedagogical). Analysis is ongoing, but preliminary findings suggest that the new curriculum addresses framework 1 quite well, which identifies five areas of personalized learning: 1) assessment for learning; 2) effective teaching and learning; 3) curriculum entitlement (choice); 4) school organization; and 5) “beyond the classroom walls” (learning in the community). Framework 2 appears to be less well developed in the new curriculum. This framework speaks to the dynamics of PL within three spheres of interaction: 1) nested agency, comprised of overarching constraints [and enablers] from policy makers, school administrators and community; 2) relational agency, which refers to a capacity for professionals to develop a network of expertise to serve shared goals; and 3) students’ personalized learning experience, which integrates differentiation with self-regulation strategies. Framework 3 appears to be well executed in the new PL curriculum, as it employs the theoretical model of technological, pedagogical content knowledge (TPACK) in which there are three interdependent bodies of knowledge. Notable within this framework is the emphasis on the pairing of technologies with excellent pedagogies to significantly assist students and teachers. This work will be of high relevance to educators interested in innovative school reform.

Keywords: curriculum reform, K-12 school change, innovations in education, personalized learning

Procedia PDF Downloads 257