Search results for: hybrid learning

Authors: A. Kesraoui, M. Seffen

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Applications of adsorption onto activated carbon for water treatment are well known. The process has been demonstrated to be widely effective for removing dissolved organic substances from wastewaters, but this treatment has a major drawback is the high operating cost. The main goal of our research work is to improve the retention capacity of Tunisian biomass for the depollution of industrial wastewater and retention of pollutants considered toxic. The biosorption process is based on the retention of molecules and ions onto a solid surface composed of biological materials. The evaluation of the potential use of these materials is important to propose as an alternative to the adsorption process generally expensive, used to remove organic compounds. Indeed, these materials are very abundant in nature and are low cost. Certainly, the biosorption process is effective to remove the pollutants, but it presents a slow kinetics. The improvement of the biosorption rates is a challenge to make this process competitive with respect to oxidation and adsorption onto lignocellulosic fibers. In this context, the alternating current appears as a new alternative, original and a very interesting phenomenon in the acceleration of chemical reactions. Our main goal is to increase the retention acceleration of dyes (indigo carmine, methylene blue) and phenol by using a new alternative: alternating current. The adsorption experiments have been performed in a batch reactor by adding some of the adsorbents in 150 mL of pollutants solution with the desired concentration and pH. The electrical part of the mounting comprises a current source which delivers an alternating current voltage of 2 to 15 V. It is connected to a voltmeter that allows us to read the voltage. In a 150 mL capacity cell, we plunged two zinc electrodes and the distance between two Zinc electrodes has been 4 cm. Thanks to alternating current, we have succeeded to improve the performance of activated carbon by increasing the speed of the indigo carmine adsorption process and reducing the treatment time. On the other hand, we have studied the influence of the alternating current on the biosorption rate of methylene blue onto Luffa cylindrica fibers and the hybrid material (Luffa cylindrica-ZnO). The results showed that the alternating current accelerated the biosorption rate of methylene blue onto the Luffa cylindrica and the Luffa cylindrica-ZnO hybrid material and increased the adsorbed amount of methylene blue on both adsorbents. In order to improve the removal of phenol, we performed the coupling between the alternating current and the biosorption onto two adsorbents: Luffa cylindrica and the hybrid material (Luffa cylindrica-ZnO). In fact, the alternating current has succeeded to improve the performance of adsorbents by increasing the speed of the adsorption process and the adsorption capacity and reduce the processing time.

Keywords: adsorption, alternating current, dyes, modeling

Procedia PDF Downloads 130

Authors: Yeimis Milton, Palomino Pichihua

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The city, like living organisms, originates from codes, structured information in the form of rules that condition the physical form and performance of urban space. Usually, the so-called urban codes clash with the spontaneous nature of the city, with the urban Kháos that contextualizes the free creation (poiesis) of human collectives. This contradiction is especially evident in Latin America, which, like other developing regions, lacks adequate instruments to guide urban growth. Thus constructing a hybrid between the formal and informal city, categories that are difficult to separate one from the other. This is a comparative study focusing on the urban codes created to address the pandemic. The objective is to build an overview of these innovations in the region. The sample is made up of official norms published in pandemic, directly linked to urban planning and building control (urban form). The countries analyzed are Brazil, Mexico, Argentina, Peru, Colombia, and Chile. The study uncovers a shared interest in facing future urban problems, in contrast to the inconsistency of proposed legal instruments. Factors such as the lack of articulation, validity time, and ambiguity, among others, accentuate this problem. Likewise, it evidences that the political situation of each country has a significant influence on the development of these norms and the possibility of their long-term impact. In summary, the global emergency has produced opportunities to transform urban systems from their internal rules; however, there are very few successful examples in this field. Therefore, Latin American cities have the task of learning from this defeat in order to lay the foundations for a more resilient and sustainable urban future.

Keywords: pandemic, regulation, urban planning, latin America

Procedia PDF Downloads 79

Authors: Elisabeth Desiana Mayasari, Laurensia Aptik Evanjeli, Brigitta Erlita Tri Anggadewi

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The condition of the COVID-19 pandemic demands adaptation in various aspects of human life, including in the field of education. Teachers are expected to do distance learning or Learning From Home (LFH). The teacher said that he experienced stress, anxiety, feeling depressed, and afraid based on the interview. Learning adaptations and pandemic situations can impact the mental health of teachers, so the purpose of this study is to determine the mental health of teachers while teaching online. This research was conducted with a quantitative approach using a survey method. The subjects in this study were 330 elementary school teachers under the auspices of a foundation in Yogyakarta. Teachers' mental health was measured using the Indonesian version of The Mental Health Inventory (MHI-38), which has a reliability of 0.888. The results showed that the teachers generally had a good mental health condition marked by a lower negative aspect score than the positive aspect. In addition, the overall mental health aspect shows that some teachers have better mental health when compared to the average score, as well as higher positive aspect scores in all sub-aspects.

Keywords: mental health, teacher, COVID-19 pandemic, MHI-38

Procedia PDF Downloads 154

Authors: Heichia Wang, Yalan Chao

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Social inequality is a persistent problem. One of the ways to solve this problem is through education. At present, vulnerable groups are often less geographically accessible to educational resources. However, compared with educational resources, communication equipment is easier for vulnerable groups. Now that information and communication technology (ICT) has entered the field of education, today we can accept the convenience that ICT provides in education, and the mobility that it brings makes learning independent of time and place. With mobile learning, teachers and students can start discussions in an online chat room without the limitations of time or place. However, because liquidity learning is quite convenient, people tend to solve problems in short online texts with lack of detailed information in a lack of convenient online environment to express ideas. Therefore, the ICT education environment may cause misunderstanding between teachers and students. Therefore, in order to better understand each other's views between teachers and students, this study aims to clarify the essays of the analysts and classify the students into several types of learning questions to clarify the views of teachers and students. In addition, this study attempts to extend the description of possible omissions in short texts by using external resources prior to classification. In short, by applying a short text classification, this study can point out each student's learning problems and inform the instructor where the main focus of the future course is, thus improving the ICT education environment. In order to achieve the goals, this research uses convolutional neural network (CNN) method to analyze short discussion content between teachers and students in an ICT education environment. Divide students into several main types of learning problem groups to facilitate answering student problems. In addition, this study will further cluster sub-categories of each major learning type to indicate specific problems for each student. Unlike most neural network programs, this study attempts to extend short texts with external resources before classifying them to improve classification performance. In short, by applying the classification of short texts, we can point out the learning problems of each student and inform the instructors where the main focus of future courses will improve the ICT education environment. The data of the empirical process will be used to pre-process the chat records between teachers and students and the course materials. An action system will be set up to compare the most similar parts of the teaching material with each student's chat history to improve future classification performance. Later, the function of short text classification uses CNN to classify rich chat records into several major learning problems based on theory-driven titles. By applying these modules, this research hopes to clarify the main learning problems of students and inform teachers that they should focus on future teaching.

Keywords: ICT education improvement, social equality, short text analysis, convolutional neural network

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Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

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Authors: Daniela Velichová

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

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

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Authors: Lorena Blasco-Arcas, Francesca Pucciarelli

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Business contexts have become globalised and digitalised, which requires that managers develop a strong sense of cross-cultural intelligence while working in geographically distant teams by means of digital technologies. How to better equip future managers on these kinds of skills has been put forward as a critical issue in Business Schools. In pursuing these goals, higher education is shifting from a passive lecture approach, to more active and experiential learning approaches that are more suitable to learn skills. For example, through the use of case studies, proposing plausible business problem to be solved by students (or teams of students), these institutions have focused for long in fostering learning by doing. Though, case studies are no longer enough as a tool to promote active teamwork and experiential learning. Moreover, digital advancements applied to educational settings have enabled augmented classrooms, expanding the learning experience beyond the class, which increase students’ engagement and experiential learning. Different authors have highlighted the benefits of digital engagement in order to achieve a deeper and longer-lasting learning and comprehension of core marketing concepts. Clickers, computer-based simulations and business games have become fairly popular between instructors, but still are limited by the fact that are fictional experiences. Further exploration of real digital platforms to implement real, live projects in the classroom seem relevant for marketing and business education. Building on this, this paper describes the development of an experiential learning activity in class, in which students developed a communication campaign in teams using the BuzzFeed platform, and subsequently implementing the campaign by using other social media platforms (e.g. Facebook, Instagram, Twitter…). The article details the procedure of using the project for a marketing module in a Bachelor program with students located in France, Italy and Spain campuses working on multi-campus groups. Further, this paper describes the project outcomes in terms of students’ engagement and analytics (i.e. visits achieved). the project included a survey in order to analyze and identify main aspects related to how the learning experience is influenced by the cultural competence developed through working in geographically distant and culturally diverse teamwork. Finally, some recommendations to use project-based social media tools while working with virtual teamwork in the classroom are provided.

Keywords: cultural competences, experiential learning, social media, teamwork, virtual group work

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Authors: Maryam Hamlehdar, Guillermo A. Narsilio

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To enhance the feasibility of utilising geothermal hot sedimentary aquifers (HSAs) for clean hydrogen production, one approach is the implementation of solar-integrated geothermal energy systems. This detailed modelling study conducts a thermo-economic assessment of an advanced Organic Rankine Cycle (ORC)-based hydrogen production system that uses low-temperature geothermal reservoirs, with a specific focus on hot sedimentary aquifers (HSAs) over a 30-year period. In the proposed hybrid system, solar-thermal energy is used to raise the water temperature extracted from the geothermal production well. This temperature increase leads to a higher steam output, powering the turbine and subsequently enhancing the electricity output for running the electrolyser. Thermodynamic modeling of a parabolic trough solar (PTS) collector is developed and integrated with modeling for a geothermal-based configuration. This configuration includes a closed regenerator cycle (CRC), proton exchange membrane (PEM) electrolyser, and thermoelectric generator (TEG). Following this, the study investigates the impact of solar energy use on the temperature enhancement of the geothermal reservoir. It assesses the resulting consequences on the lifecycle performance of the hydrogen production system in comparison with a standalone geothermal system. The results indicate that, with the appropriate solar collector area, a combined solar-geothermal hydrogen production system outperforms a standalone geothermal system in both cost and rate of production. These findings underscore a solar-assisted geothermal hybrid system holds the potential to generate lower-cost hydrogen with enhanced efficiency, thereby boosting the appeal of numerous low to medium-temperature geothermal sources for hydrogen production.

Keywords: clean hydrogen production, integrated solar-geothermal, low-temperature geothermal energy, numerical modelling

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Authors: Yingqi Cui, Changran Huang, Raymond Lee

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In this paper, we proposed an AI Tutor using ontology and natural language process techniques to generate a computer science domain knowledge graph and answer users’ questions based on the knowledge graph. We define eight types of relation to extract relationships between entities according to the computer science domain text. The AI tutor is separated into two agents: learning agent and Question-Answer (QA) agent and developed on JADE (a multi-agent system) platform. The learning agent is responsible for reading text to extract information and generate a corresponding knowledge graph by defined patterns. The QA agent can understand the users’ questions and answer humans’ questions based on the knowledge graph generated by the learning agent.

Keywords: artificial intelligence, natural Language processing, knowledge graph, intelligent agents, QA system

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Authors: Frantisek Mosna

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E-learning has become an efficient and widespread means in process of education at all branches of human activities. Statistics is not an exception. Unfortunately the main focus in the statistics teaching is usually paid to the substitution to formulas. Suitable web-sites can simplify and automate calculation and provide more attention and time to the basic principles of statistics, mathematization of real-life situations and following interpretation of results. We introduce our own web-sites for hypothesis testing. Their didactic aspects, technical possibilities of individual tools for their creating, experience and advantages or disadvantages of them are discussed in this paper. These web-sites do not substitute common statistical software but significantly improve the teaching of the statistics at universities.

Keywords: e-learning, hypothesis testing, PHP, web-sites

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Authors: Shri Krishna Mishra, Badri Yadav

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Effect of collaborative learning on development of process skills and attitude towards science is It rightly said that the destiny of the nation is shaped inside its classroom. Classroom is a place where the pupil and teacher interact purposefully to gain knowledge. Teaching is the principal mode of education. It can be called a transaction between teacher and pupil, in which one transmits knowledge to other. The teaching learning process consists of three important components, the pupils, the teacher and the curriculum; the classroom is the collection of students of their own individual abilities and needs. In the present classroom teaching learners are either persuasive recipient or passive observant. The school environment leading to low-achievement we have to try better to develop in the young mind. Children are the sticks of dynamite, bundles of energy and potential power waiting to be ignited. Guide them carefully to a place where their potentialities and strength will be used to build a better world. Man’s future depends to large extent on scientific advances and development of productive activity. Science is considered as an important subject in school curricular. The education commission (1964-66) has suggested that science education is necessary for all children at school stage. It is essential to develop children’s logical and critical thinking. But these days thinking process and academic achievement of students have been suppressed by competitive environment of our schools. How the students perceive each other and interact with one another is a neglected aspect of instruction. In the constructivist perspective learning in a process of construction of knowledge. Learners actively construct their own knowledge by connecting new ideas to existing ideas on the basis of materials/ activities presented to them (experience).

Keywords: effect of collaborative learning, development of process skills, science education, attitude towards science

Procedia PDF Downloads 250

Authors: F. Uriel, M. M. Fernandez Liporace

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In the last decade, academic achievement in higher education has become a topic of agenda in Argentina, regarding the high figures of adjustment problems, academic failure and dropout, and the low graduation rates in the context of massive classes and traditional teaching methods. Psychological variables, such as perceived social support, academic motivation and learning styles and strategies have much to offer since their measurement by tests allows a proper diagnose of their influence on academic achievement. Framed in a major research, several studies analysed multiple samples, totalizing 5135 students attending Argentinean public universities. The first goal was aimed at the identification of statistically significant differences in psychological variables -perceived social support, learning styles, learning strategies, and academic motivation- by age, gender, and degree of academic advance (freshmen versus sophomores). Thus, an inferential group differences study for each psychological dependent variable was developed by means of student’s T tests, given the features of data distribution. The second goal, aimed at examining associations between the four psychological variables on the one hand, and academic achievement on the other, was responded by correlational studies, calculating Pearson’s coefficients, employing grades as the quantitative indicator of academic achievement. The positive and significant results that were obtained led to the formulation of different predictive models of academic achievement which had to be tested in terms of adjustment and predictive power. These models took the four psychological variables above mentioned as predictors, using regression equations, examining predictors individually, in groups of two, and together, analysing indirect effects as well, and adding the degree of academic advance and gender, which had shown their importance within the first goal’s findings. The most relevant results were: first, gender showed no influence on any dependent variable. Second, only good achievers perceived high social support from teachers, and male students were prone to perceive less social support. Third, freshmen exhibited a pragmatic learning style, preferring unstructured environments, the use of examples and simultaneous-visual processing in learning, whereas sophomores manifest an assimilative learning style, choosing sequential and analytic processing modes. Despite these features, freshmen have to deal with abstract contents and sophomores, with practical learning situations due to study programs in force. Fifth, no differences in academic motivation were found between freshmen and sophomores. However, the latter employ a higher number of more efficient learning strategies. Sixth, freshmen low achievers lack intrinsic motivation. Seventh, models testing showed that social support, learning styles and academic motivation influence learning strategies, which affect academic achievement in freshmen, particularly males; only learning styles influence achievement in sophomores of both genders with direct effects. These findings led to conclude that educational psychologists, education specialists, teachers, and universities must plan urgent and major changes. These must be applied in renewed and better study programs, syllabi and classes, as well as tutoring and training systems. Such developments should be targeted to the support and empowerment of students in their academic pathways, and therefore to the upgrade of learning quality, especially in the case of freshmen, male freshmen, and low achievers.

Keywords: academic achievement, academic motivation, coping, learning strategies, learning styles, perceived social support

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Authors: Akshat Kumar, Vidushi

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This paper identifies 27 KOIs, 26 of which are currently classified as candidates and one as false positives that have a high probability of being confirmed. For this purpose, 11 machine learning algorithms were implemented on the cumulative kepler dataset sourced from the NASA exoplanet archive; it was observed that the best-performing model was HistGradientBoosting and XGBoost with a test accuracy of 93.5%, and the lowest-performing model was Gaussian NB with a test accuracy of 54%, to test model performance F1, cross-validation score and RUC curve was calculated. Based on the learned models, the significant characteristics for confirm exoplanets were identified, putting emphasis on the object’s transit and stellar properties; these characteristics were namely koi_count, koi_prad, koi_period, koi_dor, koi_ror, and koi_smass, which were later considered to filter out the potential KOIs. The paper also calculates the Earth similarity index based on the planetary radius and equilibrium temperature for each KOI identified to aid in their classification.

Keywords: Kepler objects of interest, exoplanets, space exploration, machine learning, earth similarity index, transit photometry

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Authors: John White

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This study investigated the effects of practice schedules on learning and performance in golf putting, specifically focusing on the impact of increasing contextual interference (CI). University students (n=7) were randomly assigned to blocked, random, or increasing practice schedules. During acquisition, participants performed 135 putting trials using different weighted golf balls. The blocked group followed a specific sequence of ball weights, while the random group practiced with the balls in a random order. The increasing group started with a blocked schedule, transitioned to a serial schedule, and concluded with a random schedule. Retention and transfer tests were conducted 24 hours later. The results indicated that high levels of CI (random practice) were more beneficial for learning than low levels of CI (blocked practice). The increasing practice schedule, incorporating blocked, serial, and random practice, demonstrated advantages over traditional blocked and random schedules. Additionally, EEG was used to explore the neurophysiological effects of the increasing practice schedule.

Keywords: skill acquisition, motor control, learning, contextual interference

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Authors: Angsumalin Puntho

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Disruptive technology has had a great influence on our everyday lives and the existence of an organization. Geologists in the public sector need to keep up with digital technology and be able to work and collaborate in a more effective manner. The result from SWOT and 7S McKinsey analyses suggest that there are inadequate IT personnel, no individual digital literacy development plan, and a misunderstanding of management policies. The Office of Civil Service Commission develops digital literacy skills that civil servants and government officers should possess in order to work effectively; it consists of nine dimensions, including computer skills, internet skills, cyber security awareness, word processing, spreadsheets, presentation programs, online collaboration, graphics editors and cyber security practices; and six steps of digital literacy development including self-assessment, individual development plan, self-learning, certified test, learning reflection, and practices. Geologists can use digital literacy as a learning tool to develop themselves for better career opportunities.

Keywords: disruptive technology, digital technology, digital literacy, computer skills

Procedia PDF Downloads 75

Authors: Tung-Kuang Wu, Hsing-Pei Hsieh, Ying-Ru Meng

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Special Education in Taiwan has been facing difficulties including shortage of teachers and lack in resources. Some students need to receive special education are thus not identified or admitted. Fortunately, information technologies can be applied to relieve some of the difficulties. For example, on-line multimedia courseware can be used to assist the learning of special education students and take pretty much workload from special education teachers. However, there may exist cognitive variations between students in special or regular educations, which suggests the design of online courseware requires different considerations. This study aims to investigate the difference in focus of attention (FOA) between special and regular education students of primary school in viewing the computer screen. The study is essential as it helps courseware developers in determining where to put learning elements that matter the most on the right position of screen. It may also assist special education specialists to better understand the subtle differences among various subtypes of learning disabilities. This study involves 76 special education students (among them, 39 are students with mental retardation, MR, and 37 are students with learning disabilities, LDs) and 42 regular education students. The participants were asked to view a computer screen showing a picture partitioned into 3 × 3 areas with each area filled with text or icon. The subjects were then instructed to mark on the prior given paper sheets, which are also partitioned into 3 × 3 grids, the areas corresponding to the pictures on the computer screen that they first set their eyes on. The data are then collected and analyzed. Major findings are listed: 1. In both text and icon scenario, significant differences exist in the first preferred FOA between special and regular education students. The first FOA for the former is mainly on area 1 (upper left area, 53.8% / 51.3% for MR / LDs students in text scenario; and 53.8% / 56.8% for MR / LDs students in icons scenario), while the latter on area 5 (middle area, 50.0% and 57.1% in text and icons scenarios). 2. The second most preferred area in text scenario for students with MR and LDs are area 2 (upper-middle, 20.5%) and 5 (middle area, 24.3%). In icons scenario, the results are similar, but lesser in percentage. 3. Students with LDs that show similar preference (either in text or icons scenarios) in FOA to regular education students tend to be of some specific sub-type of learning disabilities. For instance, students with LDs that chose area 5 (middle area, either in text or icon scenario) as their FOA are mostly ones that have reading or writing disability. Also, three (out of 13) subjects in this category, after going through the rediagnosis process, were excluded from being learning disabilities. In summary, the findings suggest when designing multimedia courseware for students with MR and LDs, the essential learning elements should be placed on area 1, 2 and 5. In addition, FOV preference may also potentially be used as an indicator for diagnosing students with LDs.

Keywords: focus of attention, learning disabilities, mental retardation, on-line multimedia courseware, special education

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Authors: Jiangxia Han, Liang Xue, Keda Chen

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Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.

Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation

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Authors: Yi-Hsuan Gloria Lo

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The educational objective of vocational high schools (VHSs) is to equip VHS students with practical skills and knowledge that can be applied in the job-related market. However, with the increasing number of technological universities over the past two decades, the majority of VHS students have chosen to receive higher education rather than enter the job market. VHS English education has been confronting a dilemma: Should an English for specific purposes (ESP) approach, which aligns with the educational goal of VHS education, be taken or should an English for general purposes (EGP) approach, which prepares VHS students for advanced studies in universities, be followed? While ESP theorists proposed that that ESP can be taught to secondary learners, little was known about VHS students’ perspective on this ESP-versus-EGP dilemma. Scant research has investigated different facets of students’ needs (necessities, wants, and lacks) for both ESP and EGP in terms of the four language skills and the factors that contribute to any differences. To address the gap in the literature, 100 VHS students responded to statements related to their necessities, wants, and lacks in learning ESP and EGP on a 6-point Likert scale. Six VHS students were interviewed to tap into the reasons for different facets of the needs for learning EGP and ESP. The statistical analysis indicates that at this stage of learning English, VHS subjects believed that EGP was more necessary than ESP; EGP was more desirable than ESP. However, they reported that they were more lacking in ESP than in EGP learning. Regarding EGP, the results show that the VHS subjects rated speaking as their most necessary skill, speaking as the most desirable skill, and writing as the most lacking skill. A significant difference was found between perceived learning necessities and lacks and between perceived wants and lacks. No statistical difference was found between necessities and wants. In the aspect of ESP, the results indicate that the VHS subjects marked reading as their most necessary skill, speaking as the most desirable skill, and writing as the most lacking skill. A significant difference exists between their perceived necessities and lacks and between their wants and lacks. However, there is no statistically significant difference between their perceived lacks and wants. Despite the lack of a significant difference between learning necessities and wants, the qualitative interview data reveal that the reasons for their perceived necessities and wants were different. The findings of the study confirm previous research that demonstrates that ‘needs’ is a multiple and conflicting construct. What VHS students felt most lacking was not necessarily what they believed they should learn or would like to learn. Although no statistical difference was found, different reasons were attributed to their perceived necessities and wants. Both theoretical and practical implications have been drawn and discussed for ESP research in general and teaching ESP in VHSs in particular.

Keywords: vocational high schools (VHSs), English for General Purposes (EGP), English for Specific Purposes (ESP), needs analysis

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Authors: Hirofumi Miyajima, Kazuya Kishida, Noritaka Shigei, Hiromi Miyajima

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Most of self-tuning fuzzy systems, which are automatically constructed from learning data, are based on the steepest descent method (SDM). However, this approach often requires a large convergence time and gets stuck into a shallow local minimum. One of its solutions is to use fuzzy rule modules with a small number of inputs such as DIRMs (Double-Input Rule Modules) and SIRMs (Single-Input Rule Modules). In this paper, we consider a (generalized) DIRMs model composed of double and single-input rule modules. Further, in order to reduce the redundant modules for the (generalized) DIRMs model, pruning and generative learning algorithms for the model are suggested. In order to show the effectiveness of them, numerical simulations for function approximation, Box-Jenkins and obstacle avoidance problems are performed.

Keywords: Box-Jenkins's problem, double-input rule module, fuzzy inference model, obstacle avoidance, single-input rule module

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Authors: Tapas Karmaker

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Centuries ago, we came to know about ‘Golden Ratio’ also known as Golden Angle. The idea of this research is based on this theme. Researcher perceives ‘The Golden Ratio’ in terms of harmony, meaning that every single item in the universe follows a harmonic behavior. In case of human being, brain responses easily and quickly to this harmony to help memorization. In this theory, harmony means a link. This study has been carried out on a segment of school students and a segment of common people for a period of three years from 2003 to 2006. The research in this respect intended to determine the impact of harmony in the brain of these people. It has been found that students and common people can increase their memorization capacity as much as 70 times more by applying this method. This method works faster and better between age of 8 and 30 years. This result was achieved through tests to assess memorizing capacity by using tools like words, rhymes, texts, math and drawings. The research concludes that this harmonic method can be applied for improving the capacity of learning languages, for the better quality of lifestyle, or any other terms of life as well as in professional activity.

Keywords: language, education, golden brain, learning, teaching

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Authors: Nathan Reeves

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Aim: The aim of this study was to evaluate if there was an impact on student learning when peer role play was substituted for a professional actor in the role of simulated patient in a simulation-based scenario. Method: Third-year exercise science students enrolled in a field project course in 2015 (n=24), and 2016 (n=20) participated in a simulation-based case scenario designed to develop their client-centred exercise prescription skills. During the simulation, students were provided with feedback from the simulated patients. In 2015, three professional actors played the part of the simulated patient, and in 2016 one of the simulated patients was a student from another exercise science cohort (peer role play). The student learning experience, consistency in case fidelity and feedback provided by the simulated patients was evaluated using a 5-point Likert scale survey and collecting phenomenological data. Results: Improvements to student pre and post confidence remained constant between the 2015 and 2016 cohorts (1.04 and 0.85). The perceived usefulness and enjoyability also remained high across the two cohorts (4.96 and 4.71). The feedback provided by all three simulated patients in 2016 was seen to strongly support student learning experience (4.82), and was of a consistent level (4.47). Significance of the findings to allied health: Simulation-based education is rapidly expanding in the curricula across the allied health professions. The simulated patient methodology continues to receive support as a pedagogy to develop a range of clinical skills including communication, engagement and client-centeredness. Upskilling students to peer role play can be a reasonable alternative to engaging paid actors.

Keywords: exercise science, simulation-based learning, simulated patient, peer role play

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Authors: Hung-Shuo Wu, Huan-Chieh Chiu, Xiang-Yao Zheng, Yu-Cheng Yang, Chien-Hao Wang, Jen-Cheng Wang, Chwan-Lu Tseng, Joe-Air Jiang

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Dynamic Thermal Rating (DTR) provides crucial information by estimating the ampacity of transmission lines to improve power dispatching efficiency. To perform the DTR, it is necessary to install on-line thermal sensors to monitor conductor temperature and weather variables. A simple and intuitive strategy is to allocate a thermal sensor to every span of transmission lines, but the cost of sensors might be too high to bear. To deal with the cost issue, a thermal sensor placement problem must be solved. This research proposes and implements a hybrid algorithm which combines proper orthogonal decomposition (POD) with particle swarm optimization (PSO) methods. The proposed hybrid algorithm solves a multi-objective optimization problem that concludes the minimum number of sensors and the minimum error on conductor temperature, and the optimal sensor placement is determined simultaneously. The data of 345 kV transmission lines and the hourly weather data from the Taiwan Power Company and Central Weather Bureau (CWB), respectively, are used by the proposed method. The simulated results indicate that the number of sensors could be reduced using the optimal placement method proposed by the study and an acceptable error on conductor temperature could be achieved. This study provides power companies with a reliable reference for efficiently monitoring and managing their power grids.

Keywords: dynamic thermal rating, proper orthogonal decomposition, particle swarm optimization, sensor placement, smart grid

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Authors: Anna-Kaisa Sjolund

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The doctoral thesis examines interaction design and sensory ethnography as tools to create immersive education environments. In recent years, there has been increasing interest and discussions among researchers and educators on immersive education like augmented reality tools, virtual glasses and the possibilities to utilize them in education at all levels. Using virtual devices as learning environments it is possible to create multisensory learning environments. Sensory ethnography in this study refers to the way of the senses consider the impact on the information dynamics in immersive learning environments. The past decade has seen the rapid development of virtual world research and virtual ethnography. Christine Hine's Virtual Ethnography offers an anthropological explanation of net behavior and communication change. Despite her groundbreaking work, time has changed the users’ communication style and brought new solutions to do ethnographical research. The virtual reality with all its new potential has come to the fore and considering all the senses. Movie and image have played an important role in cultural research for centuries, only the focus has changed in different times and in a different field of research. According to Karin Becker, the role of image in our society is information flow and she found two meanings what the research of visual culture is. The images and pictures are the artifacts of visual culture. Images can be viewed as a symbolic language that allows digital storytelling. Combining the sense of sight, but also the other senses, such as hear, touch, taste, smell, balance, the use of a virtual learning environment offers students a way to more easily absorb large amounts of information. It offers also for teachers’ different ways to produce study material. In this article using sensory ethnography as research tool approaches the core question. Sensory ethnography is used to describe information dynamics in immersive environment through interaction design. Immersive education environment is understood as three-dimensional, interactive learning environment, where the audiovisual aspects are central, but all senses can be taken into consideration. When designing learning environments or any digital service, interaction design is always needed. The question what is interaction design is justified, because there is no simple or consistent idea of what is the interaction design or how it can be used as a research method or whether it is only a description of practical actions. When discussing immersive learning environments or their construction, consideration should be given to interaction design and sensory ethnography.

Keywords: immersive education, sensory ethnography, interaction design, information dynamics

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Authors: V. Stejskal, K. Lundova, R. Sebesta, T. Vanina, S. Roje

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Pure strain of Arctic char (AC) Salvelinus alpinus and hybrid (HB) Salvelinus alpinus vs. Salvelinus fontinalis Mitchill belong to fish, which with great potential for culture in recirculating aquaculture systems (RAS). Aquaculture of these fish currently use flow-through systems (FTS), especially in Nordic countries such as Iceland (biggest producer), Norway, Sweden, and Canada. Four different water saturation regimes included normoxia (NOR), permanent hyperoxia (HYP), intermittent hyperoxia (HYP ± ) and regimes where one day of normoxia was followed by one day of hyperoxia (HYP1/1) were tested during 63 days of experiment in both species in two parallel experiments. Fish were reared in two identical RAS system consisted of 24 plastic round tanks (300 L each), drum filter, biological filter with moving beads and submerged biofilter. The temperature was maintained using flow-through cooler during at level of 13.6 ± 0.8 °C. Different water saturation regimes were achieved by mixing of pure oxygen (O₂) with water in three (one for each hyperoxic regime) mixing tower equipped with flowmeter for regulation of gas inflow. The water in groups HYP, HYP1/1 and HYP± was enriched with oxygen up to saturation of 120-130%. In HYP group was this level kept during whole day. In HYP ± group was hyperoxia kept for daylight phase (08:00-20:00) only and during night time was applied normoxia in this group. The oxygen saturation of 80-90% in NOR group was created using intensive aeration in header tank. The fish were fed with commercial feed to slight excess at 2 h intervals within the light phase of the day. Water quality parameters like pH, temperature and level of oxygen was monitoring three times (7 am, 10 am and 6 pm) per day using handy multimeter. Ammonium, nitrite and nitrate were measured in two day interval using spectrophotometry. Initial body weight (BW) was 40.9 ± 8.7 g and 70.6 ± 14.8 in AC and HB group, respectively. Final survival of AC ranged from 96.3 ± 4.6 (HYP) to 100 ± 0.0% in all other groups without significant differences among these groups. Similarly very high survival was reached in trial with HB with levels from 99.2 ± 1.3 (HYP, HYP1/1 and NOR) to 100 ± 0.0% (HYP ± ). HB fish showed best growth performance in NOR group reached final body weight (BW) 180.4 ± 2.3 g. Fish growth under different hyperoxic regimes was significantly reduced and final BW was 164.4 ± 7.6, 162.1 ± 12.2 and 151.7 ± 6.8 g in groups HY1/1, HYP ± and HYP, respectively. AC showed different preference for hyperoxic regimes as there were no significant difference in BW among NOR, HY1/1 and HYP± group with final values of 72.3 ± 11.3, 68.3 ± 8.4 and 77.1 ± 6.1g. Significantly reduced growth (BW 61.8 ± 6.8 g) was observed in HYP group. It is evident from present study that there are differences between pure bred Arctic char and hybrid in relation to hyperoxic regimes. The study was supported by projects 'CENAKVA' (No. CZ.1.05/2.1.00/01.0024), 'CENAKVA II' (No. LO1205 under the NPU I program), NAZV (QJ1510077) and GAJU (No. 060/2016/Z).

Keywords: recirculating aquaculture systems, Salmonidae, hyperoxia, abiotic factors

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Authors: Anass Hsissi, Hakim Allali, Abdelmajid Hajami

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This article presents the results of a doctoral research which aims to integrate metacognitive dimension in the design of human learning computing environments (ILE). We conducted a detailed study on the relationship between metacognitive processes and learning, specifically their positive impact on the performance of learners in the area of reading comprehension. Our contribution is to implement methods, using an intelligent agent based on BDI paradigm to ensure intelligent and reliable support for low readers, in order to encourage regulation and a conscious and rational use of their metacognitive abilities.

Keywords: metacognition, text comprehension EIAH, autoregulation, BDI agent

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Authors: Champa Gunawardana, Anishka Hettiarachchi

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Conducive Architecture for learning environments is an area of interest for many scholars around the world. Loss of sense of hearing leads to the assumption that deaf students are visual learners. Comprehending favorable non-hearing attributes of architecture can lead to effective, rich and friendly learning environments for hearing impaired. The objective of the current qualitative investigation is to explore the nature and parameters of a sense of place of deaf children to support optimal learning. The investigation was conducted with hearing-impaired children (age: between 8-19, Gender: 15 male and 15 female) of Yashodhara deaf and blind school at Balangoda, Sri Lanka. A sensory ethnography study was adopted to identify the nature of perception and the parameters of most preferred and least preferred spaces of the learning environment. The common perceptions behind most preferred places in the learning environment were found as being calm and quiet, sense of freedom, volumes characterized by openness and spaciousness, sense of safety, wide spaces, privacy and belongingness, less crowded, undisturbed, availability of natural light and ventilation, sense of comfort and the view of green colour in the surroundings. On the other hand, the least preferred spaces were found to be perceived as dark, gloomy, warm, crowded, lack of freedom, smells (bad), unsafe and having glare. Perception of space by deaf considering the hierarchy of sensory modalities involved was identified as; light - color perception (34 %), sight - visual perception (32%), touch - haptic perception (26%), smell - olfactory perception (7%) and sound – auditory perception (1%) respectively. Sense of freedom (32%) and sense of comfort (23%) were the predominant psychological parameters leading to an optimal sense of place perceived by hearing impaired. Privacy (16%), rhythm (14%), belonging (9%) and safety (6%) were found as secondary factors. Open and wide flowing spaces without visual barriers, transparent doors and windows or open port holes to ease their communication, comfortable volumes, naturally ventilated spaces, natural lighting or diffused artificial lighting conditions without glare, sloping walkways, wider stairways, walkways and corridors with ample distance for signing were identified as positive characteristics of the learning environment investigated.

Keywords: deaf, visual learning environment, perception, sensory ethnography

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Authors: Hamed Rahmani, Wim Groot

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The term "youth not in employment, education or training (NEET)" refers to a combination of youth unemployment and school dropout. This study investigates the variables that increase the risk of becoming NEET in Iran. A selection bias-adjusted Probit model was employed using machine learning to identify these risk factors. We used cross-sectional data obtained from the Statistical Centre of Iran and the Ministry of Cooperatives Labour and Social Welfare that was taken from the labour force survey conducted in the spring of 2021. We look at years of education, work experience, housework, the number of children under the age of six in the home, family education, birthplace, and the amount of land owned by households. Results show that hours spent performing domestic chores enhance the likelihood of youth becoming NEET, and years of education and years of potential work experience decrease the chance of being NEET. The findings also show that female youth born in cities were less likely than those born in rural regions to become NEET.

Keywords: NEET youth, probit, CART, machine learning, unemployment

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Authors: Leila Goosen, Toppie N. Mukasa-Lwanga

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The purpose of this paper relates to exploring academics’ use of distance education technologies for empowerment and equity in an Information Technology environment. Literature was studied on academics’ technology use towards effective teaching and meaningful learning in a distance education Information Technology environment. Main arguments presented center on formulating and situating significant concepts within an appropriate theoretical and conceptual framework, including those related to distance education, throughput and other measures of academic efficiency. The research design, sampling, data collection instrument and the validity and reliability thereof, as well as the data analysis method used is described. The paper discusses results related to academics’ use of technology towards effective teaching and meaningful learning in a distance education Information Technology environment. Conclusions are finally presented on the way in which this paper makes a significant and original contribution regarding academics’ use of technology towards effective teaching and meaningful learning in a distance education Information Technology environment.

Keywords: distance, education, technologies, Information Technology Environment

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Authors: Gina L. Solano

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This project endeavors to enhance learning experiences for undergraduate pre-service teachers and graduate K-12 educators by leveraging artificial intelligence (AI). Firstly, the initiative delves into integrating AI within undergraduate education courses, fostering traditional literacy skills essential for academic success and extending their applicability beyond the classroom. Education students will explore AI tools to design literacy-focused activities aligned with their curriculum. Secondly, the project investigates the utilization of AI to craft instructional materials employing gamification strategies (e.g., digital and classic games, badges, quests) to amplify student engagement and motivation in mastering course content. Lastly, it aims to create a professional repertoire that can be applied by pre-service and current teachers in P-12 classrooms, promoting seamless integration for those already in teaching positions. The project's impact extends to benefiting college students, including pre-service and graduate teachers, as they enhance literacy and digital skills through AI. It also benefits current P-12 educators who can integrate AI into their classrooms, fostering innovative teaching practices. Moreover, the project contributes to faculty development, allowing them to cultivate low-risk and engaging classroom environments, ultimately enriching the learning journey. The insights gained from this project can be shared within and beyond the discipline to advance the broader field of study.

Keywords: artificial intelligence, gamification, learning experiences, literacy skills, engagement

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Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

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