Search results for: problem-based learning approach

Authors: Helga Mayr

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In our ongoing effort to address urgent global challenges related to sustainability, higher education institutions play a central role in raising a generation of informed and empowered citizens committed to sustainable development. This paper presents the preliminary results of the so far realized evaluation of a compulsory module on education for sustainable development (ESD) offered to students in the bachelor's program in elementary education at the University College of Teacher Education Tyrol (PH Tirol), Austria. The module includes a lecture on sustainability and education as well as a project-based seminar that aims to foster a deep understanding of ESD and its application in pedagogical practice. The study examines various dimensions related to the module's impact on participating students, focusing on prevalent sustainability concepts, intentions, actions, general and sustainability-related self-efficacy, perceived competence related to ESD, and ESD-related self-efficacy. In addition, the research addresses assessment of the learning process. To obtain a comprehensive overview of the effectiveness of the module, a mixed methods approach was/is used in the evaluation. Quantitative data was/is collected through surveys and self-assessment instruments, while qualitative findings were/will be obtained through focus group interviews and reflective analysis. The PH Tirol is collaborating with another University College of Teacher Education (Styria) and a university of applied sciences in Switzerland (UAS of the Grisons) to broaden the scope of the analysis and allow for comparative findings. Preliminary results indicate that students have a relatively rudimentary understanding of sustainability. The extent to which completion of the module influences understanding of sustainability, awareness, intentions, and actions, as well as self-efficacy, is currently under investigation. The results will be available at the time of the conference and will be presented there. In terms of learning, the project-based seminar, which promotes hands-on engagement with ESD, was evaluated for its effectiveness in fostering key sustainability competencies as well as sustainability-related and ESD-related self-efficacy. The research not only provides insights into the effectiveness of the compulsory module ESD at the PH Tirol but also contributes to the broader discourse on integrating ESD into teacher education.

Keywords: education for sustainable development, teacher education, project-based learning, effectiveness measurements

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Authors: Ebtisam Alqahtani

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The purpose of this study is to investigate academic staff perspectives on using Augmented Reality in teaching practice to support students learning remotely during the COVID pandemic. the study adopted the DTPB theoretical model to guide the identification of key potential factors that could motivate academic staff to use or not use AR in teaching practices. A mixing method design was adopted for a better understanding of the study problem. A survey was completed by 851 academic staff, and this was followed by interviews with 20 academic staff. Statistical analyses were used to assess the survey data, and thematic analysis was used to assess the interview data. The study finding indicates that 75% of academic staff were aware of AR as a pedagogical tool, and they agreed on the potential benefits of AR in teaching and learning practices. However, 36% of academic staff use it in teaching and learning practice, and most of them agree with most of the potential barriers to adopting AR in educational environments. In addition, the study results indicate that 91% of them are planning to use it in the future. The most important factors that motivated them to use it in the future are the COVID pandemic factor, hedonic motivation factor, and academic staff attitude factor. The perceptions of academic staff differed according to the universities they attended, the faculties they worked in, and their gender. This study offers further empirical support for the DTPB model, as well as recommendations to help higher education implement technology in its educational environment based on the findings of the study. It is unprecedented the study the necessity of the use of AR technologies in the time of Covid-19. Therefore, the contribution is both theoretical and practice

Keywords: higher education, academic staff, AR technology as pedological tools, teaching and learning practice, benefits of AR, barriers of adopting AR, and motivating factors to adopt AR

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Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

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Authors: Lucy H. Kaiser, Kate Boersen

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Kura Kaupapa Māori (kura) and bilingual schools are primary schools in Aotearoa/New Zealand which operate fully or partially under Māori custom and have curricula developed to include Te Reo Māori and Tikanga Māori (Māori language and cultural practices). These schools were established to support Māori children and their families through reinforcing cultural identity by enabling Māori language and culture to flourish in the field of education. Māori kaupapa (values), Mātauranga Māori (Māori knowledge) and Te Reo are crucial considerations for the development of educational resources developed for kura, bilingual and mainstream schools. The inclusion of hazard risk in education has become an important issue in New Zealand due to the vulnerability of communities to a plethora of different hazards. Māori have an extensive knowledge of their local area and the history of hazards which is often not appropriately recognised within mainstream hazard education resources. Researchers from the Joint Centre for Disaster Research, Massey University and East Coast LAB (Life at the Boundary) in Napier were funded to collaboratively develop a toolkit of tsunami risk reduction activities with schools located in Hawke’s Bay’s tsunami evacuation zones. A Māori-led bicultural approach to developing and running the education activities was taken, focusing on creating culturally and locally relevant materials for students and schools as well as giving students a proactive role in making their communities better prepared for a tsunami event. The community-based participatory research is Māori-centred, framed by qualitative and Kaupapa Maori research methodologies and utilizes a range of data collection methods including interviews, focus groups and surveys. Māori participants, stakeholders and the researchers collaborated through the duration of the project to ensure the programme would align with the wider school curricula and kaupapa values. The education programme applied a tuakana/teina, Māori teaching and learning approach in which high school aged students (tuakana) developed tsunami preparedness activities to run with primary school students (teina). At the end of the education programme, high school students were asked to reflect on their participation, what they had learned and what they had enjoyed during the activities. This paper draws on lessons learned throughout this research project. As an exemplar, retaining a bicultural and bilingual perspective resulted in a more inclusive project as there was variability across the students’ levels of confidence using Te Reo and Māori knowledge and cultural frameworks. Providing a range of different learning and experiential activities including waiata (Māori songs), pūrākau (traditional stories) and games was important to ensure students had the opportunity to participate and contribute using a range of different approaches that were appropriate to their individual learning needs. Inclusion of teachers in facilitation also proved beneficial in assisting classroom behavioral management. Lessons were framed by the tikanga and kawa (protocols) of the school to maintain cultural safety for the researchers and the students. Finally, the tuakana/teina component of the education activities became the crux of the programme, demonstrating a path for Rangatahi to support their whānau and communities through facilitating disaster preparedness, risk reduction and resilience.

Keywords: school safety, indigenous, disaster preparedness, children, education, tsunami

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Authors: Larasati Zuhro, Ida F Priyanto

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Background: In March 2020, Indonesia started to be affected by Covid-19, and the number of victims increased slowly but surely until finally, the highest number of victims reached the highest—about 50,000 persons—for the daily cases in the middle of 2021. Like other institutions, schools and universities were suddenly closed in March 2020, and students had to change their ways of studying from face-to-face to online. This sudden changed affected students and faculty, including LIS students and faculty because they never experienced online classes in Indonesia due to the previous regulation that academic and school activities were all conducted onsite. For almost two years, school and academic activities were held online. This indeed has affected the way students learned and faculty delivered their courses. This raises the question of whether students are now ready for their new learning activities due to the covid-19 disruption. Objectives: this study was conducted to find out the impact of covid-19 pandemic on the LIS learning process and the effectiveness of online classes for students of LIS in Indonesia. Methodology: This was qualitative research conducted among LIS students at UIN Sunan Kalijaga, Yogyakarta, Indonesia. The population are students who were studying for masters’program during covid-19 pandemic. Results: The study showed that students were ready with the online classes because they are familiar with the technology. However, the Internet and technology infrastructure do not always support the process of learning. Students mention slow WIFI is one factor that causes them not being able to study optimally. They usually compensate themselves by visiting a public library, a café, or any other places to get WIFI network. Noises come from the people surrounding them while they are studying online.Some students could not concentrate well when attending the online classes as they studied at home, and their families sometimes talk to other family members, or they asked the students while they are attending the online classes. The noise also came when they studied in a café. Another issue is that the classes were held in shorter time than that in the face-to-face. Students said they still enjoyed the onsite classes instead of online, although they do not mind to have hybrid model of learning. Conclusion: Pandemic of Covid-19 has changed the way students of LIS in Indonesia learn. They have experienced a process of migrating the way they learn from onsite to online. They also adapted their learning with the condition of internet access speed, infrastructure, and the environment. They expect to have hybrid classes in the future.

Keywords: learning, LIS students, pandemic, covid-19

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Authors: Zhi Huang

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This study follows on from previous survey and focus group research exploring the effective teaching process in a translation classroom in Australian universities through case study method. The data analysis draws on social constructivist theory in translation teaching and focuses on teaching process aiming to discover how effective translation teachers conduct teaching in the classroom. The results suggest that effective teaching requires the teacher to have ability in four aspects: classroom management, classroom pedagogy, classroom communication, and teacher roles. Effective translation teachers are able to control the whole learning process, facilitate students in independent learning, guide students to be more critical about translation, giving both positive and negative feedback for students to reflect on their own, and being supportive, patient and encouraging to students for better classroom communication and learning outcomes. This study can be applied to other teachers in translation so that they can reflect on their own teaching in their education contexts and strive for being a more qualified translation teacher and achieving teaching effectiveness.

Keywords: case study, classroom observation, classroom teaching, effective translation teaching, teacher effectiveness

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Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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Authors: Faisal Kalota

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Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.

Keywords: big data, learning analytics, analytics, big data in education, Hadoop

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Authors: Promothes Saha

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Recently, transportation engineering industry members at the study university showed concern that students lacked the skills needed to solve real-world engineering problems using spreadsheet data analysis. In response to the concerns shown by industry members, this study investigated how to engage students in a better way by incorporating spreadsheet analysis during class - also, help them learn the course topics. Helping students link theoretical knowledge to real-world problems can be a challenge. In this effort, in-class activities and worksheets were redesigned to integrate with Excel to solve example problems using built-in tools including cell referencing, equations, data analysis tool pack, solver tool, conditional formatting, charts, etc. The effectiveness of this technique was investigated using students’ evaluations of the course, enrollment data, and students’ comments. Based on the data of those criteria, it is evident that the spreadsheet activities may increase student learning.

Keywords: civil, engineering, active learning, transportation

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Authors: I. Pelizzoni, C. Cavallini, I. Salvaderi, F. Cavallini

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We present the improvement in writing skills obtained by 94 participants (aged between six and 10 years) with special educational needs through a writing enhancement program based on fluency principles. The study was planned and conducted with a single-subject experimental plan for each of the participants, in order to confirm the results in the literature. These results were obtained using precision teaching (PT) methodology to increase the number of written graphemes per minute in the pre- and post-test, by curriculum based measurement (CBM). Results indicated an increase in the number of written graphemes for all participants. The average overall duration of the intervention is 144 minutes in five months of treatment. These considerations have been analyzed taking account of the complexity of the implementation of measurement systems in real operational contexts (an Italian learning center) and important aspects of replicability and cost-effectiveness of such interventions.

Keywords: curriculum based measurement, precision teaching, writing skill, Italian learning center

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Authors: Gaurav Kumar Sinha

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The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

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Authors: Monika Benedek

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This paper intends to present a pilot study of blended ear-training course at a Finnish university. The course ran for ten weeks and included both traditional (offline) group lessons for 90 minutes each week and an online learning platform. Twelve students majored in musicology and music education participated in the course. The aims of pilot research were to develop a new blended ear-training course at university level, to determine the ideal amount of workload in each part of the blended instruction (offline and online) and to develop the course material. The course material was selected from the Classical period in order to develop students’ aural skills together with their stylistic knowledge. Students were asked to provide written feedback of the course content and learning approaches of face-to-face group lessons and online learning platform each week during the course. Therefore, the teaching material is continuously planned for each week. This qualitative data collection and weekly analysis of data are on progress. However, based on the teacher-researcher’s experiences and the students’ feedback already collected, it could be seen that the blended instruction would be an ideal teaching strategy for ear-trainging at the music programmes of universities to develop students’ aural skills and stylistic knowledge. It is also presumed that such blended instruction with less workload would already improve university students’ aural skills and related musicianship skills. The preliminary findings of research also indicated that students generally found those ear-training tasks the most useful to learn online that combined listening, singing, singing and playing an instrument. This paper intends to summarise the final results of the pilot study.

Keywords: blended-learning, ear-training, higher music education, online-learning, pilot study

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Authors: Stijn Horck

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Background: The value of lessons learned from failure increases when these insights can be put to use by those who did not experience the failure. While learning from others has mostly been researched between individuals or teams within the same environment, transferring knowledge from the person who experienced the failure to an outsider comes with extra challenges. As sense-making of failure is an individual process leading to different learning experiences, the potential of lessons learned from failure is highly variable depending on who is transferring the lessons learned. Using an integrated framework of linguistic aspects related to attributional egotism, this study aims to offer a complete explanation of the challenges in transferring lessons learned from failures that are experienced by others. Method: A case study of a failed foundation established to address the information needs for GPs in times of COVID-19 has been used. An overview of failure causes and lessons learned were made through a preliminary analysis of data collected in two phases with metaphoric examples of failure types. This was followed up by individual narrative interviews with the board members who have all experienced the same events to analyse the individual variance of lessons learned through discourse analysis. This research design uses the researcher-as-instrument approach since the recipient of these lessons learned is the author himself. Results: Thirteen causes were given why the foundation has failed, and nine lessons were formulated. Based on the individually emphasized events, the explanation of the failure events mentioned by all or three respondents consisted of more linguistic aspects related to attributional egotism than failure events mentioned by only one or two. Moreover, the learning events mentioned by all or three respondents involved lessons learned that are based on changed insight, while the lessons expressed by only one or two are more based on direct value. Retrospectively, the lessons expressed as a group in the first data collection phase seem to have captured some but not all of the direct value lessons. Conclusion: Individual variance in expressing lessons learned to outsiders can be reduced using metaphoric or analogical explanations from a third party. In line with the attributional egotism theory, individuals separated from a group that has experienced the same failure are more likely to refer to failure causes of which the chances to be contradicted are the smallest. Lastly, this study contributes to the academic literature by demonstrating that the use of linguistic analysis is suitable for investigating the knowledge transfer from lessons learned after failure.

Keywords: failure, discourse analysis, knowledge transfer, attributional egotism

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Authors: Mulu G. Gencha, Gebremedhin Simon, Menna Olango

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This study was conducted at Hawassa University (HwU) in the Southern Nation Nationalities Peoples Regional State (SNNPRS) of Ethiopia. The prime concern of this study was to examine the writing performances of experimental and control group students, perception of experimental group students, and subject instructors. The course was blended learning (BL). Blended learning is a hybrid of classroom and on-line learning. Participants were eighty students from the School of Computer Science. Forty students attended the BL delivery involved using Face-to-Face (FTF) and campus-based online instruction. All instructors, fifty, of School of Language and Communication Studies along with 10 FGD members participated in the study. The experimental group went to the computer lab two times a week for four months, March-June, 2012, using the local area network (LAN), and software (MOODLE) writing program. On the other hand, the control group, forty students, took the FTF writing course five times a week for four months in similar academic calendar. The three instruments, the attitude questionnaire, tests and FGD were designed to identify views of students, instructors, and FGD participants on BL. At the end of the study, students’ final course scores were evaluated. Data were analyzed using independent samples t-tests. A statistically, significant difference was found between the FTF and BL (p<0.05). The analysis showed that the BL group was more successful than the conventional group. Besides, both instructors and students had positive attitude towards BL. The final section of the thesis showed the potential benefits and challenges, considering the pedagogical implications for the BL, and recommended possible avenues for further works.

Keywords: blended learning, computer attitudes, computer usefulness, computer liking, computer confidence, computer phobia

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Authors: Yumeng He

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The purpose of this paper is to establish the “extenics” of children music education, the “extenics” thought and methods are introduced into the children music education field. Discussions are made from the perspective of children music education on how to generate new music cognitive from music cognitive, how to generate new music education from music education and how to generate music learning from music learning. The research methods including the extensibility of music art, extensibility of music education, extensibility of music capability and extensibility of music learning. Results of this study indicate that the thought and research methods of children’s extended music education not only have developed the “extenics” concept and ideological methods, meanwhile, the brand-new thought and innovative research perspective have been employed in discussing the children music education. As indicated in research, the children’s extended music education has extended the horizon of children music education, and has endowed the children music education field with a new thought and research method.

Keywords: comprehensive evaluations, extension thought, extension cognition music education, extensibility

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Authors: Matan Cohen, Maxim Shoshany

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Climatic, topographic and geological diversity, together with frequent disturbance and recovery cycles, produce highly complex spatial patterns of trees, shrubs, dwarf shrubs and bare ground patches. Assessment of spatial and temporal variations of these life-forms patterns under climate change is of high ecological priority. Here we report on one of the first attempts to discriminate between images of three Mediterranean life-forms patterns at three densities. The development of an extensive database of orthophoto images representing these 9 pattern categories was instrumental for training and testing pre-trained and newly-trained DL models utilizing DenseNet architecture. Both models demonstrated the advantages of using Deep Learning approaches over existing spectral and spatial (pattern or texture) algorithmic methods in differentiation 9 life-form spatial mixtures categories.

Keywords: texture classification, deep learning, desert fringe ecosystems, climate change

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Authors: Norah Mohammed Alshahrani, Abdulaziz Almaleh

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Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD and they are Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then Feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by the Support Vector Machine (SVM), achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: autism spectrum disorder, machine learning, feature selection, support vector machine

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Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

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Authors: Bruna Azzari Puga, Richard Roe, Andre Pagani de Souza

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abstract outlines a proposed study to examine how and to what extent interactive, experiential, learner centered methodology develops learning of basic civic and democratic competencies among young children. It stems from the Literacy and Law course taught at Georgetown University Law Center in Washington, DC, since 1998. Law students, trained in best literacy practices and legal cases affecting literacy development, read “law related” children’s books and engage in interactive and extension activities with emerging readers. The law students write a monthly journal describing their experiences and a final paper: a conventional paper or a children’s book illuminating some aspect of literacy and law. This proposal is based on the recent adaptation of Literacy and Law to Brazil at Mackenzie Presbyterian University in São Paulo in three forms: first, a course similar to the US model, often conducted jointly online with Brazilian and US law students; second, a similar course that combines readings of children’s literature with activity based learning, with law students from a satellite Mackenzie campus, for young children from a vulnerable community near the city; and third, a course taught by law students at the main Mackenzie campus for 4th grade students at the Mackenzie elementary school, that is wholly activity and discourse based. The workings and outcomes of these courses are well documented by photographs, reports, lesson plans, and law student journals. The authors, faculty who teach the above courses at Mackenzie and Georgetown, observe that literacy, broadly defined as cognitive and expressive development through reading and discourse-based activities, can be influential in developing democratic civic skills, identifiable by explicit civic competencies. For example, children experience justice in the classroom through cooperation, creativity, diversity, fairness, systemic thinking, and appreciation for rules and their purposes. Moreover, the learning of civic skills as well as the literacy skills is enhanced through interactive, learner centered practices in which the learners experience literacy and civic development. This study will develop rubrics for individual and classroom teaching and supervision by examining 1) the children’s books and students diaries of participating law students and 2) the collection of photos and videos of classroom activities, and 3) faculty and supervisor observations and reports. These rubrics, and the lesson plans and activities which are employed to advance the higher levels of performance outcomes, will be useful in training and supervision and in further replication and promotion of this form of teaching and learning. Examples of outcomes include helping, cooperating and participating; appreciation of viewpoint diversity; knowledge and utilization of democratic processes, including due process, advocacy, individual and shared decision making, consensus building, and voting; establishing and valuing appropriate rules and a reasoned approach to conflict resolution. In conclusion, further development and replication of the learner centered literacy and law practices outlined here can lead to improved qualities of democratic teaching and learning supporting mutual respect, positivity, deep learning, and the common good – foundation qualities of a sustainable world.

Keywords: democracy, law, learner-centered, literacy

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.

Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation

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Authors: Bunthida Chunngam, Thanyanan Worasesthaphong

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This research had objective to develop of the website learning the local wisdom in Phra Nakhon Si Ayutthaya province and studied satisfaction of system user. This research sample was multistage sample for 100 questionnaires, analyzed data to calculated reliability value with Cronbach’s alpha coefficient method α=0.82. This system had 3 functions which were system using, system feather evaluation and system accuracy evaluation which the statistics used for data analysis was descriptive statistics to explain sample feature so these statistics were frequency, percentage, mean and standard deviation. This data analysis result found that the system using performance quality had good level satisfaction (4.44 mean), system feather function analysis had good level satisfaction (4.11 mean) and system accuracy had good level satisfaction (3.74 mean).

Keywords: website, learning, local wisdom, Phra Nakhon Si Ayutthaya province

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Authors: Jozef Jurcik, Miroslav Gutten, Milan Sebok, Daniel Korenciak, Jerzy Roj

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The paper presents the research results of electronic fuel injection system, which can be used for diagnostics of automotive systems. In the paper is described the construction and operation of a typical fuel injection system and analyzed its electronic part. It has also been proposed method for the detection of the injector malfunction, based on the analysis of differential current or voltage characteristics. In order to detect the fault state, it is needed to use self-learning process, by the use of an appropriate self-learning algorithm.

Keywords: electronic fuel injector, diagnostics, measurement, testing device

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Authors: Nongyao Intasaso, Atchara Rattanama, Navarat Pewnual

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This research is survey research purposed to study the factor affected to knowledge management efficiency of personnel in Rajamangala University of Technology Srivijaya, and study the problem of knowledge management affected to knowledge development of personnel in the university. The tool used in this study is structures questioner standardize rating scale in 5 levels. The sample selected by purposive sampling and there are 137 participation calculated in 25% of population. The result found that factor affected to knowledge management efficiency in the university included (1) result from the organization factor found that the university provided project or activity that according to strategy and mission of knowledge management affected to knowledge management efficiency in highest level (x̅ = 4.30) (2) result from personnel factor found that the personnel are eager for knowledge and active to learning to develop themselves and work (Personal Mastery) affected to knowledge management efficiency in high level (x̅ = 3.75) (3) result from technological factor found that the organization brought multimedia learning aid to facilitate learning process affected to knowledge management efficiency in high level (x̅ = 3.70) and (4) the result from learning factor found that the personnel communicated and sharing knowledge and opinion based on acceptance to each other affected to knowledge management efficiency in high level (x̅ = 3.78). The problem of knowledge management in the university included the personnel do not change their work behavior, insufficient of collaboration, lack of acceptance in knowledge and experience to each other, and limited budget. The solutions to solve these problems are the university should be support sufficient budget, the university should follow up and evaluate organization development based on knowledge using, the university should provide the activity emphasize to personnel development and assign the committee to process and report knowledge management procedure.

Keywords: knowledge management, efficiency, personnel, learning process

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Authors: Anas H. Aljemely, Jianping Xuan

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Rolling bearing fault diagnosis plays a pivotal issue in the rotating machinery of modern manufacturing. In this research, a raw vibration signal and improved deep learning method for bearing fault diagnosis are proposed. The multi-dimensional scales of raw vibration signals are selected for evaluation condition monitoring system, and the deep learning process has shown its effectiveness in fault diagnosis. In the proposed method, employing an Exponential linear unit (ELU) layer in a convolutional neural network (CNN) that conducts the identical function on positive data, an exponential nonlinearity on negative inputs, and a particular convolutional operation to extract valuable features. The identification results show the improved method has achieved the highest accuracy with a 100-dimensional scale and increase the training and testing speed.

Keywords: bearing fault prognostics, developed CNN model, multiple-scale evaluation, deep learning features

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Authors: Soumya Mishra, Elena Neiterman

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Aligned with the growing interest in the impact of the pandemic on academic experiences of university students, this study aimed to examine the challenges Canadian undergraduate students experienced during the university closures due to COVID-19. Using qualitative methodological approach, the study utilized semi-structured interviews conducted with 20 undergraduate students enrolled in an Ontario university to explore their thoughts and experience regarding online learning during the peak of the COVID-19 pandemic, from January 2021 to March 2021. The interviews yielded four major themes with the following associated subthemes: Personal Challenges Associated with Adapting to the Pandemic (Change in the Type of Stress Experienced, Unique Impact on Certain Groups of Students, Decreased Motivation, Crucial Role of Resilience), Social Challenges Associated with Adapting to the Pandemic (Increased Loneliness, Challenges Faced while Communicating, Perception of Group work, Role of Living Conditions), Challenges associated with Accessing University Resources (Crucial Role of Professors, Perception of Virtual Events, Importance of Physical Spaces). Overall, the analysis showed that the COVID-19 pandemic fostered resilience and psychological flexibility amongst all students. However, the mental health and social wellbeing of students deteriorated during the COVID-19 pandemic and they reported experiencing chronic stress, anxiety and loneliness. International students, first year and final year students experienced a unique set of challenges. It was hard for participants in our study to make strong new connections with their classmates and maintain existing friendships with their peers. The importance of professors in facilitating learning was amplified in the online environment due to the lack of in-person interaction with other students. Despite these challenges, most participants reported that they received high grades during online learning. The findings from this study could be helpful for organizations and individuals working towards fostering the wellbeing of undergraduate students. They can also help in making post-secondary institutions more resilient to future emergencies by creating contingency plans regarding online instructions and risk management techniques.

Keywords: Canadian, COVID-19, university students, wellbeing

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Authors: Ibtisam Mohammed Salim Al Quraini

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This paper examines how introducing Omani literature in foreign language classrooms can influence the students' motivation in learning the language. The data was collected through the questionnaire which was administered to two samples (A and B) of the participants. Sample A was comprised of 30 female students from English department who are specialist in English literature in college of Arts and Social Science. Sample B in contrast was comprised of 10 female students who their major is English from college of Education. Results show that each genre in literature has different influence on the students' motivation in learning the language which proves that literacy texts are powerful. Generally, Omani English teachers tend to avoid teaching literature because they think that it is a difficult method to use in teaching field. However, the advantages and the influences of teaching poetries, short stories, and plays are discussed. Recommendations for current research and further research are also discussed at the end.

Keywords: education, plays, short stories, poems

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Authors: Xabier Olaz Moratinos

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Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, gazebo, navigation

Procedia PDF Downloads 114

Authors: P. L. Cheng, I. N. Umar

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Online discussion forum is a popular e-learning technique that allows participants to interact and construct knowledge. This study aims to examine the levels of participation, categories of participants and the structure of their interactions in a forum. A convenience sampling of one course coordinator and 23 graduate students was selected in this study. The forums’ log file and the Social Network Analysis software were used in this study. The analysis reveals 610 activities (including viewing forum’s topic, viewing discussion thread, posting a new thread, replying to other participants’ post, updating an existing thread and deleting a post) performed by them in this forum, with an average of 3.83 threads posted. Also, this forum consists of five at-risk participants, six bridging participants, four isolated participants and five leaders of information. In addition, the network density value is 0.15 and there exist five reciprocal interactions in this forum. The closeness value varied between 28 and 68 while the eigen vector centrality value varied between 0.008 and 0.39. The finding indicates that the participants tend to listen more rather than express their opinions in the forum. It was also revealed that those who actively provide supports in the discussion forum were not the same people who received the most responses from their peers. This study found that cliques do not exist in the forum and the participants are not selective to whom they response to, rather, it was based on the content of the posts made by their peers. Based upon the findings, further analysis with different method and population, larger sample size and a longer time frame are recommended.

Keywords: e-learning, learning management system, online forum, social network analysis

Procedia PDF Downloads 391

Authors: Gloria Chen

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In the past, when we complimented someone who had a good command of English, we would say ‘She/He speaks/writes standard English,’ or ‘His/Her English is standard.’ However, with English has becoming a ‘global language,’ many scholars and English users even create a plural form for English as ‘world Englishes,’ which indicates that national/racial varieties of English not only exist, but also are accepted to a certain degree. Now, a question will be raised when it comes to English teaching and learning: ‘What variety/varieties of English should be taught?’ This presentation will first explore Braj Kachru’s well-known categorization of the inner circle, the outer circle, and the expanding circle of English users, as well as inner circle varieties such as ‘Ebonics’ and ‘cockney’. The presentation then will discuss the purposes and contexts of English learning, and apply different approaches to different purposes and contexts. Three major purposes of English teaching/learning will be emphasized and considered: (1) communicative competence, (2) academic competence, and (3) intercultural competence. This presentation will complete with the strategies of ‘code switch’ and ‘register switch’ in teaching English to non-standard English speakers in both speaking and writing.

Keywords: world Englishes, standard and non-standard English, inner, outer, expanded circle communicative, academic, intercultural competence

Procedia PDF Downloads 266

Authors: Julie Berame

Abstract:

The study probed that out of eight (8) lessons in Science Six have been validated, lessons 1-3 got the descriptive rating of very satisfactory and lessons 4-8 got the descriptive rating of outstanding based on the content analysis of the prepared CBL lesson plans. The evaluation of the lesson plans focused on the three main features such as statements of the lesson objectives, lesson content, and organization and effectiveness. The study used developmental research procedure that contained three phases, namely: Development phase consists of determining the learning unit, lesson plans, creation of the table of specifications, exercises/quizzes, and revision of the materials; Evaluation phase consists of the development of experts’ assessment checklist, presentation of checklist to the adviser, comments and suggestions, and final validation of the materials; and try-out phase consists of identification of the subject, try-out of the materials using CBL strategy, administering science attitude questionnaire, and statistical analysis to obtain the data. The findings of the study revealed that the relevance and usability of CBL lessons 1 and 2 in terms of lesson objective, lesson content, and organization and effectiveness got the rating of very satisfactory (4.4) and lessons 3-8 got the rating of outstanding (4.7). The lessons 1-8 got the grand rating of outstanding (4.6). Additionally, results showed that CBL strategy helped foster positive attitude among students and achieved effectiveness in psychomotor learning objectives.

Keywords: development, validation, center-based learning, science

Procedia PDF Downloads 240