Search results for: quest based learning

Authors: Saurabh Sharma, Yong Sun, Bruce Vernham

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Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O₂ concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO₂/NOx ratio etc.

Keywords: diesel engine, machine learning, NOₓ emission, semi-empirical

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Authors: Upeksha Jayasuriya

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The sudden transition from onsite to online teaching/learning due to the COVID-19 pandemic called for a need to incorporate feasible as well as effective methods of online teaching in most developing countries like Sri Lanka. The English as a Second Language (ESL) classroom faces specific challenges in this adaptation, and teaching writing can be identified as the most challenging task compared to teaching the other three skills. This study was therefore carried out to explore the challenges of teaching writing online and to provide effective means of overcoming them while taking into consideration the attitudes of students and teachers with regard to learning/teaching English writing via online platforms. A survey questionnaire was distributed (electronically) among 60 students from the University of Colombo, the University of Kelaniya, and The Open University in order to find out the challenges faced by students, while in-depth interviews were conducted with 12 lecturers from the mentioned universities. The findings reveal that the inability to observe students’ writing and to receive real-time feedback discourage students from engaging in writing activities when taught online. It was also discovered that both students and teachers increasingly prefer Google Slides over other platforms such as Padlet, Linoit, and Jam Board as it boosts learner autonomy and student-teacher interaction, which in turn allows real-time formative feedback, observation of student work, and assessment. Accordingly, it can be recommended that teaching writing online can be better facilitated by using interactive platforms such as Google Slides, for it promotes active learning and student engagement in the ESL class.

Keywords: ESL, teaching writing, online teaching, active learning, student engagement

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Authors: Dante Jose R. Amisola, Glenford M. Prospero

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'Driving What’s Next' is a strong campaign of the new administration of De La Salle Lipa in promoting social innovation in quality education. The new leadership directs social innovation in quality education in the institutional directions and initiatives to address real-world challenges with real-world solutions. This research under study aims to qualify the commitment of the institution to extend the Lasallian quality human and Christian education to all, as expressed in the Institution’s new mission-vision statement. The Classic Grounded Theory methodology is employed in the process of generating concepts in reference to the documents, a series of meetings, focus group discussions and other related activities that account for the conceptualization and formulation of the new mission-vision along with the new education innovation framework. Notably, Driving What’s Next is the emergent theory that encapsulates the commitment of giving quality human and Christian education to all. It directs the new leadership in driving social innovation in quality education initiatives. Correspondingly, Driving What’s Next is continually resolved through four interrelated strategies also termed as the institution's four strategic directions, namely: (1) driving social innovation in quality education, (2) embracing our shared humanity and championing social inclusion and justice initiatives, (3) creating sustainable futures and (4) engaging diverse stakeholders in our shared mission. Significantly, the four strategic directions capture and integrate the 17 UN sustainable development goals, making the innovative curriculum locally and globally relevant. To conclude, the main concern of the new administration and how it is continually resolved, provide meaningful and fun learning experiences and promote a new way of learning in the light of the 21^st century skills among the members of the academic community including stakeholders and extended communities at large, which are defined as: learning together and by association (collaboration), learning through engagement (communication), learning by design (creativity) and learning with social impact (critical thinking).

Keywords: DLSL four strategic directions , DLSL Lipa mission-vision, driving what's next, social innovation in quality education

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Authors: Nguyen Thu Ha, Vu Viet Phuong, Do Thi Tieu Yen, Nguyen Thi Thanh Ha

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This semi-experimental research investigated the correlation between 42 English as a foreign language (EFL) sophomores' self-regulated learning strategies (SRL) use and their reading comprehension in the Vietnamese context. The analysis from TOEIC reading tests with SPSS 25.0 indicated that there are substantial differences between the post-test reading scores between the experimental group and the control group; therefore, SRL impacts the reading comprehension of EFL participants. Contrary to the alternative hypothesis, teaching learners SRL approaches had a statistically significant influence on reading comprehension. The findings may aid educators in teaching reading comprehension as an essential skill and in using SRL to improve reading comprehension and achievement and enhance reading comprehension aids for language students and instructors. They should equip educators with a variety of instructional strategies which assist academics in preparing learners for lifetime language study and independence. Moreover, the results might encourage educators, administrators, and policymakers to capitalize on the effects of teaching SRL strategies by providing EFL teachers with preparation programs and experiences that help them improve their teaching methods and strategies, especially when teaching reading comprehension.

Keywords: correlation, reading proficiency, self-regulated learning strategies, SRL, TOEIC reading comprehension

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Authors: M. Devaki, K. B. Jayanthi

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The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%.

Keywords: water body, Deep learning, satellite images, convolution neural network

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Authors: Zahara Abdulhussan Al-Awadai

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Currently, serious games play a significant role in education, sparking an increasing interest in using games for purposes beyond mere entertainment. In this research, we investigate the main requirements and aspects of designing and developing effective serious games for learning and developing a conceptual model to describe the structure of serious games with a focus on both aspects of serious games. The main contributions of this approach are to facilitate the design and development of serious games in a flexible and easy-to-use way and also to support the cooperative work between the multidisciplinary developer team.

Keywords: game development, game design, requirements, serious games, serious game model.

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Authors: Mohammed Amraouy, Mostafa Bellafkih, Abdellah Bennane, Aziza Benomar

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Distance education has become popular due to their ability to provide learning from almost anywhere and anytime. COVID-19 forced educational institutions to urgently introduce distance education to ensure pedagogical continuity, so all stakeholders were invited to adapt to this new paradigm. In order to identify strengths and weaknesses, the research focuses on the need to create an effective mechanism for evaluating distance education. The aims of this research were to explore and evaluate the use of digital media in general and official platforms in particular in distance education practices. To this end, we have developed and validated a questionnaire before administering it to a sample of 431 teachers in Morocco. Teachers reported lower knowledge and skills in the didactic use of ICT in the distance education process. In addition, although age and educative experience of the teachers continue to modulate the level of instrumental skills. Therefore, resources (digital resources and infrastructure) and the teachers’ ICT training present serious limitations, which require a training more focused on the distance educational paradigm and educational environments that allow teachers to create educational activities able to promote and facilitate the distance learning process.

Keywords: distance education, e-learning, teachers’ perceptions, assessment

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Authors: Nashrawan Naser Taha, Andrew M. Cox

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In a multi-cultural learning context, where ties are weak and dynamic, combining qualitative with quantitative research methods may be more effective. Such a combination may also allow us to answer different types of question, such as about people’s perception of the network. In this study the use of observation, interviews and photos were explored as ways of enhancing data from social network questionnaires. Integrating all of these methods was found to enhance the quality of data collected and its accuracy, also providing a richer story of the network dynamics and the factors that shaped these changes over time.

Keywords: mixed methods, social network analysis, multi-cultural learning, social network dynamics

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Authors: Scott Hollier, Ruchi Permvattana

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The purpose of this abstract is to share the findings of a recently completed disability-related Internet of Things (IoT) project undertaken at Curtin University in Australia. The project focused on identifying how IoT could support people with disabilities with their educational outcomes. To achieve this, the research consisted of an analysis of current literature and interviews conducted with students with vision, hearing, mobility and print disabilities. While the research acknowledged the ability to collect data with IoT is now a fairly common occurrence, its benefits and applicability still need to be grounded back into real-world applications. Furthermore, it is important to consider if there are sections of our society that may benefit from these developments and if those benefits are being fully realised in a rush by large companies to achieve IoT dominance for their particular product or digital ecosystem. In this context, it is important to consider a group which, to our knowledge, has had little specific mainstream focus in the IoT area –people with disabilities. For people with disabilities, the ability for every device to interact with us and with each other has the potential to yield significant benefits. In terms of engagement, the arrival of smart appliances is already offering benefits such as the ability for a person in a wheelchair to give verbal commands to an IoT-enabled washing machine if the buttons are out of reach, or for a blind person to receive a notification on a smartphone when dinner has finished cooking in an IoT-enabled microwave. With clear benefits of IoT being identified for people with disabilities, it is important to also identify what implications there are for education. With higher education being a critical pathway for many people with disabilities in finding employment, the question as to whether such technologies can support the educational outcomes of people with disabilities was what ultimately led to this research project. This research will discuss several significant findings that have emerged from the research in relation to how consumer-based IoT can be used in the classroom to support the learning needs of students with disabilities, how industrial-based IoT sensors and actuators can be used to monitor and improve the real-time learning outcomes for the delivery of lectures and student engagement, and a proposed method for students to gain more control over their learning environment. The findings shared in this presentation are likely to have significant implications for the use of IoT in the classroom through the implementation of affordable and accessible IoT solutions and will provide guidance as to how policies can be developed as the implications of both benefits and risks continue to be considered by educators.

Keywords: disability, higher education, internet of things, students

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Authors: Muhammad Maisam Abbas, Salman Tariq, Usama Riaz, Muhammad Tanveer, Humaira Abdul Ghafoor

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Autism Spectrum Disorder (ASD) refers to a developmental disorder that impairs an individual's communication and interaction ability. Individuals feel difficult to read facial expressions while communicating or interacting. Facial Expression Recognition (FER) is a unique method of classifying basic human expressions, i.e., happiness, fear, surprise, sadness, disgust, neutral, and anger through static and dynamic sources. This paper conducts a comprehensive comparison and proposed optimal method for a continued research project—a system that can assist people who have Autism Spectrum Disorder (ASD) in recognizing facial expressions. Comparison has been conducted on three supervised learning algorithms EigenFace, FisherFace, and LBPH. The JAFFE, CK+, and TFEID (I&II) datasets have been used to train and test the algorithms. The results were then evaluated based on variance, standard deviation, and accuracy. The experiments showed that FisherFace has the highest accuracy for all datasets and is considered the best algorithm to be implemented in our system.

Keywords: autism spectrum disorder, ASD, EigenFace, facial expression recognition, FisherFace, local binary pattern histogram, LBPH

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Authors: Teja Koduru

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Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

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Authors: Sumeyra Karatas, Veysel Karatas, Reyhan Safak, Gamze Bulut-Ozturk, Ozgul Kartal

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Productive struggle entails a student's cognitive exertion to comprehend mathematical concepts and uncover solutions not immediately apparent. The significance of productive struggle in learning mathematics is accentuated by influential educational theorists, emphasizing its necessity for learning mathematics with understanding. Consequently, supporting productive struggle in learning mathematics is recognized as a high-leverage and effective mathematics teaching practice. In this study, the investigation into the role of productive struggle in learning mathematics led to the development of a comprehensive rubric for productive struggle pedagogy through an exhaustive literature review. The rubric consists of eight primary criteria and 37 sub-criteria, providing a detailed description of teacher actions and pedagogical choices that foster students' productive struggles. These criteria encompass various pedagogical aspects, including task design, tool implementation, allowing time for struggle, posing questions, scaffolding, handling mistakes, acknowledging efforts, and facilitating discussion/feedback. Utilizing this rubric, a team of researchers and teachers designed eight 90-minute lesson plans, employing a productive struggle pedagogy, for a two-week unit on solving systems of linear equations. Simultaneously, another set of eight lesson plans on the same topic, featuring identical content and problems but employing a traditional lecture-and-practice model, was designed by the same team. The objective was to assess the impact of supporting productive struggle on students' mathematics learning, defined by the strands of mathematical proficiency. This quasi-experimental study compares the control group, which received traditional lecture- and practice instruction, with the treatment group, which experienced a productive struggle in pedagogy. Sixty-six 10th and 11th-grade students from two algebra classes, taught by the same teacher at a high school, underwent either the productive struggle pedagogy or lecture-and-practice approach over two-week eight 90-minute class sessions. To measure students' learning, an assessment was created and validated by a team of researchers and teachers. It comprised seven open-response problems assessing the strands of mathematical proficiency: procedural and conceptual understanding, strategic competence, and adaptive reasoning on the topic. The test was administered at the beginning and end of the two weeks as pre-and post-test. Students' solutions underwent scoring using an established rubric, subjected to expert validation and an inter-rater reliability process involving multiple criteria for each problem based on their steps and procedures. An analysis of covariance (ANCOVA) was conducted to examine the differences between the control group, which received traditional pedagogy, and the treatment group, exposed to the productive struggle pedagogy, on the post-test scores while controlling for the pre-test. The results indicated a significant effect of treatment on post-test scores for procedural understanding (F(2, 63) = 10.47, p < .001), strategic competence (F(2, 63) = 9.92, p < .001), adaptive reasoning (F(2, 63) = 10.69, p < .001), and conceptual understanding (F(2, 63) = 10.06, p < .001), controlling for pre-test scores. This demonstrates the positive impact of supporting productive struggle in learning mathematics. In conclusion, the results revealed the significance of the role of productive struggle in learning mathematics. The study further explored the practical application of productive struggle through the development of a comprehensive rubric describing the pedagogy of supporting productive struggle.

Keywords: effective mathematics teaching practice, high school algebra, learning mathematics, productive struggle

Procedia PDF Downloads 52

Authors: S. Odabasi Cimer, A. Cimer

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Recently, the poor quality of education, low achieving students, low international exam performances and little or no effect of the education reforms on the teaching in the classrooms are the main problems of education discussed in Turkey. Research showed that the quality of an education system can not exceed the quality of its teachers and teaching. Therefore, in-service training (INSET) courses are important to improve teacher quality, thereby, the quality of education. However, according to the research conducted on the evaluation of the INSET courses in Turkey, they are not effective in improving the quality of teaching in the classroom. The main reason for this result is because INSET courses are conducted and delivered in limited time and presented theoretically, which does not meet the needs of teachers and as a result, the knowledge and skills taught are not used in the classrooms. Recently, developed countries have been using Critical Friends Groups (CFGs) successfully for the purpose of school-based training of teachers. CFGs are the learning groups which contain 6-10 teachers aimed at fostering their capacities to undertake instructional and personal improvement and schoolwide reform. CFGs have been recognized as a critical feature in school reform, improving teaching practice and improving student achievement. In addition, in the USA, teachers have named CFGs one of the most powerful professional development activities in which they have ever participated. Whereas, in Turkey, the concept is new. This study aimed to investigate the implications of application, evaluation, and promotion of CFGs which has the potential to contribute to teacher development and student learning in schools in Turkey. For this purpose, the study employed a qualitative approach and case study methodology to implement the model in high schools. The research was conducted in two schools and 13 teachers working in these schools participated. The study lasted two years and the data were collected through various data collection tools including interviews, meeting transcripts, questionnaires, portfolios, and diaries. The results of the study showed that CFGs contributed professional development of teachers and their students’ learning. It also contributed to a culture of collaborative work in schools. A number of barriers and challenges which prevent effective implementation were also determined.

Keywords: critical friends group, education reform, science learning, teacher education

Procedia PDF Downloads 127

Authors: Michele Gattullo, Vito M. Manghisi, Alessandro Evangelista, Enricoandrea Laviola

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In this work, we explored the use of Augmented Reality (AR) to support students in laboratory lectures in Distance Learning (DL), designing an application that proved to be ready for use next semester. AR could help students in the understanding of complex concepts as well as increase their motivation in the learning process. However, despite many prototypes in the literature, it is still less used in schools and universities. This is mainly due to the perceived limited advantages to the investment costs, especially regarding changes needed in the teaching modalities. However, with the spread of epidemiological emergency due to SARS-CoV-2, schools and universities were forced to a very rapid redefinition of consolidated processes towards forms of Distance Learning. Despite its many advantages, it suffers from the impossibility to carry out practical activities that are of crucial importance in STEM ("Science, Technology, Engineering e Math") didactics. In this context, AR perceived advantages increased a lot since teachers are more prepared for new teaching modalities, exploiting AR that allows students to carry on practical activities on their own instead of being physically present in laboratories. In this work, we designed an AR application for the support of engineering students in the understanding of assembly drawings of complex machines. Traditionally, this skill is acquired in the first years of the bachelor's degree in industrial engineering, through laboratory activities where the teacher shows the corresponding components (e.g., bearings, screws, shafts) in a real machine and their representation in the assembly drawing. This research aims to explore the effectiveness of AR to allow students to acquire this skill on their own without physically being in the laboratory. In a preliminary phase, we interviewed students to understand the main issues in the learning of this subject. This survey revealed that students had difficulty identifying machine components in an assembly drawing, matching between the 2D representation of a component and its real shape, and understanding the functionality of a component within the machine. We developed a mobile application using Unity3D, aiming to solve the mentioned issues. We designed the application in collaboration with the course professors. Natural feature tracking was used to associate the 2D printed assembly drawing with the corresponding 3D virtual model. The application can be displayed on students’ tablets or smartphones. Users could interact with selecting a component from a part list on the device. Then, 3D representations of components appear on the printed drawing, coupled with 3D virtual labels for their location and identification. Users could also interact with watching a 3D animation to learn how components are assembled. Students evaluated the application through a questionnaire based on the System Usability Scale (SUS). The survey was provided to 15 students selected among those we participated in the preliminary interview. The mean SUS score was 83 (SD 12.9) over a maximum of 100, allowing teachers to use the AR application in their courses. Another important finding is that almost all the students revealed that this application would provide significant power for comprehension on their own.

Keywords: augmented reality, distance learning, STEM didactics, technology in education

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Authors: Jonathan D. Moore, Mark G. Reith, David S. Long

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Serious games (SGs) have been shown to be an effective teaching tool in many contexts. Because of the success of SGs, several design frameworks have been created to expedite the process of making original serious games to teach specific learning objectives (LOs). Even with these frameworks, the time required to create a custom SG from conception to implementation can range from months to years. Furthermore, it is even more difficult to design a game framework that allows an instructor to create customized game variants supporting multiple LOs within the same field. This paper proposes a refactoring methodology to apply the theoretical principles from well-established design frameworks to a pre-existing serious game. The expected result is a generalized game that can be quickly customized to teach LOs not originally targeted by the game. This methodology begins by describing the general components in a game, then uses a combination of two SG design frameworks to extract the teaching elements present in the game. The identified teaching elements are then used as the theoretical basis to determine the range of LOs that can be taught by the game. This paper evaluates the proposed methodology by presenting a case study of refactoring the serious game Battlespace Next (BSN) to teach joint military capabilities. The range of LOs that can be taught by the generalized BSN are identified, and examples of creating custom LOs are given. Survey results from users of the generalized game are also provided. Lastly, the expected impact of this work is discussed and a road map for future work and evaluation is presented.

Keywords: serious games, learning objectives, game design, learning theory, game framework

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Authors: Alejandra Torres-Landa López

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Introduction: Can architecture students be creative in spaces conformed by an educational infrastructure build with paradigms of the past?, this question and others related are answered in this paper as it presents the PhD research: An anthropic conflict in Mexican Higher Education Institutes, problems and challenges of the educational infrastructure in teaching and learning History of Architecture. This research was finished in 2013 and is one of the first studies conducted nationwide in Mexico that analysis the educational infrastructure impact in learning architecture; its objective was to identify which elements of the educational infrastructure of Mexican Higher Education Institutes where architects are formed, hinder or contribute to the teaching and learning of History of Architecture; how and why it happens. The methodology: A mixed methodology was used combining quantitative and qualitative analysis. Different resources and strategies for data collection were used, such as questionnaires for students and teachers, interviews to architecture research experts, direct observations in Architecture classes, among others; the data collected was analyses using SPSS and MAXQDA. The veracity of the quantitative data was supported by the Cronbach’s Alpha Coefficient, obtaining a 0.86, figure that gives the data enough support. All the above enabled to certify the anthropic conflict in which Mexican Universities are. Major findings of the study: Although some of findings were probably not unknown, they haven’t been systematized and analyzed with the depth to which it’s done in this research. So, it can be said, that the educational infrastructure of most of the Higher Education Institutes studied, is a barrier to the educational process, some of the reasons are: the little morphological variation of space, the inadequate control of lighting, noise, temperature, equipment and furniture, the poor or none accessibility for disable people; as well as the absence, obsolescence and / or insufficiency of information technologies are some of the issues that generate an anthropic conflict understanding it as the trouble that teachers and students have to relate between them, in order to achieve significant learning). It is clear that most of the educational infrastructure of Mexican Higher Education Institutes is anchored to paradigms of the past; it seems that they respond to the previous era of industrialization. The results confirm that the educational infrastructure of Mexican Higher Education Institutes where architects are formed, is perceived as a "closed container" of people and data; infrastructure that becomes a barrier to teaching and learning process. Conclusion: The research results show it's time to change the paradigm in which we conceive the educational infrastructure, it’s time to stop seen it just only as classrooms, workshops, laboratories and libraries, as it must be seen from a constructive, urban, architectural and human point of view, taking into account their different dimensions: physical, technological, documental, social, among others; so the educational infrastructure can become a set of elements that organize and create spaces where ideas and thoughts can be shared; to be a social catalyst where people can interact between each other and with the space itself.

Keywords: educational infrastructure, impact of space in learning architecture outcomes, learning environments, teaching architecture, learning architecture

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Authors: Akanksha Indora

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Environmental problems are considered a vital social issue in terms of the world’s problems with pollution, environmental degradation, and resource depletion. And populism is about appropriating the social issues according to the social condition for mobilizing a mass and constructing a ‘general will’. Populism encourages a move towards a common cause, it channelizes the emotions of the ‘common people’ towards a nation and nature. The Gandhian ideology has been received as a dominant ideology and the ‘only’ solution to environmental problems. This paper strives to understand the symmetry of environmentalism and Gandhianismi.e., how the debate on the environment in India has been primarily studied through the Gandhian ideology. The Indian Social Sciences visualize the broader issues of the environment from these perspectives, thus, making it a hegemonic approach. Being anti pluralist rhetoric is major rhetoric in the becoming of a populist. This paper shall focus on the idea that how this hegemonic construction of Gandhian ideology in the debates on environmentalism has contributed to the making of anti-pluralistic rhetoric. This anti-pluralistic rhetoric has eliminated the possibility of a pluralistic perspective in the debates on the environment. The quest for a moral inspiration embedded in Gandhianism, whose situatedness is found in the Hindu Social order, seems to have been completely rationalized through the larger politics of knowledge and thus making it appear as the only way forward when it is not.

Keywords: environmental populism, gandhianism, populist rhetoric, environmentalism

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Authors: Si Chen, Quanhong Jiang

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In the increasingly mature posture recognition technology, human movement information is widely used in sports rehabilitation, human-computer interaction, medical health, human posture assessment, and other fields today; this project uses the most original ideas; it is proposed to use the collection equipment for the collection of myoelectric data, reflect the muscle posture change on a degree of freedom through data processing, carry out data-muscle three-dimensional model joint adjustment, and realize basic pose recognition. Based on this, bionic aids or medical rehabilitation equipment can be further developed with the help of robotic arms and cutting-edge technology, which has a bright future and unlimited development space.

Keywords: pose recognition, 3D animation, electromyography, machine learning, bionics

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Authors: Kadir Özsoy

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Creating a moderately competitive learning environment is believed to have positive effects on student interest and motivation. The best way today to attract young learners to get involved in a fun, competitive learning experience is possible through mobile applications as these learners mostly rely on games and applications on their phones and tablets to have fun, communicate, look for information and study. In this study, a mobile application called ‘QuizUp’ is used to create a specific game topic for elementary level students at Anadolu University Preparatory School. The topic is specially designed with weekly-added questions in accordance with the course syllabus. Students challenge their classmates or randomly chosen opponents to answer questions related to their course subjects. They also chat and post on the topic’s wall in English. The study aims at finding out students’ perceptions towards the use of the application as a classroom and extra-curricular activity through a survey. The study concludes that educational games boost students’ motivation, lead to increased effort, and positively change their studying habits.

Keywords: competitive learning, educational application, effort, motivation 'QuizUp', study habits

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Authors: Atiya Khan

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Recent research on the condition of school education in India has reaffirmed the importance of quality teacher professional development, especially in light of the rapid changes in teaching methods, learning theories, curriculum, and major shifts in information and technology that education systems are experiencing around the world. However, the quality of programs of teacher professional development in India is often uneven, in some cases non-existing. The educational authorities in India have long recognized this and have developed a range of programs to assist in-service teacher education. But, these programs have been mostly inadequate at improving the quality of teachers in India. Policy literature and reports indicate that the unevenness of these programs and more generally the lack of quality teacher professional development in India are due to factors such as a large number of teachers, budgetary constraints, top-down decision making, teacher overload, lack of infrastructure, and little or no follow-up. The disparity between the government stated goals for quality teacher professional development in India and its inability to meet the learning needs of teachers suggests that new interventions are needed. The realization that globalization has brought about an increase in the social, cultural, political and economic interconnectedness between countries has also given rise to transnational opportunities for education systems, such as India’s, aiming to build their capacity to support teacher professional development. Moreover, new developments in communication technologies seem to present a plausible means of achieving high-quality professional development for teachers through the creation of social learning spaces, such as transnational learning networks. This case study investigates the potential of one such transnational learning network to support the quality of teacher professional development in India, namely the Australia-Asia BRIDGE School Partnerships Project. It explores the participation of some fifteen teachers and their principals from BRIDGE participating schools in Delhi region of India; focusing on their professional development expectations from the BRIDGE program and account for their experiences in the program, in order to determine the program’s potential for the professional development of teachers in this study.

Keywords: case study, Australia-Asia BRIDGE Project, teacher professional development, transnational learning networks

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Authors: Ivan Kuzio

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The GIZ/TTC project is the first of its kind in the Middle East, which allows the development of a teaching training programme to degree level based on modern methodologies. The graduates from this college are part of the Saudization programme and will, over the next four years be part of and eventually run the new Colleges of Excellence. The new Colleges of Excellence are being developed to create a local vocationally trained workforce and will run initially alongside the current Colleges of Technology.

Keywords: blended learning, pedagogy, training, key competencies, social skills, cognitive development

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Authors: Shivangi Agrawal, Hsiu-I Ting

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Entrepreneurship is an essential source of economic growth and a prominent factor influencing socio-economic development. Entrepreneurship education educates and enhances entrepreneurial activity. This study aims to understand current trends in entrepreneurship education and evaluate the effectiveness of diverse entrepreneurship education programs. An increasing number of universities offer entrepreneurship education courses to create and successfully continue entrepreneurial ventures. Despite the prevalence of entrepreneurship education, research studies lack inconsistency about the effectiveness of entrepreneurship education to promote and develop entrepreneurship. Strategies to develop entrepreneurial attitudes and intentions among individuals are hindered by a lack of understanding of entrepreneurs' educational purposes, components, methodology, and resources required. Lack of adequate entrepreneurship education has been linked with low self-efficacy and lack of entrepreneurial intent. Moreover, in the age of digitisation and during the COVID-19 pandemic, digital learning platforms (e.g., online entrepreneurship education courses and programs) and other digital tools (e.g., digital game-based entrepreneurship education) have become more relevant to entrepreneurship education. This paper contributes to the continuation of academic literature in entrepreneurship education by evaluating and assessing current trends in entrepreneurship education programs, leading to better understanding to reduce gaps between entrepreneurial development requirements and higher education institutions.

Keywords: entrepreneurship education, digital technologies, academic entrepreneurship, COVID-19

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Authors: Dauda A. Oladosu, Kamorudeen A Olaiya, Abdurahman Bello

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The deployment of smart meters by utility providers to gather fine grained spatiotemporal consumption data has grossly influenced the consumers’ emotion and behavior towards energy utilization. The quest for reduction in power consumption is now a subject of concern and one the methods adopted by the consumers to achieve this is Non-intrusive Load (appliance) Monitoring. Hence, this work presents performance Analysis of Domotics System as a tool for load monitoring when integrated with Consumer Control Unit of residential building. The system was developed with basic elements which enhance remote sensing, DTMF (Dual Tone Multi-frequency) recognition and cryptic messaging when specific task was performed. To demonstrate its applicability and suitability, this prototype was used consistently for six months at different load demands and the utilities consumed were documented. The results obtained shows good response when phone dialed, and the packet delivery of feedback SMS was quite satisfactory, making the implemented system to be of good quality with affordable cost and performs the desired functions. Besides, comparative analysis showed notable reduction in energy consumption and invariably lessened electrical bill of the consumer.

Keywords: automation, domotics, energy, load, remote, schedule

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Authors: Mzamani Aaron Mabasa

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The research study examines the reality that the Language Services Directorate can be considered a language repository hub. The study postulates that multilingual education guided by language policy implementation can improve student performance and pass rate. Various documents in the form of style guides, glossaries and tutorial letters may be used to enable students to understand complex words, sentences, phrases and paragraphs when technical vocabularies are used. This paper addresses the way in which quality assurance can transform South African official languages, including Sign Language, as mandated by the Language Policy for Higher Education. The paper further emphasizes that Language Services is unique in the sense that it involves all South African officials as tools for student support and facilitation of learning. This is in line with the Constitution of the Republic of South Africa (1996) and the Unisa Language Policy of 2023, which declares the status, parity and esteem of these official languages regarding usage in formal function domains, namely education, economy, social and politics. The aim of this paper is to ensure that quality assurance is ultimately accomplished in terms of teaching and learning standards. Eventually, all South African languages can be used for official domains to achieve functional multilingualism. This paper furthermore points out that content analysis as a research instrument as far as a qualitative approach is concerned may be used as a data collection technique.

Keywords: repository, multilingualism, policy, education

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Authors: Saliha Ozcan

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Technology has become an integral part of our lives, aiding individuals in accessing higher order competencies, such as global awareness, creativity, collaborative problem solving, and self-directed learning. Students need to acquire these competencies, often referred to as 21st century skills, in order to adapt to a fast changing world. Today, an ever-increasing number of schools are exploring how engagement through telecollaboration can support language learning and promote 21st century skill development in classrooms. However, little is known regarding how telecollaboration may influence the way students acquire 21st century skills. In this paper, we aim to shed light to the potential implications of telecollaborative practices in acquisition of 21st century skills. In our context, telecollaboration, which might be carried out in a variety of settings both synchronously or asynchronously, is considered as the process of communicating and working together with other people or groups from different locations through online digital tools or offline activities to co-produce a desired work output. The study presented here will describe and analyse the implementation of a telecollaborative project between two high school classes, one in Spain and the other in Sweden. The students in these classes were asked to carry out some joint activities, including creating an online platform, aimed at raising awareness of the situation of the Syrian refugees. We conduct a qualitative study in order to explore how language, culture, communication, and technology merge into the co-construction of knowledge, as well as supporting the attainment of the 21st century skills needed for network-mediated communication. To this end, we collected a significant amount of audio-visual data, including video recordings of classroom interaction and external Skype meetings. By analysing this data, we verify whether the initial pedagogical design and intended objectives of the telecollaborative project coincide with what emerges from the actual implementation of the tasks. Our findings indicate that, as well as planned activities, unplanned classroom interactions may lead to acquisition of certain 21st century skills, such as collaborative problem solving and self-directed learning. This work is part of a wider project (KONECT, EDU2013-43932-P; Spanish Ministry of Economy and Finance), which aims to explore innovative, cross-competency based teaching that can address the current gaps between today’s educational practices and the needs of informed citizens in tomorrow’s interconnected, globalised world.

Keywords: 21st century skills, telecollaboration, language learning, network mediated communication

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Authors: Vinay P., Srinivas K. S.

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Low Light Image Enhancement is of utmost impor- tance in computer vision based tasks. Applications include vision systems for autonomous driving, night vision devices for defence systems, low light object detection tasks. Many of the existing deep learning methods are resource intensive during the inference step and take considerable time for processing. The algorithm should take considerably less than 41 milliseconds in order to process a real-time video feed with 24 frames per second and should be even less for a video with 30 or 60 frames per second. The paper presents a fast and efficient solution which has two main advantages, it has the potential to be used for a real-time video feed, and it can be used in low compute environments because of the lightweight nature. The proposed solution is a pipeline of three steps, the first one is the use of a simple function to map input RGB values to output RGB values, the second is to balance the colors and the final step is to adjust the contrast of the image. Hence a custom dataset is carefully prepared using images taken in low and bright lighting conditions. The preparation of the dataset, the proposed model, the processing time are discussed in detail and the quality of the enhanced images using different methods is shown.

Keywords: low light image enhancement, real-time video, computer vision, machine learning

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

Procedia PDF Downloads 178

Authors: Heikki Ruohomaa, Vesa Salminen

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Regions are facing huge competition to attract companies, businesses, inhabitants, students, etc. This way to improve living and business environment, which is rapidly changing due to digitalization. On the other hand, from the industry's point of view, the availability of a skilled labor force and an innovative environment are crucial factors. In this context, qualified staff has been seen to utilize the opportunities of digitalization and respond to the needs of future skills. World Manufacturing Forum has stated in the year 2019- report that in next five years, 40% of workers have to change their core competencies. Through digital transformation, new technologies like cloud, mobile, big data, 5G- infrastructure, platform- technology, data- analysis, and social networks with increasing intelligence and automation, enterprises can capitalize on new opportunities and optimize existing operations to achieve significant business improvement. Digitalization will be an important part of the everyday life of citizens and present in the working day of the average citizen and employee in the future. For that reason, the education system and education programs on all levels of education from diaper age to doctorate have been directed to fulfill this ecosystem strategy. Goal: The Fourth Industrial Revolution will bring unprecedented change to societies, education organizations and business environments. This article aims to identify how education, education content, the way education has proceeded, and overall whole the education business is changing. Most important is how we should respond to this inevitable co- evolution. Methodology: The study aims to verify how the learning process is boosted by new digital content, new learning software and tools, and customer-oriented learning environments. The change of education programs and individual education modules can be supported by applied research projects. You can use them in making proof- of- the concept of new technology, new ways to teach and train, and through the experiences gathered change education content, way to educate and finally education business as a whole. Major findings: Applied research projects can prove the concept- phases on real environment field labs to test technology opportunities and new tools for training purposes. Customer-oriented applied research projects are also excellent for students to make assignments and use new knowledge and content and teachers to test new tools and create new ways to educate. New content and problem-based learning are used in future education modules. This article introduces some case study experiences on customer-oriented digital transformation projects and how gathered knowledge on new digital content and a new way to educate has influenced education. The case study is related to experiences of research projects, customer-oriented field labs/learning environments and education programs of Häme University of Applied Sciences.

Keywords: education process, digitalization content, digital tools for education, learning environments, transdisciplinary co-operation

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Authors: Don August G. Delgado

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Foreign Language acquisition without enough motivation is tough because it is the force that drives students’ interest or enthusiasm to achieve learning. In addition, it also serves as the students’ beacon to achieve their goals, desires, dreams, and aspirations in life. Since it plays an integral factor in language learning acquisition, this study focuses on the integrative and instrumental motivation levels of all the first year students of Naresuan University International College. The identification of their motivation level and inclination in learning the English language will greatly help all NUIC lecturers and administrators to create a project or activities that they will truly enjoy and find worth doing. However, if the findings of this study will say otherwise, this study can also show to NUIC lecturers and administrators how they can help and transform NUIC freshmen on becoming motivated learners to enhance their English proficiency levels. All respondents in this study received an adopted and developed questionnaire from different researches in the same perspective. The questionnaire has 24 questions that were randomly arranged; 12 for integrative motivation and 12 for instrumental motivation. The questionnaire employed the five-point Likert scale. The tabulated data were analyzed according to its means and standard deviations using the Standard Deviation Calculator. In order to interpret the motivation level of the respondents, the Interpretation of Mean Scores was utilized. Thus, this study concludes that majority of the NUIC freshmen are neither integratively motivated nor instrumentally motivated students.

Keywords: motivation, integrative, foreign language acquisition, instrumental

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

Procedia PDF Downloads 88