Search results for: learning attitudes

Authors: Angelina A. Tzacheva, Jaishree Ranganathan

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Interest in (STEM) Science Technology Engineering Mathematics education especially Computer Science education has seen a drastic increase across the country. This fuels effort towards recruiting and admitting a diverse population of students. Thus the changing conditions in terms of the student population, diversity and the expected teaching and learning outcomes give the platform for use of Innovative Teaching models and technologies. It is necessary that these methods adapted should also concentrate on raising quality of such innovations and have positive impact on student learning. Light-Weight Team is an Active Learning Pedagogy, which is considered to be low-stake activity and has very little or no direct impact on student grades. Emotion plays a major role in student’s motivation to learning. In this work we use the student feedback data with emotion classification using surveys at a public research institution in the United States. We use Actionable Pattern Discovery method for this purpose. Actionable patterns are patterns that provide suggestions in the form of rules to help the user achieve better outcomes. The proposed method provides meaningful insight in terms of changes that can be incorporated in the Light-Weight team activities, resources utilized in the course. The results suggest how to enhance student emotions to a more positive state, in particular focuses on the emotions ‘Trust’ and ‘Joy’.

Keywords: actionable pattern discovery, education, emotion, data mining

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Authors: Seyedali Seyedkavoosi, Mohammad Obadat, Seantorrion Boyle

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The purpose of this study is to assess the effectiveness of a nontraditional experiential learning strategy in improving the success and interest of mechanical engineering students, using the Kinematics/Dynamics of Machine course as a case study. This upper-division technical course covers a wide range of topics, including mechanism and machine system analysis and synthesis, yet the complexities of ideas like acceleration, motion, and machine component relationships are hard to explain using standard teaching techniques. To solve this problem, a thorough design project was created that gave students hands-on experience developing, manufacturing, and testing their inventions. The main goals of the project were to improve students' grasp of machine design and kinematics, to develop problem-solving and presenting abilities, and to familiarize them with professional software. A questionnaire survey was done to evaluate the effect of this technique on students' performance and interest in mechanical engineering. The outcomes of the study shed light on the usefulness of nontraditional experiential learning approaches in engineering education.

Keywords: experiential learning, nontraditional teaching, hands-on design project, engineering education

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Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

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Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

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Authors: Kavitha Thamadharan, Nurazean Maarop

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The implementation of e-assessment as tool to support the process of teaching and learning in university has become a popular technological means in universities. E-Assessment provides many advantages to the users especially the flexibility in teaching and learning. The e-assessment system has the capability to improve its quality of delivering education. However, there still exists a drawback in terms of security which limits the user acceptance of the online learning system. Even though there are studies providing solutions for identified security threats in e-learning usage, there is no particular model which addresses the factors that influences the acceptance of e-assessment system by lecturers from security perspective. The aim of this study is to explore security aspects of e-assessment in regard to the acceptance of the technology. As a result a conceptual model of secure acceptance of e-assessment is proposed. Both human and security factors are considered in formulation of this conceptual model. In order to increase understanding of critical issues related to the subject of this study, interpretive approach involving convergent mixed method research method is proposed to be used to execute the research. This study will be useful in providing more insightful understanding regarding the factors that influence the user acceptance of e-assessment system from security perspective.

Keywords: secure technology acceptance, e-assessment security, e-assessment, education technology

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Authors: Guessabi Fatiha

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Nowadays, there is no sphere of human life that does not use Information and Communication Technologies (ICTs) in practice. This type of development grew widely in the last years of the 20th century and impacted many fields such as education, health, financing, job markets, communication, governments, industrial productivity, etc. Recently, in higher education, the use of ICTs has been essential and significant during the Covid19 pandemic. Thanks to technology, although the universities in Algeria were locked down during the period of covid19, learning was easily continued, and students were collaborating, communicating, socializing, and learning at a distance. Therefore, ICT tools are required in translation courses to enhance and improve translation teaching. This research explores the use of ICT in teaching and learning translation. The research comes along with a theoretical framework; the literature review is produced to highlight some essential ICT concepts and translation teaching. In order to achieve the study objective, a questionnaire is distributed to the third-year English LMD students at Tahri Mohamed University, and an interview is addressed to the translation teacher. The results and discussion obtained from this investigation confirmed the hypothesis and revealed that the use of ICT is essential in translation courses and it improves translation teaching. Hence, by using ICT in the classroom, the students become more active, and the teachers of translation become knowledge facilitators and leaders.

Keywords: COVID19, ICT, learning, students, teaching, TMU, translation

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Authors: Abdullah Malek, Muzn Al Khaldi, Lian Odeh, Atheer Tariq, Mohammad Al Fardan, Hiba Barqawi

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H. pylori bacterium is a known underlying agent for gastritis, peptic ulcer disease, and gastric cancer and is believed to infect half of the world’s population. Even with the ubiquity of H. pylori bacterium, there is lack of knowledge regarding its modes of transmission, associated diseases, carcinogenic effect and means of prevention; especially in the UAE. A cross sectional study of 500 participants, of which 58% (n= 289) of the respondents were female, and 42% (n=210) were male, was conducted in Sharjah to assess the knowledge, and explore the attitudes and practices among UAE residents towards Helicobacter Pylori and its associated PUD as well as its carcinogenic nature. A structured self-administered questionnaire was distributed to the target population to establish their demographic background and selected aspects of their lifestyle. General knowledge about H. Pylori was poor, only 24.6% stated they have heard of H. pylori. Attitudes towards prevention and practices were relatively poor as well. Subjects who suffered from severe symptoms (ALARM symptoms) had significantly lower habit scores than those with mild and moderate symptoms (p=0.0078**). To the authours’ knowledge, no previous studies were conducted in the United Arab Emirates regarding the epidemiology of the infection to detect the extent of H. Pylori’s impact on the public health. The results of this study can be used to draw conclusions about the average knowledge of the UAE population regarding H. pylori. It can also be a starting point to devise new education programs and campaigns that raise awareness of this health issue which could be easily avoided with early diagnosis and antibiotic treatment.

Keywords: chronic gastritis, community health, gastric cancer, Helicobacter pylori, peptic ulcers

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Authors: Azzeddine Atibi, Khadija El Kababi, Salim Ahmed, Mohamed Radid

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The principal objective of this study is to undertake a comprehensive comparative analysis of distance learning and blended learning modalities, with a particular emphasis on evaluating their effectiveness during the confinement period mandated by the COVID-19 pandemic. This investigation is rooted in the firsthand experiences of educators at the high school and secondary levels within both private and public educational institutions. To acquire the requisite data, we meticulously designed and distributed a survey to these educators, soliciting detailed narratives of their professional experiences throughout this challenging period. The survey aims to elucidate the specific difficulties encountered by teachers, as well as to highlight the innovative pedagogical strategies they devised in response to these challenges. By synthesizing the insights garnered from this survey, our goal is to foster an exchange of experiences among educators and to generate informed recommendations that will inform future educational reforms. Ultimately, this study aspires to contribute to the ongoing discourse on optimizing educational practices in the face of unprecedented disruptions.

Keywords: distance learning, blended learning, covid 19, secondary/ high school, teachingperformance, evaluation

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Authors: Jussi Horelli, Salla Niittymäki

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In this acceleratingly developing world, it will be crucial for our students to not only to adapt to continuous change, but to be the driving force of it. This raises the question of how can the educational processes motivate and encourage the students to learn the perhaps most important skill there for their further work career: the ability to learn and absorb more by themselves. In engineering education, the learning contents and methods have traditionally been very substance oriented and teacher-centered. In Häme University of Applied Sciences (HAMK), the pedagogical model has been completely renewed during the past few years. Terms like phenomenon or skills-based learning and collaborative teaching are things which have not very often been related to engineering education, but are now the foundation of HAMK’s pedagogical model in all disciplines, even in engineering studies. In this paper, a new flexible way of executing engineering studies will be introduced. The paper will summarize three years’ experiences and observations of a process where traditional teacher-centric mechanical engineering teaching was converted into a model where teachers work collaboratively in teams supporting the students’ learning processes.

Keywords: team teaching, collaborative learning, engineering education, new pedagogy

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Authors: Saratu Yusuf Ilu, Mumtaz B. Mustafa, Siti Salwah Salim, Mehdi Malekzadeh

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Children today use computer based application in various activities especially for learning and education. Many of these tools and application such as the Computer Aided Pronunciation Training (CAPT) system enable children to explore and experience them with little supervision from the adults. In order for these tools and application to have maximum effect on the children’s learning and education, it must be attractive to the children to use them. This could be achieved with the proper user interface (UI) design. As children grow, so do their ability, taste and preferences. They interact differently with these applications as they grow older. This study reviews several articles on how age factor influences the UI design. The review focuses on age related abilities such as cognitive, literacy, concentration and feedback requirement. We have also evaluated few of existing CAPT systems and determine the influence of age-based factors on the interface design.

Keywords: children, age-based interaction, learning application, age-based capability

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Authors: Shannon Melideo

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Post-secondary schools that provide specialized instruction for college students with special needs have been in existence for some time in the United States of America. Whether students experience learning disabilities, visual impairments, physical limitations, Autism Spectrum Disorders or any other issue that impacts their learning are able to attend universities that intentionally cater to their needs. While this selection of post-secondary education may be preferred by some students, other have sought a different experience. Over the last ten years, the number of students with Autism Spectrum Disorders (ASD) attending traditional universities in the United States of America has increased significantly. Students with ASD tend to select smaller, private institutions that appear to offer more personal attention and services. This paper will examine how traditional American universities are preparing for this relatively new group of students in their college classrooms. This paper will provide a brief historical timeline of access to university instruction for students with Autism Spectrum Disorders, and how and if students with ASD are received in colleges around the globe, and best research supported practices for success.

Keywords: autism spectrum disorders, access to learning, university instruction, accommodations

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Authors: Garry Gorman, Nigel McKelvey, James Connolly

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This study will evaluate a growth mindset intervention with Junior Cycle Coding and Senior Cycle Computer Science students in Ireland, where gamification will be used to incentivise growth mindset behaviour. An artificial intelligence (AI) driven personalised learning system will be developed to present computer programming learning tasks in a manner that is best suited to the individuals’ own learning preferences while incentivising and rewarding growth mindset behaviour of persistence, mastery response to challenge, and challenge seeking. This research endeavours to measure mindset with before and after surveys (conducted nationally) and by recording growth mindset behaviour whilst playing a digital game. This study will harness the capabilities of AI and aims to determine how a personalised learning (PL) experience can impact the mindset of a broad range of students. The focus of this study will be to determine how personalising the learning experience influences female and disadvantaged students' sense of belonging in the computer science classroom when tasks are presented in a manner that is best suited to the individual. Whole Brain Learning will underpin this research and will be used as a framework to guide the research in identifying key areas such as thinking and learning styles, cognitive potential, motivators and fears, and emotional intelligence. This research will be conducted in multiple school types over one academic year. Digital games will be played multiple times over this period, and the data gathered will be used to inform the AI algorithm. The three data sets are described as follows: (i) Before and after survey data to determine the grit scores and mindsets of the participants, (ii) The Growth Mind-Set data from the game, which will measure multiple growth mindset behaviours, such as persistence, response to challenge and use of strategy, (iii) The AI data to guide PL. This study will highlight the effectiveness of an AI-driven personalised learning experience. The data will position AI within the Irish educational landscape, with a specific focus on the teaching of CS. These findings will benefit coding and computer science teachers by providing a clear pedagogy for the effective delivery of personalised learning strategies for computer science education. This pedagogy will help prevent students from developing a fixed mindset while helping pupils to exhibit persistence of effort, use of strategy, and a mastery response to challenges.

Keywords: computer science education, artificial intelligence, growth mindset, pedagogy

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Authors: Laura Mion

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The implementation of quality management systems in higher education in different countries is determined by national regulatory choices and supranational indications (such as the European Standard Guidelines for Quality Assurance). The effective functioning and transformative capacity of these quality management systems largely depend on the organizational context in which they are applied and, more specifically, on the culture of quality developed in single universities or in single countries. The University's concept of quality culture integrates the structural dimension of QA (quality management manuals, process definitions, tools) with the value dimension of an organization (principles, skills, and attitudes). Within the EHEA (European Higher Education Area), countries such as Portugal, the Netherlands, the UK, and Norway demonstrate a greater integration of QA principles in the various organizational levels and areas of competence of university institutions or have greater experience in implementation or scientific and political debate on the matter. Therefore, the study, through an integrative literature review, of the quality management systems of these countries is aimed at determining a framework of the culture of quality, helpful in defining the elements which, both in structural-organizational terms and in terms of values and skills and attitudes, have proved to be factors of success in the effective implementation of quality assurance systems in universities and in the countries considered in the research. In order for a QA system to effectively aim for continuous improvement in a complex and dynamic context such as the university one, it must embrace a holistic vision of quality from an integrative perspective, focusing on the objective of transforming the reality being evaluated.

Keywords: higher education, quality assurance, quality culture, Portugal, Norway, Netherlands, United Kingdom

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Authors: Sibawu Witness Siyepu

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This study explores the effects of instructional design using blended learning in the learning of radian measures among Engineering students. Blended learning is an education programme that combines online digital media with traditional classroom methods. It requires the physical presence of both lecturer and student in a mathematics computer laboratory. Blended learning provides element of class control over time, place, path or pace. The focus was on the use of Khan Academy to supplement traditional classroom interactions. Khan Academy is a non-profit educational organisation created by educator Salman Khan with a goal of creating an accessible place for students to learn through watching videos in a computer assisted computer. The researcher who is an also lecturer in mathematics support programme collected data through instructing students to watch Khan Academy videos on radian measures, and by supplying students with traditional classroom activities. Classroom activities entails radian measure activities extracted from the Internet. Students were given an opportunity to engage in class discussions, social interactions and collaborations. These activities necessitated students to write formative assessments tests. The purpose of formative assessments tests was to find out about the students’ understanding of radian measures, including errors and misconceptions they displayed in their calculations. Identification of errors and misconceptions serve as pointers of students’ weaknesses and strengths in their learning of radian measures. At the end of data collection, semi-structure interviews were administered to a purposefully sampled group to explore their perceptions and feedback regarding the use of blended learning approach in teaching and learning of radian measures. The study employed Algebraic Insight Framework to analyse data collected. Algebraic Insight Framework is a subset of symbol sense which allows a student to correctly enter expressions into a computer assisted systems efficiently. This study offers students opportunities to enter topics and subtopics on radian measures into a computer through the lens of Khan Academy. Khan academy demonstrates procedures followed to reach solutions of mathematical problems. The researcher performed the task of explaining mathematical concepts and facilitated the process of reinvention of rules and formulae in the learning of radian measures. Lastly, activities that reinforce students’ understanding of radian were distributed. Results showed that this study enthused the students in their learning of radian measures. Learning through videos prompted the students to ask questions which brought about clarity and sense making to the classroom discussions. Data revealed that sense making through reinvention of rules and formulae assisted the students in enhancing their learning of radian measures. This study recommends the use of Khan Academy in blended learning to be introduced as a socialisation programme to all first year students. This will prepare students that are computer illiterate to become conversant with the use of Khan Academy as a powerful tool in the learning of mathematics. Khan Academy is a key technological tool that is pivotal for the development of students’ autonomy in the learning of mathematics and that promotes collaboration with lecturers and peers.

Keywords: algebraic insight framework, blended learning, Khan Academy, radian measures

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Authors: S. Studente, S. Ellis, S. F. Garivaldis

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We report upon a study introducing a chatbot to develop learning communities at a London University, with a largely international student base. The focus of the chatbot was twofold; to ease the transition for students into their first year of university study, and to increase study engagement. Four learning communities were created using the chatbot; level 3 foundation, level 4 undergraduate, level 6 undergraduate and level 7 post-graduate. Students and programme leaders were provided with access to the chat bot via mobile app prior to their study induction and throughout the autumn term of 2019. At the end of the term, data were collected via questionnaires and focus groups with students and teaching staff to allow for identification of benefits and challenges. Findings indicated a positive correlation between study engagement and engagement with peers. Students reported that the chatbot enabled them to obtain support and connect to their programme leader. Both staff and students also made recommendation on how engagement could be further enhanced using the bot in terms of; clearly specified purpose, integration with existing university systems, leading by example and connectivity. Extending upon these recommendations, a second pilot study is planned for September 2020, for which the focus will be upon improving attendance rates, student satisfaction and module pass rates.

Keywords: chatbot, e-learning, learning communities, student engagement

Procedia PDF Downloads 124

Authors: Maria Visitacion N. Gumabay, Byron Joseph A. Hallar, Annjeannette Alain D. Galang

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This study was intended to provide a more efficient and convenient way for mobile users to enhance their knowledge about ASEAN countries. The researchers evaluated the utility of the developed crossword puzzle application and assessed the general usability of its user interface for its intended purpose and audience of users. The descriptive qualitative research method for the research design and the Mobile-D methodology was employed for the development of the software application output. With a generally favorable reception from its users, the researchers concluded that the iSEA Mobile Based Learning Application can be considered ready for general deployment and use. It was also concluded that additional studies can also be done to make a more complete assessment of the knowledge gained by its users before and after using the application.

Keywords: mobile learning, eLearning, crossword, ASEAN, iSEA

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Authors: Romisaa Ali

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This paper presents a comparison between twin-delayed Deep Deterministic Policy Gradient (TD3) and Soft Actor-Critic (SAC) reinforcement learning algorithms in the context of training robust navigation policies for Jackal robots. By leveraging an open-source framework and custom motion control environments, the study evaluates the performance, robustness, and transferability of the trained policies across a range of scenarios. The primary focus of the experiments is to assess the training process, the adaptability of the algorithms, and the robot’s ability to navigate in previously unseen environments. Moreover, the paper examines the influence of varying environmental complexities on the learning process and the generalization capabilities of the resulting policies. The results of this study aim to inform and guide the development of more efficient and practical reinforcement learning-based navigation policies for Jackal robots in real-world scenarios.

Keywords: Jackal robot environments, reinforcement learning, TD3, SAC, robust navigation, transferability, custom environment

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Authors: Fidel O. Okopi, Aminu Kazeem Ibrahim

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The study investigated psychosocial determinants ‘attitudes and self-esteem’ of school violent behaviors and the efficacy of covert sensitization therapy in combination with systematic approach therapy among male students in Lagos metropolis. Ex-post facto experimental research design was adopted for the study. The samples consisted of 39 school violent behavior students identified through the School Disciplinary Record Books and another 39 non-school violent behavior students identified through randomization. The two groups were from four randomly selected Public Senior Secondary Schools. School Violent Behavior Attitudes Scale (SVBAS) and School Violent Behavior Self-Esteem Scale (SVBSES) were used to collect data for the study. Face and Content validity with the Reliability coefficient of 0.772 for SVBAS and 0.813 for SVBSES were obtained. The results showed that the attitude of school violent behavior students do not significantly differ from that of school non-violent behavior students; the self-esteem of school violent behavior students differs significantly from that of school non-violent behavior students and that Covert Sensitization therapy in combination with Systematic Approach therapy were effective in modifying the self-esteem and attitude of school violent behavior students as surf iced in the pre-test and post-test analysis of school violent behavior students’ responses. The School counselors can modify male school violent behaviors that are traced to attitude and self-esteem with Covert Sensitization therapy in combination with Systematic Approach therapy in metropolitan areas.

Keywords: psychosocial determinants, violent behavior, covert sensitization therapy, systematic approach therapy

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Authors: Scott McCutcheon, Karen Schreder

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Higher education is facing a new reality. Student connection with coursework, instructor, and peers competes with online gaming, screen time, and instant gratification. Pedagogical methods that align student connection and critical thinking in a content-rich environment are important in supporting student learning, a sense of community, and emotional health. This mixed methods study focuses on exploring how the use of educational escape rooms (EERs) can support student learning and learning retention while fostering engagement with each other, the instructor, and the coursework. EERs are content-specific, cooperative, team-based learning activities designed to be completed within a short segment of a typical class. Data for the study was collected over three semesters and includes results from the implementation of EERs in science-based and liberal studies courses taught by different instructors. Twenty-seven students were surveyed regarding their learning experiences with this pedagogy, and interviews with four student volunteers were conducted to add depth to the survey data. A key finding from this research indicates that students felt more connected to each other and the course content after participating in the escape room activity. Additional findings point to increased engagement and comprehension of the class material. Data indicates that the use of an EER pedagogy supports student engagement, well-being, subject comprehension, and student-student and student-instructor connection.

Keywords: gamification, innovative pedagogy, student engagement, student emotional well being

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Authors: Norzaliza Md. Nor, Sh-Hussain Salleh, Mahyar Hamedi, Hadrina Hussain, Wahab Abdul Rahman

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Motivational factor is mainly the students’ desire to involve in learning process. However, it also depends on the goal towards their involvement or non-involvement in academic activity. Even though, the students’ motivation might be in the same level, but the basis of their motivation may differ. In this study, it focuses on the intrinsic motivational factor which student enjoy learning or feeling of accomplishment the activity or study for its own sake. The intrinsic motivational factor of students in learning mathematics and science has found as difficult to be achieved because it depends on students’ interest. In the Program for International Student Assessment (PISA) for mathematics and science, Malaysia is ranked as third lowest. The main problem in Malaysian educational system, students tend to have extrinsic motivation which they have to score in exam in order to achieve a good result and enrolled as university students. The use of electroencephalogram (EEG) signals has found to be scarce especially to identify the students’ intrinsic motivational factor in learning science and mathematics. In this research study, we are identifying the correlation between precursor emotion and its dynamic emotion to verify the intrinsic motivational factor of students in learning mathematics and science. The 2-D Affective Space Model (ASM) was used in this research in order to identify the relationship of precursor emotion and its dynamic emotion based on the four basic emotions, happy, calm, fear and sad. These four basic emotions are required to be used as reference stimuli. Then, in order to capture the brain waves, EEG device was used, while Mel Frequency Cepstral Coefficient (MFCC) was adopted to be used for extracting the features before it will be feed to Multilayer Perceptron (MLP) to classify the valence and arousal axes for the ASM. The results show that the precursor emotion had an influence the dynamic emotions and it identifies that most students have no interest in mathematics and science according to the negative emotion (sad and fear) appear in the EEG signals. We hope that these results can help us further relate the behavior and intrinsic motivational factor of students towards learning of mathematics and science.

Keywords: EEG, MLP, MFCC, intrinsic motivational factor

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Authors: Gülay Dalgıç, Gildis Tachir

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Architectural design studios are ambiencein where architecture design is realized as a palpable product in architectural education. In the design studios that the architect candidate will use in the design processthe information, the methods of approaching the design problem, the solution proposals, etc., are set uptogetherwith the studio coordinators. The architectural design process, on the other hand, is complex and uncertain.Candidate architects work in a process that starts with abstre and ill-defined problems. This process starts with the generation of alternative solutions with the help of representation tools, continues with the selection of the appropriate/satisfactory solution from these alternatives, and then ends with the creation of an acceptable design/result product. In the studio ambience, many designs and thought relationships are evaluated, the most important step is the early design phase. In the early design phase, the first steps of converting the information are taken, and converted information is used in the constitution of the first design decisions. This phase, which positively affects the progress of the design process and constitution of the final product, is complex and fuzzy than the other phases of the design process. In this context, the aim of the study is to investigate the effects of face-to-face learning model and e-learning model on the early design phase. In the study, the early design phase was defined by literature research. The data of the defined early design phase criteria were obtained with the feedback graphics created for the architect candidates who performed e-learning in the first year of architectural education and continued their education with the face-to-face learning model. The findings of the data were analyzed with the common graphics program. It is thought that this research will contribute to the establishment of a contemporary architectural design education model by reflecting the evaluation of the data and results on architectural education.

Keywords: education modeling, architecture education, design education, design process

Procedia PDF Downloads 138

Authors: Alexander Huang

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Online learning sessions have become an indispensable complement to in-classroom-learning sessions in the past two years due to the emergence of Covid-19. Due to social distance requirements, many courses and interaction-intensive sessions, ranging from music classes to debate camps, are online. However, online learning imposes a significant challenge for engaging students effectively during the learning sessions. To resolve this problem, Project PWR, a non-profit organization formed by high school students, developed an online kid-teach-kid learning environment to boost students' learning interests and further improve students’ engagement during online learning. Fundamentally, the kid-teach-kid learning model creates an affinity space to form learning groups, where like-minded peers can learn and teach their interests. The role of the teacher can also help a kid identify the instructional task and set the rules and procedures for the activities. The approach also structures initial discussions to reveal a range of ideas, similar experiences, thinking processes, language use, and lower student-to-teacher ratio, which become enriched online learning experiences for upcoming lessons. In such a manner, a kid can practice both the teacher role and the student role to accumulate experiences on how to convey ideas and questions over the online session more efficiently and effectively. In this research work, we conducted two case studies involving a 3D-Design course and a Speech and Debate course taught by high-school kids. Through Project PWR, a kid first needs to design the course syllabus based on a provided template to become a student-teacher. Then, the Project PWR academic committee evaluates the syllabus and offers comments and suggestions for changes. Upon the approval of a syllabus, an experienced and voluntarily adult mentor is assigned to interview the student-teacher and monitor the lectures' progress. Student-teachers construct a comprehensive final evaluation for their students, which they grade at the end of the course. Moreover, each course requires conducting midterm and final evaluations through a set of surveyed replies provided by students to assess the student-teacher’s performance. The uniqueness of Project PWR lies in its established kid-teach-kids affinity space. Our research results showed that Project PWR could create a closed-loop system where a student can help a teacher improve and vice versa, thus improving the overall students’ engagement. As a result, Project PWR’s approach can train teachers and students to become better online learners and give them a solid understanding of what to prepare for and what to expect from future online classes. The kid-teach-kid learning model can significantly improve students' engagement in the online courses through the Project PWR to effectively supplement the traditional teacher-centric model that the Covid-19 pandemic has impacted substantially. Project PWR enables kids to share their interests and bond with one another, making the online learning environment effective and promoting positive and effective personal online one-on-one interactions.

Keywords: kid-teach-kid, affinity space, online learning, engagement, student-teacher

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Authors: Mohd Khairezan Rahmat

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Since the impetus of becoming a develop country by the year 2020, the Malaysian government have been proactive in strengthening the integration of ICT into the national educational system. Teacher-education programs have the responsibility to prepare the nation future teachers by instilling in them the desire, confidence, and ability to fully utilized the potential of ICT into their instruction process. In an effort to fulfill this responsibility, teacher-education program are beginning to create alternatives means for preparing cutting-edge teachers. One of the alternatives is the student’s learning portal. In line with this mission, this study investigates the Faculty of Education, University Teknologi MARA (UiTM) pre-service teachers’ perception of usefulness, attitude, and ability toward the usage of the university learning portal, known as iLearn. The study also aimed to predict factors that might hinder the pre-service teachers’ decision to used iLearn as their platform in learning. The Structural Equation Modeling (SEM), was employed in analyzed the survey data. The suggested findings informed that pre-service teacher’s successful integration of the iLearn was highly influenced by their perception of usefulness of the system. The findings also suggested that the more familiar the pre-service teacher with the iLearn, the more possibility they will use the system. In light of similar study, the present findings hope to highlight the important to understand the user’s perception toward any proposed technology.

Keywords: e-learning, prediction factors, pre-service teacher, structural equation modeling (SEM)

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Authors: Claire Griffin

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Recent years have witnessed a surge in the use of innovative teaching approaches to support student engagement and higher-order learning within higher education. This paper seeks to explore the use of collaborative, interactive teaching and learning strategies to support student engagement in a final year undergraduate Developmental Psychology module. In particular, the use of the jigsaw method, in-class presentations and online discussion fora were adopted in a ‘lectorial’ style teaching approach, aimed at scaffolding learning, fostering social interdependence and supporting various levels of student engagement in higher education. Using the ‘Student Course Engagement Questionnaire’, the impact of such teaching strategies on students’ college classroom experience was measured, with additional qualitative student feedback gathered. Results illustrate the positive impact of the teaching methodologies on students’ levels of engagement, with positive implications emerging across the four engagement factors: skills engagement, emotional engagement, participation/interaction engagement and performance engagement. Thematic analysis on students’ qualitative comments also provided greater insight into the positive impact of the ‘lectorial’ teaching approach on students’ classroom experience within higher level education. Implications of the findings are presented in terms of informing effective teaching practices within higher education. Additional avenues for future research and strategy usage will also be discussed, in light of evolving practice and cutting edge literature within the field.

Keywords: learning, higher education, scaffolding, student engagement

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Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi

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In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.

Keywords: ANPR, CS, CNN, deep learning, NPL

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Authors: Shubham Bhonde, Nekzad Doctor, Shashwat Gawande

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For the use and the import of Keys and ID Transmitter as well as Body Control Modules with radio transmission in a lot of countries, homologation is required. Final deliverables in homologation of the product are certificates. In considering the world of homologation, there are approximately 200 certificates per product, with most of the certificates in local languages. It is challenging to manually investigate each certificate and extract relevant data from the certificate, such as expiry date, approval date, etc. It is most important to get accurate data from the certificate as inaccuracy may lead to missing re-homologation of certificates that will result in an incompliance situation. There is a scope of automation in reading the certificate data in the field of homologation. We are using deep learning as a tool for automation. We have first trained a model using machine learning by providing all country's basic data. We have trained this model only once. We trained the model by feeding pdf and jpg files using the ETL process. Eventually, that trained model will give more accurate results later. As an outcome, we will get the expiry date and approval date of the certificate with a single click. This will eventually help to implement automation features on a broader level in the database where certificates are stored. This automation will help to minimize human error to almost negligible.

Keywords: homologation, re-homologation, data science, deep learning, machine learning, ETL (extract transform loading)

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Authors: Anupriya Sharma, Sapna Narula

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Over the past decade, sustainability has gone mainstream as more people are worried about environment-related issues than ever before. These issues are of even more concern for industries which leave a significant impact on the environment. Following these ecological issues, corporates are beginning to comprehend the impact on their business. Many such initiatives have been made to address these emerging issues in the consumer-driven textile industry. Demand from customers, local communities, government regulations, etc. are considered some of the major factors affecting environmental decision-making. Research also shows that motivations to go green are inevitably determined by the way top managers perceive environmental issues as managers personal values and ethical commitment act as a motivating factor towards corporate social responsibility. Little empirical research has been conducted to examine the relationship between top managers’ personal environmental attitudes and corporate environmental behaviors for the textile industry in the Indian context. The primary purpose of this study is to determine the current state of environmental management in textile industry and whether the attitude of textile firms’ top managers is significantly related to firm’s response to environmental issues and their perceived benefits of environmental management. To achieve the aforesaid objectives of the study, authors used structured questionnaire based on literature review. The questionnaire consisted of six sections with a total length of eight pages. The first section was based on background information on the position of the respondents in the organization, annual turnover, year of firm’s establishment and so on. The other five sections of the questionnaire were based upon (drivers, attitude, and awareness, sustainable business practices, barriers to implementation and benefits achieved). To test the questionnaire, a pretest was conducted with the professionals working in corporate sustainability and had knowledge about the textile industry and was then mailed to various stakeholders involved in textile production thereby covering firms top manufacturing officers, EHS managers, textile engineers, HR personnel and R&D managers. The results of the study showed that most of the textile firms were implementing some type of environmental management practice, even though the magnitude of firm’s involvement in environmental management practices varied. The results also show that textile firms with a higher level of involvement in environmental management were more involved in the process driven technical environmental practices. It also identified that firm’s top managers environmental attitudes were correlated with perceived advantages of environmental management as textile firm’s top managers are the ones who possess managerial discretion on formulating and deciding business policies such as environmental initiatives.

Keywords: attitude and awareness, Environmental management, sustainability, textile industry

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Authors: Mahmoud I. Syam, Osama K. El-Hafy

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With lack of student motivation, there will be a little or no real learning in the class and this directly effects student achievement and test scores. Some students are naturally motivated to learn, but many students are not motivated, they do care little about learning and need their instructors to motivate them. Thus, motivating students is part of the instructor’s job. It’s a tough task to motivate students and make them have more attention and enthusiasm. As a part of this research, a questionnaire has been distributed among a sample of 155 students out of 1502 students from Foundation Program at Qatar University. The questionnaire helped us to determine some methods to motivate the students and encourage them to study such as variety of teaching activities, encouraging students to participate during the lectures, creating intense competition between the students, using instructional technology, not using grades as a threat and respecting the students and treating them in a good manner. Accordingly, some hypotheses are tested and some recommendations are presented.

Keywords: learning, motivating, student, teacher, testing hypotheses

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Authors: Marcel Chevalier, Léo Dupont, Sylvain Marié, Frédérique Roffet, Elena Stolyarova, William Templier, Costin Vasile

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Industrial end-users are currently facing an increasing need to reduce the risk of unexpected failures and optimize their maintenance. This calls for both short-term analysis and long-term ageing anticipation. At Schneider Electric, we tackle those two issues using both machine learning and first principles models. Machine learning models are incrementally trained from normal data to predict expected values and detect statistically significant short-term deviations. Ageing models are constructed by breaking down physical systems into sub-assemblies, then determining relevant degradation modes and associating each one to the right kinetic law. Validating such anomaly detection and maintenance models is challenging, both because actual incident and ageing data are rare and distorted by human interventions, and incremental learning depends on human feedback. To overcome these difficulties, we propose to simulate physics, systems, and humans -including asset maintenance operations- in order to validate the overall approaches in accelerated time and possibly choose between algorithmic alternatives.

Keywords: degradation models, ageing, anomaly detection, soft sensor, incremental learning

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Authors: Shiyin He, Zheng Huang

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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

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Authors: Ghiwa Dandach

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By challenging the anti-failure bias and contributing to the theoretical territory of the attribution theory, this thesis develops a comprehensive process for entrepreneurial learning from failure. The practical implication of the findings suggests assisting entrepreneurs (current, failing, and nascent) in effectively anticipating and reflecting upon failure. Additionally, the process is suggested to enhance the level of institutional and private (accelerators and financers) support provided to entrepreneurs, the implications of which may improve future opportunities for entrepreneurial success. Henceforth, exploring learning from failure is argued to impact the potential survival of future ventures, subsequently revitalizing the economic contribution of entrepreneurship. This learning process can be enhanced with the cognitive development of causal ascriptions for failure, which eventually impacts learning outcomes. However, the mechanism with which entrepreneurs make sense of failure, reflect on the journey, and transform experience into knowledge is still under-researched. More specifically, the cognitive process of failure attribution is under-explored, majorly in the context of developing economies, calling for a more insightful understanding on how entrepreneurs ascribe failure. Responding to the call for more thorough research in such cultural contexts, this study expands the understanding of the dimensions of failure attributions as perceived by entrepreneurs and the impact of these dimensions on learning outcomes in the Lebanese context. The research adopted the exploratory interpretivism paradigm and collected data from interviews with industry experts first, followed by narratives of entrepreneurs using the qualitative multimethod approach. The holistic and categorical content analysis of narratives, preceded by the thematic analysis of interviews, unveiled how entrepreneurs ascribe failure by developing minor and major dimensions of each failure attribution. The findings have also revealed how each dimension impacts the learning from failure when accompanied by emotional resilience. The thesis concludes that exploring in-depth the dimensions of failure attributions significantly determines the level of learning generated. They are moving beyond the simple categorisation of ascriptions as primary internal or external unveiled how learning may occur with each attribution at the individual, venture, and ecosystem levels. This has further accentuated that a major internal attribution of failure combined with a minor external attribution generated the highest levels of transformative and double-loop learning, emphasizing the role of personal blame and responsibility on enhancing learning outcomes.

Keywords: attribution, entrepreneurship, reflection, sense-making, emotions, learning outcomes, failure, exit

Procedia PDF Downloads 227