Search results for: MATLAB supported learning

Authors: Vishal D. Pandya

Abstract:

A great deal of perceptible change has been taking place in the way our institutions of higher learning are being managed in India today. It is believed that managers, whose intuition proves to be accurate, often tend to be the most successful, and this is what makes them almost like entrepreneurs. A certain entrepreneurial spirit is what is expected and requires a degree of insight of the manager to be successful depending upon the situational and more importantly, the heterogeneity as well as the socio-cultural aspect. Teachers in Higher Education have to play multiple roles to make sure that the Learning-Teaching process becomes effective in the real sense of the term. This paper makes an effort to take a close look at that, especially in the context of the management of English language teaching in Higher Education and, therefore, focuses on the management of English language teaching in higher education by understanding target situation analyses at the socio-cultural level.

Keywords: management, language teaching, English language teaching, higher education

Procedia PDF Downloads 242

Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

Abstract:

Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

Procedia PDF Downloads 85

Authors: Eva Laryea, Clement Yeboah Authors

Abstract:

A pretest-posttest within subjects, experimental design was employed to examine the effects of a computerized basic statistics learning game on achievement and statistics-related anxiety of students enrolled in introductory graduate statistics course. Participants (N = 34) were graduate students in a variety of programs at state-funded research university in the Southeast United States. We analyzed pre-test posttest differences using paired samples t-tests for achievement and for statistics anxiety. The results of the t-test for knowledge in statistics were found to be statistically significant indicating significant mean gains for statistical knowledge as a function of the game-based intervention. Likewise, the results of the t-test for statistics-related anxiety were also statistically significant indicating a decrease in anxiety from pretest to posttest. The implications of the present study are significant for both teachers and students. For teachers, using computer games developed by the researchers can help to create a more dynamic and engaging classroom environment, as well as improve student learning outcomes. For students, playing these educational games can help to develop important skills such as problem solving, critical thinking, and collaboration. Students can develop interest in the subject matter and spend quality time to learn the course as they play the game without knowing that they are even learning the presupposed hard course. The future directions of the present study are promising, as technology continues to advance and become more widely available. Some potential future developments include the integration of virtual and augmented reality into educational games, the use of machine learning and artificial intelligence to create personalized learning experiences, and the development of new and innovative game-based assessment tools. It is also important to consider the ethical implications of computer game-based pedagogy, such as the potential for games to perpetuate harmful stereotypes and biases. As the field continues to evolve, it will be crucial to address these issues and work towards creating inclusive and equitable learning experiences for all students. This study has the potential to revolutionize the way basic statistics graduate students learn and offers exciting opportunities for future development and research. It is an important area of inquiry for educators, researchers, and policymakers, and will continue to be a dynamic and rapidly evolving field for years to come.

Keywords: pretest-posttest within subjects, experimental design, achievement, statistics-related anxiety

Procedia PDF Downloads 57

Authors: Christodoulakis Georgios, Kiourti Elisavet

Abstract:

The Covid-19 pandemic has affected millions of people on a global scale, while lockdowns and quarantine measures were adopted periodically by a vast number of countries. These peculiar socio-historical conditions have led to the growth of participation in online environments. At the same time, the official educational bodies of many countries have been forced, for the first time at least for Greece and Cyprus, to switch to distance learning methods throughout the educational levels. However, this has not been done without issues, both in the technological and functional level, concerning the tools and the processes. Video games are the finest example of simulations of distance learning problem-solving environments. They incorporate different semiotic modes (e.g., a combination of image, sound, texts, gesture) while all this takes place in social and cultural constructed contexts. Players interact in the game environment in terms of spaces, objects, and actions in order to accomplish their goals, solve its problems, and win the game. In addition, players are engaging in layering literacies, which include combinations of independent and collaborative, digital and nondigital practices and spaces acting jointly to support meaning making, including interaction among and across texts and modalities (Abrams, 2017). From this point of view, players are engaged in collaborative, self-directed, and interest-based experiences by going back and forth and around gameplay. Within this context, this paper investigates the way Einstown, a greek serious video game, functions as an effective distance learning environment for teaching Greek as a second|foreign language to adults. The research methodology adopted is the case study approach using mixed methods. The participants were two adult women who are immigrants in Greece and who had zero gaming experience. The results of this research reveal that the videogame Einstown is, in fact, a digital environment of literacy through which the participants achieve active learning, cooperation, and engage in digital and non-digital literacy practices that result in improving the learning of specialized vocabulary presented throughout the gameplay.

Keywords: second/foreign language, vocabulary acquisition, literacy, serious video games

Procedia PDF Downloads 153

Authors: Raeed Alanazi

Abstract:

Introduction: Nursing students have a crucial role to play in the inhibition of infectious diseases and, therefore, must be trained in infection control and prevention modules prior to entering clinical settings. Simulations have been found to have a positive impact on infection control skills and the use of standard precautions. Aim: The purpose of this study was to use the four sources of self-efficacy in explaining the level of clinical self-efficacy and adherence to infection control practices in Saudi nursing students during simulation practice. Method: A cross-sectional design with convenience sampling was used. This study was conducted in all Saudi nursing schools, with a total number of 197 students participated in this study. Three scales were used simulation self- efficacy Scale (SSES), the four sources of self-efficacy scale (SSES), and Compliance with Standard Precautions Scale (CSPS). Multiple linear regression was used to test the use of the four sources of self-efficacy (SSES) in explaining level of clinical self-efficacy and adherence to infection control in nursing students. Results: The vicarious experience subscale (p =.044) was statistically significant. The regression model indicated that for every one unit increase in vicarious experience (observation and reflection in simulation), the participants’ adherence to infection control increased by .13 units (β =.22, t = 2.03, p =.044). In addition, the regression model indicated that for every one unit increase in education level, the participants’ adherence to infection control increased by 1.82 units (beta=.34= 3.64, p <.001). Also, the mastery experience subscale (p <.001) and vicarious experience subscale (p = .020) were shared significant associations with clinical self-efficacy. Conclusion: The findings of this research support the idea that simulation-based learning can be a valuable teaching-learning method to help nursing students develop clinical competence, which is essential in providing quality and safe nursing care.

Keywords: simulation-based learning, clinical self-efficacy, infection control, nursing students

Procedia PDF Downloads 70

Authors: Isabel Moscol, Carlos J. Díaz, Ciro Rodríguez

Abstract:

Hip replacement becomes necessary when a person suffers severe pain or considerable functional limitations and the best option to enhance their quality of life is through the replacement of the damaged joint. One of the main components in femoral prostheses is the stem which distributes the loads from the joint to the proximal femur. To preserve more bone stock and avoid weakening of the diaphysis, a short starting stem was selected, generated from the intramedullary morphology of the patient's femur. It ensures the implantability of the design and leads to geometric delimitation for personalized optimization with machine learning (ML) and metaheuristic algorithms. The present study attempts to design a cementless short stem to make the strain deviation before and after implantation close to zero, promoting its fixation and durability. Regression models developed to estimate the percentage change of maximum principal stresses were used as objective optimization functions by the metaheuristic algorithm. The latter evaluated different geometries of the short stem with the modification of certain parameters in oblique sections from the osteotomy plane. The optimized geometry reached a global stress shielding (SS) of 18.37% with a determination factor (R²) of 0.667. The predicted results favour implantability integration in the short stem optimization to effectively reduce SS in the proximal femur.

Keywords: machine learning techniques, metaheuristic algorithms, short-stem design, stress shielding, hip replacement

Procedia PDF Downloads 194

Authors: Benjamin Beltzung, Marie Pelé, Julien P. Renoult, Cédric Sueur

Abstract:

To this day, it is not known if drawing is specifically human behavior or if this behavior finds its origins in ancestor species. An interesting window to enlighten this question is to analyze the drawing behavior in genetically close to human species, such as non-human primate species. A good candidate for this approach is the orangutan, who shares 97% of our genes and exhibits multiple human-like behaviors. Focusing on figurative aspects may not be suitable for orangutans’ drawings, which may appear as scribbles but may have meaning. A manual feature selection would lead to an anthropocentric bias, as the features selected by humans may not match with those relevant for orangutans. In the present study, we used deep learning to analyze the drawings of a female orangutan named Molly († in 2011), who has produced 1,299 drawings in her last five years as part of a behavioral enrichment program at the Tama Zoo in Japan. We investigate multiple ways to decipher Molly’s drawings. First, we demonstrate the existence of differences between seasons by training a deep learning model to classify Molly’s drawings according to the seasons. Then, to understand and interpret these seasonal differences, we analyze how the information spreads within the network, from shallow to deep layers, where early layers encode simple local features and deep layers encode more complex and global information. More precisely, we investigate the impact of feature complexity on classification accuracy through features extraction fed to a Support Vector Machine. Last, we leverage style transfer to dissociate features associated with drawing style from those describing the representational content and analyze the relative importance of these two types of features in explaining seasonal variation. Content features were relevant for the classification, showing the presence of meaning in these non-figurative drawings and the ability of deep learning to decipher these differences. The style of the drawings was also relevant, as style features encoded enough information to have a classification better than random. The accuracy of style features was higher for deeper layers, demonstrating and highlighting the variation of style between seasons in Molly’s drawings. Through this study, we demonstrate how deep learning can help at finding meanings in non-figurative drawings and interpret these differences.

Keywords: cognition, deep learning, drawing behavior, interpretability

Procedia PDF Downloads 163

Authors: S. Toufigh Bararpour, Davood Karami, Nader Mahinpey

Abstract:

Dependence of global economics on fossil fuels has led to a large growth in the emission of greenhouse gases (GHGs). Among the various GHGs, carbon dioxide is the main contributor to the greenhouse effect due to its huge emission amount. To mitigate the threatening effect of CO₂, carbon capture and sequestration (CCS) technologies have been studied widely in recent years. For the combustion processes, three main CO₂ capture techniques have been proposed such as post-combustion, pre-combustion and oxyfuel combustion. Post-combustion is the most commonly used CO₂ capture process as it can be readily retrofit into the existing power plants. Multiple advantages have been reported for the post-combustion by solid sorbents such as high CO₂ selectivity, high adsorption capacity, and low required regeneration energy. Chemical adsorption of CO₂ over alkali-metal-based solid sorbents such as K₂CO₃ is a promising method for the selective capture of diluted CO₂ from the huge amount of nitrogen existing in the flue gas. To improve the CO₂ capture performance, K₂CO₃ is supported by a stable and porous material. Al₂O₃ has been employed commonly as the support and enhanced the cyclic CO₂ capture efficiency of K₂CO₃. Different phases of alumina can be obtained by setting the calcination temperature of boehmite at 300, 600 (γ-alumina), 950 (δ-alumina) and 1200 °C (α-alumina). By increasing the calcination temperature, the regeneration capacity of alumina increases, while the surface area reduces. However, sorbents with lower surface areas have lower CO₂ capture capacity as well (except for the sorbents prepared by hydrophilic support materials). To resolve this issue, a highly efficient alumina-aerogel support was synthesized with a BET surface area of over 2000 m²/g and then calcined at a high temperature. The synthesized alumina-aerogel was impregnated on K₂CO₃ based on 50 wt% support/K₂CO₃, which resulted in the preparation of a sorbent with remarkable CO₂ capture performance. The effect of synthesis conditions such as types of alcohols, solvent-to-co-solvent ratios, and aging times was investigated on the performance of the support. The best support was synthesized using methanol as the solvent, after five days of aging time, and at a solvent-to-co-solvent (methanol-to-toluene) ratio (v/v) of 1/5. Response surface methodology was used to investigate the effect of operating parameters such as carbonation temperature and H₂O-to-CO₂ flowrate ratio on the CO₂ capture capacity. The maximum CO₂ capture capacity, at the optimum amounts of operating parameters, was 7.2 mmol CO₂ per gram K₂CO₃. Cyclic behavior of the sorbent was examined over 20 carbonation and regenerations cycles. The alumina-aerogel-supported K₂CO₃ showed a great performance compared to unsupported K₂CO₃ and γ-alumina-supported K₂CO₃. Fundamental performance analyses and long-term thermal and chemical stability test will be performed on the sorbent in the future. The applicability of the sorbent for a bench-scale process will be evaluated, and a corresponding process model will be established. The fundamental material knowledge and respective process development will be delivered to industrial partners for the design of a pilot-scale testing unit, thereby facilitating the industrial application of alumina-aerogel.

Keywords: alumina-aerogel, CO₂ capture, K₂CO₃, optimization

Procedia PDF Downloads 115

Authors: Z. Sadeghi, M. R. Omidkhah, M. E. Masoomi

Abstract:

The purpose of this paper is to examine gas transport behavior of mixed matrix membranes (MMMs) combined with porous particles. Main existing models are categorized in two main groups; two-phase (ideal contact) and three-phase (non-ideal contact). A new coefficient, J, was obtained to express equations for estimating effect of the particle porosity in two-phase and three-phase models. Modified models evaluates with existing models and experimental data using Matlab software. Comparison of gas permeability of proposed modified models with existing models in different MMMs shows a better prediction of gas permeability in MMMs.

Keywords: mixed matrix membrane, permeation models, porous particles, porosity

Procedia PDF Downloads 382

Authors: Farhan Beg

Abstract:

This paper presents a method for the efficient implementation of a unidirectional or bidirectional DC/DC converter. The DC/DC converter is used essentially for energy exchange between the low voltage service battery and a high voltage battery commonly found in Electric Vehicle applications. In these applications, apart from cost, efficiency of design is an important characteristic. A useful way to reduce the size of electronic equipment in the electric vehicles is proposed in this paper. The technique simplifies the mechanical complexity and maximizes the energy usage using the latest converter control techniques. Moreover a bidirectional battery charger for hybrid electric vehicles is also implemented in this paper. Several simulations on the test system have been carried out in Matlab/Simulink environment. The results exemplify the robustness of the proposed design methodology in case of a 1.5 KW DC-DC converter.

Keywords: DC-DC converters, electric vehicles, power electronics, direct current control

Procedia PDF Downloads 724

Authors: Min-Feng Hsieh

Abstract:

Nowadays, we are facing a highly competitive environment in which the situation for survival has come even more critical than ever before. The challenge we will be confronted with is no longer can be dealt with the single system of knowledge. The abilities we urgently need to acquire is something that can lead us to cross over the boundaries between different disciplines and take us to a neutral ground that gathers and integrates powers and intelligence that surrounds us. This paper aims at discussing how a trans-disciplinary design course organized by the College of Design at Chaoyang University can react to this modern challenge. By orchestrating an experimental course format and by developing a series of coaching strategies, a trans-disciplinary learning environment has been created and practiced in which students selected from five different departments, including Architecture, Interior Design, Visual Design, Industrial Design, Landscape and Urban Design, are encouraged to think outside their familiar knowledge pool and to learn with/from each other. In the course of implementing this program, a parallel research has been conducted alongside by adopting the theory and principles of Action Research which is a research methodology that can provide the course organizer emergent, responsive, action-oriented, participative and critically reflective insights for the immediate changes and amendments in order to improve the effect of teaching and learning experience. In the conclusion, how the learning and teaching experience of this trans-disciplinary design studio can offer us some observation that can help us reflect upon the constraints and division caused by the subject base curriculum will be pointed out. A series of concepts for course design and teaching strategies developed and implemented in this trans-disciplinary course are to be introduced as a way to promote learners’ self-motivated, collaborative, cross-disciplinary and student-centered learning skills. The outcome of this experimental course can exemplify an alternative approach that we could adopt in pursuing a remedy for dealing with the problematic issues of the current educational practice.

Keywords: course design, coaching strategy, subject base curriculum, trans-disciplinary

Procedia PDF Downloads 202

Authors: Hsin-Jen Chen

Abstract:

Primary schooling in Taiwan is in a process of radical restructuring during the decade. At the center of these restructuring is the position of the principal and questions to do with how principals, as school leaders, respond to radical change. Adopting a case-study approach, the study chose a middle Taiwanese primary school to investigate how the principal learned to be political. Using micropolitical leadership, the principal at the researched site successfully coped with internal change and external demands. On the whole, judging from the principal’s leadership style on the mediation between parents and teachers, as well as school-based curriculum development, it could be argued that the principal was on the stance of being a leader of the cultural transformation instead of cultural reproduction. In doing so, the qualitative evidence has indicated that the principal seemed to be successful in coping with the demands of rapid change. Continuing learning for leadership is the core of working as a principal.

Keywords: micropolitics, leadership, micropolitical leadership, learning for leadership

Procedia PDF Downloads 229

Authors: Nidhal K. Azawi, John M. Gauch

Abstract:

Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

Procedia PDF Downloads 250

Authors: Hans Schumann, Colin Domnauer, Louis Rosenberg

Abstract:

In this study, machine learning techniques were deployed on real-time human swarm data to forecast the likelihood of outcomes for English Premier League matches in the 2020/21 season. These techniques included ensemble models in combination with neural networks and were tested against an industry standard of Vegas Oddsmakers. Predictions made from the collective intelligence of human swarm participants managed to achieve a positive return on investment over a full season on matches, empirically proving the usefulness of a new artificial intelligence valuing human instinct and intelligence.

Keywords: artificial intelligence, data science, English Premier League, human swarming, machine learning, sports betting, swarm intelligence

Procedia PDF Downloads 211

Authors: Marija Mihajlovic Pereira

Abstract:

Teaching and learning a musical instrument is challenging for both teachers and students. Teachers generally use diverse strategies to resolve students' particular issues in a one-to-one context. Considering individual sessions as a supportive educational context, the teacher can play a decisive role in stimulating and promoting self-regulated learning strategies, especially with beginning learners. The teachers who promote self-controlling behaviors, strategic monitoring, and regulation of actions toward goals could expect their students to practice more qualitatively and consciously. When encouraged to adopt self-regulation habits, students' could benefit from greater productivity on a longer path. Founded on Bary Zimmerman's cyclical model that comprehends three phases - forethought, performance, and self-reflection, this work aims to articulate self-regulated and music learning. Self-regulated learning appeals to the individual's attitude in planning, controlling, and reflecting on their performance. Furthermore, this study aimed to present an observation grid for perceiving teaching instructions that encourage students' controlling cognitive behaviors in light of the belief that conscious promotion of self-regulation may motivate strategic actions toward goals in musical performance. The participants, two teachers, and two students have been involved in the social inclusion project in Lisbon (Portugal). The author and one independent inter-observer analyzed six video-recorded string instrument lessons. The data correspond to three sessions per teacher lectured to one (different) student. Violin (f) and violoncello (m) teachers hold a Master's degree in music education and approximately five years of experience. In their second year of learning an instrument, students have acquired reasonable skills in musical reading, posture, and sound quality until then. The students also manifest positive learning behaviors, interest in learning a musical instrument, although their study habits are still inconsistent. According to the grid's four categories (parent codes), in-class rehearsal frames were coded using MaxQda software, version 20, according to the grid's four categories (parent codes): self-regulated learning, teaching verbalizations, teaching strategies, and students' in-class performance. As a result, selected rehearsal frames qualitatively describe teaching instructions that might promote students' body and hearing awareness, such as "close the eyes while playing" or "sing to internalize the pitch." Another analysis type, coding the short video events according to the observation grid's subcategories (child codes), made it possible to perceive the time teachers dedicate to specific verbal or non-verbal strategies. Furthermore, a coding overlay analysis indicated that teachers tend to stimulate. (i) Forethought – explain tasks, offer feedback and ensure that students identify a goal, (ii) Performance – teach study strategies and encourage students to sing and use vocal abilities to ensure inner audition, (iii) Self-reflection – frequent inquiring and encouraging the student to verbalize their perception of performance. Although developed in the context of individual string instrument lessons, this classroom observation grid brings together essential variables in a one-to-one lesson. It may find utility in a broader context of music education due to the possibility to organize, observe and evaluate teaching practices. Besides that, this study contributes to cognitive development by suggesting a practical approach to fostering self-regulated learning.

Keywords: music education, observation grid, self-regulated learning, string instruments, teaching practices

Procedia PDF Downloads 97

Authors: Vilma Zydziunaite, Vaida Jurgile, Roman Balandiuk

Abstract:

Good, great, and leading teachers are experienced and respected role models, who are innovative, organized, collaborative, trustworthy, and confident facilitators of learning. They model integrity, have strong interpersonal and communication skills, display the highest level of professionalism, a commitment to students, and expertise, and demonstrate a passion for student learning while taking the initiative as influential change agents. Usually, we call them teacher(s) leaders by integrating three notions such as good, great, and leading in a one-teacher leader. Here are described essences of three concepts: ‘good teacher,’ ‘great teacher,’ and teacher leader’ as they are inseparable in teaching practices, teacher’s professional life, and educational interactions with students, fellow teachers, school administration, students’ families and school communities.

Keywords: great teacher, good teacher, leading teacher, school, student

Procedia PDF Downloads 144

Authors: Daniel Icaza, Federico Córdova, Chiristian Castro, Fernando Icaza, Juan Portoviejo

Abstract:

In this article, the mathematical model is presented, and simulations were carried out using specialized software such as MATLAB before the construction of a 900-W wind turbine. The present study was conducted with the intention of taking advantage of the rotation of the blades of the wind generator after going through a process of amplification of speed by means of a system of gears to finally mechanically couple two electric generators of similar characteristics. This coupling allows generating a maximum voltage of 6 V in DC for each generator and putting in series the 12 V DC is achieved, which is later stored in batteries and used when the user requires it. Laboratory tests were made to verify the level of power generation produced based on the wind speed at the entrance of the blades.

Keywords: smart grids, wind turbine, modeling, renewable energy, robust control

Procedia PDF Downloads 230

Authors: Juliana Osman, David Gilbert, Caroline Tan

Abstract:

Innovation capability is recognized as a critical factor that contributes to promoting firm growth and wealth creation. While studies on innovation are in abundance, few empirical studies have been undertaken to examine the relationships of intellectual capital with innovation capability, and research investigating the combinations of strategic orientation dimensions is limited and virtually nothing in regard to the Malaysian context. This research investigates the impact of intellectual capital and three strategic orientations on the innovation capability and firm performance of Malaysian ICT SMEs. Data was collected from 213 firms relating to intellectual capital and the three strategic orientations; market orientation, learning orientation and technology orientation. Using partial least squares structural equation modelling (PLS-SEM) to analyse the data, results indicate that while market orientation has a direct negative relationship to firm performance, it is positively related to performance through the mediating effect of innovation capability. Learning orientation and technology orientation are mediated by innovation capability, while intellectual capital was found to be partially mediated by innovation capability. Findings indicate that firm performance is positively and significantly related to innovation capability and that market orientation, learning orientation, technology orientation and intellectual capital are all significant and positively related to innovation capability. The developed model indicates that Malaysian ICT SMEs would perform better with greater emphasis on developing innovation capability through enhancement of intellectual capital and the strategic orientations measured in this study.

Keywords: innovation capability, intellectual capital, strategic orientations, PLS-SEM

Procedia PDF Downloads 470

Authors: Shona Tritt, William Cunningham

Abstract:

Our study examines whether teaching effectiveness is perceived differently in online versus traditional classroom contexts. To do so, we analyzed teaching evaluations from courses that were offered as web options and as in-person classes simultaneously at the University of [removed for blinding] (N=87). Although teaching evaluations were on average lower for larger classes, we found that learning context (traditional versus online) moderated this effect. Specifically, we found a crossover effect such that in relatively smaller classes, teaching was perceived to be more effective in-person versus online, whereas, in relatively larger classes, teaching was perceived to be more effective when engaged online versus in-person.

Keywords: teaching evaluations, teaching effectiveness, e-learning, web-option

Procedia PDF Downloads 147

Authors: Pauline Calleja, Brooke Alexander

Abstract:

In 2010 the College of Emergency Nursing Australasia (CENA) undertook sole administration of the Trauma Nursing Program (TNP) across Australia. The original TNP was developed from recommendations by the Review of Trauma and Emergency Services-Victoria. While participant and faculty feedback about the program was positive, issues were identified that were common for industry training programs in Australia. These issues included didactic approaches, with many lectures and little interaction/activity for participants. Participants were not necessarily encouraged to undertake deep learning due to the teaching and learning principles underpinning the course, and thus participants described having to learn by rote, and only gain a surface understanding of principles that were not always applied to their working context. In Australia, a trauma or emergency nurse may work in variable contexts that impact on practice, especially where resources influence scope and capacity of hospitals to provide trauma care. In 2011, a program review was undertaken resulting in major changes to the curriculum, teaching, learning and assessment approaches. The aim was to improve learning including a greater emphasis on pre-program preparation for participants, the learning environment and clinically applicable contextualized outcomes participants experienced. Previously if participants wished to undertake assessment, they were given a take home examination. The assessment had poor uptake and return, and provided no rigor since assessment was not invigilated. A new assessment structure was enacted with an invigilated examination during course hours. These changes were implemented in early 2012 with great improvement in both faculty and participant satisfaction. This presentation reports on a comparison of participant evaluations collected from courses post implementation in 2012 and in 2015 to evaluate if positive changes were sustained. Methods: Descriptive statistics were applied in analyzing evaluations. Since all questions had more than 20% of cells with a count of <5, Fisher’s Exact Test was used to identify significance (p = <0.05) between groups. Results: A total of fourteen group evaluations were included in this analysis, seven CENA TNP groups from 2012 and seven from 2015 (randomly chosen). A total of 173 participant evaluations were collated (n = 81 from 2012 and 92 from 2015). All course evaluations were anonymous, and nine of the original 14 questions were applicable for this evaluation. All questions were rated by participants on a five-point Likert scale. While all items showed improvement from 2012 to 2015, significant improvement was noted in two items. These were in regard to the content being delivered in a way that met participant learning needs and satisfaction with the length and pace of the program. Evaluation of written comments supports these results. Discussion: The aim of redeveloping the CENA TNP was to improve learning and satisfaction for participants. These results demonstrate that initial improvements in 2012 were able to be maintained and in two essential areas significantly improved. Changes that increased participant engagement, support and contextualization of course materials were essential for CENA TNP evolution.

Keywords: emergency nursing education, industry training programs, teaching and learning, trauma education

Procedia PDF Downloads 266

Authors: Melissa C. Ingram

Abstract:

This literature review sought to explore the dimensions of diversity that can affect classroom learning. This review is significant as it can aid educators in reaching more of their diverse student population and creating supportive classrooms for teachers and students. For this study, peer-reviewed articles were found and compiled using Google Scholar. Key terms used in the search include student individuality, classroom equality, student development, teacher development, and teacher individuality. Relevant educational standards such as Common Core and Partnership for the 21st Century were also included as part of this review. Student and teacher individuality and equality is discussed as well as methods to grow both within educational settings. Embracing student and teacher individuality was found to be key as it may affect how each person interacts with given information. One method to grow individuality and equality in educational settings included drafting and employing revised teaching standards which include various Common Core and U.S. State standards. Another was to use educational theories such as constructivism, cognitive learning, and Experiential Learning Theory. However, barriers to growing individuality, such as not acknowledging differences in a population’s dimensions of diversity, still exist. Studies found preserving the dimensions of diversity owned by both teachers and students yielded more positive and beneficial classroom experiences.

Keywords: classroom equality, student development, student individuality, teacher development, teacher individuality

Procedia PDF Downloads 187

Authors: Mirzaii Khadigeh

Abstract:

Background and objectives: Sexual health education is an important part of health promotion services. The major role of sex education is on mothers’ shoulders. So, they have to be equipped with enough knowledge, attitude and self-efficacy for teens’ education. The present study aimed to determine the effect of team-learning and multimedia software on mothers’ knowledge, attitudes and self-efficacy in sexual health education to 12-14-year-old sons in Mashhad in 1395. Materials and methods: In this research, two experimental and one control group were employed using random sampling, which was done on 132 mothers of high school pupils. They were randomly assigned into experimental and control groups. The data were collected using demographic information and a researcher-constructed questionnaire to investigate the mothers’ knowledge, attitude, and self-efficacy and DASS21(The Depression, Anxiety and Stress Scale). They were run after confirming their reliability and validity. Intervention for the multimedia group was in the form of four CDs- each for 45 minutes- that were given to the mothers each week. At the end of the fourth week, a question-and-answer session was administered for 60 minutes. The team-learning group received intervention once a week (totally four weeks). Two weeks later, the data were collected and analyzed via Chi-square, Fisher, Kruskal-Wallis and ANOVA. Findings: Knowledge, attitude and self-efficacy of mothers in sexual health before the intervention did not have any significant differences (p >0.05). At the end of the study, the difference between the scores of the knowledge, attitude and self-efficacy in the three groups was meaningfully different (p < 0/001), but the difference between the two groups of multimedia and team-learning was not significant (p> 0.05 ). Discussion and conclusion: The result reported the efficacy of both team-leaning and multimedia software, which implies that the multimedia software training method was as effective as team-learning training one on the knowledge, attitude and self-efficacy of mothers. But, the multimedia training method is highly advised due to its availability, flexibility, and interest.

Keywords: training one on the knowledge, attitude, self-efficacy of mothers, boys

Procedia PDF Downloads 174

Authors: Salome Schulze

Abstract:

The delay of students in completing their dissertations is a worldwide problem. At the University of South Africa where this research was done, only about a third of the students complete their studies within the required period of time. This study explored the reasons why the students interrupted their studies, and why they resumed their research at a later stage. If this knowledge could be utilised to improve the throughput of doctoral students, it could have significant economic benefits for institutions of higher education while at the same time enhancing their academic prestige. To inform the investigation, attention was given to key theories concerning the learning of doctoral students, namely the situated learning theory, the social capital theory and the self-regulated learning theory, based on the social cognitive theory of learning. Ten students in the faculty of Education were purposefully selected on the grounds of their poor progress, or of having been in the system for too long. The collection of the data was in accordance with a Finnish study, since the two studies had the same aims, namely to investigate student engagement and disengagement. Graphic elicitation interviews, based on visualisations were considered appropriate to collect the data. This method could stimulate the reflection and recall of the participants’ ‘stories’ with very little input from the interviewer. The interviewees were requested to visualise, on paper, their journeys as doctoral students from the time when they first registered. They were to indicate the significant events that occurred and which facilitated their engagement or disengagement. In the interviews that followed, they were requested to elaborate on these motivating or challenging events by explaining when and why they occurred, and what prompted them to resume their studies. The interviews were tape-recorded and transcribed verbatim. Information-rich data were obtained containing visual metaphors. The data indicated that when the students suffered a period of disengagement, it was sometimes related to a lack of self-regulated learning, in particular, a lack of autonomy, and the inability to manage their time effectively. When the students felt isolated from the academic community of practice disengagement also occurred. This included poor guidance by their supervisors, which accordingly deprived them of significant social capital. The study also revealed that situational factors at home or at work were often the main reasons for the students’ procrastinating behaviour. The students, however, remained in the system. They were motivated towards a renewed engagement with their studies if they were self-regulated learners, and if they felt a connectedness with the academic community of practice because of positive relationships with their supervisors and of participation in the activities of the community (e.g., in workshops or conferences). In support of their learning, networking with significant others who were sources of information provided the students with the necessary social capital. Generally, institutions of higher education cannot address the students’ personal issues directly, but they can deal with key institutional factors in order to improve the throughput of doctoral students. It is also suggested that graphic elicitation interviews be used more often in social research that investigates the learning and development of the students.

Keywords: doctoral students, engaging and disengaging experiences, graphic elicitation interviews, student procrastination

Procedia PDF Downloads 193

Authors: Iqra Yaseen

Abstract:

One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

Procedia PDF Downloads 104

Authors: Chechen Liao, Yi-Jen Huang, Yu-Ting Lu

Abstract:

This study explores and complements digital aspects. In this study, we construct a research model based on the theory of reasoned action and extend it with the advantages and disadvantages of intangibility (convenience, perceived risk), some characteristics of digital products (price, variety, trialability), and factors related to entertainment (perceived playfulness) to predict what consumers really consider when they buy digital music. Eight hypotheses were tested and supported. Finally, we prove that the theory of reasoned action is still valid in the field of digital products.

Keywords: digital music, digital product, theory of reasoned action

Procedia PDF Downloads 440

Authors: Sarvada Nand

Abstract:

Teacher quality is directly proportional to the achievement level of students. Recent researches reveal that the teacher learning communities enhance the quality of teacher. It is a proven fact that community does help in enhancing teachers’ self-esteem as professionals, their teaching skills and enhancing classroom transaction that results in the higher achievement of students. The purpose of this study is to develop TLC and provide them platform where they share their views and ideas on various academic issues. The study examines how teachers conceptualize TLCs, up to what extent TLC help in developing professionalism among teachers and how they prepare themselves for the days to come. In this study, pre-test in five subjects, Hindi, English, Mathematics, Science and Social Studies was conducted and a questionnaire was designed to judge the teachers' attitude towards teaching practice. After completion of the project duration of three and a half-month, an exercise of post-test was conducted in all the above subjects. The post tests show tremendous improvements in achievement level of those students who were regular in their classes and were attended through this new method. A visible shift in teacher’s attitude is seen for the better. They were able to realize their own potentials. There was a group of Facilitators formed to perform continuously supervision and monitor in regular intervals so that they could easily handle the challenges, and factors much important for the attainment towards the fulfillment of the objectives.

Keywords: teacher learning communities, best practice, teacher professionalism, student achievement

Procedia PDF Downloads 217

Authors: Sandy Bao, Yankang Bao

Abstract:

The understanding of information that is being processed in the brain, especially in the lateral geniculate nucleus (LGN), has been proven challenging for modern neuroscience and for researchers with a focus on how neurons process signals and images. In this paper, we are proposing a method to image process different colors within different layers of LGN, that is, green information in layers 4 & 6 and red & blue in layers 3 & 5 based on the surface dimension of layers. We take into consideration the images in LGN and visual cortex, and that the edge detected information from the visual cortex needs to be considered in order to return back to the layers of LGN, along with the image in LGN to form the new image, which will provide an improved image that is clearer, sharper, and making it easier to identify objects in the image. Matrix Laboratory (MATLAB) simulation is performed, and results show that the clarity of the output image has significant improvement.

Keywords: lateral geniculate nucleus, matrix laboratory, neuroscience, visual cortex

Procedia PDF Downloads 277

Authors: Gaya Tridinanti

Abstract:

Enhanching English vocabulary in early childhood is the main problem often faced by teachers. Thus, the purpose of this study was to determine the enhancement of children’s English vocabulary acquisition by using digital storytelling. This type of research was an action research. It consisted of a series of four activities done in repeated cycles: planning, implementation, observation, and reflection. The subject of the study consisted of 30 students of B group (5-6 years old) attending Happy Kids Kindergarten Palembang, Indonesia. This research was conducted in three cycles. The methods used for data collection were observation and documentation. Descriptive qualitative and quantitative methods were also used to analyse the data. The research showed that the digital storytelling learning activities could enhance the children’s English vocabulary acquisition. It is based on the data in which the enhancement in pre-cycle was 37% and 51% in Cycle I. In Cycle II it was 71% and in Cycle III it was 89.3%. The results showed an enhancement of about 14% from the pre-cycle to Cycle I, 20% from Cycle I to Cycle II, and enhancement of about 18.3% from Cycle II to Cycle III. The conclusion of this study suggests that digital storytelling learning method could enhance the English vocabulary acquisition of B group children at the Happy Kids Kindergarten Palembang. Therefore, digital storytelling can be considered as an alternative to improve English language learning in the classroom.

Keywords: acquisition, enhancing, digital storytelling, English vocabulary

Procedia PDF Downloads 255

Authors: Chien-kuo Chang, Bo-wei Wu, Yi-yun Tang, Min-chiu Wu

Abstract:

This paper proposes a power equipment diagnosis system based on partial discharge (PD), which is characterized by increasing the readability of experimental data and the convenience of operation. This system integrates a variety of analysis programs of different data formats and different programming languages and then establishes a set of interfaces that can follow and expand the structure, which is also helpful for subsequent maintenance and innovation. This study shows a case of using the developed Convolutional Neural Networks (CNN) to integrate with this system, using the designed model architecture to simplify the complex training process. It is expected that the simplified training process can be used to establish an adaptive deep learning experimental structure. By selecting different test data for repeated training, the accuracy of the identification system can be enhanced. On this platform, the measurement status and partial discharge pattern of each equipment can be checked in real time, and the function of real-time identification can be set, and various training models can be used to carry out real-time partial discharge insulation defect identification and insulation state diagnosis. When the electric power equipment entering the dangerous period, replace equipment early to avoid unexpected electrical accidents.

Keywords: partial discharge, convolutional neural network, partial discharge analysis platform, adaptive deep learning

Procedia PDF Downloads 77

Authors: Ana Mouta, Ana Paulino

Abstract:

The following text presents the ik.model, a theoretical framework that guided the pedagogical implementation of meaningful educational technology-based projects in formal education worldwide. In this paper, we will focus on how this framework has enabled the development of media literacy projects for early childhood education during the last three years. The methodology that guided educators through the challenge of systematically merging analogic and digital means in dialogic high-quality opportunities of world exploration is explained throughout these lines. The effects of this methodology on early age media literacy development are considered. Also considered is the relevance of this skill in terms of post-contemporary challenges posed to learning.

Keywords: early learning, ik.model, media literacy, pedagogy

Procedia PDF Downloads 322