Search results for: learning science

Authors: B. Baran, S. N. Kaptanoglu, M. Ocal, Y. Kagnici, E. Esen, E. Siyez, D. M. Siyez

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Infertility is the fact that couples cannot have children despite 1 year of unprotected sexual life. Infertility can be considered as an important problem affecting not only sexual life but also social and psychological conditions of couples. Learning about information about preventable factors related to infertility during university years plays an important role in preventing a possible infertility case in older ages. The possibility to facilitate access to information with the internet has provided the opportunity to reach a broad audience in the diverse learning environments and educational environment. Moreover, the internet has become a basic resource for the 21st-century learners. Providing information about infertility over the internet will enable more people to reach in a short time. When studies conducted abroad about infertility are examined, interactive websites and online education programs come to the fore. In Turkey, while there is no comprehensive online education program for university students, it seems that existing studies are aimed to make more advertisements for doctors or hospitals. In this study, it was aimed to design and develop online infertility prevention education for university students. Mayer’s Multimedia Learning Theory made up the framework for the online learning environment in this study. The results of the needs analysis collected from the university students in Turkey who were selected with sampling to represent the audience for online learning contributed to the design phase. In this study, an infertility prevention online education environment designed as a 4-week education was developed by explaining the theoretical basis and needs analysis results. As a result; in the development of the online environment, different kind of visual aids that will increase teaching were used in the environment of online education according to Mayer’s principles of extraneous processing (coherence, signaling, spatial contiguity, temporal contiguity, redundancy, expectation principles), essential processing (segmenting, pre-training, modality principles) and generative processing (multimedia, personalization, voice principles). For example, the important points in reproductive systems’ expression were emphasized by visuals in order to draw learners’ attention, and the presentation of the information was also supported by the human voice. In addition, because of the limited knowledge of university students in the subject, the issue of female reproductive and male reproductive systems was taught before preventable factors related to infertility. Furthermore, 3D video and augmented reality application were developed in order to embody female and male reproductive systems. In conclusion, this study aims to develop an interactive Online Infertility Prevention Education in which university students can easily access reliable information and evaluate their own level of knowledge about the subject. It is believed that the study will also guide the researchers who want to develop online education in this area as it contains design-stage decisions of interactive online infertility prevention education for university students.

Keywords: infertility, multimedia learning theory, online education, reproductive health

Procedia PDF Downloads 155

Authors: Olga C. Rodrigue

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Long-term care and skilled nursing facilities experience ebbs and flows of nursing staffing, a problem compounded by the perception of the facilities as undesirable workplaces and competition for staff from other healthcare entities. Travel nurses are contracted to fill staffing needs due to increased admissions, increased and unexpected attrition of nurses, or facility expansion of services. Prior to beginning the contracted assignment, the travel nurse must meet industry, company, and regulatory requirements (The Joint Commission and CMS) for skills and knowledge. Travel nurses, however, inconsistently receive the pre-assignment orientation needed to work at the contracted facility, if any information is given at all. When performance expectations are not met, travel nurses may subsequently choose to leave the position without completing the terms of the contract, and some facilities may choose to terminate the contract prior to the expected end date. The overarching goal of the Doctor of Nursing Practice evidence-based practice improvement project is to provide travel nurses with the basic and necessary information to prepare them to begin a long-term and skilled nursing assignment. The project involves the identification of travel nurse learning needs through a survey and the development and provision of web-based learning modules to address those needs prior to arrival for a long-term and skilled nursing assignment.

Keywords: nurse staffing, travel nurse, travel staff, contract staff, contracted assignment, long-term care, skilled nursing, onboarding, orientation, staff development, supplemental staff

Procedia PDF Downloads 150

Authors: Fatemeh Moosavi, Tumelo Franck Nkoshwane

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Peter Drucker the renowned management guru once said, “The best way to predict the future is to create it.” Mr. Drucker is also the man who placed human capital as the most vital resource of any institution. As such any institution bent on creating a better future, requires a competent human capital, one that is able to execute with efficiency and effectiveness the objective a society aspires to. Technology today is accelerating the rate at which many societies transition to knowledge based societies. In this accelerated paradigm, it is imperative that those in leadership establish a platform capable of sustaining the planned future; intellectual capital. The capitalist economy going into the future will not just be sustained by dollars and cents, but by individuals who possess the creativity to enterprise, innovate and create wealth from ideas. This calls for cities of the future, to have this premise at the heart of their future plan, if the objective of designing sustainable and liveable future cities will be realised. The knowledge economy, now transitioning to the creative economy, requires cities of the future to be ‘gardens’ of inspiration, to be places where knowledge, creativity, and innovation can thrive as these instruments are becoming critical assets for creating wealth in the new economic system. Developing nations must accept that learning is a lifelong process that requires keeping abreast with change and should invest in teaching people how to keep learning. The need to continuously update one’s knowledge, turn these cities into vibrant societies, where new ideas create knowledge and in turn enriches the quality of life of the residents. Cities of the future must have as one of their objectives, the ability to motivate their citizens to learn, share knowledge, evaluate the knowledge and use it to create wealth for a just society. The five functional factors suggested by Kevin Lynch;-vitality, meaning/sense, adaptability, access, control, and monitoring should form the basis on which policy makers and urban designers base their plans for future cities. The authors of this paper believe that developing nations “creative economy clusters”, cities where creative industries drive the need for constant new knowledge creating sustainable learning creative cities. Obviously the form, shape and size of these districts should be cognisant of the environmental, cultural and economic characteristics of each locale. Gaborone city in the republic of Botswana is presented as the case study for this paper.

Keywords: learning city, sustainable creative city, creative industry, good city form

Procedia PDF Downloads 289

Authors: Hatice Canan Gungor, Ahmet Akdemir

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The fields of engineering and technological sciences are increasing in quality and quantity day by day all over the world. Countries have to follow, implement and adapt these developments in order to economical empowerments. In our era, it's possible to follow the rapidly developing technology and to produce new technologies by inquisitive, curious, numerical thinking individuals who can show several approaches to problem solving. In this case, countries should develop te result oriented and need-focused curriculums in university education. As in the whole world, there are more space studies in our country as well. Universities should undertake the task of supply the need for staff of this technological race. In this context, questions about the purpose, content and learning outcomes of the space sciences and space engineering departments in our country will be researched answers to reveal the characteristic of this section. In this study, it was determined in which universities the space engineering and the departments of basic sciences educate with formal education and the contents of this education, and the universities were compared with each other as of 2017. In our country three universities provide Aeronautical and Aerospace Engineering, two universities provide Space Sciences and Technologies, two universities provide Aerospace Engineering, two universities provide Aeronautics and Astronautics Engineering education. In all universities, specialized courses are taught after basic engineering education. But the question that needs to be answered is, do the lessons benefit in practice? The answer of this question will reveal the quality of the education. This paper suggests that surveys be conducted to search for the answer to this question. It's thought to be the base for the next works.

Keywords: education, space engineering, space science, quality of systems

Procedia PDF Downloads 268

Authors: Yifan Fan, Xudong Luo, Pingping Lin

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An essential task in the field of artificial intelligence is to allow computers to interact with people through natural language. Therefore, researches such as virtual assistants and dialogue systems have received widespread attention from industry and academia. The response generation plays a crucial role in dialogue systems, so to push forward the research on this topic, this paper surveys various methods for response generation. We sort out these methods into three categories. First one includes finite state machine methods, framework methods, and instance methods. The second contains full-text indexing methods, ontology methods, vast knowledge base method, and some other methods. The third covers retrieval methods and generative methods. We also discuss some hybrid methods based knowledge and deep learning. We compare their disadvantages and advantages and point out in which ways these studies can be improved further. Our discussion covers some studies published in leading conferences such as IJCAI and AAAI in recent years.

Keywords: deep learning, generative, knowledge, response generation, retrieval

Procedia PDF Downloads 121

Authors: Ozlem Kaya

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21st-century learners are energetic and tech-savvy, and the skills and the knowledge required in this century are complex and challenging. Therefore, teachers need to find new ways to appeal to the needs and interests of their students and meet the demands of the 21st century at the same time. One way to do so in English language learning has been to incorporate various technology tools into classroom practices. Although teachers think these practices are effective and their students enjoy them, students may have different perceptions. To find out what students think about the use of technology tools in terms of developing 21st-century skills and knowledge, this study was conducted at Anadolu University School of Foreign Languages. A questionnaire was administered to 40 students at elementary level. Afterward, semi-structured interviews were held with 8 students to provide deeper insight into their perceptions. The details of the findings of the study will be presented and discussed during the presentation.

Keywords: 21st century skills, technology tools, perception, English Language Learning

Procedia PDF Downloads 278

Authors: Sylvie Studente

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Despite the increase in international students migrating to the UK, the transition from home environment to a host institution abroad can be overwhelming for many students due to acculturative stressors. These stressors are reported to peak within the first six months of transitioning into study abroad which has determinantal impacts for Higher Education Institutions. These impacts include; increased drop-out rates and overall decreases in academic performance. Research suggests that belongingness can negate acculturative stressors through providing opportunities for students to form necessary social connections. In response to this universities have focussed on utilising technology to create learning communities with the most commonly deployed being social media, blogs, and discussion forums. Despite these attempts, the application of technology in supporting international students is still ambiguous. With the reported growing popularity of mobile devices among students and accelerations in learning technology owing to the COVID-19 pandemic, the potential is recognised to address this challenge via the use of chatbot technology. Whilst traditionally, chatbots were deployed as conversational agents in business domains, they have since been applied to the field of education. Within this emerging area of research, a gap exists in addressing the educational value of chatbots over and above the traditional service orientation categorisation. The proposed study seeks to extend upon current understandings by investigating the challenges faced by international students in studying abroad and exploring the potential of chatbots as a solution to assist students’ acculturation. There has been growing interest in the application of chatbot technology to education accelerated by the shift to online learning during the COVID-19 pandemic. Although interest in educational chatbots has surged, there is a lack of consistency in the research area in terms of guidance on the design to support international students in HE. This gap is widened when considering the additional challenge of supporting multicultural international students with diverse. Diversification in education is rising due to increases in migration trends for international study. As global opportunities for education increase, so does the need for multiculturally inclusive learning support.

Keywords: chatbots, education, international students, acculturation

Procedia PDF Downloads 16

Authors: Annette Cosgrove, Carina Ginty, Tony Hall, Cornelia Connolly

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The objectives of this research study is to examine the impact of professional development in Technology Enhanced Learning (TEL) and the digitization of learning in teaching communities across multiple higher education sites in the ATU (Atlantic Technological University *) ( 2020-2025), including the proposal of an evidence-based digital teaching model for use in a future pandemic. The research strategy undertaken for this study is a multi-site study using mixed methods. Qualitative & quantitative methods are being used in the study to collect data. A pilot study was carried out initially, feedback was collected and the research instrument was edited to reflect this feedback before being administered. The purpose of the staff questionnaire is to evaluate the impact of professional development in the area of TEL, and to capture the practitioner's views on the perceived impact on their teaching practice in the higher education sector across ATU (West of Ireland – 5 Higher education locations ). The phenomenon being explored is ‘ the impact of professional development in the area of technology-enhanced learning and on teaching practice in a higher education institution. The research methodology chosen for this study is an Action based Research Study. The researcher has chosen this approach as it is a prime strategy for developing educational theory and enhancing educational practice. This study includes quantitative and qualitative methods to elicit data that will quantify the impact that continuous professional development in the area of digital teaching practice and technologies has on the practitioner’s teaching practice in higher education. The research instruments/data collection tools for this study include a lecturer survey with a targeted TEL Practice group ( Pre and post covid experience) and semi-structured interviews with lecturers. This research is currently being conducted across the ATU multi-site campus and targeting Higher education lecturers that have completed formal CPD in the area of digital teaching. ATU, a West of Ireland university, is the focus of the study. The research questionnaire has been deployed, with 75 respondents to date across the ATU - the primary questionnaire and semi-formal interviews are ongoing currently – the purpose being to evaluate the impact of formal professional development in the area of TEL and its perceived impact on the practitioners teaching practice in the area of digital teaching and learning. This paper will present initial findings, reflections and data from this ongoing research study.

Keywords: TEL, technology, digital, education

Procedia PDF Downloads 63

Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

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The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

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Authors: Mayank Raj, V. G. Narendra

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Ever since the DARPA challenge on autonomous vehicles in 2005, there has been a lot of buzz about ‘Autonomous Vehicles’ amongst the major tech giants such as Google, Uber, and Tesla. Numerous approaches have been adopted to solve this problem, which can have a long-lasting impact on mankind. In this paper, we have used Deep Learning techniques and TensorFlow framework with the goal of building a neural network model to predict (speed, acceleration, steering angle, and brake) features needed for navigation of autonomous vehicles. The Deep Neural Network has been trained on images and sensor data obtained from the comma.ai dataset. A heatmap was used to check for correlation among the features, and finally, four important features were selected. This was a multivariate regression problem. The final model had five convolutional layers, followed by five dense layers. Finally, the calculated values were tested against the labeled data, where the mean squared error was used as a performance metric.

Keywords: autonomous vehicles, deep learning, computer vision, artificial intelligence

Procedia PDF Downloads 141

Authors: Doseong Eom, Jeongmin Kim, Kwang Ryel Ryu

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Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.

Keywords: building energy management, machine learning, operation planning, simulation-based optimization

Procedia PDF Downloads 306

Authors: Camille Van Eupen, Dirk Maes, Marc Herremans, Kristijn R. R. Swinnen, Ben Somers, Stijn Luca

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In ecology, species distribution models are commonly implemented to study species-environment relationships. These models increasingly rely on opportunistic citizen science data when high-quality species records collected through standardized recording protocols are unavailable. While these opportunistic data are abundant, uncertainty is usually high, e.g., due to observer effects or a lack of metadata. Data quality filtering is often used to reduce these types of uncertainty in an attempt to increase the value of studies relying on opportunistic data. However, filtering should not be performed blindly. In this study, recommendations are built for data quality filtering of opportunistic species occurrence data that are used as input for species distribution models. Using an extensive database of 5.7 million citizen science records from 255 species in Flanders, the impact on model performance was quantified by applying three data quality filters, and these results were linked to species traits. More specifically, presence records were filtered based on record attributes that provide information on the observation process or post-entry data validation, and changes in the area under the receiver operating characteristic (AUC), sensitivity, and specificity were analyzed using the Maxent algorithm with and without filtering. Controlling for sample size enabled us to study the combined impact of data quality filtering, i.e., the simultaneous impact of an increase in data quality and a decrease in sample size. Further, the variation among species in their response to data quality filtering was explored by clustering species based on four traits often related to data quality: commonness, popularity, difficulty, and body size. Findings show that model performance is affected by i) the quality of the filtered data, ii) the proportional reduction in sample size caused by filtering and the remaining absolute sample size, and iii) a species ‘quality profile’, resulting from a species classification based on the four traits related to data quality. The findings resulted in recommendations on when and how to filter volunteer generated and opportunistically collected data. This study confirms that correctly processed citizen science data can make a valuable contribution to ecological research and species conservation.

Keywords: citizen science, data quality filtering, species distribution models, trait profiles

Procedia PDF Downloads 182

Authors: Keyvanl Yahya

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This paper aims to find a algorithmic structure that affords to predict and explain economic choice behaviour particularly under uncertainty (random policies) by manipulating the prevalent Actor-Critic learning method that complies with the requirements we have been entrusted ever since the field of neuroeconomics dawned on us. Whilst skimming some basics of neuroeconomics that might be relevant to our discussion, we will try to outline some of the important works which have so far been done to simulate choice making processes. Concerning neurological findings that suggest the existence of two specific functions that are executed through Basal Ganglia all the way down to sub-cortical areas, namely 'rewards' and 'beliefs', we will offer a modified version of actor/critic algorithm to shed a light on the relation between these functions and most importantly resolve what is referred to as a challenge for actor-critic algorithms, that is lack of inheritance or hierarchy which avoids the system being evolved in continuous time tasks whence the convergence might not emerge.

Keywords: neuroeconomics, choice behaviour, decision making, reinforcement learning, actor-critic algorithm

Procedia PDF Downloads 388

Authors: Teresa B. King

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In the millennial age, with more students desiring a fashion major yet fewer having sewing and manufacturing knowledge, this increases demand on academicians to adequately educate. While fashion museums have a prominent place for historical preservation, the need for apparel education via working collections of handmade or mass manufactured apparel is lacking in most universities in the United States, especially in the Southern region. Created in 1988, Middle Tennessee State University’s historic clothing collection provides opportunities to study apparel construction methods throughout history, to compare and apply to today’s construction and manufacturing methods, as well as to learn the cyclical nature/importance of historic styles on current and upcoming fashion. In 2019, a class exercise experiment was implemented for which students researched their family genealogy using Ancestry.com, identified the oldest visual media (photographs, etc.) available, and analyzed the garment represented in said media. The student then located a comparable garment in the historic collection and evaluated the construction methods of the ancestor’s time period. A class 'fashion' genealogy tree was created and mounted for public viewing/education. Results of this exercise indicated that student learning increased due to the 'personal/familial connection' as it triggered more interest in historical garments as related to the student’s own personal culture. Students better identified garments regarding the historical time period, fiber content, fabric, and construction methods utilized, thus increasing learning and retention. Students also developed increased learning and recognition of custom construction methods versus current mass manufacturing techniques, which impact today’s fashion industry. A longitudinal effort will continue with the growth of the historic collection and as students continue to utilize the historic clothing collection.

Keywords: ancestry, clothing history, fashion history, genealogy, historic fashion museum collection

Procedia PDF Downloads 120

Authors: Triyanto

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Radicalism poses a real threat to Indonesia's future. The target of radicalism is the youth of Indonesia. This is proven by the majority of terrorists are young people. Radicalization is not only a repressive act but also requires educational action. One of the educational efforts is civic education. This study discusses the prevention of radicalism for students through civic education and its constraints. This is qualitative research. Data were collected through literature studies, observations and in-depth interviews. Data were validated by triangulation. The sample of this research is 30 high school students in Surakarta. Data were analyzed by the interactive model of analysis from Miles & Huberman. The results show that (1) civic education can be a way of preventing student radicalism in schools in the form of cultivating the values of education through learning in the classroom and outside the classroom; (2) The obstacles encountered include the lack of learning facilities, the limited ability of teachers and the low attention of students to the civic education.

Keywords: prevention, radicalism, senior high school student, civic education

Procedia PDF Downloads 215

Authors: Wilma Coetzee

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Statistics lecturers experience that many students who are taking a service course in statistics do not like statistics. Students in these courses tend to struggle and do not perform well. This research takes a look at the student’s perspective, with the aim to determine how to change the teaching of statistics so that students will enjoy it more and perform better. Questionnaires were used to determine the perspectives of first year service statistics students at a South African university. Factors addressed included motivation to study, attitude toward statistics, statistical anxiety, mathematical abilities and tendency to procrastinate. Logistic regression was used to determine what contributes to students performing badly in statistics. The results show that the factors that contribute the most to students performing badly are: statistical anxiety, not being motivated and having had mathematical literacy instead of mathematics in secondary school. Two open ended questions were included in the questionnaire: 'I will enjoy statistics more if…' and 'I will perform better in statistics if…'. The answers to these questions were analyzed using qualitative methods. Frequent themes were identified for each of the questions. A simulation study incorporating bootstrapping was done to determine the saturation of the themes. The majority of the students indicated that they would perform better in statistics if they studied more, managed their time better, had a flare for mathematics and if the lecturer was able to explain difficult concepts better. They also want more active learning. To ensure that students enjoy statistics more, they want an active learning experience. They want fun activities, more interaction with the lecturer and with one another, more computer based problems, and more challenges. They want a better understanding of the subject, want to understand the relevance of statistics to their future career and want excellent lecturers. These findings can be used to direct the improvement of the tuition of statistics.

Keywords: active learning, performance in statistics, statistical anxiety, statistics education

Procedia PDF Downloads 135

Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

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Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

Procedia PDF Downloads 116

Authors: Shieh Shiow-Fang

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Superstitious thoughts or actions often occur during athletic competitions. Often "superstitious rituals" have a positive impact on the performance of competitive athletes. Athletes affirm the many psychological benefits of religious beliefs mostly in a positive way. Method: By snowball sampling, we recruited 10 experienced competitive athletes as participants. We used in-person and online one-to-one in-depth interviews to collect their experiences about sports superstition. The total interview time was 795 minutes. We analyzed the raw data with the grounded theory processes suggested by Strauss and Corbin (1990). Results: The factors affecting athlete performance are ritual beliefs, taboo awareness, learning norms, and spontaneous attribution behaviors. Conclusion: We concluded that sports superstition reflects several psychological implications. The analysis results of this paper can provide another research perspective for the future study of sports superstition behavior.

Keywords: superstition, taboo awarences, competitive athlete, learning norms

Procedia PDF Downloads 65

Authors: Chevon Fernando, Banuka Athuraliya

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The purpose of this research is to provide a solution to the students’ time management, which usually becomes an issue because students must study and manage their personal commitments. "TimeTune," an AI-based study planner that provides an opportunity to maneuver study timeframes by incorporating modern machine learning algorithms with calendar applications, is unveiled as the ideal solution. The research is focused on the development of LSTM models that connect to the Google Calendar API in the process of developing learning paths that would be fit for a unique student's daily life experience and study history. A key finding of this research is the success in building the LSTM model to predict optimal study times, which, integrating with the real-time data of Google Calendar, will generate the timetables automatically in a personalized and customized manner. The methodology encompasses Agile development practices and Object-Oriented Analysis and Design (OOAD) principles, focusing on user-centric design and iterative development. By adopting this method, students can significantly reduce the tension associated with poor study habits and time management. In conclusion, "TimeTune" displays an advanced step in personalized education technology. The fact that its application of ML algorithms and calendar integration is quite innovative is slowly and steadily revolutionizing the lives of students. The excellence of maintaining a balanced academic and personal life is stress reduction, which the applications promise to provide for students when it comes to managing their studies.

Keywords: personalized learning, study planner, time management, calendar integration

Procedia PDF Downloads 27

Authors: Friman Hen, Banner Ifaa, Shalom-Tuchin Bosmat, Einav Yulia

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The action learning course is an academic course which involves academic learning and social activities. The courses deal with processes and social challenges, reveal different ideologies, and develop critical thinking and pragmatic ideas. Students receive course credits and a grade for being part of such courses. Participating students enroll in courses that involve action and activities to engage in the experiential learning process, thereby creating a dialogue and cross-fertilization between being taught in the classroom and experiencing the reality in the real world. A learning experience includes meeting with social organizations, institutions, and state authorities and carrying out practical work with diverse populations. Through experience, students strengthen their academic skills, formulate ethical attitudes toward reality, develop professional and civilian perspectives, and realize how they can influence their surrounding in the present and the hereafter. Under the guidance and supervision of Dr. Hen Friman, H.I.T. has built an innovative course that combines action and activities to increase the awareness and accessibility of the community in an experiential way. The end goal is to create Green Ambassadors—children with a high level of environmental awareness. This course is divided into two parts. The first part, focused on frontal teaching, delivers knowledge from extensive environmental fields to students. These areas include introduction to ecology, the process of electricity generation, air pollution, renewable energy, water economy, waste and recycling, and energy efficiency (first stage). In addition to the professional content in the environment field, students learn the method of effective and experiential teaching to younger learners (4 to 8 years old). With the attainment of knowledge, students are divided into operating groups. The second part of the course shows how the theory becomes practical and concrete. At this stage, students are asked to introduce to the first- and second-graders of ‘Revivim’ School in Holon a lesson of 90 minutes focused on presenting the issues and their importance during the course (second stage). This course is the beginning of a paradigm shift regarding energy usage in the modern society in Israel. The objective of the course is to expand worldwide and train the first and second-graders, and even pre-schoolers, in a wide scope to increase population awareness rate, both in Israel and all over the world, for a green future.

Keywords: air pollution, green ambassador, recycling, renewable energy

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Authors: Aarti Muley

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An ancient Vedic philosophy defines the three basic gods i.e Bramha, Vishnu and Shiva. Bramha is known as a supreme god and responsible for creating a universe. Vedic scriptures have not given the direct description of Lord Bramha but with the name Hiranyagarbha Rig Veda describes Bramha. Vedas, Bhagwat Gita, Mahabharata describes Bramha and modern science has found that many theories and principle is directly related with the life of Lord Bramha but there is no direct explanation and evidence regarding a planet Bramhaloka or also called as Satyaloka. Neither the ancient scriptures nor the Indian astrology which is based on the motion of the planet have given any evidence to the planet Bramhaloka directly. In this paper, the efforts have been made to study who is god Bramha and the planet Bramhaloka from Vedic scriptures and using the theories of modern science it has been found that it has strong resemblance with the star Sun. To the best of author’s knowledge, this is the first report which gives the explanation that the lord Bramha’s planet Bramhaloka and the Sun is one and the same.

Keywords: God Bramha, ancient scriptures, cosmic theory, scientific explanation

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Authors: Kamel Belammi, Houria Fatrim

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imbalanced data set, a problem often found in real world application, can cause seriously negative effect on classification performance of machine learning algorithms. There have been many attempts at dealing with classification of imbalanced data sets. In medical diagnosis classification, we often face the imbalanced number of data samples between the classes in which there are not enough samples in rare classes. In this paper, we proposed a learning method based on a cost sensitive extension of Least Mean Square (LMS) algorithm that penalizes errors of different samples with different weight and some rules of thumb to determine those weights. After the balancing phase, we applythe different classifiers (support vector machine (SVM), k- nearest neighbor (KNN) and multilayer neuronal networks (MNN)) for balanced data set. We have also compared the obtained results before and after balancing method.

Keywords: multilayer neural networks, k- nearest neighbor, support vector machine, imbalanced medical data, least mean square algorithm, diabetes

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Authors: Abigaile Rose Mary R. Capay, Janne Ly Castillon-Gilpo, Sheila A. Javier

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The transition to online learning has been a challenging feat on the mental health of tertiary students. This study investigated whether learning mindfulness strategies online would help in improving students’ imagination, conscientiousness, extraversion, agreeableness and emotional stability, as measured by the International Personality Item Pool (IPIP) Big Five Factor Markers, as well as their dispositional mindfulness as measured by the Mindfulness Attention Awareness Scale (MAAS). Fifty-two college students participated in the experiment. The 23 participants assigned to the treatment condition received 6-weekly experiential sessions of online mindfulness training and were advised to follow a daily mindfulness practice, while the 29 participants from the control group only received a 1-hour lecture. Scores were collected at pretest and posttest. Findings show that there was a significant difference in the pretest and posttest scores of students assigned in the treatment group, likewise medium effect sizes in the variables: dispositional mindfulness (t (22) = 2.64, p = 0.015, d = .550), extraversion (t (22) = 2.76, p = 0.011, d = 0.575), emotional stability (t (22) = 2.99, p = 0.007, d = .624), conscientiousness (t (22) = 2.74, p = 0.012, d = .572) and imagination (t (22) = 4.08, p < .001), but not for agreeableness (t (22) = 2.01, p = 0.057, d = .419). No significant differences were observed on the scores of the control group. Educational institutions are recommended to consider teaching basic mindfulness strategies to tertiary students, as a valuable resource in improving their mental health as they navigate through adjustments in online learning.

Keywords: mindfulness, school-based interventions, MAAS, IPIP Big Five Markers, experiment

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Authors: Hisham Md.Suhadi, Faaizah Shahbodin, Jamaluddin Hashim, Nurul Huda Mahsudi, Mahathir Mohd Sarjan

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The study is the way to identify the problems that occur in organizing short courses lifelong learning in the information and communication technology (ICT) education which are faced by the lecturer and staff at the Mara Skill Institute and Industrial Training Institute in Pahang, Malaysia. The important aspects of these issues are classified to five which are selecting the courses administrative. Fifty lecturers and staff were selected as a respondent. The sample is selected by using the non-random sampling method purpose sampling. The questionnaire is used as a research instrument and divided into five main parts. All the data that gain from the questionnaire are analyzed by using the SPSS in term of mean, standard deviation and percentage. The findings showed that there are the problems occur in organizing the short course for lifelong learning in ICT education.

Keywords: lifelong Education, information and communication technology, short course, ICT education, courses administrative

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Authors: Adamu Abdullahi, On Francisca, Saidu Isah Rambo, G. N. Obunadike, D. T. Chinyio

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The paper discusses the potential threat of Denial of Service (DoS) attacks in the Internet of Things (IoT) networks on constrained application protocols (CoAP). As billions of IoT devices are expected to be connected to the internet in the coming years, the security of these devices is vulnerable to attacks, disrupting their functioning. This research aims to tackle this issue by applying mixed methods of qualitative and quantitative for feature selection, extraction, and cluster algorithms to detect DoS attacks in the Constrained Application Protocol (CoAP) using the Machine Learning Algorithm (MLA). The main objective of the research is to enhance the security scheme for CoAP in the IoT environment by analyzing the nature of DoS attacks and identifying a new set of features for detecting them in the IoT network environment. The aim is to demonstrate the effectiveness of the MLA in detecting DoS attacks and compare it with conventional intrusion detection systems for securing the CoAP in the IoT environment. Findings: The research identifies the appropriate node to detect DoS attacks in the IoT network environment and demonstrates how to detect the attacks through the MLA. The accuracy detection in both classification and network simulation environments shows that the k-means algorithm scored the highest percentage in the training and testing of the evaluation. The network simulation platform also achieved the highest percentage of 99.93% in overall accuracy. This work reviews conventional intrusion detection systems for securing the CoAP in the IoT environment. The DoS security issues associated with the CoAP are discussed.

Keywords: algorithm, CoAP, DoS, IoT, machine learning

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Authors: Abubakar Attahiru

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Mathematics plays an important role in the real situation. The development of the study of mathematics is a result of the needs of man to survive and interact with one another in society. Mathematics is the universal language that is applied in almost every aspect of life. Mathematics gives us a way to understand patterns, define relationships, and predict the future. The changes in the content and methods of studying mathematics follow the trends in societal needs and developments. Also, the developments in mathematics affect the developments in society. Generally, education helps to develop society while the activities and needs of the society dictate e educational policy of any society. Among all the academic subjects studied at school, mathematics has distinctly contributed more to the objectives of general education of man than any other subject. This is a result of the applications of mathematics to all spheres of human endeavors’. This paper looks at the meaning of the basic concepts of mathematics, science, and technology, the application of mathematics in a real-life situation, and their relationships with society. The paper also shows how mathematics, science, and technology affect the existence and development of society and how society determines the nature of mathematics studied in society through its educational system.

Keywords: application, mathematics, real life, situation

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Authors: Kim Norgaard Helmersen, Jan Silberberger

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Questions of style and reproducibility in relation to architectural design are not only continuously debated; the very concepts can seem quite provocative to architects, who like to think of architectural design as depending on intuition, ideas, and individual personalities. This standpoint - dominant in architectural discourse - is challenged in the present paper presenting early findings from a comparative STS-inspired research study of architectural design teaching and research at different architecture schools in varying national contexts. In philosophy of science framework, the paper reflects empirical observations of design teaching at the Royal Academy of Fine Arts in Copenhagen and presents a tentative theoretical framework for the on-going research project. The framework suggests that architecture – as a field of knowledge production – is mainly dominated by three epistemological positions, which will be presented and discussed. Besides serving as a loosely structured framework for future data analysis, the proposed framework brings forth the argument that architecture can be roughly divided into different schools of thought, like the traditional science disciplines. Without reducing the complexity of the discipline, describing its main intellectual positions should prove fruitful for the future development of architecture as a theoretical discipline, moving an architectural critique beyond discussions of taste preferences. Unlike traditional science disciplines, there is a lack of a community-wide, shared pool of codified references in architecture, with architects instead referencing art projects, buildings, and famous architects, when positioning their standpoints. While these inscriptions work as an architectural reference system, to be compared to codified theories in academic writing of traditional research, they are not used systematically in the same way. As a result, architectural critique is often reduced to discussions of taste and subjectivity rather than epistemological positioning. Architects are often criticized as judges of taste and accused that their rationality is rooted in cultural-relative aesthetical concepts of taste closely linked to questions of style, but arguably their supposedly subjective reasoning, in fact, forms part of larger systems of thought. Putting architectural ‘styles’ under a loop, and tracing their philosophical roots, can potentially open up a black box in architectural theory. Besides ascertaining and recognizing the existence of specific ‘styles’ and thereby schools of thought in current architectural discourse, the study could potentially also point at some mutations of the conventional – something actually ‘new’ – of potentially high value for architectural design education.

Keywords: architectural theory, design research, science and technology studies (STS), sociology of architecture

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Authors: Mary H Moen, Lauren H. Mandel

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Creating a sense of community in online learning is important for student engagement and success. The integration of discussion forums within online learning environments presents an opportunity to explore how this computer mediated communications format can cultivate a sense of community among students in accelerated master’s degree programs. This research has two aims, to delve into the ways instructors utilize this communications technology to create community and to understand the feelings and experiences of graduate students participating in these forums in regard to its effectiveness in community building. This study is a two-phase approach encompassing qualitative and quantitative methodologies. The data will be collected at an online accelerated Master of Library and Information Studies program at a public university in the northeast of the United States. Phase 1 is a content analysis of the syllabi from all courses taught in the 2023 calendar year, which explores the format and rules governing discussion forum assignments. Four to six individual interviews of department faculty and part time faculty will also be conducted to illuminate their perceptions of the successes and challenges of their discussion forum activities. Phase 2 will be an online survey administered to students in the program during the 2023 calendar year. Quantitative data will be collected for statistical analysis, and short answer responses will be analyzed for themes. The survey is adapted from the Classroom Community Scale Short-Form (CSS-SF), which measures students' self-reported responses on their feelings of connectedness and learning. The prompts will contextualize the items from their experience in discussion forums during the program. Short answer responses on the challenges and successes of using discussion forums will be analyzed to gauge student perceptions and experiences using this type of communication technology in education. This research study is in progress. The authors anticipate that the findings will provide a comprehensive understanding of the varied approaches instructors use in discussion forums for community-building purposes in an accelerated MLIS program. They predict that the more varied, flexible, and consistent student uses of discussion forums are, the greater the sense of community students will report. Additionally, students’ and instructors’ perceptions and experiences within these forums will shed light on the successes and challenges faced, thereby offering valuable recommendations for enhancing online learning environments. The findings are significant because they can contribute actionable insights for instructors, educational institutions, and curriculum designers aiming to optimize the use of discussion forums in online accelerated graduate programs, ultimately fostering a richer and more engaging learning experience for students.

Keywords: accelerated online learning, discussion forums, LIS programs, sense of community, g

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Authors: Haneen Alrawashdeh, Naciye Kunt

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Intercultural communicative competence or (ICC), is an extension of communicative competence that takes into account the intercultural aspect of learning a foreign language. Accordingly, this study aimed at investigating the intercultural interaction impact on English as a foreign language learners' academic achievement of language as a scholastic subject and their motivation towards learning it. To achieve the aim of the study, a qualitative research approach was implemented by means of semi-structured interviews. Interview sessions were conducted with eight teachers of English as well as ten English language learners who work in the tourism industry in a variety of career paths, such as selling antiques and traditional costumes. An analysis of learners' grades of English subjects from 2014 to 2019 academic years was performed by using the Open Education Management Information System Database in Jordan to support the findings of the study. The results illustrated that due to the fact that they work in the tourism sector, students gain skills and knowledge that assist them in better academic achievement in the subject of English by practicing intercultural communication with different nationalities on a daily basis; intercultural communication enhances students speaking skills, lexicon, and fluency; however, despite that their grades showed increasing, from teachers perspectives, intercultural communicative competence reduces their linguistic accuracy and ability to perform English academic writing in academic contexts such as exams.

Keywords: intercultural communicative competence, Jordan, language learning motivation, language academic achievement

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Authors: Albert Acheampong, Tamer Elshandidy

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We investigate the extent to which sustainability disclosure from the narrative section of European banks’ annual reports improves analyst forecast accuracy. We capture sustainability disclosure using a machine learning approach and use forecast error to proxy analyst forecast accuracy. Our results suggest that sustainability disclosure significantly improves analyst forecast accuracy by reducing the forecast error. In a further analysis, we also find that the induction of Directive 2014/95/European Union (EU) is associated with increased disclosure content, which then reduces forecast error. Collectively, our results suggest that sustainability disclosure improves forecast accuracy, and the induction of the new EU directive strengthens this improvement. These results hold after several further and robustness analyses. Our findings have implications for market participants and policymakers.

Keywords: sustainability disclosure, machine learning, analyst forecast accuracy, forecast error, European banks, EU directive

Procedia PDF Downloads 52