Search results for: learning strategy

Authors: Burçe Boyraz

Abstract:

This study examines appearances of brand placement as an alternative communication strategy in television series by focusing on Yalan Dünya which is one of the most popular television series in Turkey. Consequently, this study has a descriptive research design and quantitative content analysis method is used in order to analyze frequency and time data of brand placement appearances in first 3 seasons of Yalan Dünya with 16 episodes. Analysis of brand placement practices in Yalan Dünya is dealt in three categories: episode-based analysis, season-based analysis and comparative analysis. At the end, brand placement practices in Yalan Dünya are evaluated in terms of type, form, duration and legal arrangements. As a result of this study, it is seen that brand placement plays a determinant role in Yalan Dünya content. Also, current legal arrangements make brand placement closer to other traditional communication strategies instead of differing brand placement from them distinctly.

Keywords: advertising, alternative communication strategy, brand placement, Yalan Dünya

Procedia PDF Downloads 232

Authors: Xiao-Yan Li, Takashi Hashimoto, Guanhong Li, Shuo Yang

Abstract:

In Japanese, onomatopoeia is an important element in the lively expression of feelings and experiences. It is very difficult for students of Japanese to acquire onomatopoeia, especially, its nuances. In this paper, based on traditional L2 learning theories, we propose a new method to improve the efficiency of teaching the nuances – both explicit and tacit - to non-native speakers of Japanese. The method for teaching the tacit nuances of onomatopoeia consists of three elements. First is to teach the formal rules representing the explicit nuances of onomatopoeic words. Second is to have the students create new onomatopoeic words by utilizing those formal rules. The last element is to provide feedback by evaluating the onomatopoeias created. Our previous study used five-grade relative estimation. However students were confused about the five-grade system, because they could not understand the evaluation criteria only based on a figure. In this new system, then, we built an evaluation database through native speakers’ narrative interpretation. We asked Japanese native speakers to describe their awareness of the nuances of onomatopoeia in writing. Then they voted on site and defined priorities for showing to learners on the system. To verify the effectiveness of the proposed method and the learning system, we conducted a preliminary experiment involving two groups of subjects. While Group A got feedback about the appropriateness of their onomatopoeic constructions from the native speakers’ narrative interpretation, Group B got feedback just in the form of the five-grade relative estimation. A questionnaire survey administered to all of the learners clarified our learning system availability and also identified areas that should be improved. Repetitive learning of word-formation rules, creating new onomatopoeias and gaining new awareness from narrative interpretation is the total process used to teach the explicit and tacit nuances of onomatopoeia.

Keywords: onomatopoeia, tacit nuance, narrative interpretation, e-learning system, second language teaching

Procedia PDF Downloads 386

Authors: Hui-Yi Wang, Shu-Mei Chen, Mei-Fang Liu

Abstract:

Background and purpose: Providing clinical experience in medical education is an important discipline method where students can gradually apply their academic knowledge to clinical situations. The purpose of this study was to establish self-assessment questionnaires for students to assess their learning outcomes for two fields of physical therapy, orthopedic physical therapy, and pediatric physical therapy, in a clinical fieldwork course. Methods: The questionnaires were developed based on the core competence dimensions of the course. The content validity of the questionnaires was evaluated and established by expert meetings. Among the third-year undergraduate students who took the clinical fieldwork course, there were 49 students participated in this study. Teachers arranged for the students to study two professional fields, and each professional field conducted a three-week clinical lesson. The students filled out the self-assessment questionnaires before and after each three-week lesson. Results: The self-assessment questionnaires were established by expert meetings that there were six core competency dimensions in each of the two fields, with 20 and 21 item-questions, respectively. After each three-week clinical fieldwork, the self-rating scores in each core competency dimension were higher when compared to those before the course, indicating having better clinical abilities after the lessons. The best self-rating scores were the dimension of attitude and humanistic literacy, and the two lower scores were the dimensions of professional knowledge and skills and problem-solving critical thinking. Conclusions: This study developed questionnaires for clinical fieldwork courses to reflect students' learning outcomes, including the performance of professional knowledge, practice skills, and professional attitudes. The use of self-assessment of learning performance can help students build up their reflective competencies. Teachers can guide students to pay attention to the performance of abilities in each core dimension to enhance the effectiveness of learning through self-reflection and improvement.

Keywords: physical therapy, clinical fieldwork course, learning outcomes assessment, medical education, self-reflection ability

Procedia PDF Downloads 104

Authors: Libor Zachoval, Daire O Broin, Oisin Cawley

Abstract:

E-learning platforms, such as Blackboard have two major shortcomings: limited data capture as a result of the limitations of SCORM (Shareable Content Object Reference Model), and lack of incorporation of Artificial Intelligence (AI) and machine learning algorithms which could lead to better course adaptations. With the recent development of Experience Application Programming Interface (xAPI), a large amount of additional types of data can be captured and that opens a window of possibilities from which online education can benefit. In a corporate setting, where companies invest billions on the learning and development of their employees, some learner behaviours can be troublesome for they can hinder the knowledge development of a learner. Behaviours that hinder the knowledge development also raise ambiguity about learner’s knowledge mastery, specifically those related to gaming the system. Furthermore, a company receives little benefit from their investment if employees are passing courses without possessing the required knowledge and potential compliance risks may arise. Using xAPI and rules derived from a state-of-the-art review, we identified three learner behaviours, primarily related to guessing, in a corporate compliance course. The identified behaviours are: trying each option for a question, specifically for multiple-choice questions; selecting a single option for all the questions on the test; and continuously repeating tests upon failing as opposed to going over the learning material. These behaviours were detected on learners who repeated the test at least 4 times before passing the course. These findings suggest that gauging the mastery of a learner from multiple-choice questions test scores alone is a naive approach. Thus, next steps will consider the incorporation of additional data points, knowledge estimation models to model knowledge mastery of a learner more accurately, and analysis of the data for correlations between knowledge development and identified learner behaviours. Additional work could explore how learner behaviours could be utilised to make changes to a course. For example, course content may require modifications (certain sections of learning material may be shown to not be helpful to many learners to master the learning outcomes aimed at) or course design (such as the type and duration of feedback).

Keywords: artificial intelligence, corporate e-learning environment, knowledge maintenance, xAPI

Procedia PDF Downloads 109

Authors: Jamshaid ul Rahman, Akhter Ali, Adnan Manzoor

Abstract:

Learning-based systems have received increasing interest in recent years; recognition structures, including end-to-end speak recognition, are one of the hot topics in this area. A famous work on end-to-end speaker verification by using Angular Softmax Loss gained significant importance and is considered useful to directly trains a discriminative model instead of the traditional adopted i-vector approach. The margin-based strategy in angular softmax is beneficial to learn discriminative speaker embeddings where the random selection of margin values is a big issue in additive angular margin and multiplicative angular margin. As a better solution in this matter, we present an alternative approach by introducing a bit similar form of an additive parameter that was originally introduced for face recognition, and it has a capacity to adjust automatically with the corresponding margin values and is applicable to learn more discriminative features than the Softmax. Experiments are conducted on the part of Fisher dataset, where it observed that the additive parameter with angular softmax to train the front-end and probabilistic linear discriminant analysis (PLDA) in the back-end boosts the performance of the structure.

Keywords: additive parameter, angular softmax, speaker verification, PLDA

Procedia PDF Downloads 84

Authors: Dinda N. Lestari

Abstract:

Sundanese language is one of heritage language in Indonesia that must be maintained especially the formal type of it because teenagers nowadays do not speak Sundanese language formally in their daily lives. To maintain it, Cultural and Education Ministry of Indonesia has input Sundanese language lesson at senior high school in West Java area. The aim of this study was to observe whether the existence of Sundanese language lesson in senior high school in the big town of Karawang, West Java - Indonesia give the contribution to the formal type of Sundanese language maintenance or not. For gathering the data, the researcher interviewed the senior high school students who have learned Sundanese language to observe their acquisition of it. As a result of the interview, the data was presented in qualitative research by using the interviewing method. Then, the finding indicated that the existence of Sundanese language in Senior High School also the educational program which is related to it, for instance, Kemis Nyunda seemed to do not effective enough in maintaining the formal type of Sundanese language. Therefore, West Java government must revise the learning strategy of it, including the role of the Sundanese language teacher.

Keywords: heritage language, language maintenance and shift, senior high school, Sundanese language, Sundanese language lesson

Procedia PDF Downloads 141

Authors: Shamie Kumar

Abstract:

Background: Radiologists and radiographers (RR) need to educate themselves and their colleagues to ensure that AI is integrated safely, useful, and in a meaningful way with the direction it always benefits the patients. AI education and training are fundamental to the way RR work and interact with it, such that they feel confident using it as part of their clinical practice in a way they understand it. Methodology: This exploratory research will outline the current educational and training gaps for radiographers and radiologists in AI radiology diagnostics. It will review the status, skills, challenges of educating and teaching. Understanding the use of artificial intelligence within daily clinical practice, why it is fundamental, and justification on why learning about AI is essential for wider adoption. Results: The current knowledge among RR is very sparse, country dependent, and with radiologists being the majority of the end-users for AI, their targeted training and learning AI opportunities surpass the ones available to radiographers. There are many papers that suggest there is a lack of knowledge, understanding, and training of AI in radiology amongst RR, and because of this, they are unable to comprehend exactly how AI works, integrates, benefits of using it, and its limitations. There is an indication they wish to receive specific training; however, both professions need to actively engage in learning about it and develop the skills that enable them to effectively use it. There is expected variability amongst the profession on their degree of commitment to AI as most don’t understand its value; this only adds to the need to train and educate RR. Currently, there is little AI teaching in either undergraduate or postgraduate study programs, and it is not readily available. In addition to this, there are other training programs, courses, workshops, and seminars available; most of these are short and one session rather than a continuation of learning which cover a basic understanding of AI and peripheral topics such as ethics, legal, and potential of AI. There appears to be an obvious gap between the content of what the training program offers and what the RR needs and wants to learn. Due to this, there is a risk of ineffective learning outcomes and attendees feeling a lack of clarity and depth of understanding of the practicality of using AI in a clinical environment. Conclusion: Education, training, and courses need to have defined learning outcomes with relevant concepts, ensuring theory and practice are taught as a continuation of the learning process based on use cases specific to a clinical working environment. Undergraduate and postgraduate courses should be developed robustly, ensuring the delivery of it is with expertise within that field; in addition, training and other programs should be delivered as a way of continued professional development and aligned with accredited institutions for a degree of quality assurance.

Keywords: artificial intelligence, training, radiology, education, learning

Procedia PDF Downloads 76

Authors: Md. Aminul Islam, Adel Merabet, Rachid Beguenane, Hussein Ibrahim

Abstract:

This paper presents a simulation and mathematical model of stand-alone solar-wind-diesel based hybrid energy system (HES). A power management system is designed for multiple energy resources in a stand-alone hybrid energy system. Both Solar photovoltaic and wind energy conversion system consists of maximum power point tracking (MPPT), voltage regulation, and basic power electronic interfaces. An additional diesel generator is included to support and improve the reliability of stand-alone system when renewable energy sources are not available. A power management strategy is introduced to distribute the generated power among resistive load banks. The frequency regulation is developed with conventional phase locked loop (PLL) system. The power management algorithm was applied in Matlab®/Simulink® to simulate the results.

Keywords: solar photovoltaic, wind energy, diesel engine, hybrid energy system, power management, frequency and voltage regulation

Procedia PDF Downloads 440

Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

Abstract:

Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

Procedia PDF Downloads 89

Authors: Ramalan Musa Yerima

Abstract:

The paper titled “loading by number” explained a strategy developed recently by Zonal Commanding Officer of the Federal Road Safety Corps of Nigeria, covering Sokoto, Kebbi and Zamfara States of Northern Nigeria. The strategy is aimed at reducing competition, which will invariably leads to the reduction in speed, reduction in dangerous driving, reduction in crash rate, reduction in injuries, reduction in property damages and reduction in death through road traffic crashes (RTC). This research paper presents a study focused on enhancing the safety of commercial vehicles. The background of this study highlights the alarming statistics related to commercial vehicle crashes in Nigeria with focus on Sokoto, Kebbi and Zamfara States, which often result in significant damage to property, loss of lives, and economic costs. The significance and aims is to investigate and propose effective strategy to enhance the safety of commercial vehicles. The study recognizes the pressing need for heightened safety measures in commercial transportation, as it impacts not only the well-being of drivers and passengers but also the overall public safety. To achieve the objectives, an examination of accident data, including causes and contributing factors, was performed to identify critical areas for improvement. The major finding of the study reveals that when competition comes into play within the realm of commercial driving, it has detrimental effects on road safety and resource management. Commercial drivers are pushed to complete their routes quickly, deliver goods on time or they pushed themselves to arrive quickly for more passengers and new contracts. This competitive environment, fuelled by internal and external pressures such as tight deadlines, poverty and greed, often leads to sad endings. The study recommend that if a strategy called loading by number is integrated with other multiple safety measures such as driver training programs, regulatory enforcement, and infrastructure improvements, commercial vehicle safety can be significantly enhanced. "Loading by Number” approach is design to ensure that the sequence of departure of drivers from motor park ‘A’ would be communicated to motor park officials of park ‘B’, which would be considered sequentially when giving them returning passengers, regardless of the first to arrive. In conclusion, this paper underscores the significance of improving the safety measures of commercial vehicles, as they are often larger and heavier than other vehicles on the road. Whenever they are involved in accidents, the consequences can be more severe. Commercial vehicles are also frequently involved in long-haul or interstate transportation, which means they cover longer distances and spend more time on the road. This increased exposure to driving conditions increases the probability of accidents occurring. By implementing the suggested measures, policymakers, transportation authorities, and industry stakeholders can work collectively towards ensuring a safer commercial transportation system.

Keywords: commercial, safety, strategy, transportation

Procedia PDF Downloads 45

Authors: Xi Liu, Fan Yuan

Abstract:

In the evolving landscape of physics-based machine learning (PBML), particularly within fluid dynamics and its applications in electromechanical engineering, robot vision, and robot learning, achieving precision and alignment with researchers' specific needs presents a formidable challenge. In response, this work proposes a methodology that integrates neural transformation with a modified smoothed particle hydrodynamics model for generating transformed 3D fluid simulations. This approach is useful for nanoscale science, where the unique and complex behaviors of viscoelastic medium demand accurate neurally-transformed simulations for materials understanding and manipulation. In electromechanical engineering, the method enhances the design and functionality of fluid-operated systems, particularly microfluidic devices, contributing to advancements in nanomaterial design, drug delivery systems, and more. The proposed approach also aligns with the principles of PBML, offering advantages such as multi-fluid stylization and consistent particle attribute transfer. This capability is valuable in various fields where the interaction of multiple fluid components is significant. Moreover, the application of neurally-transformed hydrodynamical models extends to manufacturing processes, such as the production of microelectromechanical systems, enhancing efficiency and cost-effectiveness. The system's ability to perform neural transfer on 3D fluid scenes using a deep learning algorithm alongside physical models further adds a layer of flexibility, allowing researchers to tailor simulations to specific needs across scientific and engineering disciplines.

Keywords: physics-based machine learning, robot vision, robot learning, hydrodynamics

Procedia PDF Downloads 55

Authors: Pegah Eshraghi, Zahra Sadat Zomorodian, Mohammad Tahsildoost

Abstract:

Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

Procedia PDF Downloads 70

Authors: Zahra Alikhani Koopaei

Abstract:

In the fifth lesson of the third-grade mathematics book, students are introduced to the concept of multiplication. However, some students showed a lack of interest in learning this topic. To address this, a simple electronic multiplication table was designed with the aim of making the concept of multiplication entertaining and engaging for students. It provides them with moments of excitement during the learning process. To achieve this goal, a device was created that produced a bell sound when two wire ends were connected. Each wire end was connected to a specific number in the multiplication table, and the other end was linked to the corresponding answer. Consequently, if the answer is correct, the bell will ring. This study employs interactive and engaging methods to teach mathematics, particularly to students who have previously shown little interest in the subject. By integrating game-based learning and critical thinking, we observed an increase in understanding and interest in learning multiplication compared to before using this method. This further motivated the students. As a result, the intelligent multiplication table was successfully designed. Students, under the instructor's supervision, could easily construct the device during the lesson. Through the implementation of these operations, the concept of multiplication was firmly established in the students' minds. Engaging multiple intelligences in each student enhances a more stable and improved understanding of the concept of multiplication.

Keywords: intelligent multiplication table, design, construction, education, increased interest, students

Procedia PDF Downloads 51

Authors: J. Mano Ranjini

Abstract:

Each and every child is special, born with a unique talent to explore this world. The word Dyslexia is derived from the Greek language in which “dys” meaning poor or inadequate and “lexis” meaning words or language. Dyslexia describes about a different kind of mind, which is often gifted and productive, that learns the concept differently. The main aim of the study is to bring the positive outcome of the reading level by examining the effectiveness of Visual Auditory Kinesthetic Tactile technique on Reading Level among Dyslexic Children at Helikx Open School and Learning Centre. A Quasi experimental one group pretest post test design was adopted for this study. The Reading Level was assessed by using the Schonell Graded Word Reading Test. Thirty subjects were drawn by using purposive sampling technique and the intervention Visual Auditory Kinesthetic Tactile technique was implemented to the Dyslexic Children for 30 consecutive days followed by the post Reading Level assessment revealed the improvement in the mean score value of reading level by 12%. Multi-sensory (VAKT) teaching uses all learning pathways in the brain (visual, auditory, kinesthetic-tactile) in order to enhance memory and learning and the ability in uplifting emotional, physical and societal dimensions. VAKT is an effective method to improve the reading skill of the Dyslexic Children that ensures the enormous significance of learning thereby influencing the wholesome of the child’s life.

Keywords: visual auditory kinesthetic tactile technique, reading level, dyslexic children, Helikx Open School

Procedia PDF Downloads 591

Authors: Suraj Gururaj, Sumantha Udupa U.

Abstract:

Browsing the Web has emerged as the de facto activity performed on the Internet. Although browsing gets tracked, the manageability aspect of Web browsing history is very poor. In this paper, we have a workable solution implemented by using machine learning and natural language processing techniques for efficient manageability of user’s browsing history. The significance of adding such a capability to a Web browser is that it ensures efficient and quick information retrieval from browsing history, which currently is very challenging. Our solution guarantees that any important websites visited in the past can be easily accessible because of the intelligent and automatic classification. In a nutshell, our solution-based paper provides an implementation as a browser extension by intelligently classifying the browsing history into most relevant category automatically without any user’s intervention. This guarantees no information is lost and increases productivity by saving time spent revisiting websites that were of much importance.

Keywords: adhoc retrieval, Chrome extension, supervised learning, tile, Web personalization

Procedia PDF Downloads 358

Authors: Sankarprasad Bhuniya, Sukhendu Maiti, Eun-Joong Kim, Hyunseung Lee, Jonathan L. Sessler, Kwan Soo Hong, Jong Seung Kim

Abstract:

A new theranostic strategy is described. It is based on the use of an “all in one” prodrug, namely the biotinylated piperazine-rhodol conjugate 4a. This conjugate, which incorporates the anticancer drug SN-38, undergoes self-immolative cleavage when exposed to biological thiols. This leads to the tumor-targeted release of the active SN-38 payload along with fluorophore 1a. This release is made selective as the result of the biotin functionality. Fluorophore 1a is 32-fold more fluorescent than prodrug 4a. It permits the delivery and release of the SN-38 payload to be monitored easily in vitro and in vivo, as inferred from cell studies and ex vivo analyses of mice xenografts derived HeLa cells, respectively. Prodrug 4a also displays anticancer activity in the HeLa cell murine xenograft tumor model. On the basis of these findings we suggest that the present strategy, which combines within a single agent the key functions of targeting, release, imaging, and treatment, may have a role to play in cancer diagnosis and therapy.

Keywords: theranostic, prodrug, cancer therapy, fluorescence

Procedia PDF Downloads 523

Authors: Ramalan Musa Yerima

Abstract:

The paper titled “Loading by number” explained a strategy developed recently by the Zonal Commanding Officer of the Federal Road Safety Corps of Nigeria, covering Sokoto, Kebbi and Zamfara States of Northern Nigeria. The strategy is aimed at reducing competition, which will invariably lead to a reduction in speed, reduction in dangerous driving, reduction in crash rate, reduction in injuries, reduction in property damages and reduction in death through road traffic crashes (RTC). This research paper presents a study focused on enhancing the safety of commercial vehicles. The background of this study highlights the alarming statistics related to commercial vehicle crashes in Nigeria with a focus on Sokoto, Kebbi and Zamfara States, which often result in significant damage to property, loss of lives, and economic costs. The significance and aims is to investigate and propose an effective strategy to enhance the safety of commercial vehicles. The study recognizes the pressing need for heightened safety measures in commercial transportation, as it impacts not only the well-being of drivers and passengers but also the overall public safety. To achieve the objectives, an examination of accident data, including causes and contributing factors, was performed to identify critical areas for improvement. The major finding of the study reveals that when competition comes into play within the realm of commercial driving, it has detrimental effects on road safety and resource management. Commercial drivers are pushed to complete their routes quickly and deliver goods on time, or they push themselves to arrive quickly for more passengers and new contracts. This competitive environment, fuelled by internal and external pressures such as tight deadlines, poverty and greed, often leads to sad endings. The study recommends that if a strategy called loading by number is integrated with other multiple safety measures, such as driver training programs, regulatory enforcement, and infrastructure improvements, commercial vehicle safety can be significantly enhanced. "Loading by Number” approach is designed to ensure that the sequence of departure of drivers from the motor park ‘A’ would be communicated to motor park officials of park ‘B’, which would be considered sequentially when giving them returning passengers, regardless of the first to arrive. In conclusion, this paper underscores the significance of improving the safety measures of commercial vehicles, as they are often larger and heavier than other vehicles on the road. Whenever they are involved in accidents, the consequences can be more severe. Commercial vehicles are also frequently involved in long-haul or interstate transportation, which means they cover longer distances and spend more time on the road. This increased exposure to driving conditions increases the probability of accidents occurring. By implementing the suggested measures, policymakers, transportation authorities, and industry stakeholders can work collectively toward ensuring a safer commercial transportation system.

Keywords: commercial, safety, strategy, transport

Procedia PDF Downloads 49

Authors: A. Alshabeb

Abstract:

Vocabulary is one of the elements that links the four skills of reading, writing, speaking, and listening and is very critical in learning a foreign language. This study aims to determine how Saudi Arabian EFL students learn English vocabulary via Twitter. The study adopts a mixed sequential research design in collecting and analysing data. The results of the study provide several recommendations for vocabulary learning. Moreover, the study can help teachers to consider the possibilities of using Twitter further, and perhaps to develop new approaches to vocabulary teaching and to support students in their use of social media.

Keywords: social media, twitter, vocabulary, web 2

Procedia PDF Downloads 406

Authors: Amir Mabhout, Toktam Ghafarian, Amirhossein Farzin, Zahra Makki, Sajjad Alizadeh, Amirhossein Ghavi

Abstract:

The high number of Netflix subscribers makes it attractive for data scientists to extract valuable knowledge from the viewers' behavioural analyses. This paper presents a set of statistical insights into viewers' viewing history. After that, a deep learning model is used to predict the future watching behaviour of the users based on previous watching history within the Netflixlatte data pool. Netflixlatte in an aggregated and anonymized data pool of 320 Netflix viewers with a length 250 000 data points recorded between 2008-2022. We observe insightful correlations between the distribution of viewing time and the COVID-19 pandemic outbreak. The presented deep learning model predicts future movie and TV series viewing habits with an average loss of 0.175.

Keywords: data analysis, deep learning, LSTM neural network, netflix

Procedia PDF Downloads 222

Authors: Haojie Wang, Xun Li, Rui Yin

Abstract:

In order to solve the memorization overfitting in the meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels, so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to exponential growth of computation, this paper also proposes a key data extraction method, that only extracts part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: data augmentation, mutex task generation, meta-learning, text classification.

Procedia PDF Downloads 80

Authors: Aber Aboalgasm, Rupert Ward, Ruth Taylor, Jonathan Glazzard

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Teaching art by digital means is a big challenge for the majority of teachers of art and artistic design courses in primary education schools. These courses can clearly identify relationships between art, technology, and creativity in the classroom .The aim of this article is to present a modern way of teaching art, using digital tools in the art classroom in order to improve creative ability in pupils aged between 9 and 11 years; it also presents a conceptual model for creativity based on digital art. The model could be useful for pupils interested in learning drawing and using an e-drawing package, and for teachers who are interested in teaching their students modern digital art, and improving children’s creativity. This model is designed to show the strategy of teaching art through technology, in order for children to learn how to be creative. This will also help education providers to make suitable choices about which technological approaches they should choose to teach students and enhance their creative ability. It is also expected that use of this model will help to develop social interactive qualities that may improve intellectual ability.

Keywords: digital tools, motivation, creative activity, education

Procedia PDF Downloads 325

Authors: Salima R. Rajwani, Tazeen Ali, Rubina Barolia, Yasmin Parpio, Nasreen Alwani, Salima B. Virani

Abstract:

Introduction: Nurses and physicians have a critical role in initiating lifesaving interventions during cardiac arrest. It is important that timely delivery of high quality Cardio Pulmonary Resuscitation (CPR) with advanced resuscitation skills and management of cardiac arrhythmias is a key dimension of code during cardiac arrest. It will decrease the chances of patient survival if the healthcare professionals are unable to initiate CPR timely. Moreover, traditional training will not prepare physicians and nurses at a competent level and their knowledge level declines over a period of time. In this regard, simulation training has been proven to be effective in promoting resuscitation skills. Simulation teaching learning strategy improves knowledge level, and skills performance during resuscitation through experiential learning without compromising patient safety in real clinical situations. The purpose of the study is to evaluate the effectiveness of simulation training in Advanced Cardiac Life Support Courses by using the selfefficacy tool. Methods: The study design is a quantitative research design and non-randomized quasi-experimental study design. The study examined the effectiveness of simulation through self-efficacy in two instructional methods; one is Medium Fidelity Simulation (MFS) and second is Traditional Training Method (TTM). The sample size was 220. Data was compiled by using the SPSS tool. The standardized simulation based training increases self-efficacy, knowledge, and skills and improves the management of patients in actual resuscitation. Results: 153 students participated in study; CG: n = 77 and EG: n = 77. The comparison was done between arms in pre and post-test. (F value was 1.69, p value is <0.195 and df was 1). There was no significant difference between arms in the pre and post-test. The interaction between arms was observed and there was no significant difference in interaction between arms in the pre and post-test. (F value was 0.298, p value is <0.586 and df is 1. However, the results showed self-efficacy scores were significantly higher within experimental group in post-test in advanced cardiac life support resuscitation courses as compared to Traditional Training Method (TTM) and had overall (p <0.0001) and F value was 143.316 (mean score was 45.01 and SD was 9.29) verses pre-test result showed (mean score was 31.15 and SD was 12.76) as compared to TTM in post-test (mean score was 29.68 and SD was 14.12) verses pre-test result showed (mean score was 42.33 and SD was 11.39). Conclusion: The standardized simulation-based training was conducted in the safe learning environment in Advanced Cardiac Life Suport Courses and physicians and nurses benefited from self-confidence, early identification of life-threatening scenarios, early initiation of CPR, and provides high-quality CPR, timely administration of medication and defibrillation, appropriate airway management, rhythm analysis and interpretation, and Return of Spontaneous Circulation (ROSC), team dynamics, debriefing, and teaching and learning strategies that will improve the patient survival in actual resuscitation.

Keywords: advanced cardiac life support, cardio pulmonary resuscitation, return of spontaneous circulation, simulation

Procedia PDF Downloads 67

Authors: Walter M. Millanzi, Stephen M. Kibusi

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Background: Currently, there has been a progressive shortage not only to the number but also the quality of medical practitioners for the most of nursing. Despite that, those who are present exhibit unethical and illegal practices, under standard care and malpractices. The concern is raised in the ways they are prepared, or there might be something missing in nursing curricula or how it is delivered. There is a need for transforming or testing new teaching modalities to enhance competent health workforces. Objective: to investigate the Effect of Facilitation in a Problem-based Environment (FPBE) on metacognition, self-directed learning and learning motivation to undergraduate nurse student in Tanzanian higher learning institutions. Methods: quasi-experimental study (quantitative research approach). A purposive sampling technique was employed to select institutions and achieving a sample size of 401 participants (interventional = 134 and control = 267). Self-administered semi-structured questionnaire; was the main data collection methods and the Statistical Package for Service Solution (v. 20) software program was used for data entry, data analysis, and presentations. Results: The pre-post test results between groups indicated noticeably significant change on metacognition in an intervention (M = 1.52, SD = 0.501) against the control (M = 1.40, SD = 0.490), t (399) = 2.398, p < 0.05). SDL in an intervention (M = 1.52, SD = 0.501) against the control (M = 1.40, SD = 0.490), t (399) = 2.398, p < 0.05. Motivation to learn in an intervention (M = 62.67, SD = 14.14) and the control (n = 267, M = 57.75), t (399) = 2.907, p < 0.01). A FPBE teaching pedagogy, was observed to be effective on the metacognition (AOR = 1.603, p < 0.05), SDL (OR = 1.729, p < 0.05) and Intrinsic motivation in learning (AOR = 1.720, p < 0.05) against conventional teaching pedagogy. Needless, was less likely to enhance Extrinsic motivation (AOR = 0.676, p > 0.05) and Amotivation (AOR = 0.538, p > 0.05). Conclusion and recommendation: FPBE teaching pedagogy, can improve student’s metacognition, self-directed learning and intrinsic motivation to learn among nurse students. Nursing curricula developers should incorporate it to produce 21st century competent and qualified nurses.

Keywords: facilitation, metacognition, motivation, self-directed

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Authors: Pi-Chi Wu, Tsui-Ping Chu, Hsiu-Hung Wang

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Background: The ability to provide immediate medical service in outpatient departments is one of the keys to patient satisfaction. Objectives: This project used electronic equipment to integrate nursing care information to patient care at a blood pressure diagnostic counter. Through process reengineering, the average patient waiting time decreased from 35 minutes to 5 minutes, while service satisfaction increased from a score of 2.7 to 4.6. Methods: Data was collected from a local hospital in Southern Taiwan from a daily average of 2,200 patients in the outpatient department. Previous waiting times were affected by (1) space limitations, (2) the need to help guide patient mobility, (3) the need for nurses to appease irate patients and give instructions, (4), the need for patients to replace lost counter tickets, (5) the need to re-enter information, (6) the replacement of missing patient information. An ad hoc group was established to enhance patient satisfaction and shorten waiting times for patients to see a doctor. A four step strategy consisting of (1) counter relocation, (2) queue reorganization, (3) electronic information integration, (4) process reengineering was implemented. Results: Implementation of the developed strategy decreased patient waiting time from 35 minutes to an average of 5 minutes, and increased patient satisfaction scores from 2.7 to 6.4. Conclusion: Through the integration of information technology and process transformation, waiting times were drastically reduced, patient satisfaction increased, and nurses were allowed more time to engage in more cost-effective services. This strategy was simultaneously enacted in separate hospitals throughout Taiwan.

Keywords: process reengineering, electronic information integration, patient satisfaction, patient waiting time

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Authors: Bruno Pinto Vieira, Marco Antonio Calijorne Soares, Armando Sérgio de Aguiar Filho

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Nowadays, a massive amount of information has been produced by different data sources, including mobile devices and transactional systems. In this scenario, concerns arise on how to maintain or establish data quality, which is now treated as a product to be defined, measured, analyzed, and improved to meet consumers' needs, which is the one who uses these data in decision making and companies strategies. Information that reaches low levels of quality can lead to issues that can consume time and money, such as missed business opportunities, inadequate decisions, and bad risk management actions. The step of selecting, identifying, evaluating, and selecting data sources with significant quality according to the need has become a costly task for users since the sources do not provide information about their quality. Traditional data quality control methods are based on user experience or business rules limiting performance and slowing down the process with less than desirable accuracy. Using advanced machine learning algorithms, it is possible to take advantage of computational resources to overcome challenges and add value to companies and users. In this study, machine learning is applied to data quality analysis on different datasets, seeking to compare the performance of the techniques according to the dimensions of quality assessment. As a result, we could create a ranking of approaches used, besides a system that is able to carry out automatically, data quality assessment.

Keywords: machine learning, data quality, quality dimension, quality assessment

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Authors: Kuek Teik Sheng, Leaw Zee Guan, Lim Wah Kien, Ting Tin Tin

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Educational technology such as YouTube and Kahoot have arisen as an alternative to effective learning among higher education institutions. There are many researches done in carrying out experiments to test different educational technologies and received positive feedback from students. Yet, similar study is hardly found in Malaysia especially study that includes the latest educational technologies. As a developing country, it is crucial to ensure that these emerging technologies are assisting students in learning process before it is widely adopted in institutions. This paper conducted a study to explore the perception of higher education institution students on the current educational technologies in Malaysia which include online educational games, online videos/course, social media, presentation tools and resource management tool. Some of these technologies have not been looked into its potential in effective learning process. An online survey using questionnaire is conducted among a target of 300 university/college. In the survey, the result shows that majority of the target students in Malaysia agree that the current educational technologies help them in learning, understanding and manage their studies. It is necessary to discover students’ perceptions on the educational technologies in order to provide guidelines for the educators/institutions in selecting appropriate technology to conduct the lecture/tutorial efficiently and effectively.

Keywords: education, educational technology, Facebook, PowerPoint, YouTube

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Authors: Nazym Zhumabayeva, Aleksandr Mezin, Alexandra Knysheva

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Women's underrepresentation in STEM is critical, worsened by ineffective engagement in educational practices. UNICEF Kazakhstan and GameLab KBTU's collaborative initiatives aim to enhance female STEM participation by fostering an inclusive environment. Learning from LEVEL UP's 2023 program, which featured a hackathon, the 2024 strategy pivots towards non-competitive gamification. Although the data from last year's project showed higher than average student engagement, observations and in-depth interviews with participants showed that the format was stressful for the girls, making them focus on points rather than on other values. This study presents a gamified educational system, DPG Lab, aimed at incentivizing young women's participation in STEM through the development of digital public goods (DPGs). By prioritizing collaborative gamification elements, the project seeks to create an inclusive learning environment that increases engagement and interest in STEM among young women. The DPG Lab aims to find a solution to minimize competition and support collaboration. The project is designed to motivate female participants towards the development of digital solutions through an introduction to the concept of DPGs. It consists of a short online course, a simulation videogame, and a real-time online quest with an offline finale at the KBTU campus. The online course offers short video lectures on open-source development and DPG standards. The game facilitates the practical application of theoretical knowledge, enriching the learning experience. Learners can also participate in a quest that encourages participants to develop DPG ideas in teams by choosing missions throughout the quest path. At the offline quest finale, the participants will meet in person to exchange experiences and accomplishments without engaging in comparative assessments: the quest ensures that each team’s trajectory is distinct by design. This marks a shift from competitive hackathons to a collaborative format, recognizing the unique contributions and achievements of each participant. The pilot batch of students is scheduled to commence in April 2024, with the finale anticipated in June. It is projected that this group will comprise 50 female high-school students from various regions across Kazakhstan. Expected outcomes include increased engagement and interest in STEM fields among young female participants, positive emotional and psychological impact through an emphasis on collaborative learning environments, and improved understanding and skills in DPG development. GameLab KBTU intends to undertake a hypothesis evaluation, employing a methodology similar to that utilized in the preceding LEVEL UP project. This approach will encompass the compilation of quantitative metrics (conversion funnels, test results, and surveys) and qualitative data from in-depth interviews and observational studies. For comparative analysis, a select group of participants from the previous year's project will be recruited to engage in the DPG Lab. By developing and implementing a gamified framework that emphasizes inclusion, engagement, and collaboration, the study seeks to provide practical knowledge about effective gamification strategies for promoting gender diversity in STEM. The expected outcomes of this initiative can contribute to the broader discussion on gamification in education and gender equality in STEM by offering a replicable and scalable model for similar interventions around the world.

Keywords: collaborative learning, competitive learning, digital public goods, educational gamification, emerging regions, STEM, underprivileged groups

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Authors: Htay Htay Yi, Zin May Aye

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Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: false negative rate, intrusion detection system, machine learning methods, performance

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Authors: Kim Bower

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Evaluating and researching motivation in language learning is a complex and multi-faceted activity. Various models for investigating learner motivation have been proposed in the literature, but no one model supplies a complex and coherent model for investigating a range of motivational characteristics. Here, such a methodological framework, which includes exemplification of sources of evidence and potential methods of investigation, is proposed. The process model for the investigation of motivation within language learning settings proposed is based on a complex dynamic systems perspective that takes account of cognition and affects. It focuses on three overarching aspects of motivation: the learning environment, learner engagement and learner identities. Within these categories subsets are defined: the learning environment incorporates teacher, course and group specific aspects of motivation; learner engagement addresses the principal characteristics of learners' perceived value of activities, their attitudes towards language learning, their perceptions of their learning and engagement in learning tasks; and within learner identities, principal characteristics of self-concept and mastery of the language are explored. Exemplifications of potential sources of evidence in the model reflect the multiple influences within and between learner and environmental factors and the possible changes in both that may emerge over time. The model was initially developed as a framework for investigating different models of Content and Language Integrated Learning (CLIL) in contrasting contexts in secondary schools in England. The study, from which examples are drawn to exemplify the model, aimed to address the following three research questions: (1) in what ways does CLIL impact on learner motivation? (2) what are the main elements of CLIL that enhance motivation? and (3) to what extent might these be transferable to other contexts? This new model has been tried and tested in three locations in England and reported as case studies. Following an initial visit to each institution to discuss the qualitative research, instruments were developed according to the proposed model. A questionnaire was drawn up and completed by one group prior to a 3-day data collection visit to each institution, during which interviews were held with academic leaders, the head of the department, the CLIL teacher(s), and two learner focus groups of six-eight learners. Interviews were recorded and transcribed verbatim. 2-4 naturalistic observations of lessons were undertaken in each setting, as appropriate to the context, to provide colour and thereby a richer picture. Findings were subjected to an interpretive analysis by the themes derived from the process model and are reported elsewhere. The model proved to be an effective and coherent framework for planning the research, instrument design, data collection and interpretive analysis of data in these three contrasting settings, in which different models of language learning were in place. It is hoped that the proposed model, reported here together with exemplification and commentary, will enable teachers and researchers in a wide range of language learning contexts to investigate learner motivation in a systematic and in-depth manner.

Keywords: investigate, language-learning, learner motivation model, dynamic systems perspective

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Authors: Alonge Isaac Olusola

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Taking a cue from countries such as China and Japan, there is no doubt that the teaching and learning of Mother Tongue ( MT) or Language of Immediate Environment (LIE) is a potential source of development in every country. The engine of economic, scientific, technological and political advancement would be more functional when the language of instruction for teaching and learning in schools is in the child’s mother tongue. The purpose of this paper therefore, is to delve into the genesis of the official recognition given to the teaching and learning of Nigerian languages at national level with special focus on Yoruba language. Yoruba language and other Nigerian languages were placed on a national pedestal by a Nigerian Educational Minister, Late Professor Babatunde Fafunwa, who served under the government of General Ibrahim Babangida (1985 – 1993). Through his laudable effort, the teaching and learning of Nigerian languages in schools all over the nation was incorporated officially in the national policy of education. Among all the Nigerian languages, Hausa, Igbo and Yoruba were given foremost priorities because of the large population of their speakers. Since the Fafunwa era, Yoruba language has become a national subject taught in primary, secondary and tertiary institutions in Nigeria. However, like every new policy, its implementation has suffered several forms of criticisms and impediments from governments, policy makers, curriculum developers, school administrators, teachers and learners. This paper has been able to arrive at certain findings through oral interviews, questionnaires and evaluation of pupils/students enrolment and performances in Yoruba language with special focus on the South-west and North central regions of Nigeria. From the research carried out, some factors have been found to be responsible for the successful implementation or otherwise of Yoruba language instruction policy in some schools, colleges and higher institutions in Nigeria. In conclusion, the paper made recommendations on how the National Policy of Education would be implemented to enhance the teaching and learning of Yoruba language in all Nigerian schools.

Keywords: language of immediate environment, mother tongue, national policy of education, yoruba language

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