Search results for: mathematical learning activities
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 14060

Search results for: mathematical learning activities

11720 Obesity and Lifestyle of Students in Roumanian Southeastern Region

Authors: Mariana Stuparu-Cretu, Doina-Carina Voinescu, Rodica-Mihaela Dinica, Daniela Borda, Camelia Vizireanu, Gabriela Iordachescu, Camelia Busila

Abstract:

Obesity is involved in the etiology or acceleration of progression of important non-communicable diseases, such as: metabolic, cardiovascular, rheumatological, oncological and depression. It is a need to prevent the obesity occurrence, like a key link in disease management. From this point of view, the best approach is to early educate youngsters upon the need for a healthy nutrition lifestyle associated with constant physical activities. The objective of the study was to assess correlations between weight condition, physical activities and food preferences of students from South East Romania. Questionnaires were applied on high school students in Galati: 1006 girls and 880 boys, aged between 14 and 19 years (being approved by Local School Inspectorate and the Ethics Committee of the 'Dunarea de Jos' University of Galati). The collected answers have been statistically processed by using the multivariate regression method (PLS2) by Unscramble X program (Camo, Norway). Multiple variables such as age group, body mass index, nutritional habits and physical activities were separately analysed, depending on gender and general mathematical models were proposed to explain the obesity trend at an early age. The study results show that overweight and obesity are present in less than a fifth of the adolescents who were surveyed. With a very small variation and a strong correlation of over 86% for 99% of the cases, a general preference for sweet foods, nocturnal eating associated with computer work and a reduced period of physical activity is noticed for girls. In addition, the overweight girls consume sweet juices and alcohol, although a percentage of them also practice the gym. There is also a percentage of the normoponderal girls that consume high caloric foods which predispose this group to turn into overweight cases in time. Within the studied group, statistics for the boys show a positive correlation of almost 87% for over 96% of cases. They prefer high calories foods, fast food, and sweet juices, and perform medium physical activities. Both overweight and underweight boys are more sedentary. Over 15% of girls and over a quarter of boys consume alcohol. All these bad eating habits seem to increase with age, for both sexes. To conclude, obesity and overweight assessed in adolescents in S-E Romania reveal nonsignificant percentage differences between boys and girls. However, young people in this area of the country are sedentary in general; a significant percentage prefers sweets / sweet juices / fast-food and practice computer nourishing. The authors consider that at this age, it is very useful to adapt nutritional education by new methods of food processing and market supply. This would require an early understanding of the difference among foods and nutrients and the benefits of physical activities integrated into the healthy current lifestyle, as a measure for preventing and managing non-communicable chronic diseases related to nutritional errors and sedentarism. Acknowledgment— This study has been partial founded by the Francophone University Agency, Project Réseau régional dans le domaine de la santé, la nutrition et la sécurité alimentaire (SaIN), no.21899/ 06.09.2017.

Keywords: adolescents, body mass index, nutritional habits, obesity, physical activity

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11719 Efficient Subgoal Discovery for Hierarchical Reinforcement Learning Using Local Computations

Authors: Adrian Millea

Abstract:

In hierarchical reinforcement learning, one of the main issues encountered is the discovery of subgoal states or options (which are policies reaching subgoal states) by partitioning the environment in a meaningful way. This partitioning usually requires an expensive global clustering operation or eigendecomposition of the Laplacian of the states graph. We propose a local solution to this issue, much more efficient than algorithms using global information, which successfully discovers subgoal states by computing a simple function, which we call heterogeneity for each state as a function of its neighbors. Moreover, we construct a value function using the difference in heterogeneity from one step to the next, as reward, such that we are able to explore the state space much more efficiently than say epsilon-greedy. The same principle can then be applied to higher level of the hierarchy, where now states are subgoals discovered at the level below.

Keywords: exploration, hierarchical reinforcement learning, locality, options, value functions

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11718 Machine Learning for Classifying Risks of Death and Length of Stay of Patients in Intensive Unit Care Beds

Authors: Itamir de Morais Barroca Filho, Cephas A. S. Barreto, Ramon Malaquias, Cezar Miranda Paula de Souza, Arthur Costa Gorgônio, João C. Xavier-Júnior, Mateus Firmino, Fellipe Matheus Costa Barbosa

Abstract:

Information and Communication Technologies (ICT) in healthcare are crucial for efficiently delivering medical healthcare services to patients. These ICTs are also known as e-health and comprise technologies such as electronic record systems, telemedicine systems, and personalized devices for diagnosis. The focus of e-health is to improve the quality of health information, strengthen national health systems, and ensure accessible, high-quality health care for all. All the data gathered by these technologies make it possible to help clinical staff with automated decisions using machine learning. In this context, we collected patient data, such as heart rate, oxygen saturation (SpO2), blood pressure, respiration, and others. With this data, we were able to develop machine learning models for patients’ risk of death and estimate the length of stay in ICU beds. Thus, this paper presents the methodology for applying machine learning techniques to develop these models. As a result, although we implemented these models on an IoT healthcare platform, helping clinical staff in healthcare in an ICU, it is essential to create a robust clinical validation process and monitoring of the proposed models.

Keywords: ICT, e-health, machine learning, ICU, healthcare

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11717 An Exploration of Possible Impact of Drumming on Mental Health in a Hospital Setting

Authors: Zhao Luqian, Wang Yafei

Abstract:

Participation in music activities is beneficial for enhancing wellbeing, especially for aged people (Creech, 2013). Looking at percussion group in particular, it can facilitate a sense of belonging, relaxation, energy, and productivity, learning, enhanced mood, humanising, seems of accomplishment, escape from trauma, and emotional expression (Newman, 2015). In health literatures, group drumming is effective in reducing stress and improving multiple domains of social-motional behaviors (Ho et al., 2011; Maschi et al., 2010) because it offers a creative and mutual learning space that allows patients to establish a positive peer interaction (Mungas et al., 2014; Perkins, 2016). However, very few studies have investigated the effect of group drumming from the aspect of patients’ needs. Therefore, this study focuses on the discussion of patients' specific needs within mental health and explores how group percussion may meet their needs. Seligman’s (2011) five core elements of mental health were applied as patients’ needs in this study: (1) Positive emotions; (2) Engagement; (3) Relationships; (4) Meaning and (5) Accomplishment. 12 participants aged 57- 80 years were interviewed individually. The researcher also had observation in four drumming groups simultaneously. The results reveal that group drumming could improve participants’ mental wellbeing. First, it created a therapeutic health care environment extending beyond the elimination of boredom, and patients could focus on positive emotions during the session of group drumming. Secondly, it was effective in satisfying patients’ level of engagement. Thirdly, this study found that joining a percussion group would require patients to work on skills such as turn-taking and sharing. This equal relationship is helpful for releasing patients’ negative mood and thus forming tighter relationships between and among them. Fourthly, group drumming was found to meet patients’ meaning needs through offering them a place of belonging and a place for sharing. Its leaner-oriented approach engaged patients by a sense of belonging, accepting, connecting, and ownership. Finally, group drumming could meet patients’ needs for accomplishment through the learning process. The inclusive learning process, which indicates there is no right or wrong throughout the process, allowed patients to make their own decisions. In conclusion, it is difficult for patients to achieve positive emotions, engagement, relationships, meanings, and accomplishments in a hospital setting. Drumming can be practiced for enhancement in terms of reducing patients’ negative emotions and improving their experiences in a hospital through enriched social interaction and sense of accomplishment. Also, it can help patients to enhance social skills in a controlled environment.

Keywords: group drumming, hospital, mental health, music psychology

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11716 Applied Mathematical Approach on “Baut” Special High Performance Metal Aggregate by Formulation and Equations

Authors: J. R. Bhalla, Gautam, Gurcharan Singh, Sanjeev Naval

Abstract:

Mathematics is everywhere behind the every things on the earth as well as in the universe. Predynastic Egyptians of the 5th millennium BC pictorially represented geometric designs. Now a day’s we can made and apply an equation on a complex geometry through applied mathematics. Here we work and focus on to create a formula which apply in the field of civil engineering in new concrete technology. In this paper our target is to make a formula which is applied on “BAUT” Metal Aggregate. In this paper our approach is to make formulation and equation on special “BAUT” Metal Aggregate by Applied Mathematical Study Case 1. BASIC PHYSICAL FORMULATION 2. ADVANCE EQUATION which shows the mechanical performance of special metal aggregates for concrete technology. In case 1. Basic physical formulation shows the surface area and volume manually and in case 2. Advance equation shows the mechanical performance has been discussed, the metal aggregates which had outstandingly qualities to resist shear, tension and compression forces. In this paper coarse metal aggregates is 20 mm which used for making high performance concrete (H.P.C).

Keywords: applied mathematical study case, special metal aggregates, concrete technology, basic physical formulation, advance equation

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11715 Changing Misconceptions in Heat Transfer: A Problem Based Learning Approach for Engineering Students

Authors: Paola Utreras, Yazmina Olmos, Loreto Sanhueza

Abstract:

This work has the purpose of study and incorporate Problem Based Learning (PBL) for engineering students, through the analysis of several thermal images of dwellings located in different geographical points of the Region de los Ríos, Chile. The students analyze how heat is transferred in and out of the houses and how is the relation between heat transfer and climatic conditions that affect each zone. As a result of this activity students are able to acquire significant learning in the unit of heat and temperature, and manage to reverse previous conceptual errors related with energy, temperature and heat. In addition, student are able to generate prototype solutions to increase thermal efficiency using low cost materials. Students make public their results in a report using scientific writing standards and in a science fair open to the entire university community. The methodology used to measure previous Conceptual Errors has been applying diagnostic tests with everyday questions that involve concepts of heat, temperature, work and energy, before the unit. After the unit the same evaluation is done in order that themselves are able to evidence the evolution in the construction of knowledge. As a result, we found that in the initial test, 90% of the students showed deficiencies in the concepts previously mentioned, and in the subsequent test 47% showed deficiencies, these percent ages differ between students who carry out the course for the first time and those who have performed this course previously in a traditional way. The methodology used to measure Significant Learning has been by comparing results in subsequent courses of thermodynamics among students who have received problem based learning and those who have received traditional training. We have observe that learning becomes meaningful when applied to the daily lives of students promoting internalization of knowledge and understanding through critical thinking.

Keywords: engineering students, heat flow, problem-based learning, thermal images

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11714 Mathematical Modeling of District Cooling Systems

Authors: Dana Alghool, Tarek ElMekkawy, Mohamed Haouari, Adel Elomari

Abstract:

District cooling systems have captured the attentions of many researchers recently due to the enormous benefits offered by such system in comparison with traditional cooling technologies. It is considered a major component of urban cities due to the significant reduction of energy consumption. This paper aims to find the optimal design and operation of district cooling systems by developing a mixed integer linear programming model to minimize the annual total system cost and satisfy the end-user cooling demand. The proposed model is experimented with different cooling demand scenarios. The results of the very high cooling demand scenario are only presented in this paper. A sensitivity analysis on different parameters of the model was performed.

Keywords: Annual Cooling Demand, Compression Chiller, Mathematical Modeling, District Cooling Systems, Optimization

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11713 A Study of Taiwanese Students' Language Use in the Primary International Education via Video Conferencing Course

Authors: Chialing Chang

Abstract:

Language and culture are critical foundations of international mobility. However, the students who are limited to the local environment may affect their learning outcome and global perspective. Video Conferencing has been proven an economical way for students as a medium to communicate with international students around the world. In Taiwan, the National Development Commission advocated the development of bilingual national policies in 2030 to enhance national competitiveness and foster English proficiency and fully launched bilingual activation of the education system. Globalization is closely related to the development of Taiwan's education. Therefore, the teacher conducted an integrated lesson through interdisciplinary learning. This study aims to investigate how the teacher helps develop students' global and language core competencies in the international education class. The methodology comprises four stages, which are lesson planning, class observation, learning data collection, and speech analysis. The Grice's Conversational Maxims are adopted to analyze the students' conversation in the video conferencing course. It is the action research from the teacher's reflection on approaches to developing students' language learning skills. The study lays the foundation for mastering the teacher's international education professional development and improving teachers' teaching quality and teaching effectiveness as a reference for teachers' future instruction.

Keywords: international education, language learning, Grice's conversational maxims, video conferencing course

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11712 Autonomy in Teaching and Learning Subject-Specific Academic Literacy

Authors: Maureen Lilian Klos

Abstract:

In this paper, the notion of autonomy in language teaching and learning is explored with a view to designing particular subject-specific academic literacy at higher education level, for mostly English second or third language learners at the Nelson Mandela University, Port Elizabeth, South Africa. These courses that are contextualized in subject-specific fields studied by students in Arts, Education and Social Science Faculties aim to facilitate learners in the manipulation of cognitively demanding academic texts. However, classroom contact time for these courses is limited to one ninety sessions per week. Thus, learners need to be autonomously responsible for developing their own skills when manipulating and negotiating appropriate academic textual conventions. Thus, a model was designed to allow for gradual learner independence in language learning skills. Learners experience of the model was investigated using the Phenomenological Research Approach. Data in the form of individual written reflections and transcripts of unstructured group interviews were analyzed for themes and sub-themes. These findings are discussed in the article with a view to addressing the practical concerns of the learners in this case study.

Keywords: academic literacies, autonomy, language learning and teaching, subject-specific language

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11711 An Adaptive Conversational AI Approach for Self-Learning

Authors: Airy Huang, Fuji Foo, Aries Prasetya Wibowo

Abstract:

In recent years, the focus of Natural Language Processing (NLP) development has been gradually shifting from the semantics-based approach to deep learning one, which performs faster with fewer resources. Although it performs well in many applications, the deep learning approach, due to the lack of semantics understanding, has difficulties in noticing and expressing a novel business case with a pre-defined scope. In order to meet the requirements of specific robotic services, deep learning approach is very labor-intensive and time consuming. It is very difficult to improve the capabilities of conversational AI in a short time, and it is even more difficult to self-learn from experiences to deliver the same service in a better way. In this paper, we present an adaptive conversational AI algorithm that combines both semantic knowledge and deep learning to address this issue by learning new business cases through conversations. After self-learning from experience, the robot adapts to the business cases originally out of scope. The idea is to build new or extended robotic services in a systematic and fast-training manner with self-configured programs and constructed dialog flows. For every cycle in which a chat bot (conversational AI) delivers a given set of business cases, it is trapped to self-measure its performance and rethink every unknown dialog flows to improve the service by retraining with those new business cases. If the training process reaches a bottleneck and incurs some difficulties, human personnel will be informed of further instructions. He or she may retrain the chat bot with newly configured programs, or new dialog flows for new services. One approach employs semantics analysis to learn the dialogues for new business cases and then establish the necessary ontology for the new service. With the newly learned programs, it completes the understanding of the reaction behavior and finally uses dialog flows to connect all the understanding results and programs, achieving the goal of self-learning process. We have developed a chat bot service mounted on a kiosk, with a camera for facial recognition and a directional microphone array for voice capture. The chat bot serves as a concierge with polite conversation for visitors. As a proof of concept. We have demonstrated to complete 90% of reception services with limited self-learning capability.

Keywords: conversational AI, chatbot, dialog management, semantic analysis

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11710 Parkinson’s Disease Detection Analysis through Machine Learning Approaches

Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

Abstract:

Machine learning and data mining are crucial in health care, as well as medical information and detection. Machine learning approaches are now being utilized to improve awareness of a variety of critical health issues, including diabetes detection, neuron cell tumor diagnosis, COVID 19 identification, and so on. Parkinson’s disease is basically a disease for our senior citizens in Bangladesh. Parkinson's Disease indications often seem progressive and get worst with time. People got affected trouble walking and communicating with the condition advances. Patients can also have psychological and social vagaries, nap problems, hopelessness, reminiscence loss, and weariness. Parkinson's disease can happen in both men and women. Though men are affected by the illness at a proportion that is around partial of them are women. In this research, we have to get out the accurate ML algorithm to find out the disease with a predictable dataset and the model of the following machine learning classifiers. Therefore, nine ML classifiers are secondhand to portion study to use machine learning approaches like as follows, Naive Bayes, Adaptive Boosting, Bagging Classifier, Decision Tree Classifier, Random Forest classifier, XBG Classifier, K Nearest Neighbor Classifier, Support Vector Machine Classifier, and Gradient Boosting Classifier are used.

Keywords: naive bayes, adaptive boosting, bagging classifier, decision tree classifier, random forest classifier, XBG classifier, k nearest neighbor classifier, support vector classifier, gradient boosting classifier

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11709 Training of Future Computer Science Teachers Based on Machine Learning Methods

Authors: Meruert Serik, Nassipzhan Duisegaliyeva, Danara Tleumagambetova

Abstract:

The article highlights and describes the characteristic features of real-time face detection in images and videos using machine learning algorithms. Students of educational programs reviewed the research work "6B01511-Computer Science", "7M01511-Computer Science", "7M01525- STEM Education," and "8D01511-Computer Science" of Eurasian National University named after L.N. Gumilyov. As a result, the advantages and disadvantages of Haar Cascade (Haar Cascade OpenCV), HoG SVM (Histogram of Oriented Gradients, Support Vector Machine), and MMOD CNN Dlib (Max-Margin Object Detection, convolutional neural network) detectors used for face detection were determined. Dlib is a general-purpose cross-platform software library written in the programming language C++. It includes detectors used for determining face detection. The Cascade OpenCV algorithm is efficient for fast face detection. The considered work forms the basis for the development of machine learning methods by future computer science teachers.

Keywords: algorithm, artificial intelligence, education, machine learning

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11708 Personal Information Classification Based on Deep Learning in Automatic Form Filling System

Authors: Shunzuo Wu, Xudong Luo, Yuanxiu Liao

Abstract:

Recently, the rapid development of deep learning makes artificial intelligence (AI) penetrate into many fields, replacing manual work there. In particular, AI systems also become a research focus in the field of automatic office. To meet real needs in automatic officiating, in this paper we develop an automatic form filling system. Specifically, it uses two classical neural network models and several word embedding models to classify various relevant information elicited from the Internet. When training the neural network models, we use less noisy and balanced data for training. We conduct a series of experiments to test my systems and the results show that our system can achieve better classification results.

Keywords: artificial intelligence and office, NLP, deep learning, text classification

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11707 Integrating Practice-Based Learning in Accounting Education: Bolstering Students Engagement and Learning

Authors: Humayun Murshed, Shibly Abdullah

Abstract:

This paper focuses on sharing experience gained through a pilot project undertaken to teach an introductory accounting subject linking real-life ground realities with the fundamental concepts of accounting. In view of the practical dimensions of Accounting it has been observed that adopting a teaching approach based on practical illustrations help students to motivate and generate interests to take accounting profession as their career. The paper reports that students’ perception about accounting as ‘dreary’ has been changed to ‘interesting’ due to adoption of practice based approach in teaching. The authors argue that ‘concept mapping’ can play a vital role in facilitating practice based education in accounting which promotes a rewarding learning experience among the students. The paper considers taking into account generic skills development, student centric learning, development of innovative assessment tasks, making students aware of the potential benefits of practice based education primarily through concept mapping, and engaging them both inside and outside of the class rooms are critical for ensuring success of this approach.

Keywords: accounting education, pedagogy, practice-based education, concept mapping

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11706 Understanding How Posting and Replying Behaviors in Social Media Differentiate the Social Capital Cultivation Capabilities of Users

Authors: Jung Lee

Abstract:

This study identifies how the cultivation capabilities of social capital influence the overall attitudes of social media users and how these influences differ across user groups. First, the cultivation capabilities of social capital are identified from three aspects, namely, social capital accessibility, potentiality and sensitivity. These three types of social capital acquisition capabilities collectively represent how the social media users perceive the social media environment in terms of possibilities for social capital creation. These three capabilities are hypothesized to influence social media satisfaction and continuing use intention. Next, two essential activities in social media are identified, namely, posting and replying, to categorise social media users based on behavioral patterns. Various social media activities consist of the combinations of these two basic activities. Posting represents the broadcasting aspect of social media, whereas replying represents the communicative aspect of social media. We categorize users into four from communicators to observers by using these two behaviors to develop usage pattern matrix. By applying the usage pattern matrix to the capability model, we argue that posting behavior generally has a positive moderating effect on the attitudes of social media users, whereas replying behavior occasionally exhibits the negative moderating effect. These different moderating effects of posting and replying behavior are explained based on the different levels of social capital sensitivity and expectation of individuals. When a person is highly expecting social capital from social media, he or she would post actively. However, when one is highly sensitive to social capital, he or she would actively respond and reply to postings of other people because such an act would create a longer and more interactive relationship. A total of 512 social media users are invited to answer the survey. They were asked about their attitudes toward the social media and how they expect social capital through this practice. They were asked to check their general social media usage pattern for user categorization. Result confirmed that most of the hypotheses were supported. Three types of social capital cultivation capabilities are significant determinants of social media attitudes, and two social media activities (i.e., posting and replying) exhibited different moderating effects on attitudes. This study provides following discussions. First, three types of social capital cultivation capabilities were identified. Despite the numerous concerns about social media, such as whether it is a decent and real environment that produces social capital, this study confirms that people explicitly expect and experience social capital values from social media. Second, posting and replying activities are two building blocks of social media activities. These two activities are useful in explaining different the attitudes of social media users and predict future usage.

Keywords: social media, social capital, social media satisfaction, social media use intention

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11705 Machine Learning Techniques for Estimating Ground Motion Parameters

Authors: Farid Khosravikia, Patricia Clayton

Abstract:

The main objective of this study is to evaluate the advantages and disadvantages of various machine learning techniques in forecasting ground-motion intensity measures given source characteristics, source-to-site distance, and local site condition. Intensity measures such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Estimating these variables for future earthquake events is a key step in seismic hazard assessment and potentially subsequent risk assessment of different types of structures. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as a statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The algorithms are adjusted to quantify event-to-event and site-to-site variability of the ground motions by implementing them as random effects in the proposed models to reduce the aleatory uncertainty. All the algorithms are trained using a selected database of 4,528 ground-motions, including 376 seismic events with magnitude 3 to 5.8, recorded over the hypocentral distance range of 4 to 500 km in Oklahoma, Kansas, and Texas since 2005. The main reason of the considered database stems from the recent increase in the seismicity rate of these states attributed to petroleum production and wastewater disposal activities, which necessities further investigation in the ground motion models developed for these states. Accuracy of the models in predicting intensity measures, generalization capability of the models for future data, as well as usability of the models are discussed in the evaluation process. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available.

Keywords: artificial neural network, ground-motion models, machine learning, random forest, support vector machine

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11704 Potential Usefulness of Video Lectures as a Tool to Improve Synchronous and Asynchronous the Online Education

Authors: Omer Shujat Bhatti, Afshan Huma

Abstract:

Online educational system were considered a great opportunity for distance learning. In recent days of COVID19 pandemic, it enable the continuation of educational activities at all levels of education, from primary school to the top level universities. One of the key considered element in supporting the online educational system is video lectures. The current research explored the usefulness of the video lectures delivered to technical students of masters level with a focus on MSc Sustainable Environmental design students who have diverse backgrounds in the formal educational system. Hence they were unable to cope right away with the online system and faced communication and understanding issues in the lecture session due to internet and allied connectivity issues. Researcher used self prepared video lectures for respective subjects and provided them to the students using Youtube channel and subject based Whatsapp groups. Later, students were asked about the usefulness of the lectures towards a better understanding of the subject and an overall enhanced learning experience. More than 80% of the students appreciated the effort and requested it to be part of the overall system. Data collection was done using an online questionnaire which was prior briefed to the students with the purpose of research. It was concluded that video lectures should be considered an integral part of the lecture sessions and must be provided prior to the lecture session, ensuring a better quality of delivery. It was also recommended that the existing system must be upgraded to support the availability of these video lectures through the portal. Teachers training must be provided to help develop quality video content ensuring that is able to cover the content and courses taught.

Keywords: video lectures, online distance education, synchronous instruction, asynchronous communication

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11703 Taking Learning beyond Kirkpatrick’s Levels: Applying Return on Investment Measurement in Training

Authors: Charles L. Sigmund, M. A. Aed, Lissa Graciela Rivera Picado

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One critical component of the training development process is the evaluation of the impact and value of the program. Oftentimes, however, learning organizations bypass this phase either because they are unfamiliar with effective methods for measuring the success or effect of the training or because they believe the effort to be too time-consuming or cumbersome. As a result, most organizations that do conduct evaluation limit their scope to Kirkpatrick L1 (reaction) and L2 (learning), or at most carry through to L4 (results). In 2021 Microsoft made a strategic decision to assess the measurable and monetized impact for all training launches and designed a scalable and program-agnostic tool for providing full-scale L5 return on investment (ROI) estimates for each. In producing this measurement tool, the learning and development organization built a framework for making business prioritizations and resource allocations that is based on the projected ROI of a course. The analysis and measurement posed by this process use a combination of training data and operational metrics to calculate the effective net benefit derived from a given training effort. Business experts in the learning field generally consider a 10% ROI to be an outstanding demonstration of the value of a project. Initial findings from this work applied to a critical customer-facing program yielded an estimated ROI of more than 49%. This information directed the organization to make a more concerted and concentrated effort in this specific line of business and resulted in additional investment in the training methods and technologies being used.

Keywords: evaluation, measurement, return on investment, value

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11702 Stimulating Effects of Media in Improving Quality of Distance Education: A Literature Based Study

Authors: Tahzeeb Mahreen

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Distance education refers to giving instruction in which students are remote from the institution and once in a while go to formal demonstration classes, and teaching sessions. Segments of media, for example, radio, TV, PC and Internet and so on are the assets and method for correspondence being utilized as a part of learning material by many open and distance learning institutions. Media has a great part in maximizing the learning opportunities thus enabling distance education, a mode of increased literacy rate of the country. This study goes for analyzing how media had affected distance education through its different mediums. The objectives of the study were (i) to determine the direct impact of media on distance education? (ii) To know how media effects distance education pedagogy (iii) To find out how media works to increase student’s achievement. Literature-based methodology was used, and books, peer-reviewed articles, press reports and internet-based materials were studied as a result. By using descriptive qualitative research analysis, the researcher has interpreted that distance education programs are progressively utilizing mixes of media to convey training that has a positive impact on learning along with a few challenges. In addition, the perception of the researcher varied depending on the programs of distance learning but generally believed that electronic media were moderately more supportive in enhancing the overall performance of the learners. It was concluded that the intellectual style, identity qualities, and self-expectations are the three primary enhanced areas in a student’s educational life in distance education programs. It was portrayed that a comprehension of how individual learners approach learning may make it workable for the distance educator to see an example of learning styles and arrange or modify course presentations through media. Moreover, it is noticed that teaching in distance education address the developing role of the instructor, the requirement for diminishing resistance as conventional teachers utilize remove conveyance frameworks lastly, staff state of mind toward the utilization of innovation. Furthermore, the results showed that media had assumed its part to make distance learning educators more dynamic, capable and concerned about their individual works. The study also indicated a high positive relationship between the media available at study centers and media used by the distance education. The challenge pointed out by the researcher was the clash of distance and time with communication as the life situations of every learner are varied. Recommendations included the realization of the duty of distance learning instructor to help students understand the effective use of media for their study lessons and also to develop online learning communities to be in instant connection with the students.

Keywords: distance education, education, media, teaching and learning

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11701 EFL Teacher Cognition and Learner Autonomy: An Exploratory Study into Algerian Teachers’ Understanding of Learner Autonomy

Authors: Linda Ghout

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The main aim of the present case study was to explore EFL teachers’ understanding of learner autonomy. Thus, it sought to uncover how teachers at the de Department of English, University of Béjaia, Algeria view the process of language learning, their learners’ roles, their own roles and their practices to promote learner autonomy. For data collection, firstly, a questionnaire was designed and administered to all the teachers in the department. Secondly, interviews were conducted with some volunteers for the sake of clarifying emerging issues and digging deeper into some of the teachers’ answers to the questionnaire. The analysis revealed interesting data pertaining to the teachers’ cognition and its effects on their teaching practices. With regard to their views of language learning, it seems that the participants hold discrete views which are in opposition with the principles of learner autonomy. The teachers seemed to have a limited knowledge of the characteristics of autonomous learners and autonomy- based methodology. When it comes to teachers’ practices to promote autonomy in their classes, the majority reported that the most effective way is to ask students to search for information on their own. However, in defining their roles in the EFL learning process, most of the respondents claimed that teachers should play the role of facilitators.

Keywords: English, learner autonomy, learning process, teacher cognition

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11700 Exploring the Formation of High School Students’ Science Identity: A Qualitative Study

Authors: Sitong. Chen, Bing Wei

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As a sociocultural concept, identity has increasingly gained attention in educational research, and the notion of students’ science identity has been widely discussed in the field of science education. Science identity was proved to be a key indicator of students’ learning engagement, persistence, and career intentions in science-related and STEM fields. Thus, a great deal of educational effort has been made to promote students’ science identity in former studies. However, most of this research was focused on students’ identity development during undergraduate and graduate periods, except for a few studies exploring high school students’ identity formation. High school has been argued as a crucial period for promoting science identity. This study applied a qualitative method to explore how high school students have come to form their science identities in previous learning and living experiences. Semi-structured interviews were conducted with 8 newly enrolled undergraduate students majoring in science-related fields. As suggested by the narrative data from interviews, students’ formation of science identities was driven by their five interrelated experiences: growing self-recognition as a science person, achieving success in learning science, getting recognized by influential others, being interested in science subjects, and informal science experiences in various contexts. Specifically, students’ success and achievement in science learning could facilitate their interest in science subjects and others’ recognition. And their informal experiences could enhance their interest and performance in formal science learning. Furthermore, students’ success and interest in science, as well as recognition from others together, contribute to their self-recognition. Based on the results of this study, some practical implications were provided for science teachers and researchers in enhancing high school students’ science identities.

Keywords: high school students, identity formation, learning experiences, living experiences, science identity

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11699 Animations for Teaching Food Chemistry: A Design Approach for Linking Chemistry Theory to Everyday Food

Authors: Paulomi (Polly) Burey, Zoe Lynch

Abstract:

In STEM education, students often have difficulty linking static images and words from textbooks or online resources, to the underlying mechanisms of the topic of study. This can often dissuade some students from pursuing study in the physical and chemical sciences. A growing movement in current day students demonstrates that the YouTube generation feel they learn best from video or dynamic, interactive learning tools, and will seek these out as alternatives to their textbooks and the classroom learning environment. Chemistry, and in particular visualization of molecular structures in everyday materials, can prove difficult to comprehend without significant interaction with the teacher of the content and concepts, beyond the timeframe of a typical class. This can cause a learning hurdle for distance education students, and so it is necessary to provide strong electronic tools and resources to aid their learning. As one of the electronic resources, an animation design approach to link everyday materials to their underlying chemistry would be beneficial for student learning, with the focus here being on food. These animations were designed and storyboarded with a scaling approach and commence with a focus on the food material itself and its component parts. This is followed by animated transitions to its underlying microstructure and identifying features, and finally showing the molecules responsible for these microstructural features. The animation ends with a reverse transition back through the molecular structure, microstructure, all the way back to the original food material, and also animates some reactions that may occur during food processing to demonstrate the purpose of the underlying chemistry and how it affects the food we eat. Using this cyclical approach of linking students’ existing knowledge of food to help guide them to understanding more complex knowledge, and then reinforcing their learning by linking back to their prior knowledge again, enhances student understanding. Food is also an ideal material system for students to interact with, in a hands-on manner to further reinforce their learning. These animations were launched this year in a 2nd year University Food Chemistry course with improved learning outcomes for the cohort.

Keywords: chemistry, food science, future pedagogy, STEM Education

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11698 Internal Assessment of Satisfaction with the Quality of the Learning Process

Authors: Bulatbayeva A. A., Maxutova I. O., Ergalieva A. N.

Abstract:

This article presents a study of the practice of self-assessment of the quality of training cadets in a military higher specialized educational institution. The research was carried out by means of a questionnaire survey aimed at identifying the degree of satisfaction of cadets with the organization of the educational process, quality of teaching, the quality of the organization of independent work, and the system of their assessment. In general, the results of the study are of an intermediate nature. Proven tools will be incorporated into the planning and effective management of the learning process. The results of the study can be useful for the administrators and managers of the military education system for teachers of military higher educational institutions for adjusting the content and technologies of training future specialists. The publication was prepared as part of applied grant research for 2020-2022 by order of the Ministry of Education and Science of the Republic of Kazakhstan on the topic "Development of a comprehensive methodology for assessing the quality of education of graduates of military special educational institutions."

Keywords: teaching quality, quality satisfaction, learning management, quality management, process approach, classroom learning, interactive technologies, teaching quality

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11697 Prediction of Remaining Life of Industrial Cutting Tools with Deep Learning-Assisted Image Processing Techniques

Authors: Gizem Eser Erdek

Abstract:

This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

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11696 MULTI-FLGANs: Multi-Distributed Adversarial Networks for Non-Independent and Identically Distributed Distribution

Authors: Akash Amalan, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang

Abstract:

Federated learning is an emerging concept in the domain of distributed machine learning. This concept has enabled General Adversarial Networks (GANs) to benefit from the rich distributed training data while preserving privacy. However, in a non-IID setting, current federated GAN architectures are unstable, struggling to learn the distinct features, and vulnerable to mode collapse. In this paper, we propose an architecture MULTI-FLGAN to solve the problem of low-quality images, mode collapse, and instability for non-IID datasets. Our results show that MULTI-FLGAN is four times as stable and performant (i.e., high inception score) on average over 20 clients compared to baseline FLGAN.

Keywords: federated learning, generative adversarial network, inference attack, non-IID data distribution

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11695 Lung Disease Detection from the Chest X Ray Images Using Various Transfer Learning

Authors: Aicha Akrout, Amira Echtioui, Mohamed Ghorbel

Abstract:

Pneumonia remains a significant global health concern, posing a substantial threat to human lives due to its contagious nature and potentially fatal respiratory complications caused by bacteria, fungi, or viruses. The reliance on chest X-rays for diagnosis, although common, often necessitates expert interpretation, leading to delays and potential inaccuracies in treatment. This study addresses these challenges by employing transfer learning techniques to automate the detection of lung diseases, with a focus on pneumonia. Leveraging three pre-trained models, VGG-16, ResNet50V2, and MobileNetV2, we conducted comprehensive experiments to evaluate their performance. Our findings reveal that the proposed model based on VGG-16 demonstrates superior accuracy, precision, recall, and F1 score, achieving impressive results with an accuracy of 93.75%, precision of 94.50%, recall of 94.00%, and an F1 score of 93.50%. This research underscores the potential of transfer learning in enhancing pneumonia diagnosis and treatment outcomes, offering a promising avenue for improving healthcare delivery and reducing mortality rates associated with this debilitating respiratory condition.

Keywords: chest x-ray, lung diseases, transfer learning, pneumonia detection

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11694 Mathematical Properties of the Viscous Rotating Stratified Fluid Counting with Salinity and Heat Transfer in a Layer

Authors: A. Giniatoulline

Abstract:

A model of the mathematical fluid dynamics which describes the motion of a three-dimensional viscous rotating fluid in a homogeneous gravitational field with the consideration of the salinity and heat transfer is considered in a vertical finite layer. The model is a generalization of the linearized Navier-Stokes system with the addition of the Coriolis parameter and the equations for changeable density, salinity, and heat transfer. An explicit solution is constructed and the proof of the existence and uniqueness theorems is given. The localization and the structure of the spectrum of inner waves is also investigated. The results may be used, in particular, for constructing stable numerical algorithms for solutions of the considered models of fluid dynamics of the Atmosphere and the Ocean.

Keywords: Fourier transform, generalized solutions, Navier-Stokes equations, stratified fluid

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11693 Effective Strategies for Teaching English Language to Beginners in Primary Schools in Nigeria

Authors: Halima Musa Kamilu

Abstract:

This paper discusses the effective strategies for teaching English language to learners in primary schools in Nigeria. English language development is the systematic use of instructional strategies designed to promote the acquisition of English by pupils in primary schools whose primary language is not English. Learning a second language is through total immersion. These strategies support this learning method, allowing pupils to have the knowledge of English language in a pattern similar to the way they learned their native language through regular interaction with others who already know the language. The focus is on fluency and learning to speak English in a social context with native speakers. The strategies allow for effective acquisition. The paper also looked into the following areas: visuals that reinforce spoken or written words, employ gestures for added emphasis, adjusting of speech, stressing of high-frequency vocabulary words, use of fewer idioms and clarifying the meaning of words or phrases in context, stressing of participatory learning and maintaining a low anxiety level and boosting of enthusiasm. It recommended that the teacher include vocabulary words that will make the content more comprehensible to the learner.

Keywords: effective, strategies, teaching, beginners and primary schools

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11692 Pre-Service Science Teachers' Perceptions Related to the Concept of Laboratory: A Metaphorical Analysis

Authors: Salih Uzun

Abstract:

The laboratory activities are seen an indispensable part of science, teaching, and learning. In this study, the aim was to identify pre-service science teachers’ perceptions related to the concept of laboratory through metaphors. It is expressed that metaphors can be used as a powerful research tool in order to understand personal perceptions. Therefore, metaphors were used with the aim of revealing a picture regarding how pre-service science teachers perceive laboratory. Within the scope of this aim, phenomenographic research design was adopted for this study and an answer was sought to the question; ‘What are pre-service science teachers’ perceptions about the concept of laboratory?’. The sample of this study was a total of 80 pre-service science teachers at various grade levels in Turkey. Participants were asked to complete the sentence; ‘Laboratory is like…; because…’. Documents including pre-service science teachers’ answers to the open-ended questions were used as data sources and the data were analysed with content analysis.

Keywords: laboratory, metaphor, phenomenology, pre-service science teachers

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11691 Beyond Typical Textbooks: Adapting Authentic Materials for Engaged Learning in the ELT Classroom

Authors: Fatemeh Miraki

Abstract:

The use of authentic materials in English Language Teaching (ELT) has become increasingly prominent as educators recognize the value of exposing learners to real-world language use and cultural contexts. The integration of authentic materials in ELT aligns with the understanding that language learning is most effective when situated within authentic contexts (Richards & Rodgers, 2001). Tomlinson (1998) highlights the significance of authentic materials in ELT by research indicating that they offer learners exposure to genuine language use and cultural contexts. Tomlinson's work emphasizes the importance of creating meaningful learning experiences through the use of authentic materials. Research by Dörnyei (2001) underscores the potential of authentic materials to enhance students' intrinsic motivation through their relevance to real-life language use. The goal of this review paper is to explore the use of authentic materials in English Language Teaching (ELT) and its impact on language learning. It also discusses best practices for selecting and integrating such authentic materials into ELT curriculum, highlighting the benefits and challenges of using authentic materials to enhance student engagement, motivation, and language proficiency. Drawing on current research and practical examples, this paper provides insights into how teachers can effectively navigate the world of authentic materials to create dynamic and meaningful learning experiences for 21st century ELT learners. The findings of this study advocates for a shift towards embracing authentic materials within the ELT classroom, acknowledging their profound impact on language proficiency, intercultural competence, and learner engagement. It showed the transformative potential of authentic materials, educators can undergo a vibrant and immersive language learning experience, enriched with real-world application and cultural authenticity.

Keywords: authentic materials, ELT Classroom, ELT curriculum, students’ engagement

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