Search results for: Deep learning

Authors: Pajaree Naramitpanich, Natchanok Jansawang, Panwilai Chomchid

Abstract:

The aims of this are compared between the students’ logical thinking abilities of their learning for designing the 5-lesson instructional plans of the 2-instructional methods, namely; the STEM Education and the Creative Learning Process (CLP) for developing students’ logical thinking abilities that a sample consisted of 90 students from two chemistry classes of different learning outcomes in Wapi Phathum School with the cluster random sampling technique was used at the 11th grade level. To administer of their learning environments with the 45-experimenl student group by the STEM Education method and the 45-controlling student group by the Creative Learning Process. These learning different groups were obtained using the 5 instruments; the 5-lesson instructional plans of the STEM Education and the Creative Learning Process to enhance the logical thinking tests on Mineral issue were used. The efficiency of the Creative Learning Processes (CLP) Model and the STEM Education’s innovations of these each five instructional lesson plans based on criteria are higher than of 80/80 standard level with the IOC index from the expert educators. The averages mean scores of students’ learning achievement motives were assessed with the Pre and Post Techniques and Logical Thinking Ability Test (LTAT) and dependent t-test analysis were differentiated between the CLP and the STEM, significantly. Students’ perceptions of their chemistry classroom environment inventories with the MCI with the CLP and the STEM methods also were found, differently. Associations between students’ perceptions of their chemistry classroom learning environment inventories on the CLP Model and the STEM Education learning designs toward their logical thinking abilities toward chemistry, the predictive efficiency of R2 values indicate that 68% and 76% of the variances in students’ logical thinking abilities toward chemistry to their controlling and experimental chemistry classroom learning environmental groups with the MCI were correlated at .05 levels, significantly. Implementations of this result are showed the students’ learning by the CLP of the potential thinking life-changing roles in most their logical thinking abilities that it is revealed that the students perceive their abilities to be highly learning achievement in chemistry group are differentiated with the STEM education of students’ outcomes.

Keywords: design, the lesson instructional plans, the stem education, the creative learning process, logical thinking ability, different, learning outcome, student, chemistry class

Procedia PDF Downloads 321

Authors: Eiman Kattan

Abstract:

This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.

Keywords: conventional neural network, remote sensing, land cover, land use

Procedia PDF Downloads 370

Authors: Ng Liang Shen, Hau Yuan Wen

Abstract:

Arrhythmia analysis of ECG signal plays a major role in diagnosing most of the cardiac diseases. Therefore, a single arrhythmia detection of an electrocardiographic (ECG) record can determine multiple pattern of various algorithms and match accordingly each ECG beats based on Machine Learning supervised learning. These researchers used different features and classification methods to classify different arrhythmia types. A major problem in these studies is the fact that the symptoms of the disease do not show all the time in the ECG record. Hence, a successful diagnosis might require the manual investigation of several hours of ECG records. The point of this paper presents investigations cardiovascular ailment in Electrocardiogram (ECG) Signals for Cardiac Arrhythmia utilizing examination of ECG irregular wave frames via heart beat as correspond arrhythmia which with Machine Learning Pattern Recognition.

Keywords: electrocardiogram, ECG, classification, machine learning, pattern recognition, detection, QRS

Procedia PDF Downloads 376

Authors: U.-B. Schaer, M. Wehr, R. Hodler

Abstract:

Background: Most nursing students require more training time for necessary nursing skills than defined by nursing schools curriculum to acquire basic nursing skills. Given skills training lessons are too brief to enable effective student learning, meaning in-depth skills practice and repetition various learning steps. This increases stress levels and the pressure to succeed for a nursing student with slower learning capabilities. Another possible consequence is that nursing students are less prepared in the required skills for future clinical practice. Intervention: The Bern College of Higher Education of Nursing, Switzerland, started the independent peer practice learning program in 2012. A concept was developed which defines specific aims and content as well as student’s rights and obligations. Students enlist beforehand and order the required materials. They organize themselves and train in small groups in allocated training location in the area of Learning Training and Transfer (LTT). During the peer practice, skills and knowledge can be repeatedly trained and reflected in the peer groups without the presence of a tutor. All invasive skills are practiced only on teaching dummies. This allows students to use all their potential. The students may access learning materials as literature and their own student notes. This allows nursing students to practice their skills and to deepen their knowledge on corresponding with their own learning rate. Results: Peer group discussions during the independent peer practice learning support the students in gaining certainty and confidence in their knowledge and skills. This may improve patient safety in future daily care practice. Descriptive statics show that the number of students who take advantage of the independent peer practice learning increased continuously (2012-2018). It has to be mentioned that in 2012, solely students of the first semester attended the independent peer practice learning program, while in 2018 over one-third of the participating students were in their fifth semester and final study year. It is clearly visible that the demand for independent peer practice learning is increasing. This has to be considered in the development of future teaching curricula.

Keywords: learning program, nursing students, peer learning, skill training

Procedia PDF Downloads 121

Authors: Mohammad Arabi

Abstract:

The development of advanced technologies in the field of signal processing and vibration analysis has enabled more accurate analysis and fault detection in electrical systems. This research investigates the application of temporal and frequency features in detecting faults in electric motor bearings, aiming to enhance fault detection accuracy and prevent unexpected failures. The use of methods such as deep learning algorithms and neural networks in this process can yield better results. The main objective of this research is to evaluate the efficiency and accuracy of methods based on temporal and frequency features in identifying faults in electric motor bearings to prevent sudden breakdowns and operational issues. Additionally, the feasibility of using techniques such as machine learning and optimization algorithms to improve the fault detection process is also considered. This research employed an experimental method and random sampling. Vibration signals were collected from electric motors under normal and faulty conditions. After standardizing the data, temporal and frequency features were extracted. These features were then analyzed using statistical methods such as analysis of variance (ANOVA) and t-tests, as well as machine learning algorithms like artificial neural networks and support vector machines (SVM). The results showed that using temporal and frequency features significantly improves the accuracy of fault detection in electric motor bearings. ANOVA indicated significant differences between normal and faulty signals. Additionally, t-tests confirmed statistically significant differences between the features extracted from normal and faulty signals. Machine learning algorithms such as neural networks and SVM also significantly increased detection accuracy, demonstrating high effectiveness in timely and accurate fault detection. This study demonstrates that using temporal and frequency features combined with machine learning algorithms can serve as an effective tool for detecting faults in electric motor bearings. This approach not only enhances fault detection accuracy but also simplifies and streamlines the detection process. However, challenges such as data standardization and the cost of implementing advanced monitoring systems must also be considered. Utilizing temporal and frequency features in fault detection of electric motor bearings, along with advanced machine learning methods, offers an effective solution for preventing failures and ensuring the operational health of electric motors. Given the promising results of this research, it is recommended that this technology be more widely adopted in industrial maintenance processes.

Keywords: electric motor, fault detection, frequency features, temporal features

Procedia PDF Downloads 47

Authors: Marlies Achenbach

Abstract:

System competencies play a key role to ensure an effective and efficient improvement of production systems. Thus, there can be observed an increasing demand for developing system competencies in industry as well as in engineering education. System competencies consist of the following two main abilities: Evaluating the current state of a production system and developing a target state. The innovative course ‘multi-perspective learning in a real production plant (multi real)’ is developed to create a learning setting that supports the development of these system competencies. Therefore, the setting combines two innovative aspects: First, the Learning takes place in heterogeneous groups formed by students as well as professionals and managers from industry. Second, the learning takes place in a real production plant. This paper presents the innovative didactic concept of ‘multi real’ in detail, which will initially be implemented in October/November 2016 in the industrial engineering, logistics and mechanical master’s program at TU Dortmund University.

Keywords: experiential learning, heterogeneous groups, improving production systems, system competencies

Procedia PDF Downloads 426

Authors: Joanne Rieta Miranda

Abstract:

Learning anatomy and physiology among Deaf Non-Science major students is a challenge. They have this mindset that Anatomy and Physiology are difficult and very technical. In this study, nine (9) deaf students who are business majors were considered. Non-conventional teaching strategies and classroom activities were employed such as cooperative learning, virtual lab, Facebook live, big sky, blood typing, mind mapping, reflections, etc. Of all the activities; the deaf students ranked cooperative learning as the best learning activity. This is where they played doctors. They measured the pulse rate, heart rate and blood pressure of their partner classmate. In terms of mindset, 2 out of 9 students have a growth mindset with some fixed ideas while 7 have a fixed mindset with some growth ideas. All the students passed the course. Three out of nine students got a grade of 90% and above. The teacher was evaluated by the deaf students as very satisfactory with a mean score of 3.54. This means that the learner-centered practices in the classroom are manifested to a great extent.

Keywords: deaf students, learning anatomy and physiology, teaching strategies, learner-entered practices

Procedia PDF Downloads 231

Authors: Fahad Suleiman

Abstract:

The aim of this paper is to study students’ view on mathematics learning in Katsina State Senior Secondary Schools of Nigeria, such as their conceptions of mathematics, attitudes toward mathematics learning, etc. A questionnaire was administered to a random sample of 1,225 senior secondary two (SS II) students of Katsina State in Nigeria. The data collected showed a clear picture of the hurdles that affect the teaching and learning of mathematics in our schools. Problems such as logistics and operational which include shortage of mathematics teachers, non–availability of a mathematics laboratory, etc. were identified. It also depicted the substantial trends of changing views and attitudes toward mathematics across secondary schools. Students’ responses to the conception of mathematics were consistent and they demonstrated some specific characteristics of their views in learning mathematics. This survey has provided useful information regarding students’ needs and aspirations in mathematics learning for curriculum planners and frontline teachers for future curriculum reform and implementation.

Keywords: attitudes, mathematics, students, teacher

Procedia PDF Downloads 327

Authors: Eleni Giouli

Abstract:

Distance learning provides a flexible approach to education, enabling busy learners to complete their coursework at their own pace, on their own schedule, and from a convenient location. This flexibility combined with a series of other issues; make the benefits of lifelong distance learning numerous. The purpose of the paper is to investigate whether distance education can contribute to the improvement of adult skills in Greece, highlighting in this way the necessity of the lifelong distance learning. To investigate this goal, a questionnaire is constructed and analyzed based on responses from 3,016 attendees of lifelong distance learning programs in the e-learning of the National and Kapodistrian University of Athens in Greece. In order to do so, a series of relationships is examined including the effects of a) the gender, b) the previous educational level, c) the current employment status, and d) the method used in the distance learning program, on the development of new general, technical, administrative, social, cultural, entrepreneurial and green skills. The basic conclusions that emerge after using a binary logistic framework are that the following factors are critical in order to develop new skills: the gender, the education level and the educational method used in the lifelong distance learning program. The skills more significantly affected by those factors are the acquiring new skills in general, as well as acquiring general, language and cultural, entrepreneurial and green skills, while for technical and social skills only gender and educational method play a crucial role. Moreover, routine skills and social skills are not affected by the four factors included in the analysis.

Keywords: adult skills, distance learning, education, lifelong learning

Procedia PDF Downloads 137

Authors: Mostert Jacques, Gulseven Osman, Williams Courtney

Abstract:

The Covid-19 pandemic caused unparalleled disruption in the lives of the majority of the world. This included school closures and introduction of Online Learning. In this article we investigated the impact of distance learning on the self-efficacy and anxiety levels experienced by educators in South Africa. We surveyed 60 respondents from Independent Schools using a Likert Scale rating of 0 to 4. The results suggested that despite experiencing moderate anxiety, educators showed a sense of high self-efficacy during distance learning. This was specifically true for those with underlying health concerns. There was no significant difference between how the different genders experienced anxiety and self-efficacy. Further research into the impact on learners’ anxiety levels during distance learning will provide policymakers and educators with a better understanding of how the use of technology is influencing the effectiveness of teaching, learning, and assessment.

Keywords: COVID-19, education, self-efficacy, anxiety

Procedia PDF Downloads 205

Authors: Karen Butler

Abstract:

Johnson C. Smith University, one of the nation’s oldest Historically Black Colleges and Universities, has a strong history of service learning and community service. We first integrated service learning and peer education into health education courses in the spring of 2000. Students enrolled in the classes served as peer educators for the semester. Since then, the program has evolved and expanded but remains an integral part of several courses. The purpose of this session is to describe our program in terms of development, successes, and obstacles, and feedback received. A detailed description of the service learning component in HED 235: Drugs and Drug Education and HED 337: Environmental Health will be provided. These classes are required of our Community Health majors but are also popular electives for students in other disciplines. Three sources of student feedback were used to evaluate and continually modify the component: the SIR II course evaluation, service learning reflection papers, and focus group interviews. Student feedback has been largely positive. When criticism was given, it was thoughtful and constructive – given in the spirit of making it better for the next group. Students consistently agreed that the service learning program increased their awareness of pertinent health issues; that both the service providers and service recipients benefited from the project; and that the goals/issues targeted by the service learning component fit the objectives of the course. Also, evidence of curriculum and learning enhancement was found in the reflection papers and focus group sessions. Service learning sets up a win-win situation. It provides a way to respond to campus and community health needs while enhancing the curriculum, as students learn more by doing things that benefit the health and wellness of others. Service learning is suitable for any health education course and any target audience would welcome the effort.

Keywords: black colleges, community health, health education, service learning

Procedia PDF Downloads 340

Authors: S. Art-in

Abstract:

This research was a survey research. The objective of this study was to study current situation and need in learning management for developing the analytical thinking of teachers in basic education of Thailand. The target group consisted of 400 teachers teaching in basic education level. They were selected by multi-stage random sampling. The instrument used in this study was the questionnaire asking current situation and need in learning management for developing the analytical thinking, 5 level rating scale. Data were analyzed by calculating the frequency, mean, standard deviation, percentage and content analysis. The research found that: 1) For current situation, the teachers provided learning management for developing analytical thinking, in overall, in “high” level. The issue with lowest level of practice: the teachers had competency in designing and establishing the learning management plan for developing the students’ analytical thinking. Considering each aspect it was found that: 1.1) the teacher aspect; the issue with lowest level of practice was: the teachers had competency in designing and establishing the learning management plan for developing the students’ analytical thinking, and 1.2) the learning management aspect for developing the students’ analytical thinking, the issue with lowest level of practice was: the learning activities provided opportunity for students to evaluate their analytical thinking process in each learning session. 2) The teachers showed their need in learning management for developing the analytical thinking, in overall, in “the highest” level. The issue with highest level of the need was: to obtain knowledge and competency in model, technique, and method for learning management or steps of learning management for developing the students’ analytical thinking. Considering each aspect it was found that: 2.1) teacher aspect; the issue with highest level of the need was: to obtain knowledge and comprehension in model, technique, and method for learning management or steps of learning management for developing the students’ analytical thinking, and 2.2) learning management aspect for developing the analytical thinking, the issue with highest level of need consisted of the determination of learning activities as problem situation, and the opportunity for students to comprehend the problem situation as well as practice their analytical thinking in order to find the answer.

Keywords: current situation and need, learning management, analytical thinking, teachers in basic education level, Thailand

Procedia PDF Downloads 352

Authors: Victoria Appatova

Abstract:

internal and external, that are largely shaped by the student’s perceptions. Since 2006, the ELE concept has been studied by an international group of scholars through the creation of an ELE survey which was administered in nine countries and translated into five languages. The survey compares students’ perceptions of their learning environments and self-efficacy across A student’s effective learning environment (ELE) is comprised of multiple factors, both cultures as well as distinguishes similarities and differences in the students’ needs related to their learning. The main objectives of this international project include the following: Determine a system of components constituting ELE from the perspective of students and other academic populations Analyze students’ expectations, and their chances to succeed in college based on their expectations Conceptualize a comprehensive approach for assessing the effectiveness of a learning environment Compare the actualization of the ELE concept in American schools versus other national educational systems Compare student perceptions of ELE with those of faculty, administrators, and professional staff Four major factors influencing student learning across cultures and various national educational systems were determined: students’ initiative in using support services; learning skills; external comfort; and curriculum. Recent changes in the students’ perceptions, resulting from technology advances and a rapid shift to online learning, are being explored. The findings call for administrative and pedagogical actions which would cultivate more equitable education systems.

Keywords: learning environment, student perception, global perspectives, self-efficacy

Procedia PDF Downloads 88

Authors: Abdulaziz Fageeh

Abstract:

This study investigates the integration of artificial intelligence (AI) within the landscape of language learning and teaching, exploring its potential benefits and challenges. Employing a mixed-methods approach, the research draws upon a comprehensive literature review, case studies, user reviews, and in-depth interviews with educators and students. Findings demonstrate that AI tools, including language learning apps and writing assistants, can enhance personalization, improve writing skills, and increase accessibility to language learning resources. However, the study also highlights concerns regarding over-reliance on AI, potential accuracy and reliability issues, and ethical implications such as data privacy and potential bias. User and educator perspectives emphasize the importance of balancing AI with traditional teaching methods, fostering critical thinking skills, and addressing potential misuse. The study concludes by underscoring the need for ongoing research and development to ensure responsible AI integration in language learning, focusing on pedagogical strategies, ethical frameworks, and the long-term impact of AI on learning outcomes.

Keywords: artificial intelligence, language learning, education, technology, ethical considerations, user perceptions

Procedia PDF Downloads 16

Authors: Anjalika Fernando, Banuka Athuraliya

Abstract:

This paper presents a comprehensive approach for converting Sinhala Sign Language (SSL) into grammatically correct sentences using Natural Language Processing (NLP) techniques in real-time. While previous studies have explored various aspects of SSL translation, the research gap lies in the absence of grammar checking for SSL. This work aims to bridge this gap by proposing a two-stage methodology that leverages deep learning models to detect signs and translate them into coherent sentences, ensuring grammatical accuracy. The first stage of the approach involves the utilization of a Long Short-Term Memory (LSTM) deep learning model to recognize and interpret SSL signs. By training the LSTM model on a dataset of SSL gestures, it learns to accurately classify and translate these signs into textual representations. The LSTM model achieves a commendable accuracy rate of 94%, demonstrating its effectiveness in accurately recognizing and translating SSL gestures. Building upon the successful recognition and translation of SSL signs, the second stage of the methodology focuses on improving the grammatical correctness of the translated sentences. The project employs a Neural Machine Translation (NMT) architecture, consisting of an encoder and decoder with LSTM components, to enhance the syntactical structure of the generated sentences. By training the NMT model on a parallel corpus of Sinhala wrong sentences and their corresponding grammatically correct translations, it learns to generate coherent and grammatically accurate sentences. The NMT model achieves an impressive accuracy rate of 98%, affirming its capability to produce linguistically sound translations. The proposed approach offers significant contributions to the field of SSL translation and grammar correction. Addressing the critical issue of grammar checking, it enhances the usability and reliability of SSL translation systems, facilitating effective communication between hearing-impaired and non-sign language users. Furthermore, the integration of deep learning techniques, such as LSTM and NMT, ensures the accuracy and robustness of the translation process. This research holds great potential for practical applications, including educational platforms, accessibility tools, and communication aids for the hearing-impaired. Furthermore, it lays the foundation for future advancements in SSL translation systems, fostering inclusive and equal opportunities for the deaf community. Future work includes expanding the existing datasets to further improve the accuracy and generalization of the SSL translation system. Additionally, the development of a dedicated mobile application would enhance the accessibility and convenience of SSL translation on handheld devices. Furthermore, efforts will be made to enhance the current application for educational purposes, enabling individuals to learn and practice SSL more effectively. Another area of future exploration involves enabling two-way communication, allowing seamless interaction between sign-language users and non-sign-language users.In conclusion, this paper presents a novel approach for converting Sinhala Sign Language gestures into grammatically correct sentences using NLP techniques in real time. The two-stage methodology, comprising an LSTM model for sign detection and translation and an NMT model for grammar correction, achieves high accuracy rates of 94% and 98%, respectively. By addressing the lack of grammar checking in existing SSL translation research, this work contributes significantly to the development of more accurate and reliable SSL translation systems, thereby fostering effective communication and inclusivity for the hearing-impaired community

Keywords: Sinhala sign language, sign Language, NLP, LSTM, NMT

Procedia PDF Downloads 104

Authors: P. R. Prabhu, S. M. Kulkarni, S. S. Sharma, K. Jagannath, Achutha Kini U.

Abstract:

In the present study, response surface methodology has been used to optimize turn-assisted deep cold rolling process of AISI 4140 steel. A regression model is developed to predict surface hardness and surface roughness using response surface methodology and central composite design. In the development of predictive model, deep cold rolling force, ball diameter, initial roughness of the workpiece, and number of tool passes are considered as model variables. The rolling force and the ball diameter are the significant factors on the surface hardness and ball diameter and numbers of tool passes are found to be significant for surface roughness. The predicted surface hardness and surface roughness values and the subsequent verification experiments under the optimal operating conditions confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface hardness and surface roughness is calculated as 0.16% and 1.58% respectively. Using the optimal processing parameters, the hardness is improved from 225 to 306 HV, which resulted in an increase in the near surface hardness by about 36% and the surface roughness is improved from 4.84µm to 0.252 µm, which resulted in decrease in the surface roughness by about 95%. The depth of compression is found to be more than 300µm from the microstructure analysis and this is in correlation with the results obtained from the microhardness measurements. Taylor Hobson Talysurf tester, micro Vickers hardness tester, optical microscopy and X-ray diffractometer are used to characterize the modified surface layer.

Keywords: hardness, response surface methodology, microstructure, central composite design, deep cold rolling, surface roughness

Procedia PDF Downloads 422

Authors: Yinghui Shang, Ziqing Zhou, Rong Han, Hang Wang, Xiaodi Liu, Yong Yang

Abstract:

The design of advanced amorphous solids, such as metallic glasses, with targeted properties through artificial intelligence signifies a paradigmatic shift in physical metallurgy and materials technology. Here, we developed a machine-learning architecture that facilitates the generation of metallic glasses with targeted multifunctional properties. Our architecture integrates the state-of-the-art unsupervised generative adversarial network model with supervised models, allowing the incorporation of general prior knowledge derived from thousands of data points across a vast range of alloy compositions, into the creation of data points for a specific type of composition, which overcame the common issue of data scarcity typically encountered in the design of a given type of metallic glasses. Using our generative model, we have successfully designed copper-based metallic glasses, which display exceptionally high hardness or a remarkably low modulus. Notably, our architecture can not only explore uncharted regions in the targeted compositional space but also permits self-improvement after experimentally validated data points are added to the initial dataset for subsequent cycles of data generation, hence paving the way for the customized design of amorphous solids without human intervention.

Keywords: metallic glass, artificial intelligence, mechanical property, automated generation

Procedia PDF Downloads 56

Authors: Jude Harrison

Abstract:

Child protection is a complex and sensitive practice. The core responsibility is the care and protection of children and young people who have been subject to or who are at risk from abuse and neglect. The work involves investigating allegations of harm, preparing for and making representations to the legal system, and case planning and management across a continuum of complicated care interventions. Professionals’ learning for child protection practice is evident in a range of literature investigating multiple learning processes such as university preparation, student placements, professional supervision, training, and other post-qualifying professional development experiences at work. There is, however, very limited research into how caseworkers learn in and through their daily practice. Little is known, therefore, about how learning at work unfolds for caseworkers, the dimensions in which it can be understood or the ways in which it can be best facilitated and supported. Compounding this, much of the current child protection learning literature reflects an orthodox conception of learning as mentalistic and individualised, in which knowledge is typically understood as abstract theory or as technical skill or competency. This presentation outlines key findings from a PhD research study that explored learning at work for statutory child protection caseworkers from an alternative interpretation of learning using a practice theory approach. Practice theory offers an interpretation of learning as performative and grounded in situated experience. The findings of the study show that casework practice is both a mode and site of learning. The study was ethnographic in design based and followed 17 child protection caseworkers via in-depth interviews, observations and participant reflective journaling. Inductive and abductive analysis was used to organise and interpret the data and expand analysis, leading to themes. Key findings show learning to be a sociomaterial property of doing; the social ontological character of learning; and teleoaffectivity as a feature of learning. The findings contribute to theoretical and practical understandings of learning and practice in child protection, child welfare and the professional learning literature more broadly. The findings have potential to contribute to policy directions at state, territory and national levels to enhance child protection practice and systems.

Keywords: adiult learning, workplace learning, child welfare, sociomaterial, practice theory

Procedia PDF Downloads 75

Authors: J. Kontoleon, D.Gall, M.Pidskalny

Abstract:

FisherONE offers a distinct pedagogic model for senior secondary education that integrates advanced technology to meet the learning needs of Year 11 and 12 students across Catholic schools in Queensland. As a fully online platform, FisherONE employs pedagogy that combines flexibility with personalized, data-driven learning. The model leverages tools like the MaxHub hybrid interactive system and AI-powered learning assistants to create tailored learning pathways that promote student autonomy and engagement. This paper examines FisherONE’s success in employing pedagogic strategies through technology. Initial findings suggest that students benefit from the blended approach of virtual assessments and real-time support, even as AI-assisted tools remain in the proof-of-concept phase. The study outlines how FisherONE plans to continue refining its educational methods to better serve students in distance learning environments, specifically in challenging subjects like physics. The integration of technology in FisherONE enhances the effectiveness of teaching and learning, addressing common challenges in online education by offering scalable, individualized learning experiences. This approach demonstrates the future potential of technology in education and the role it can play in fostering meaningful student outcomes.

Keywords: AI-assisted learning, innovative pedagogy, personalized learning, senior education, technology in education

Procedia PDF Downloads 18

Authors: Vincent Liu

Abstract:

Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

Procedia PDF Downloads 61

Authors: Nanyonjo Juliet

Abstract:

Across Sub-Saharan Africa, it’s increasingly becoming an absolute necessity for either parents or governments to encourage learners, most particularly those attending high schools, to study a second or foreign language other than the “official language” or the language of instruction in schools. The major second or foreign languages under consideration include but are not necessarily limited to English, French, German, Arabic, Swahili/Kiswahili, Spanish and Chinese. The benefits of learning a second (foreign) language in the globalized world cannot be underestimated. Amongst others, it has been expounded to especially involve such opportunities related to traveling, studying abroad and widening one’s career prospects. Research has also revealed that beyond these non-cognitive rewards, learning a second language enables learners to become more thoughtful, considerate and confident, make better decisions, keep their brain healthier and generally – speaking, broaden their world views. The methodology of delivering a successful 2nd language – learning process by a professionally qualified teacher is located in motivation. We strongly believe that the psychology involved in teaching a foreign language is of paramount importance to a learner’s successful learning experience. The aim of this paper, therefore, is to explore and show the importance of motivation in the teaching and learning of a given 2nd (foreign) language in the local Ugandan high schools.

Keywords: second language, foreign language, language learning, language teaching, official language, language of instruction, globalized world, cognitive rewards, non-cognitive rewards, learning process, motivation

Procedia PDF Downloads 68

Authors: Mehmet Karabekir

Abstract:

Attack helicopters (AHs) are usually deployed in conventional warfare to destroy armored and mechanized forces of enemy. In addition, AHs are able to perform various tasks in the deep, and close operations – intelligence, surveillance, reconnaissance, air assault operations, and search and rescue operations. Apache helicopters were properly employed in the Gulf Wars and contributed the success of campaign by destroying a large number of armored and mechanized vehicles of Iraq Army. The purpose of this article is to discuss the deployment of AHs in conventional warfare in the light of Gulf Wars. First, the employment of AHs in deep and close operations will be addressed regarding the doctrine. Second, the US armed forces AH-64 doctrinal and tactical usage will be argued in the 1st and 2nd Gulf Wars.

Keywords: attack helicopter, conventional warfare, gulf wars

Procedia PDF Downloads 473

Authors: Mahalingam Palaniandi

Abstract:

Higher education plays vital role in the nation building process for a country and the rest of world. The higher education sector develops the change-agents for the various fields which will help the human-kind wheel to run further. Conventional and traditional class-room based learning and teaching was followed in many decades which is one-to-one and one-to-many. In a way, these are simplest form of learners to be assembled in a class room wherein the teacher used the blackboard to demonstrate the theory and laboratories used for practical. As the technology evolved tremendously for the last 40 years, the teaching and learning environment changed slowly, wherein, the learning community will be anywhere in the world and teacher deliver the content through internet based tools such as video conferencing, web based conferencing tools or E-learning platforms such as Blackboard or noodle. Present day, the mobile technologies plays an important tool to deliver the teaching content on-the-go. Both PC based and mobile based learning technology brought the learning and teaching community together in various aspects. However, as the learning technology also brought various hurdles for learning processes such as plagiarism and not using the reference books entirely as most of the students wants the information instantaneously using internet without actually going to the library to take the notes from the millions of the books which are not available online as e-books which result lack of fundamental knowledge of the concepts complex theories. However, technology is inseparable in human life, now-a-days and every part of it contains piece of information technology right from computers to home appliances. To make use of the IT based learning and teaching at most efficiency, we should have a proper framework and recommendations laid to the learning community in order to derive the maximum efficiency from the IT based teaching and leaning. This paper discusses various IT based tools available for the learning community, efficiency from its usage and recommendations for the suitable framework that needs to be implemented at higher education institutions which makes the learners stronger in both theory as well as real-time knowledge of their studies that is going to be used in their future for the better world.

Keywords: higher education, e-learning, teaching learning, eLearning tools

Procedia PDF Downloads 426

Authors: S. K. Ashiquer Rahman

Abstract:

This paper presents a knowledge mediation platform, “ePLANETe Blue” that addresses the challenge of building knowledge partnerships for higher education. The purpose is to present, as an institutional perception, the ‘ePLANETe' idea and functionalities as a practical and pedagogical innovation program contributing to the collaborative learning goals in higher education. In consequence, the set of functionalities now amalgamated in ‘ePLANETe’ can be seen as an investigation of the challenges of “Collaborative Learning Digital Process.” It can exploit the system to facilitate collaborative education, research and student learning in higher education. Moreover, the platform is projected to support the identification of best practices at explicit levels of action and to inspire knowledge interactions in a “virtual community” and thus to advance in deliberation and learning evaluation of higher education through the engagement of collaborative activities of different sorts.

Keywords: mediation, collaboration, deliberation, evaluation

Procedia PDF Downloads 140

Authors: Ying Zhou, Jian-Hua Wang

Abstract:

Based upon the self-determination theory and self-regulated learning theory, this study examined the predictiveness of goal orientation and self-regulated learning strategies on academic achievement of adult students in distance learning. The results show a positive relation between goal orientation and the use of self-regulated strategies, and academic achievements. A significant and positive indirect relation of mastery goal orientation through self-regulated learning strategies was also found. In addition, results pointed to a positive indirect impact of performance-approach goal orientation on academic achievement. The effort regulation strategy fully mediated this relation. The theoretical and instructional implications are discussed. Interventions can be made to motivate students’ mastery or performance approach goal orientation and help them manage their time or efforts.

Keywords: goal orientation, self-regulated strategies, achievement, adult distance students

Procedia PDF Downloads 274

Authors: Christie DeGregorio

Abstract:

In today's rapidly evolving educational landscape, adult learners are becoming an increasingly significant demographic. These individuals often possess a wealth of life experiences and diverse interests that can greatly influence their learning styles. Recognizing and incorporating these interests into educational practices can lead to enhanced engagement, motivation, and overall learning outcomes for adult learners. This essay aims to explore the significance of incorporating adult learners' interests into learning styles and provide an overview of the methodologies used in related studies. When investigating the incorporation of adult learners' interests into learning styles, researchers have employed various methodologies to gather valuable insights. These methodologies include surveys, interviews, case studies, and classroom observations. Surveys and interviews allow researchers to collect self-reported data directly from adult learners, providing valuable insights into their interests, preferences, and learning styles. Case studies offer an in-depth exploration of individual adult learners, highlighting how their interests can be integrated into personalized learning experiences. Classroom observations provide researchers with a firsthand understanding of the dynamics between adult learners' interests and their engagement within a learning environment. The major findings from studies exploring the incorporation of adult learners' interests into learning styles reveal the transformative impact of this approach. Firstly, aligning educational content with adult learners' interests increases their motivation and engagement in the learning process. By connecting new knowledge and skills to topics they are passionate about, adult learners become active participants in their own education. Secondly, integrating interests into learning styles fosters a sense of relevance and applicability. Adult learners can see the direct connection between the knowledge they acquire and its real-world applications, which enhances their ability to transfer learning to various contexts. Lastly, personalized learning experiences tailored to individual interests enable adult learners to take ownership of their educational journey, promoting lifelong learning habits and self-directedness.

Keywords: integration, personalization, transferability, learning style

Procedia PDF Downloads 74

Authors: Layla Albdr

Abstract:

Saudi Arabia instituted the policy of Sensitizing and Training Stakeholders for E-learning and witnessed wide adoption in many institutions. However, it is at the infancy stage and needs time to develop to mirror the US and UK. The majority of the higher education institutions in Saudi Arabia have adopted E-learning as an alternative to traditional methods to advance education. Conversely, effective implementation of the policy of sensitization and training of stakeholders for E-learning implementation has not been attained because of various challenges. The objectives included determining the challenges and opportunities of the E-learning policy of sensitization and training of stakeholders in Saudi Arabia's higher education and examining if sensitization and training of stakeholder's policy will help promote the implementation of E-learning in institutions. The study employed a descriptive research design based on qualitative analysis. The researcher recruited 295 students and 60 academic staff from four Saudi Arabian universities to participate in the study. An online questionnaire was used to collect the data. The data was then analyzed and reported both quantitatively and qualitatively. The analysis provided an in-depth understanding of the opportunities and challenges of E-learning policy in Saudi Arabian universities. The main challenges identified as internal challenges were the lack of educators’ interest in adopting the policy, and external challenges entailed lack of ICT infrastructure and Internet connectivity. The study recommends encouraging, sensitizing, and training all stakeholders to address these challenges and adopt the policy.

Keywords: e-learning, educational policy, Saudi Arabia, policy of sensitization and training

Procedia PDF Downloads 157

Authors: Nasrin Mohammadhasani, Rosa Angela Fabio

Abstract:

The attention to relevance information is the key element for learning. Otherwise, Attention Deficit Hyperactivity Disorder (ADHD) students have a fuzzy visual pattern that prevents them to attention and remember learning subject. The present study aimed to test the hypothesis that the presence of a pedagogical agent can effectively support ADHD learner's attention and learning outcomes in a multimedia learning environment. The learning environment was integrated with a pedagogical agent, named Koosha as a social peer. This study employed a pretest and posttest experimental design with control group. The statistical population was 30 boys students, age 10-11 with ADHD that randomly assigned to learn with/without an agent in well designed environment for mathematic. The results suggested that experimental and control groups show a significant difference in time when they participated and mathematics achievement. According to this research, using the pedagogical agent can enhance learning of ADHD students by gaining and guiding their attention to relevance information part on display, so it can be considered as asocial cue that provides theme cognitive supports.

Keywords: attention, computer assisted instruction, multimedia learning environment, pedagogical agent

Procedia PDF Downloads 314

Authors: Mahesh Balan U, Rohith Srinivaas Mohanakrishnan, Venkat Subramanian

Abstract:

Positive and unlabeled learning (PU) has gained more attention in both academic and industry research literature recently because of its relevance to existing business problems today. Yet, there still seems to be some existing challenges in terms of validating the performance of PU learning, as the actual truth of unlabeled data points is still unknown in contrast to a binary classification where we know the truth. In this study, we propose a novel PU learning technique based on the Pseudo-F measure, where we address this research gap. In this approach, we train the PU model to discriminate the probability distribution of the positive and unlabeled in the validation and spy data. The predicted probabilities of the PU model have a two-fold validation – (a) the predicted probabilities of reliable positives and predicted positives should be from the same distribution; (b) the predicted probabilities of predicted positives and predicted unlabeled should be from a different distribution. We experimented with this approach on a credit marketing case study in one of the world’s biggest fintech platforms and found evidence for benchmarking performance and backtested using historical data. This study contributes to the existing literature on semi-supervised learning.

Keywords: PU learning, semi-supervised learning, pseudo f measure, classification

Procedia PDF Downloads 235

Authors: Naduni Ranasinghe

Abstract:

E-learning environments are getting more popular than any other due to the impact of COVID19. Even though e-learning is one of the best solutions for the teaching-learning process in the academic process, it’s not without major challenges. Nowadays, machine learning approaches are utilized in the analysis of how behavioral factors lead to better adoption and how they related to better performance of the students in eLearning environments. During the pandemic, we realized the academic process in the eLearning approach had a major issue, especially for the performance of the students. Therefore, an approach that investigates student behaviors in eLearning environments using a data-intensive machine learning approach is appreciated. A hybrid approach was used to understand how each previously told variables are related to the other. A more quantitative approach was used referred to literature to understand the weights of each factor for adoption and in terms of performance. The data set was collected from previously done research to help the training and testing process in ML. Special attention was made to incorporating different dimensionality of the data to understand the dependency levels of each. Five independent variables out of twelve variables were chosen based on their impact on the dependent variable, and by considering the descriptive statistics, out of three models developed (Random Forest classifier, SVM, and Decision tree classifier), random forest Classifier (Accuracy – 0.8542) gave the highest value for accuracy. Overall, this work met its goals of improving student performance by identifying students who are at-risk and dropout, emphasizing the necessity of using both static and dynamic data.

Keywords: academic performance prediction, e learning, learning analytics, machine learning, predictive model

Procedia PDF Downloads 157