Search results for: social learning

Authors: Eva Wagner, Lucely Vargas

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Corporate Social Responsibility (CSR) plays an important role in (large-scale) enterprises’ business strategy in developed and emerging countries. This article approaches CSR in international comparison by examining the CSR reporting of 116 leading companies in Austria, Germany, Colombia and Chile from 2006 to 2010. We have used an independently developed scoring model which analyzes reported CSR-activities using seven dimensions to efficiently assess CSR. The study reveals that there are significant differences in CSR-commitment among countries and regions: German companies, as expected, lead most of the investigated CSR dimensions revealing stronger commitment to CSR than their Austrian, Colombian and Chilean counterparts. Even if Latin American companies lag behind their European counterparts, they exhibit high CSR-performance in the social dimension: corporate giving and philanthropic activities are firmly anchored in the tradition of Latin American companies. This indicates that particular CSR-emphases reflect the political and social circumstances of each individual country.

Keywords: corporate social responsibility, corporate social performance, international comparison

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Authors: Zebider Asire Munyelet, Yibeltal Chanie Manie

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In the modern digital landscape, the increase of social media platforms has become identical to the evolution of online consumer behavior. This study investigates the complicated relationship between social media and the purchasing decisions of online buyers. Through an extensive review of existing literature and empirical research, the aim is to comprehensively analyze the multidimensional impact that social media exerts on the various stages of the online buyer's journey. The investigation encompasses the exploration of how social media platforms serve as influential channels for information dissemination, product discovery, and consumer engagement. Additionally, the study investigates the psychological aspects underlying the role of social media in shaping buyer preferences, perceptions, and trust in online transactions. The methodologies employed include both quantitative and qualitative analyses, incorporating surveys, interviews, and data analytics to derive meaningful insights. Statistical models are applied to distinguish patterns in online buyer behavior concerning product awareness, brand loyalty, and decision-making processes. The expected outcomes of this research contribute not only to the academic understanding of the dynamic interplay between social media and online buyer behavior but also offer practical implications for marketers, e-commerce platforms, and policymakers.

Keywords: social platforms, buyer behavior, consumer behavior, digital era

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Authors: Joy Winston James, Abdul Kadher Jilani

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This review article provides a comprehensive overview of social engineering attacks, specifically those executed through the Kali Linux operating system. It aims to present an in-depth analysis of the background and importance of social engineering in cybersecurity, the tools, and techniques used in these attacks, real-world case studies that demonstrate their effectiveness, and ethical considerations that need to be taken into account while using them. The article highlights the Kali Linux tools that are commonly used in social engineering attacks, including SET, Metasploit, and BeEF, and discusses techniques such as phishing, pretexting, and baiting that are crucial in conducting successful social engineering attacks. It further explores real-world case studies that demonstrate the effectiveness of these techniques, emphasizing the importance of implementing effective countermeasures to reduce the risk of successful social engineering attacks. Moreover, the article sheds light on ethical considerations that need to be taken into account while using social engineering tools, emphasizing the importance of using them ethically and legally. Finally, the article provides potential countermeasures such as two-factor authentication, strong password policies, and regular security audits to help individuals and organizations better protect themselves against this growing threat. By understanding the tools and techniques used in social engineering attacks and implementing appropriate countermeasures, individuals and organizations can minimize the risk of successful social engineering attacks and improve their cybersecurity posture. To illustrate the effectiveness of social engineering attacks, we present real-world case studies that demonstrate how easily individuals and organizations can fall prey to these attacks. We also discuss ethical considerations that must be taken into account while using social engineering tools, emphasizing the need for responsible and legal use of these tools.

Keywords: pen testing, hacking, Kali Linux, social engineering

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Authors: Anamika Devi

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Based on Vygotsky’s cultural, historical theory and Hedegaard’s concept of transition, this study aims to investigate to propose strategies to maintain digital wellbeing of children and parents during and post COVID pandemic. Due COVID 19 pandemic, children and families have been facing new challenges and sudden changes in their everyday life. While children are juggling to adjust themselves in new circumstance of onsite and online learning settings, parents are juggling with their work-life balance. A number of papers have identified that the COVID-19 pandemic has affected the lives of many families around the world in many ways, for example, the stress level of many parents increased, families faced financial difficulties, uncertainty impacted on long term effects on their emotional and social wellbeing. After searching and doing an intensive literature review from 2020 and 2021, this study has found some scholarly articles provided solution or strategies of reducing stress levels of parents and children in this unprecedented time. However, most of them are not underpinned by proper theoretical lens to ensure they validity and success. Therefore, this study has proposed strategies that are underpinned by theoretical lens to ensure their impact on children’s and parents' emotional wellbeing during and post COVID-19 era. The strategies will highlight on activities for positive coping strategies to the best use of family values and digital technologies.

Keywords: onsite and online learning, strategies, emotional wellbeing, tips, and strategies, COVID19

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Authors: Vinayaka Gude Divya Sampath

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The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.

Keywords: deep learning, disaster management, flood prediction, urban flooding

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Authors: Linghui Meng, James Atlas, Deborah Munro

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There is an increasing demand for prosthetics capable of mimicking natural limb movements and hand gestures, but precise movement control of prosthetics using only electrode signals continues to be challenging. This study considers the implementation of machine learning as a means of improving accuracy and presents an initial investigation into hand gesture recognition using models based on electromyographic (EMG) signals. EMG signals, which capture muscle activity, are used as inputs to machine learning algorithms to improve prosthetic control accuracy, functionality and adaptivity. Using logistic regression, a machine learning classifier, this study evaluates the accuracy of classifying two hand gestures from the publicly available Ninapro dataset using two-time series feature extraction algorithms: Time Series Feature Extraction (TSFE) and Convolutional Neural Networks (CNNs). Trials were conducted using varying numbers of EMG channels from one to eight to determine the impact of channel quantity on classification accuracy. The results suggest that although both algorithms can successfully distinguish between hand gesture EMG signals, CNNs outperform TSFE in extracting useful information for both accuracy and computational efficiency. In addition, although more channels of EMG signals provide more useful information, they also require more complex and computationally intensive feature extractors and consequently do not perform as well as lower numbers of channels. The findings also underscore the potential of machine learning techniques in developing more effective and adaptive prosthetic control systems.

Keywords: EMG, machine learning, prosthetic control, electromyographic prosthetics, hand gesture classification, CNN, computational neural networks, TSFE, time series feature extraction, channel count, logistic regression, ninapro, classifiers

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Authors: Aziza Tahar Djebbar

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Throughout American history, many American presidents have tried to create new reforms to enhance the living conditions of the American citizens and promote their welfare. Among these reforms were those dealing with health care, education, as well as social security, which would facilitate accordingly the evolution of the American welfare state. After the New Deal, from 1945 to 1969, American presidents sought to carry out and enlarge the scope of the welfare state that emerged during the Roosevelt Administration by introducing new social reforms. Yet, there were some American presidents who succeeded, and there were some presidents who failed.The task of this research work is to depict the postwar period from 1945 to 1969. Some light will be shed on the main causes that led to the delay of many programs from 1945 to 1960. Further, the focus will be on the main factors that contributed to the reappearance of many social reforms and the dramatic expansion of the welfare state all along the 1960s.

Keywords: new deal, great society, medicaid, medicare, war on poverty, social reforms, welfare reforms

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Authors: Aysen Celen Ozturk, Hatice Dulger

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University may be defined as a teaching institution consisting of faculties, institutes, colleges, and units that have undergraduate and graduate education, scientific research and publications. It has scientific autonomy and public legal personality. Today, universities are not only the institutions in which students and lecturers experience education, training and scientific work. They also offer social, cultural and artistic activities that strengthen the link with the city. This also incorporates all city users into the campus borders. Thus, universities contribute to social and individual development of the country by providing science, art, socio-cultural development, communication and socialization with people of different cultural and social backgrounds. Moreover, universities provide an active social life, where the young population is the majority. This enables the sense of belonging to the users to develop, to increase the interaction between academicians and students, and to increase the learning / producing community by continuing academic sharing environments outside the classrooms. For this reason, besides academic spaces in university campuses, the users also need closed and open spaces where they can socialize, spend time together and relax. Public open spaces are the most important social spaces that individuals meet, express themselves and share. Individuals belonging to different socio-cultural structures and ethnic groups maintain their social experiences with the physical environment they are in, the outdoors, and their actions and sharing in these spaces. While university campuses are being designed for their individual and social development roles, user needs must be determined correctly and design should be realized in this direction. While considering that requirements may change over time, user satisfaction should be questioned at certain periods and new arrangements should be made in existing applications in the direction of current demands. This study aims to determine the user requirements through the case of Eskişehir Osmangazi University, Meşelik Campus / Turkey. Post Occupancy Evaluation (POE) questionnaire, cognitive mapping and deep interview methods are used in the research process. All these methods show that the students, academicians and other officials in the Meşelik Campus of Eskişehir Osmangazi University find way finding elements insufficient and are in need of efficient landscape design and social spaces. This study is important in terms of determining the needs of the users as a design input. This will help improving the quality of common space in Eskişehir Osmangazi University and in other similar universities.

Keywords: university campuses, public open space, user requirement, post occupancy evaluation

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Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

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Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.

Keywords: basketball, deep learning, feature extraction, single-camera, tracking

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Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li

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With the widespread popularity of mobile devices and the development of artificial intelligence (AI), deep learning (DL) has been extensively applied in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace; a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Moreover, using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. We conducted an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace has a more robust performance than FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.

Keywords: mobile computing, deep learning apps, sensitive information, static analysis

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Authors: Hao Li, Guy Y. Cornejo Maceda, Yiqing Li, Jianguo Tan, Marek Morzynski, Bernd R. Noack

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We propose an automated analysis of the flow control behaviour from an ensemble of control laws and associated time-resolved flow snapshots. The input may be the rich database of machine learning control (MLC) optimizing a feedback law for a cost function in the plant. The proposed methodology provides (1) insights into the control landscape, which maps control laws to performance, including extrema and ridge-lines, (2) a catalogue of representative flow states and their contribution to cost function for investigated control laws and (3) visualization of the dynamics. Key enablers are classification and feature extraction methods of machine learning. The analysis is successfully applied to the stabilization of a mixing layer with sensor-based feedback driving an upstream actuator. The fluctuation energy is reduced by 26%. The control replaces unforced Kelvin-Helmholtz vortices with subsequent vortex pairing by higher-frequency Kelvin-Helmholtz structures of lower energy. These efforts target a human interpretable, fully automated analysis of MLC identifying qualitatively different actuation regimes, distilling corresponding coherent structures, and developing a digital twin of the plant.

Keywords: machine learning control, mixing layer, feedback control, model-free control

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Authors: Fariba Ebrahimi, Mehdi Ghorbani, Ali Salajegheh

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Comprehensively water management considers economic, environmental, technical and social and also sustainability of water resources for future generations. Grassland management implies cooperative approach and involves all stakeholders and also introduces issues to managers, decision and policy makers. Solving these issues needs integrated and system approach. According to the recognition of actors or key persons in necessary to apply cooperative management of Water. Therefore, based on stakeholder analysis and social network analysis can be used to demonstrate the most effective actors for environmental decisions. In this research, social powers according are specified to social network approach at Water utilizers’ level of Natural in Jirood catchment of Latian basin. In this paper, utilizers of water resources were recognized using field trips and then, trust and collaboration matrix produced using questionnaires. In the next step, degree centrality index were Examined. Finally, geometric position of each actor was illustrated in the network. The results of the research based on centrality index have a key role in recognition of cooperative management of Water in Jirood and also will help managers and planners of water in the case of recognition of social powers in order to organization and implementation of sustainable management of Water.

Keywords: social network analysis, water co-management, social power, centrality index, local stakeholders network, Jirood catchment

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Authors: Pi-Lan Yang

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It is controversial which type of gloss condition (i.e., gloss language or gloss position) is more effective in second or foreign language (L2) vocabulary learning. The present study compared the performance on learning ten English words in the conditions of L2 English reading with no glosses and with glosses of Chinese equivalents/translations and L2 English definitions at the side of a page and at an attached sheet for low-intermediate Chinese-speaking learners of English, who were technology university students in Taiwan. It is found first that the performances on the immediate posttest and the delayed posttest were overall better in the gloss condition than those in the no-gloss condition. Next, it is found that the glosses of Chinese translations were more effective and sustainable than those of L2 English definitions. Finally, the effects of L2 English glosses at the side of a page were observed to be less sustainable than those at an attached sheet. In addition, an opinion questionnaire used also showed a preference for the glosses of Chinese translations in L2 English reading. These results would be discussed in terms of automated lexical access, sentence processing mechanisms, and the trade-off nature of storage and processing functions in working memory system, proposed by the capacity theory of language comprehension.

Keywords: glosses of Chinese equivalents/translations, glosses of L2 English definitions, L2 vocabulary learning, L2 English reading

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Authors: Hsiu-Hua Cheng

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Recently, the competition between websites becomes intense. How to make users “adopt” their websites is an issue of urgent importance for online communities companies. Social procedures (such as social influence) can possibly explain how and why users’ technologies usage behaviors affect other people to use the technologies. This study proposes two types of social influences on the initial usage of Facebook Check In-friends and group members. Besides, this study indicates that Facebook friends’ previous usage of Facebook Check In and Facebook group members’ previous usage of Facebook Check In will positively influence focal actors’ Facebook Check In adoption intention. The article concludes with contributions to academic research and practice.

Keywords: social influence, adoption intention, facebook check in, previous usage behavior

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Authors: Shamshuddin K., Nagaraj Vannal, Diwakar Kulkarni

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This paper presents details of teaching and learning pedagogical techniques attempted for the undergraduate engineering program to improve the concentration span of students in a classroom. The details of activities such as valid statement, quiz competition, classroom paper, group work and product marketing to make the students remain active for the entire class duration and to improve presentation skills are presented. These activities shown tremendous improvement in student’s performance in academics, also in asking questions, concept understanding and interaction with the course instructor. With these pedagogical activities we are able to achieve Program outcome elements and ABET Program outcomes such as d, i, g and h which are difficult to achieve through the conventional teaching methods.

Keywords: activities, pedagogy, interactive learning, valid statement, quiz competition, classroom papers, group work, product marketing

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Authors: Apipol Penkitti

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The new normal or a new way of life stemmed from the COVID-19 outbreak, gave rise to a new form of social media: audio-based social platforms (ABSPs), known as Clubhouse, Twitter space, and Facebook live audio room. These platforms, on which audio-based communication is featured, became popular in a short span of time. The objective of the research study is to understand ABSPs users’ behaviors in Thailand. The study, in which functional attitude theory, uses and gratifications theory, and social influence theory are referred to, is conducted through consumer perceived utilitarian, hedonic, and social value that affect engagement. This research study is mixed method paradigm, utilizing Model of Triangulation as its framework. The data acquisition is proceeded through questionnaires from a sample of 384 male, female and LGBTQA+ individuals aged 25 - 34 who, from various occupations, have used audio-based social platform applications. This research study employs the structural equation modeling to analyze the relationships between variables, and it uses the semi - structured interviewing to comprehend the rationality of the variables in the study. The study found that hedonic value directly affects engagement.

Keywords: audio based social platform, engagement, hedonic, perceived value, social, utilitarian

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Authors: María-Dolores Olvera-Lobo, Bryan John Robinson, Juncal Gutierrez-Artacho

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Graduates are equipped with a wide range of generic competencies which complement solid curricular competencies and facilitate their access to the labour market in diverse fields and careers. However, some generic competencies such as instrumental, personal and systemic competencies related to teamwork and interpersonal communication skills, decision-making and organization skills are seldom taught explicitly and even less often assessed. In this context, translator training has embraced a broad range of competencies specified in the undergraduate program currently taught at universities and opens up the learning experience to cover areas often ignored due to the difficulties inherent in both teaching and assessment. In practice, translator training combines two well-established approaches to teaching/learning: project-based learning and genuinely cooperative – or merely collaborative – learning. Our professional approach to translator training is a model focused on and adapted to the teleworking context of professional translation and presented through the medium of blended e-learning. Teamwork-related competencies are extremely relevant, and they require explicit and implicit teaching so that graduates can be confident about their capacity to make their way in professional contexts. In order to highlight the importance of teamwork and intra-team relationships beyond the classroom, we aim to raise awareness of teamwork processes so as to empower translation students in managing their interaction and ensure that they gain valuable pre-professional experience. With these objectives, at the University of Granada (Spain) we have developed a range of classroom activities and assessment tools. The results of their application are summarized in this study.

Keywords: blended learning, collaborative teamwork, cross-curricular competencies, higher education, intra-team relationships, students’ perceptions, translator training

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Authors: Romisaa Ali

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The Policy Gradient approach is one of the deep reinforcement learning families that combines deep neural networks (DNN) with reinforcement learning RL to discover the optimum of the control problem through experience gained from the interaction between the robot and its surroundings. In contrast to earlier policy gradient algorithms, which were unable to handle these two types of error because of over-or under-estimation introduced by the deep neural network model, this article will discuss the state-of-the-art SOTA policy gradient technique, trust region policy optimization (TRPO), by applying this method in various environments compared to another policy gradient method, the Proximal Policy Optimization (PPO), to explain their robust optimization, using this SOTA to gather experience data during various training phases after observing the impact of hyper-parameters on neural network performance.

Keywords: deep neural networks, deep reinforcement learning, proximal policy optimization, state-of-the-art, trust region policy optimization

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Authors: Cristina Maria Ribeiro Martins Pereira Caridade, Ana Rita Ferreira Morais

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The use of computational tools has become essential in the context of interactive learning, especially in engineering education. In the medical industry, teaching medical image processing techniques is a crucial part of training biomedical engineers, as it has integrated applications with healthcare facilities and hospitals. The aim of this article is to present a teaching-learning simulation tool developed in MATLAB using a graphical user interface for medical image fusion that explores different image fusion methodologies and processes in combination with image pre-processing techniques. The application uses different algorithms and medical fusion techniques in real time, allowing you to view original images and fusion images, compare processed and original images, adjust parameters, and save images. The tool proposed in an innovative teaching and learning environment consists of a dynamic and motivating teaching simulation for biomedical engineering students to acquire knowledge about medical image fusion techniques and necessary skills for the training of biomedical engineers. In conclusion, the developed simulation tool provides real-time visualization of the original and fusion images and the possibility to test, evaluate and progress the student’s knowledge about the fusion of medical images. It also facilitates the exploration of medical imaging applications, specifically image fusion, which is critical in the medical industry. Teachers and students can make adjustments and/or create new functions, making the simulation environment adaptable to new techniques and methodologies.

Keywords: image fusion, image processing, teaching-learning simulation tool, biomedical engineering education

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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There has been a need in recent years to predict student academic achievement prior to graduation. This is to assist them in improving their grades, especially for those who have struggled in the past. The purpose of this research is to use supervised learning techniques to create a model that predicts student academic progress. Many scholars have developed models that predict student academic achievement based on characteristics including smoking, demography, culture, social media, parent educational background, parent finances, and family background, to mention a few. This element, as well as the model used, could have misclassified the kids in terms of their academic achievement. As a prerequisite to predicting if the student will perform well in the future on related courses, this model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester. With a 96.7 percent accuracy, the model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost. This model is offered as a desktop application with user-friendly interfaces for forecasting student academic progress for both teachers and students. As a result, both students and professors are encouraged to use this technique to predict outcomes better.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Alvyra Galkienė, Ona Monkevičienė

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The full participation of all pupils in the overall educational process is defined by the concept of inclusive education, which is gradually evolving in education policy and practice. It includes the full participation of all pupils in a shared learning experience and educational practices that address barriers to learning. Inclusive education applying the principles of Universal Design for Learning (UDL), which includes promoting students' involvement in learning processes, guaranteeing a deep understanding of the analysed phenomena, initiating self-directed learning, and using e-tools to create a barrier-free environment, is a prerequisite for the personal success of each pupil. However, the sustainability of quality education is affected by the transformation of education systems. This was particularly evident during the period of the forced transition from contact to distance education in the COVID-19 pandemic. Research Problem: The transformation of the educational environment from real to virtual one and the loss of traditional forms of educational support highlighted the need for new research, revealing the individual profiles of teachers using UDL-based learning and the pathways of sustainable transfer of successful practices to non-conventional learning environments. Research Methods: In order to identify individual latent teacher profiles that encompass the essential components of UDL-based inclusive teaching and direct leadership of students' learning, the quantitative analysis software Mplius was used for latent profile analysis (LPA). In order to reveal proven, i.e., sustainable, pathways for the transit of the components of UDL-based inclusive learning to distance learning, latent profile transit analysis (LPTA) via Mplius was used. An online self-reported questionnaire was used for data collection. It consisted of blocks of questions designed to reveal the experiences of subject teachers in contact and distance learning settings. 1432 Lithuanian, Latvian, and Estonian subject teachers took part in the survey. Research Results: The LPA analysis revealed eight latent teacher profiles with different characteristics of UDL-based inclusive education or traditional teaching in contact teaching conditions. Only 4.1% of the subject teachers had a profile characterised by a sustained UDL approach to teaching: promoting pupils' self-directed learning; empowering pupils' engagement, understanding, independent action, and expression; promoting pupils' e-inclusion; and reducing the teacher's direct supervision of the students. Other teacher profiles were characterised by limited UDL-based inclusive education either due to the lack of one or more of its components or to the predominance of direct teacher guidance. The LPTA analysis allowed us to highlight the following transit paths of teacher profiles in the extreme conditions of the transition from contact to distance education: teachers staying in the same profile of UDL-based inclusive education (sustainable transit) or jumping to other profiles (unsustainable transit in case of barriers), and teachers from other profiles moving to this profile (ongoing transit taking advantage of the changed new possibilities in the teaching process).

Keywords: distance education, latent teacher profiles, sustainable transit, UDL

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Authors: Thomas Turner

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Due to the Covid-19 pandemic alternative ways of delivering dental education were required. As a result, many institutions moved teaching online. The impact of this is poorly understood. Is online problem-based learning (PBL) and case-based learning (CBL) effective and is it suitable in the post-pandemic era? PBL and CBL are both types of interactive, group-based learning which are growing in popularity within many dental schools. PBL was first introduced in the 1960’s and can be defined as learning which occurs from collaborative work to resolve a problem. Whereas CBL encourages learning from clinical cases, encourages application of knowledge and helps prepare learners for clinical practice. To evaluate the use of online PBL and CBL. A literature search was conducted using the CINAHL, Embase, PubMed and Web of Science databases. Literature was also identified from reference lists. Studies were only included from dental education. Seven suitable studies were identified. One of the studies found a high learner and facilitator satisfaction rate with online CBL. Interestingly one study found learners preferred CBL over PBL within an online format. A study also found, that within the context of distance learning, learners preferred a hybrid curriculum including PBL over a traditional approach. A further study pointed to the limitations of PBL within an online format, such as reduced interaction, potentially hindering the development of communication skills and the increased time and technology support required. An audience response system was also developed for use within CBL and had a high satisfaction rate. Interestingly one study found achievement of learning outcomes was correlated with the number of student and staff inputs within an online format. Whereas another study found the quantity of learner interactions were important to group performance, however the quantity of facilitator interactions was not. This review identified generally favourable evidence for the benefits of online PBL and CBL. However, there is limited high quality evidence evaluating these teaching methods within dental education and there appears to be limited evidence comparing online and faceto-face versions of these sessions. The importance of the quantity of learner interactions is evident, however the importance of the quantity of facilitator interactions appears to be questionable. An element to this may be down to the quality of interactions, rather than just quantity. Limitations of online learning regarding technological issues and time required for a session are also highlighted, however as learners and facilitators get familiar with online formats, these may become less of an issue. It is also important learners are encouraged to interact and communicate during these sessions, to allow for the development of communication skills. Interestingly CBL appeared to be preferred to PBL in an online format. This may reflect the simpler nature of CBL, however further research is required to explore this finding. Online CBL and PBL appear promising, however further research is required before online formats of these sessions are widely adopted in the post-pandemic era.

Keywords: case-based learning, online, problem-based learning, remote, virtual

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Authors: Andrew Kipp

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Student absenteeism is harmful to both the school and the absentee student. One approach to improving student absenteeism is targeting contextual factors within the students’ learning environment. However, contemporary literature has not taken an ecological agency approach to understanding student absenteeism. Ecological agency is a theoretical framework that magnifies the interplay between the environment and the actions of people within the environment. To elaborate, the person’s personal history and aspirations and the environmental conditions provide potential outlets or restrictions to their intended action. The framework provides the unique perspective of understanding absentee students’ decision-making through the affordances and constraints found in their learning environment. To that effect, the study was guided by the question, “Why do absentee students decide to engage in absenteeism in a suburban Kansas school?” A case study methodology was used to answer the research question. Four suburban, Kansas high school absentee students in the 2020-2021 school year were selected for the study. The fall 2020 semester was in a remote learning setting, and the spring 2021 semester was in an in-person learning setting. The study captured their decision-making with respect to school attendance throughsemi-structured interviews, prolonged observations, drawings, and concept maps. The data was analyzed through thematic analysis. The findings revealed that peer socialization opportunities, methods of instruction, shifts in cultural beliefs due to COVID-19, manifestations of anxiety and lack of space to escape their anxiety, social media bullying, and the inability to receive academic tutoring motivated the participants’ daily decision to either attend or miss school. The findings provided a basis to improve several institutional and classroom practices. These practices included more student-led instruction and less teacher-led instruction in both in-person and remote learning environments, promoting socialization through classroom collaboration and clubs based on emerging student interests, reducing instances of bullying through prosocial education, safe spaces for students to escape the classroom to manage their anxiety, and more opportunities for one-on-one tutoring to improve grades. The study provides an example of using the ecological agency approach to better understand the personal and environmental factors that lead to absenteeism. The study also informs educational policies and classroom practices to better promote student attendance. Further research should investigate other school contexts using the ecological agency theoretical framework to better understand the influence of the school environment on student absenteeism.

Keywords: student absenteeism, ecological agency, classroom practices, educational policy, student decision-making

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Authors: Mohamed M. Elsherbiny

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Social Avoidance is one of the most important problems that face a good number of disabled students. It results from the negative attitudes of non-disabled students, teachers and others. Some of the past research has shown that non-disabled individuals hold negative attitudes toward persons with disabilities. The present study aims to alleviate Social Avoidance by applying the Cognitive Behavioral Intervention. 24 Blind students aged 19–24 (university students) were randomly chosen we compared an experimental group (consisted of 12 students) who went through the intervention program, with a control group (12 students also) who did not go through such intervention. We used the Social Avoidance and Distress Scale (SADS) to assess social anxiety and distress behavior. The author used many techniques of cognitive behavioral intervention such as modeling, cognitive restructuring, extension, contingency contracts, self-monitoring, assertiveness training, role play, encouragement and others. Statistically, T-test was employed to test the research hypothesis. Result showed that there is a significance difference between the experimental group and the control group after the intervention and also at the follow up stages of the Social Avoidance and Distress Scale. Also for the experimental group, there is a significance difference before the intervention and the follow up stages for the scale. Results showed that, there is a decrease in social avoidance. Accordingly, cognitive behavioral intervention program was successful in decreasing social avoidance for blind students.

Keywords: social avoidance, cognitive behavioral intervention, blind disability, disability

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Authors: Julianne Mullen-Williams

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This paper will provide an overview of a three year mixed methods research project that explores if methods from the supervision of dramatherapy can augment the occupational psychology of newly qualified secondary school teachers. It will consider how creativity and the use of metaphor, as applied in the supervision of dramatherapists, can be translated to an educational context in order to explore the explicit / implicit dynamics between the teacher trainee/ newly qualified teacher and the organisation in order to support the super objective in training for teaching; how to ‘be a teacher.’ There is growing evidence that attrition rates among teachers are rising after only five years of service owing to too many national initiatives, an unmanageable curriculum and deteriorating student discipline. The fieldwork conducted entailed facilitating a reflective space for Newly Qualified Teachers from all subject areas, using methods from the supervision of dramatherapy, to explore the social and emotional aspects of teaching and learning with the ultimate aim of improving the occupational psychology of teachers. Clinical supervision is a formal process of professional support and learning which permits individual practitioners in frontline service jobs; counsellors, psychologists, dramatherapists, social workers and nurses to expand their knowledge and proficiency, take responsibility for their own practice, and improve client protection and safety of care in complex clinical situations. It is deemed integral to continued professional practice to safeguard vulnerable people and to reduce practitioner burnout. Dramatherapy supervision incorporates all of the above but utilises creative methods as a tool to gain insight and a deeper understanding of the situation. Creativity and the use of metaphor enable the supervisee to gain an aerial view of the situation they are exploring. The word metaphor in Greek means to ‘carry across’ indicating a transfer of meaning form one frame of reference to another. The supervision support was incorporated into each group’s induction training programme. The first year group attended fortnightly one hour sessions, the second group received two one hour sessions every term. The existing literature on the supervision and mentoring of secondary school teacher trainees calls for changes in pre-service teacher education and in the induction period. There is a particular emphasis on the need to include reflective and experiential learning, within training programmes and within the induction period, in order to help teachers manage the interpersonal dynamics and emotional impact within a high pressurised environment

Keywords: dramatherapy supervision, newly qualified secondary school teachers, professional development, teacher education

Procedia PDF Downloads 393

Authors: Ananya Rajagopal

Abstract:

The study is based on an analysis of qualitative data used to analyze the business performance of entrepreneurs in emerging markets based on core variables such as collective leadership in reference to social entrepreneurship and reverse accountability attributes of stakeholders. In-depth interviews were conducted with 25 emerging enterprises within Mexico across five industrial segments. The study has been conducted focusing on five major research questions, which helped in developing the grounded theory related to reverser accountability. The results of the study revealed that the traditional entrepreneurship model based on an individualistic leadership style is being replaced by a collective leadership model. The study focuses on the leadership styles within social enterprises aimed at enhancing managerial capabilities and competencies, stakeholder values, and entrepreneurial growth. The theoretical motivation of this study has been derived from stakeholder theory and agency theory.

Keywords: reverse accountability, social enterprises, collective leadership, grounded theory, social governance

Procedia PDF Downloads 125

Authors: Hollie M. Lewis

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A large body of corroborating research provides evidence that traditional undergraduate engineering education fails to provide students with a role and identity that requires social concern and moral reasoning. Engineering students demonstrate a low level of engagement with social and political contexts, which further declines over the course of engineering education. This detachment is thought to stem from beliefs that the role of the engineer is purely to design machines, systems, and structures. In effect, engineers objectify the world. The purpose of this paper is to provide an ecofeminist critique of engineering education and pose the benefits of social justice pedagogies incorporating ecofeminist discourse. The challenges currently facing the world stem from anthropocentric industrialization, an agenda that is historically absent of Environmental, Feminist, People of Color, and Indigenous voices. A future in which the global collective achieves its Sustainable Development Goals requires its engineers to have a solid understanding of the broader social and political contexts in which they manage projects. Engineering education must convey the influence of the professional role of engineer and encourage the practice of critical reflection and social perspective-taking, priming students with the skills to engage with varying perspectives and discourses. There will be discussed the facets of social justice pedagogies that aid students in surpassing threshold concepts in social justice.

Keywords: feminism in engineering, sustainable development, engineering education, social justice pedagogies

Procedia PDF Downloads 67

Authors: Sanaz Kavianpour, Zuraini Ismail, Bharanidharan Shanmugam

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Social Network Sites (SNSs) can be served as an invaluable platform to transfer the information across a large number of individuals. A substantial component of communicating and managing information is to identify which individual will influence others in propagating information and also whether dissemination of information in the absence of social signals about that information will be occurred or not. Classifying the final audience of social data is difficult as controlling the social contexts which transfers among individuals are not completely possible. Hence, undesirable information diffusion to an unauthorized individual on SNSs can threaten individuals’ privacy. This paper highlights the information diffusion in SNSs and moreover it emphasizes the most significant privacy issues to individuals of SNSs. The goal of this paper is to propose a privacy-preserving model that has urgent regards with individuals’ data in order to control availability of data and improve privacy by providing access to the data for an appropriate third parties without compromising the advantages of information sharing through SNSs.

Keywords: anonymization algorithm, classification algorithm, information diffusion, privacy, social network sites

Procedia PDF Downloads 324

Authors: Chaiwat Waree

Abstract:

The purposes of the research were to develop online lessons to strengthen the learning process of Master's degree students majoring in Curriculum and Instruction at Suan Sunandha Rajabhat University; to achieve the efficiency criteria of 80/80; and to study the satisfaction of students who use online lessons to strengthen the learning process of Master’s degree students majoring in Curriculum and Instruction at Suan Sunandha Rajabhat University. The sample consisted of 40 University students studying in semester 1, academic year 2012. The sample was determined by Purposive Sampling. Selected students were from the class which the researcher was the homeroom tutor. The tutor was responsible for the teaching of learning process. Tools used in the study were online lessons, 60-point performance test, and evaluation test of satisfaction of students on online lessons. Data analysis yielded the following results; 83.66/88.29 efficiency of online lessons measured against the criteria; the comparison of performance before and after taking online lessons using t-test yielded 29.67. The statistical significance was at 0.05; the average satisfaction level of forty students on online lessons was 4.46 with standard deviation of 0.68.

Keywords: online, lessons, curriculum, instruction

Procedia PDF Downloads 225

Authors: Omar Alzeley, Sergey Utev

Abstract:

Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

Procedia PDF Downloads 472