Search results for: unsupervised machine learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8524

Search results for: unsupervised machine learning

6904 Advancement of Computer Science Research in Nigeria: A Bibliometric Analysis of the Past Three Decades

Authors: Temidayo O. Omotehinwa, David O. Oyewola, Friday J. Agbo

Abstract:

This study aims to gather a proper perspective of the development landscape of Computer Science research in Nigeria. Therefore, a bibliometric analysis of 4,333 bibliographic records of Computer Science research in Nigeria in the last 31 years (1991-2021) was carried out. The bibliographic data were extracted from the Scopus database and analyzed using VOSviewer and the bibliometrix R package through the biblioshiny web interface. The findings of this study revealed that Computer Science research in Nigeria has a growth rate of 24.19%. The most developed and well-studied research areas in the Computer Science field in Nigeria are machine learning, data mining, and deep learning. The social structure analysis result revealed that there is a need for improved international collaborations. Sparsely established collaborations are largely influenced by geographic proximity. The funding analysis result showed that Computer Science research in Nigeria is under-funded. The findings of this study will be useful for researchers conducting Computer Science related research. Experts can gain insights into how to develop a strategic framework that will advance the field in a more impactful manner. Government agencies and policymakers can also utilize the outcome of this research to develop strategies for improved funding for Computer Science research.

Keywords: bibliometric analysis, biblioshiny, computer science, Nigeria, science mapping

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6903 Analysing the Variables That Affect Digital Game-Based L2 Vocabulary Learning

Authors: Jose Ramon Calvo-Ferrer

Abstract:

Video games have been extensively employed in educational contexts to teach contents and skills, upon the premise that they engage students and provide instant feedback, which makes them adequate tools in the field of education and training. Term frequency, along with metacognition and implicit corrective feedback, has often been identified as powerful variables in the learning of vocabulary in a foreign language. This study analyses the learning of L2 mobile operating system terminology by a group of students and uses the data collected by the video game The Conference Interpreter to identify the predictive strength of term frequency (times a term is shown), positive metacognition (times a right answer is provided), and negative metacognition (times a term is shown as wrong) regarding L2 vocabulary learning and perceived learning outcomes. The regression analysis shows that the factor ‘positive metacognition’ is a positive predictor of both dependent variables, whereas the other factors seem to have no statistical effect on any of them.

Keywords: digital game-based learning, feedback, metacognition, frequency, video games

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6902 Optimizing PharmD Education: Quantifying Curriculum Complexity to Address Student Burnout and Cognitive Overload

Authors: Frank Fan

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PharmD (Doctor of Pharmacy) education has confronted an increasing challenge — curricular overload, a phenomenon resulting from the expansion of curricular requirements, as PharmD education strives to produce graduates who are practice-ready. The aftermath of the global pandemic has amplified the need for healthcare professionals, leading to a growing trend of assigning more responsibilities to them to address the global healthcare shortage. For instance, the pharmacist’s role has expanded to include not only compounding and distributing medication but also providing clinical services, including minor ailments management, patient counselling and vaccination. Consequently, PharmD programs have responded by continually expanding their curricula adding more requirements. While these changes aim to enhance the education and training of future professionals, they have also led to unintended consequences, including curricular overload, student burnout, and a potential decrease in program quality. To address the issue and ensure program quality, there is a growing need for evidence-based curriculum reforms. My research seeks to integrate Cognitive Load Theory, emerging machine learning algorithms within artificial intelligence (AI), and statistical approaches to develop a quantitative framework for optimizing curriculum design within the PharmD program at the University of Toronto, the largest PharmD program within Canada, to provide quantification and measurement of issues that currently are only discussed in terms of anecdote rather than data. This research will serve as a guide for curriculum planners, administrators, and educators, aiding in the comprehension of how the pharmacy degree program compares to others within and beyond the field of pharmacy. It will also shed light on opportunities to reduce the curricular load while maintaining its quality and rigor. Given that pharmacists constitute the third-largest healthcare workforce, their education shares similarities and challenges with other health education programs. Therefore, my evidence-based, data-driven curriculum analysis framework holds significant potential for training programs in other healthcare professions, including medicine, nursing, and physiotherapy.

Keywords: curriculum, curriculum analysis, health professions education, reflective writing, machine learning

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6901 Assessment of Ultra-High Cycle Fatigue Behavior of EN-GJL-250 Cast Iron Using Ultrasonic Fatigue Testing Machine

Authors: Saeedeh Bakhtiari, Johannes Depessemier, Stijn Hertelé, Wim De Waele

Abstract:

High cycle fatigue comprising up to 107 load cycles has been the subject of many studies, and the behavior of many materials was recorded adequately in this regime. However, many applications involve larger numbers of load cycles during the lifetime of machine components. In this ultra-high cycle regime, other failure mechanisms play, and the concept of a fatigue endurance limit (assumed for materials such as steel) is often an oversimplification of reality. When machine component design demands a high geometrical complexity, cast iron grades become interesting candidate materials. Grey cast iron is known for its low cost, high compressive strength, and good damping properties. However, the ultra-high cycle fatigue behavior of cast iron is poorly documented. The current work focuses on the ultra-high cycle fatigue behavior of EN-GJL-250 (GG25) grey cast iron by developing an ultrasonic (20 kHz) fatigue testing system. Moreover, the testing machine is instrumented to measure the temperature and the displacement of  the specimen, and to control the temperature. The high resonance frequency allowed to assess the  behavior of the cast iron of interest within a matter of days for ultra-high numbers of cycles, and repeat the tests to quantify the natural scatter in fatigue resistance.

Keywords: GG25, cast iron, ultra-high cycle fatigue, ultrasonic test

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6900 The Wider Benefits of Negotiations: Austrian Perspective on Educational Leadership as a ‘Power Game’ for Trade Unions

Authors: Rudolf Egger

Abstract:

This paper explores the relationships between the basic learning processes of leading trade union workers and their methods for coping with the changes in the life-courses of societies today. It will discuss the fragile discourse on lifelong learning in trade unions and the “production of self-techniques” to get in touch with the new economic forms. On the basis of an empirical project, different processes of the socialization of leading trade union workers will be analysed to discover the consequences of the lifelong learning discourse. The results show what competences they need to develop for the “wider benefits of negotiations”. The main challenge remains to make visible how deeply intertwined trade union learning and education are with development in an ongoing dynamic economic process, rather than a quick-fix injection of skills and information. There is a complex relationship existing between the three ‘partners’, work, learning and society forming. The author suggests that contemporary trade unions could be trendsetters who make their own learning agendas by drawing less on formal education and more on informal and non-formal learning contexts. This is in parallel with growing political and scientific consciousness of the need to arrive at new educational/vocational policies and practices.

Keywords: trade union workers, educational leadership, learning societies, social acting

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6899 Strategies to Improve Learning and Teaching of Software Packages Among Undergraduate Students

Authors: Sara Moridpour

Abstract:

Engineering students need to learn different software packages to meet the emerging industry needs. Face-to-face lectures provide an interactive environment for learning software packages. However, COVID changed expectations of face-to-face learning and teaching. It is essential to enhance the interaction among students and teachers in online and virtual learning and teaching of software packages. The proposed study introduces strategies for teaching engineering software packages in online and hybrid environments and evaluates students’ skills by an authentic assignment.

Keywords: teaching software packages, authentic assessment., engineering, undergraduate students

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6898 Students’ Awareness of the Use of Poster, Power Point and Animated Video Presentations: A Case Study of Third Year Students of the Department of English of Batna University

Authors: Bahloul Amel

Abstract:

The present study debates students’ perceptions of the use of technology in learning English as a Foreign Language. Its aim is to explore and understand students’ preparation and presentation of Posters, PowerPoint and Animated Videos by drawing attention to visual and oral elements. The data is collected through observations and semi-structured interviews and analyzed through phenomenological data analysis steps. The themes emerged from the data, visual learning satisfaction in using information and communication technology, providing structure to oral presentation, learning from peers’ presentations, draw attention to using Posters, PowerPoint and Animated Videos as each supports visual learning and organization of thoughts in oral presentations.

Keywords: EFL, posters, PowerPoint presentations, Animated Videos, visual learning

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6897 Explaining E-Learning Systems Usage in Higher Education Institutions: UTAUT Model

Authors: Muneer Abbad

Abstract:

This research explains the e-learning usage in a university in Jordan. Unified theory of acceptance and use of technology (UTAUT) model has been used as a base model to explain the usage. UTAUT is a model of individual acceptance that is compiled mainly from different models of technology acceptance. This research is the initial part from full explanations of the users' acceptance model that use Structural Equation Modelling (SEM) method to explain the users' acceptance of the e-learning systems based on UTAUT model. In this part data has been collected and prepared for further analysis. The main factors of UTAUT model has been tested as different factors using exploratory factor analysis (EFA). The second phase will be confirmatory factor analysis (CFA) and SEM to explain the users' acceptance of e-learning systems.

Keywords: e-learning, moodle, adoption, Unified Theory of Acceptance and Use of Technology (UTAUT)

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6896 A Study to Explore the Views of Students regarding E-Learning as an Instructional Tool at University Level

Authors: Zafar Iqbal

Abstract:

This study involved students of 6th semester enrolled in a Bachelor of Computer Science Program at university level. In this era of science and technology, e-learning can be helpful for grassroots in providing them access to education tenant in less developed areas. It is a potential substitute of face-to-face teaching being used in different countries. The purpose of the study was to explore the views of students about e-learning (Facebook) as an instructional tool. By using purposive sampling technique an intact class of 30 students included both male and female were selected where e-learning was used as an instructional tool. The views of students were explored through qualitative approach by using focus group interviews. The approach was helpful to develop comprehensive understanding of students’ views towards e- learning. In addition, probing questions were also asked and recorded. Data was transcribed, generated nodes and then coded text against these nodes. For this purpose and further analysis, NVivo 10 software was used. Themes were generated and tangibly presented through cluster analysis. Findings were interesting and provide sufficient evidence that face book is a subsequent e-learning source for students of higher education. Students acknowledged it as best source of learning and it was aligned with their academic and social behavior. It was not time specific and therefore, feasible for students who work day time and can get on line access to the material when they got free time. There were some distracters (time wasters) reported by the students but can be minimized by little effort. In short, e-learning is need of the day and potential learning source for every individual who have access to internet living at any part of the globe.

Keywords: e-learning, facebook, instructional tool, higher education

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6895 Auditory and Visual Perceptual Category Learning in Adults with ADHD: Implications for Learning Systems and Domain-General Factors

Authors: Yafit Gabay

Abstract:

Attention deficit hyperactivity disorder (ADHD) has been associated with both suboptimal functioning in the striatum and prefrontal cortex. Such abnormalities may impede the acquisition of perceptual categories, which are important for fundamental abilities such as object recognition and speech perception. Indeed, prior research has supported this possibility, demonstrating that children with ADHD have similar visual category learning performance as their neurotypical peers but use suboptimal learning strategies. However, much less is known about category learning processes in the auditory domain or among adults with ADHD in which prefrontal functions are more mature compared to children. Here, we investigated auditory and visual perceptual category learning in adults with ADHD and neurotypical individuals. Specifically, we examined learning of rule-based categories – presumed to be optimally learned by a frontal cortex-mediated hypothesis testing – and information-integration categories – hypothesized to be optimally learned by a striatally-mediated reinforcement learning system. Consistent with striatal and prefrontal cortical impairments observed in ADHD, our results show that across sensory modalities, both rule-based and information-integration category learning is impaired in adults with ADHD. Computational modeling analyses revealed that individuals with ADHD were slower to shift to optimal strategies than neurotypicals, regardless of category type or modality. Taken together, these results suggest that both explicit, frontally mediated and implicit, striatally mediated category learning are impaired in ADHD. These results suggest impairments across multiple learning systems in young adults with ADHD that extend across sensory modalities and likely arise from domain-general mechanisms.

Keywords: ADHD, category learning, modality, computational modeling

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6894 Design of Fuzzy Logic Based Global Power System Stabilizer for Dynamic Stability Enhancement in Multi-Machine Power System

Authors: N. P. Patidar, J. Earnest, Laxmikant Nagar, Akshay Sharma

Abstract:

This paper describes the diligence of a new input signal based fuzzy power system stabilizer in multi-machine power system. Instead of conventional input pairs like speed deviation (∆ω) and derivative of speed deviation i.e. acceleration (∆ω ̇) or speed deviation and accelerating power deviation of each machine, in this paper, deviation of active power through the tie line colligating two areas is used as one of the inputs to the fuzzy logic controller in concurrence with the speed deviation. Fuzzy Logic has the features of simple concept, easy effectuation, and computationally efficient. The advantage of this input is that, the same signal can be fed to each of the fuzzy logic controller connected with each machine. The simulated system comprises of two fully symmetrical areas coupled together by two 230 kV lines. Each area is equipped with two superposable generators rated 20 kV/900MVA and area-1 is exporting 413 MW to area-2. The effectiveness of the proposed control scheme has been assessed by performing small signal stability assessment and transient stability assessment. The proposed control scheme has been compared with a conventional PSS. Digital simulation is used to demonstrate the performance of fuzzy logic controller.

Keywords: Power System Stabilizer (PSS), small signal stability, inter-area oscillation, fuzzy logic controller, membership function, rule base

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6893 Evaluating the Role of Multisensory Elements in Foreign Language Acquisition

Authors: Sari Myréen

Abstract:

The aim of this study was to evaluate the role of multisensory elements in enhancing and facilitating foreign language acquisition among adult students in a language classroom. The use of multisensory elements enables the creation of a student-centered classroom, where the focus is on individual learner’s language learning process, perceptions and motivation. Multisensory language learning is a pedagogical approach where the language learner uses all the senses more effectively than in a traditional in-class environment. Language learning is facilitated due to multisensory stimuli which increase the number of cognitive connections in the learner and take into consideration different types of learners. A living lab called Multisensory Space creates a relaxed and receptive state in the learners through various multisensory stimuli, and thus promotes their natural foreign language acquisition. Qualitative and quantitative data were collected in two questionnaire inquiries among the Finnish students of a higher education institute at the end of their basic French courses in December 2014 and 2016. The inquiries discussed the effects of multisensory elements on the students’ motivation to study French as well as their learning outcomes. The results show that the French classes in the Multisensory Space provide the students with an encouraging and pleasant learning environment, which has a positive impact on their motivation to study the foreign language as well as their language learning outcomes.

Keywords: foreign language acquisition, pedagogical approach, multisensory learning, transcultural learning

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6892 The Need for the Utilization of Instructional Materials on the Teaching and Learning of Agricultural Science Education in Developing Countries

Authors: Ogoh Andrew Enokela

Abstract:

This paper dwelt on the need for the utilization of instructional materials with highlights on the type of instructional materials, selection, uses and their importance on the learning and teaching of Agricultural Science Education in developing countries. It further discussed the concept of improvisation with some recommendation in terms of availability, utilization on the teaching and learning of Agricultural Science Education.

Keywords: instructional materials, agricultural science education, improvisation, teaching and learning

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6891 The Implementation of Teaching and Learning Quality Assurance System at the Chaoyang University of Technology for Academic Year 2013-2015

Authors: Ting Hsiang Chang

Abstract:

Nowadays in Taiwan, higher education, which was previously more emphasized on teaching-oriented approaches, has gradually shifted to an approach more focusing on students learning outcomes. With student employment rate as an important indicator for University Program Evaluation periodically held by the Ministry of Education, it becomes extremely critical for a university to build up a teaching and learning quality assurance system to bridge the gap between learning and practice. Teaching and Learning Quality Assurance System has been built and implemented at Chaoyang University of Technology for years and has received substantial results. By employing various forms of evaluation and performance appraisals, the effectiveness of teaching and learning can consistently be tracked as a means of ensuring teaching and learning quality. This study aims to explore the evaluation system of teaching and learning quality assurance system at the Chaoyang University of Technology by means of content analysis. The study contents the evaluation reports on the teaching and learning quality assurance at the Chaoyang University of Technology in the Academic Year 2013-2015. The quantitative results of the assessment were analyzed using the five-point Likert Scale. Quality assurance Committee meetings were further held for examining and discussions on the results. To the end, the annual evaluation report is to be produced as references used to improve approaches in both teaching and learning. The findings indicate that there is a respective relationship between the overall teaching evaluation items and the teaching goals and core competencies. In addition, graduates’ feedbacks were also collected for further analysis to examine if the current educational planning is able to achieve the university’s teaching goal and cultivation of core competencies.

Keywords: core competencies, teaching and learning quality assurance system, teaching goals, university program evaluation

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6890 Mobile Mediated Learning and Teachers Education in Less Resourced Region

Authors: Abdul Rashid Ahmadi, Samiullah Paracha, Hamidullah Sokout, Mohammad Hanif Gharana

Abstract:

Conventional educational practices, do not offer all the required skills for teachers to successfully survive in today’s workplace. Due to poor professional training, a big gap exists across the curriculum plan and the teacher practices in the classroom. As such, raising the quality of teaching through ICT-enabled training and professional development of teachers should be an urgent priority. ‘Mobile Learning’, in that vein, is an increasingly growing field of educational research and practice across schools and work places. In this paper, we propose a novel Mobile learning system that allows the users to learn through an intelligent mobile learning in cooperatively every-time and every-where. The system will reduce the training cost and increase consistency, efficiency, and data reliability. To establish that our system will display neither functional nor performance failure, the evaluation strategy is based on formal observation of users interacting with system followed by questionnaires and structured interviews.

Keywords: computer assisted learning, intelligent tutoring system, learner centered design, mobile mediated learning and teacher education

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6889 Re-identification Risk and Mitigation in Federated Learning: Human Activity Recognition Use Case

Authors: Besma Khalfoun

Abstract:

In many current Human Activity Recognition (HAR) applications, users' data is frequently shared and centrally stored by third parties, posing a significant privacy risk. This practice makes these entities attractive targets for extracting sensitive information about users, including their identity, health status, and location, thereby directly violating users' privacy. To tackle the issue of centralized data storage, a relatively recent paradigm known as federated learning has emerged. In this approach, users' raw data remains on their smartphones, where they train the HAR model locally. However, users still share updates of their local models originating from raw data. These updates are vulnerable to several attacks designed to extract sensitive information, such as determining whether a data sample is used in the training process, recovering the training data with inversion attacks, or inferring a specific attribute or property from the training data. In this paper, we first introduce PUR-Attack, a parameter-based user re-identification attack developed for HAR applications within a federated learning setting. It involves associating anonymous model updates (i.e., local models' weights or parameters) with the originating user's identity using background knowledge. PUR-Attack relies on a simple yet effective machine learning classifier and produces promising results. Specifically, we have found that by considering the weights of a given layer in a HAR model, we can uniquely re-identify users with an attack success rate of almost 100%. This result holds when considering a small attack training set and various data splitting strategies in the HAR model training. Thus, it is crucial to investigate protection methods to mitigate this privacy threat. Along this path, we propose SAFER, a privacy-preserving mechanism based on adaptive local differential privacy. Before sharing the model updates with the FL server, SAFER adds the optimal noise based on the re-identification risk assessment. Our approach can achieve a promising tradeoff between privacy, in terms of reducing re-identification risk, and utility, in terms of maintaining acceptable accuracy for the HAR model.

Keywords: federated learning, privacy risk assessment, re-identification risk, privacy preserving mechanisms, local differential privacy, human activity recognition

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6888 Implications of Humanizing Pedagogy on Learning Design in a Technology-Enhanced Language Learning Environment: Critical Reflections on Student Identity and Agency

Authors: Mukhtar Raban

Abstract:

Nelson Mandela University subscribes to a humanizing pedagogy (HP), as housed under broader critical pedagogy, that underpins and informs learning and teaching activities at the institution. The investigation sought to explore the implications of humanizing and critical pedagogical considerations for a technology-enhanced language learning (TELL) environment in a university course. The paper inquires into the design of a learning resource in an online learning environment of an English communication module, that applied HP principles. With an objective of creating agentive spaces for foregrounding identity, student voice, critical self-reflection, and recognition of others’ humanity; a flexible and open 'My Presence' feature was added to the TELL environment that allowed students and lecturers to share elements of their backgrounds in a ‘mutually vulnerable’ manner as a way of establishing digital identity and a more ‘human’ presence in the online language learning encounter, serving as a catalyst for the recognition of the ‘other’. Following a qualitative research design, the study adopted an auto-ethnographic approach, complementing the critical inquiry nature embedded into the activity’s practices. The study’s findings provide critical reflections and deductions on the possibilities of leveraging digital human expression within a humanizing pedagogical framework to advance the realization of HP-adoption in language learning and teaching encounters. It was found that the consideration of humanizing pedagogical principles in the design of online learning was more effective when the critical outcomes were explicated to students and lecturers prior to the completion of the activities. The integration of humanizing pedagogy also led to a contextual advancement of ‘affective’ language learning. Upon critical reflection and analysis, student identity and agency can flourish in a technology-enhanced learning environment when humanizing, and critical pedagogy influences the learning design.

Keywords: critical reflection, humanizing pedagogy, student identity, technology-enhanced language learning

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6887 Impact of Team-Based Learning Approach in English Language Learning Process: A Case Study of Universidad Federico Santa Maria

Authors: Yessica A. Aguilera

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English is currently the only foreign language included in the national educational curriculum in Chile. The English curriculum establishes that once completed secondary education, students are expected to reach B1 level according to the Common European Reference Framework (CEFR) scale. However, the objective has not been achieved, and to the author’s best knowledge, there is still a severe lack of English language skills among students who have completed their secondary education studies. In order to deal with the fact that students do not manage English as expected, team-based learning (TBL) was introduced in English language lessons at the Universidad Federico Santa María (USM). TBL is a collaborative teaching-learning method which enhances active learning by combining individual and team work. This approach seeks to help students achieve course objectives while learning how to function in teams. The purpose of the research was to assess the implementation and effectiveness of TBL in English language classes at USM technical training education. Quantitative and qualitative data were collected from teachers and students about their experience through TBL. Research findings show that both teachers and students are satisfied with the method and that students’ engagement and participation in class is higher. Additionally, students score higher on examinations improving academic outcomes. The findings of the research have the potential to guide how TBL could be included in future English language courses.

Keywords: collaborative learning, college education, English language learning, team-based learning

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6886 The Impact of Gamification on Self-Assessment for English Language Learners in Saudi Arabia

Authors: Wala A. Bagunaid, Maram Meccawy, Arwa Allinjawi, Zilal Meccawy

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Continuous self-assessment becomes crucial in self-paced online learning environments. Students often depend on themselves to assess their progress; which is considered an essential requirement for any successful learning process. Today’s education institutions face major problems around student motivation and engagement. Thus, personalized e-learning systems aim to help and guide the students. Gamification provides an opportunity to help students for self-assessment and social comparison with other students through attempting to harness the motivational power of games and apply it to the learning environment. Furthermore, Open Social Student Modeling (OSSM) as considered as the latest user modeling technologies is believed to improve students’ self-assessment and to allow them to social comparison with other students. This research integrates OSSM approach and gamification concepts in order to provide self-assessment for English language learners at King Abdulaziz University (KAU). This is achieved through an interactive visual representation of their learning progress.

Keywords: e-learning system, gamification, motivation, social comparison, visualization

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6885 Hybrid Approach for Country’s Performance Evaluation

Authors: C. Slim

Abstract:

This paper presents an integrated model, which hybridized data envelopment analysis (DEA) and support vector machine (SVM) together, to class countries according to their efficiency and performance. This model takes into account aspects of multi-dimensional indicators, decision-making hierarchy and relativity of measurement. Starting from a set of indicators of performance as exhaustive as possible, a process of successive aggregations has been developed to attain an overall evaluation of a country’s competitiveness.

Keywords: Artificial Neural Networks (ANN), Support vector machine (SVM), Data Envelopment Analysis (DEA), Aggregations, indicators of performance

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6884 Employing QR Code as an Effective Educational Tool for Quick Access to Sources of Kindergarten Concepts

Authors: Ahmed Amin Mousa, M. Abd El-Salam

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This study discusses a simple solution for the problem of shortage in learning resources for kindergarten teachers. Occasionally, kindergarten teachers cannot access proper resources by usual search methods as libraries or search engines. Furthermore, these methods require a long time and efforts for preparing. The study is expected to facilitate accessing learning resources. Moreover, it suggests a potential direction for using QR code inside the classroom. The present work proposes that QR code can be used for digitizing kindergarten curriculums and accessing various learning resources. It investigates using QR code for saving information related to the concepts which kindergarten teachers use in the current educational situation. The researchers have established a guide for kindergarten teachers based on the Egyptian official curriculum. The guide provides different learning resources for each scientific and mathematical concept in the curriculum, and each learning resource is represented as a QR code image that contains its URL. Therefore, kindergarten teachers can use smartphone applications for reading QR codes and displaying the related learning resources for students immediately. The guide has been provided to a group of 108 teachers for using inside their classrooms. The results showed that the teachers approved the guide, and gave a good response.

Keywords: kindergarten, child, learning resources, QR code, smart phone, mobile

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6883 Integrating Inference, Simulation and Deduction in Molecular Domain Analysis and Synthesis with Peculiar Attention to Drug Discovery

Authors: Diego Liberati

Abstract:

Standard molecular modeling is traditionally done through Schroedinger equations via the help of powerful tools helping to manage them atom by atom, often needing High Performance Computing. Here, a full portfolio of new tools, conjugating statistical inference in the so called eXplainable Artificial Intelligence framework (in the form of Machine Learning of understandable rules) to the more traditional modeling and simulation control theory of mixed dynamic logic hybrid processes, is offered as quite a general purpose even if making an example to a popular chemical physics set of problems.

Keywords: understandable rules ML, k-means, PCA, PieceWise Affine Auto Regression with eXogenous input

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6882 Integrations of Students' Learning Achievements and Their Analytical Thinking Abilities with the Problem-Based Learning and the Concept Mapping Instructional Methods on Gene and Chromosome Issue at the 12th Grade Level

Authors: Waraporn Thaimit, Yuwadee Insamran, Natchanok Jansawang

Abstract:

Focusing on Analytical Thinking and Learning Achievement are the critical component of visual thinking that gives one the ability to solve problems quickly and effectively that allows to complex problems into components, and the result had been achieved or acquired form of the subject students of which resulted in changes within the individual as a result of activity in learning. The aims of this study are to administer on comparisons between students’ analytical thinking abilities and their learning achievements sample size consisted of 80 students who sat at the 12th grade level in 2 classes from Chaturaphak Phiman Ratchadaphisek School, the 40-student experimental group with the Problem-Based Learning (PBL) and 40-student controlling group with the Concept Mapping Instructional (CMI) methods were designed. Research instruments composed with the 5-lesson instructional plans to be assessed with the pretest and posttest techniques on each instructional method. Students’ responses of their analytical thinking abilities were assessed with the Analytical Thinking Tests and students’ learning achievements were tested of the Learning Achievement Tests. Statistically significant differences with the paired t-test and F-test (Two-way MANCOVA) between post- and pre-tests of the whole students in two chemistry classes were found. Associations between student learning outcomes in each instructional method and their analytical thinking abilities to their learning achievements also were found (ρ < .05). The use of two instructional methods for this study is revealed that the students perceive their abilities to be highly learning achievement in chemistry classes with the PBL group ought to higher than the CMI group. Suggestions that analytical thinking ability involves the process of gathering relevant information and identifying key issues related to the learning achievement information.

Keywords: comparisons, students learning achievements, analytical thinking abilities, the problem-based learning method, the concept mapping instructional method, gene and chromosome issue, chemistry classes

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6881 An Evaluation of the Artificial Neural Network and Adaptive Neuro Fuzzy Inference System Predictive Models for the Remediation of Crude Oil-Contaminated Soil Using Vermicompost

Authors: Precious Ehiomogue, Ifechukwude Israel Ahuchaogu, Isiguzo Edwin Ahaneku

Abstract:

Vermicompost is the product of the decomposition process using various species of worms, to create a mixture of decomposing vegetable or food waste, bedding materials, and vemicast. This process is called vermicomposting, while the rearing of worms for this purpose is called vermiculture. Several works have verified the adsorption of toxic metals using vermicompost but the application is still scarce for the retention of organic compounds. This research brings to knowledge the effectiveness of earthworm waste (vermicompost) for the remediation of crude oil contaminated soils. The remediation methods adopted in this study were two soil washing methods namely, batch and column process which represent laboratory and in-situ remediation. Characterization of the vermicompost and crude oil contaminated soil were performed before and after the soil washing using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), X-ray fluorescence (XRF), X-ray diffraction (XRD) and Atomic adsorption spectrometry (AAS). The optimization of washing parameters, using response surface methodology (RSM) based on Box-Behnken Design was performed on the response from the laboratory experimental results. This study also investigated the application of machine learning models [Artificial neural network (ANN), Adaptive neuro fuzzy inference system (ANFIS). ANN and ANFIS were evaluated using the coefficient of determination (R²) and mean square error (MSE)]. Removal efficiency obtained from the Box-Behnken design experiment ranged from 29% to 98.9% for batch process remediation. Optimization of the experimental factors carried out using numerical optimization techniques by applying desirability function method of the response surface methodology (RSM) produce the highest removal efficiency of 98.9% at absorbent dosage of 34.53 grams, adsorbate concentration of 69.11 (g/ml), contact time of 25.96 (min), and pH value of 7.71, respectively. Removal efficiency obtained from the multilevel general factorial design experiment ranged from 56% to 92% for column process remediation. The coefficient of determination (R²) for ANN was (0.9974) and (0.9852) for batch and column process, respectively, showing the agreement between experimental and predicted results. For batch and column precess, respectively, the coefficient of determination (R²) for RSM was (0.9712) and (0.9614), which also demonstrates agreement between experimental and projected findings. For the batch and column processes, the ANFIS coefficient of determination was (0.7115) and (0.9978), respectively. It can be concluded that machine learning models can predict the removal of crude oil from polluted soil using vermicompost. Therefore, it is recommended to use machines learning models to predict the removal of crude oil from contaminated soil using vermicompost.

Keywords: ANFIS, ANN, crude-oil, contaminated soil, remediation and vermicompost

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6880 Open and Distance Learning (ODL) Education in Nigeria: Challenge of Academic Quality

Authors: Edu Marcelina, Sule Sheidu A., Nsor Eunice

Abstract:

As open and distance education is gradually becoming an acceptable means of solving the problem of access in higher education, quality has now become one of the main concerns among institutions and stakeholders of open and distance learning (ODL) and the education sector in general. This study assessed the challenges of academic quality in the open and distance learning (ODL) education in Nigeria using Distance Learning Institute (DLI), University of Lagos and National Open University of Nigeria as a case. In carrying out the study, a descriptive survey research design was employed. A researcher-designed and validated questionnaire was used to elicit responses that translated to the quantitative data for this study. The sample comprised 665 students of the Distance Learning Institute (DLI), and National Open University of Nigeria (NOUN), carefully selected through the method of simple random sampling. Data collected from the study were analyzed using Chi-Square (X2) at 0.05 Level of significance. The results of the analysis revealed that; the use of ICT tools is a factor in ensuring quality in the Open and Distance Learning (ODL) operations; the quality of the materials made available to ODL students will determine the quality of education that will be received by the students; and the time scheduled for students for self-study, online lecturing/interaction and face to face study and the quality of education in Open and Distance Learning Institutions has a lot of impact on the quality of education the students receive. Based on the findings, a number of recommendations were made.

Keywords: open and distance learning, quality, ICT, face-to-face interaction

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6879 Effectiveness of a Traits Cooperative Learning on Developing Writing Achievement and Composition among Teacher Candidates

Authors: Abdelaziz Hussien

Abstract:

This article reports investigations of a study into the effectiveness of a traits cooperative learning (TCL) on teacher candidates’ writing achievement, composition, and attitudes towards traits of writing approach and small group learning. Mixed methodologies were used with the participants in a repeated measures quasi-experimental design. Forty-two class teacher candidates, enrolled in the Bahrain Teachers College, completed the pre and post author-developed measures. The results suggest that TCL has a positive effect on the participants’ writing achievement, composition, and attitudes towards traits of writing approach, but not on the attitudes towards small group learning. Further implications to teacher education are presented.

Keywords: trait-based language education, cooperative learning, writing achievement, writing composition, traits of writing, teacher education

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6878 Floodnet: Classification for Post Flood Scene with a High-Resolution Aerial Imaginary Dataset

Authors: Molakala Mourya Vardhan Reddy, Kandimala Revanth, Koduru Sumanth, Beena B. M.

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Emergency response and recovery operations are severely hampered by natural catastrophes, especially floods. Understanding post-flood scenarios is essential to disaster management because it facilitates quick evaluation and decision-making. To this end, we introduce FloodNet, a brand-new high-resolution aerial picture collection created especially for comprehending post-flood scenes. A varied collection of excellent aerial photos taken during and after flood occurrences make up FloodNet, which offers comprehensive representations of flooded landscapes, damaged infrastructure, and changed topographies. The dataset provides a thorough resource for training and assessing computer vision models designed to handle the complexity of post-flood scenarios, including a variety of environmental conditions and geographic regions. Pixel-level semantic segmentation masks are used to label the pictures in FloodNet, allowing for a more detailed examination of flood-related characteristics, including debris, water bodies, and damaged structures. Furthermore, temporal and positional metadata improve the dataset's usefulness for longitudinal research and spatiotemporal analysis. For activities like flood extent mapping, damage assessment, and infrastructure recovery projection, we provide baseline standards and evaluation metrics to promote research and development in the field of post-flood scene comprehension. By integrating FloodNet into machine learning pipelines, it will be easier to create reliable algorithms that will help politicians, urban planners, and first responders make choices both before and after floods. The goal of the FloodNet dataset is to support advances in computer vision, remote sensing, and disaster response technologies by providing a useful resource for researchers. FloodNet helps to create creative solutions for boosting communities' resilience in the face of natural catastrophes by tackling the particular problems presented by post-flood situations.

Keywords: image classification, segmentation, computer vision, nature disaster, unmanned arial vehicle(UAV), machine learning.

Procedia PDF Downloads 74
6877 Multimodal Sentiment Analysis With Web Based Application

Authors: Shreyansh Singh, Afroz Ahmed

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Sentiment Analysis intends to naturally reveal the hidden mentality that we hold towards an entity. The total of this assumption over a populace addresses sentiment surveying and has various applications. Current text-based sentiment analysis depends on the development of word embeddings and Machine Learning models that take in conclusion from enormous text corpora. Sentiment Analysis from text is presently generally utilized for consumer loyalty appraisal and brand insight investigation. With the expansion of online media, multimodal assessment investigation is set to carry new freedoms with the appearance of integral information streams for improving and going past text-based feeling examination using the new transforms methods. Since supposition can be distinguished through compelling follows it leaves, like facial and vocal presentations, multimodal opinion investigation offers good roads for examining facial and vocal articulations notwithstanding the record or printed content. These methodologies use the Recurrent Neural Networks (RNNs) with the LSTM modes to increase their performance. In this study, we characterize feeling and the issue of multimodal assessment investigation and audit ongoing advancements in multimodal notion examination in various spaces, including spoken surveys, pictures, video websites, human-machine, and human-human connections. Difficulties and chances of this arising field are additionally examined, promoting our theory that multimodal feeling investigation holds critical undiscovered potential.

Keywords: sentiment analysis, RNN, LSTM, word embeddings

Procedia PDF Downloads 114
6876 Proteome-Wide Convergent Evolution on Vocal Learning Birds Reveals Insight into cAMP-Based Learning Pathway

Authors: Chul Lee, Seoae Cho, Erich D. Jarvis, Heebal Kim

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Vocal learning, the ability to imitate vocalizations based on auditory experience, is a homoplastic character state observed in different independent lineages of animals such as songbirds, parrots, hummingbirds and human. It has now become possible to perform genome-wide molecular analyses across vocal learners and vocal non-learners with the recent expansion of avian genome data. It was analyzed the whole genomes of human and 48 avian species including those belonging to the three avian vocal learning lineages, to determine if behavior and neural convergence are associated with molecular convergence in divergent species of vocal learners. Analyses of 8295 orthologous genes across bird species revealed 141 genes with amino acid substitutions specific to vocal learners. Out of these, 25 genes have vocal learner specific genetic homoplasies, and their functions were enriched for learning. Several sites in these genes are estimated under convergent evolution and positive selection. A potential role for a subset of these genes in vocal learning was supported by associations with gene expression profiles in vocal learning brain regions of songbirds and human disease that cause language dysfunctions. The key candidate gene with multiple independent lines of the evidences specific to vocal learners was DRD5. Our findings suggest cAMP-based learning pathway in avian vocal learners, indicating molecular homoplastic changes associated with a complex behavioral trait, vocal learning.

Keywords: amino acid substitutions, convergent evolution, positive selection, vocal learning

Procedia PDF Downloads 337
6875 Assessment of E-Learning Facilities in Open and Distance Learning and Information Need by Students

Authors: Sabo Elizabeth

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Electronic learning is increasingly popular learning approach in higher educational institutions due to vast growth of internet technology. This approach is important in human capital development. An investigation of open distance and e-learning facilities and information need by open and distance learning students was carried out in Jalingo, Nigeria. Structured questionnaires were administered to 70 registered ODL students of the NOUN. Information sourced from the respondents covered demographic, economic and institutional variables. Data collected for demographic variables were computed as frequency count and percentages. Assessment of the effectiveness of ODL facilities and information need among open and distance learning students was computed on a three or four point Likert Rating Scale. Findings indicated that there are more men compared to women. A large proportion of the respondents are married and there are more matured students in ODL compared to the youth. A high proportion of the ODL students obtained qualifications higher than the secondary school certificate. The proportion of computer literate ODL students was high, and large number of the students does not own a laptop computer. Inadequate e -books and reference materials, internet gadgets and inadequate books (hard copies) and reference material are factors that limit utilization of e-learning facilities in the study areas. Inadequate computer facilities and power back up caused inconveniences and delay in administering and use of e learning facilities. To a high extent, open and distance learning students needed information on university time table and schedule of activities, availability and access to books (hard and e-books) and reference materials. The respondents emphasized that contact with course coordinators via internet will provide a better learning and academic performance.

Keywords: open and distance learning, information required, electronic books, internet gadgets, Likert scale test

Procedia PDF Downloads 322