Search results for: unsupervised learning approach

Authors: Ying Zhou, Jian-Hua Wang

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

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

Procedia PDF Downloads 259

Authors: Hélène Knoerr

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In an increasingly global world, more and more international students attend academic courses and programs in a second or foreign language, and local students register in language learning classes in order to improve their employability. These students need to quickly become proficient in the new language. How can we, as administrators, curriculum developers and teachers, make sure that they have the tools they need in order to develop their language skills in an academic context? This paper will describe the development and implementation of a new course, Learning to learn, as part of the Major in French/English as a Second Language at the University of Ottawa. This academic program was recently completely overhauled in order to reflect the current approaches in language learning (more specifically, the action-oriented approach as embodied in the Common European Framework of Reference for Languages, and the concept of life-long autonomous learning). The course itself is based on research on language learning strategies, with a particular focus on the characteristics of the “good language learner”. We will present the methodological and pedagogical foundations, describe the course objectives and learning outcomes, the language learning strategies, and the classroom activities. The paper will conclude with students’ feedback and suggest avenues for further exploration.

Keywords: curriculum development, language learning, learning strategies, second language

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Authors: Amal A. Abdel-Sattar

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The curriculum of architecture department in Prince Sultan University includes ‘Building Surveying’ course which is usually a part of civil engineering courses. As a fundamental requirement of the course, it requires a strong background in mathematics and physics, which are not usually preferred subjects to the architecture students and many of them are not giving the required and necessary attention to these courses during their preparation year before commencing their architectural study. This paper introduces the concept and the methodology of the student-centered learning approach in the course of building surveying for architects. One of the major outcomes is the improvement in the students’ involvement in the course and how this will cover and strength their analytical weak points and improve their mathematical skills. The study is conducted through three semesters with a total number of 99 students. The effectiveness of the student-centered learning approach is studied using the student survey at the end of each semester and teacher observations. This survey showed great acceptance of the students for these methods. Also, the teachers observed a great improvement in the students’ mathematical abilities and how keener they became in attending the classes which were clearly reflected on the low absence record.

Keywords: architecture, building surveying, student-centered learning, teaching and learning

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Authors: Aloysius Hardoko, Susilo

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The root cause of environmental damage post coal mining activities as determined by the province of East Kalimantan as a corridor of economic activity masterplan acceleration of economic development expansion (MP3EI) is the behavior of adults. Adult behavior can be changed through knowledge management and attitude. Based on the root of the problem, the objective of the research is to apply knowledge management and attitude based on holistic approach in learning andragogy as an effort to solve environmental problems after coal mining activities. Research methods to achieve the objective of using quantitative research with pretest posttest group design. Knowledge management and attitudes based on a holistic approach in adult learning are applied through initial learning activities, core and case-based cover of environmental damage. The research instrument is a description of the case of environmental damage. The data analysis uses t-test to see the effect of knowledge management attitude based on holistic approach before and after adult learning. Location and sample of representative research of adults as many as 20 people in Kutai Kertanegara District, one of the districts in East Kalimantan province, which suffered the worst environmental damage. The conclusion of the research result is the application of knowledge management and attitude in adult learning influence to adult knowledge and attitude to overcome environmental problem post coal mining activity.

Keywords: knowledge management and attitude, holistic approach, andragogy learning, environmental damage

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Authors: Mafawez Alharbi, Mahdi Jemmali

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E-learning is a developing area especially in education. E-learning can provide several benefits to learners. An intelligent system to collect all components satisfying user preferences is so important. This research presents an approach that it capable to personalize e-information and give the user their needs following their preferences. This proposal can make some knowledge after more evaluations made by the user. In addition, it can learn from the habit from the user. Finally, we show a walk-through to prove how intelligent process work.

Keywords: artificial intelligence, architecture, e-learning, software engineering, processing

Procedia PDF Downloads 173

Authors: Pinn Tsin Isabel Yee

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Students are increasingly turning towards online learning materials to supplement their education. One such approach would be the gamified student engagement platforms (GSEPs) to instill a new learning culture. Data was collected from closed-ended questions via content analysis techniques. About 81.8% of college students from the Monash University Foundation Year agreed that GSEPs (Quizizz) was an effective tool for learning. Approximately 85.5% of students disagreed that games were a waste of time. GSEPs were highly effective among students to facilitate the learning process.

Keywords: engagement, gamified, Quizizz, technology

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Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

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Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: evolutionary computation, feature selection, classification, clustering

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Authors: Huie-Wen Lin

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This study integrated various teaching factors -based on the idea of a flipped classroom- in a financial management course. The study’s aim was to establish an effective teaching implementation strategy and evaluation mechanism with respect to learning outcomes, which can serve as a reference for the future modification of teaching methods. This study implemented a teaching method in five stages and estimated the learning efficiencies of 22 students (in the teaching scenario and over two semesters). Subsequently, data envelopment analysis (DEA) was used to compare, for each student, between the learning efficiencies before and after participation in the flipped classroom -in the first and second semesters, respectively- to identify the crucial external factors influencing learning efficiency. According to the results, the average overall student learning efficiency increased from 0.901 in the first semester to 0.967 in the second semester, which demonstrate that the flipped classroom approach can improve teaching effectiveness and learning outcomes. The results also revealed a difference in learning efficiency between male and female students.

Keywords: data envelopment analysis, flipped classroom, learning outcome, teaching and learning

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Authors: Firas A. Al Laban, Mohamed Chabi, Sammani Danwawu Abdullahi

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There are a real needs to integrate types of Open Educational Resources (OER) with an intelligent system to extract information and knowledge in the semantic searching level. Those needs raised because most of current learning standard adopted web based learning and the e-learning systems does not always serve all educational goals. Semantic Web systems provide educators, students, and researchers with intelligent queries based on a semantic knowledge management learning system. An ontology-based learning system is an advanced system, where ontology plays the core of the semantic web in a smart learning environment. The objective of this paper is to discuss the potentials of ontologies and mapping different kinds of ontologies; heterogeneous or homogenous to manage and control different types of Open Educational Resources. The important contribution of this research is to approach a methodology uses logical rules and conceptual relations to map between ontologies of different educational resources. We expect from this methodology to establish for an intelligent educational system supporting student tutoring, self and lifelong learning system.

Keywords: knowledge management systems, ontologies, semantic web, open educational resources

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Authors: Bryan Crompton, Daniel Giger, Tanay Mehta, Apurva Mody

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The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time.

Keywords: signal processing, machine learning, cyclostationary signal processing, signal classification

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Authors: Z. Abdullah, A. R. Hamdan

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Clustering is a process of grouping objects and data into groups of clusters to ensure that data objects from the same cluster are identical to each other. Clustering algorithms in one of the areas in data mining and it can be classified into partition, hierarchical, density based, and grid-based. Therefore, in this paper, we do a survey and review for four major hierarchical clustering algorithms called CURE, ROCK, CHAMELEON, and BIRCH. The obtained state of the art of these algorithms will help in eliminating the current problems, as well as deriving more robust and scalable algorithms for clustering.

Keywords: clustering, unsupervised learning, algorithms, hierarchical

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Authors: Konstantinos Sofianos, Michael Stefanidakis

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Nowadays, advances in information and communication technologies offer a range of opportunities for new approaches, methods, and tools in the field of education and training. Teacher-centered learning has changed to student-centered learning. E-learning has now matured and enables the design and construction of intelligent learning systems. A smart learning system fully adapts to a student's needs and provides them with an education based on their preferences, learning styles, and learning backgrounds. It is a wise friend and available at any time, in any place, and with any digital device. In this paper, we propose an intelligent learning system, which includes an ontology with all elements of the learning process (learning objects, learning activities) and a massive open online course (MOOC) system. This intelligent learning system can be used in music education.

Keywords: intelligent learning systems, e-learning, music education, ontology, semantic web

Procedia PDF Downloads 293

Authors: Roshani S. Golhar, Neerajkumar S. Sathawane, Snehal Dongre

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Background and objectives: As the, cardiovascular illnesses increasing and becoming cause of mortality worldwide, killing around lot of people each year. Arrhythmia is a type of cardiac illness characterized by a change in the linearity of the heartbeat. The goal of this study is to develop novel deep learning algorithms for successfully interpreting arrhythmia using a single second segment. Because the ECG signal indicates unique electrical heart activity across time, considerable changes between time intervals are detected. Such variances, as well as the limited number of learning data available for each arrhythmia, make standard learning methods difficult, and so impede its exaggeration. Conclusions: The proposed method was able to outperform several state-of-the-art methods. Also proposed technique is an effective and convenient approach to deep learning for heartbeat interpretation, that could be probably used in real-time healthcare monitoring systems

Keywords: electrocardiogram, ECG classification, neural networks, convolutional neural networks, portable document format

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Authors: Aloysius Hardoko, Susilo

Abstract:

The root cause of the problem after the environmental damage due to coal mining activities defined as the province of East Kalimantan corridor masterplan economic activity accelerated the expansion of Indonesia's economic development (MP3EI) is the behavior of adults. Adult behavior can be changed through knowledge management and attitude. Based on the root of the problem, the objective of the research is to apply knowledge management and attitude based on holistic approach in learning andragogy as an effort to solve environmental problems after coal mining activities. Research methods to achieve the objective of using quantitative research with pretest postes group design. Knowledge management and attitudes based on a holistic approach in adult learning are applied through initial learning activities, core and case-based cover of environmental damage. The research instrument is a description of the case of environmental damage. The data analysis uses t-test to see the effect of knowledge management attitude based on holistic approach before and after adult learning. Location and sample of representative research of adults as many as 20 people in Kutai Kertanegara District, one of the districts in East Kalimantan province, which suffered the worst environmental damage. The conclusion of the research result is the application of knowledge management and attitude in adult learning influence to adult knowledge and attitude to overcome environmental problem post-coal mining activity.

Keywords: knowledge management and attitude, holistic approach, andragogy learning, environmental Issue

Procedia PDF Downloads 192

Authors: H. Alqunayeer, S. Zamir

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Blended learning, an ideal amalgamation of online learning and face to face traditional approach is a new approach that may result in outstanding outcomes in the realm of teaching and learning. The dexterity and effectiveness offered by e-learning experience cannot be guaranteed in a traditional classroom, whereas one-to-one interaction the essential element of learning that can only be found in a traditional classroom. In recent years, a spectacular expansion in the incorporation of technology in language teaching and learning is observed in many universities of Saudi Arabia. Some universities recognize the importance of blending face-to-face with online instruction in language pedagogy, Qassim University is one of the many universities adopting Blackboard Learning Management system (LMS). The university has adopted this new mode of teaching/learning in year 2015. Although the experience is immature; however great pedagogical transformations are anticipated in the university through this new approach. This paper examines the role of blended language learning with particular reference to the influence of Blackboard Learning Management System on the development of English language learning for EFL learners registered in Bachelors of English language program. This paper aims at exploring three main areas: (i) the present status of Blended learning in the educational process in Saudi Arabia especially in Qassim University by providing a survey report on the number of training courses on Blackboard LMS conducted for the male and female teachers at various colleges of Qassim University, (ii) a survey on teachers perception about the utility, application and the outcome of using blended Learning approach in teaching English language skills courses, (iii) the students’ views on the efficiency of Blended learning approach in learning English language skills courses. Besides, analysis of students’ limitations and challenges related to the experience of blended learning via Blackboard, the suggestion and recommendations offered by the language learners have also been thought-out. The study is empirical in nature. In order to gather data on the afore mentioned areas survey questionnaire method has been used: in order to study students’ perception, a 5 point Likert-scale questionnaire has been distributed to 200 students of English department registered in Bachelors in English program (level 5 through level 8). Teachers’ views have been surveyed with the help of interviewing 25 EFL teachers skilled in using Blackboard LMS in their lectures. In order to ensure the validity and reliability of questionnaire, the inter-rater approach and Cronbach’s Alpha analysis have been used respectively. Analysis of variance (ANOVA) has been used to analyze the students’ perception about the productivity of the Blended approach in learning English language skills. The analysis of feedback by Saudi teachers and students about the usefulness, ingenuity, and productivity of Blended Learning via Blackboard LMS highlights the need of encouraging and expanding the implementation of this new approach into the field of English language teaching in Saudi Arabia, in order to augment congenial learning aura. Furthermore, it is hoped that the propositions and practical suggestions offered by the study will be functional for other similar learning environments.

Keywords: blended learning, black board learning management system, English as foreign language (EFL) learners, EFL teachers

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Authors: Marian Sorin Ionescu, Olivia Negoita, Cosmin Dobrin

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This scientific communication reports and discusses learning models adaptable to modern business problems and models specific to digital concepts and paradigms. In the PAC (probably approximately correct) learning model approach, in which the learning process begins by receiving a batch of learning examples, the set of learning processes is used to acquire a hypothesis, and when the learning process is fully used, this hypothesis is used in the prediction of new operational examples. For complex business models, a lot of models should be introduced and evaluated to estimate the induced results so that the totality of the results are used to develop a predictive rule, which anticipates the choice of new models. In opposition, for online learning-type processes, there is no separation between the learning (training) and predictive phase. Every time a business model is approached, a test example is considered from the beginning until the prediction of the appearance of a model considered correct from the point of view of the business decision. After choosing choice a part of the business model, the label with the logical value "true" is known. Some of the business models are used as examples of learning (training), which helps to improve the prediction mechanisms for future business models.

Keywords: machine learning, business models, convex analysis, online learning

Procedia PDF Downloads 127

Authors: K. V. F. Fatokun, P. A. Eniayeju

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This study concerns the effects of concept mapping-guided discovery integrated teaching approach on the learning style and achievement of chemistry students. The sample comprised 162 senior secondary school (SS 2) students drawn from two science schools in Nasarawa State which have equivalent mean scores of 9.68 and 9.49 in their pre-test. Five instruments were developed and validated while the sixth was purely adopted by the investigator for the study, Four null hypotheses were tested at α = 0.05 level of significance. Chi square analysis showed that there is a significant shift in students’ learning style from accommodating and diverging to converging and assimilating when exposed to concept mapping- guided discovery approach. Also t-test and ANOVA that those in experimental group achieve and retain content learnt better. Results of the Scheffe’s test for multiple comparisons showed that boys in the experimental group performed better than girls. It is therefore concluded that the concept mapping-guided discovery integrated approach should be used in secondary schools to successfully teach electrochemistry. It is strongly recommended that chemistry teachers should be encouraged to adopt this method for teaching difficult concepts.

Keywords: integrated teaching approach, concept mapping-guided discovery, achievement, retention, learning styles and interest

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Authors: Yasser F. Hassan

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Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: cellular automata, neural cellular automata, deep learning, classification

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Authors: Abraham Ampong

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BACKGROUND AND SIGNIFICANCE OF THE STUDY: The development of information technology and its influence today is inevitable in the world of education. The development of information technology and communication (ICT) has an impact on the use of teaching aids such as computers and the Internet, for example, E-learning. E-learning is a learning process attained through electronic means. But learning is not merely technology because learning is essentially more about the process of interaction between teacher, student, and source study. The main purpose of the study is to investigate learners’ online learning experiences in a blended learning approach, evaluate how learners’ experience of an online learning environment affects the blended learning approach and examine the future of online learning in a blended learning environment. Blended learning pedagogies have been recognized as a path to improve teacher’s instructional strategies for teaching using technology. Blended learning is perceived to have many advantages for teachers and students, including any-time learning, anywhere access, self-paced learning, inquiry-led learning and collaborative learning; this helps institutions to create desired instructional skills such as critical thinking in the process of learning. Blended learning as an approach to learning has gained momentum because of its widespread integration into educational organizations. METHODOLOGY: Based on the research objectives and questions of the study, the study will make use of the qualitative research approach. The rationale behind the selection of this research approach is that participants are able to make sense of their situations and appreciate their construction of knowledge and understanding because the methods focus on how people understand and interpret their experiences. A case study research design is adopted to explore the situation under investigation. The target population for the study will consist of selected students from selected universities. A simple random sampling technique will be used to select the targeted population. The data collection instrument that will be adopted for this study will be questions that will serve as an interview guide. An interview guide is a set of questions that an interviewer asks when interviewing respondents. Responses from the in-depth interview will be transcribed into word and analyzed under themes. Ethical issues to be catered for in this study include the right to privacy, voluntary participation, and no harm to participants, and confidentiality. INDICATORS OF THE MAJOR FINDINGS: It is suitable for the study to find out that online learning encourages timely feedback from teachers or that online learning tools are okay to use without issues. Most of the communication with the teacher can be done through emails and text messages. It is again suitable for sampled respondents to prefer online learning because there are few or no distractions. Learners can have access to technology to do other activities to support their learning”. There are, again, enough and enhanced learning materials available online. CONCLUSION: Unlike the previous research works focusing on the strengths and weaknesses of blended learning, the present study aims at the respective roles of its two modalities, as well as their interdependencies.

Keywords: online learning, blended learning, technologies, teaching methods

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Authors: Evgeny Pyshkin, Maxim Mozgovoy, Vladislav Volkov

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The paper follows a discourse on computer-assisted language learning. We examine problems of foreign language teaching and learning and introduce a metamodel that can be used to define learning models of language grammar structures in order to support teacher/student interaction. Special attention is paid to the concept of a virtual language lab. Our approach to language education assumes to encourage learners to experiment with a language and to learn by discovering patterns of grammatically correct structures created and managed by a language expert.

Keywords: computer-assisted instruction, language learning, natural language grammar models, HCI

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Authors: Rita Gill Singh, Alex Chun Koon, Cindy Sing Bik Ngai, Joanna Wen Ying Ho, Mei Li Khong, Enoch Chan, Terrence Lau

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Although humour is viewed as a beneficial element in teaching, there has been little attempt to systematize humour in teaching, possibly because it is difficult to teach someone to be humorous. This study integrated planned humour pedagogical approach into teaching and learning activities and examined the effect of systematically planned humour on students’ engagement and learning in different courses. Specifically, appropriate types of humour (i.e. analogy, absurdity and wordplay) and incorporation methods and frequency were systematically integrated into the lessons of courses at some higher education institutions in Hong Kong. The results showed that the planned humour pedagogical approach increased student engagement, as well as enhanced learning and motivation while reducing students’ stress. The pedagogical implications of this study will be useful for researchers, practitioners, and educators.

Keywords: higher education, pedagogy, humour, student engagement, learning, motivation

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

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

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

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Authors: Xin Zhao

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The project aims to expand the notion of narrative learning and address the importance of learning by reflection in our learning and teaching context at a British university. Drawing on the key concepts such as development ZPD, transition and reflection-in and –on-action, this project analyses the learning experiences of a small sample of Chinese postgraduate students in a British University, who use part-time job experience to develop cross-cultural communication skills. The project adopts a mixed methods approach. Questionnaires and focus group interviews are used to examine the way in which students adapt (or not adapt) to the culture of learning in a British university and develop a renewed sense of self in transitions from one culture to the other. The project also looks at how the students appropriate opportunities for learning not just from classrooms but outside classrooms from everyday encounters. The project aims to address the implication of learning by reflection as development in transition. Time in and for learning, or duration, is taken for granted in theorising narrative learning. The project shall explore this very issue of time in relation to learning by reflection in considering time in/of/for learning as duration.

Keywords: cross-cultural competence, learning by refection, international student transition, part-time work experience

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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Authors: Aqeel Zeid, Hasna Anees, Mohamed Adheeb, Mohamed Rifan, Kalpani Manathunga

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To achieve constructive alignment in a higher education program, a clear set of learning outcomes must be defined. Traditional learning outcome definition techniques such as Bloom’s taxonomy are not written to be utilized by the student. This might be disadvantageous for students in student-centric learning settings where the students are expected to formulate their own learning strategies. To solve the problem, we propose the learning outcome relation and aggregation (LORA) model. To achieve alignment, we developed learning outcome, assessment, and resource authoring tools which help teachers to tag learning outcomes during creation. A pilot study was conducted with an expert panel consisting of experienced professionals in the education domain to evaluate whether the LORA model and tools present an improvement over the traditional methods. The panel unanimously agreed that the model and tools are beneficial and effective. Moreover, it helped them model learning outcomes in a more student centric and descriptive way.

Keywords: learning design, constructive alignment, Bloom’s taxonomy, learning outcome modelling

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Authors: Kenneth N. Ohei, Roelien Brink

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For decades, teaching and learning processes have centered on the traditional approach (Web 1.0) that promoted teacher-directed pedagogical practices. Currently, there is a realization that the traditional approach is not adequate to effectively address and improve all student-learning outcomes. The subsequent incorporation of social software, Information, and Communication Technology (ICT) tools in universities may serve as complementary to support educational goals, offering students the affordability and opportunity to educational choices and learning platforms. Consequently, educators’ inability to incorporate these instructional ICT tools in their teaching and learning practices remains a challenge. This will signify that educators still lack the ICT skills required to administer lectures and bridging learning gaps. This study probes a methodological concept with the aim of developing a framework towards the adoption of social software in HES to help facilitate business processes and can build social presence among students. A mixed method will be appropriate to develop a comprehensive framework needed in Higher Educational System (HES). After research have been conducted, the adoption of social software will be based on the developed comprehensive framework which is supposed to impact positively on education and approach of delivery, improves learning experience, engagement and finally, increases educational opportunities and easy access to educational contents.

Keywords: blended and integrated learning, learning experience and engagement, higher educational system, HES, information and communication technology, ICT, social presence, Web 1.0, Web 2.0, Web 3.0

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Authors: B.J. Khoza, B. Kembo

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Global socioeconomic developments and ever-growing technological advancements of the art and design industry indicate the pivotal importance of lifelong learning. There exists a discrepancy between competencies, personal ambition, and workplace requirements. There are few , if at all, institutions of higher learning in South Africa which offer Short Learning Programmes (SLP) in Art and Design Education. Traditionally, Art and Design education is delivered face to face via a hands-on approach. In this way the enduring perception among educators is that art and design education does not lend itself to online delivery. Short Learning programmes (SLP) are a concentrated approach to make revenue and lure potential prospective students to embark on further education study, this is often of weighted value to both students and employers. SLPs are used by Higher Education institutions to generate income in support of the core academic programmes. However, there is a gap in terms of the translation of art and design studio pedagogy into SLPs which provide quality education, are adaptable and delivered via a blended mode. In our paper, we propose a conceptual framework drawing on secondary research to analyse existing research to SLPs for arts and design education. We aim to indicate a new dimension to the process of using a design-based research approach for short learning programmes in art and design education. The study draws on a conceptual framework, a qualitative analysis through the lenses of Herrington, McKenney, Reeves and Oliver (2005) principles of the design-based research approach. The results of this study indicate that design-based research is not only an effective methodological approach for developing and deploying arts and design education curriculum for 1st years in Higher Education context but it also has the potential to guide future research. The findings of this study propose that the design-based research approach could bring theory and praxis together regarding a common purpose to design context-based solutions to educational problems.

Keywords: design education, design-based research, digital literacies, multi-literacies, short learning programme

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Authors: Ouafa Amira, Jiangshe Zhang

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Clustering is an unsupervised machine learning technique; its aim is to extract the data structures, in which similar data objects are grouped in the same cluster, whereas dissimilar objects are grouped in different clusters. Clustering methods are widely utilized in different fields, such as: image processing, computer vision , and pattern recognition, etc. Fuzzy c-means clustering (fcm) is one of the most well known fuzzy clustering methods. It is based on solving an optimization problem, in which a minimization of a given cost function has been studied. This minimization aims to decrease the dissimilarity inside clusters, where the dissimilarity here is measured by the distances between data objects and cluster centers. The degree of belonging of a data point in a cluster is measured by a membership function which is included in the interval [0, 1]. In fcm clustering, the membership degree is constrained with the condition that the sum of a data object’s memberships in all clusters must be equal to one. This constraint can cause several problems, specially when our data objects are included in a noisy space. Regularization approach took a part in fuzzy c-means clustering technique. This process introduces an additional information in order to solve an ill-posed optimization problem. In this study, we focus on regularization by relative entropy approach, where in our optimization problem we aim to minimize the dissimilarity inside clusters. Finding an appropriate membership degree to each data object is our objective, because an appropriate membership degree leads to an accurate clustering result. Our clustering results in synthetic data sets, gaussian based data sets, and real world data sets show that our proposed model achieves a good accuracy.

Keywords: clustering, fuzzy c-means, regularization, relative entropy

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Authors: Yi-Hsiang Pan, Ching-Hsiang Chen, Wei-Ting Hsu

Abstract:

The purpose of this study was to compare the learning effects of the sports education model (SEM) to those of the traditional teaching model (TTM) in physical education classes in terms of students learning motivation, action control, learning strategies, and learning performance. A quasi-experimental design was utilized in this study, and participants included two physical educators and four classes with a total of 94 students in grades 5 and 6 of elementary schools. Two classes implemented the SEM (n=47, male=24, female=23; age=11.89, SD=0.78) and two classes implemented the TTM (n=47, male=25, female=22, age=11.77; SD=0.66). Data were collected from these participants using a self-report questionnaire (including a learning motivation scale, action control scale, and learning strategy scale) and a game performance assessment instrument, and multivariate analysis of covariance was used to conduct statistical analysis. The findings of the study revealed that the SEM was significantly better than the TTM in promoting students learning motivation, action control, learning strategies, and game performance. It was concluded that the SEM could promote the mechanics of students self-regulated learning process, and thereby improve students movement performance.

Keywords: self-regulated learning theory, learning process, curriculum model, physical education

Procedia PDF Downloads 323

Authors: M. Kharrat, G. Moreau, Z. Aboura

Abstract:

The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

Procedia PDF Downloads 142