Search results for: robust learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8355

Search results for: robust learning

7935 Deep Learning-Based Liver 3D Slicer for Image-Guided Therapy: Segmentation and Needle Aspiration

Authors: Ahmedou Moulaye Idriss, Tfeil Yahya, Tamas Ungi, Gabor Fichtinger

Abstract:

Image-guided therapy (IGT) plays a crucial role in minimally invasive procedures for liver interventions. Accurate segmentation of the liver and precise needle placement is essential for successful interventions such as needle aspiration. In this study, we propose a deep learning-based liver 3D slicer designed to enhance segmentation accuracy and facilitate needle aspiration procedures. The developed 3D slicer leverages state-of-the-art convolutional neural networks (CNNs) for automatic liver segmentation in medical images. The CNN model is trained on a diverse dataset of liver images obtained from various imaging modalities, including computed tomography (CT) and magnetic resonance imaging (MRI). The trained model demonstrates robust performance in accurately delineating liver boundaries, even in cases with anatomical variations and pathological conditions. Furthermore, the 3D slicer integrates advanced image registration techniques to ensure accurate alignment of preoperative images with real-time interventional imaging. This alignment enhances the precision of needle placement during aspiration procedures, minimizing the risk of complications and improving overall intervention outcomes. To validate the efficacy of the proposed deep learning-based 3D slicer, a comprehensive evaluation is conducted using a dataset of clinical cases. Quantitative metrics, including the Dice similarity coefficient and Hausdorff distance, are employed to assess the accuracy of liver segmentation. Additionally, the performance of the 3D slicer in guiding needle aspiration procedures is evaluated through simulated and clinical interventions. Preliminary results demonstrate the effectiveness of the developed 3D slicer in achieving accurate liver segmentation and guiding needle aspiration procedures with high precision. The integration of deep learning techniques into the IGT workflow shows great promise for enhancing the efficiency and safety of liver interventions, ultimately contributing to improved patient outcomes.

Keywords: deep learning, liver segmentation, 3D slicer, image guided therapy, needle aspiration

Procedia PDF Downloads 43
7934 An Experience Report on Course Teaching in Information Systems

Authors: Carlos Oliveira

Abstract:

This paper is a criticism of the traditional model of teaching and presents alternative teaching methods, different from the traditional lecture. These methods are accompanied by reports of experience of their application in a class. It was concluded that in the lecture, the student has a low learning rate and that other methods should be used to make the most engaging learning environment for the student, contributing (or facilitating) his learning process. However, the teacher should not use a single method, but rather a range of different methods to ensure the learning experience does not become repetitive and fatiguing for the student.

Keywords: educational practices, experience report, IT in education, teaching methods

Procedia PDF Downloads 393
7933 Design of Neural Predictor for Vibration Analysis of Drilling Machine

Authors: İkbal Eski

Abstract:

This investigation is researched on design of robust neural network predictors for analyzing vibration effects on moving parts of a drilling machine. Moreover, the research is divided two parts; first part is experimental investigation, second part is simulation analysis with neural networks. Therefore, a real time the drilling machine is used to vibrations during working conditions. The measured real vibration parameters are analyzed with proposed neural network. As results: Simulation approaches show that Radial Basis Neural Network has good performance to adapt real time parameters of the drilling machine.

Keywords: artificial neural network, vibration analyses, drilling machine, robust

Procedia PDF Downloads 388
7932 An Experimental Study of Online Peer-to-Peer Language Learning

Authors: Abrar Al-Hasan

Abstract:

Web 2.0 has significantly increased the amount of information available to users not only about firms and their offerings, but also about the activities of other individuals in their networks and markets. It is widely acknowledged that this increased availability of ‘social’ information, particularly about other individuals, is likely to influence a user’s behavior and choices. However, there are very few systematic studies of how such increased information transparency on the behavior of other users in a focal users’ network influences a focal users’ behavior in the emerging marketplace of online language learning. This study seeks to examine the value and impact of ‘social activities’ – wherein, a user sees and interacts with the learning activities of her peers – on her language learning efficiency. An online experiment in a peer-to-peer language marketplace was conducted to compare the learning efficiency of users with ‘social’ information versus users with no ‘social’ information. The results of this study highlight the impact and importance of ‘social’ information within the language learning context. The study concludes by exploring how these insights may inspire new developments in online education.

Keywords: e-Learning, language learning marketplace, peer-to-peer, social network

Procedia PDF Downloads 379
7931 Investigating the Experiences of Higher Education Academics on the Blended Approach Used during the Induction Course

Authors: Ann-May Marais

Abstract:

South African higher education institutions are following the global adoption of a blended approach to teaching and learning. Blended learning is viewed as a transformative teaching-learning approach, as it provides students with the optimum experience by mixing the best of face-to-face and online learning. Although academics realise the benefits of blended learning, they find it challenging and time-consuming to implement blended strategies. Professional development is a critical component of the adoption of higher education teaching-learning approaches. The Institutional course for higher education academics offered at a South African University was designed in a blended model, implemented and evaluated. This paper reports on a study that investigated the experiences of academics on the blended approach used during the induction course. A qualitative design-based research methodology was employed, and data was collected using participant feedback and document analysis. The data gathered from each of the four ICNL offerings were used to inform the design of the next course. Findings indicated that lecturers realised that blended learning could cater to student diversity, different learning styles, engagement, and innovation. Furthermore, it emerged that the course has to cater for diversity in technology proficiency and readiness of participants. Participants also require ongoing support in technology usage and discipline-specific blended learning workshops. This paper contends that the modelling of a blended approach to professional development can be an effective way to motivate academics to apply blended learning in their teaching-learning experiences.

Keywords: blended learning, professional development, induction course, integration of technology

Procedia PDF Downloads 158
7930 Research on Community-Based Engineering Learning and Undergraduate Students’ Creativity in China: The Moderate Effect of Engineering Identity

Authors: Liang Wang, Wei Zhang

Abstract:

There have been some existing researches on design-based engineering learning (DBEL) and project-based or problem-based engineering learning (PBEL). Those findings have greatly promoted the reform of engineering education in China. However, the engineering with a big E means that more and more engineering activities are designed and operated by communities of practice (CoPs), namely community-based engineering learning. However, whether community-based engineering learning can promote students' innovation has not been verified in published articles. This study fills this gap by investigating the relationship between community-based learning approach and students’ creativity, using engineering identity as an intermediary variable. The goal of this study is to discover the core features of community-based engineering learning, and make the features more beneficial for students’ creativity. The study created and adapted open survey items from previously published studies and a scale on learning community, students’ creativity and engineering identity. Firstly, qualitative content analysis methods by MAXQDA were used to analyze 32 open-ended questionnaires. Then the authors collected data (n=322) from undergraduate students in engineering competition teams and engineering laboratories in Zhejiang University, and structural equation modelling (SEM) was used to understand the relationship between different factors. The study finds: (a) community-based engineering learning has four main elements like real-task context, self-inquiry learning, deeply-consulted cooperation and circularly-iterated design, (b) community-based engineering learning can significantly enhance the engineering undergraduate students’ creativity, and (c) engineering identity partially moderated the relationship between community-based engineering learning and undergraduate students' creativity. The findings further illustrate the value of community-based engineering learning for undergraduate students. In the future research, the authors should further clarify the core mechanism of community-based engineering learning, and pay attention to the cultivation of undergraduate students’ engineer identity in learning community.

Keywords: community-based engineering learning, students' creativity, engineering identity, moderate effect

Procedia PDF Downloads 142
7929 A Peer-Produced Community of Learning: The Case of Second-Year Algerian Masters Students at a Distance

Authors: Nihad Alem

Abstract:

Nowadays, distance learning (DL) is widely perceived as a reformed type of education that takes advantage of technology to give more appealing opportunities especially for learners whose life conditions impede their attendance to regular classrooms however, creating interactional environment for students to expand their learning community and alleviate the feeling of loneliness and isolation should receive more attention when designing a distance learning course. This research aims to explore whether the audio/video peer learning can offer pedagogical add-ons to the Algerian distance learners and what are the pros and cons of its application as an educational experience in a synchronous environment mediated by Skype. Data were collected using video recordings of six sessions, reflective logs, and in-depth semi-structured interviews and will be analyzed by qualitatively identifying and measuring the three constitutional elements of the educational experience of peer learning namely the social presence, the cognitive presence, and the facilitation presence using a modified community of inquiry coding template. The findings from this study will provide recommendations for effective peer learning educational experience using the facilitation presence concept.

Keywords: audio/visual peer learning, community of inquiry, distance learning, facilitation presence

Procedia PDF Downloads 146
7928 Web Application for Evaluating Tests in Distance Learning Systems

Authors: Bogdan Walek, Vladimir Bradac, Radim Farana

Abstract:

Distance learning systems offer useful methods of learning and usually contain final course test or another form of test. The paper proposes web application for evaluating tests using expert system in distance learning systems. Proposed web application is appropriate for didactic tests or tests with results for subsequent studying follow-up courses. Web application works with test questions and uses expert system and LFLC tool for test evaluation. After test evaluation the results are visualized and shown to student.

Keywords: distance learning, test, uncertainty, fuzzy, expert system, student

Procedia PDF Downloads 482
7927 Investigation the Impact of Flipped Learning on Developing Meta-Cognitive Ability in Chemistry Courses of Science Education Students

Authors: R. Herscu-Kluska

Abstract:

The rise of the flipped or inverted classroom meet the conceptual needs of our time. The evidence of increased student satisfaction and course grades improvement promoted the flipped learning approach. Due to the successful outcomes of the inverted classroom, the flipped learning became a pedagogy and educational rising strategy among all education sciences. The aim of this study is to analyze the effect of flipped classroom on higher order learning in chemistry courses since it has been suggested that in higher education courses, class time should focus on knowledge application. The results of this study indicate improving meta-cognitive thinking and learning skills. The students showed better ability to cope with higher order learning assignments during the actual class time, using inverted classroom strategy. These results suggest that flipped learning can be used as an effective pedagogy and educational strategy for developing higher order thinking skills, proved to contribute to building lifelong learning.

Keywords: chemistry education, flipped classroom, flipped learning, inverted classroom, science education

Procedia PDF Downloads 340
7926 Metanotes and Foreign Language Learning: A Case of Iranian EFL Learners

Authors: Nahıd Naderı Anarı, Mojdeh Shafıee

Abstract:

Languaging has been identified as a contributor to language learning. Compared to oral languaging, written languaging seems to have been less explored. In order to fill this gap, this paper examined the effect of ‘metanotes’, namely metatalk in a written modality to identify whether written languaging actually facilitates language learning. Participants were instructed to take metanotes as they performed a translation task. The effect of metanotes was then analyzed by comparing the results of these participants’ pretest and posttest with those of participants who performed the same task without taking metanotes. The statistical tests showed no evidence of the expected role of metanotes in foreign language learning.

Keywords: EFL learners, foreign language learning, language teaching, metanotes

Procedia PDF Downloads 440
7925 Fault-Tolerant Predictive Control for Polytopic LPV Systems Subject to Sensor Faults

Authors: Sofiane Bououden, Ilyes Boulkaibet

Abstract:

In this paper, a robust fault-tolerant predictive control (FTPC) strategy is proposed for systems with linear parameter varying (LPV) models and input constraints subject to sensor faults. Generally, virtual observers are used for improving the observation precision and reduce the impacts of sensor faults and uncertainties in the system. However, this type of observer lacks certain system measurements which substantially reduce its accuracy. To deal with this issue, a real observer is then designed based on the virtual observer, and consequently a real observer-based robust predictive control is designed for polytopic LPV systems. Moreover, the proposed observer can entirely assure that all system states and sensor faults are estimated. As a result, and based on both observers, a robust fault-tolerant predictive control is then established via the Lyapunov method where sufficient conditions are proposed, for stability analysis and control purposes, in linear matrix inequalities (LMIs) form. Finally, simulation results are given to show the effectiveness of the proposed approach.

Keywords: linear parameter varying systems, fault-tolerant predictive control, observer-based control, sensor faults, input constraints, linear matrix inequalities

Procedia PDF Downloads 195
7924 Scaling Siamese Neural Network for Cross-Domain Few Shot Learning in Medical Imaging

Authors: Jinan Fiaidhi, Sabah Mohammed

Abstract:

Cross-domain learning in the medical field is a research challenge as many conditions, like in oncology imaging, use different imaging modalities. Moreover, in most of the medical learning applications, the sample training size is relatively small. Although few-shot learning (FSL) through the use of a Siamese neural network was able to be trained on a small sample with remarkable accuracy, FSL fails to be effective for use in multiple domains as their convolution weights are set for task-specific applications. In this paper, we are addressing this problem by enabling FSL to possess the ability to shift across domains by designing a two-layer FSL network that can learn individually from each domain and produce a shared features map with extra modulation to be used at the second layer that can recognize important targets from mix domains. Our initial experimentations based on mixed medical datasets like the Medical-MNIST reveal promising results. We aim to continue this research to perform full-scale analytics for testing our cross-domain FSL learning.

Keywords: Siamese neural network, few-shot learning, meta-learning, metric-based learning, thick data transformation and analytics

Procedia PDF Downloads 51
7923 Control of Underactuated Biped Robots Using Event Based Fuzzy Partial Feedback Linearization

Authors: Omid Heydarnia, Akbar Allahverdizadeh, Behnam Dadashzadeh, M. R. Sayyed Noorani

Abstract:

Underactuated biped robots control is one of the interesting topics in robotics. The main difficulties are its highly nonlinear dynamics, open-loop instability, and discrete event at the end of the gait. One of the methods to control underactuated systems is the partial feedback linearization, but it is not robust against uncertainties and disturbances that restrict its performance to control biped walking and running. In this paper, fuzzy partial feedback linearization is presented to overcome its drawback. Numerical simulations verify the effectiveness of the proposed method to generate stable and robust biped walking and running gaits.

Keywords: underactuated system, biped robot, fuzzy control, partial feedback linearization

Procedia PDF Downloads 347
7922 International Service Learning 3.0: Using Technology to Improve Outcomes and Sustainability

Authors: Anthony Vandarakis

Abstract:

Today’s International Service Learning practices require an update: modern technologies, fresh educational frameworks, and a new operating system to accountably prosper. This paper describes a model of International Service Learning (ISL), which combines current technological hardware, electronic platforms, and asynchronous communications that are grounded in inclusive pedagogy. This model builds on the work around collaborative field trip learning, extending the reach to international partnerships across continents. Mobile technology, 21st century skills and summit-basecamp modeling intersect to support novel forms of learning that tread lightly on fragile natural ecosystems, affirm local reciprocal partnership in projects, and protect traveling participants from common yet avoidable cultural pitfalls.

Keywords: International Service Learning, ISL, field experiences, mobile technology, out there in here, summit basecamp pedagogy

Procedia PDF Downloads 170
7921 Fostering Students’ Active Learning in Speaking Class through Project-Based Learning

Authors: Rukminingsih Rukmi

Abstract:

This paper addresses the issue of L2 teaching speaking to ESL students by fostering their active learning through project-based learning. Project-based learning was employed in classrooms where teachers support students by giving sufficient guidance and feedback. The students drive the inquiry, engage in research and discovery, and collaborate effectively with teammates to deliver the final work product. The teacher provides the initial direction and acts as a facilitator along the way. This learning approach is considered helpful for fostering students’ active learning. that the steps in implementing of project-based learning that fosters students’ critical thinking in TEFL class are in the following: (1) Discussing the materials about Speaking Class, (2) Working with the group to construct scenario of ways on speaking practice, (3) Practicing the scenario, (4) Recording the speaking practice into video, and (5) Evaluating the video product. This research is aimed to develop a strategy of teaching speaking by implementing project-based learning to improve speaking skill in the second Semester of English Department of STKIP PGRI Jombang. To achieve the purpose, the researcher conducted action research. The data of the study were gathered through the following instruments: test, observation checklists, and questionnaires. The result was indicated by the increase of students’ average speaking scores from 65 in the preliminary study, 73 in the first cycle, and 82 in the second cycle. Besides, the results of the study showed that project-based learning considered to be appropriate strategy to give students the same amount of chance in practicing their speaking skill and to pay attention in creating a learning situation.

Keywords: active learning, project-based learning, speaking ability, L2 teaching speaking

Procedia PDF Downloads 396
7920 A Framework for SQL Learning: Linking Learning Taxonomy, Cognitive Model and Cross Cutting Factors

Authors: Huda Al Shuaily, Karen Renaud

Abstract:

Databases comprise the foundation of most software systems. System developers inevitably write code to query these databases. The de facto language for querying is SQL and this, consequently, is the default language taught by higher education institutions. There is evidence that learners find it hard to master SQL, harder than mastering other programming languages such as Java. Educators do not agree about explanations for this seeming anomaly. Further investigation may well reveal the reasons. In this paper, we report on our investigations into how novices learn SQL, the actual problems they experience when writing SQL, as well as the differences between expert and novice SQL query writers. We conclude by presenting a model of SQL learning that should inform the instructional material design process better to support the SQL learning process.

Keywords: pattern, SQL, learning, model

Procedia PDF Downloads 253
7919 Problems of Learning English Vowels Pronunciation in Nigeria

Authors: Wasila Lawan Gadanya

Abstract:

This paper examines the problems of learning English vowel pronunciation. The objective is to identify some of the factors that affect the learning of English vowel sounds and their proper realization in words. The theoretical framework adopted is based on both error analysis and contrastive analysis. The data collection instruments used in the study are questionnaire and word list for the respondents (students) and observation of some of their lecturers. All the data collected were analyzed using simple percentage. The findings show that it is not a single factor that affects the learning of English vowel pronunciation rather many factors concurrently do so. Among the factors examined, it has been found that lack of correlation between English orthography and its pronunciation, not mother-tongue (which most people consider as a factor affecting learning of the pronunciation of a second language), has the greatest influence on students’ learning and realization of English vowel sounds since the respondents in this study are from different ethnic groups of Nigeria and thus speak different languages but having the same or almost the same problem when pronouncing the English vowel sounds.

Keywords: English vowels, learning, Nigeria, pronunciation

Procedia PDF Downloads 441
7918 Personalize E-Learning System Based on Clustering and Sequence Pattern Mining Approach

Authors: H. S. Saini, K. Vijayalakshmi, Rishi Sayal

Abstract:

Network-based education has been growing rapidly in size and quality. Knowledge clustering becomes more important in personalized information retrieval for web-learning. A personalized-Learning service after the learners’ knowledge has been classified with clustering. Through automatic analysis of learners’ behaviors, their partition with similar data level and interests may be discovered so as to produce learners with contents that best match educational needs for collaborative learning. We present a specific mining tool and a recommender engine that we have integrated in the online learning in order to help the teacher to carry out the whole e-learning process. We propose to use sequential pattern mining algorithms to discover the most used path by the students and from this information can recommend links to the new students automatically meanwhile they browse in the course. We have Developed a specific author tool in order to help the teacher to apply all the data mining process. We tend to report on many experiments with real knowledge so as to indicate the quality of using both clustering and sequential pattern mining algorithms together for discovering personalized e-learning systems.

Keywords: e-learning, cluster, personalization, sequence, pattern

Procedia PDF Downloads 424
7917 Comparing Xbar Charts: Conventional versus Reweighted Robust Estimation Methods for Univariate Data Sets

Authors: Ece Cigdem Mutlu, Burak Alakent

Abstract:

Maintaining the quality of manufactured products at a desired level depends on the stability of process dispersion and location parameters and detection of perturbations in these parameters as promptly as possible. Shewhart control chart is the most widely used technique in statistical process monitoring to monitor the quality of products and control process mean and variability. In the application of Xbar control charts, sample standard deviation and sample mean are known to be the most efficient conventional estimators in determining process dispersion and location parameters, respectively, based on the assumption of independent and normally distributed datasets. On the other hand, there is no guarantee that the real-world data would be normally distributed. In the cases of estimated process parameters from Phase I data clouded with outliers, efficiency of traditional estimators is significantly reduced, and performance of Xbar charts are undesirably low, e.g. occasional outliers in the rational subgroups in Phase I data set may considerably affect the sample mean and standard deviation, resulting a serious delay in detection of inferior products in Phase II. For more efficient application of control charts, it is required to use robust estimators against contaminations, which may exist in Phase I. In the current study, we present a simple approach to construct robust Xbar control charts using average distance to the median, Qn-estimator of scale, M-estimator of scale with logistic psi-function in the estimation of process dispersion parameter, and Harrell-Davis qth quantile estimator, Hodge-Lehmann estimator and M-estimator of location with Huber psi-function and logistic psi-function in the estimation of process location parameter. Phase I efficiency of proposed estimators and Phase II performance of Xbar charts constructed from these estimators are compared with the conventional mean and standard deviation statistics both under normality and against diffuse-localized and symmetric-asymmetric contaminations using 50,000 Monte Carlo simulations on MATLAB. Consequently, it is found that robust estimators yield parameter estimates with higher efficiency against all types of contaminations, and Xbar charts constructed using robust estimators have higher power in detecting disturbances, compared to conventional methods. Additionally, utilizing individuals charts to screen outlier subgroups and employing different combination of dispersion and location estimators on subgroups and individual observations are found to improve the performance of Xbar charts.

Keywords: average run length, M-estimators, quality control, robust estimators

Procedia PDF Downloads 186
7916 DNA Methylation Score Development for In utero Exposure to Paternal Smoking Using a Supervised Machine Learning Approach

Authors: Cristy Stagnar, Nina Hubig, Diana Ivankovic

Abstract:

The epigenome is a compelling candidate for mediating long-term responses to environmental effects modifying disease risk. The main goal of this research is to develop a machine learning-based DNA methylation score, which will be valuable in delineating the unique contribution of paternal epigenetic modifications to the germline impacting childhood health outcomes. It will also be a useful tool in validating self-reports of nonsmoking and in adjusting epigenome-wide DNA methylation association studies for this early-life exposure. Using secondary data from two population-based methylation profiling studies, our DNA methylation score is based on CpG DNA methylation measurements from cord blood gathered from children whose fathers smoked pre- and peri-conceptually. Each child’s mother and father fell into one of three class labels in the accompanying questionnaires -never smoker, former smoker, or current smoker. By applying different machine learning algorithms to the accessible resource for integrated epigenomic studies (ARIES) sub-study of the Avon longitudinal study of parents and children (ALSPAC) data set, which we used for training and testing of our model, the best-performing algorithm for classifying the father smoker and mother never smoker was selected based on Cohen’s κ. Error in the model was identified and optimized. The final DNA methylation score was further tested and validated in an independent data set. This resulted in a linear combination of methylation values of selected probes via a logistic link function that accurately classified each group and contributed the most towards classification. The result is a unique, robust DNA methylation score which combines information on DNA methylation and early life exposure of offspring to paternal smoking during pregnancy and which may be used to examine the paternal contribution to offspring health outcomes.

Keywords: epigenome, health outcomes, paternal preconception environmental exposures, supervised machine learning

Procedia PDF Downloads 181
7915 Cultural Understanding in Chinese Language Education for Foreigners: A Quest for Better Integration

Authors: Linhan Sun

Abstract:

With the gradual strengthening of China's economic development, more and more people around the world are learning Chinese due to economic and trade needs, which has also promoted the research related to Chinese language education for foreigners. Because the Chinese language system is different from the Western language system, learning Chinese is not easy for many learners. In addition, language learning cannot be separated from the learning and understanding of culture. How to integrate cultural learning into the curriculum of Chinese language education for foreigners is the focus of this study. Through a semi-structured in-depth interview method, 15 foreigners who have studied or are studying Chinese participated in this study. This study found that cultural learning and Chinese as a foreign language are relatively disconnected. In other words, learners were able to acquire a certain degree of knowledge of the Chinese language through textbooks or courses but did not gain a deeper understanding of Chinese culture.

Keywords: Chinese language education, Chinese culture, qualitative methods, intercultural communication

Procedia PDF Downloads 162
7914 Robust Noisy Speech Identification Using Frame Classifier Derived Features

Authors: Punnoose A. K.

Abstract:

This paper presents an approach for identifying noisy speech recording using a multi-layer perception (MLP) trained to predict phonemes from acoustic features. Characteristics of the MLP posteriors are explored for clean speech and noisy speech at the frame level. Appropriate density functions are used to fit the softmax probability of the clean and noisy speech. A function that takes into account the ratio of the softmax probability density of noisy speech to clean speech is formulated. These phoneme independent scoring is weighted using a phoneme-specific weightage to make the scoring more robust. Simple thresholding is used to identify the noisy speech recording from the clean speech recordings. The approach is benchmarked on standard databases, with a focus on precision.

Keywords: noisy speech identification, speech pre-processing, noise robustness, feature engineering

Procedia PDF Downloads 124
7913 Customization of Moodle Open Source LMS for Tanzania Secondary Schools’ Use

Authors: Ellen A. Kalinga

Abstract:

Moodle is an open source learning management system that enables creation of a powerful and flexible learning environment. Many organizations, especially learning institutions have customized Moodle open source LMS for their own use. In general open source LMSs are of great interest due to many advantages they offer in terms of cost, usage and freedom to customize to fit a particular context. Tanzania Secondary School e-Learning (TanSSe-L) system is the learning management system for Tanzania secondary schools. TanSSe-L system was developed using a number of methods, one of them being customization of Moodle Open Source LMS. This paper presents few areas on the way Moodle OS LMS was customized to produce a functional TanSSe-L system fitted to the requirements and specifications of Tanzania secondary schools’ context.

Keywords: LMS, Moodle, e-learning, Tanzania, secondary school

Procedia PDF Downloads 387
7912 Improving Learning and Teaching of Software Packages among Engineering Students

Authors: Sara Moridpour

Abstract:

To meet emerging industry needs, engineering students must learn different software packages and enhance their computational skills. Traditionally, face-to-face is selected as the preferred approach to teaching software packages. Face-to-face tutorials and workshops provide an interactive environment for learning software packages where the students can communicate with the teacher and interact with other students, evaluate their skills, and receive feedback. However, COVID-19 significantly limited face-to-face learning and teaching activities at universities. Worldwide lockdowns and the shift to online and remote learning and teaching provided the opportunity to introduce different strategies to enhance the interaction among students and teachers in online and virtual environments and improve the learning and teaching of software packages in online and blended teaching methods. This paper introduces a blended strategy to teach engineering software packages to undergraduate students. This article evaluates the effectiveness of the proposed blended learning and teaching strategy in students’ learning by comparing the impact of face-to-face, online and the proposed blended environments on students’ software skills. The paper evaluates the students’ software skills and their software learning through an authentic assignment. According to the results, the proposed blended teaching strategy successfully improves the software learning experience among undergraduate engineering students.

Keywords: teaching software packages, undergraduate students, blended learning and teaching, authentic assessment

Procedia PDF Downloads 112
7911 A Machine Learning Approach for the Leakage Classification in the Hydraulic Final Test

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

Procedia PDF Downloads 206
7910 How To Get Students’ Attentions?: Little Tricks From 15 English Teachers In Labuan

Authors: Suriani Oxley

Abstract:

All teachers aim to conduct a successful and an effective teaching. Teacher will use a variety of teaching techniques and methods to ensure that students achieve the learning objectives but often the teaching and learning processes are interrupted by a number of things such as noisy students, students not paying attention, the students play and so on. Such disturbances must be addressed to ensure that students can concentrate on their learning activities. This qualitative study observed and captured a video of numerous tricks that teachers in Labuan have implemented in helping the students to pay attentions in the classroom. The tricks are such as Name Calling, Non-Verbal Clues, Body Language, Ask Question, Offer Assistance, Echo Clapping, Call and Response & Cues and Clues. All of these tricks are simple but yet interesting language learning strategies that helped students to focus on their learning activities.

Keywords: paying attention, observation, tricks, learning strategies, classroom

Procedia PDF Downloads 562
7909 'English in Tourism' in the Project 'English for Community'

Authors: Nguyen Duc An

Abstract:

To the movement towards learning community, creating friendly, positive and appropriate learning environments which best suit the local features is the most salient and decisive factor of the development and success of that learning society. With the aim at building such an English language learning community for the inhabitants in Moc Chau - the national tourist zone, Tay Bac University has successfully designed and deployed the program ‘English in Tourism’ in the project ‘English for Community’. With the strong attachment to the local reality and close knit to the certain communicative situations, this program which was carefully designed and compiled with interesting and practical activities, has greatly helped the locals confidently introduce and popularize the natural beauty, unique culture and specific characteristics of Moc Chau to the foreign tourists; in addition, reinforce awareness of the native culture of the local people as well as improve the professional development in tourism and service.

Keywords: English for community, learning society, learning community, English in tourism

Procedia PDF Downloads 364
7908 A Study on Pre-Service English Language Teacher's Language Self-Efficacy and Goal Orientation

Authors: Ertekin Kotbas

Abstract:

Teaching English as a Foreign Language (EFL) is on the front burner of many countries in the world, in particular for English Language Teaching departments that train EFL teachers. Under the head of motivational theories in foreign language education, there are numerous researches in literature. However; researches comprising English Language Self-Efficacy and Teachers’ Learning Goal Orientation which has a positive impact on learning teachings skills are scarce. Examination of these English Language self-efficacy beliefs and Learning Goal Orientations of Pre-Service EFL Teachers may broaden the horizons, in consideration the importance of self-efficacy and goal orientation on learning and teaching activities. At this juncture, the present study aims to investigate the relationship between English Language Self-Efficacy and Teachers’ Learning Goal Orientation from Turkish context.

Keywords: English language, learning goal orientation, self-efficacy, pre-service teachers

Procedia PDF Downloads 488
7907 Revisiting High School Students’ Learning Styles in English Subject

Authors: Aroona Hashmi

Abstract:

The prime motive for this endeavor was to explore the tenth grade English class students’ preferred learning styles studying in government secondary school so that English subject teachers could tailor their pedagogical strategies in relation to their students learning needs. The further aim of this study was to identify any significance difference among the students on a gender basis, area basis and different categories of school basis. The population of this study consisting of all the secondary level schools working in the government sector and positioned in the province of Punjab. The multi-stage cluster sampling method was employed while selecting the study sample from the population. The scale used for the identification of students’ learning styles in this study was developed by Grasha-Riechmann. The data collected through learning style scale was analyzed by employing descriptive statistics technique. The results from data analysis depict that learning styles of the majority of students found to be Collaborative and Competitive. Overall, no considerable difference was surfaced between male-female, urban-rural, general-other categories of 10th grade English class students learning styles.

Keywords: learning style, learning style scale, grade, government sector

Procedia PDF Downloads 337
7906 Reducing Lean by Implementing Distance Learning in the Training Programs of Oil and Gas Industries

Authors: Sayed-Mahdi Hashemi-Dehkordi, Ian Baker

Abstract:

This paper investigates the benefits of implementing distance learning in training courses for the oil and gas industries to reduce lean. Due to the remote locations of many oil and gas operations, scheduling and organizing in-person training classes for employees in these sectors is challenging. Furthermore, considering that employees often work in periodic shifts such as day, night, and resting periods, arranging in-class training courses requires significant time and transportation. To explore the effectiveness of distance learning compared to in-class learning, a set of questionnaires was administered to employees of a far on-shore refinery unit in Iran, where both in-class and distance classes were conducted. The survey results revealed that over 72% of the participants agreed that distance learning saved them a significant amount of time by rating it 4 to 5 points out of 5 on a Likert scale. Additionally, nearly 67% of the participants acknowledged that distance learning considerably reduced transportation requirements, while approximately 64% agreed that it helped in resolving scheduling issues. Introducing and encouraging the use of distance learning in the training environments of oil and gas industries can lead to notable time and transportation savings for employees, ultimately reducing lean in a positive manner.

Keywords: distance learning, in-class learning, lean, oil and gas, scheduling, time, training programs, transportation

Procedia PDF Downloads 66