Search results for: quest based learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31649

Search results for: quest based learning

30989 A Study on Pre-Service English Teachers' Language Self Efficacy and Learning Goal Orientation

Authors: Erteki̇n Kotbaş

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, considering the importance of self-efficacy and goal orientation on learning and teaching activities. At this juncture, present study aims to investigate the strong relationship between English language self efficacy and teachers’ learning goal orientation from Turkish context in addition to teacher students’ grade factor.

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

Procedia PDF Downloads 447
30988 E-Learning Approach for Improving Classroom Teaching to Enhance Students' Learning in Secondary Schools in Nigeria

Authors: Chika Ethel Esege

Abstract:

Electronic learning is learning facilitated by technology which has basically altered approaches globally, including the field of education. This trend is compelling educators to focus on approaches that improve classroom practices in order to enhance students’ learning and participation in a global digital society. However, e-learning is not fully utilized across subject disciplines particularly in the field of humanities, in the context of Nigerian secondary education. This study focused on the use of e-learning to enhance the development of digital skills, particularly, collaboration and communication in secondary school students in Nigeria. The study adopted an ‘action research’ involving 210 students and 7 teachers, who utilised the e-learning platform designed by the researcher for the survey. Mixed methods- qualitative and quantitative- were used for data collection including questionnaire, observation, interview, and analysis of statutory documents. The data were presented using frequency counts for questionnaire responses and figures of screenshots for learning tasks. The VOD Burner software was also used to analyse interviews and video recordings. The study showed that the students acquired collaboration and communication skills through e-learning intervention lesson, and demonstrated satisfaction with this approach. However, the study further revealed that the traditional teaching approach could not provide digital education or develop the digital skills of the students. Based on these findings, recommendations were made that the Nigerian Government should incorporate digital content across subject disciplines into secondary school education curricular and provide adequate infrastructure in order to enable educators to adopt relevant approaches necessary for the enhancement of students’ learning especially in a technologically evolving and advancing world.

Keywords: developing collaboration and communication skills, electronic learning, improving classroom teaching, secondary schools in Nigeria

Procedia PDF Downloads 124
30987 Resources-Based Ontology Matching to Access Learning Resources

Authors: A. Elbyed

Abstract:

Nowadays, ontologies are used for achieving a common understanding within a user community and for sharing domain knowledge. However, the de-centralized nature of the web makes indeed inevitable that small communities will use their own ontologies to describe their data and to index their own resources. Certainly, accessing to resources from various ontologies created independently is an important challenge for answering end user queries. Ontology mapping is thus required for combining ontologies. However, mapping complete ontologies at run time is a computationally expensive task. This paper proposes a system in which mappings between concepts may be generated dynamically as the concepts are encountered during user queries. In this way, the interaction itself defines the context in which small and relevant portions of ontologies are mapped. We illustrate application of the proposed system in the context of Technology Enhanced Learning (TEL) where learners need to access to learning resources covering specific concepts.

Keywords: resources query, ontologies, ontology mapping, similarity measures, semantic web, e-learning

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30986 Teacher-Child Interactions within Learning Contexts in Prekindergarten

Authors: Angélique Laurent, Marie-Josée Letarte, Jean-Pascal Lemelin, Marie-France Morin

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This study aims at exploring teacher-child interactions within learning contexts in public prekindergartens of the province of Québec (Canada). It is based on previous research showing that teacher-child interactions in preschools have direct and determining effects on the quality of early childhood education and could directly or indirectly influence child development. However, throughout a typical preschool day, children experience different learning contexts to promote their learning opportunities. Depending on these specific contexts, teacher-child interactions could vary, for example, between free play and shared book reading. Indeed, some studies have found that teacher-directed or child-directed contexts might lead to significant variations in teacher-child interactions. This study drew upon both the bioecological and the Teaching Through Interactions frameworks. It was conducted through a descriptive and correlational design. Fifteen teachers were recruited to participate in the study. At Time 1 in October, they completed a diary to report the learning contexts they proposed in their classroom during a typical week. At Time 2, seven months later (May), they were videotaped three times in the morning (two weeks’ time between each recording) during a typical morning class. The quality of teacher-child interactions was then coded with the Classroom Assessment Scoring System (CLASS) through the contexts identified. This tool measures three main domains of interactions: emotional support, classroom organization, and instruction support, and10 dimensions scored on a scale from 1 (low quality) to 7 (high quality). Based on the teachers’ reports, five learning contexts were identified: 1) shared book reading, 2) free play, 3) morning meeting, 4) teacher-directed activity (such as craft), and 5) snack. Based on preliminary statistical analyses, little variation was observed within the learning contexts for each domain of the CLASS. However, the instructional support domain showed lower scores during specific learning contexts, specifically free play and teacher-directed activity. Practical implications for how preschool teachers could foster specific domains of interactions depending on learning contexts to enhance children’s social and academic development will be discussed.

Keywords: teacher practices, teacher-child interactions, preschool education, learning contexts, child development

Procedia PDF Downloads 91
30985 An Artificially Intelligent Teaching-Agent to Enhance Learning Interactions in Virtual Settings

Authors: Abdulwakeel B. Raji

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This paper introduces a concept of an intelligent virtual learning environment that involves communication between learners and an artificially intelligent teaching agent in an attempt to replicate classroom learning interactions. The benefits of this technology over current e-learning practices is that it creates a virtual classroom where real time adaptive learning interactions are made possible. This is a move away from the static learning practices currently being adopted by e-learning systems. Over the years, artificial intelligence has been applied to various fields, including and not limited to medicine, military applications, psychology, marketing etc. The purpose of e-learning applications is to ensure users are able to learn outside of the classroom, but a major limitation has been the inability to fully replicate classroom interactions between teacher and students. This study used comparative surveys to gain information and understanding of the current learning practices in Nigerian universities and how they compare to these practices compare to the use of a developed e-learning system. The study was conducted by attending several lectures and noting the interactions between lecturers and tutors and as an aftermath, a software has been developed that deploys the use of an artificial intelligent teaching-agent alongside an e-learning system to enhance user learning experience and attempt to create the similar learning interactions to those found in classroom and lecture hall settings. Dialogflow has been used to implement a teaching-agent, which has been developed using JSON, which serves as a virtual teacher. Course content has been created using HTML, CSS, PHP and JAVASCRIPT as a web-based application. This technology can run on handheld devices and Google based home technologies to give learners an access to the teaching agent at any time. This technology also implements the use of definite clause grammars and natural language processing to match user inputs and requests with defined rules to replicate learning interactions. This technology developed covers familiar classroom scenarios such as answering users’ questions, asking ‘do you understand’ at regular intervals and answering subsequent requests, taking advanced user queries to give feedbacks at other periods. This software technology uses deep learning techniques to learn user interactions and patterns to subsequently enhance user learning experience. A system testing has been undergone by undergraduate students in the UK and Nigeria on the course ‘Introduction to Database Development’. Test results and feedback from users shows that this study and developed software is a significant improvement on existing e-learning systems. Further experiments are to be run using the software with different students and more course contents.

Keywords: virtual learning, natural language processing, definite clause grammars, deep learning, artificial intelligence

Procedia PDF Downloads 125
30984 Improving Listening Comprehension for EFL Pre-Intermediate Students through a Blended Learning Strategy

Authors: Heba Mustafa Abdullah

Abstract:

The research aimed at examining the effect of using a suggested blended learning (BL) strategy on developing EFL pre- intermediate students. The study adopted the quasi-experimental design. The sample of the research consisted of a group of 26 EFL pre- intermediate students. Tools of the study included a listening comprehension checklist and a pre-post listening comprehension test. Results were discussed in relation to several factors that affected the language learning process. Finally, the research provided beneficial contributions in relation to manipulating BL strategy with respect to language learning process in general and oral language learning in particular.

Keywords: blended learning, english as a foreign language, listening comprehension, oral language instruction

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30983 Identifying E-Learning Components at North-West University, Mafikeng Campus

Authors: Sylvia Tumelo Nthutang, Nehemiah Mavetera

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Educational institutions are under pressure from their competitors. Regulators and community groups need educational institutions to adopt appropriate business and organizational practices. Globally, educational institutions are now using e-learning as the best teaching and learning approach. E-learning is becoming the center of attention to the learning institutions, educational systems and software inventors. North-West University (NWU) is currently using eFundi, a Learning Management System (LMS). LMS are all information systems and procedures that adds value to students learning and support the learning material in text or any multimedia files. With various e-learning tools, students would be able to access all the materials related to the course in electronic copies. The study was tasked with identifying the e-learning components at the NWU, Mafikeng campus. Quantitative research methodology was considered in data collection and descriptive statistics for data analysis. The Activity Theory (AT) was used as a theory to guide the study. AT outlines the limitations amongst e-learning at the macro-organizational level (plan, guiding principle, campus-wide solutions) and micro-organization (daily functioning practice, collaborative transformation, specific adaptation). On a technological environment, AT gives people an opportunity to change from concentrating on computers as an area of concern but also understand that technology is part of human activities. The findings have identified the university’s current IT tools and knowledge on e-learning elements. It was recommended that university should consider buying computer resources that consumes less power and practice e-learning effectively.

Keywords: e-learning, information and communication technology (ICT), teaching, virtual learning environment

Procedia PDF Downloads 269
30982 Lectures in Higher Education Using Teaching Strategies and Digital Tools to Overcome Challenges Faced in South Africa by Implementing Blended Learning

Authors: Thaiurie Govender, Shannon Verne

Abstract:

The Fourth Industrial Revolution has ushered in an era where technology significantly impacts various aspects of life, including higher education. Blended learning, which combines synchronous and asynchronous learning, has gained popularity as a pedagogical approach. However, its effective implementation is a challenge, particularly in the context of the COVID-19 pandemic and technological obstacles faced in South Africa. This study focused on lecturers' teaching and learning practices to implement blended learning, aiming to understand the teaching and learning strategies used with the integration of digital tools to facilitate the blended learning approach within a private higher educational institution in South Africa. Using heutagogy and constructivism theoretical frameworks, the study aimed to uncover insights into the lecturer’s teaching and learning practices to overcome challenges in designing and facilitating blended learning modules. Through a qualitative analysis, the themes of student engagement, teaching and learning strategies, digital tools, and feedback emerged, highlighting the complexities and opportunities in a blended learning classroom. The findings emphasize the importance of tailoring methods to students' needs and subject matter, aligning with constructivist principles. Recommendations include promoting professional development opportunities, addressing infrastructure issues, and fostering a supportive learning environment.

Keywords: blended learning, digital tools, higher education, teaching strategies

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30981 Preservice EFL Teachers in a Blended Professional Development Program: Learning to Teach Speech Acts

Authors: Mei-Hui Liu

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This study examines the effectiveness of a blended professional development program on preservice EFL (English as a foreign language) teachers’ learning to teach speech acts with the advent of Information and Communication Technology, researchers and scholars underscore the significance of integrating online and face-to-face learning opportunities in the teacher education field. Yet, a paucity of evidence has been documented to investigate the extent to which such a blended professional learning model may impact real classroom practice and student learning outcome. This yearlong project involves various stakeholders, including 25 preservice teachers, 5 English professionals, and 45 secondary school students. Multiple data sources collected are surveys, interviews, reflection journals, online discussion messages, artifacts, and discourse completion tests. Relying on the theoretical lenses of Community of Inquiry, data analysis depicts the nature and process of preservice teachers’ professional development in this blended learning community, which triggers and fosters both face-to-face and synchronous/asynchronous online interactions among preservice teachers and English professionals (i.e., university faculty and in-service teachers). Also included is the student learning outcome after preservice teachers put what they learn from the support community into instructional practice. Pedagogical implications and research suggestions are further provided based on the research findings and limitations.

Keywords: blended professional development, preservice EFL teachers, speech act instruction, student learning outcome

Procedia PDF Downloads 215
30980 Social Media Data Analysis for Personality Modelling and Learning Styles Prediction Using Educational Data Mining

Authors: Srushti Patil, Preethi Baligar, Gopalkrishna Joshi, Gururaj N. Bhadri

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In designing learning environments, the instructional strategies can be tailored to suit the learning style of an individual to ensure effective learning. In this study, the information shared on social media like Facebook is being used to predict learning style of a learner. Previous research studies have shown that Facebook data can be used to predict user personality. Users with a particular personality exhibit an inherent pattern in their digital footprint on Facebook. The proposed work aims to correlate the user's’ personality, predicted from Facebook data to the learning styles, predicted through questionnaires. For Millennial learners, Facebook has become a primary means for information sharing and interaction with peers. Thus, it can serve as a rich bed for research and direct the design of learning environments. The authors have conducted this study in an undergraduate freshman engineering course. Data from 320 freshmen Facebook users was collected. The same users also participated in the learning style and personality prediction survey. The Kolb’s Learning style questionnaires and Big 5 personality Inventory were adopted for the survey. The users have agreed to participate in this research and have signed individual consent forms. A specific page was created on Facebook to collect user data like personal details, status updates, comments, demographic characteristics and egocentric network parameters. This data was captured by an application created using Python program. The data captured from Facebook was subjected to text analysis process using the Linguistic Inquiry and Word Count dictionary. An analysis of the data collected from the questionnaires performed reveals individual student personality and learning style. The results obtained from analysis of Facebook, learning style and personality data were then fed into an automatic classifier that was trained by using the data mining techniques like Rule-based classifiers and Decision trees. This helps to predict the user personality and learning styles by analysing the common patterns. Rule-based classifiers applied for text analysis helps to categorize Facebook data into positive, negative and neutral. There were totally two models trained, one to predict the personality from Facebook data; another one to predict the learning styles from the personalities. The results show that the classifier model has high accuracy which makes the proposed method to be a reliable one for predicting the user personality and learning styles.

Keywords: educational data mining, Facebook, learning styles, personality traits

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30979 The Asymmetric Proximal Support Vector Machine Based on Multitask Learning for Classification

Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

Abstract:

Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

Procedia PDF Downloads 100
30978 A Deep Learning Based Integrated Model For Spatial Flood Prediction

Authors: Vinayaka Gude Divya Sampath

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

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

Procedia PDF Downloads 131
30977 English and Information and Communication Technology: Zones of Exclusion in Education in Low-Income Countries

Authors: Ram A. Giri, Amna Bedri, Abdou Niane

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Exclusion in education on the basis of language in multilingual contexts operates at multiple levels. Learners of diverse ethnolinguistic backgrounds are often expected to learn through English and are pushed further down the learning ladder if they also have to access education through Information and Communication Technology (ICT). The paper explores marginalized children’s lived experiences in accessing technology and English in four low-income countries in Africa and Asia. Based on the findings of the first phase of a multinational qualitative research study, we report on the factors or barriers that affect children’s access, opportunities and motivation for learning through technology and English. ICT and English - the language of ICT and education - can enhance learning and can even be essential. However, these two important keys to education can also function as barriers to accessing quality education, and therefore as zones of exclusion. This paper looks into how marginalized children (aged 13-15) engage in learning through ICT and English and to what extent the restrictive access and opportunities contribute to the widening of the already existing gap in education. By applying the conceptual frameworks of “access and accessibility of learning” and “zones of exclusion,” the paper elucidates how the barriers prevent children’s effective engagement with learning and addresses such questions as to how marginalized children access technology and English for learning; whether the children value English, and what their motivation and opportunity to learn it are. In addition, the paper will point out policy and pedagogic implications.

Keywords: exclusion, inclusion, inclusive education, marginalization

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30976 Instructional Material Development in ODL: Achievements, Prospects, and Challenges

Authors: Felix Gbenoba, Opeyemi Dahunsi

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Customised, self-instructional materials are at the heart of instructional delivery in Open and Distance Learning (ODL). The success of any ODL institution depends on the availability of learning materials in quality and quantity. An ODL study material is expected to imitate what the teacher does in the face-to-face learning environment. This paper evaluates these expectation based on existing data and evidence. It concludes that the reality has not matched the expectation so far in terms of pedagogic aspect of instructional delivery especially in West Africa. This does not mean that instructional materials development has not produced any significant positive results in improving the overall learning (and teaching) experience in these institutions; it implies what will help further to identify the new challenges. Obstacles and problems of instructional materials development that could have affected the open educational resource initiatives are well established. The first section of this paper recalls some of the proposed values of instructional materials. The second section compares achievements so far and suggests that instructional materials development should be consider first at an early stage to realise the aspirations of instructional delivery. The third section highlights the challenges of instructional materials development in the future.

Keywords: face-to-face learning, instructional delivery, open and distance education, self-instructional materials

Procedia PDF Downloads 358
30975 Integration of Social Media in Teaching and Learning Activities: A Case Study

Authors: A. Nagaletchimee Annamalai

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The study investigated on how a small group of pre-service teachers and lecturers used social media to interact and collaborate to complete their tasks. The study is a qualitative case study that explored the lecturers’ reflections and pre-service teachers’ interviews. The lecturers were given the option to choose Facebook or any other social media as their teaching and learning platforms. However, certain guidelines based on were given to lecturers to conduct their teaching and learning activities. The findings revealed that although Facebook was a popular social networking site, it was not a preferred educational platform. Lecturers preferred to use WhatsApp, Canvas, and email. The focus group interview found positive and negative experiences of the pre-service teachers. The study suggested several pedagogical implications and importantly highlighted the need for changes in curriculum to ensure lecturers leverage the potential of technology in education.

Keywords: social media, interactions, collaboration, online learning environment

Procedia PDF Downloads 175
30974 Intelligent Process and Model Applied for E-Learning Systems

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 178
30973 Business Skills Laboratory in Action: Combining a Practice Enterprise Model and an ERP-Simulation to a Comprehensive Business Learning Environment

Authors: Karoliina Nisula, Samuli Pekkola

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Business education has been criticized for being too theoretical and distant from business life. Different types of experiential learning environments ranging from manual role-play to computer simulations and enterprise resource planning (ERP) systems have been used to introduce the realistic and practical experience into business learning. Each of these learning environments approaches business learning from a different perspective. The implementations tend to be individual exercises supplementing the traditional courses. We suggest combining them into a business skills laboratory resembling an actual workplace. In this paper, we present a concrete implementation of an ERP-supported business learning environment that is used throughout the first year undergraduate business curriculum. We validate the implementation by evaluating the learning outcomes through the different domains of Bloom’s taxonomy. We use the role-play oriented practice enterprise model as a comparison group. Our findings indicate that using the ERP simulation improves the poor and average students’ lower-level cognitive learning. On the affective domain, the ERP-simulation appears to enhance motivation to learn as well as perceived acquisition of practical hands-on skills.

Keywords: business simulations, experiential learning, ERP systems, learning environments

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30972 The Experience of Community-based Tourism in Yunguilla, Ecuador and Its Social-Cultural Impact

Authors: York Neudel

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The phenomenon of tourism has been considered as tool to overcome cultural frontiers, to comprehend the other and to cope with mutual mistrust and suspicion. Well, that has been a myth, at least when it comes to mass-tourism. Other approaches, like community-based tourism, still are based on the idea of embracing the other in order to help or to understand the cultural difference. In 1997, two American NGOs incentivized a tourism-project in a community in the highlands of Ecuador, in order to protect the cloud forest from destructive exploitation of its own inhabitants. Nineteen years after that, I analyze in this investigation the interactions between the Ecuadorian hosts in the mestizo-community of Yunguilla and the foreign tourist in the quest for “authentic life” in the Ecuadorian cloud forest. As a sort of “contemporary pilgrim” the traveller tries to find authenticity in other times and places far away from their everyday life in Europe or North America. Therefore, tourists are guided by stereotypes and expectations that are produced by the touristic industry. The host, on the other hand, has to negotiate this pre-established imaginary. That generates a kind of theatre-play with front- and backstage in organic gardens, little fabrics and even private housing, since this alternative project offers to share the private space of the host with the tourist in the setting the community-based tourism. In order to protect their privacy, the community creates new hybrid spaces that oscillate between front- and backstages that culminates in a game of hide and seek – a phenomenon that promises interesting frictions for an anthropological case-study.

Keywords: Tourism, Authenticity, Community-based tourism, Ecuador, Yunguilla

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30971 Teaching Children With Differential Learning Needs By Understanding Their Talents And Interests

Authors: Eunice Tan

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The purpose of this presentation is to look at an alternative to the approach and methodologies of working with special needs. The strength-based approach to education embodies a paradigm shift. It is a strategy to move away from a deficit-based methodology which inadvertently may lead to an extensive list of things that the child cannot do or is unable to do. Today, many parents of individuals with special needs are focused on the child’s deficits rather than on his or her strengths. Even when parents Recognise and identify their child’s strengths to be valuable and wish to develop their abilities, they face the challenge that there are insufficient programs committed to supporting the development and improvement of such abilities. What is a strength-based approach in education? A strength-based approach in education focuses on students' positive qualities and contributions to class instead of the skills and abilities they may not have. Many schools are focused on the child’s special educational needs rather than the whole child. Parents interviewed have said that they have to engage external tutors to help hone in on their child’s interests and strengths.

Keywords: differential learning needs, special needs, instructional style, talents

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30970 Bridging the Data Gap for Sexism Detection in Twitter: A Semi-Supervised Approach

Authors: Adeep Hande, Shubham Agarwal

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This paper presents a study on identifying sexism in online texts using various state-of-the-art deep learning models based on BERT. We experimented with different feature sets and model architectures and evaluated their performance using precision, recall, F1 score, and accuracy metrics. We also explored the use of pseudolabeling technique to improve model performance. Our experiments show that the best-performing models were based on BERT, and their multilingual model achieved an F1 score of 0.83. Furthermore, the use of pseudolabeling significantly improved the performance of the BERT-based models, with the best results achieved using the pseudolabeling technique. Our findings suggest that BERT-based models with pseudolabeling hold great promise for identifying sexism in online texts with high accuracy.

Keywords: large language models, semi-supervised learning, sexism detection, data sparsity

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30969 Time Series Forecasting (TSF) Using Various Deep Learning Models

Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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30968 Social Media as an Interactive Learning Tool Applied to Faculty of Tourism and Hotels, Fayoum University

Authors: Islam Elsayed Hussein

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The aim of this paper is to discover the impact of students’ attitude towards social media and the skills required to adopt social media as a university e-learning (2.0) platform. In addition, it measures the effect of social media adoption on interactive learning effectiveness. The population of this study was students at Faculty of tourism and Hotels, Fayoum University. A questionnaire was used as a research instrument to collect data from respondents, which had been selected randomly. Data had been analyzed using quantitative data analysis method. Findings showed that the students have a positive attitude towards adopting social networking in the learning process and they have also good skills for effective use of social networking tools. In addition, adopting social media is effectively affecting the interactive learning environment.

Keywords: attitude, skills, e-learning 2.0, interactive learning, Egypt

Procedia PDF Downloads 502
30967 Code Embedding for Software Vulnerability Discovery Based on Semantic Information

Authors: Joseph Gear, Yue Xu, Ernest Foo, Praveen Gauravaran, Zahra Jadidi, Leonie Simpson

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Deep learning methods have been seeing an increasing application to the long-standing security research goal of automatic vulnerability detection for source code. Attention, however, must still be paid to the task of producing vector representations for source code (code embeddings) as input for these deep learning models. Graphical representations of code, most predominantly Abstract Syntax Trees and Code Property Graphs, have received some use in this task of late; however, for very large graphs representing very large code snip- pets, learning becomes prohibitively computationally expensive. This expense may be reduced by intelligently pruning this input to only vulnerability-relevant information; however, little research in this area has been performed. Additionally, most existing work comprehends code based solely on the structure of the graph at the expense of the information contained by the node in the graph. This paper proposes Semantic-enhanced Code Embedding for Vulnerability Discovery (SCEVD), a deep learning model which uses semantic-based feature selection for its vulnerability classification model. It uses information from the nodes as well as the structure of the code graph in order to select features which are most indicative of the presence or absence of vulnerabilities. This model is implemented and experimentally tested using the SARD Juliet vulnerability test suite to determine its efficacy. It is able to improve on existing code graph feature selection methods, as demonstrated by its improved ability to discover vulnerabilities.

Keywords: code representation, deep learning, source code semantics, vulnerability discovery

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30966 Flood-prone Urban Area Mapping Using Machine Learning, a Case Sudy of M'sila City (Algeria)

Authors: Medjadj Tarek, Ghribi Hayet

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This study aims to develop a flood sensitivity assessment tool using machine learning (ML) techniques and geographic information system (GIS). The importance of this study is integrating the geographic information systems (GIS) and machine learning (ML) techniques for mapping flood risks, which help decision-makers to identify the most vulnerable areas and take the necessary precautions to face this type of natural disaster. To reach this goal, we will study the case of the city of M'sila, which is among the areas most vulnerable to floods. This study drew a map of flood-prone areas based on the methodology where we have made a comparison between 3 machine learning algorithms: the xGboost model, the Random Forest algorithm and the K Nearest Neighbour algorithm. Each of them gave an accuracy respectively of 97.92 - 95 - 93.75. In the process of mapping flood-prone areas, the first model was relied upon, which gave the greatest accuracy (xGboost).

Keywords: Geographic information systems (GIS), machine learning (ML), emergency mapping, flood disaster management

Procedia PDF Downloads 80
30965 Machine Learning Approach for Mutation Testing

Authors: Michael Stewart

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Mutation testing is a type of software testing proposed in the 1970s where program statements are deliberately changed to introduce simple errors so that test cases can be validated to determine if they can detect the errors. Test cases are executed against the mutant code to determine if one fails, detects the error and ensures the program is correct. One major issue with this type of testing was it became intensive computationally to generate and test all possible mutations for complex programs. This paper used reinforcement learning and parallel processing within the context of mutation testing for the selection of mutation operators and test cases that reduced the computational cost of testing and improved test suite effectiveness. Experiments were conducted using sample programs to determine how well the reinforcement learning-based algorithm performed with one live mutation, multiple live mutations and no live mutations. The experiments, measured by mutation score, were used to update the algorithm and improved accuracy for predictions. The performance was then evaluated on multiple processor computers. With reinforcement learning, the mutation operators utilized were reduced by 50 – 100%.

Keywords: automated-testing, machine learning, mutation testing, parallel processing, reinforcement learning, software engineering, software testing

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30964 An Exploration of Promoting EFL Students’ Language Learning Autonomy Using Multimodal Teaching - A Case Study of an Art University in Western China

Authors: Dian Guan

Abstract:

With the wide application of multimedia and the Internet, the development of teaching theories, and the implementation of teaching reforms, many different university English classroom teaching modes have emerged. The university English teaching mode is changing from the traditional teaching mode based on conversation and text to the multimodal English teaching mode containing discussion, pictures, audio, film, etc. Applying university English teaching models is conducive to cultivating lifelong learning skills. In addition, lifelong learning skills can also be called learners' autonomous learning skills. Learners' independent learning ability has a significant impact on English learning. However, many university students, especially art and design students, don't know how to learn individually. When they become university students, their English foundation is a relative deficiency because they always remember the language in a traditional way, which, to a certain extent, neglects the cultivation of English learners' independent ability. As a result, the autonomous learning ability of most university students is not satisfactory. The participants in this study were 60 students and one teacher in their first year at a university in western China. Two observations and interviews were conducted inside and outside the classroom to understand the impact of a multimodal teaching model of university English on students' autonomous learning ability. The results were analyzed, and it was found that the multimodal teaching model of university English significantly affected learners' autonomy. Incorporating classroom presentations and poster exhibitions into multimodal teaching can increase learners' interest in learning and enhance their learning ability outside the classroom. However, further exploration is needed to develop multimodal teaching materials and evaluate multimodal teaching outcomes. Despite the limitations of this study, the study adopts a scientific research method to analyze the impact of the multimodal teaching mode of university English on students' independent learning ability. It puts forward a different outlook for further research on this topic.

Keywords: art university, EFL education, learner autonomy, multimodal pedagogy

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30963 Challenges to Collaborative Learning in Architectural Education in the Middle East

Authors: Lizmol Mathew, Divya Thomas, Shiney Rajan

Abstract:

Educational paradigm all over the globe is undergoing significant reform today. Because of this, so-called flipped classroom model is becoming increasingly popular in higher education. Flipped classroom has proved to be more effective than traditional lecture based model as flipped classroom model promotes active learning by encouraging students to work on in collaborative tasks and peer-led learning during the class-time. However, success of flipped classrooms relies on students’ ability and their attitudes towards collaboration and group work. This paper examines: 1) Students’ attitudes towards collaborative learning; 2) Main challenges to successful collaboration from students’ experience and 3) Students’ perception of criteria for successful team work. 4) Recommendations for enhancing collaborative learning. This study’s methodology involves quantitative analysis of surveys collected from students enrolled in undergraduate Architecture program at Qatar University. Analysis indicates that in general students enrolled in the program do not have positive perceptions or experiences associated with group work. Positive and negative factors that influence collaborative learning in higher education have been identified. Recommendations for improving collaborative work experience have been proposed.

Keywords: architecture, collaborative learning, female, group work, higher education, Middle East, Qatar, student experience

Procedia PDF Downloads 316
30962 Foot Recognition Using Deep Learning for Knee Rehabilitation

Authors: Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia

Abstract:

The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.

Keywords: foot recognition, deep learning, knee rehabilitation, convolutional neural network

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30961 Exploring Instructional Designs on the Socio-Scientific Issues-Based Learning Method in Respect to STEM Education for Measuring Reasonable Ethics on Electromagnetic Wave through Science Attitudes toward Physics

Authors: Adisorn Banhan, Toansakul Santiboon, Prasong Saihong

Abstract:

Using the Socio-Scientific Issues-Based Learning Method is to compare of the blended instruction of STEM education with a sample consisted of 84 students in 2 classes at the 11th grade level in Sarakham Pittayakhom School. The 2-instructional models were managed of five instructional lesson plans in the context of electronic wave issue. These research procedures were designed of each instructional method through two groups, the 40-experimental student group was designed for the instructional STEM education (STEMe) and 40-controlling student group was administered with the Socio-Scientific Issues-Based Learning (SSIBL) methods. Associations between students’ learning achievements of each instructional method and their science attitudes of their predictions to their exploring activities toward physics with the STEMe and SSIBL methods were compared. The Measuring Reasonable Ethics Test (MRET) was assessed students’ reasonable ethics with the STEMe and SSIBL instructional design methods on two each group. Using the pretest and posttest technique to monitor and evaluate students’ performances of their reasonable ethics on electromagnetic wave issue in the STEMe and SSIBL instructional classes were examined. Students were observed and gained experience with the phenomena being studied with the Socio-Scientific Issues-Based Learning method Model. To support with the STEM that it was not just teaching about Science, Technology, Engineering, and Mathematics; it is a culture that needs to be cultivated to help create a problem solving, creative, critical thinking workforce for tomorrow in physics. Students’ attitudes were assessed with the Test Of Physics-Related Attitude (TOPRA) modified from the original Test Of Science-Related Attitude (TOSRA). Comparisons between students’ learning achievements of their different instructional methods on the STEMe and SSIBL were analyzed. Associations between students’ performances the STEMe and SSIBL instructional design methods of their reasonable ethics and their science attitudes toward physics were associated. These findings have found that the efficiency of the SSIBL and the STEMe innovations were based on criteria of the IOC value higher than evidence as 80/80 standard level. Statistically significant of students’ learning achievements to their later outcomes on the controlling and experimental groups with the SSIBL and STEMe were differentiated between students’ learning achievements at the .05 level. To compare between students’ reasonable ethics with the SSIBL and STEMe of students’ responses to their instructional activities in the STEMe is higher than the SSIBL instructional methods. Associations between students’ later learning achievements with the SSIBL and STEMe, the predictive efficiency values of the R2 indicate that 67% and 75% for the SSIBL, and indicate that 74% and 81% for the STEMe of the variances were attributable to their developing reasonable ethics and science attitudes toward physics, consequently.

Keywords: socio-scientific issues-based learning method, STEM education, science attitudes, measurement, reasonable ethics, physics classes

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30960 Recommender Systems for Technology Enhanced Learning (TEL)

Authors: Hailah Alballaa, Azeddine Chikh

Abstract:

Several challenges impede the adoption of Recommender Systems for Technology Enhanced Learning (TEL): to collect and identify possible datasets; to select between different recommender approaches; to evaluate their performances. The aim is of this paper is twofold: First, it aims to introduce a survey on the most significant work in this area. Second, it aims at identifying possible research directions.

Keywords: datasets, content-based filtering, recommender systems, TEL

Procedia PDF Downloads 232