Search results for: learning satisfaction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8656

Search results for: learning satisfaction

6616 Learning to Teach on the Cloud: Preservice EFL Teachers’ Online Project-Based Practicum Experience

Authors: Mei-Hui Liu

Abstract:

This paper reports 20 preservice EFL teachers’ learning-to-teach experience when they were engaged in an online project-based practicum implemented on a Cloud Platform. This 10-month study filled in the literature gap by documenting the impact of online project-based instruction on preservice EFL teachers’ professional development. Data analysis showed that the online practicum was regarded as a flexible mechanism offering chances of teaching practices without geographical barriers. Additionally, this project-based practice helped the participants integrate the theories they had learned and further foster them how to create a self-directed online learning environment. Furthermore, these preservice teachers with experiences of technology-enabled practicum showed their motivation to apply technology and online platforms into future instructional practices. Yet, this study uncovered several concerns encountered by these participants during this online field experience. The findings of this study rendered meaning and lessons for teacher educators intending to integrate online practicum into preservice training courses.

Keywords: online teaching practicum, project-based learning, teacher preparation, English language education

Procedia PDF Downloads 371
6615 Response of First Bachelor of Medicine, Bachelor of Surgery (MBBS) Students to Integrated Learning Program

Authors: Raveendranath Veeramani, Parkash Chand, H. Y. Suma, A. Umamageswari

Abstract:

Background and Aims: The aim of this study was to evaluate students’ perception of Integrated Learning Program[ILP]. Settings and Design: A questionnaire was used to survey and evaluate the perceptions of 1styear MBBS students at the Department of Anatomy at our medical college in India. Materials and Methods: The first MBBS Students of Anatomy were involved in the ILP on the Liver and extra hepatic biliary apparatus integrating the Departments of Anatomy, Biochemistry and Hepato-biliary Surgery. The evaluation of the ILP was done by two sets of short questionnaire that had ten items using the Likert five-point grading scale. The data involved both the students’ responses and their grading. Results: A majority of students felt that the ILP was better in as compared to the traditional lecture method of teaching.The integrated teaching method was better at fulfilling learning objectives (128 students, 83%), enabled better understanding (students, 94%), were more interesting (140 students, 90%), ensured that they could score better in exams (115 students, 77%) and involved greater interaction (100 students, 66%), as compared to traditional teaching methods. Most of the students (142 students, 95%) opined that more such sessions should be organized in the future. Conclusions: Responses from students show that the integrated learning session should be incorporated even at first phase of MBBS for selected topics so as to create interest in the medical sciences at the entry level and to make them understand the importance of basic science.

Keywords: integrated learning, students response, vertical integration, horizontal integration

Procedia PDF Downloads 201
6614 Using Short Learning Programmes to Develop Students’ Digital Literacies in Art and Design Education

Authors: B.J. Khoza, B. Kembo

Abstract:

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

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

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6613 Collaborative Learning Strategies in Engineering Tuition Focused on Students’ Engagement

Authors: Maria Gonzalez Alriols, Itziar Egues, Maria A. Andres, Mirari Antxustegi

Abstract:

Peer to peer learning is an educational tool very useful to enhance teamwork and reinforce cooperation between mates. It is particularly successful to work with students of different level of previous knowledge, as it often happens among pupils of subjects in the first course of science and engineering studies. Depending on the performed pre-university academic itinerary, the acquired knowledge in disciplines as mathematics, physics, or chemistry may be quite different. This fact is an added difficulty to the tuition of first-course basic science subjects of engineering degrees, with inexperienced students that do not know each other. In this context, peer to peer learning applied in small groups facilitates the communication between mates and makes it easier for the students with low level to be helped by the ones with better prior knowledge. In this work, several collaborative learning strategies were designed to be applied in the tuition of the subject 'chemistry', which is imparted in the first course of an engineering degree. Students were organized in groups combining mates with different level of prior knowledge. The teaching role was offered to the more experienced students who were responsible for designing learning pills to help the other mates in their group. This workload was rewarded with an extra mark, and more extra points were offered to all the group mates if every student in the group reached a determined level at the end of the semester. It was very important to start these activities from the beginning of the semester in order to avoid absenteeism. The obtained results were positive as a higher percentage of mates signed up and passed the final exam, the obtained final marks were higher, and a much better atmosphere was observed in the class.

Keywords: peer to peer tuition, collaborative learning, engineering instruction, chemistry

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6612 The Use of Creativity to Nudge Students Into Heutagogy: An Implementation in Graduate Business Education

Authors: Ricardo Bragança, Tom Vinaimont

Abstract:

This paper discusses the introduction of processes of self-determined learning (heutagogy) into a graduate course on financial modeling, using elements of entangled pedagogy and Biggs’ constructive alignment. To encourage learners to take control of their own learning journey and develop critical thinking and problem-solving skills, each session in the course receives tailor-made media-enhanced pedagogical assets. The design of those assets specifically supports entangled pedagogy, which opposes technological or pedagogical determinism in support of the collaborative integration of pedagogy and technology. Media assets for each of the ten sessions in this course consist of three components. The first component in this three-pronged approach is a game-cut-like cinematographic representation that introduces the context of the session. The second component represents a character from an open-source-styled community that encourages self-determined learning. The third component consists of a character, which refers to the in-person instructor and also aligns learning outcomes and assessment tasks, using Biggs’ constructive alignment, to the cinematographic and open-source-styled component. In essence, the course's metamorphosis helps students apply the concepts they've studied to actual financial modeling issues. The audio-visual media assets create a storyline throughout the course based on gamified and real-world applications, thus encouraging student engagement and interaction. The structured entanglement of pedagogy and technology also guides the instructor in the design of the in-class interactions and directs the focus on outcomes and assessments. The transformation process of this graduate course in financial modeling led to an institutional teaching award in 2021. The transformation of this course may be used as a model for other courses and programs in many disciplines to help with intended learning outcomes integration, constructive alignment, and Assurance of Learning.

Keywords: innovative education, active learning, entangled pedagogy, heutagogy, constructive alignment, project based learning, financial modeling, graduate business education

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6611 OER on Academic English, Educational Research and ICT Literacy, Promoting International Graduate Programs in Thailand

Authors: Maturos Chongchaikit, Sitthikorn Sumalee, Nopphawan Chimroylarp, Nongluck Manowaluilou, Thapanee Thammetha

Abstract:

The 2015 Kasetsart University Research Plan, which was funded by the National Research Institutes: TRF – NRCT, comprises four sub-research projects on the development of three OER websites and on their usage study by students in international programs. The goals were to develop the open educational resources (OER) in the form of websites that will promote three key skills of quality learning and achievement: Academic English, Educational Research, and ICT Literacy, to graduate students in international programs of Thailand. The statistics from the Office of Higher Education showed that the number of foreign students who come to study in international higher education of Thailand has increased respectively by 25 percent per year, proving that the international education system and institutes of Thailand have been already recognized regionally and globally as meeting the standards. The output of the plan: the OER websites and their materials, and the outcome: students’ learning improvement due to lecturers’ readiness for open educational media, will ultimately lead the country to higher business capabilities for international education services in ASEAN Community in the future. The OER innovation is aimed at sharing quality knowledge to the world, with the adoption of Creative Commons Licenses that makes sharing be able to do freely (5Rs openness), without charge and leading to self and life-long learning. The research has brought the problems on the low usage of existing OER in the English language to develop the OER on three specific skills and try them out with the sample of 100 students randomly selected from the international graduate programs of top 10 Thai universities, according to QS Asia University Rankings 2014. The R&D process was used for product evaluation in 2 stages: the development stage and the usage study stage. The research tools were the questionnaires for content and OER experts, the questionnaires for the sample group and the open-ended interviews for the focus group discussions. The data were analyzed using frequency, percentage, mean and SD. The findings revealed that the developed websites were fully qualified as OERs by the experts. The students’ opinions and satisfaction were at the highest levels for both the content and the technology used for presentation. The usage manual and self-assessment guide were finalized during the focus group discussions. The direct participation according to the concept of 5Rs Openness Activities through the provided tools of OER models like MERLOT and OER COMMONS, as well as the development of usage manual and self-assessment guide, were revealed as a key approach to further extend the output widely and sustainably to the network of users in various higher education institutions.

Keywords: open educational resources, international education services business, academic English, educational research, ICT literacy, international graduate program, OER

Procedia PDF Downloads 223
6610 Correlation between Speech Emotion Recognition Deep Learning Models and Noises

Authors: Leah Lee

Abstract:

This paper examines the correlation between deep learning models and emotions with noises to see whether or not noises mask emotions. The deep learning models used are plain convolutional neural networks (CNN), auto-encoder, long short-term memory (LSTM), and Visual Geometry Group-16 (VGG-16). Emotion datasets used are Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Crowd-sourced Emotional Multimodal Actors Dataset (CREMA-D), Toronto Emotional Speech Set (TESS), and Surrey Audio-Visual Expressed Emotion (SAVEE). To make it four times bigger, audio set files, stretch, and pitch augmentations are utilized. From the augmented datasets, five different features are extracted for inputs of the models. There are eight different emotions to be classified. Noise variations are white noise, dog barking, and cough sounds. The variation in the signal-to-noise ratio (SNR) is 0, 20, and 40. In summation, per a deep learning model, nine different sets with noise and SNR variations and just augmented audio files without any noises will be used in the experiment. To compare the results of the deep learning models, the accuracy and receiver operating characteristic (ROC) are checked.

Keywords: auto-encoder, convolutional neural networks, long short-term memory, speech emotion recognition, visual geometry group-16

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6609 Practice of Applying MIDI Technology to Train Creative Teaching Skills

Authors: Yang Zhuo

Abstract:

This study explores the integration of MIDI technology as one of the important digital technologies in music teaching, from the perspective of teaching practice, into the process of cultivating students' teaching skills. At the same time, the framework elements of the learning environment for music education students are divided into four aspects: digital technology supported learning space, new knowledge learning, teaching methods, and teaching evaluation. In teaching activities, more attention should be paid to students' subjectivity and interaction between them so as to enhance their emotional experience in teaching practice simulation. In the process of independent exploration and cooperative interaction, problems should be discovered and solved, and basic knowledge of music and teaching methods should be exercised in practice.

Keywords: music education, educational technology, MIDI, teacher training

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6608 Prediction of MicroRNA-Target Gene by Machine Learning Algorithms in Lung Cancer Study

Authors: Nilubon Kurubanjerdjit, Nattakarn Iam-On, Ka-Lok Ng

Abstract:

MicroRNAs are small non-coding RNA found in many different species. They play crucial roles in cancer such as biological processes of apoptosis and proliferation. The identification of microRNA-target genes can be an essential first step towards to reveal the role of microRNA in various cancer types. In this paper, we predict miRNA-target genes for lung cancer by integrating prediction scores from miRanda and PITA algorithms used as a feature vector of miRNA-target interaction. Then, machine-learning algorithms were implemented for making a final prediction. The approach developed in this study should be of value for future studies into understanding the role of miRNAs in molecular mechanisms enabling lung cancer formation.

Keywords: microRNA, miRNAs, lung cancer, machine learning, Naïve Bayes, SVM

Procedia PDF Downloads 400
6607 Radar Fault Diagnosis Strategy Based on Deep Learning

Authors: Bin Feng, Zhulin Zong

Abstract:

Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

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6606 Errors and Misconceptions for Students with Mathematical Learning Disabilities: Quest for Suitable Teaching Strategy

Authors: A. K. Tsafe

Abstract:

The study investigates the efficacy of Special Mathematics Teaching Strategy (SMTS) as against Conventional Mathematics Teaching Strategy (CMTS) in teaching students identified with Mathematics Learning Disabilities (MLDs) – dyslexia, Down syndrome, dyscalculia, etc., in some junior secondary schools around Sokoto metropolis. Errors and misconceptions in learning Mathematics displayed by these categories of students were observed. Theory of variation was used to provide a prism for viewing the MLDs from theoretical perspective. Experimental research design was used, involving pretest-posttest non-randomized approach. Pretest was administered to the intact class taught using CMTS before the class was split into experimental and control groups. Experimental group of the students – those identified with MLDs was taught with SMTS and later mean performance of students taught using the two strategies was sought to find if there was any significant difference between the performances of the students. A null hypothesis was tested at α = 0.05 level of significance. T-test was used to establish the difference between the mean performances of the two tests. The null hypothesis was rejected. Hence, the performance of students, identified with MLDs taught using SMTS was found to be better than their earlier performance taught using CMTS. The study, therefore, recommends amongst other things that teachers should be encouraged to use SMTS in teaching mathematics especially when students are found to be suffering from MLDs and exhibiting errors and misconceptions in the process of learning mathematics.

Keywords: disabilities, errors, learning, misconceptions

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6605 Automated Adaptions of Semantic User- and Service Profile Representations by Learning the User Context

Authors: Nicole Merkle, Stefan Zander

Abstract:

Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

Procedia PDF Downloads 281
6604 A Development of Creative Instruction Model through Digital Media

Authors: Kathaleeya Chanda, Panupong Chanplin, Suppara Charoenpoom

Abstract:

This purposes of the development of creative instruction model through digital media are to: 1) enable learners to learn from instruction media application; 2) help learners implementing instruction media correctly and appropriately; and 3) facilitate learners to apply technology for searching information and practicing skills to implement technology creatively. The sample group consists of 130 cases of secondary students studying in Bo Kluea School, Bo Kluea Nuea Sub-district, Bo Kluea District, Nan Province. The probability sampling was selected through the simple random sampling and the statistics used in this research are percentage, mean, standard deviation and one group pretest – posttest design. The findings are summarized as follows: The congruence index of instruction media for occupation and technology subjects is appropriate. By comparing between learning achievements before implementing the instruction media and learning achievements after implementing the instruction media, it is found that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. For the learning achievements from instruction media implementation, pretest mean is 16.24 while posttest mean is 26.28. Besides, pretest and posttest results are compared and differences of mean are tested, the test results show that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. This can be interpreted that the learners achieve better learning progress.

Keywords: teaching learning model, digital media, creative instruction model, Bo Kluea school

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6603 The Influence of Teacher’s Non-Verbal Communication on Ondo State Secondary School Students’ Learning Outcomes in English Language

Authors: Bola M. Tunde-Awe

Abstract:

The study investigated the influence of teacher’s non-verbal communication on secondary school students’ learning outcomes in English language. The study was a survey research. Participants were three hundred Senior Secondary School II students randomly selected from ten schools in Akoko South West Local Government Area of Ondo State, Nigeria. The instrument used for data collection was a questionnaire containing twenty items on a four-point Likert scale which measured teacher’s use of three types of non-verbal communication modes: body movement, eye contact and spatial distance. The data collected was analysed using simple percentage. Findings revealed that teacher’s use of these non-verbal communication modes enhanced learners’ learning outcomes in English language: a total of 271 (90.33%) participants affirmed that teacher’s body language influenced their learning of English; 224 (74.66%) maintained the same stand for eye contact; while 202 (67.33%) affirmed that teacher’s spatial distance had positive influence. Consequent upon these findings, it was recommended that teachers of English language should constantly utilize non-verbal communication in their instructional delivery. Also, non-verbal communication modes should be included in teacher education programme to equip prospective pre-service teachers with the art of non-verbal communication.

Keywords: non-verbal communication, body language, eye contact, spatial distance, learning outcomes

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6602 Social Media Engagement in Academic Library to Advocate Participatory Service towards Dynamic Learning Community

Authors: Siti Marlia Abd Rahim, Mad Khir Johari Abdullah Sani

Abstract:

The ever-increasing use of social media applications by library users has raised concerns about the purpose and effectiveness of these platforms in academic libraries. While social media has the potential to revolutionize library services, its usage for non-educational purposes and security concerns have hindered its full potential. This paper aims to address the user behavioral factors affecting social media engagement in academic libraries and examine the impact of social media engagement on user participation. Additionally, it seeks to measure the effect of user participation in social media on the development of powerful learning communities.

Keywords: social media adoption, social media engagement, academic library, social media in academic library, learning community

Procedia PDF Downloads 117
6601 Deep Learning Based Road Crack Detection on an Embedded Platform

Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

Abstract:

It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

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6600 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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6599 Undergraduate Students’ Learning Experience and Practices in Multilingual Higher Education Institutions: The Case of the University of Luxembourg

Authors: Argyro Maria Skourmalla

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The present paper draws on the example of the University of Luxembourg as a multilingual and international setting. The University of Luxembourg, which is located between France, Germany, and Belgium, has adopted a new multilingualism policy in 2020, establishing English, French, German, and Luxembourgish as the official languages of the Institution. With around 7.000 students, more than half of which are international students, the University is a meeting point for languages and cultures. This paper includes data from an online survey that with undergraduate students from different disciplines at the University of Luxembourg. Students shared their personal experience and opinions regarding language use in this higher education context, as well as practices they use in learning in this multilingual context. Findings show the role of technology in assisting students in different aspects of learning this multilingual context. At the same time, more needs to be done to avoid an exclusively monolingual paradigm in higher education. Findings also show that some languages remain ‘unseen’ in this context. Overall, even though linguistic diversity in this University is seen as an asset, a lot needs to be done towards the recognition of staff and students’ linguistic repertoires for inclusion and education equity.

Keywords: higher education, learning, linguistic diversity, multilingual practices

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6598 Flipped Learning in the Delivery of Structural Analysis

Authors: Ali Amin

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This paper describes a flipped learning initiative which was trialed in the delivery of the course: structural analysis and modelling. A short series of interactive videos were developed, which introduced the key concepts of each topic. The purpose of the videos was to introduce concepts and give the students more time to develop their thoughts prior to the lecture. This allowed more time for face to face engagement during the lecture. As part of the initial study, videos were developed for half the topics covered. The videos included a short summary of the key concepts ( < 10 mins each) as well as fully worked-out examples (~30mins each). Qualitative feedback was attained from the students. On a scale from strongly disagree to strongly agree, students were rate statements such as 'The pre-class videos assisted your learning experience', 'I felt I could appreciate the content of the lecture more by watching the videos prior to class'. As a result of the pre-class engagement, the students formed more specific and targeted questions during class, and this generated greater comprehension of the material. The students also scored, on average, higher marks in questions pertaining to topics which had videos assigned to them.

Keywords: flipped learning, structural analysis, pre-class videos, engineering education

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6597 Metabolic Predictive Model for PMV Control Based on Deep Learning

Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

Procedia PDF Downloads 257
6596 Investigating Gender Differences in M-Learning Gameplay Adoption

Authors: Chih-Ping Chen

Abstract:

Despite the increasing popularity of and interest in mobile games, there has been little research that evaluates gender differences in users’ actual preferences for mobile game content, and the factors that influence entertainment and mobile-learning habits. To fill this void, this study examines different gender users’ experience of mobile English learning game adoption in order to identify the areas of development in Taiwan, using Uses and Gratification Theory, Expectation Confirmation Theory and experiential value. The integration of these theories forms the basis of an extended research concept. Users’ responses to questions about cognitive perceptions, confirmation, gratifications and continuous use were collected and analyzed with various factors derived from the theories.

Keywords: expectation confirmation theory, experiential value, gender difference, mobile game, uses and gratification

Procedia PDF Downloads 331
6595 Physical Education Effect on Sports Science Analysis Technology

Authors: Peter Adly Hamdy Fahmy

Abstract:

The aim of the study was to examine the effects of a physical education program on student learning by combining the teaching of personal and social responsibility (TPSR) with a physical education model and TPSR with a traditional teaching model, these learning outcomes involving self-learning. -Study. Athletic performance, enthusiasm for sport, group cohesion, sense of responsibility and game performance. The participants were 3 secondary school physical education teachers and 6 physical education classes, 133 participants with students from the experimental group with 75 students and the control group with 58 students, and each teacher taught the experimental group and the control group for 16 weeks. The research methods used surveys, interviews and focus group meetings. Research instruments included the Personal and Social Responsibility Questionnaire, Sports Enthusiasm Scale, Group Cohesion Scale, Sports Self-Efficacy Scale, and Game Performance Assessment Tool. Multivariate analyzes of covariance and repeated measures ANOVA were used to examine differences in student learning outcomes between combining the TPSR with a physical education model and the TPSR with a traditional teaching model. The research findings are as follows: 1) The TPSR sports education model can improve students' learning outcomes, including sports self-efficacy, game performance, sports enthusiasm, team cohesion, group awareness and responsibility. 2) A traditional teaching model with TPSR could improve student learning outcomes, including sports self-efficacy, responsibility, and game performance. 3) The sports education model with TPSR could improve learning outcomes more than the traditional teaching model with TPSR, including sports self-efficacy, sports enthusiasm, responsibility and game performance. 4) Based on qualitative data on teachers' and students' learning experience, the physical education model with TPSR significantly improves learning motivation, group interaction and sense of play. The results suggest that physical education with TPSR could further improve learning outcomes in the physical education program. On the other hand, the hybrid model curriculum projects TPSR - Physical Education and TPSR - Traditional Education are good curriculum projects for moral character education that can be used in school physics.

Keywords: approach competencies, physical, education, teachers employment, graduate, physical education and sport sciences, SWOT analysis character education, sport season, game performance, sport competence

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6594 Nalanda ‘School of Joy’: Teaching Learning Strategies and Support System, for Implementing Child-Friendly Education in Bangladesh

Authors: Sufia Ferdousi

Abstract:

Child-friendly education (CFE) is very important for the children, especially the early year’s students, because it fosters the holistic development of a child. Teacher plays a key role in creating child-friendly education. This study intends to learn about child-friendly education in Bangladesh. The purpose of the study is to explore how CFE is being practiced in Bangladesh. The study attempted to fulfill the purpose through case study investigation. One school, named Nalanda, was selected for the study as it claims to run the school through CFE approach. The objective of the study was to identify, how this school is different from the other schools in Bangladesh, to explore overall teaching learning system like, curriculum, teaching strategies, assessments and to investigate the support system for Child Friendly Education provided to the teachers through training or mentoring. The nature of the case study was qualitative method to get maximum information from the students, parents, teachers and school authorities. The findings were based on 3 classroom observations, interviews with 1 teacher, 1 head teacher and 1 trainer, FGD with 10 students and 6 parents, were used to collect the data. It has been found that Nalanda is different than the other schools in Bangladesh in terms of, parents’ motivation about school curriculum, and sufficiency of teachers’ knowledge on joyful learning/child-friendly learning. The students took part in the extracurricular activities alongside the national curriculum. Teachers showed particular strength in the teaching learning strategies, using materials and assessment. And Nalanda gives strong support for teacher’s training. In conclusion, The Nalanda School in Dhaka was found appropriate for the requirements of Child-friendly education.

Keywords: child friendly education, overall teaching learning system, the requirements of child-friendly education, the alternative education approach

Procedia PDF Downloads 247
6593 Forensic Imaging as an Effective Learning Tool for Teaching Forensic Pathology to Undergraduate Medical Students

Authors: Vasudeva Murthy Challakere Ramaswamy

Abstract:

Background: Conventionally forensic pathology is learnt through autopsy demonstrations which carry various limitations such as unavailability of cases in the mortuary, medico-legal implication and infection. Over the years forensic pathology and science has undergone significant evolution in this digital world. Forensic imaging is a technology which can be effectively utilized for overcoming the current limitations in the undergraduate learning of forensic curriculum. Materials and methods: demonstration of forensic imaging was done using a novel technology of autopsy which has been recently introduced across the globe. Three sessions were conducted in international medical university for a total of 196 medical students. The innovative educational tool was evacuated by using quantitative questionnaire with the scoring scales between 1 to 10. Results: The mean score for acceptance of new tool was 82% and about 74% of the students recommended incorporation of the forensic imaging in the regular curriculum. 82% of students were keen on collaborative research and taking further training courses in forensic imaging. Conclusion: forensic imaging can be an effective tool and also a suitable alternative for teaching undergraduate students. This feedback also supports the fact that students favour the use of contemporary technologies in learning medicine.

Keywords: forensic imaging, forensic pathology, medical students, learning tool

Procedia PDF Downloads 480
6592 Container Chaos: The Impact of a Casual Game on Learning and Behavior

Authors: Lori L. Scarlatos, Ryan Courtney

Abstract:

This paper explores the impact that playing a casual game can have on a player's learning and subsequent behavior. A casual mobile game, Container Chaos, was created to teach undergraduate students about the carbon footprint of various disposable beverage containers. Learning was tested with a short quiz, and behavior was tested by observing which beverage containers players choose when offered a drink and a snack. The game was tested multiple times, under a variety of different circumstances. Findings of these tests indicate that, with extended play over time, players can learn new information and sometimes even change their behavior as a result. This has implications for how other casual games can be used to teach concepts and possibly modify behavior.

Keywords: behavior, carbon footprint, casual games, environmental impact, material sciences

Procedia PDF Downloads 160
6591 Developing a Model of Teaching Writing Based On Reading Approach through Reflection Strategy for EFL Students of STKIP YPUP

Authors: Eny Syatriana, Ardiansyah

Abstract:

The purpose of recent study was to develop a learning model on writing, based on the reading texts which will be read by the students using reflection strategy. The strategy would allow the students to read the text and then they would write back the main idea and to develop the text by using their own sentences. So, the writing practice was begun by reading an interesting text, then the students would develop the text which has been read into their writing. The problem questions are (1) what kind of learning model that can develop the students writing ability? (2) what is the achievement of the students of STKIP YPUP through reflection strategy? (3) is the using of the strategy effective to develop students competence In writing? (4) in what level are the students interest toward the using of a strategy In writing subject? This development research consisted of some steps, they are (1) need analysis (2) model design (3) implementation (4) model evaluation. The need analysis was applied through discussion among the writing lecturers to create a learning model for writing subject. To see the effectiveness of the model, an experiment would be delivered for one class. The instrument and learning material would be validated by the experts. In every steps of material development, there was a learning process, where would be validated by an expert. The research used development design. These Principles and procedures or research design and development .This study, researcher would do need analysis, creating prototype, content validation, and limited empiric experiment to the sample. In each steps, there should be an assessment and revision to the drafts before continue to the next steps. The second year, the prototype would be tested empirically to four classes in STKIP YPUP for English department. Implementing the test greatly was done through the action research and followed by evaluation and validation from the experts.

Keywords: learning model, reflection, strategy, reading, writing, development

Procedia PDF Downloads 365
6590 The Effect of Computer-Mediated vs. Face-to-Face Instruction on L2 Pragmatics: A Meta-Analysis

Authors: Marziyeh Yousefi, Hossein Nassaji

Abstract:

This paper reports the results of a meta-analysis of studies on the effects of instruction mode on learning second language pragmatics during the last decade (from 2006 to 2016). After establishing related inclusion/ exclusion criteria, 39 published studies were retrieved and included in the present meta-analysis. Studies were later coded for face-to-face and computer-assisted mode of instruction. Statistical procedures were applied to obtain effect sizes. It was found that Computer-Assisted-Language-Learning studies generated larger effects than Face-to-Face instruction.

Keywords: meta-analysis, effect size, L2 pragmatics, comprehensive meta-analysis, face-to-face, computer-assisted language learning

Procedia PDF Downloads 223
6589 An Analysis of Institutional Audits: Basis for Teaching, Learning and Assessment Framework and Principles

Authors: Nabil El Kadhi, Minerva M. Bunagan

Abstract:

The dynamism in education, particularly in the area of teaching, learning and assessment has caused Higher Education Institutions (HEIs) worldwide to seek for ways to continuously improve their educational processes. HEIs use outcomes of institutional audits, assessments and accreditations, for improvement. In this study, the published institutional audit reports of HEIs in the Sultanate of Oman were analyzed to produce features of good practice; identify challenges along Teaching, Learning Assessment (TLA); and propose a framework that puts major emphasis in having a quality-assured TLA, including a set of principles that can be used as basis in succeeding an institutional visit. The TLA framework, which shows the TLA components, characteristics of the components, related expectation, including implementation tool/ strategy and pitfalls can be used by HEIs to have an adequate understanding of the scope of audit and be able to satisfy institutional audit requirements. The scope of this study can be widened by exploring the other requirements of the Institutional Audits in the Sultanate of Oman, particularly the area on Governance and Management and Student Support Services.

Keywords: accreditation, audit, teaching, learning and assessment, quality assurance

Procedia PDF Downloads 304
6588 Algorithms Inspired from Human Behavior Applied to Optimization of a Complex Process

Authors: S. Curteanu, F. Leon, M. Gavrilescu, S. A. Floria

Abstract:

Optimization algorithms inspired from human behavior were applied in this approach, associated with neural networks models. The algorithms belong to human behaviors of learning and cooperation and human competitive behavior classes. For the first class, the main strategies include: random learning, individual learning, and social learning, and the selected algorithms are: simplified human learning optimization (SHLO), social learning optimization (SLO), and teaching-learning based optimization (TLBO). For the second class, the concept of learning is associated with competitiveness, and the selected algorithms are sports-inspired algorithms (with Football Game Algorithm, FGA and Volleyball Premier League, VPL) and Imperialist Competitive Algorithm (ICA). A real process, the synthesis of polyacrylamide-based multicomponent hydrogels, where some parameters are difficult to obtain experimentally, is considered as a case study. Reaction yield and swelling degree are predicted as a function of reaction conditions (acrylamide concentration, initiator concentration, crosslinking agent concentration, temperature, reaction time, and amount of inclusion polymer, which could be starch, poly(vinyl alcohol) or gelatin). The experimental results contain 175 data. Artificial neural networks are obtained in optimal form with biologically inspired algorithm; the optimization being perform at two level: structural and parametric. Feedforward neural networks with one or two hidden layers and no more than 25 neurons in intermediate layers were obtained with values of correlation coefficient in the validation phase over 0.90. The best results were obtained with TLBO algorithm, correlation coefficient being 0.94 for an MLP(6:9:20:2) – a feedforward neural network with two hidden layers and 9 and 20, respectively, intermediate neurons. Good results obtained prove the efficiency of the optimization algorithms. More than the good results, what is important in this approach is the simulation methodology, including neural networks and optimization biologically inspired algorithms, which provide satisfactory results. In addition, the methodology developed in this approach is general and has flexibility so that it can be easily adapted to other processes in association with different types of models.

Keywords: artificial neural networks, human behaviors of learning and cooperation, human competitive behavior, optimization algorithms

Procedia PDF Downloads 108
6587 A Framework for Internet Education: Personalised Approach

Authors: Zoe Wong

Abstract:

The purpose of this paper is to develop a framework for internet education. This framework uses the personalized learning approach for everyone who can freely develop their qualifications & careers. The key components of the framework includes students, teachers, assessments and infrastructure. It allows remove the challenges and limitations of the current educational system and allows learners' to cope with progressing learning materials.

Keywords: internet education, personalized approach, information technology, framework

Procedia PDF Downloads 358