Search results for: online teaching and learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10041

Search results for: online teaching and learning

4131 Improving the Quality of Higher Education for Students with Disability in Universities of Pakistan

Authors: Nasir Sulman

Abstract:

In Pakistan, the inclusion of persons with disabilities in higher education institutions has significantly been increased with every passing year and anyone can observe a sizeable number of these students in each faculty. The study executes to conduct a baseline survey for measuring faculty understanding about the special needs, experiences of students with disabilities and support provided by university administration in order to teach these students effectively. The researcher has used mixed methods and the University of Karachi was selected through non-probability-based sampling method. This university is one of the largest universities in Pakistan where more than 40,000 students have been enrolled. Data was gathered through a questionnaire and focused group discussion from three stakeholders including students with disabilities, faculty members and members of the university administration. The key findings show that students with disabilities experience a number of problems related to accommodating their special needs. However, the most encouraging factors identified are the attitude, support, and motivation they received from various faculty members and university administration. On the basis of the findings of the study the researcher has prepared a faculty guidebook and established a ‘Model Learning Assistance Centre for Students with Disabilities’ in the Department of Special Education, University of Karachi. Both these efforts will be helpful for improving the support services for students with disabilities to strengthen the existing laws, policies, and practices in institutions of higher education.

Keywords: persons with disabilities, higher education, learning assistance center, faculty guidebook

Procedia PDF Downloads 146
4130 Optimal Driving Strategies for a Hybrid Street Type Motorcycle: Modelling and Control

Authors: Jhon Vargas, Gilberto Osorio-Gomez, Tatiana Manrique

Abstract:

This work presents an optimal driving strategy proposal for a 125 c.c. street-type hybrid electric motorcycle with a parallel configuration. The results presented in this article are complementary regarding the control proposal of a hybrid motorcycle. In order to carry out such developments, a representative dynamic model of the motorcycle is used, in which also are described different optimization functionalities for predetermined driving modes. The purpose is to implement an off-line optimal driving strategy which distributes energy to both engines by minimizing an objective torque requirement function. An optimal dynamic contribution is found from the optimization routine, and the optimal percentage contribution for vehicle cruise speed is implemented in the proposed online PID controller.

Keywords: dynamic model, driving strategies, parallel hybrid motorcycle, PID controller, optimization

Procedia PDF Downloads 183
4129 The Impact of Artificial Intelligence on Children with Autism

Authors: Rania Melad Kamel Hakim

Abstract:

A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. These have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these ‘syndrome’ forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or ‘non-syndrome’ autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way to improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co-morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties (‘sticky attention’), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.

Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills

Procedia PDF Downloads 50
4128 Integrating Microcontroller-Based Projects in a Human-Computer Interaction Course

Authors: Miguel Angel Garcia-Ruiz, Pedro Cesar Santana-Mancilla, Laura Sanely Gaytan-Lugo

Abstract:

This paper describes the design and application of a short in-class project conducted in Algoma University’s Human-Computer Interaction (HCI) course taught at the Bachelor of Computer Science. The project was based on the Maker Movement (people using and reusing electronic components and everyday materials to tinker with technology and make interactive applications), where students applied low-cost and easy-to-use electronic components, the Arduino Uno microcontroller board, software tools, and everyday objects. Students collaborated in small teams by completing hands-on activities with them, making an interactive walking cane for blind people. At the end of the course, students filled out a Technology Acceptance Model version 2 (TAM2) questionnaire where they evaluated microcontroller boards’ applications in HCI classes. We also asked them about applying the Maker Movement in HCI classes. Results showed overall students’ positive opinions and response about using microcontroller boards in HCI classes. We strongly suggest that every HCI course should include practical activities related to tinkering with technology such as applying microcontroller boards, where students actively and constructively participate in teams for achieving learning objectives.

Keywords: maker movement, microcontrollers, learning, projects, course, technology acceptance

Procedia PDF Downloads 168
4127 talk2all: A Revolutionary Tool for International Medical Tourism

Authors: Madhukar Kasarla, Sumit Fogla, Kiran Panuganti, Gaurav Jain, Abhijit Ramanujam, Astha Jain, Shashank Kraleti, Sharat Musham, Arun Chaudhury

Abstract:

Patients have often chosen to travel for care — making pilgrimages to academic meccas and state-of-the-art hospitals for sophisticated surgery. This culture is still persistent in the landscape of US healthcare, with hundred thousand of visitors coming to the shores of United States to seek the high quality of medical care. One of the major challenges in this form of medical tourism has been the language barrier. Thus, an Iraqi patient, with immediate needs of communicating the healthcare needs to the treating team in the hospital, may face huge barrier in effective patient-doctor communication, delaying care and even at times reducing the quality. To circumvent these challenges, we are proposing the use of a state-of-the-art tool, Talk2All, which can translate nearly one hundred international languages (and even sign language) in real time. The tool is an easy to download app and highly user friendly. It builds on machine learning principles to decode different languages in real time. We suggest that the use of Talk2All will tremendously enhance communication in the hospital setting, effectively breaking the language barrier. We propose that vigorous incorporation of Talk2All shall overcome practical challenges in international medical and surgical tourism.

Keywords: language translation, communication, machine learning, medical tourism

Procedia PDF Downloads 208
4126 Analysis of Engagement Methods in the College Classroom Post Pandemic

Authors: Marsha D. Loda

Abstract:

College enrollment is declining and generation Z, today’s college students, are struggling. Before the pandemic, researchers characterized this generational cohort as unique. Gen Z has been called the most achievement-oriented generation, as they enjoy greater economic status, are more racially and ethnically diverse, and better educated than any other generation. However, they are also the most likely generation to suffer from depression and anxiety. Gen Z has grown up largely with usually well-intentioned but overprotective parents who inadvertently kept them from learning life skills, likely impacting their ability to cope with and to effectively manage challenges. The unprecedented challenges resulting from the pandemic up ended their world and left them emotionally reeling. One of the ramifications of this for higher education is how to reengage current Gen Z students in the classroom. This research presents qualitative findings from 24 single-spaced pages of verbatim comments from college students. Research questions concerned what helps them learn and what they abhor, as well as how to engage them with the university outside of the classroom to aid in retention. Students leave little doubt about what they want to experience in the classroom. In order of mention, students want discussion, to engage with questions, to hear how a topic relates to real life and the real world, to feel connections with the professor and fellow students, and to have an opportunity to give their opinions. They prefer a classroom that involves conversation, with interesting topics and active learning. “professor talks instead of lecturing” “professor builds a connection with the classroom” “I am engaged because it feels like a respectful conversation” Similarly, students are direct about what they dislike in a classroom. In order of frequency, students dislike teachers unenthusiastically reading word or word from notes or presentations, repeating the text without adding examples, or addressing how to apply the information. “All lecture. I can read the book myself” “Not taught how to apply the skill or lesson” “Lectures the entire time. Lesson goes in one ear and out the other.” Pertaining to engagement outside the classroom, Gen Z challenges higher education to step outside the box. They don’t want to just hear from professionals in their field, they want to meet and interact with them. Perhaps because of their dependence on technology and pandemic isolation, they seem to reach out for assistance in forming social bonds. “I believe fun and social events are the best way to connect with students and get them involved. Cookouts, raffles, socials, or networking events would all most likely appeal to many students”. “Events… even if they aren’t directly related to learning. Maybe like movie nights… doing meet ups at restaurants”. Qualitative research suggests strategy. This research is rife with strategic implications to improve learning, increase engagement and reduce drop-out rates among Generation Z higher education students. It also compliments existing research on student engagement. With college enrollment declining by some 1.3 million students over the last two years, this research is both timely and important.

Keywords: college enrollment, generation Z, higher education, pandemic, student engagement

Procedia PDF Downloads 99
4125 Discrimination of Artificial Intelligence

Authors: Iman Abu-Rub

Abstract:

This research paper examines if Artificial Intelligence is, in fact, racist or not. Different studies from all around the world, and covering different communities were analyzed to further understand AI’s true implications over different communities. The black community, Asian community, and Muslim community were all analyzed and discussed in the paper to figure out if AI is biased or unbiased towards these specific communities. It was found that the biggest problem AI faces is the biased distribution of data collection. Most of the data inserted and coded into AI are of a white male, which significantly affects the other communities in terms of reliable cultural, political, or medical research. Nonetheless, there are various research was done that help increase awareness of this issue, but also solve it completely if done correctly. Governments and big corporations are able to implement different strategies into their AI inventions to avoid any racist results, which could cause hatred culturally but also unreliable data, medically, for example. Overall, Artificial Intelligence is not racist per se, but the data implementation and current racist culture online manipulate AI to become racist.

Keywords: social media, artificial intelligence, racism, discrimination

Procedia PDF Downloads 111
4124 Artificial Intelligence and the Next Generation Journalistic Practice: Prospects, Issues and Challenges

Authors: Shola Abidemi Olabode

Abstract:

The technological revolution over the years has impacted journalistic practice. As a matter of fact, journalistic practice has evolved alongside technologies of every generation transforming news and reporting, entertainment, and politics. Alongside these developments, the emergence of new kinds of risks and harms associated with generative AI has become rife with implications for media and journalism. Despite their numerous benefits for research and development, generative AI technologies like ChatGPT introduce new practical, ethical, and regulatory complexities in the practice of media and journalism. This paper presents a preliminary overview of the new kinds of challenges and issues for journalism and media practice in the era of generative AI, the implications for Nigeria, and invites a consideration of methods to mitigate the evolving complexity. It draws mainly on desk-based research underscoring the literature in both developed and developing non-western contexts as a contribution to knowledge.

Keywords: AI, journalism, media, online harms

Procedia PDF Downloads 74
4123 The Impact of Artificial Intelligence on Autism Attitudes

Authors: Sara Asham Mahrous Kamel

Abstract:

A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.

Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills

Procedia PDF Downloads 45
4122 Alphabet Recognition Using Pixel Probability Distribution

Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

Abstract:

Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

Procedia PDF Downloads 380
4121 Characterization of Crustin from Litopenaeus vannamei

Authors: Suchao Donpudsa, Anchalee Tassanakajon, Vichien Rimphanitchayakit

Abstract:

A crustin gene, LV-SWD1, previously found in the hemocyte cDNA library of Litopenaeus vannamei, contains the open reading frames of 288 bp encoding a putative protein of 96 amino acid residues. The putative signal peptides of the LV-SWD1 were identified using the online SignalP 3.0 with predicted cleavage sites between Ala24-Val25, resulting in 72 residue mature protein with calculated molecular mass of 7.4 kDa and predicted pI of 8.5. This crustin contains a Arg-Pro rich region at the amino-terminus and a single whey acidic protein (WAP) domain at the carboxyl-terminus. In order to characterize their properties and biological activities, the recombinant crustin protein was produced in the Escherichia coli expression system. Antimicrobial assays showed that the growth of Bacillus subtilis was inhibited by this recombinant crustin with MIC of about 25-50 µM.

Keywords: crustin, single whey acidic protein, Litopenaeus vannamei, antimicrobial activity

Procedia PDF Downloads 239
4120 BodeACD: Buffer Overflow Vulnerabilities Detecting Based on Abstract Syntax Tree, Control Flow Graph, and Data Dependency Graph

Authors: Xinghang Lv, Tao Peng, Jia Chen, Junping Liu, Xinrong Hu, Ruhan He, Minghua Jiang, Wenli Cao

Abstract:

As one of the most dangerous vulnerabilities, effective detection of buffer overflow vulnerabilities is extremely necessary. Traditional detection methods are not accurate enough and consume more resources to meet complex and enormous code environment at present. In order to resolve the above problems, we propose the method for Buffer overflow detection based on Abstract syntax tree, Control flow graph, and Data dependency graph (BodeACD) in C/C++ programs with source code. Firstly, BodeACD constructs the function samples of buffer overflow that are available on Github, then represents them as code representation sequences, which fuse control flow, data dependency, and syntax structure of source code to reduce information loss during code representation. Finally, BodeACD learns vulnerability patterns for vulnerability detection through deep learning. The results of the experiments show that BodeACD has increased the precision and recall by 6.3% and 8.5% respectively compared with the latest methods, which can effectively improve vulnerability detection and reduce False-positive rate and False-negative rate.

Keywords: vulnerability detection, abstract syntax tree, control flow graph, data dependency graph, code representation, deep learning

Procedia PDF Downloads 164
4119 Contextual Toxicity Detection with Data Augmentation

Authors: Julia Ive, Lucia Specia

Abstract:

Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

Procedia PDF Downloads 166
4118 Self-Regulation and School Adjustment of Students with Autism Spectrum Disorder in Hong Kong

Authors: T. S. Terence Ma, Irene T. Ho

Abstract:

Conducting adequate assessment of the challenges students with ASD (Autism Spectrum Disorder) face and the support they need is imperative for promoting their school adjustment. Students with ASD often show deficits in communication, social interaction, emotional regulation, and self-management in learning. While targeting these areas in intervention is often helpful, we argue that not enough attention has been paid to weak self-regulation being a key factor underlying their manifest difficulty in all these areas. Self-regulation refers to one’s ability to moderate their behavioral or affective responses without assistance from others. Especially for students with high functioning autism, who often show problems not so much in acquiring the needed skills but rather in applying those skills appropriately in everyday problem-solving, self-regulation becomes a key to successful adjustment in daily life. Therefore, a greater understanding of the construct of self-regulation, its relationship with other daily skills, and its role in school functioning for students with ASD would generate insights on how students’ school adjustment could be promoted more effectively. There were two focuses in this study. Firstly, we examined the extent to which self-regulation is a distinct construct that is differentiable from other daily skills and the most salient indicators of this construct. Then we tested a model of relationships between self-regulation and other daily school skills as well as their relative and combined effects on school adjustment. A total of 1,345 Grade1 to Grade 6 students with ASD attending mainstream schools in Hong Kong participated in the research. In the first stage of the study, teachers filled out a questionnaire consisting of 136 items assessing a wide range of student skills in social, emotional and learning areas. Results from exploratory factor analysis (EFA) with 673 participants and subsequent confirmatory factor analysis (CFA) with another group of 672 participants showed that there were five distinct factors of school skills, namely (1) communication skills, (2) pro-social behavior, (3) emotional skills, (4) learning management, and (5) self-regulation. Five scales representing these skill dimensions were generated. In the second stage of the study, a model postulating the mediating role of self-regulation for the effects of the other four types of skills on school adjustment was tested with structural equation modeling (SEM). School adjustment was defined in terms of the extent to which the student is accepted well in school, with high engagement in school life and self-esteem as well as good interpersonal relationships. A 5-item scale was used to assess these aspects of school adjustment. Results showed that communication skills, pro-social behavior, emotional skills and learning management had significant effects on school adjustment only indirectly through self-regulation, and their total effects were found to be not high. The results indicate that support rendered to students with ASD focusing only on the training of well-defined skills is not adequate for promoting their inclusion in school. More attention should be paid to the training of self-management with an emphasis on the application of skills backed by self-regulation. Also, other non-skill factors are important in promoting inclusive education.

Keywords: autism, assessment, factor analysis, self-regulation, school adjustment

Procedia PDF Downloads 103
4117 Development of Gamma Configuration Stirling Engine Using Polymeric and Metallic Additive Manufacturing for Education

Authors: J. Otegui, M. Agirre, M. A. Cestau, H. Erauskin

Abstract:

The increasing accessibility of mid-priced additive manufacturing (AM) systems offers a chance to incorporate this technology into engineering instruction. Furthermore, AM facilitates the creation of manufacturing designs, enhancing the efficiency of various machines. One example of these machines is the Stirling cycle engine. It encompasses complex thermodynamic machinery, revealing various aspects of mechanical engineering expertise upon closer inspection. In this publication, the application of Stirling Engines fabricated via additive manufacturing techniques will be showcased for the purpose of instructive design and product enhancement. The performance of a Stirling engine's conventional displacer and piston is contrasted. The outcomes of utilizing this instructional tool in teaching are demonstrated.

Keywords: 3D printing, additive manufacturing, mechanical design, stirling engine.

Procedia PDF Downloads 45
4116 The Struggle to teach/learn English as a Foreign Language in Turkiye: A Critical Report

Authors: Gizem Yilmazel

Abstract:

Turkiye has been facing failure in English language teaching despite long years of English studies during mandatory education. A body of research studying the reasons of the failure in the literature exists yet the problem has not been solved and English language education is still a phenomenon in Turkiye. The failure is mostly attributed to the methods used in English education (Grammar Translation Method), lack of exposure to the language, inability to practice the language, financial difficulties, the belief of abroad experience necessity, national examinations, and conservative institutional policies. The findings are evident and tangible yet the problem persists. This paper aims to bring the issue a critical perspective and discuss the reasons of the failure.

Keywords: EFL, failure, critical perspective, language education

Procedia PDF Downloads 50
4115 A Comparison Study: Infant and Children’s Clothing Size Charts in South Korea and UK

Authors: Hye-Won Lim, Tom Cassidy, Tracy Cassidy

Abstract:

Infant and children’s body shapes are changing constantly while they are growing up into adults and are also distinctive physically between countries. For this reason, optimum size charts which can represent body sizes and shapes of infants and children are required. In this study, investigations of current size charts in South Korea and UK (n=50 each) were conducted for understanding and figuring out the sizing perspectives of the clothing manufacturers. The size charts of the two countries were collected randomly from online shopping websites and those size charts’ average measurements were compared with both national sizing surveys (SizeKorea and Shape GB). The size charts were also classified by age, gender, clothing type, fitting, and other factors. In addition, the key measurement body parts of size charts of each country were determined and those will be suggested for new size charts and sizing system development.

Keywords: infant clothing, children’s clothing, body shapes, size charts

Procedia PDF Downloads 311
4114 Design of a Small and Medium Enterprise Growth Prediction Model Based on Web Mining

Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

Abstract:

Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

Procedia PDF Downloads 261
4113 Object-Oriented Modeling Simulation and Control of Activated Sludge Process

Authors: J. Fernandez de Canete, P. Del Saz Orozco, I. Garcia-Moral, A. Akhrymenka

Abstract:

Object-oriented modeling is spreading in current simulation of wastewater treatments plants through the use of the individual components of the process and its relations to define the underlying dynamic equations. In this paper, we describe the use of the free-software OpenModelica simulation environment for the object-oriented modeling of an activated sludge process under feedback control. The performance of the controlled system was analyzed both under normal conditions and in the presence of disturbances. The object-oriented described approach represents a valuable tool in teaching provides a practical insight in wastewater process control field.

Keywords: object-oriented programming, activated sludge process, OpenModelica, feedback control

Procedia PDF Downloads 381
4112 The Cultural Shift in Pre-owned Fashion as Sustainable Consumerism in Vietnam

Authors: Lam Hong Lan

Abstract:

The textile industry is said to be the second-largest polluter, responsible for 92 million tonnes of waste annually. There is an urgent need to practice the circular economy to increase the use and reuse around the world. By its nature, the pre-owned fashion business is considered part of the circular economy as it helps to eliminate waste and circulate products. Second-hand clothes and accessories used to be associated with a ‘cheap image’ that carried ‘old energy’ in Vietnam. This perception has been shifted, especially amongst the younger generation. Vietnamese consumer is spending more on products and services that increase self-esteem. The same consumer is moving away from a collectivist social identity towards a ‘me, not we’ outlook as they look for a way to express their individual identity. And pre-owned fashion is one of their solutions as it values money, can create a unique personal style for the wearer and links with sustainability. The design of this study is based on the second-hand shopping motivation theory. A semi-structured online survey with 100 consumers from one pre-owned clothing community and one pre-owned e-commerce site in Vietnam. The findings show that in contrast with Vietnamese older consumers (55+yo) who, in the previous study, generally associated pre-owned fashion with ‘low-cost’, ‘cheap image’ that carried ‘old energy’, young customers (20-30 yo) were actively promoted their pre-owned fashion items to the public via outlet’s social platforms and their social media. This cultural shift comes from the impact of global and local discourse around sustainable fashion and the growth of digital platforms in the pre-owned fashion business in the last five years, which has generally supported wider interest in pre-owned fashion in Vietnam. It can be summarised in three areas: (1) global and local celebrity influencers. A number of celebrities have been photographed wearing vintage items in music videos, photoshoots or at red carpet events. (2) E-commerce and intermediaries. International e-commerce sites – e.g., Vinted, TheRealReal – and/or local apps – e.g., Re.Loved – can influence attitudes and behaviors towards pre-owned consumption. (3) Eco-awareness. The increased online coverage of climate change and environmental pollution has encouraged customers to adopt a more eco-friendly approach to their wardrobes. While sustainable biomaterials and designs are still navigating their way into sustainability, sustainable consumerism via pre-owned fashion seems to be an immediate solution to lengthen the clothes lifecycle. This study has found that young consumers are primarily seeking value for money and/or a unique personal style from pre-owned/vintage fashion while using these purchases to promote their own “eco-awareness” via their social media networks. This is a good indication for fashion designers to keep in mind in their design process and for fashion enterprises in their business model’s choice to not overproduce fashion items.

Keywords: cultural shift, pre-owned fashion, sustainable consumption, sustainable fashion.

Procedia PDF Downloads 78
4111 The Impact of Technology and Artificial Intelligence on Children in Autism

Authors: Dina Moheb Rashid Michael

Abstract:

A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.

Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills

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4110 Women’s Experience of Managing Pre-Existing Lymphoedema during Pregnancy and the Early Postnatal Period

Authors: Kim Toyer, Belinda Thompson, Louise Koelmeyer

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Lymphoedema is a chronic condition caused by dysfunction of the lymphatic system, which limits the drainage of fluid and tissue waste from the interstitial space of the affected body part. The normal physiological changes in pregnancy cause an increased load on a normal lymphatic system which can result in a transient lymphatic overload (oedema). The interaction between lymphoedema and pregnancy oedema is unclear. Women with pre-existing lymphoedema require accurate information and additional strategies to manage their lymphoedema during pregnancy. Currently, no resources are available to guide women or their healthcare providers with accurate advice and additional management strategies for coping with lymphoedema during pregnancy until they have recovered postnatally. This study explored the experiences of Australian women with pre-existing lymphoedema during recent pregnancy and the early postnatal period to determine how their usual lymphoedema management strategies were adapted and what were their additional or unmet needs. Interactions with their obstetric care providers, the hospital maternity services, and usual lymphoedema therapy services were detailed. Participants were sourced from several Australian lymphoedema community groups, including therapist networks. Opportunistic sampling is appropriate to explore this topic in a small target population as lymphoedema in women of childbearing age is uncommon, with prevalence data unavailable. Inclusion criteria were aged over 18 years, diagnosed with primary or secondary lymphoedema of the arm or leg, pregnant within the preceding ten years (since 2012), and had their pregnancy and postnatal care in Australia. Exclusion criteria were a diagnosis of lipedema and if unable to read or understand a reasonable level of English. A mixed-method qualitative design was used in two phases. This involved an online survey (REDCap platform) of the participants followed by online semi-structured interviews or focus groups to provide the transcript data for inductive thematic analysis to gain an in-depth understanding of issues raised. Women with well-managed pre-existing lymphoedema coped well with the additional oedema load of pregnancy; however, those with limited access to quality conservative care prior to pregnancy were found to be significantly impacted by pregnancy, including many reporting deterioration of their chronic lymphoedema. Misinformation and a lack of support increased fear and apprehension in planning and enjoying their pregnancy experience. Collaboration between maternity and lymphoedema therapy services did not happen despite study participants suggesting it. Helpful resources and unmet needs were identified in the recent Australian context to inform further research and the development of resources to assist women with lymphoedema who are considering or are pregnant and their supporters, including health care providers.

Keywords: lymphoedema, management strategies, pregnancy, qualitative

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4109 Automation of AAA Game Development using AI and Procedural Generation

Authors: Paul Toprac, Branden Heng, Harsheni Siddharthan, Allison Tseng, Sarah Abraham, Etienne Vouga

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The goal of this project was to evaluate and document the capabilities and limitations of AI tools for empowering small teams to create high budget, high profile (AAA) 3D games typically developed by large studios. Two teams of novice game developers attempted to create two different games using AI and Unreal Engine 5.3. First, the teams evaluated 60 AI art, design, sound, and programming tools by considering their capability, ease of use, cost, and license restrictions. Then, the teams used a shortlist of 13 AI tools for game development. During this process, the following tools were found to be the most productive: (1) ChatGPT 4.0 for both game and narrative concepting and documentation; (2) Dall-E 3 and OpenArt for concept art; (3) Beatoven for music drafting; (4) Epic PCG for level design; and (5) ChatGPT 4.0 and Github Copilot for generating simple code and to complement human-made tutorials as an additional learning resource. While current generative AI may appear impressive at first glance, the assets they produce fall short of AAA industry standards. Generative AI tools are helpful when brainstorming ideas such as concept art and basic storylines, but they still cannot replace human input or creativity at this time. Regarding programming, AI can only effectively generate simple code and act as an additional learning resource. Thus, generative AI tools are at best tools to enhance developer productivity rather than as a system to replace developers.

Keywords: AAA games, AI, automation tools, game development

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4108 Content Monetization as a Mark of Media Economy Quality

Authors: Bela Lebedeva

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Characteristics of the Web as a channel of information dissemination - accessibility and openness, interactivity and multimedia news - become wider and cover the audience quickly, positively affecting the perception of content, but blur out the understanding of the journalistic work. As a result audience and advertisers continue migrating to the Internet. Moreover, online targeting allows monetizing not only the audience (as customarily given to traditional media) but also the content and traffic more accurately. While the users identify themselves with the qualitative characteristics of the new market, its actors are formed. Conflict of interests is laid in the base of the economy of their relations, the problem of traffic tax as an example. Meanwhile, content monetization actualizes fiscal interest of the state too. The balance of supply and demand is often violated due to the political risks, particularly in terms of state capitalism, populism and authoritarian methods of governance such social institutions as the media. A unique example of access to journalistic material, limited by monetization of content is a television channel Dozhd' (Rain) in Russian web space. Its liberal-minded audience has a better possibility for discussion. However, the channel could have been much more successful in terms of unlimited free speech. Avoiding state pressure and censorship its management has decided to save at least online performance and monetizing all of the content for the core audience. The study Methodology was primarily based on the analysis of journalistic content, on the qualitative and quantitative analysis of the audience. Reconstructing main events and relationships of actors on the market for the last six years researcher has reached some conclusions. First, under the condition of content monetization the capitalization of its quality will always strive to quality characteristics of user, thereby identifying him. Vice versa, the user's demand generates high-quality journalism. The second conclusion follows the previous one. The growth of technology, information noise, new political challenges, the economy volatility and the cultural paradigm change – all these factors form the content paying model for an individual user. This model defines him as a beneficiary of specific knowledge and indicates the constant balance of supply and demand other conditions being equal. As a result, a new economic quality of information is created. This feature is an indicator of the market as a self-regulated system. Monetized information quality is less popular than that of the Public Broadcasting Service, but this audience is able to make decisions. These very users keep the niche sectors which have more potential of technology development, including the content monetization ways. The third point of the study allows develop it in the discourse of media space liberalization. This cultural phenomenon may open opportunities for the development of social and economic relations architecture both locally and regionally.

Keywords: content monetization, state capitalism, media liberalization, media economy, information quality

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4107 The Active Social Live of #Lovewins: Understanding the Discourse of Homosexual Love and Rights in Thailand

Authors: Tinnaphop Sinsomboonthong

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The hashtag, #LoveWins, has been widely used for celebrating the victory of the LGBTQ movement since June 2015 when the US Supreme Court enacted the rights of same-sex marriage. Nowadays, the hashtag is generally used among active social media users in many countries, including Thailand. Amidst the political conflict between advocates of the junta-backed legislation related to same-sex marriage laws, known as ‘Thailand’s Civil Partnership Draft Bills,’ and its detractors, the hashtag becomes crucial for Thailand’s 2019 national election season and shortly afterward as it was one of the most crucial parts of a political campaign to rebrand many political parties’ image, create an LGBT-friendly atmosphere and neutralize the bi-polarized politics of the law. The use of the hashtag is, therefore, not just an online entertainment but a politico-discursive tool, used by many actors for many purposes. Behind the confrontation between supporters and opposers of the law, the hashtag is used by both sides to highlight the Western-centric normativity of homosexual love, closely associated with Eurocentric modernity and heteronormativity. As an online ethnographical study, this paper aims to analyze how #LoveWins is used among Thai social media users in late 2018 to mid-2019 and how it is signified by Thai social media users during the Drafted-Bills period and the 2019 national election. A number of preliminary surveys of data on Twitter were conducted in December 2018 and, more intensely, in January 2019. Later, the data survey was officially conducted twice during February and April 2019, while the data collection was done during May-June 2019. Only public posts on Twitter that include the hashtag, #LoveWins, or any hashtags quoting ‘love’ and ‘wins’ are the main targets of this research. As a result of this, the use of the hashtag can be categorized into three levels, including banal decoration, homosexual love celebration, and colonial discourse on homosexual love. Particularly in the third type of the use of the hashtag, discourse analysis is applied to reveal that this hashtag is closely associated with the discourse of development and modernity as most of the descriptive posts demonstrate aspirations to become more ‘developed and modernized’ like many Western countries and Taiwan, the LGBT capital in Asia. Thus, calls for the ‘right to homosexual love’ and the ‘right to same-sex marriage’ in Thailand are shaped and formulated within the discursive linkage between modernity, development, and love. Also, the use of #LoveWins can be considered as a de-queering process of love as only particular types of gender identity, sexual orientation, and relationships that reflect Eurocentric modernity and heteronormativity are acceptable and advocated. Due to this, more inclusive queer loves should be supported rather than a mere essentialist-traditionalist homosexual love. Homonormativity must be deconstructed, and love must no longer be reserved for only one particular type of relationship that is standardized from/by the West. It must become more inclusive.

Keywords: #LoveWins, homosexual love, LGBT rights, same-sex marriage

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4106 Identifying Autism Spectrum Disorder Using Optimization-Based Clustering

Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning

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4105 The Status of English in the Israeli Academy

Authors: Ronit German, Alexandra Beytenbrat

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Although English seems to be prevalent in every sphere of Israeli daily life, not many Israeli students have a sufficient level of writing and speaking in English which is necessary for academic studies. The inadequate level of English among Israeli students, almost the sole focus on teaching reading comprehension, and the need to adapt to the trends of the professional worldwide demands triggered a reform that requires to implement Common European Framework of Reference (CEFR) and English as a Medium of Instruction (EMI) courses in the Israeli academic institutions. However, it will be argued that this reform is challenging to implement. The fact that modern Hebrew is a revived language, and that English is L3 for more than 30% of the population, the diverse social and cultural students’ background, and psychological factors stand in the way of the new reform.

Keywords: CEFR, cultural diversity, EMI courses, English in Israel, reform

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4104 Teaching Academic Vocabulary: A Recent and Old Approach

Authors: Sara Fine-Meltzer

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An obvious, but ill-addressed hindrance to reading comprehension in academic English is poor vocabulary. Unfortunately, dealing with the problem is usually delayed until university entrance. It is the contention of this paper that the chore should be confronted much earlier and by using a very old-fashioned method. This presentation is accompanied by vocabulary lists for advanced level university students with explanations concerning the content and justification for the 500-word lists: how they change over time in accordance with evolving styles of academic writing. There are also sample quizzes and methods to ensure that the words are “absorbed” over time. There is a discussion of other vocabulary acquisition methods and conclusions drawn from the drawbacks of such methods. The paper concludes with the rationale for beginning the study of “academic” vocabulary earlier than is generally acceptable.

Keywords: academic vocabulary, old-fashioned methods, quizzes, vocabulary lists

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4103 Implementation of Nutritional Awareness Programme on Eating Habits of Primary School Children

Authors: Gulcin Satir, Ahmet Yildirim

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Globally, including Turkey, health problems associated with malnutrition and nutrient deficiencies in childhood will remain major public health problems in future. Nutrition is a major environmental influence on physical and mental growth and development in early life. Many studies support the fact that nutritional knowledge makes contribution to wellbeing of children and their school performance. The purpose of this study was to examine nutritional knowledge and eating habits of primary school children and to investigate differences in these variables by socioeconomic status. A quasi-experimental one group pretest/posttest design study was conducted in five primary schools totaling 200 children aging 9-10 years in grade 4 to determine the effect of nutritional awareness programme on eating habits of primary school children. The schools were chosen according to parents’ social and demographic characteristics. The implemented nutritional awareness education programme focused on healthy lifestyle such as beneficial foods, eating habits, personal hygiene, physical activity and the programme consisted of eight lessons. The teaching approaches used included interactive teaching, role-playing, demonstration, small group discussions, questioning, and feedback. The lessons were given twice a week for four weeks totaling eight lessons. All lessons lasted 45-60 minutes and first 5 minutes of this was pre-assessment and last 5 minutes post assessment evaluation. The obtained data were analyzed for normality, and the distribution of the variables was tested by the Kolmogorov-Smirnov test. Paired t-test was used to evaluate the effectiveness of education programme and to compare the above-mentioned variables in each school separately before and after the lessons. The result of the paired t-test conducted separately for each school showed that on average after eight lessons, there was a 25-32% increase in nutritional knowledge of students regardless of the school they attend to and this rate was significant (P < 0.01). This shows that increase in nutritional awareness in these five schools having different socio-economic status was similar to each other. This study suggests that having children involved directly in lessons help to achieve nutritional awareness leading to healthy eating habits. It is concluded that nutritional awareness is a valuable tool to change eating habits. Study findings will provide information for developing nutrition education programmes for the healthy life and obesity prevention in children.

Keywords: children, nutritional awareness, obesity, socioeconomic status

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4102 Testing a Motivational Model of Physical Education on Contextual Outcomes and Total Moderate to Vigorous Physical Activity of Middle School Students

Authors: Arto Grasten

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Given the rising trend in obesity in children and youth, age-related decline in moderate- to- vigorous-intensity physical activity (MVPA) in several Western, African, and Asian countries in addition to limited evidence of behavioral, affective, cognitive outcomes in physical education, it is important to clarify the motivational processes in physical education classes behind total MVPA engagement. The present study examined the full sequence of the Hierarchical Model of Motivation in physical education including motivational climate, basic psychological needs, intrinsic motivation, contextual behavior, affect, cognition, total MVPA, and associated links to body mass index (BMI) and gender differences. A cross-sectional data comprised self-reports and objective assessments of 770 middle school students (Mage = 13.99 ± .81 years, 52% of girls) in North-East Finland. In order to test the associations between motivational climate, psychological needs, intrinsic motivation, cognition, behavior, affect, and total MVPA, a path model was implemented. Indirect effects between motivational climate and cognition, behavior, affect and total MVPA were tested by setting basic needs and intrinsic motivation as mediators into the model. The findings showed that direct and indirect paths for girls and boys associated with different contextual outcomes and girls’ indirect paths were not related with total MVPA. Precisely, task-involving climate-mediated by physical competence and intrinsic motivation related to enjoyment, importance, and graded assessments within girls, whereas task-involving climate associated with enjoyment and importance via competence and autonomy, and total MVPA via autonomy, intrinsic motivation, and importance within boys. Physical education assessments appeared to be essential in motivating students to participate in greater total MVPA. BMI was negatively linked with competence and relatedness only among girls. Although, the current and previous empirical findings supported task-involving teaching methods in physical education, in some cases, ego-involving climate should not be totally avoided. This may indicate that girls and boys perceive physical education classes in a different way. Therefore, both task- and ego-involving teaching practices can be useful ways of driving behavior in physical education classes.

Keywords: achievement goal theory, assessment, enjoyment, hierarchical model of motivation, physical activity, self-determination theory

Procedia PDF Downloads 275