Search results for: machine learning techniques
10947 Brain Networks and Mathematical Learning Processes of Children
Authors: Felicitas Pielsticker, Christoph Pielsticker, Ingo Witzke
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Neurological findings provide foundational results for many different disciplines. In this article we want to discuss these with a special focus on mathematics education. The intention is to make neuroscience research useful for the description of cognitive mathematical learning processes. A key issue of mathematics education is that students often behave as if their mathematical knowledge is constructed in isolated compartments with respect to the specific context of the original learning situation; supporting students to link these compartments to form a coherent mathematical society of mind is a fundamental task not only for mathematics teachers. This aspect goes hand in hand with the question if there is such a thing as abstract general mathematical knowledge detached from concrete reality. Educational Neuroscience may give answers to the question why students develop their mathematical knowledge in isolated subjective domains of experience and if it is generally possible to think in abstract terms. To address these questions, we will provide examples from different fields of mathematics education e.g. students’ development and understanding of the general concept of variables or the mathematical notion of universal proofs. We want to discuss these aspects in the reflection of functional studies which elucidate the role of specific brain regions in mathematical learning processes. In doing this the paper addresses concept formation processes of students in the mathematics classroom and how to support them adequately considering the results of (educational) neuroscience.Keywords: brain regions, concept formation processes in mathematics education, proofs, teaching-learning processes
Procedia PDF Downloads 14910946 Development and Psychometric Properties of the Dutch Contextual Assessment of Social Skills: A Blinded Observational Outcome Measure of Social Skills for Adolescents with Autism Spectrum Disorder
Authors: Sakinah Idris, Femke Ten Hoeve, Kirstin Greaves-Lord
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Background: Social skills interventions are considered to be efficacious if social skills are improved as a result of an intervention. Nevertheless, the objective assessment of social skills is hindered by a lack of sensitive and validated measures. To measure the change in social skills after an intervention, questionnaires reported by parents, clinicians and/or teachers are commonly used. Observations are the most ecologically valid method of assessing improvements in social skills after an intervention. For this purpose, The Program for the Educational and Enrichment of Relational Skills (PEERS) was developed for adolescents, in order to teach them the age-appropriate skills needed to participate in society. It is an evidence-based intervention for adolescents with ASD that taught ecologically valid social skills techniques. Objectives: The current study aims to describe the development and psychometric evaluation of the Dutch Contextual Assessment of Social Skills (CASS), an observational outcome measure of social skills for adolescents with Autism Spectrum Disorder (ASD). Methods: 64 adolescents (M = 14.68, SD = 1.41, 71% boys) with ASD performed the CASS before and after a social skills intervention (i.e. PEERS or the active control condition). Each adolescent completed a 3-minute conversation with a confederate. The conversation was prompt as a natural introduction between two-unfamiliar, similar ages, opposite-sex peers who meet for the first time. The adolescent and the confederate completed a brief questionnaire about the conversation (Conversation Rating Scale). Results: Results indicated sufficient psychometric properties. The Dutch CASS has a high level of internal consistency (Cronbach's α coefficients = 0.84). Data supported the convergent validity (i.e., significant correlated with the Social Skills Improvement System (SSiS). The Dutch CASS did not significantly correlate with the autistic mannerism subscale from Social Responsiveness Scale (SRS), thus proved the divergent validity. Based on scorings made by raters who were kept blind to the time points, reliable change index was computed to assess the change in social skills. With regard to the content validity, only the learning objectives of the first two meetings of PEERS about conversational skills relatively matched with rating domains of the CASS. Due to this underrepresentation, we found an existing observational measure (TOPICC) that covers some of the other learning objectives of PEERS. TOPICC covers 22% of the learning objectives of PEERS about conversational skills, meanwhile, CASS is 45%. Unfortunately, 33% of the learning objectives of PEERS was not covered by CASS or TOPICC. Conclusion: Recommendations are made to improve the psychometric properties and content validity of the Dutch CASS.Keywords: autism spectrum disorder, observational, PEERS, social skills
Procedia PDF Downloads 15510945 Pattern Discovery from Student Feedback: Identifying Factors to Improve Student Emotions in Learning
Authors: Angelina A. Tzacheva, Jaishree Ranganathan
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Interest in (STEM) Science Technology Engineering Mathematics education especially Computer Science education has seen a drastic increase across the country. This fuels effort towards recruiting and admitting a diverse population of students. Thus the changing conditions in terms of the student population, diversity and the expected teaching and learning outcomes give the platform for use of Innovative Teaching models and technologies. It is necessary that these methods adapted should also concentrate on raising quality of such innovations and have positive impact on student learning. Light-Weight Team is an Active Learning Pedagogy, which is considered to be low-stake activity and has very little or no direct impact on student grades. Emotion plays a major role in student’s motivation to learning. In this work we use the student feedback data with emotion classification using surveys at a public research institution in the United States. We use Actionable Pattern Discovery method for this purpose. Actionable patterns are patterns that provide suggestions in the form of rules to help the user achieve better outcomes. The proposed method provides meaningful insight in terms of changes that can be incorporated in the Light-Weight team activities, resources utilized in the course. The results suggest how to enhance student emotions to a more positive state, in particular focuses on the emotions ‘Trust’ and ‘Joy’.Keywords: actionable pattern discovery, education, emotion, data mining
Procedia PDF Downloads 9810944 The Effect of Artificial Intelligence on Accounting and Finance
Authors: Evrime Fawzy Ishak Gadelsayed
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This paper presents resource intake accounting as an inventive manner to cope with control accounting, which concentrates on administrators as the crucial customers of the information and offers satisfactory statistics of conventional control accounting. This machine underscores that the association's asset motivates prices; as a consequence, in costing frameworks, the emphasis ought to be on assets and their usage. Resource consumption accounting consolidates two costing methodologies, action-based totally and the German cost accounting approach called GPK. This methodology, however, is a danger to managers when making the management accounting undertaking operational. The motive for this article is to clarify the concept of resource intake accounting, its elements and highlights and use of this approach in associations. Inside the first area, we present useful resource consumption accounting, the basis, reasons for its improvement, and the issues that are faced beyond costing frameworks. At that point, we deliver the requirements and presumptions of this approach; ultimately, we depict the execution of this approach in associations and its preferences over other costing techniques.Keywords: financial statement fraud, forensic accounting, fraud prevention and detection, auditing, audit expectation gap, corporate governance resource consumption accounting, management accounting, action based method, German cost accounting method
Procedia PDF Downloads 710943 Applying Big Data Analysis to Efficiently Exploit the Vast Unconventional Tight Oil Reserves
Authors: Shengnan Chen, Shuhua Wang
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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves
Procedia PDF Downloads 28310942 A Survey on Data-Centric and Data-Aware Techniques for Large Scale Infrastructures
Authors: Silvina Caíno-Lores, Jesús Carretero
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Large scale computing infrastructures have been widely developed with the core objective of providing a suitable platform for high-performance and high-throughput computing. These systems are designed to support resource-intensive and complex applications, which can be found in many scientific and industrial areas. Currently, large scale data-intensive applications are hindered by the high latencies that result from the access to vastly distributed data. Recent works have suggested that improving data locality is key to move towards exascale infrastructures efficiently, as solutions to this problem aim to reduce the bandwidth consumed in data transfers, and the overheads that arise from them. There are several techniques that attempt to move computations closer to the data. In this survey we analyse the different mechanisms that have been proposed to provide data locality for large scale high-performance and high-throughput systems. This survey intends to assist scientific computing community in understanding the various technical aspects and strategies that have been reported in recent literature regarding data locality. As a result, we present an overview of locality-oriented techniques, which are grouped in four main categories: application development, task scheduling, in-memory computing and storage platforms. Finally, the authors include a discussion on future research lines and synergies among the former techniques.Keywords: data locality, data-centric computing, large scale infrastructures, cloud computing
Procedia PDF Downloads 25910941 Formation of Science Literations Based on Indigenous Science Mbaru Niang Manggarai
Authors: Yuliana Wahyu, Ambros Leonangung Edu
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The learning praxis that is proposed by 2013 Curriculum (K-13) is no longer school-oriented as a supply-driven, but now a demand-driven provider. This vision is connected with Jokowi-Kalla Nawacita program to create a competitive nation in the global era. Competition is a social fact that must be faced. Therefore the curriculum will design a process to be the innovators and entrepreneurs.To get this goal, K-13 implements the character education. This aims at creating the innovators and entrepreneurs from an early age (primary school). One part of strengthening it is literacy formations (reading, numeracy, science, ICT, finance, and culture). Thus, science literacy is an integral part of character education. The above outputs are only formed through the innovative process through intra-curricular (blended learning), co-curriculer (hands-on learning) and extra-curricular (personalized learning). Unlike the curriculums before that child cram with the theories dominating the intellectual process, new breakthroughs make natural, social, and cultural phenomena as learning sources. For example, Science in primary schoolsplaceBiology as the platform. And Science places natural, social, and cultural phenomena as a learning field so that students can learn, discover, solve concrete problems, and the prospects of development and application in their everyday lives. Science education not only learns about facts collection or natural phenomena but also methods and scientific attitudes. In turn, Science will form the science literacy. Science literacy have critical, creative, logical, and initiative competences in responding to the issues of culture, science and technology. This is linked with science nature which includes hands-on and minds-on. To sustain the effectiveness of science learning, K-13 opens a new way of viewing a contextual learning model in which facts or natural phenomena are drawn closer to the child's learning environment to be studied and analyzed scientifically. Thus, the topic of elementary science discussion is the practical and contextual things that students encounter. This research is about to contextualize Science in primary schools at Manggarai, NTT, by placing local wisdom as a learning source and media to form the science literacy. Explicitly, this study discovers the concept of science and mathematics in Mbaru Niang. Mbaru Niang is a forgotten potentials of the centralistic-theoretical mainstream curriculum so far. In fact, the traditional Manggarai community stores and inherits much of the science-mathematical indigenous sciences. In the traditional house structures are full of science and mathematics knowledge. Every details have style, sound and mathematical symbols. Learning this, students are able to collaborate and synergize the content and learning resources in student learning activities. This is constructivist contextual learning that will be applied in meaningful learning. Meaningful learning allows students to learn by doing. Students then connect topics to the context, and science literacy is constructed from their factual experiences. The research location will be conducted in Manggarai through observation, interview, and literature study.Keywords: indigenous science, Mbaru Niang, science literacy, science
Procedia PDF Downloads 20910940 The Acceptance of E-Assessment Considering Security Perspective: Work in Progress
Authors: Kavitha Thamadharan, Nurazean Maarop
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The implementation of e-assessment as tool to support the process of teaching and learning in university has become a popular technological means in universities. E-Assessment provides many advantages to the users especially the flexibility in teaching and learning. The e-assessment system has the capability to improve its quality of delivering education. However, there still exists a drawback in terms of security which limits the user acceptance of the online learning system. Even though there are studies providing solutions for identified security threats in e-learning usage, there is no particular model which addresses the factors that influences the acceptance of e-assessment system by lecturers from security perspective. The aim of this study is to explore security aspects of e-assessment in regard to the acceptance of the technology. As a result a conceptual model of secure acceptance of e-assessment is proposed. Both human and security factors are considered in formulation of this conceptual model. In order to increase understanding of critical issues related to the subject of this study, interpretive approach involving convergent mixed method research method is proposed to be used to execute the research. This study will be useful in providing more insightful understanding regarding the factors that influence the user acceptance of e-assessment system from security perspective.Keywords: secure technology acceptance, e-assessment security, e-assessment, education technology
Procedia PDF Downloads 45910939 Using Information and Communication Technologies in Teaching Translation: Students of English as a Case Study
Authors: Guessabi Fatiha
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Nowadays, there is no sphere of human life that does not use Information and Communication Technologies (ICTs) in practice. This type of development grew widely in the last years of the 20th century and impacted many fields such as education, health, financing, job markets, communication, governments, industrial productivity, etc. Recently, in higher education, the use of ICTs has been essential and significant during the Covid19 pandemic. Thanks to technology, although the universities in Algeria were locked down during the period of covid19, learning was easily continued, and students were collaborating, communicating, socializing, and learning at a distance. Therefore, ICT tools are required in translation courses to enhance and improve translation teaching. This research explores the use of ICT in teaching and learning translation. The research comes along with a theoretical framework; the literature review is produced to highlight some essential ICT concepts and translation teaching. In order to achieve the study objective, a questionnaire is distributed to the third-year English LMD students at Tahri Mohamed University, and an interview is addressed to the translation teacher. The results and discussion obtained from this investigation confirmed the hypothesis and revealed that the use of ICT is essential in translation courses and it improves translation teaching. Hence, by using ICT in the classroom, the students become more active, and the teachers of translation become knowledge facilitators and leaders.Keywords: COVID19, ICT, learning, students, teaching, TMU, translation
Procedia PDF Downloads 12810938 Deep Learning Based Polarimetric SAR Images Restoration
Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli
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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry
Procedia PDF Downloads 9110937 Exploring 3-D Virtual Art Spaces: Engaging Student Communities Through Feedback and Exhibitions
Authors: Zena Tredinnick-Kirby, Anna Divinsky, Brendan Berthold, Nicole Cingolani
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Faculty members from The Pennsylvania State University, Zena Tredinnick-Kirby, Ph.D., and Anna Divinsky are at the forefront of an innovative educational approach to improve access in asynchronous online art courses. Their pioneering work weaves virtual reality (VR) technologies to construct a more equitable educational experience for students by transforming their learning and engagement. The significance of their study lies in the need to bridge the digital divide in online art courses, making them more inclusive and interactive for all distance learners. In an era where conventional classroom settings are no longer the sole means of instruction, Tredinnick-Kirby and Divinsky harness the power of instructional technologies to break down geographical barriers by incorporating an interactive VR experience that facilitates community building within an online environment transcending physical constraints. The methodology adopted by Tredinnick-Kirby, and Divinsky is centered around integrating 3D virtual spaces into their art courses. Spatial.io, a virtual world platform, enables students to develop digital avatars and engage in virtual art museums through a free browser-based program or an Oculus headset, where they can interact with other visitors and critique each other’s artwork. The goal is not only to provide students with an engaging and immersive learning experience but also to nourish them with a more profound understanding of the language of art criticism and technology. Furthermore, the study aims to cultivate critical thinking skills among students and foster a collaborative spirit. By leveraging cutting-edge VR technology, students are encouraged to explore the possibilities of their field, experimenting with innovative tools and techniques. This approach not only enriches their learning experience but also prepares them for a dynamic and ever-evolving art landscape in technology and education. One of the fundamental objectives of Tredinnick-Kirby and Divinsky is to remodel how feedback is derived through peer-to-peer art critique. Through the inclusion of 3D virtual spaces into the curriculum, students now have the opportunity to install their final artwork in a virtual gallery space and incorporate peer feedback, enabling students to exhibit their work opening the doors to a collaborative and interactive process. Students can provide constructive suggestions, engage in discussions, and integrate peer commentary into developing their ideas and praxis. This approach not only accelerates the learning process but also promotes a sense of community and growth. In summary, the study conducted by the Penn State faculty members Zena Tredinnick-Kirby, and Anna Divinsky represents innovative use of technology in their courses. By incorporating 3D virtual spaces, they are enriching the learners' experience. Through this inventive pedagogical technique, they nurture critical thinking, collaboration, and the practical application of cutting-edge technology in art. This research holds great promise for the future of online art education, transforming it into a dynamic, inclusive, and interactive experience that transcends the confines of distance learning.Keywords: Art, community building, distance learning, virtual reality
Procedia PDF Downloads 7110936 Assessing Remote and Hybrid Education Amidst the COVID-19 Pandemic: Insights and Innovations from Secondary School Educators
Authors: Azzeddine Atibi, Khadija El Kababi, Salim Ahmed, Mohamed Radid
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The principal objective of this study is to undertake a comprehensive comparative analysis of distance learning and blended learning modalities, with a particular emphasis on evaluating their effectiveness during the confinement period mandated by the COVID-19 pandemic. This investigation is rooted in the firsthand experiences of educators at the high school and secondary levels within both private and public educational institutions. To acquire the requisite data, we meticulously designed and distributed a survey to these educators, soliciting detailed narratives of their professional experiences throughout this challenging period. The survey aims to elucidate the specific difficulties encountered by teachers, as well as to highlight the innovative pedagogical strategies they devised in response to these challenges. By synthesizing the insights garnered from this survey, our goal is to foster an exchange of experiences among educators and to generate informed recommendations that will inform future educational reforms. Ultimately, this study aspires to contribute to the ongoing discourse on optimizing educational practices in the face of unprecedented disruptions.Keywords: distance learning, blended learning, covid 19, secondary/ high school, teachingperformance, evaluation
Procedia PDF Downloads 3210935 Multimodal Convolutional Neural Network for Musical Instrument Recognition
Authors: Yagya Raj Pandeya, Joonwhoan Lee
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The dynamic behavior of music and video makes it difficult to evaluate musical instrument playing in a video by computer system. Any television or film video clip with music information are rich sources for analyzing musical instruments using modern machine learning technologies. In this research, we integrate the audio and video information sources using convolutional neural network (CNN) and pass network learned features through recurrent neural network (RNN) to preserve the dynamic behaviors of audio and video. We use different pre-trained CNN for music and video feature extraction and then fine tune each model. The music network use 2D convolutional network and video network use 3D convolution (C3D). Finally, we concatenate each music and video feature by preserving the time varying features. The long short term memory (LSTM) network is used for long-term dynamic feature characterization and then use late fusion with generalized mean. The proposed network performs better performance to recognize the musical instrument using audio-video multimodal neural network.Keywords: multimodal, 3D convolution, music-video feature extraction, generalized mean
Procedia PDF Downloads 21510934 Rapid Processing Techniques Applied to Sintered Nickel Battery Technologies for Utility Scale Applications
Authors: J. D. Marinaccio, I. Mabbett, C. Glover, D. Worsley
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Through use of novel modern/rapid processing techniques such as screen printing and Near-Infrared (NIR) radiative curing, process time for the sintering of sintered nickel plaques, applicable to alkaline nickel battery chemistries, has been drastically reduced from in excess of 200 minutes with conventional convection methods to below 2 minutes using NIR curing methods. Steps have also been taken to remove the need for forming gas as a reducing agent by implementing carbon as an in-situ reducing agent, within the ink formulation.Keywords: batteries, energy, iron, nickel, storage
Procedia PDF Downloads 44010933 Upgrading Engineering Education in Häme University of Applied Sciences: Towards Teacher Teams, Flexible Processes and Versatile Company Collaboration
Authors: Jussi Horelli, Salla Niittymäki
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In this acceleratingly developing world, it will be crucial for our students to not only to adapt to continuous change, but to be the driving force of it. This raises the question of how can the educational processes motivate and encourage the students to learn the perhaps most important skill there for their further work career: the ability to learn and absorb more by themselves. In engineering education, the learning contents and methods have traditionally been very substance oriented and teacher-centered. In Häme University of Applied Sciences (HAMK), the pedagogical model has been completely renewed during the past few years. Terms like phenomenon or skills-based learning and collaborative teaching are things which have not very often been related to engineering education, but are now the foundation of HAMK’s pedagogical model in all disciplines, even in engineering studies. In this paper, a new flexible way of executing engineering studies will be introduced. The paper will summarize three years’ experiences and observations of a process where traditional teacher-centric mechanical engineering teaching was converted into a model where teachers work collaboratively in teams supporting the students’ learning processes.Keywords: team teaching, collaborative learning, engineering education, new pedagogy
Procedia PDF Downloads 22110932 Age-Based Interface Design for Children’s CAPT Systems
Authors: Saratu Yusuf Ilu, Mumtaz B. Mustafa, Siti Salwah Salim, Mehdi Malekzadeh
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Children today use computer based application in various activities especially for learning and education. Many of these tools and application such as the Computer Aided Pronunciation Training (CAPT) system enable children to explore and experience them with little supervision from the adults. In order for these tools and application to have maximum effect on the children’s learning and education, it must be attractive to the children to use them. This could be achieved with the proper user interface (UI) design. As children grow, so do their ability, taste and preferences. They interact differently with these applications as they grow older. This study reviews several articles on how age factor influences the UI design. The review focuses on age related abilities such as cognitive, literacy, concentration and feedback requirement. We have also evaluated few of existing CAPT systems and determine the influence of age-based factors on the interface design.Keywords: children, age-based interaction, learning application, age-based capability
Procedia PDF Downloads 42410931 A Chronological and Comparative Examination of Traditional American Post-Secondary Institutions of Higher Learning Delivery of Instruction for College Students with Autism Spectrum Disorders
Authors: Shannon Melideo
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Post-secondary schools that provide specialized instruction for college students with special needs have been in existence for some time in the United States of America. Whether students experience learning disabilities, visual impairments, physical limitations, Autism Spectrum Disorders or any other issue that impacts their learning are able to attend universities that intentionally cater to their needs. While this selection of post-secondary education may be preferred by some students, other have sought a different experience. Over the last ten years, the number of students with Autism Spectrum Disorders (ASD) attending traditional universities in the United States of America has increased significantly. Students with ASD tend to select smaller, private institutions that appear to offer more personal attention and services. This paper will examine how traditional American universities are preparing for this relatively new group of students in their college classrooms. This paper will provide a brief historical timeline of access to university instruction for students with Autism Spectrum Disorders, and how and if students with ASD are received in colleges around the globe, and best research supported practices for success.Keywords: autism spectrum disorders, access to learning, university instruction, accommodations
Procedia PDF Downloads 17410930 Knowledge Reactor: A Contextual Computing Work in Progress for Eldercare
Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams
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The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.Keywords: ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph
Procedia PDF Downloads 17510929 Actionable Personalised Learning Strategies to Improve a Growth-Mindset in an Educational Setting Using Artificial Intelligence
Authors: Garry Gorman, Nigel McKelvey, James Connolly
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This study will evaluate a growth mindset intervention with Junior Cycle Coding and Senior Cycle Computer Science students in Ireland, where gamification will be used to incentivise growth mindset behaviour. An artificial intelligence (AI) driven personalised learning system will be developed to present computer programming learning tasks in a manner that is best suited to the individuals’ own learning preferences while incentivising and rewarding growth mindset behaviour of persistence, mastery response to challenge, and challenge seeking. This research endeavours to measure mindset with before and after surveys (conducted nationally) and by recording growth mindset behaviour whilst playing a digital game. This study will harness the capabilities of AI and aims to determine how a personalised learning (PL) experience can impact the mindset of a broad range of students. The focus of this study will be to determine how personalising the learning experience influences female and disadvantaged students' sense of belonging in the computer science classroom when tasks are presented in a manner that is best suited to the individual. Whole Brain Learning will underpin this research and will be used as a framework to guide the research in identifying key areas such as thinking and learning styles, cognitive potential, motivators and fears, and emotional intelligence. This research will be conducted in multiple school types over one academic year. Digital games will be played multiple times over this period, and the data gathered will be used to inform the AI algorithm. The three data sets are described as follows: (i) Before and after survey data to determine the grit scores and mindsets of the participants, (ii) The Growth Mind-Set data from the game, which will measure multiple growth mindset behaviours, such as persistence, response to challenge and use of strategy, (iii) The AI data to guide PL. This study will highlight the effectiveness of an AI-driven personalised learning experience. The data will position AI within the Irish educational landscape, with a specific focus on the teaching of CS. These findings will benefit coding and computer science teachers by providing a clear pedagogy for the effective delivery of personalised learning strategies for computer science education. This pedagogy will help prevent students from developing a fixed mindset while helping pupils to exhibit persistence of effort, use of strategy, and a mastery response to challenges.Keywords: computer science education, artificial intelligence, growth mindset, pedagogy
Procedia PDF Downloads 8810928 Morphological Analysis of Manipuri Language: Wahei-Neinarol
Authors: Y. Bablu Singh, B. S. Purkayashtha, Chungkham Yashawanta Singh
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Morphological analysis forms the basic foundation in NLP applications including syntax parsing Machine Translation (MT), Information Retrieval (IR) and automatic indexing in all languages. It is the field of the linguistics; it can provide valuable information for computer based linguistics task such as lemmatization and studies of internal structure of the words. Computational Morphology is the application of morphological rules in the field of computational linguistics, and it is the emerging area in AI, which studies the structure of words, which are formed by combining smaller units of linguistics information, called morphemes: the building blocks of words. Morphological analysis provides about semantic and syntactic role in a sentence. It analyzes the Manipuri word forms and produces several grammatical information associated with the words. The Morphological Analyzer for Manipuri has been tested on 3500 Manipuri words in Shakti Standard format (SSF) using Meitei Mayek as source; thereby an accuracy of 80% has been obtained on a manual check.Keywords: morphological analysis, machine translation, computational morphology, information retrieval, SSF
Procedia PDF Downloads 32610927 Learning to Play in South Africa
Authors: Thelma Mort
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Currently, in South African schools, under the fast-paced and content-heavy CAPS curriculum, the notion of play is being lost in the foundation phase. Even in Grade R, aimed at improving the quality of education, there is a focus on mathematical literacy, language, and life skills (DoE, 2001). This is largely due to the dichotomizing of play and learning. And although the play is meant to be the primary means of achieving these skills, it somehow loses its playfulness in the face of early academic pressure. Student teachers similarly have not been trained to use play in the early years of schooling. This action research study shares findings from the “Learn to Play” intervention in teacher training at one university in which student teachers were given substantial training in types of play, the ways they could use and promote play, and the changing roles of teachers in play-based learning. Using observation focus group interviews, reflections, student teacher engagement in learning communities, and Theories of Change, the study measures the changes made by the intervention in student teachers’ approaches and attitudes to play in the classroom. Key findings were that the student teachers learned new skills, had better relationships with pupils, and became more confident in their foundation phase settings.Keywords: action research, foundation phase, South Africa, student teacher training
Procedia PDF Downloads 18010926 Iranian EFL Learners' Attitudes towards Computer Assisted Language Learning (CALL)
Authors: Rose Shayeghi, Pejman Hosseiniun, Ghasem Ghorbanirostam
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The present study was conducted to investigate the Iranian EFL learners’ attitudes toward the use of computer technology in language classes as a method of improving English learning. To this end, 120 male and female Iranian learners participated in the study. Instrumentation included a 20-item questionnaire. The analysis of the data revealed that the majority of learners had a positive attitude towards the application of CALL in language classes. Moreover, independent samples t-tests indicated that male participants had a significantly more positive attitude compared with that of the female participants. Finally, the results obtained through ANOVA revealed that the youngest age group had a significantly more positive attitude toward the use of technology in language classes compared to the other age groups.Keywords: EFL learners, Iranian learners, CALL, language learning
Procedia PDF Downloads 44310925 Spatiotemporal Neural Network for Video-Based Pose Estimation
Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan
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Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series
Procedia PDF Downloads 14810924 Blended Learning in a Mathematics Classroom: A Focus in Khan Academy
Authors: Sibawu Witness Siyepu
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This study explores the effects of instructional design using blended learning in the learning of radian measures among Engineering students. Blended learning is an education programme that combines online digital media with traditional classroom methods. It requires the physical presence of both lecturer and student in a mathematics computer laboratory. Blended learning provides element of class control over time, place, path or pace. The focus was on the use of Khan Academy to supplement traditional classroom interactions. Khan Academy is a non-profit educational organisation created by educator Salman Khan with a goal of creating an accessible place for students to learn through watching videos in a computer assisted computer. The researcher who is an also lecturer in mathematics support programme collected data through instructing students to watch Khan Academy videos on radian measures, and by supplying students with traditional classroom activities. Classroom activities entails radian measure activities extracted from the Internet. Students were given an opportunity to engage in class discussions, social interactions and collaborations. These activities necessitated students to write formative assessments tests. The purpose of formative assessments tests was to find out about the students’ understanding of radian measures, including errors and misconceptions they displayed in their calculations. Identification of errors and misconceptions serve as pointers of students’ weaknesses and strengths in their learning of radian measures. At the end of data collection, semi-structure interviews were administered to a purposefully sampled group to explore their perceptions and feedback regarding the use of blended learning approach in teaching and learning of radian measures. The study employed Algebraic Insight Framework to analyse data collected. Algebraic Insight Framework is a subset of symbol sense which allows a student to correctly enter expressions into a computer assisted systems efficiently. This study offers students opportunities to enter topics and subtopics on radian measures into a computer through the lens of Khan Academy. Khan academy demonstrates procedures followed to reach solutions of mathematical problems. The researcher performed the task of explaining mathematical concepts and facilitated the process of reinvention of rules and formulae in the learning of radian measures. Lastly, activities that reinforce students’ understanding of radian were distributed. Results showed that this study enthused the students in their learning of radian measures. Learning through videos prompted the students to ask questions which brought about clarity and sense making to the classroom discussions. Data revealed that sense making through reinvention of rules and formulae assisted the students in enhancing their learning of radian measures. This study recommends the use of Khan Academy in blended learning to be introduced as a socialisation programme to all first year students. This will prepare students that are computer illiterate to become conversant with the use of Khan Academy as a powerful tool in the learning of mathematics. Khan Academy is a key technological tool that is pivotal for the development of students’ autonomy in the learning of mathematics and that promotes collaboration with lecturers and peers.Keywords: algebraic insight framework, blended learning, Khan Academy, radian measures
Procedia PDF Downloads 31010923 An Efficient Motion Recognition System Based on LMA Technique and a Discrete Hidden Markov Model
Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier
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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.Keywords: human motion recognition, motion representation, Laban Movement Analysis, Discrete Hidden Markov Model
Procedia PDF Downloads 20710922 Exploring the Potential of Chatbots in Higher Education: A Preliminary Study
Authors: S. Studente, S. Ellis, S. F. Garivaldis
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We report upon a study introducing a chatbot to develop learning communities at a London University, with a largely international student base. The focus of the chatbot was twofold; to ease the transition for students into their first year of university study, and to increase study engagement. Four learning communities were created using the chatbot; level 3 foundation, level 4 undergraduate, level 6 undergraduate and level 7 post-graduate. Students and programme leaders were provided with access to the chat bot via mobile app prior to their study induction and throughout the autumn term of 2019. At the end of the term, data were collected via questionnaires and focus groups with students and teaching staff to allow for identification of benefits and challenges. Findings indicated a positive correlation between study engagement and engagement with peers. Students reported that the chatbot enabled them to obtain support and connect to their programme leader. Both staff and students also made recommendation on how engagement could be further enhanced using the bot in terms of; clearly specified purpose, integration with existing university systems, leading by example and connectivity. Extending upon these recommendations, a second pilot study is planned for September 2020, for which the focus will be upon improving attendance rates, student satisfaction and module pass rates.Keywords: chatbot, e-learning, learning communities, student engagement
Procedia PDF Downloads 12410921 iSEA: A Mobile Based Learning Application for History and Culture Knowledge Enhancement for the ASEAN Region
Authors: Maria Visitacion N. Gumabay, Byron Joseph A. Hallar, Annjeannette Alain D. Galang
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This study was intended to provide a more efficient and convenient way for mobile users to enhance their knowledge about ASEAN countries. The researchers evaluated the utility of the developed crossword puzzle application and assessed the general usability of its user interface for its intended purpose and audience of users. The descriptive qualitative research method for the research design and the Mobile-D methodology was employed for the development of the software application output. With a generally favorable reception from its users, the researchers concluded that the iSEA Mobile Based Learning Application can be considered ready for general deployment and use. It was also concluded that additional studies can also be done to make a more complete assessment of the knowledge gained by its users before and after using the application.Keywords: mobile learning, eLearning, crossword, ASEAN, iSEA
Procedia PDF Downloads 31310920 Operating System Based Virtualization Models in Cloud Computing
Authors: Dev Ras Pandey, Bharat Mishra, S. K. Tripathi
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Cloud computing is ready to transform the structure of businesses and learning through supplying the real-time applications and provide an immediate help for small to medium sized businesses. The ability to run a hypervisor inside a virtual machine is important feature of virtualization and it is called nested virtualization. In today’s growing field of information technology, many of the virtualization models are available, that provide a convenient approach to implement, but decision for a single model selection is difficult. This paper explains the applications of operating system based virtualization in cloud computing with an appropriate/suitable model with their different specifications and user’s requirements. In the present paper, most popular models are selected, and the selection was based on container and hypervisor based virtualization. Selected models were compared with a wide range of user’s requirements as number of CPUs, memory size, nested virtualization supports, live migration and commercial supports, etc. and we identified a most suitable model of virtualization.Keywords: virtualization, OS based virtualization, container based virtualization, hypervisor based virtualization
Procedia PDF Downloads 32910919 A Comparative Study of Twin Delayed Deep Deterministic Policy Gradient and Soft Actor-Critic Algorithms for Robot Exploration and Navigation in Unseen Environments
Authors: Romisaa Ali
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This paper presents a comparison between twin-delayed Deep Deterministic Policy Gradient (TD3) and Soft Actor-Critic (SAC) reinforcement learning algorithms in the context of training robust navigation policies for Jackal robots. By leveraging an open-source framework and custom motion control environments, the study evaluates the performance, robustness, and transferability of the trained policies across a range of scenarios. The primary focus of the experiments is to assess the training process, the adaptability of the algorithms, and the robot’s ability to navigate in previously unseen environments. Moreover, the paper examines the influence of varying environmental complexities on the learning process and the generalization capabilities of the resulting policies. The results of this study aim to inform and guide the development of more efficient and practical reinforcement learning-based navigation policies for Jackal robots in real-world scenarios.Keywords: Jackal robot environments, reinforcement learning, TD3, SAC, robust navigation, transferability, custom environment
Procedia PDF Downloads 10210918 Escape Room Pedagogy: Using Gamification to Promote Engagement, Encourage Connections, and Facilitate Skill Development in Undergraduate Students
Authors: Scott McCutcheon, Karen Schreder
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Higher education is facing a new reality. Student connection with coursework, instructor, and peers competes with online gaming, screen time, and instant gratification. Pedagogical methods that align student connection and critical thinking in a content-rich environment are important in supporting student learning, a sense of community, and emotional health. This mixed methods study focuses on exploring how the use of educational escape rooms (EERs) can support student learning and learning retention while fostering engagement with each other, the instructor, and the coursework. EERs are content-specific, cooperative, team-based learning activities designed to be completed within a short segment of a typical class. Data for the study was collected over three semesters and includes results from the implementation of EERs in science-based and liberal studies courses taught by different instructors. Twenty-seven students were surveyed regarding their learning experiences with this pedagogy, and interviews with four student volunteers were conducted to add depth to the survey data. A key finding from this research indicates that students felt more connected to each other and the course content after participating in the escape room activity. Additional findings point to increased engagement and comprehension of the class material. Data indicates that the use of an EER pedagogy supports student engagement, well-being, subject comprehension, and student-student and student-instructor connection.Keywords: gamification, innovative pedagogy, student engagement, student emotional well being
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