Search results for: multimedia learning tools

Authors: Jamie David Hopkin

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This study aims to contribute uniquely to help colleges and community learning and development institutes to help aid progression within ESOL learning. The study investigates the barriers that migrant and displaced learners face accessing further education in Scotland. The study also includes a set of recommendations both for colleges and CLD institutes to help ESOL learners in their journey to further education. The research found that integration into Scottish society is one of the biggest motivators for ESOL students to learn English. It also found that the place of gender and “gender roles” contribute to the barriers that learners face in terms of progression and learning. The study also reviews all literature related to ESOL learning in Scotland and found that there are only two main policies that support ESOL learning, and both are slightly outdated in terms of supporting progression. This study aims to help bridge the gap in knowledge around the progression from informal learning to formal education. The recommendations that are made in this study are aimed to help institutes and learners on their journey to a positive destination. The main beneficiaries of this research are current and future ESOL learners in Scotland, ESOL institutes, and TESOL professionals.

Keywords: community learning and development, English for speakers of other languages, further education, higher education TESOL, teaching English as a second language

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Authors: Jong Boonpracha

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This paper studied the application of the design of local wisdom learning for providing creative activity for juveniles with exhibit media. The Suan-oui Youth Center has the objectives to design and develop exhibit media that encourage participation and learning of youths on local wisdom of Ratanakosin Island. The research was conducted in three stages: 1) to study the principle of local wisdom learning of cultural heritage at Ratanakosin Island 2) to study exhibit media that encouraged participation and creative activities of youth on local wisdom learning, and 3) to design a youth center that provide media exhibition for local wisdom learning. The research revealed the following: 34.6 percent of respondents wanted to apply local living wisdom in their career and for hobby. At least two kinds of exhibit media effectively provided creative activities for youths. A multi-purpose area, for example, with still pictures, visual symbols, and simulations would increase the level of youths’ interaction and participation.

Keywords: exhibit media, local wisdom, youth center, design

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Authors: Zahra Alqahtani

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The use of e-learning technologies is gaining momentum in all educational institutions of the world, including Saudi universities. In the e-learning context, there is a growing need and concern among Saudi universities to improve and enhance quality assurance for e-learning systems. Practicing quality assurance activities and applying quality standards in e-learning in Saudi universities is thought to reduce the negative viewpoints of some stakeholders and ensure stakeholders’ satisfaction and needs. As a contribution to improving the quality of e-learning method in Saudi universities, the main purpose of this study is to explore and investigate strategies for the development of quality assurance in e-learning in one university in Saudi Arabia, which is considered a good reference university using the best and ongoing practices in e-learning systems among Saudi universities. In order to ensure the quality of its e-learning methods, Saudi university has adopted Quality Matters Standards as a controlling guide for the quality of its blended and full e-course electronic courses. Furthermore, quality assurance can be further improved if a variety of perspectives are taken into consideration from the comprehensive viewpoints of faculty members, administrative staff, and students.This qualitative research involved the use of different types of interviews, as well as documents that contain data related to e-learning methods in the Saudi university environment. This exploratory case study was undertaken, from the perspectives of various participants, to understand the phenomenon of quality assurance using an inductive technique.The results revealed six main supportive factors that assist in ensuring the quality of e-learning in the Saudi university environment. Essentially, these factors are institutional support, faculty member support, evaluation of faculty, quality of e-course design, technology support, and student support, which together have a remarkable positive effect on quality, forming intrinsic columns connected by bricks leading to quality e-learning. Quality Matters standards are considered to have a strong impact on improving faculty members' skills and on the development of high-quality blended and full e-courses.

Keywords: E-learning, quality assurance, quality matters standards, KKU-supportive factors

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Authors: Aung Aung Kyi, Khin Khin Aye

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The mode of teaching and learning has been changed dramatically due to the Covid-19 pandemic that made schools close and students may have been away from the campus. However, many schools all over the countries are helping students to facilitate e-learning through online teaching and learning platform. Regarding this, Sarasas bilingual school in Bangkok conducted the high school students’ satisfaction survey since it is important for every school to improve its quality of education that must meet the students' need. For the good of the school's reputation, the purpose of the study is to examine the level of satisfaction that enhances the best services in the future. This study applied random sampling techniques and the data were collected using a self-administered survey. Descriptive analysis and independent sample t-tests were used to measure the importance of satisfaction components. The results showed G-11 (A) students were extremely satisfied with “Accessibility of course resources and materials through online platform” and “Ontime homework submission” while G-11 (B) students were extremely satisfied with “Teacher assisted with guiding my learning activities” and “Course teacher for this online course interacted with me in a timely fashion”. Additionally, they were also satisfied with a clear understanding of the teacher’s introduction during online learning. A significant difference in the satisfaction was observed between G-11 (A) and G-11 (B) students in terms of “A clear understanding on introduction was given by the teacher at the beginning of this online course”(P=0.03), “Teacher assisted with guiding my learning activities” (P=0.003), and “Comfortable surrounding during online learning” (P=0.02). With regard to gender, it has been seen that female high school students were extremely satisfied with the amount of course interaction with their teacher and her guidance with learning activities during online learning. By understanding the survey assessment, schools can improve their quality of education through the best digital educational platform that helps satisfy their students in the future.

Keywords: Bangkok high school students., covid-19 pandemic, online learning platform, satisfaction

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Authors: Mya Achike

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Background and Significance: Perinatal mental illness covers a wide range of conditions and has a huge influence on maternal-child health. Issues and challenges with perinatal mental health have been associated with poor pregnancy, birth, and postpartum outcomes. It is estimated that one out of five new and expectant mothers experience some degree of perinatal mental illness, which makes this a hugely significant health outcome. Certain factors increase the maternal risk for mental illness. Challenges related to poverty, migration, extreme stress, exposure to violence, emergency and conflict situations, natural disasters, and pandemics can exacerbate mental health disorders. It is widely expected that perinatal mental health is being negatively affected during the present COVID-19 pandemic. Methods: A review of studies that reported a measurement tool to assess perinatal mental health outcomes during the COVID-19 pandemic was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. PubMed, CINAHL, and Google Scholar were used to search for peer-reviewed studies published after late 2019, in accordance with the emergence of the virus. The search resulted in the inclusion of ten studies. Approach to measure health outcome: The main approach to measure perinatal mental illness is the use of self-administered, validated questionnaires, usually in the clinical setting. Summary: Widespread use of these tools has afforded the clinical and research communities the ability to identify and support women who may be suffering from mental illness disorders during a pandemic. More research is needed to validate tools in other vulnerable, perinatal populations.

Keywords: mental health during covid, perinatal mental health, perinatal mental health measurement tools, perinatal mental health tools

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Authors: K. Myška, L. Pilařová

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The article deals with possibilities of using cheap mobile devices with the combination of free or open source software tools as an alternative to professional hardware and software equipment. Especially in social work, it is important to find cheap yet functional solution that can compete with complex but expensive solutions for digitizing paper materials. Our research was focused on the analysis of cheap and affordable solutions for digitizing the most frequently used paper materials that are being commonly used by terrain workers in social work. We used comparative analysis as a research method. Social workers need to process data from paper forms quite often. It is still more affordable, time and cost-effective to use paper forms to get feedback in many cases. Collecting data from paper quizzes and questionnaires can be done with the help of professional scanners and software. These technologies are very powerful and have advanced options for digitizing and processing digitized data, but are also very expensive. According to results of our study, the combination of open source software and mobile phone or cheap scanner can be considered as a cost-effective alternative to professional equipment.

Keywords: digitalization, e-learning, mobile devices, questionnaire

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Authors: Daniel Motlhanka, Neo Kerebotswe

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The strong and long history of use of medicinal plants in Botswana to address existing and emerging health threats provides undebatable evidence for their potential as innovative therapeutic tools. The prevalence of emerging health threats, such as COVID-19 and hard-to-treat non-communicable diseases, warrants the scientific community to revisit and exploit ethnopharmacology for its potential as a source of therapeutic tools. Many studies conducted on bioactivity-guided bioassays of ethnobotanical resources have proved a number of health beneficial properties of these plants, such as free radical scavenging, anti-inflammatory, antimicrobial and, most importantly, the capability of medicinal plants to alleviate oxidative stress. In this work, a number of medicinal plants used in Botswana traditional medicine were investigated for both their free radical scavenging capability and total phenolic contents using the Free Radical Scavenging Power (FRSP) and Folin Ciocalteau (FC) method. At 100 micrograms/ml all the studied plants expressed above 90% Scavenging power and expressed total phenolic contents between 5000- 8890 mg/L.GAE. These plants are promising tools for engineering active therapeutic tools against life-threatening diseases of oxidative stress origin.

Keywords: oxidative stress, non-communicable diseases, total phenolics, ethnobotanicals

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Authors: Andre Bechuke

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The quality of every learning programme in Higher Education (HE) is dependent on the planning, design, and development of the curriculum decisions. These curriculum development decisions are highly influenced by the knowledge of the end-user, who are not always just the students. When curriculum experts plan, design and develop learning programmes, they always have the end-users in mind throughout the process. Without proper knowledge of the end-user(s), the design and development of a learning programme might be flawed. Curriculum experts often struggle to determine who the real end-user is. As such, it is even more challenging to establish what needs to be known about the end user that should inform the plan, design, and development of a learning programme. This research sought suggest approaches to guide curriculum experts to identify the end-user(s), taking into consideration the pressure and influence other agencies and structures or stakeholders (industry, students, government, universities context, lecturers, international communities, professional regulatory bodies) have on the design of a learning programme and the graduates of the programmes. Considering the influence of these stakeholders, which is also very important, the task of deciding who the real end-user of the learning programme becomes very challenging. This study makes use of criteria 1 and 18 of the Council on Higher Education criteria for programme accreditation to guide the process of identifying the end-users when developing a learning programme. Criterion 1 suggests that designers must ensure that the programme is consonant with the institution’s mission, forms part of institutional planning and resource allocation, meets national requirements and the needs of students and other stakeholders, and is intellectually credible. According to criterion 18, in designing a learning programme, steps must be taken to enhance the employability of students and alleviate shortages of expertise in relevant fields. In conclusion, there is hardly ever one group of end-users to be considered for developing a learning programme, and the notion that students are the end-users is not true, especially when the graduates are unable to use the qualification for employment.

Keywords: council on higher education, curriculum design and development, higher education, learning programme

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Authors: Hoda A. Abdel Hafez

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Mining big data represents a big challenge nowadays. Many types of research are concerned with mining massive amounts of data and big data streams. Mining big data faces a lot of challenges including scalability, speed, heterogeneity, accuracy, provenance and privacy. In telecommunication industry, mining big data is like a mining for gold; it represents a big opportunity and maximizing the revenue streams in this industry. This paper discusses the characteristics of big data (volume, variety, velocity and veracity), data mining techniques and tools for handling very large data sets, mining big data in telecommunication and the benefits and opportunities gained from them.

Keywords: mining big data, big data, machine learning, telecommunication

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Authors: Bahareh Golchin, Nooshin Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: Amy Hodges, Deanna Rasmussen, Sherry Ward

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This paper examines the use of ePortfolios in a two-course sequence for ESL (English as a Second Language) students at an international branch campus in Doha, Qatar. ePortfolios support the transfer of language learning, but few have examined the sustainability of that transfer across an ESL program. Drawing upon surveys and interviews with students, we analyze three case studies that complicate previous research on metacognition, language learning, and ePortfolios. Our findings have implications for those involved in ESL programs and assessment of student writing.

Keywords: TESOL, electronic portfolios, assessment, technology

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Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

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Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

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Authors: Junior George Martin

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The purpose of this study was to explore college instructors’ integration of technology in their content area curriculum. The instructors indicated that they were in need of additional training to successfully integrate technology in their subject areas. The findings point to the implementation of a proposed the Technological, Pedagogical, and Content Knowledge (TPACK) model professional development workshop to satisfactorily address the weaknesses of the instructors in technology integration. The professional development workshop is proposed as a rational solution to adequately address the instructors’ inability to the successful integration of technology in their subject area in an effort to improve their pedagogy. The intense workshop would last for 5 days and will be designed to provide instructors with training in areas such as a use of technology applications and tools, and using modern methodologies to improve technology integration. Exposing the instructors to the specific areas identified will address the weaknesses they demonstrated during the study. Professional development is deemed the most appropriate intervention based on the opportunities it provides the instructors to access hands-on training to overcome their weaknesses. The purpose of the TPACK professional development workshop will be to improve the competence of the instructors so that they are adequately prepared to integrate technology successfully in their curricula. At the end of the period training, the instructors are expected to adopt strategies that will have a positive impact on the learning experiences of the students.

Keywords: higher education, modern technology tools, professional development, technology integration

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Authors: Yavuz Bağcı, Levent Keskin

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The study was carried out in 2011-2014 period to determine plant-based hand tools uses of plants in Kadınhanı (Konya) and surrounding villages. A total of 153 individuals, who lived or were living during this study in 4 towns, 37 villages and 9 neighborhood were interviewed. It was found that of a total about 20 plants belonging to 10 families in the study area, about 60 hand-made goods were used by peoples for various purposes.

Keywords: ethnobotanic, handmade, Kadınhanı, Konya, plant-human relationship

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Aftab Hameed Memon, Shadab Noor, Muhammad Akram Akhund

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Lean construction is a philosophy adopted in the construction industry to increase the value of a project by reducing waste and improving construction productivity. Lean emphasizes on maximizing the value of a project with less expenditure. Globally, lean philosophy has received wider popularity in construction sector. Lean construction has supported the practitioners with several tools and techniques to implement at various stages of a construction project. Following the global trends, this study has investigated the lean practice in Pakistan. The level of implementation of different lean tools and techniques altogether with potential benefits experienced by its implementation in construction projects of Pakistan is analyzed. To achieve the targets, the opinion was sought by the practitioners involved in handling construction projects representing four stakeholders that are a client, consultant, contractors and material suppliers through a structured questionnaire. A total of 34 completed questionnaires were collected and then statistically analyzed. The findings of the analysis have highlighted that pull approach, work standardization, just in time, increase visualization tools, integrated project delivery method and fail-safe for quality are common lean techniques implemented in the local construction industry. While reduction in waste, client’s satisfaction, improved communication, visual control and proper task management are major benefits of the lean construction application.

Keywords: lean construction, lean tools and techniques, lean benefits, waste reduction, Pakistan

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Authors: Khalil Bachiri, Ali Yahyaouy, Nicoleta Rogovschi

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Improved user experience is a goal of contemporary recommender systems. Recommender systems are starting to incorporate reinforcement learning since it easily satisfies this goal of increasing a user’s reward every session. In this paper, we examine the most effective Reinforcement Learning agent tactics on the Movielens (1M) dataset, balancing precision and a variety of recommendations. The absence of variability in final predictions makes simplistic techniques, although able to optimize ranking quality criteria, worthless for consumers of the recommendation system. Utilizing the stochasticity of Leonard-Ornstein processes, our suggested strategy encourages the agent to investigate its surroundings. Research demonstrates that raising the NDCG (Discounted Cumulative Gain) and HR (HitRate) criterion without lowering the Ornstein-Uhlenbeck process drift coefficient enhances the diversity of suggestions.

Keywords: recommender systems, reinforcement learning, deep learning, DDPG, Leonard-Ornstein process

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Authors: Kaycee Bills

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Action research is a method of inquiry useful in solving social problems in social work. This study seeks to address a significant problem: higher education’s use of traditional instructional methods in social work education. Ineffective techniques, such as lecturing, fail to account for students’ variable learning needs. In contrast to traditional pedagogy, universal design for learning (UDL) is a robust framework that '[improves] and [optimizes] teaching and learning for all people' (CAST, 2018), including students with disabilities. For this project, the research team interviewed the UDL and Accessibility Specialist at their institution for two reasons: (1) to learn how to implement UDL practices in their classrooms, and in turn, (2) to motivate other faculty members at their institution to consider enacting UDL principles. A thematic analysis of the interview’s transcript reveals themes relevant to practicing UDL. Implications for future practice, as well as the researcher’s reflections on the research process, are shared in the discussion section.

Keywords: disabilities, higher education, inclusive education, universal design for learning

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Authors: Victor Ananth Paramananth, Rashid Muniginin, Mahaya Abd Rahman, Siti Afifah Ismail

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Safety issues, scene protection, and appropriate evidence collection must be handled in any bio crime scene. There will be a scene or multi-scene to be cordoned for investigation in any bio-incident or bio crime event. Evidence collection is critical in determining the type of microbial or toxin, its lethality, and its source. As a consequence, from the start of the investigation, a proper sampling method is required. The most significant challenges for the crime scene officer would be deciding where to obtain samples, the best sampling method, and the sample sizes needed. Since there could be evidence in liquid, viscous, or powder shape at a crime scene, crime scene officers have difficulty determining which tools to use for sampling. To maximize sample collection, the appropriate tools for sampling methods are necessary. This study aims to assist the crime scene officer in collecting liquid, viscous, and powder biological samples in sufficient quantity while preserving sample quality. Observational tests on sample collection using liquid, viscous, and powder samples for adequate quantity and sample quality were performed using UV light in this research. The density of the light emission varies upon the method of collection and sample types. The best tools for collecting sufficient amounts of liquid, viscous, and powdered samples can be identified by observing UV light. Instead of active microorganisms, the invisible powder is used to assess sufficient sample collection during a crime scene investigation using various collection tools. The liquid, powdered and viscous samples collected using different tools were analyzed using Fourier transform infrared - attenuate total reflection (FTIR-ATR). FTIR spectroscopy is commonly used for rapid discrimination, classification, and identification of intact microbial cells. The liquid, viscous and powdered samples collected using various tools have been successfully observed using UV light. Furthermore, FTIR-ATR analysis showed that collected samples are sufficient in quantity while preserving their quality.

Keywords: biological sample, crime scene, collection tool, UV light, forensic

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Authors: Eva Laryea, Clement Yeboah Authors

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A pretest-posttest within subjects, experimental design was employed to examine the effects of a computerized basic statistics learning game on achievement and statistics-related anxiety of students enrolled in introductory graduate statistics course. Participants (N = 34) were graduate students in a variety of programs at state-funded research university in the Southeast United States. We analyzed pre-test posttest differences using paired samples t-tests for achievement and for statistics anxiety. The results of the t-test for knowledge in statistics were found to be statistically significant indicating significant mean gains for statistical knowledge as a function of the game-based intervention. Likewise, the results of the t-test for statistics-related anxiety were also statistically significant indicating a decrease in anxiety from pretest to posttest. The implications of the present study are significant for both teachers and students. For teachers, using computer games developed by the researchers can help to create a more dynamic and engaging classroom environment, as well as improve student learning outcomes. For students, playing these educational games can help to develop important skills such as problem solving, critical thinking, and collaboration. Students can develop interest in the subject matter and spend quality time to learn the course as they play the game without knowing that they are even learning the presupposed hard course. The future directions of the present study are promising, as technology continues to advance and become more widely available. Some potential future developments include the integration of virtual and augmented reality into educational games, the use of machine learning and artificial intelligence to create personalized learning experiences, and the development of new and innovative game-based assessment tools. It is also important to consider the ethical implications of computer game-based pedagogy, such as the potential for games to perpetuate harmful stereotypes and biases. As the field continues to evolve, it will be crucial to address these issues and work towards creating inclusive and equitable learning experiences for all students. This study has the potential to revolutionize the way basic statistics graduate students learn and offers exciting opportunities for future development and research. It is an important area of inquiry for educators, researchers, and policymakers, and will continue to be a dynamic and rapidly evolving field for years to come.

Keywords: pretest-posttest within subjects, experimental design, achievement, statistics-related anxiety

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Authors: Snezana Savoska, Blagoj Ristevski, Violeta Manevska, Zlatko Savoski, Ilija Jolevski

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Big data is widely accepted by the pharmaceutical companies as a result of business demands create through legal pressure. Pharmaceutical companies have many legal demands as well as standards’ demands and have to adapt their procedures to the legislation. To manage with these demands, they have to standardize the usage of the current information technology and use the latest software tools. This paper highlights some important aspects of experience with big data projects implementation in a pharmaceutical Macedonian company. These projects made improvements of their business processes by the help of new software tools selected to comply with legal and business demands. They use IT as a strategic tool to obtain competitive advantage on the market and to reengineer the processes towards new Internet economy and quality demands. The company is required to manage vast amounts of structured as well as unstructured data. For these reasons, they implement projects for emerging and appropriate software tools which have to deal with big data concepts accepted in the company.

Keywords: big data, unstructured data, SAP ERP, documentum

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Authors: B. Ramesh Naik, T. Venugopal

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This paper presents a novel approach which improves the high-level semantics of images based on machine learning approach. The contemporary approaches for image retrieval and object recognition includes Fourier transforms, Wavelets, SIFT and HoG. Though these descriptors helpful in a wide range of applications, they exploit zero order statistics, and this lacks high descriptiveness of image features. These descriptors usually take benefit of primitive visual features such as shape, color, texture and spatial locations to describe images. These features do not adequate to describe high-level semantics of the images. This leads to a gap in semantic content caused to unacceptable performance in image retrieval system. A novel method has been proposed referred as discriminative learning which is derived from machine learning approach that efficiently discriminates image features. The analysis and results of proposed approach were validated thoroughly on WANG and Caltech-101 Databases. The results proved that this approach is very competitive in content-based image retrieval.

Keywords: CBIR, discriminative learning, region weight learning, scale invariant feature transforms

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Authors: Pauli P.Y. Lai

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Students with Special Education Needs (SEN) face many challenges in learning. Various challenges include difficulty in handwriting, slow understanding and assimilation, difficulty in paying attention during class, and lack of communication skills. To engage students with Special Education Needs in class with general students, Blackboard Collaborate is used as a teaching and learning tool to deliver a lecture with interactive activities. Blackboard Collaborate provides a good platform to create and enhance active, collaborative and interactive learning experience whereby the SEN students can easily interact with their general peers and the instructor by using the features of drawing on a virtual whiteboard, file sharing, classroom chatter, breakout room, hand-raising feature, polling, etc. By integrating a blended learning approach with Blackboard Collaborate, the students with Special Education Needs could engage in interactive activities with ease in class. Our research aims at exploring and discovering the use of Blackboard Collaborate for inclusive education based on a qualitative design with in-depth interviews. Being served in a general education environment, three university students with different kinds of learning disabilities have participated in our study. All participants agreed that functions provided by Blackboard Collaborate have enhanced their learning experiences and helped them learn better. Their academic performances also showed that SEN students could perform well with the help of technology. This research studies different aspects of using Blackboard Collaborate to create an inclusive learning environment for SEN students.

Keywords: blackboard collaborate, enhanced learning experience, inclusive education, special education needs

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Authors: Blanco T. F., Fernández-López A.

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Nowadays, education, motivated by the new demands of the 21st century, acquires a dimension that converts the skills that new generations may need into a huge and uncertain set of knowledge too broad to be entirety covered. Within this set, and as tools to reach them, we find Learning and Knowledge Technologies (LKT). Thus, in order to prepare students for an everchanging society in which the technological boom involves everything, it is essential to develop digital competence. Nevertheless LKT seems not to have found their place in the educational system. This work is aimed to go a step further in the research of the most appropriate procedures and resources for technological integration in the classroom. The main objective of this exploratory study is to analyze the didactic suitability (epistemic, cognitive, affective, interactional, mediational and ecological) for teaching and learning processes of mathematics with robotics and 3D printing. The analysis carried out is drawn from a STEAM (Science, Technology, Engineering, Art and Mathematics) project that has the Pilgrimage way to Santiago de Compostela as a common thread. The sample is made up of 25 Primary Education students (10 and 11 years old). A qualitative design research methodology has been followed, the sessions have been distributed according to the type of technology applied. Robotics has been focused towards learning two-dimensional mathematical notions while 3D design and printing have been oriented towards three-dimensional concepts. The data collection instruments used are evaluation rubrics, recordings, field notebooks and participant observation. Indicators of didactic suitability proposed by Godino (2013) have been used for the analysis of the data. In general, the results show a medium-high level of didactic suitability. Above these, a high mediational and cognitive suitability stands out, which led to a better understanding of the positions and relationships of three-dimensional bodies in space and the concept of angle. With regard to the other indicators of the didactic suitability, it should be noted that the interactional suitability would require more attention and the affective suitability a deeper study. In conclusion, the research has revealed great expectations around the combination of teaching-learning processes of mathematics and LKT. Although there is still a long way to go in terms of the provision of means and teacher training.

Keywords: 3D printing, didactic suitability, educational design, robotics

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Authors: C. Mayr, J. Periya, A. Kariminezhad

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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

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Authors: Valerie Yocco Rossi

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Objective: The author will share why differentiation is necessary for all classrooms as well as strategies for differentiating content, process, and product. Through learning how to differentiate, teachers will be able to create activities and assessments to meet the abilities, readiness levels, and interests of all learners. Content and Purpose: This work will focus on how to create a learning experience for students that recognizes their different interests, abilities, and readiness levels by differentiating content, process, and product. Likewise, the best learning environments allow for choice. Choice boards allow students to select tasks based on interests. There can be challenging and basic tasks to meet the needs of various abilities. Equally, rubrics allow for personalized and differentiated assessments based on readiness levels and cognitive abilities. The principals of DI help to create a classroom where all students are learning to the best of their abilities. Outcomes: After reviewing the work, readers will be able to (1) identify the benefits of differentiated instruction; (2) convert traditional learning activities to differentiated ones; (3) differentiate, writing-based assessments.

Keywords: differentiation, personalized learning, design, instructional strategies

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Authors: Abenezer Nigussie

Abstract:

Strategic control practice is a critical exercise, as it provides a sturdy influence towards firms or production partners to achieve the full implementation of effective predetermined plans. The importance of strategic control in a company is often measured by observing the relationship between strategic management and organizational performance. The conventional philosophy of strategic control in academia and the industry places significant emphasis on the ability to plan and execute initiatives. In contrast, the same emphasis on strategic management has received less attention in the housing industry. Although the pressures of project performance can often obscure the wider social, economic, and professional context in which strategic management is undertaken, it is these broad contextual areas that make strategic control a vital issue for construction businesses. Rapidly changing social and technological issues are creating an informed environment that will appear very different in the coming decades from what is experienced in today’s companies. Construction project activity is not adequately led by strategic management tools; projects are mostly executed through simple plans and schedules. The issues that this thesis addresses and solves involve the successful accompaniment of the construction project process through these strategic management tools. The second important aspect is an evaluation of project activity, which is mostly done through simple economic and technical valuation. However, during this research, effective strategic management tools are evaluated and suggested for the assessment of project activities. The research introduces a study of the current strategic management practices of construction companies and also presents the concept of strategic management and the areas that companies need to address to compete in the global market. A summary of an industry survey is documented along with the historical research that prompted the investigation of these topics with a focus on the implementation of tools. Strategic management is a concept that concerns making decisions and taking corrective actions to achieve the future goals and objectives of a company. The objective of this paper is to review the practice of strategic management in construction companies. Questionnaires were distributed to major construction companies listed under categories of each project capable of specifying the complete expression of strategic management tools. Findings of the research showed that the majority of development companies practice strategic management tools in the process and implementation of each tool.

Keywords: strategic management, management, analysis, project management

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Authors: Caroline Labib

Abstract:

This paper reports on a qualitative study exploring the approaches teachers used to integrate computers or smart tablets into their program planning. Their aim was to integrate ICT into children’s play, thereby supporting children’s learning and development. Data was collected in preschool settings in Melbourne in 2016. Interviews with teachers, observations of teacher interactions with children and copies of teachers’ planning and observation documents informed the study. The paper looks closely at findings from two early childhood settings and focuses on exploring the differing approaches two EC teachers have adopted when integrating iPad or computers into their settings. Data analysis revealed three key approaches which have been labelled: free digital play, guided digital play and teacher-led digital use. Importantly, teacher decisions were influenced by the interplay between the opportunities that the ICT tools offered, the teachers’ prior knowledge and experience about ICT and children’s learning needs and contexts. This paper is a snapshot of two early childhood settings, and further research will encompass data from six more early childhood settings in Victoria with the aim of exploring a wide range of motivating factors for early childhood teachers trying to integrate ICT into their programs.

Keywords: early childhood education (ECE), digital play, information and communication technologies (ICT), play, and teachers' interaction approaches

Procedia PDF Downloads 191

Authors: Rajesh Ranjan, Marimuthu Palaniswami, A. A. Hashmi

Abstract:

With the changing lifestyle and environment around us, the prevalence of the critical and incurable disease has proliferated. One such condition is the neurological disorder which is rampant among the old age population and is increasing at an unstoppable rate. Most of the neurological disorder patients suffer from some movement disorder affecting the movement of their body parts. Tremor is the most common movement disorder which is prevalent in such patients that infect the upper or lower limbs or both extremities. The tremor symptoms are commonly visible in Parkinson’s disease patient, and it can also be a pure tremor (essential tremor). The patients suffering from tremor face enormous trouble in performing the daily activity, and they always need a caretaker for assistance. In the clinics, the assessment of tremor is done through a manual clinical rating task such as Unified Parkinson’s disease rating scale which is time taking and cumbersome. Neurologists have also affirmed a challenge in differentiating a Parkinsonian tremor with the pure tremor which is essential in providing an accurate diagnosis. Therefore, there is a need to develop a monitoring and assistive tool for the tremor patient that keep on checking their health condition by coordinating them with the clinicians and caretakers for early diagnosis and assistance in performing the daily activity. In our research, we focus on developing a system for automatic classification of tremor which can accurately differentiate the pure tremor from the Parkinsonian tremor using a wearable accelerometer-based device, so that adequate diagnosis can be provided to the correct patient. In this research, a study was conducted in the neuro-clinic to assess the upper wrist movement of the patient suffering from Pure (Essential) tremor and Parkinsonian tremor using a wearable accelerometer-based device. Four tasks were designed in accordance with Unified Parkinson’s disease motor rating scale which is used to assess the rest, postural, intentional and action tremor in such patient. Various features such as time-frequency domain, wavelet-based and fast-Fourier transform based cross-correlation were extracted from the tri-axial signal which was used as input feature vector space for the different supervised and unsupervised learning tools for quantification of severity of tremor. A minimum covariance maximum correlation energy comparison index was also developed which was used as the input feature for various classification tools for distinguishing the PT and ET tremor types. An automatic system for efficient classification of tremor was developed using feature extraction methods, and superior performance was achieved using K-nearest neighbors and Support Vector Machine classifiers respectively.

Keywords: machine learning approach for neurological disorder assessment, automatic classification of tremor types, feature extraction method for tremor classification, neurological movement disorder, parkinsonian tremor, essential tremor

Procedia PDF Downloads 138

Authors: Shuqi Zhang

Abstract:

Federated learning allows users to participate in collaborative model training without sending data to third-party servers, reducing the risk of user data privacy leakage, and is widely used in smart finance and smart healthcare. However, the distributed architecture design of federation learning itself and the existence of secure aggregation protocols make it inherently vulnerable to backdoor attacks. To solve this problem, the federated learning backdoor defense framework FLEX based on group aggregation, cluster analysis, and neuron pruning is proposed, and inter-compatibility with secure aggregation protocols is achieved. The good performance of FLEX is verified by building a horizontal federated learning framework on the CIFAR-10 dataset for experiments, which achieves 98% success rate of backdoor detection and reduces the success rate of backdoor tasks to 0% ~ 10%.

Keywords: federated learning, secure aggregation, backdoor attack, cluster analysis, neuron pruning

Procedia PDF Downloads 82