Search results for: student-centered learning technologies

Authors: Aguiar-Castillo Lidia, Perez-Jimenez Rafael

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The integration of gamification in educational settings aims to enhance student engagement and motivation through game design elements in learning activities. This paper introduces "Gamipulation," the subtle manipulation of students via gamification techniques serving hidden agendas without explicit consent. It highlights the need to distinguish between beneficial and exploitative uses of gamification in education, focusing on its potential to psychologically manipulate students for purposes misaligned with their best interests Through a literature review and expert interviews, this study presents a conceptual framework outlining gamipulation's features. It examines ethical concerns like gradually introducing desired behaviors, using distraction to divert attention from significant learning objectives, immediacy of rewards fostering short-term engagement over long-term learning, infantilization of students, and exploitation of emotional responses over reflective thinking. Additionally, it discusses ethical issues in collecting and utilizing student data within gamified environments. Key findings suggest that while gamification can enhance motivation and engagement, there's a fine line between ethical motivation and unethical manipulation. The study emphasizes the importance of transparency, respect for student autonomy, and alignment with educational values in gamified systems. It calls for educators and designers to be aware of gamification's manipulative potential and strive for ethical implementation that benefits students. In conclusion, this paper provides a framework for educators and researchers to understand and address gamipulation's ethical challenges. It encourages developing ethical guidelines and practices to ensure gamification in education remains a tool for positive engagement and learning rather than covert manipulation.

Keywords: gradualness, distraction, immediacy, infantilization, emotion

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Authors: Hamed Zolfaghari, Mojtaba Kord

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After feasibility study the design phase is started and the rest of other phases are highly dependent on this phase. forecasting the duration of design phase could do a miracle and would save a lot of time. This study provides a fast and accurate Machine learning (ML) and optimization framework, which allows a quick duration estimation of project design phase, hence improving operational efficiency and competitiveness of a design construction company. 3 data sets of three years composed of daily time spent for different design projects are used to train and validate the ML models to perform multiple projects. Our study concluded that Artificial Neural Network (ANN) performed an accuracy of 0.94.

Keywords: time estimation, machine learning, Artificial neural network, project design phase

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Authors: Sebastian Leal-Arenas

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TikTok’s influence on contemporary society is undeniable. The impact of the mobile app transcends entertainment, as shown by the growing presence of specialized accounts dedicated to providing educational content, particularly as it pertains to language learning. However, the prevailing trend on the platform is vocabulary and grammar acquisition, neglecting a critical component: pronunciation. This study examines English pronunciation materials available on TikTok by taking a comprehensive approach that incorporates established assessment tools, such as the Learning Object Review Instrument and the Framework for Language Learning App Evaluation. Furthermore, novel evaluation categories are introduced to provide a more holistic assessment of these educational resources. 60 English pronunciation videos were part of the analysis. The findings reveal that these audio-visual materials present clear audio bolstered by high-quality video content and automatically generated closed captions. These three components enhance the comprehensibility of the input, making these concise videos valuable assets for language learners. Nevertheless, certain deficiencies are observed, such as the lack of emphasis on specific segments and their relationship with articulators. Improvements and refinements are discussed, as well as their potential utility within the language classroom. This study contributes to the ongoing investigation of multimedia materials used for language teaching and emphasizes the need to adapt pronunciation instruction methods to today’s technology.

Keywords: pronunciation, segments, teaching materials, technology

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Authors: Maximilian Elsen, Frank Tietze

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The development and diffusion of green technologies are crucial for achieving our ambitious climate targets. The Paris Agreement commits its members to develop strategies for achieving net zero greenhouse gas emissions by the second half of the century. Governments, executives, and academics are working on net-zero strategies and the business of rating organisations on their environmental, social and governance (ESG) performance has grown tremendously in its public interest. ESG data is now commonly integrated into traditional investment analysis and an important factor in investment decisions. Creating these metrics, however, is inherently challenging as environmental and social impacts are hard to measure and uniform requirements on ESG reporting are lacking. ESG metrics are often incomplete and inconsistent as they lack fully accepted reporting standards and are often of qualitative nature. This study explores the use of patent data for assessing the environmental performance of companies by focusing on their patented inventions in the space of climate change mitigation and adaptation technologies (CCMAT). The present study builds on the successful identification of CCMAT patents. In this context, the study adopts the Y02 patent classification, a fully cross-sectional tagging scheme that is fully incorporated in the Cooperative Patent Classification (CPC), to identify Climate Change Adaptation Technologies. The Y02 classification was jointly developed by the European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) and provides means to examine technologies in the field of mitigation and adaptation to climate change across relevant technologies. This paper develops sustainability-related metrics for firm-level patent portfolios. We do so by adopting a three-step approach. First, we identify relevant CCMAT patents based on their classification as Y02 CPC patents. Second, we examine the technological strength of the identified CCMAT patents by including more traditional metrics from the field of patent analytics while considering their relevance in the space of CCMAT. Such metrics include, among others, the number of forward citations a patent receives, as well as the backward citations and the size of the focal patent family. Third, we conduct our analysis on a firm level by sector for a sample of companies from different industries and compare the derived sustainability performance metrics with the firms’ environmental and financial performance based on carbon emissions and revenue data. The main outcome of this research is the development of sustainability-related metrics for firm-level environmental performance based on patent data. This research has the potential to complement existing ESG metrics from an innovation perspective by focusing on the environmental performance of companies and putting them into perspective to conventional financial performance metrics. We further provide insights into the environmental performance of companies on a sector level. This study has implications of both academic and practical nature. Academically, it contributes to the research on eco-innovation and the literature on innovation and intellectual property (IP). Practically, the study has implications for policymakers by deriving meaningful insights into the environmental performance from an innovation and IP perspective. Such metrics are further relevant for investors and potentially complement existing ESG data.

Keywords: climate change mitigation, innovation, patent portfolios, sustainability

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Authors: Tiptunya Duangsri, Panwilai Chomchid, Natchanok Jansawang

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This research study was to investigate of education decisions must be made which a part of it should be passed on to future generations as obligatory for all members of a chemistry class for students who will prepare themselves for a special position. The descriptions of instructional design were provided and the recent criticisms are discussed. This research study to an outline of an integrative framework for the description of information and the instructional design model give structure to negotiate a semblance of conscious understanding. The aims of this study are to describe the instructional design model for comparisons between students’ genders of their effects on STEM educational learning achievement motives to their science attitudes and logical thinking abilities with a sample size of 18 students at the 11th grade level with the cluster random sampling technique in Mahawichanukul School were designed. The chemistry learning environment was administered with the STEM education method. To build up the 5-instrument lesson instructional plan issues were instructed innovations, the 30-item Logical Thinking Test (LTT) on 5 scales, namely; Inference, Recognition of Assumptions, Deduction, Interpretation and Evaluation scales was used. Students’ responses of their perceptions with the Test Of Chemistry-Related Attitude (TOCRA) were assessed of their attitude in science toward chemistry. The validity from Index Objective Congruence value (IOC) checked by five expert specialist educator in two chemistry classroom targets in STEM education, the E1/E2 process were equaled evidence of 84.05/81.42 which results based on criteria are higher than of 80/80 standard level with the IOC from the expert educators. Comparisons between students’ learning achievement motives with STEM educational model on stoichiometry issue in chemistry classes with different genders were differentiated at evidence level of .05, significantly. Associations between students’ learning achievement motives on their posttest outcomes and logical thinking abilities, the predictive efficiency (R2) values indicate that 69% and 70% of the variances in different male and female student groups of their logical thinking abilities. The predictive efficiency (R2) values indicate that 73%; and 74% of the variances in different male and female student groups of their science attitudes toward chemistry were associated. Statistically significant on students’ perceptions of their chemistry learning classroom environment and their science attitude toward chemistry when using the MCI and TOCRA, the predictive efficiency (R2) values indicated that 72% and 74% of the variances in different male and female student groups of their chemistry classroom climate, consequently. Suggestions that supporting chemistry or science teachers from science, technology, engineering and mathematics (STEM) in addressing complex teaching and learning issues related instructional design to develop, teach, and assess traditional are important strategies with a focus on STEM education instructional method.

Keywords: development, the instructional design model, students learning achievement motives, science attitudes with STEM educational model, stoichiometry issue, chemistry classes, genders

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Authors: Hyo Jung Lee

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The purpose of this study is to develop a literature appreciation education program for classic literatures and apply them to the field, and to derive the achievements and improvement points. Classic literature is a work of value recognized in the context of literature history and culture history, and learners can develop interest in literature and inherit tradition through appreciation of classic literature. However, in Korean educational environment, classic literature is a means for college entrance examination, and many learners analyze contents and language in textbooks and concentrate on memorizing the whole plot. This study is one of the reasons that classic literature appreciation education is not done properly and it is not able to give an opportunity to appreciate the whole work in the early learning stage. In Korean primary education, classic literature is used as a means to achieve the goals of reading, writing, speaking and listening, rather than being used as a material for its own appreciation. It is problematic to make the piece appreciation experience fragmentary. This study proposes a program to experience classic literatures by linking school education and school library with primary school students in grades 4-6. We work with local primary schools (siheung-si, gyeonggi-do, Korea) to provide appropriate activities and rewards to learners, observe their participation, and introduce student learning outcomes. Through this, we are able to systematically improve the learner 's ability to appreciate the literature and to diversify primary education.

Keywords: classic literature education, primary education, out-of-school program, learning by appreciation experience

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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Authors: Cansu Gülser, Tuğce Ercan

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The construction sector is a key driver of the global economy, contributing significantly to growth and employment through a diverse array of sub-sectors. However, it faces challenges due to its project-based nature, which often hampers long-term collaboration and broader incentives beyond individual projects. These limitations are frequently discussed in scientific literature as obstacles to innovation and industry-wide change. Traditional practices and unwritten rules further hinder the adoption of new processes within the construction industry. The disadvantages of the construction industry’s project-based structure in fostering innovation and long-term relationships include limited continuity, fragmented collaborations, and a focus on short-term goals, which collectively hinder the development of sustained partnerships, inhibit the sharing of knowledge and best practices, and reduce incentives for investing in innovative processes and technologies. This structure typically emphasizes specific projects, which restricts broader collaborations and incentives that extend beyond individual projects, thus impeding innovation and change. The temporal complexities inherent in project-based sectors like construction make it difficult to address societal challenges through collaborative efforts. Traditional management approaches are inadequate for scaling up innovations and adapting to significant changes. For systemic transformation in the construction sector, there is a need for more collaborative relationships and activities beyond traditional supply chains. This study delves into the concept of an innovation ecosystem within the construction sector, highlighting various research findings. It aims to explore key questions about the components that enhance innovation capacity, the relationship between a robust innovation ecosystem and this capacity, and the reasons why innovation is less prevalent and implemented in this sector compared to others. Additionally, it examines the main factors hindering innovation within companies and identifies strategies to improve these efforts, particularly in developing countries. The innovation ecosystem in the construction sector generates various outputs through interactions between business resources and external components. These outputs include innovative value creation, sustainable practices, robust collaborations, knowledge sharing, competitiveness, and advanced project management, all of which contribute significantly to company market performance and competitive advantage. This article offers insights and strategic recommendations for industry professionals, policymakers, and researchers interested in developing and sustaining innovation ecosystems in the construction sector. Future research should focus on broader samples for generalization, comparative sector analysis, and application-focused studies addressing real industry challenges. Additionally, studying the long-term impacts of innovation ecosystems, integrating advanced technologies like AI and machine learning into project management, and developing future application strategies and policies are also important.

Keywords: construction industry, innovation ecosystem, innovation ecosystem components, project management

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Authors: Vishnu Pratap Singh Kirar

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The main aim of the communication system is to achieve maximum performance. In cognitive radio, any user or transceiver have the ability to sense best suitable channel, while the channel is not in use. It means an unlicensed user can share the spectrum of licensed user without any interference. Though the spectrum sensing consumes a large amount of energy and it can reduce by applying various artificial intelligent methods for determining proper spectrum holes. It also increases the efficiency of Cognitive Radio Network (CRN). In this survey paper, we discuss the use of different learning models and implementation of Artificial Neural Network (ANN) to increase the learning and decision-making capacity of CRN without affecting bandwidth, cost and signal rate.

Keywords: artificial neural network, cognitive radio, cognitive radio networks, back propagation, spectrum sensing

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Authors: Chante Van Tonder, Bart Bossink, Chris Schachtebeck, Cecile Nieuwenhuizen

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Small and Medium-Sized Enterprises (SMEs) play a key role in national economies around the world, being contributors to economic and social well-being. Due to this, the success, growth and competitiveness of SMEs are critical. However, there are many factors that undermine this, such as resource constraints, poor information communication infrastructure (ICT), skills shortages and poor management. The Fourth Industrial Revolution offers new tools and opportunities such as digital transformation and business model innovation (BMI) to the SME sector to enhance its competitiveness. Adopting and leveraging digital technologies such as cloud, mobile technologies, big data and analytics can significantly improve business efficiencies, value proposition and customer experiences. Digital transformation can contribute to the growth and competitiveness of SMEs. However, SMEs are lagging behind in the participation of digital transformation. Extant research lacks conceptual and empirical research on how digital transformation drives BMI and the impact it has on the growth and competitiveness of SMEs. The purpose of the study is, therefore, to close this gap by developing and empirically validating a conceptual model to determine if SMEs are achieving BMI through digital transformation and how this is impacting the growth, competitiveness and overall business performance. An empirical study is being conducted on 300 SMEs, consisting of 150 South-African and 150 Dutch SMEs, to achieve this purpose. Structural equation modeling is used, since it is a multivariate statistical analysis technique that is used to analyse structural relationships and is a suitable research method to test the hypotheses in the model. Empirical research is needed to gather more insight into how and if SMEs are digitally transformed and how BMI can be driven through digital transformation. The findings of this study can be used by SME business owners, managers and employees at all levels. The findings will indicate if digital transformation can indeed impact the growth, competitiveness and overall performance of an SME, reiterating the importance and potential benefits of adopting digital technologies. In addition, the findings will also exhibit how BMI can be achieved in light of digital transformation. This study contributes to the body of knowledge in a highly relevant and important topic in management studies by analysing the impact of digital transformation on BMI on a large number of SMEs that are distinctly different in economic and cultural factors

Keywords: business models, business model innovation, digital transformation, SMEs

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Authors: Wong Seng Yue

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Game dynamics and game mechanics are the two main components that used in gamification to engage and encourage students to learn. The advantages of gamified classroom are engaging students, increasing students interest, preserving students focus and remain a positive behaviour. However, the empirical studies on gamification are still at early stage, especially the effectiveness of various gamification components have not been evaluated. Thus, this study is aimed to conduct a user experience (UX) evaluation on gamified classroom through Prezi, which focused on learning experience, gaming experience, adaptivity, and gameplay experience. This study is a further study extended from the previous exploratory study to explore more on UX of gamified classroom via Prezi by interview. A focus group study, which involves 22 students from a foundation course has been conducted for the study. Besides the empirical data from the previous study, this focus group study has significantly found that 90.9% respondents show their positive perceptions on gaming experience via Prezi. They are interested, feel fresh, good, and highly motivated of the contents of Prezi. 95.5% participants have had a positive learning experience from the gamified classroom via Prezi, which can engage them, made them concentrate on learning and easy to remember what they have learned if compared to the traditional classroom slides. The adaptivity of the gamified classroom also high due to its zooming user interface, narrative, rewards and engagement features. This study has uncovered on how far the impact of gamification components in the classroom, especially UX that implemented in gamified classroom.

Keywords: user experience (UX), gamification, gamified classroom, Prezi

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Authors: Weidong Xia, Malgorzata Kolotylo, Xuan Tan

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This study examines the key factors that influence general practitioners’ learning and transfer of specialized arthritis knowledge and self-care techniques to patients during normal patient visits. Drawing on the theory of planed behavior and using matched survey data collected from general practitioners before and after training sessions provided by specialized orthopedic physicians, the study suggests that the general practitioner’s intention to use and transfer learned knowledge was influenced mainly by intrinsic motivation, organizational learning culture and absorptive capacity, but was not influenced by extrinsic motivation. The results provide both theoretical and practical implications.

Keywords: empirical study, healthcare knowledge management, patient self-care, physician knowledge transfer

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Authors: Ramona-Niculina Jurcau, Ioana-Marieta Jurcau

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Background: Preparing in the stress field (SF) is, increasingly, a concern for doctors of different specialties. Aims: The aim was to evaluate the importance of an e-learning program for doctors postgraduate courses, in SF. Methods: Doctors (n= 40 male, 40 female) of different specialties and ages (31-71 years), who attended postgraduate courses in SF, voluntarily responded to a questionnaire that included the following themes: Importance of SF courses for specialty practiced by each respondent doctor (using visual analogue scale, VAS); What SF themes would be indicated as e-learning (EL); Preferred form of SF information assimilation: Classical lectures (CL), EL or a combination of these methods (CL+EL); Which information on the SF course are facilitated by EL model versus CL; In their view which are the first four advantages and the first four disadvantages of EL compared to CL, for SF. Results: To most respondents, the SF courses are important for the specialty they practiced (VAS by an average of 4). The SF themes suggested to be done as EL were: Stress mechanisms; stress factor models for different medical specialties; stress assessment methods; primary stress management methods for different specialties. Preferred form of information assimilation was CL+EL. Aspects of the course facilitated by EL versus CL model: Active reading of theoretical information, with fast access to keywords details; watching documentaries in everyone's favorite order; practice through tests and the rapid control of results. The first four EL advantages, mentioned for SF were: Autonomy in managing the time allocated to the study; saving time for traveling to the venue; the ability to read information in various contexts of time and space; communication with colleagues, in good times for everyone. The first three EL disadvantages, mentioned for SF were: It decreases capabilities for group discussion and mobilization for active participation; EL information accession may depend on electrical source or/and Internet; learning slowdown can appear, by temptation of postponing the implementation. Answering questions was partially influenced by the respondent's age and genre. Conclusions: 1) Post-graduate courses in SF are of interest to doctors of different specialties. 2) The majority of participating doctors preferred EL, but combined with CL (CL+EL). 3) Preference for EL was manifested mainly by young or middle age men doctors. 4) It is important to balance the proper formula for chosen EL, to be the most efficient, interesting, useful and agreeable.

Keywords: stress field, doctors’ postgraduate courses, classical lectures, e-learning lecture

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Authors: Jacinta Ifeoma Obidile

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Teachers (vocational and technical educators inclusive) use Information and Communications Technology (ICT) for tasks outside of their normal working hours. This expansion of work duties to non-work time challenges their work-life balance. However, there has been inconsistency in the results on how these relationships correlate. This, therefore, calls for further research studies to examine the moderating mechanisms of such relationships. The present study, therefore, ascertained how vocational and technical educators’ technology acceptance relates to their work-related ICT use beyond their working hours and work-life balance, as well as how their integration affects these relationships. The population of the study comprised 320 Vocational and Technical Educators from the Southeast geopolitical zone of Nigeria. Data were collected from the respondents using the structured questionnaire. The questionnaire was validated by three experts. The reliability of the study was conducted using 20 vocational and technical educators from the South who were not part of the population. The overall reliability coefficient of 0.81 was established using Cronbach’s alpha method. The data collected was analyzed using Structural equation modeling. Findings, among others, revealed that vocational and technical educators’ work-life balance was mediated by increased digital learning environment use after work hours, although reduced by social influence.

Keywords: vocational and technical educators, digital learning environment, working hours, work-life balance, integration preference

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Authors: Raiya Kishwar Ashraf

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The National University, the largest public educational institution in Bangladesh, recently made it mandatory for all students to study a course in Bangladesh‘s history of the 1971 Liberation War. This introduction was accompanied by massive political, financial and academic movement that allocated resources towards achieving greater awareness of the country‘s spirit, goals of liberation and patriotism among the youth. This study argues that the infrastructure and political economy around the course heavily politicizes the education system and more specifically the teaching and learning the process. By conducting a qualitative study in three affiliated colleges under the National University, this study aimed to explore the extent to which politicization affected higher education curriculum, especially history education in Bangladesh. The findings revealed significant levels of politicization and structural constraints present in the process that restricts the teacher and student engagement with course materials. The results of this study are useful for curriculum designers and higher education teachers and staffs who wish to develop content and deliver education that promotes critical inquiry among students. The findings further shed light on the importance of identifying and addressing political influences in education curriculum and programme development.

Keywords: Bangladesh higher education, critical thinking, curriculum politicization, history curriculum, National University, teaching-learning method

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Authors: Roula Kitsiou, Sofia Tsioli, Eleni Gana

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The current sociopolitical realities (displacement, encampment, and resettlement) refugees experience in Greece are a quite complex issue. Their educational and social ‘integration’ is characterized by transition, insecurity, and constantly changing needs. Based on the current research data, technology and more specifically mobile phones are one of the most important resources for refugees, regardless of their levels of conventional literacy. The proposed paper discusses the challenges encountered during the design and implementation of the educational Action 16 ‘Language Education for Adult Refugees’. Action 16 is one of the 24 Actions of the Project PRESS (Provision of Refugee Education and Support Scheme), funded by the Hellenic Open University (2016-2017). Project PRESS had two main objectives: a) to address the educational and integration needs of refugees in transit, who currently reside in Greece, and b) implement research-based educational interventions in online and offline sites. In the present paper, the focus is on reflection and discussion about the challenges and the potential of integrating technology in language learning for a target-group with many specific needs, which have been recorded in field notes among other research tools (ethnographic data) used in the context of PRESS. Action 16, explores if and how technology enhanced language activities in real-time and place mediated through teachers, as well as an autonomous computer-mediated learning space (moodle platform and application) builds on and expands the linguistic, cultural and digital resources and repertoires of the students by creating collaborative face-to-face and digital learning spaces. A broader view on language as a dynamic puzzle of semiotic resources and processes based on the concept of translanguaging is adopted. Specifically, designing the blended learning environment we draw on the construct of translanguaging a) as a symbolic means to valorize students’ repertoires and practices, b) as a method to reach to specific applications of a target-language that the context brings forward (Greek useful to them), and c) as a means to expand refugees’ repertoires. This has led to the creation of a learning space where students' linguistic and cultural resources can find paths to expression. In this context, communication and learning are realized by mutually investing multiple aspects of the team members' identities as educational material designers, teachers, and students on the teaching and learning processes. Therefore, creativity, humour, code-switching, translation, transference etc. are all possible means that can be employed in order to promote multilingual communication and language learning towards raising intercultural awareness in a critical digital pedagogy context. The qualitative analysis includes critical reflection on the developed educational material, team-based reflexive discussions, teachers’ reports data, and photographs from the interventions. The endeavor to involve women and men with a refugee background into a blended learning experience was quite innovative especially for the Greek context. It reflects a pragmatist ethos of the choices made in order to respond to the here-and-now needs of the refugees, and finally it was a very challenging task that has led all actors involved into Action 16 to (re)negotiations of subjectivities and products in a creative and hopeful way.

Keywords: blended learning, integration, language education, refugees

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Authors: Valerie Triggs, Michele Sorensen

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As two university professors in postsecondary faculties of social work and education, we have observed that students often recognize the importance of learning facts about colonization but have difficulty grappling with how they themselves might be implicated in reconciliation or how they might respond to these facts in meaningful ways. The detachment observed between students and factual information results in the initiation of a research study centered around an approach to teaching the course. This involved transitioning its pedagogical format to embrace a/r/tographic methods of teaching, learning, and inquiry. By taking seriously the arguments of various Indigenous scholars for learning from the land and by working alongside traditional Indigenous knowledge, we chose to engage a speculative approach to course design and teaching, which actually used the land as one of the course texts. We incorporated art practices that involved connecting bodies with land as well as using land materials in various creative and aesthetic projects while being informed by Medicine Keepers, Indigenous and settler artists, and knowledge-keeper helpers. In this study, we share some of the unanticipated themes that arose when students began to allow land and artmaking, both aesthetically and intuitively, through both joy and sorrow, to affect a reimagining and repositioning of selves and relations. We found that time and engagement with land and art began to build more empathic understanding and foster personal and professional practices grounded in respect, relevance, reciprocity, and responsibility.

Keywords: reconciliation, decolonization, artmaking, respect

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Authors: Sebastián Olivares Lizana, Marianna Oyanedel González

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This study takes part of a major project based on implementing a CLIL program (Content and Language Integrated Learning) at Universidad Técnica Federico Santa María, a leading Chilean tertiary Institution. It aims at examining the relationship between the development of Reflective Processes (RP) and Cognitive Academic Language Proficiency (CALP) in weekly learning logs written by faculty members, participants of an initial professional development online course on English for Academic Purposes (EAP). Such course was designed with a genre-based approach, and consists of multiple tasks directed to academic writing proficiency. The results of this analysis will be described and classified in a scale of key indicators that represent both the Reflective Processes and the advances in CALP, and that also consider linguistic proficiency and task progression. Such indicators will evidence affordances and constrains of using a genre-based approach in an EFL Engineering CLIL program implementation at tertiary level in Chile, and will serve as the starting point to the design of a professional development course directed to teaching methodologies in a CLIL EFL environment in Engineering education at Universidad Técnica Federico Santa María.

Keywords: EFL, EAL, genre, CLIL, engineering

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Authors: Ann Dashwood

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Using Standard Australian English with confidence is a cultural expectation of parents of primary school aged children who want to engage effectively with their children’s teachers and school administration. That confidence in support of their children’s learning at school is seldom experienced by parents whose first language is not English. Sharing language with competence in an intercultural environment is the common denominator for meaningful communication and engagement to occur in a school community. Experience in relevant, interactive sessions is known to enhance engagement and participation. The purpose of this paper is to identify a pedagogy for parents otherwise isolated from daily use of functional Australian cultural language learned to engage effectively in their children’s learning at school. The outcomes measure parents’ intercultural engagement with classroom teachers and attention to the school’s administrative procedures using quantitative and qualitative methods. A principled communicative task-based language learning approach, combined with intercultural communication strategies provide the theoretical base for intensive English inquiry-based learning and engagement. The quantitative analysis examines data samples collected by classroom teachers and administrators and parents’ writing samples. Interviews and observations qualitatively inform the study. Currently, significant numbers of projects are active in community centers and schools to enhance English language knowledge of parents from Language Backgrounds Other Than English (LBOTE). The study is significant to explore the effects of an intensive English pedagogy with parents of varied English language backgrounds, by targeting inquiry-based language use for social interactions in the school and wider community, specific engagement and cultural interaction with teachers and school activities and procedures.

Keywords: engagement, intercultural communication, language teaching pedagogy, LBOTE, school community

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Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

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Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, this project proposes AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project presents the best-in-school techniques used to preserve the data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptographic techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures and identifies potential correction/mitigation measures.

Keywords: data privacy, artificial intelligence (AI), healthcare AI, data sharing, healthcare organizations (HCOs)

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Authors: Aqsa Ali, Aleem Mushtaq, Attaullah Memon, Monna

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In this paper, we present a low cost design for a smart glove that can perform sign language recognition to assist the speech impaired people. Specifically, we have designed and developed an Assistive Hand Gesture Interpreter that recognizes hand movements relevant to the American Sign Language (ASL) and translates them into text for display on a Thin-Film-Transistor Liquid Crystal Display (TFT LCD) screen as well as synthetic speech. Linear Bayes Classifiers and Multilayer Neural Networks have been used to classify 11 feature vectors obtained from the sensors on the glove into one of the 27 ASL alphabets and a predefined gesture for space. Three types of features are used; bending using six bend sensors, orientation in three dimensions using accelerometers and contacts at vital points using contact sensors. To gauge the performance of the presented design, the training database was prepared using five volunteers. The accuracy of the current version on the prepared dataset was found to be up to 99.3% for target user. The solution combines electronics, e-textile technology, sensor technology, embedded system and machine learning techniques to build a low cost wearable glove that is scrupulous, elegant and portable.

Keywords: American sign language, assistive hand gesture interpreter, human-machine interface, machine learning, sensing glove

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Authors: Shashwat, Sandra G. L. Persiani, Yew Wah Wong, Pramod S. Kamath, Avinash H. Anantharam, Hui Ling Aw, Yann Grynberg

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Achieving zero-energy targets in existing buildings is known to be a difficult task, hence targets are addressed at new buildings almost exclusively. Although these ultra-efficient case-studies remain essential to develop future technologies and drive the concepts of Zero-energy, the immediate need to cut the consumption of the existing building stock remains unaddressed. This work aims to present a reliable and straightforward methodology for assessing the potential of energy-efficient upgrading in existing buildings. Public Singaporean school buildings, characterized by low energy use intensity and large roof areas, were identified as potential objects for conversion to highly-efficient buildings with a positive energy balance. A first study phase included the development of a detailed energy model for two case studies (a primary and a secondary school), based on the architectural drawings provided, site-visits and calibrated using measured end-use power consumption of different spaces. The energy model was used to demonstrate compliances or predict energy consumption of proposed changes in the two buildings. As complete energy monitoring is difficult and substantially time-consuming, short-term energy data was collected in the schools by taking spot measurements of power, voltage, and current for all the blocks of school. The figures revealed that the bulk of the consumption is attributed in decreasing order of magnitude to air-conditioning, plug loads, and lighting. In a second study-phase, a number of energy-efficient technologies and strategies were evaluated through energy-modeling to identify the alternatives giving the highest energy saving potential, achieving a reduction in energy use intensity down to 19.71 kWh/m²/y and 28.46 kWh/m²/y for the primary and the secondary schools respectively. This exercise of field evaluation and computer simulation of energy saving potential aims at a preliminary assessment of the positive-energy feasibility enabling future implementation of the technologies on the buildings studied, in anticipation of a broader and more widespread adoption in Singaporean schools.

Keywords: energy simulation, school building, tropical climate, zero energy buildings, positive energy

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Authors: E. J. Spamer, J. M. Van Zyl, MHA Combrinck

Abstract:

The Unit for Open Distance Learning (UODL) at the North-West University (NWU), South Africa was established in 2013 with its main function to deliver open distance learning (ODL) programmes to approximately 30 000 students from the Faculties of Education Sciences, Health Sciences, Theology and Arts and Culture. Quality operational and administrative processes are key components in the delivery of these programmes and they need to function optimally for students to be successful in their studies. Operational and administrative processes include aspects such as applications, registration, dissemination of study material, availability of electronic platforms, the management of assessment, and the dissemination of important information. To be able to ensure and enhance quality during these processes, it is vital to determine students’ perceptions with regards to these mentioned processes. A questionnaire was available online and also distributed to the 63 tuition centres. The purpose of this research was to determine the perceptions of ODL students from NWU regarding operational and administrative processes. 1903 students completed and submitted the questionnaire. The data was quantitatively analysed and discussed. Results indicated that the majority of students are satisfied with the operational and administrative processes; however, the results also indicated some areas that need improvement. The data gathered is important to identify strengths and areas for improvement and form part of a bigger strategy of qualitative assurance at the UODL.

Keywords: administrative support, ODL programmes, quantitative study, students' perceptions

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Authors: Ivana Hrebickova, Maria Sevcikova, Romana Slamberova

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The present study was aimed at evaluation of cognitive changes following scheduled neonatal methamphetamine exposure in combination with long-term exposure in adulthood of female Wistar rats. Pregnant mothers were divided into two groups: group with indirect exposure (methamphetamine in dose 5 mg/ml/kg, saline in dose 1 ml/kg) during early lactation period (postnatal day 1–11) - progeny of these mothers were exposed to the effects of methamphetamine or saline indirectly via the breast milk; and the second group with direct exposure – all mothers were left intact for the entire lactation period, while progeny was treated with methamphetamine (5 mg/ml/kg) by injection or the control group, which was received needle pick (shame, not saline) at the same time each day of period of application (postnatal day 1–11). Learning ability and memory consolidation were tested in the Morris Water Maze, which consisted of three types of tests: ‘Place Navigation Test ‘; ‘Probe Test ‘; and ‘Memory Recall Test ‘. Adult female progeny were injected daily, after completion last trial with saline or methamphetamine (1 mg/ml/kg). We compared the effects of indirect/direct neonatal methamphetamine exposure and adult methamphetamine treatment on cognitive function of female rats. Statistical analyses showed that neonatal methamphetamine exposure worsened spatial learning and ability to remember the position of the platform. The present study demonstrated that direct methamphetamine exposure has more significant impact on process of learning and memory than indirect exposure. Analyses of search strategies (thigmotaxis, scanning) used by females during the Place Navigation Test and Memory Recall Test confirm all these results.

Keywords: methamphetamine, Morris water maze, neonatal exposure, strategies, Wistar rats

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

Procedia PDF Downloads 138

Authors: Yi-Ju Lee

Abstract:

This study identified the hypothesised relationship between creative experience, and revisit intention of handmade oriental parasol umbrella in Kaohsiung, Taiwan. A face-to-face questionnaire survey was administered in Meinong town, Kaohsiung. The components of creative experience were found as “sense of achievement”, “unique learning” and “interaction with instructors” in creative tourism. The result also revealed significant positive relationships between creative experience and revisit intention in handmade activities. This paper provides additional suggestions for enhancing revisit intention and guidance regarding creative tourism.

Keywords: creative tourism, sense of achievement, unique learning, interaction with instructors, folk art

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Authors: Joel S. Mtebe, Aron Kondoro, Mussa M. Kissaka, Elia Kibga

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Sub-Saharan Africa is described as the second fastest growing mobile phone penetration in the world more than in the United States or the European Union. Mobile phones have been used to provide a lot of opportunities to improve people’s lives in the region such as in banking, marketing, entertainment, and paying various bills such as water, TV, and electricity. However, the potential of using mobile phones to enhance teaching and learning has not been explored. This study presents an experience of developing and delivering SMS quizzes questions that were used to assess mastery of the subject content knowledge of science and mathematics secondary school teachers in Tanzania. The SMS quizzes were used as a follow up support mechanism to 500 teachers who participated in a project to upgrade subject content knowledge of science and mathematics subjects. Quizzes of 10-15 questions were sent to teachers each week for 8 weeks and the results were analyzed using SPSS. The results showed that chemistry and biology had better performance compared to mathematics and physics. Teachers reported some challenges that led to poor performance, invalid answers, and non-responses and they are presented. This research has several practical implications for those who are implementing or planning to use mobile phones for teaching and learning especially in rural secondary schools in sub-Saharan Africa.

Keywords: mobile learning, elearning, educational technolgies, SMS, secondary education, assessment

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Authors: Rujia Chen, Ajit Narayanan

Abstract:

Convolutional neural networks (CNN), as typically applied in deep learning, use layer-wise backpropagation (BP) to construct filters and kernels for feature extraction. Such filters are 2D or 3D groups of weights for constructing feature maps at subsequent layers of the CNN and are shared across the entire input. BP as a gradient descent algorithm has well-known problems of getting stuck at local optima. The use of genetic algorithms (GAs) for evolving weights between layers of standard artificial neural networks (ANNs) is a well-established area of neuroevolution. In particular, the use of crossover techniques when optimizing weights can help to overcome problems of local optima. However, the application of GAs for evolving the weights of filters and kernels in CNNs is not yet an established area of neuroevolution. In this paper, a GA-based filter development algorithm is proposed. The results of the proof-of-concept experiments described in this paper show the proposed GA algorithm can find filter weights through evolutionary techniques rather than BP learning. For some simple classification tasks like geometric shape recognition, the proposed algorithm can achieve 100% accuracy. The results for MNIST classification, while not as good as possible through standard filter learning through BP, show that filter and kernel evolution warrants further investigation as a new subarea of neuroevolution for deep architectures.

Keywords: neuroevolution, convolutional neural network, genetic algorithm, filters, kernels

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Authors: El Miloudi Djelloul

Abstract:

Based on analysis on applications by perception control technology in computer network security status and security protection measures, from the angles of network physical environment and network software system environmental security, this paper provides network security system perception control solution using Internet of Things (IOT), telecom and other perception technologies. Security Perception Control System is in the computer network environment, utilizing Radio Frequency Identification (RFID) of IOT and telecom integration technology to carry out integration design for systems. In the network physical security environment, RFID temperature, humidity, gas and perception technologies are used to do surveillance on environmental data, dynamic perception technology is used for network system security environment, user-defined security parameters, security log are used for quick data analysis, extends control on I/O interface, by development of API and AT command, Computer Network Security Perception Control based on Internet and GSM/GPRS is achieved, which enables users to carry out interactive perception and control for network security environment by WEB, E-MAIL as well as PDA, mobile phone short message and Internet. In the system testing, through middle ware server, security information data perception in real time with deviation of 3-5% was achieved; it proves the feasibility of Computer Network Security Perception Control System.

Keywords: computer network, perception control system security strategy, Radio Frequency Identification (RFID)

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Authors: Tewelde Gebreslassie Gebreanenia, Frie Ayalew Yimam, Seada Hussen Adem

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Patient safety and quality of care are essential goals of health care delivery, but they are often compromised by human errors, system failures, or resource constraints. In a variety of healthcare contexts, artificial intelligence (AI), a quickly developing field, can provide fresh approaches to enhancing patient safety and treatment quality. Artificial Intelligence (AI) has the potential to decrease errors and enhance patient outcomes by carrying out tasks that would typically require human intelligence. These tasks include the detection and prevention of adverse events, monitoring and warning patients and clinicians about changes in vital signs, symptoms, or risks, offering individualized and evidence-based recommendations for diagnosis, treatment, or prevention, and assessing and enhancing the effectiveness of health care systems and services. This study examines the state-of-the-art and potential future applications of AI-based technologies for enhancing patient safety and care quality, as well as the opportunities and problems they present for patients, policymakers, researchers, and healthcare providers. In order to ensure the safe, efficient, and responsible application of AI in healthcare, the paper also addresses the ethical, legal, social, and technical challenges that must be addressed and regulated.

Keywords: artificial intelligence, health care, human intelligence, patient safty, quality of care

Procedia PDF Downloads 67