4,264 research outputs found

    Comparative Multiple Case Study into the Teaching of Problem-Solving Competence in Lebanese Middle Schools

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    This multiple case study investigates how problem-solving competence is integrated into teaching practices in private schools in Lebanon. Its purpose is to compare instructional approaches to problem-solving across three different programs: the American (Common Core State Standards and New Generation Science Standards), French (Socle Commun de Connaissances, de Compétences et de Culture), and Lebanese with a focus on middle school (grades 7, 8, and 9). The project was conducted in nine schools equally distributed among three categories based on the programs they offered: category 1 schools offered the Lebanese program, category 2 the French and Lebanese programs, and category 3 the American and Lebanese programs. Each school was treated as a separate case. Structured observation data were collected using observation logs that focused on lesson objectives and specific cognitive problem-solving processes. The two logs were created based on a document review of the requirements for the three programs. Structured observations were followed by semi-structured interviews that were conducted to explore teachers' beliefs and understandings of problem-solving competence. The comparative analysis of within-category structured observations revealed an instruction ranging from teacher-led practices, particularly in category 1 schools, to more student-centered approaches in categories 2 and 3. The cross-category analysis showed a reliance on cognitive processes primarily promoting exploration, understanding, and demonstrating understanding, with less emphasis on planning and executing, monitoring and reflecting, thus uncovering a weakness in addressing these processes. The findings of the post-observation semi-structured interviews disclosed a range of definitions of problem-solving competence prevalent amongst teachers with clear divergences across the three school categories. This research is unique in that it compares problem-solving teaching approaches across three different programs and explores underlying teachers' beliefs and understandings of problem-solving competence in the Lebanese context. It is hoped that this project will inform curriculum developers about future directions and much-anticipated reforms of the Lebanese program and practitioners about areas that need to be addressed to further improve the teaching of problem-solving competence

    Practitioners’ Perceptions and Attitudes Towards Inclusion of Children with Special Educational Needs and/or Disabilities [SEND] in a Primary Mainstream School

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    In the 1970s, mounting pressure from the Education (Handicapped Children) Act (DES, 1970), requiring children who were previously deemed 'Ineducable' to attend school, led to a United Kingdom government inquiry into standards of national provision for children with Special Educational Needs (DES, 1978: 6) chaired by Lady Warnock. The Warnock report (1978) proposed three models to integrate children with disabilities: Locational, Social and Functional Integration, marking a major shift in special needs and disability discourse. Warnock (1978) introduced Special Educational Needs as an umbrella term, replacing the ten ‘handicap’ categories set out in the 1944 ‘Education Act’ regulations. The SEN and SEND acronyms emerged due to the SEND Code of Practices (DfES, 2001; DfE, 2014). The Salamanca agreement (UNESCO, 1994), a United Nations initiative, introduced the terms ‘Inclusion’ and ‘education for all’ (Unesco, 1994: ix), with a vision for all children with Special Educational Needs to be educated in primary mainstream settings. The Salamanca agreement recognised some children with disabilities would be best supported in a special school; however, it also stressed that children attending a special school should not be segregated and, thus, encouraged part-time attendance in a mainstream setting (Unesco, 1994). The notion of Inclusion shifted in light of multiple policies introduced after 1994. Research and this inquiry reveal that Inclusion’s success depends on practitioners’ attitudes (Brown, 2016), which are grounded in a complex web of training, support, expertise in SEND, specialists’ input and the complexity of Special Needs. This inquiry examined practitioners' perceptions and attitudes towards Inclusion for children with SEND attending a primary mainstream school. This research was conducted in a three-form entry school in England, teaching approximately 750 children with various abilities and disabilities. The research design was a case study comprising nine interviews and 27 questionnaires. Qualitative data were collected from practitioners [teachers, teaching assistants, learning mentor, headteacher, Chief Education Officer] via semi-structured interviews; the questionnaires accumulated qualitative and quantitative data. This inquiry used thematic analysis (Braun and Clarke 2013), examining themes and patterns of meaning associated with Inclusion and SEND. Extensive literature was examined, accentuating mixed reviews about Inclusion’s success in a primary mainstream school. While practitioners supported Inclusion in a mainstream school, they voiced concerns about the challenges of achieving Inclusion. Practitioners expressed concerns about the expectations of teaching children with diverse/complex SEND, irrespective of practitioner confidence, depleting funding, support, resources, training, and SEND expertise. The unrealistic expectations created challenges, resulting in some children facing Functional Integration, not Inclusion, as practitioners struggled to cater for all children’s SEND

    Modelling, Monitoring, Control and Optimization for Complex Industrial Processes

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    This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors

    Inclusive Intelligent Learning Management System Framework - Application of Data Science in Inclusive Education

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    Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceBeing a disabled student the author faced higher education with a handicap which as experience studying during COVID 19 confinement periods matched the findings in recent research about the importance of digital accessibility through more e-learning intensive academic experiences. Narrative and systematic literature reviews enabled providing context in World Health Organization’s International Classification of Functioning, Disability and Health, legal and standards framework and information technology and communication state-of-the art. Assessing Portuguese higher education institutions’ web sites alerted to the fact that only outlying institutions implemented near perfect, accessibility-wise, websites. Therefore a gap was identified in how accessible the Portuguese higher education websites are, the needs of all students, including those with disabilities, and even the accessibility minimum legal requirements for digital products and the services provided by public or publicly funded organizations. Having identified a problem in society and exploring the scientific base of knowledge for context and state of the art was a first stage in the Design Science Research methodology, to which followed development and validation cycles of an Inclusive Intelligent Learning Management System Framework. The framework blends various Data Science study fields contributions with accessibility guidelines compliant interface design and content upload accessibility compliance assessment. Validation was provided by a focus group whose inputs were considered for the version presented in this dissertation. Not being the purpose of the research to deliver a complete implementation of the framework and lacking consistent data to put all the modules interacting with each other, the most relevant modules were tested with open data as proof of concept. The rigor cycle of DSR started with the inclusion of the previous thesis on Atlântica University Institute Scientific Repository and is to be completed with the publication of this thesis and the already started PhD’s findings in relevant journals and conferences

    Real Estate Investment Trusts (REITs) Corporate Governance and Investment Decision-Making in the United Kingdom, South Africa and Nigeria

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    Adopting Real Estate Investment Trusts (REITs) has been relatively slow due to corporate governance issues and a limited understanding of investment decision-making processes. This study aims to enhance the performance of REITs by developing a Corporate Governance Scoring Framework and improving the investment decision-making process. A mixed-method research strategy was employed to gather data on investment decisionmaking processes and corporate governance in the UK, SA, and Nigeria from 2014-2019. Qualitative data was collected through semi-structured telephone interviews with key decision-makers in the three regimes and analysed using content and discourse analysis techniques. Quantitative data was obtained from the annual financial reports of listed REITs during the study period and analysed using OLS, fixed effects, and random effect models. The Integrated Corporate Governance Index (ICGI), a self-scoring framework, was used to measure the quality of corporate governance strength. The qualitative analysis identified four stages in the investment decision-making process: strategy, search, analysis and adjustment, and consultation or decision and review. The interviews revealed that the board, remuneration, and fee proxies were relevant factors across all three regimes, with audit and ownership also significant in the developing regimes of SA and Nigeria. The board's reputation, experience, and management role were highlighted as crucial during the decision-making process. Performance factors such as 'Operational Stability,' 'Tenant Quality,' 'Experience,' and metrics including 'Rental Income,' 'Dividend Payment,' and 'Yield' were identified. The quantitative analysis demonstrated that adherence to corporate governance codes was highest in the UK, followed by SA and Nigeria. Regression analysis results showed that a higher ICGI score improved return on assets (ROA) and return on equity (ROE) in the UK but not in SA and Nigeria. The index did not significantly impact firm value in the UK and pooled country analysis, but it led to better firm valuation in SA. In the Nigeria REIT regime, the ICGI harmed firm valuation. The study concluded that adherence to country-level corporate governance was more predictive of operational performance than firm valuation. In summary, this study contributes to the existing knowledge by providing insights into the investment decision-making processes of REITs and the importance of corporate governance in improving their performance. The developed Corporate Governance Scoring Framework offers a valuable tool for evaluating the quality of corporate governance in REITs, but further refinement is necessary to keep up with evolving policies

    Platform://Democracy: Perspectives on Platform Power, Public Values and the Potential of Social Media Councils

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    Social media platforms have created private communication orders which they rule through terms of service and algorithmic moderation practices. As their impact on public communication and human rights has grown, different models to increase the role of public interests and values in the design of their rules and their practices has, too. But who should speak for both the users and the public at large? Bodies of experts and/or selected user representatives, usually called Platform Councils of Social Media Councils (SMCs) have gained attention as a potential solution. Examples of Social Media Councils include Meta’s Oversight Board but most platforms companies have so far shied away from installing one. This survey of approaches to increasing the quality of platform decision-making and content governance involving more than 35 researchers from four continents brough to together in regional "research clinics" makes clear that trade-offs have to be carefully balanced. The larger the council, the less effective is its decision-making, even if its legitimacy might be increased. While there is no one-size-fits-all approach, the projects demonstrates that procedures matter, that multistakeholderism is a key concept for effective Social Media Councils, and that incorporating technical expertise and promoting inclusivity are important considerations in their design. As the Digital Services Act becomes effective in 2024, a Social Media Council for Germany’s Digital Services Coordinator (overseeing platforms) can serve as test case and should be closely monitored. Beyond national councils, there is strong case for a commission focused on ensuring human rights online can be modeled after the Venice Commission and can provide expertise and guidelines on policy questions related to platform governance, particularly those that affect public interests like special treatment for public figures, for mass media and algorithmic diversity. The commission can be staffed by a diverse set of experts from selected organizations and institutions established in the platform governance field

    Video Recommendation Using Social Network Analysis and User Viewing Patterns

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    With the meteoric rise of video-on-demand (VOD) platforms, users face the challenge of sifting through an expansive sea of content to uncover shows that closely match their preferences. To address this information overload dilemma, VOD services have increasingly incorporated recommender systems powered by algorithms that analyze user behavior and suggest personalized content. However, a majority of existing recommender systems depend on explicit user feedback in the form of ratings and reviews, which can be difficult and time-consuming to collect at scale. This presents a key research gap, as leveraging users' implicit feedback patterns could provide an alternative avenue for building effective video recommendation models, circumventing the need for explicit ratings. However, prior literature lacks sufficient exploration into implicit feedback-based recommender systems, especially in the context of modeling video viewing behavior. Therefore, this paper aims to bridge this research gap by proposing a novel video recommendation technique that relies solely on users' implicit feedback in the form of their content viewing percentages

    Artificial Intelligence (AI) and User Experience (UX) design: A systematic literature review and future research agenda

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    PurposeThe aim of this article is to map the use of AI in the user experience (UX) design process. Disrupting the UX process by introducing novel digital tools such as Artificial Intelligence (AI) has the potential to improve efficiency and accuracy, while creating more innovative and creative solutions. Thus, understanding how AI can be leveraged for UX has important research and practical implications.Design/Methodology/ApproachThis article builds on a systematic literature review approach and aims to understand how AI is used in UX design today, as well as uncover some prominent themes for future research. Through a process of selection and filtering, 46 research articles are analysed, with findings synthesized based on a user-centred design and development process.FindingsOur analysis shows how AI is leveraged in the UX design process at different key areas. Namely, these include understanding the context of use, uncovering user requirements, aiding solution design, and evaluating design, and for assisting development of solutions. We also highlight the ways in which AI is changing the UX design process through illustrative examples.Originality/valueWhile there is increased interest in the use of AI in organizations, there is still limited work on how AI can be introduced into processes that depend heavily on human creativity and input. Thus, we show the ways in which AI can enhance such activities and assume tasks that have been typically performed by humans
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