Search results for: learning outcomes framework

Authors: Elias Kodjo Kekesi

Abstract:

This study seeks to investigate a critical but neglected area in disaster and emergency management in Ghana. It explores aspects of work within one of the safety-critical work environments that expose workers to psychological, social and physical harm. With much attention to crises’ survivors, deceased and their families, this research attempts to answer a key question: ‘What happens to the rescuer’? Emergency response is associated with immense and unprecedented pressure that puts responders’ physical, mental and social well-being at risk. Despite the negative psychological outcomes, scholars argue that being in a traumatic situation may trigger positive outcomes for some people. Thus, the study also focuses on the positive impact of working in a risky crisis environment. Additionally, people’s interpretation of negative experiences or exposure to adverse conditions differ owing to their personal resources which explains why some people may be negatively affected whiles others are positively impacted. To examine these complex nuances, an exploratory sequential mixed method design is adopted. This paper will highlight the findings of study one, which explores the underlying themes emerging from the Ghanaian disaster and emergency response environment regarding psychosocial hazard exposures and the corresponding outcomes.

Keywords: psychosocial hazards, organisational outcomes, qualitative research, Ghana

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Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi

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In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.

Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh

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Authors: Qiang Fu, Abu Saleh

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Research studies are highly fragmented when an innovation management framework is being discussed. With the aim to identify an innovation management framework/assessment tool suitable for small & medium enterprises (SMEs) in the service industry, this researcher critically reviewed existing innovation management frameworks and assessment models/tools and discovered a number of literature gaps. It is established that existing literature lacks generally agreed innovation management dimensions, commonly accepted knowledge creation through empirical studies on innovation management in SMEs, effective innovation management performance measurements, and studies on innovation management in the service industry, in particular in retail SMEs. As such, there is a dire need to develop an appropriate firm-level innovation management framework suitable for SMEs in the service industry for a future research project and further study. In addition, this researcher also discussed the significance of establishing such an innovation management framework.

Keywords: innovation management, innovation management framework, innovation management assessment tools, SMEs, service industry

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Authors: Sobhy Fathy A. Hashesh

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This study aimed at investigating the effect of Andalus Knowledge Phases and Times (ANPT) model of learning and the effect of 'Intel Education Contribution in ANPT' on the development of students’ academic performance and emotional quotient. The society of the study composed of Andalus Private Schools, elementary school students (N=700), while the sample of the study composed of four randomly assigned groups (N=80) with one experimental group and one control group to study "ANPT" effect and the "Intel Contribution in ANPT" effect respectively. The study followed the quantitative and qualitative approaches in collecting and analyzing data to answer the study questions. Results of the study revealed that there were significant statistical differences between students’ academic performances and emotional quotients for the favor of the experimental groups. The study recommended applying this model on different educational variables and on other age groups to generate more data leading to more educational results for the favor of students’ learning outcomes.

Keywords: Al Andalus, emotional quotient, students, academic performance development

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Authors: Virginia Chambers, Kamryn York, Mark Marnich

Abstract:

T.I.M.E. for STEM (Transforming Integrative Maker Education for STEM learning) focuses on improving the quality and effectiveness of STEM education for pre-service teachers through a focus on the integration of maker space pedagogy. This National Science Foundation-funded project primarily focuses on undergraduate pre-service teaching students majoring in elementary education. The study contributes to the knowledge about teaching and learning by developing, implementing, and assessing faculty development, interactive instruction, and STEM lesson plan development. This project offers a valuable opportunity to improve STEM thinking skills by formally integrating STEM concepts throughout the pre-service teacher curriculum using an interdisciplinary approach. T.I.M.E. for STEM utilizes a maker space laboratory at Point Park University in Pittsburgh, PA, USA. However, the project design is such that other institutions of higher education can replicate the program with or without a physical maker space lab as the project’s findings and “maker mindset” are employed. Utilizing qualitative research methodology, the project investigates the following research question: What do pre-service teachers (education students) and faculty members identify as areas of pedagogical growth in STEM learning and teaching in a makerspace environment? This research highlights the impact of makerspace pedagogy on improving STEM education learning outcomes through an interdisciplinary constructivist approach. The project is expected to have a multiplier effect as it impacts STEM disciplinary and higher education faculty, pre-service teachers, and teacher preparation programs at other universities that benefit from what is learned at Point Park University. Ultimately, the future elementary students of the well-prepared pre-service teachers steeped in maker pedagogy and STEM content will have the potential to develop higher-level thinking skills and improve their mathematics and scientific achievement, which are essential for the 21st century STEM workforce.

Keywords: maker education, STEM learning, teacher education, elementary education

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Authors: Mafawez Alharbi, Mahdi Jemmali

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E-learning is a developing area especially in education. E-learning can provide several benefits to learners. An intelligent system to collect all components satisfying user preferences is so important. This research presents an approach that it capable to personalize e-information and give the user their needs following their preferences. This proposal can make some knowledge after more evaluations made by the user. In addition, it can learn from the habit from the user. Finally, we show a walk-through to prove how intelligent process work.

Keywords: artificial intelligence, architecture, e-learning, software engineering, processing

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Authors: Rebecca Haythorne

Abstract:

Background: Agendas continuously emphasise the need to increase work based training and opportunities for individuals with learning disabilities. However research and statistics suggest that there is still significant stigma and stereotypes as to what they can contribute, or gain from being part of the working environment. Method: To tackles some of these prejudices an Occupational Therapy based intervention was developed for learning disability service users working at a social enterprise farm. The intervention aimed to increase positive public perception around individual capabilities and encourage individuals with learning disabilities to take ownership and be proud of their individual personhood and citizenship. This was achieved by using components of the Model of Human Occupation to tailor the intervention to individual values, skills and working contributions. The final project involved making creative wall art for public viewing, focusing on 'who works there and what they do'. This was accompanied by a visitor information guide, allowing individuals to tell visitors about themselves, the work they do and why it is meaningful to them. Outcomes: The intervention has helped to increased metal well-being and confidence of learning disability service users “people will know I work here now” and “I now have something to show my family about the work I do at the farm”. The intervention has also increased positive public perception and community awareness “you can really see the effort that’s gone into doing this” and “it’s a really visual experience to see people you don’t expect to see doing this type of work”. Resources left behind have further supported individuals to take ownership in creating more wall art to be sold at the farm shop. Conclusion: the intervention developed has helped to improve mental well-being of both service users and staff and improve community awareness. Due to this, the farm has decided to roll out the intervention to other areas of the social enterprise and is considering having more Occupational Therapy involvement in the future.

Keywords: citizenship, intervention, occupational therapy, personhood

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Authors: Salina Budin, Shaira Ismail

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Students learn effectively in a learning environment with a suitable teaching approach that matches their learning preferences. The main objective of the study is to examine the learning preferences amongst the students in the Science and Technology (S&T), and Social Science (SS) fields of study at the Universiti Teknologi Mara (UiTM), Pulau Pinang. The measurement instrument is based on the Dunn and Dunn Learning Styles which measure five elements of learning styles; environmental, sociological, emotional, physiological and psychological. Questionnaires are distributed amongst undergraduates in the Faculty of Mechanical Engineering and Faculty of Business Management. The respondents comprise of 131 diploma students of the Faculty of Mechanical Engineering and 111 degree students of the Faculty of Business Management. The results indicate that, both S&T and SS students share a similar learning preferences on the environmental aspect, emotional preferences, motivational level, learning responsibility, persistent level in learning and learning structure. Most of the S&T students are concluded as analytical learners and the majority of SS students are global learners. Both S&T and SS students are concluded as visual learners, preferred to be in an active mobility in a relaxing and enjoying mode with some light of refreshments during the learning process and exhibited reflective characteristics in learning. Obviously, the S&T students are considered as left brain dominant, whereas the SS students are right brain dominant. The findings highlighted that both categories of students exhibited similar learning preferences except on psychological preferences.

Keywords: learning preferences, Dunn and Dunn learning style, teaching approach, science and technology, social science

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Authors: Khan Shahid, Shahid Zakia

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This article explores the fields of Theology and Islamic Philosophy in alignment with the SOUL (Sincere act, Optimization efforts, Ultimate goal, Law compliance) framework. It examines their historical development and demonstrates how embracing sincerity, optimization, ultimate goals, and law compliance enhances these disciplines within the Islamic context. By emphasizing the importance of Sincere acts, Optimization efforts, Ultimate goal, and Law compliance, this article provides a framework for enriching Theology and Islamic Philosophy.

Keywords: SOUL framework, Theology, Islamic Philosophy, Sincerity act, Optimization effort, Ultimate goal, Law compliance

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Authors: Said Ahmed Zohairy

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Significant shifts in the theory and practice of teaching vocabulary affect teachers’ decisions about learning materials’ design. Relevant literature supports teaching specialised, authentic, and multi-word lexical items rather than focusing on single-word vocabulary lists. Corpora, collections of texts stored in a database, presents a reliable source of teaching and learning materials. Although corpus-informed studies provided guidance for teachers to identify useful language chunks and phraseological units, there is a scarcity in the literature discussing the use of corpora in teaching English for academic and specific purposes (EASP). The aim of this study is to improve teaching practices and provide a description of the pedagogical choices and procedures of an EASP tutor in an attempt to offer guidance for novice corpus users. It draws on the researcher’s experience of utilising corpus linguistic tools to design vocabulary learning activities without focusing on students’ learning outcomes. Hence, it adopts a self-study research methodology which is based on five methodological components suggested by other self-study researchers. The findings of the study noted that designing specialised and corpus-informed vocabulary learning activities could be challenging for teachers, as they require technical knowledge of how to navigate corpora and utilise corpus analysis tools. Findings also include a description of the researcher’s approach to building and analysing a specialised corpus for the benefit of novice corpus users; they should be able to start their own journey of designing corpus-based activities.

Keywords: corpora, corpus linguistics, corpus-informed, English for academic and specific purposes, agribusiness, vocabulary, phraseological units, materials design

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Authors: Bhavani Veasuvalingam

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Case-based learning (CBL) is a popular instructional method aimed to bridge theory to clinical practice. This study aims to explore CBL mixed modality curriculum in influencing students’ learning styles and strategies that support learning. An explanatory sequential mixed method study was employed with initial phase, 44-itemed Felderman’s Index of Learning Style (ILS) questionnaire employed across year one medical students (n=142) using convenience sampling to describe the preferred learning styles. The qualitative phase utilised three focus group discussions (FGD) to explore in depth on the multimodal learning style exhibited by the students. Most students preferred combination of learning stylesthat is reflective, sensing, visual and sequential i.e.: RSVISeq style (24.64%) from the ILS analysis. The frequency of learning preference from processing to understanding were well balanced, with sequential-global domain (66.2%); sensing-intuitive (59.86%), active- reflective (57%), and visual-verbal (51.41%). The qualitative data reported three major themes, namely Theme 1: CBL mixed modalities navigates learners’ learning style; Theme 2: Multimodal learners active learning strategies supports learning. Theme 3: CBL modalities facilitating theory into clinical knowledge. Both quantitative and qualitative study strongly reports the multimodal learning style of the year one medical students. Medical students utilise multimodal learning styles to attain the clinical knowledge when learning with CBL mixed modalities. Educators’ awareness of the multimodal learning style is crucial in delivering the CBL mixed modalities effectively, considering strategic pedagogical support students to engage and learn CBL in bridging the theoretical knowledge into clinical practice.

Keywords: case-based learning, learnign style, medical students, learning

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Authors: E. N. R. de Silva

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The main purpose of this research is to set a policy framework for establishing a legal, institutional and social infrastructure that enhances the welfare, health, safety and economic interest of the consumers in Sri Lanka. It will help to develop an approach to continuously and successfully advocate for a consumer protection legal reform agenda and also it is significant as it gives directions to create national consumer protection associations in Sri Lanka. The methodology adopted for this research is purely a qualitative approach and it is generally and specifically categorized. Generally, part of this research looked at the existing laws, regulations and how effective they are in order to protect consumers. It will analyze the consumer protection framework and specially, consumer protection enhanced by the public organizations in Japan. This research offers a model with methods and legal instruments to enforce advocacy group to enhance consumer welfare, also brings out reforms to be made in the national legal framework on consumer welfare.

Keywords: consumer protection association, consumer protection law, consumer welfare, legal framework

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Authors: Bryan Jenkins

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Introduction: The expansion of irrigation in the Canterbury region has led to the sustainability limits being reached for water availability and the cumulative effects of land use intensification. The institutional framework under New Zealand’s Resource Management Act was found to be an inadequate basis for managing water at sustainability limits. An alternative paradigm for water management was developed based on collaborative governance and nested adaptive systems. This led to the formulation and implementation of the Canterbury Water Management Strategy. Methods: The nested adaptive system approach was adopted. Sustainability issues were identified at multiple spatial and time scales and defined potential failure pathways for the water resource system. These included biophysical and socio-economic issues such as water availability, cumulative effects on water quality due to land use intensification, projected changes in climate, public health, institutional arrangements, economic outcomes and externalities, and, social effects of changing technology. This led to the derivation of sustainability strategies to address these failure pathways. The collaborative governance approach involved stakeholder participation and community engagement to decide on a regional strategy; regional and zone committees of community and rūnanga (Māori groups) members to develop implementation programmes for the strategy; and, farmer collectives for operational management. Findings: The strategy identified improvements in the efficiency of use of water already allocated was more effective in improving water availability than a reliance on increased storage alone. New forms of storage with less adverse impacts were introduced, such as managed aquifer recharge and off-river storage. Reductions of nutrients from land use intensification by improving management practices has been a priority. Solutions packages for addressing the degradation of vulnerable lakes and rivers have been prepared. Biodiversity enhancement projects have been initiated. Greater involvement of Māori has led to the incorporation of kaitiakitanga (resource stewardship) into implementation programmes. Emerging issues are the need for improved integration of surface water and groundwater interactions, increased use of modelling of water and financial outcomes to guide decision making, and, equity in allocation among existing users as well as between existing and future users. Conclusions: However, sustainability analysis indicates that the proposed levels of management interventions are not sufficient to achieve community targets for water management. There is a need for more proactive recovery and rehabilitation measures. Managing to environmental limits is not sufficient, rather managing adaptive cycles is needed. Better measurement and management of water use efficiency is required. Proposed implementation packages are not sufficient to deliver desired water quality outcomes. Greater attention to targets important to environmental and recreational interests is needed to maintain trust in the collaborative process. Implementation programmes don’t adequately address climate change adaptations and greenhouse gas mitigation. Affordability is a constraint on adaptive capacity of farmers and communities. More funding mechanisms are required to implement proactive measures. The legislative and institutional framework needs to be changed to incorporate water framework legislation, regional sustainability strategies and water infrastructure coordination.

Keywords: collaborative governance, irrigation management, nested adaptive systems, sustainable water management

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Authors: Marc Dorval, Marie-Hélène Jobin

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This work presents the various perspectives, dimensions, components and definitions given to quality in the operations management (OM) and healthcare services (HCS) literature in time, highlighting gaps and learning opportunities between the two disciplines through a thorough search into their rich and distinct body of knowledge. Greater and new insights about the general nature of quality are obtained with findings such as in OM, quality has been approached in six fairly distinct paradigms (excellence, value, conformity to specifications, attributes, satisfaction and meeting or exceeding customer expectations), whereas in HCS, two approaches are prominent (Donabedian’s structure, process and outcomes model and Lohr and Schroeder’s circumscribed definition). The two disciplines views on quality seem to have progressed much in parallel with little cross-learning from each other. This work then proposes an encompassing definition of quality as a lever and suggests further research and development avenues for a better use of the concept of quality by academics and practitioners alike toward the goals of greater organizational performance and improved management in healthcare and possibly other service domains.

Keywords: healthcare, management, operations, quality, services

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Authors: Nirmani Wijenayake, Louise Lutze-Mann, Lucy Jo, John Wilson, Vivian Yeung, Dean Lovett, Kim Snepvangers

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Sessional academic staff at universities have the most influence and impact on student learning, engagement, and experience as they have the most direct contact with undergraduate students. A blended technology-enhanced program was created for the development and support of sessional staff to ensure adequate training is provided to deliver quality educational outcomes for the students. This program combines innovative mixed media educational modules, a peer-driven support forum, and face-to-face workshops to provide a comprehensive training and support package for staff. Additionally, the program encourages the development of learning communities and peer mentoring among the sessional staff to enhance their support system. In 2018, the program was piloted on 100 sessional staff in the School of Biotechnology and Biomolecular Sciences to evaluate the effectiveness of this model. As part of the program, rotoscope animations were developed to showcase ‘typical’ interactions between staff and students. These were designed around communication, confidence building, consistency in grading, feedback, diversity awareness, and mental health and wellbeing. When surveyed, 86% of sessional staff found these animations to be helpful in their teaching. An online platform (Moodle) was set up to disseminate educational resources and teaching tips, to host a discussion forum for peer-to-peer communication and to increase critical thinking and problem-solving skills through scenario-based lessons. The learning analytics from these lessons were essential in identifying difficulties faced by sessional staff to further develop supporting workshops to improve outcomes related to teaching. The face-to-face professional development workshops were run by expert guest speakers on topics such as cultural diversity, stress and anxiety, LGBTIQ and student engagement. All the attendees of the workshops found them to be useful and 88% said they felt these workshops increase interaction with their peers and built a sense of community. The final component of the program was to use an adaptive e-learning platform to gather feedback from the students on sessional staff teaching twice during the semester. The initial feedback provides sessional staff with enough time to reflect on their teaching and adjust their performance if necessary, to improve the student experience. The feedback from students and the sessional staff on this model has been extremely positive. The training equips the sessional staff with knowledge and insights which can provide students with an exceptional learning environment. This program is designed in a flexible and scalable manner so that other faculties or institutions could adapt components for their own training. It is anticipated that the training and support would help to build the next generation of educators who will directly impact the educational experience of students.

Keywords: designing effective instruction, enhancing student learning, implementing effective strategies, professional development

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Authors: Hoong C. Chin, Soon H. Chew, Zhaoxia Wang

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Work on sustainable developments and the call for action in education for sustainable development have been ongoing for a number of years. Training engineering students with the relevant competencies, particularly in sustainable development literacy, has been identified as an urgent task in universities. This requires not only a holistic, multi-disciplinary approach to education but also a suitable training environment to develop the needed skills and to inculcate the appropriate attitudes in students towards sustainable development. To demonstrate how this can be done, a module involving an overseas field trip was introduced in 2013 at the National University of Singapore. This paper provides details of the module and describes its training philosophy and methods. Measured against the student learning outcomes, stipulated by the Engineering Accreditation Board, the module scored well on all of them, particularly those related to complex problem solving, environmental and sustainability awareness, multi-disciplinary team work and varied-level communications.

Keywords: civil engineering education, socio-economically sustainable infrastructure, student learning outcome, sustainable development

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Authors: Dennis Infante

Abstract:

This paper examined the reflections of teachers on curriculum reforms, the implementation of the K-12 Basic Education Program in the Philippines. The results revealed that problems and concerns raised by teachers could be classified into curriculum materials and design; competence, readiness and motivation of the teachers; the learning environment, and support systems; readiness, competence and motivation of students; and other relevant factors. The best features of the K-12 curriculum reforms included (1) the components, curriculum materials; (2) the design, structure and delivery of the lessons; (3) the framework and theoretical approach; (3) the qualities of the teaching-learning activities; (4) and other relevant features. With the demanding task of implementing the new curriculum, the teachers expressed their needs which included (1) making the curriculum materials available to achieve the goals of the curriculum reforms; (2) enrichment of the learning environments; (3) motivating and encouraging the teachers to embrace change; (4) providing appropriate support systems; (5) re-tooling, and empowering teachers to implement the curriculum reforms; and (6) other relevant factors. The research concluded with a synthesis that provided a paradigm for implementing curriculum reforms which recognizes the needs of the teachers and the features of the new curriculum.

Keywords: curriculum reforms, K-12, teachers' reflections, implementing curriculum change

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Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

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Authors: Sakae Suzuki

Abstract:

Although Japanese students study English for six years in secondary schools, they demonstrate little success with it when they enter higher education. Learners’ beliefs can predict the future behavior of students, so it may be effective to investigate how learners’ beliefs limit their success and how beliefs might be nudged in a positive direction. While many researchers still depend on a questionnaire called BALLI to reveal explicit beliefs, alternative approaches, especially those designed to reveal implicit beliefs, might be helpful for promoting learning. The present study seeks to identify beliefs with a discursive approach using visual metaphors and narratives. Employing a sociocultural framework, this study investigates how students’ beliefs are revealed by drawings of themselves and their surrounding environments and artifacts while they are engaged in language learning. Research questions are: (1) Can we identify beliefs through an analysis of students’ visual narratives? (2) What environments and artifacts can be found in students’ drawings, and what do they mean? (3) To what extent do students see language learning as a solitary, rather than a social, activity? Participants are university students majoring in science and technology in Japan. The questionnaire was administered to 70 entering students in April, 2014. Data included students drawings of themselves as learners of English as well as written descriptions of students’ backgrounds, English-learning experiences, and analogies and metaphors that they used in written descriptions of themselves as learners. Data will be analyzed qualitatively and quantitatively. Anticipated results include students’ perceptions of themselves as language learners, including their sense of agency, awareness of artifacts, and social contexts of language learning. Comments will be made on implications for teaching, as well as the use of visual narratives as research tools, and recommended further research.

Keywords: drawings, learners' beliefs, metaphors, BALLI

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Authors: Islam Elsayed Hussein

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The aim of this paper is to discover the impact of students’ attitude towards social media and the skills required to adopt social media as a university e-learning (2.0) platform. In addition, it measures the effect of social media adoption on interactive learning effectiveness. The population of this study was students at Faculty of tourism and Hotels, Fayoum University. A questionnaire was used as a research instrument to collect data from respondents, which had been selected randomly. Data had been analyzed using quantitative data analysis method. Findings showed that the students have a positive attitude towards adopting social networking in the learning process and they have also good skills for effective use of social networking tools. In addition, adopting social media is effectively affecting the interactive learning environment.

Keywords: attitude, skills, e-learning 2.0, interactive learning, Egypt

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Authors: A. Giannakopoulos, S. B. Buckley

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Problem solving in any field is recognised as a prerequisite for any advancement in knowledge. For example in South Africa it is one of the seven critical outcomes of education together with critical thinking. As a systematic way to problem solving was initiated in mathematics by the great mathematician George Polya (the father of problem solving), more detailed and comprehensive ways in problem solving have been developed. This paper is based on the findings by the author and subsequent recommendations for further research in problem solving and critical thinking. Although the study was done in mathematics, there is no doubt by now in almost anyone’s mind that mathematics is involved to a greater or a lesser extent in all fields, from symbols, to variables, to equations, to logic, to critical thinking. Therefore it stands to reason that mathematical principles and learning cannot be divorced from any field. In management of knowledge situations, the types of problems are similar to mathematics problems varying from simple to analogical to complex; from well-structured to ill-structured problems. While simple problems could be solved by employees by adhering to prescribed sequential steps (the process), analogical and complex problems cannot be proceduralised and that diminishes the capacity of the organisation of knowledge creation and innovation. The low efficiency in some organisations and the low pass rates in mathematics prompted the author to view problem solving as a product. The authors argue that using mathematical approaches to knowledge management problem solving and treating problem solving as a product will empower the employee through further training to tackle analogical and complex problems. The question the authors asked was: If it is true that problem solving and critical thinking are indeed basic skills necessary for advancement of knowledge why is there so little literature of knowledge management (KM) about them and how they are connected and advance KM?This paper concludes with a conceptual model which is based on general accepted principles of knowledge acquisition (developing a learning organisation), knowledge creation, sharing, disseminating and storing thereof, the five pillars of knowledge management (KM). This model, also expands on Gray’s framework on KM practices and problem solving and opens the doors to a new approach to training employees in general and domain specific areas problems which can be adapted in any type of organisation.

Keywords: critical thinking, knowledge management, mathematics, problem solving

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Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra

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In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of Artificial Intelligence (AI), specifically Deep Learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our pioneering approach introduces a hybrid model, amalgamating the strengths of two renowned Convolutional Neural Networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging

Procedia PDF Downloads 87

Authors: Libor Zachoval, Daire O Broin, Oisin Cawley

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E-learning platforms, such as Blackboard have two major shortcomings: limited data capture as a result of the limitations of SCORM (Shareable Content Object Reference Model), and lack of incorporation of Artificial Intelligence (AI) and machine learning algorithms which could lead to better course adaptations. With the recent development of Experience Application Programming Interface (xAPI), a large amount of additional types of data can be captured and that opens a window of possibilities from which online education can benefit. In a corporate setting, where companies invest billions on the learning and development of their employees, some learner behaviours can be troublesome for they can hinder the knowledge development of a learner. Behaviours that hinder the knowledge development also raise ambiguity about learner’s knowledge mastery, specifically those related to gaming the system. Furthermore, a company receives little benefit from their investment if employees are passing courses without possessing the required knowledge and potential compliance risks may arise. Using xAPI and rules derived from a state-of-the-art review, we identified three learner behaviours, primarily related to guessing, in a corporate compliance course. The identified behaviours are: trying each option for a question, specifically for multiple-choice questions; selecting a single option for all the questions on the test; and continuously repeating tests upon failing as opposed to going over the learning material. These behaviours were detected on learners who repeated the test at least 4 times before passing the course. These findings suggest that gauging the mastery of a learner from multiple-choice questions test scores alone is a naive approach. Thus, next steps will consider the incorporation of additional data points, knowledge estimation models to model knowledge mastery of a learner more accurately, and analysis of the data for correlations between knowledge development and identified learner behaviours. Additional work could explore how learner behaviours could be utilised to make changes to a course. For example, course content may require modifications (certain sections of learning material may be shown to not be helpful to many learners to master the learning outcomes aimed at) or course design (such as the type and duration of feedback).

Keywords: artificial intelligence, corporate e-learning environment, knowledge maintenance, xAPI

Procedia PDF Downloads 121

Authors: N. Paparisteidi, D. Rodamitou

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This article focuses on the skills development and path planning of students studying computer science in EPITECH: french private institute of Higher Education. The researchers examine students’ points of view and experience in a blended learning model based on a skills development curriculum. The study is based on the collection of four main categories of data: semi-participant observation, distribution of questionnaires, interviews, and analysis of internal school databases. The findings seem to indicate that a skills-based program on active learning enables students to develop their learning strategies as well as their personal skills and to actively engage in the creation of their career path and contribute to providing additional information to curricula planners and decision-makers about learning design in higher education.

Keywords: active learning, blended learning, higher education, skills development

Procedia PDF Downloads 104

Authors: Patrick Mbassegue, Mickael Gardoni

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In a market environment centered more and more on services and the digital economy, knowledge management becomes a framework that can help organizations to create value and to improve their overall performance. Based on an optimal allocation of scarce resources, managers are interested in demonstrating the added value generated by knowledge management projects. One of the challenges faced by organizations is the difficulty in measuring impacts and concrete results of knowledge management initiatives. The present article concerns the measure of concrete results coming from knowledge management projects based on balance scorecard model. One of the goals is to underline what can be done based on this model but also to highlight the limits associated. The present article is structured in five parts; 1-knowledge management projects and organizational impacts; 2- a framework and a methodology to measure organizational impacts; 3- application illustrated in two case studies; 4- limits concerning the proposed framework; 5- the proposal of a new framework to measure organizational impacts.

Keywords: knowledge management, project, balance scorecard, impacts

Procedia PDF Downloads 262

Authors: Robin Ferguson

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The context which this paper explores is the provision of Technical Vocational Education and Training (TVET) of southern African workers at sea on local and foreign vessels using a blended learning approach. The pedagogical challenge of providing quality education in this context is that multiple African and foreign languages and cultural norms are found amongst the all-male crew; and there are widely differing levels of education, low levels of digital literacy and limited connectivity. The methodology used is a nested case study. The study describes the mechanisms used to provide ongoing, real-time workplace TVET on two foreign vessels. Some training was done in person when the vessels came into port, however, the majority of the TVET was achieved from shore to ship using a combination of commonly available Google and Microsoft Apps and WhatsApp. Voice, video and text in multiple languages were used to accommodate different learning styles. The learning was supported by the development of learning networks using social media. This paper also reflects on the shore-based organisational change processes required to support sea learning. The conceptual framework used is the Theory of Practice Architectures (TPA) as is provides a site-ontological perspective of the sayings/thinkings, doings and relatings of this workplace training which is multiplanar as it plays out at sea and ashore, in-person and on-line. Using TPA, the overarching practice architectures and supporting structures which confound or enable these learning practices are revealed. The contribution which this paper makes is an insight into an innovative vocational pedagogy which promotes ICT-mediated learning amongst workers who suffer from low levels of literacies and limited ICT-access and who work and live in remote places. It is a pedagogy of possibility which crosses the digital divide.

Keywords: theory of practice architecture, microsoft, google, whatsapp, vocational pedagogy, mariners, distributed workplaces

Procedia PDF Downloads 81

Authors: Jacqueline Żammit

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Online learning has become more popular as a substitute for traditional classroom instruction because of the COVID-19 epidemic. The study aimed to investigate how adult Maltese language learners evaluated the benefits and drawbacks of online instruction. 35 adult participants provided data through semi-structured interviews with open-ended questions. NVivo software was used to analyze the interview data using the thematic analysis method in order to find themes and group the data based on common responses. The advantages of online learning that the participants mentioned included accessing subject content even without live learning sessions, balancing learning with household duties, and lessening vulnerability to problems like fatigue, time-wasting traffic, school preparation, and parking space constraints. Conversely, inadequate Internet access, inadequate IT expertise, a shortage of personal computers, and domestic distractions adversely affected virtual learning. Lack of an Internet connection, IT expertise, a personal computer, or a phone with Internet access caused inequality in access to online learning sessions. Participants thought online learning was a way to resume academic activity, albeit with drawbacks. In order to address the challenges posed by online learning, several solutions are proposed in the research's conclusion.

Keywords: adult learners, online education, e-learning, challenges of online learning, benefits ofonline learning

Procedia PDF Downloads 60

Authors: Nir Nissim, Ran Yahalom, Tomer Lancewiki, Yuval Elovici, Boaz Lerner

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Background: Attackers increasingly take advantage of innocent users who tend to use USB devices casually, assuming these devices benign when in fact they may carry an embedded malicious behavior or hidden malware. USB devices have many properties and capabilities that have become the subject of malicious operations. Many of the recent attacks targeting individuals, and especially organizations, utilize popular and widely used USB devices, such as mice, keyboards, flash drives, printers, and smartphones. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched via USB devices. Significance: We propose USBWARE, a project that focuses on the vulnerabilities of USB devices and centers on the development of a comprehensive detection framework that relies upon a crucial attack repository. USBWARE will allow researchers and companies to better understand the vulnerabilities and attacks associated with USB devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The framework of USBWARE is aimed at accurate detection of both known and unknown USB-based attacks by a process that efficiently enhances the framework's detection capabilities over time. The framework will integrate two main security approaches in order to enhance the detection of USB-based attacks associated with a variety of USB devices. The first approach is aimed at the detection of known attacks and their variants, whereas the second approach focuses on the detection of unknown attacks. USBWARE will consist of six independent but complimentary detection modules, each detecting attacks based on a different approach or discipline. These modules include novel ideas and algorithms inspired from or already developed within our team's domains of expertise, including cyber security, electrical and signal processing, machine learning, and computational biology. The establishment and maintenance of the USBWARE’s dynamic and up-to-date attack repository will strengthen the capabilities of the USBWARE detection framework. The attack repository’s infrastructure will enable researchers to record, document, create, and simulate existing and new USB-based attacks. This data will be used to maintain the detection framework’s updatability by incorporating knowledge regarding new attacks. Based on our experience in the cyber security domain, we aim to design the USBWARE framework so that it will have several characteristics that are crucial for this type of cyber-security detection solution. Specifically, the USBWARE framework should be: Novel, Multidisciplinary, Trusted, Lightweight, Extendable, Modular and Updatable and Adaptable. Major Findings: Based on our initial survey, we have already found more than 23 types of USB-based attacks, divided into six major categories. Our preliminary evaluation and proof of concepts showed that our detection modules can be used for efficient detection of several basic known USB attacks. Further research, development, and enhancements are required so that USBWARE will be capable to cover all of the major known USB attacks and to detect unknown attacks. Conclusion: USBWARE is a crucial detection framework that must be further enhanced and developed.

Keywords: USB, device, cyber security, attack, detection

Procedia PDF Downloads 398

Authors: Neneng Hayatul Milah

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The most important reading skill for students is comprehension. Understanding the reading text will have an impact on learning outcomes. However, reading comprehension instruction in Indonesian elementary schools is lacking. A more effective learning model is needed to enhance students' reading comprehension. This study aimed to evaluate the effectiveness of the CIRC (Cooperative Integrated Reading and Composition) model with Padlet integration in improving the reading comprehension skills of grade IV students in elementary schools in Cimahi City, Indonesia. This research methodology was quantitative with a pre-experiment research type and one group pretest-posttest research design. The sample of this study consisted of 30 students. The results of statistical analysis showed that there was a significant effect of using the CIRC learning model using Padlet on improving students' reading comprehension skills of narrative text. The mean score of students' pretest was 67.41, while the mean score of the posttest increased to 84.82. The paired sample t-test resulted in a t-count score of -13.706 with a significance score of <0.001, which is smaller than α = 0.05. This research is expected to provide useful insights for educational practitioners on how the use of the CIRC model using Padlet can improve the reading comprehension skills of elementary school students.

Keywords: reading comprehension skills, CIRC, Padlet, narrative text

Procedia PDF Downloads 33

Authors: Syamsul Syafiq, Maslina Daud, Hafizah Hasan, Ahmad Zairi, Shazil Imri, Ezaini Akmar, Norbazilah Rahim

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Over recent years, web development has changed significantly. Driven largely by the rise of trends like mobiles, the world of development is rapidly evolving. The rise of the Internet makes web applications crucial nowadays. The web application has been an interface for a company and one of the ways they present their portfolio to the client. On the other hand, the web has become part of the file management system which takes over the role of paper. Due to high demand in web applications, developers are required to develop a web application that are cost-effective, secure and well coded. A framework has been proposed to develop an application rather than using library style development. The framework is helping the developer in creating the structure of a web automatically. This paper will compare the advantages and disadvantages of web development using framework against library-style development. This comparison is based on a previous research paper focusing on two main indicators, which are the impact to management and impact to the developer.

Keywords: framework, library style development, web application development, traditional web, static web, dynamic web

Procedia PDF Downloads 224