Search results for: learning evaluation

Authors: Nils Haglund, Svenolof Dahlgren, Maria Rastam, Peik Gustafsson, Karin Kalien

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In Sweden, like in most developed countries, there is a substantial increase of children diagnosed with autism and other conditions within the autism spectrum (ASD). The rapid increase of ASD rates stresses the importance of developing care programs to provide support and comprehensive interventions for affected families. The current observational study was conducted in order to evaluate an ongoing Comprehensive Intensive Early Intervention (CIEI) program for children with autism in southern Sweden. The change in autism symptoms among children participating in CIEI (intervention group, n=67) was compared with children who received traditional habilitation services only (comparison group, n=27). Children of parents who accepted the offered CIEI-program, constituted the intervention group, whereas children, whose parents (for some reason) were not interested in the offered CIEI-program, constituted the comparison group. The CIEI-program was individualized to each child by experienced applied behavior analysis (ABA) specialists with different backgrounds as psychologists, speech pathologists or special education teachers, in cooperation with parents and preschool staff. Due to the individualization, the intervention could vary in intensity and techniques. The intensity was calculated to 15-25 hours each week at home and the preschool altogether. Each child was assigned one 'trainer', who was often employed as a preschool teacher but could have another educational background. An agreement between supervisor- parents and preschool staff was reached to confirm the intensity and content of the CIEI- program over an approximately two-year intervention period. Symptom changes were measured as evaluation-ADOS-2-scores, total- and severity-scores, minus the corresponding baseline-scores, divided by the time between baseline and evaluation. The difference between the study-groups regarding change of ADOS-2-scores was estimated using ANCOVA. In the current study, children in the CIEI-group improved their ADOS-2-total scores between baseline and evaluation (-0.8 scores per year; 95%CI: -1.2 to -0.4), whereas no such improvement was detected in the comparison group (+0.1 scores per year; 95%CI: -0.7 to +0.9). The change difference (change in the CIEI-group vs. change in the comparison group) was statistically significant, both crude and after adjusting for possible confounders (-1.1; 95%CI -1.9 to -0.4). Children in the CIEI-group also significantly improved their ADOS-calibrated severity scores, but not significantly differently so from the comparison group. The results from the current study indicate that the CIEI program significantly improves social and communicative skills among children with autism and that children with developmental delay could benefit to a similar degree as other children. The results support earlier studies reporting on the improvement of autism symptoms after early intensive interventions. The results from observational studies are difficult to interpret, but it is nevertheless of uttermost importance to evaluate costly autism intervention programs. Such results may be of immediate importance to healthcare organizations when allocating the already strained resources to different patient groups. Albeit the obvious limitation of the current naturalistic study, the results support previous positive studies and indicate that children with autism benefit from participating in early comprehensive, intensive programs and that investments in these programs may be highly justifiable.

Keywords: autism symptoms, ADOS-scores, evaluation, intervention program

Procedia PDF Downloads 141

Authors: Francesca Carta, Giovanna Linfante, Laura Agneni, Debora Radicchia, Camilla Micheletta, Angelo Del Cimmuto

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Overtaking competence mismatches and fostering career pathways congruent with the individual skills profile would significantly contribute to fighting unemployment. The aim of this paper is to examine the usefulness and efficiency of qualitative tools in supporting and improving the quality of caseworkers’ activities during the jobseekers’ profile analysis and career guidance process. The selected target groups are long-term and middle term unemployed, job seekers, young people at the end of the vocational training pathway and unemployed woman with social disadvantages. The experimentation is conducted in Italy at public employment services in 2017. In the framework of Italian labour market reform, the experimentation represents the first step to develop a customized qualitative model profiling; the final general object is to improve the public employment services quality. The experimentation tests the transferability of an OECD self-assessment competences tool in the Italian public employment services. On one hand, the first analysis results will indicate the user’s perception concerning the tool’s application and their different competence levels (literacy, numeracy, problem solving, career interest, subjective well-being and health, behavioural competencies) with reference to the specific target. On the other hand, the experimentation outcomes will show caseworkers understanding regarding the tool’s usability and efficiency for career guidance and reskilling and upskilling programs.

Keywords: career guidance, evaluation competences, reskilling pathway, unemployment

Procedia PDF Downloads 316

Authors: Gul Rahim Rahimi

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The IoT-based soil moisture monitoring system for indoor plants is designed to address the challenges of maintaining optimal moisture levels in soil for plant growth and health. The system utilizes sensor technology to collect real-time data on soil moisture levels, which is then processed and analyzed using machine learning algorithms. This allows for accurate and timely monitoring of soil moisture levels, ensuring plants receive the appropriate amount of water to thrive. The main objectives of the system are twofold: to keep plants fresh and healthy by preventing water deficiency and to provide users with comprehensive insights into the water content of the soil on a daily and hourly basis. By monitoring soil moisture levels, users can identify patterns and trends in water consumption, allowing for more informed decision-making regarding watering schedules and plant care. The scope of the system extends to the agriculture industry, where it can be utilized to minimize the efforts required by farmers to monitor soil moisture levels manually. By automating the process of soil moisture monitoring, farmers can optimize water usage, improve crop yields, and reduce the risk of plant diseases associated with over or under-watering. Key technologies employed in the system include the Capacitive Soil Moisture Sensor V1.2 for accurate soil moisture measurement, the Node MCU ESP8266-12E Board for data transmission and communication, and the Arduino framework for programming and development. Additionally, machine learning algorithms are utilized to analyze the collected data and provide actionable insights. Cloud storage is utilized to store and manage the data collected from multiple sensors, allowing for easy access and retrieval of information. Overall, the IoT-based soil moisture monitoring system offers a scalable and efficient solution for indoor plant care, with potential applications in agriculture and beyond. By harnessing the power of IoT and machine learning, the system empowers users to make informed decisions about plant watering, leading to healthier and more vibrant indoor environments.

Keywords: IoT-based, soil moisture monitoring, indoor plants, water management

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Authors: Yash Goyal, Manish Korde, Juned Siddiqui

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Today online education has gained more popularity so that people can easily complete their curriculum on their own time. Virtual learning has been widely used by many educators, especially in higher education institutions due to its benefits to students and faculty. A good knowledge of teaching theory and instructional design systems is required to experience meaningful learning. However, most educational websites are not designed to adapt to all screen sizes. Making the website accessible on all screen sizes is our main objective, so we have created a website that is readily accessible across all screen sizes and accepts all types of payment methods. And we see generally educational websites interface is simple and unexciting. So, we have made a user interface attractive and user friendly. It is not enough for a website to be user-friendly, but also to be familiar to admins and to reduce the workload of the admin as well. We visited so many popular websites under development that they all had issues like responsiveness, simple interface, security measures, payment methods, etc. To overcome this limitation, we have created a website which has taken care of security issues that is why we have created only one admin id and it can be control from that only. And if the user has successfully done the payment, then the admin can send him a username and password through mail individually so there will no fraud in the payment of the course.

Keywords: responsive, accessible, attractive, interface, objective, security.

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Authors: Parisa Mansour

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Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

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Authors: Maha Rashid Al-Azib, Almuzn Qasem Alqathradi, Amal Munir Alshahrani, Bilqis Mohammed Assiri, Ali Almuflih

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The Occupational Safety and Health Management System in one of the largest Saudi companies has been experiencing in the last 10 years extensive direct and indirect expenses due to lack of proactive leading indicators and safety leadership effective procedures. And since there are no studies that are associated with this department of safety in the company, this research has been conducted. In this study we used a mixed method approach containing a literature review and experts input, then a qualitative questionnaire provided by Institute for Work and Health related to determining the company’s occupational safety and health management system level out from three levels (Compliance - Improvement - Continuous Learning) and the output regarding the company’s level was in Continuous Learning. After that Deming cycle was employed to create a set of proactive leading indicators and analyzed using the SMART method to make sure of its effectiveness and suitability to the company. The objective of this research is to provide a set of proactive indicators to contribute in making an efficient occupational safety and health management system that has less accidents which results in less expenses. Therefore, we provided the company with a prototype of an APP, designed and empowered with our final results to contribute in supporting decisions making processes.

Keywords: proactive leading indicators, OSH MS, safety leadership, accidents reduction

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Authors: Lauren McGillivray, Michelle Torok, Alison Calear

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Suicide is the leading cause of death for Australians aged 15-24 years, with rates increasing over the past decade. As young people can be particularly vulnerable to mental health problems and suicidal behavior, they are an essential and obvious target for suicide prevention efforts. This study investigates the effectiveness of the universal mental health promotion and suicide prevention program, Youth Aware of Mental Health (YAM), to reduce suicidal ideation and attempts and increase help-seeking in young people. This trial took place in Australian schools across four regions in New South Wales that form part of LifeSpan, a larger multilevel suicide prevention research trial. The YAM program was delivered to Year 9 students in up to 78 schools over two years (from January 2017 to December 2019). All schools were invited to participate in YAM's evaluation, which included completing a student questionnaire at three time-points: baseline, 3-month post-intervention, and 6-month follow-up. The primary outcome is suicidal ideation severity. Secondary outcomes are new reports of suicide attempts, stigma towards suicide, knowledge about suicide, help-seeking intentions and behaviors, and depressive symptoms. Results from pre-post and follow-up data will be presented. These research findings are promising and will contribute to the evidence-based for YAM and suicide prevention programs in Australian schools. These findings are also expected to promote YAM's value and sustainability to be more widely delivered in Australian secondary schools.

Keywords: adolescent mental health, suicidal ideation, suicide prevention, universal program

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Authors: Suzan Ghaddar, Aline Pinon, Manuel Gallardo-villagran, Mona Diab-assaf, Bruno Therrien, Bertrand Liagre

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Colorectal cancer (CRC) is the third most common cancer and exhibits a consistently rising incidence worldwide. Despite notable advancements in CRC treatment, frequent occurrences of side effects and the development of therapy resistance persistently challenge current approaches. Eventually, innovations in focal therapies remain imperative to enhance the patient’s overall quality of life. Photodynamic therapy (PDT) emerges as a promising treatment modality, clinically used for the treatment of various cancer types. It relies on the use of photosensitive molecules called photosensitizers (PS), which are photoactivated after accumulation in cancer cells, to induce the production of reactive oxygen species (ROS) that cause cancer cell death. Among commonly used metal-based drugs in cancer therapy, ruthenium (Ru) possesses favorable attributes that demonstrate its selectivity towards cancer cells and render it suitable for anti-cancer drug design. In vitro studies using distinct arene-Ru complexes, encapsulating porphin PS, are conducted on human HCT116 and HT-29 colorectal cancer cell lines. These studies encompass the evaluation of the antiproliferative effect, ROS production, apoptosis, cell cycle progression, molecular localization, and protein expression. Preliminary results indicated that these complexes exert significant photocytotoxicity on the studied colorectal cancer cell lines, representing them as promising and potential candidates for anti- cancer agents.

Keywords: colorectal cancer, photodynamic therapy, photosensitizers, arene-ruthenium complexes, apoptosis

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Authors: Floriane Shala, Evangeline Wagner, Yichun Zhao

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Background: Proper educational training and support are proven to be major components of EHR (Electronic Health Record) implementation and use. However, the majority of health providers are not sufficiently trained in EHR use, leading to adverse events, errors, and decreased quality of care. In response to this, students studying Health Information Science, Public Health, Nursing, and Medicine should all gain a thorough understanding of EHR use at different levels for different purposes. The design of a usable and safe EHR system that accommodates the needs and workflows of different users, user groups, and disciplines is required for EHR learning to be efficient and effective. Objectives: This project builds several artifacts which seek to address both the educational and usability aspects of an educational EHR. The artifacts proposed are models for and examples of such an EHR with a configurable UI to be learned by students who need a background in EHR use during their degrees. Methods: Review literature and gather professional opinions from domain experts on usability, the use of workflow patterns, UI configurability and design, and the educational aspect of EHR use. Conduct interviews in a semi-casual virtual setting with open discussion in order to gain a deeper understanding of the principal aspects of EHR use in educational settings. Select a specific task and user group to illustrate how the proposed solution will function based on the current research. Develop three artifacts based on the available research, professional opinions, and prior knowledge of the topic. The artifacts capture the user task and user’s interactions with the EHR for learning. The first generic model provides a general understanding of the EHR system process. The second model is a specific example of performing the task of MRI ordering with a configurable UI. The third artifact includes UI mock-ups showcasing the models in a practical and visual way. Significance: Due to the lack of educational EHRs, medical professionals do not receive sufficient EHR training. Implementing an educational EHR with a usable and configurable interface to suit the needs of different user groups and disciplines will help facilitate EHR learning and training and ultimately improve the quality of patient care.

Keywords: education, EHR, usability, configurable

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Authors: Lancer Scott

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Purpose: High quality clinical disaster medicine requires providers working collaboratively to care for multiple patients in chaotic environments; however, many providers lack adequate training. To address this deficit, we created a competency-based, 5-hour Emergency Preparedness Training (EPT) curriculum using didactics, small-group discussion, and kinetic learning. The goal was to evaluate the effect of a short course on improving provider knowledge, confidence and skills in disaster scenarios. Methods: Diverse groups of medical university students, health care professionals, and community members were enrolled between 2011 and 2014. The course consisted of didactic lectures, small group exercises, and two live, multi-patient mass casualty incident (MCI) scenarios. The outcome measures were based on core competencies and performance objectives developed by a curriculum task force and assessed via trained facilitator observation, pre- and post-testing, and a course evaluation. Results: 708 participants completed were trained between November 2011 and August 2014, including 49.9% physicians, 31.9% medical students, 7.2% nurses, and 11% various other healthcare professions. 100% of participants completed the pre-test and 71.9% completed the post-test, with average correct answers increasing from 39% to 60%. Following didactics, trainees met 73% and 96% of performance objectives for the two small group exercises and 68.5% and 61.1% of performance objectives for the two MCI scenarios. Average trainee self-assessment of both overall knowledge and skill with clinical disasters improved from 33/100 to 74/100 (overall knowledge) and 33/100 to 77/100 (overall skill). The course assessment was completed by 34.3% participants, of whom 91.5% highly recommended the course. Conclusion: A relatively short, intensive EPT course can improve the ability of a diverse group of disaster care providers to respond effectively to mass casualty scenarios.

Keywords: clinical disaster medicine, training, hospital preparedness, surge capacity, education, curriculum, research, performance, training, student, physicians, nurses, health care providers, health care

Procedia PDF Downloads 190

Authors: Goldie Lynn Diaz, Ma. Teresa Tricia G. Bautista, Elisabeth Engeljakob, Mary Glaze Rosal

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Introduction: Residents are expected to convey unfavorable news, discuss prognoses, and relieve suffering, and address do-not-resuscitate orders, yet some report a lack of competence in providing this type of care. Recognizing this need, Family Medicine residency programs are incorporating end-of-life care from symptom and pain control, counseling, and humanistic qualities as core proficiencies in training. Objective: This study determined the competency of Family Medicine Residents from various institutions in Metro Manila on rendering care for the dying. Materials and Methods: Trainees completed a Palliative Care Evaluation tool to assess their degree of confidence in patient and family interactions, patient management, and attitudes towards hospice care. Results: Remarkably, only a small fraction of participants were confident in performing independent management of terminal delirium and dyspnea. Fewer than 30% of residents can do the following without supervision: discuss medication effects and patient wishes after death, coping with pain, vomiting and constipation, and reacting to limited patient decision-making capacity. Half of the respondents had confidence in supporting the patient or family member when they become upset. Majority expressed confidence in many end-of-life care skills if supervision, coaching and consultation will be provided. Most trainees believed that pain medication should be given as needed to terminally ill patients. There was also uncertainty as to the most appropriate person to make end-of-life decisions. These attitudes may be influenced by personal beliefs rooted in cultural upbringing as well as by personal experiences with death in the family, which may also affect their participation and confidence in caring for the dying. Conclusion: Enhancing the quality and quantity of end-of-life care experiences during residency with sufficient supervision and role modeling may lead to knowledge and skill improvement to ensure quality of care. Fostering bedside learning opportunities during residency is an appropriate venue for teaching interventions in end-of-life care education.

Keywords: end of life care, geriatrics, palliative care, residency training skill

Procedia PDF Downloads 255

Authors: Stijn Horck

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Background: The value of lessons learned from failure increases when these insights can be put to use by those who did not experience the failure. While learning from others has mostly been researched between individuals or teams within the same environment, transferring knowledge from the person who experienced the failure to an outsider comes with extra challenges. As sense-making of failure is an individual process leading to different learning experiences, the potential of lessons learned from failure is highly variable depending on who is transferring the lessons learned. Using an integrated framework of linguistic aspects related to attributional egotism, this study aims to offer a complete explanation of the challenges in transferring lessons learned from failures that are experienced by others. Method: A case study of a failed foundation established to address the information needs for GPs in times of COVID-19 has been used. An overview of failure causes and lessons learned were made through a preliminary analysis of data collected in two phases with metaphoric examples of failure types. This was followed up by individual narrative interviews with the board members who have all experienced the same events to analyse the individual variance of lessons learned through discourse analysis. This research design uses the researcher-as-instrument approach since the recipient of these lessons learned is the author himself. Results: Thirteen causes were given why the foundation has failed, and nine lessons were formulated. Based on the individually emphasized events, the explanation of the failure events mentioned by all or three respondents consisted of more linguistic aspects related to attributional egotism than failure events mentioned by only one or two. Moreover, the learning events mentioned by all or three respondents involved lessons learned that are based on changed insight, while the lessons expressed by only one or two are more based on direct value. Retrospectively, the lessons expressed as a group in the first data collection phase seem to have captured some but not all of the direct value lessons. Conclusion: Individual variance in expressing lessons learned to outsiders can be reduced using metaphoric or analogical explanations from a third party. In line with the attributional egotism theory, individuals separated from a group that has experienced the same failure are more likely to refer to failure causes of which the chances to be contradicted are the smallest. Lastly, this study contributes to the academic literature by demonstrating that the use of linguistic analysis is suitable for investigating the knowledge transfer from lessons learned after failure.

Keywords: failure, discourse analysis, knowledge transfer, attributional egotism

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Authors: James Banda, Jupiter Simbeye, Essau Chisale, Geoffrey Kanyerere, Kings Kamtambe

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Improved solar tent dryers for processing small fish species were designed to reduce post-harvest fish losses and improve supply of quality fish products in the southern part of Lake Malawi under CultiAF project. A comparative analysis of the quality of Diplotaxodon (Ndunduma) from Lake Malawi processed in solar tent dryer and open sun drying was conducted using proximate analysis, microbial analysis and sensory evaluation. Proximates for solar tent dried fish and open sun dried fish in terms of proteins, fats, moisture and ash were 63.3±0.15% and 63.3±0.34%, 19.6±0.09% and 19.9±0.25%, 8.3±0.12% and 17.0±0.01%, and 15.6±0.61% and 21.9±0.91% respectively. Crude protein and crude fat showed non-significant differences (p = 0.05), while moisture and ash content were significantly different (p = 001). Open sun dried fish had significantly higher numbers of viable bacteria counts (5.2×10⁶ CFU) than solar tent dried fish (3.9×10² CFU). Most isolated bacteria from solar tent dried and open sun dried fish were 1.0×10¹ and 7.2×10³ for Total coliform, 0 and 4.5 × 10³ for Escherishia coli, 0 and 7.5 × 10³ for Salmonella, 0 and 5.7×10² for shigella, 4.0×10¹ and 6.1×10³ for Staphylococcus, 1.0×10¹ and 7.0×10² for vibrio. Qualitative evaluation of sensory properties showed higher acceptability of 3.8 for solar tent dried fish than 1.7 for open sun dried fish. It is concluded that promotion of solar tent drying in processing small fish species in Malawi would support small-scale fish processors to produce quality fish in terms of nutritive value, reduced microbial contamination, sensory acceptability and reduced moisture content.

Keywords: diplotaxodon, Malawi, open sun drying, solar tent drying

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Authors: Francisca Margarita Ocran

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Underwear, and more particularly bras and panties, are defined as intimate clothing. Strictly speaking, they enhance the place of women in the public or private satchel. Therefore, women's lingerie is a complex garment with a high involvement profile, motivating consumers to buy it not only by its functional utility but also by the multisensory experience it provides them. Customer behavior models are generally based on customer data mining, and each model is designed to answer questions at a specific time. Predicting the customer experience is uncertain and difficult. Thus, knowledge of consumers' tastes in lingerie deserves to be treated as an experiential product, where the dimensions of the experience motivating consumers to buy a lingerie product and to remain faithful to it must be analyzed in detail by the manufacturers and retailers to engage and retain consumers, which is why this research aims to identify the variables that push consumers to choose their lingerie product, based on an in-depth analysis of the types of fabrics used to make lingerie. The data used in this study comes from online purchases. Machine learning approach with the use of Python programming language and Pycaret gives us a precision of 86.34%, 85.98%, and 84.55% for the three algorithms to use concerning the preference of a buyer in front of a range of lingerie. Gradient Boosting, random forest, and K Neighbors were used in this study; they are very promising and rich in the classification of preference in the textile industry.

Keywords: consumer behavior, data mining, lingerie, machine learning, preference

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Authors: Susan Catapano, Meredith Jones, Carol McNulty

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Analysis of one state’s collaborative effort to support teachers, in both public and private schools, as they moved from face-to-face teaching to remote teaching during the Covid pandemic to identify lessons learned and materials put into place to support teachers and families. Surveys were created, distributed, and analyzed throughout the three months of remote teaching, documents and lesson plans were developed, and training materials were created. All data collected and materials developed were analyzed to identify supports teachers used and needed for successful remote teaching. Researchers found most teachers easily moved to online teaching; however, many families did not have access to technology, so teachers needed to develop non-technology-based access and support for remote teaching. Teachers also reported the need to prepare to teach remotely as part of their teaching training, so they were prepared in the future. Finally, data indicated teachers were able to establish stronger relationships with families than usual as a result of remote teaching. The lessons learned and support developed are part of the state’s ongoing policy for online teaching in the event of disasters and pandemics in the future.

Keywords: remote learning, teacher education, pandemic, families

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Authors: Ahsan R. Khokhar, Fizza Hassan

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Alkali-Silica Reaction (ASR) has been recognized as a potential cause of concrete degradation in the world since the 1940s. In Pakistan, mega hydropower structures like dams, weirs constructed from aggregates extracted from a local riverbed exhibited different levels of alkali-silica reactivity over an extended service period. The concrete expansion potential due to such aggregates has been categorized as slow-reactive. Apart from hydropower structures, ASR existence has been identified in the concrete structural elements of a Textile Mill building which used aggregates extracted from the nearby riverbed. The original structure of the Textile Mill was erected in the 80s with the addition of a textile ‘sizing and wrapping’ hall constructed in the 90s. In the years to follow, intensive spalling was observed in the structural members of the subject hall; enough to threat to the overall stability of the building. Limitations such as incomplete building data posed hurdles during the detailed structural investigation. The paper lists observations made while assessing the extent of damage and its effect on the building hall structure. Core testing and Petrographic tests were carried out as per the ASTM standards for strength degradation analysis followed by the identifying its root cause. Results confirmed significant structural strength reduction because of ASR which necessitated the formulation of an immediate re-strengthening solution. The paper also discusses the possible tracks of rehabilitative measures which are being adapted to stabilize the structure and seize further concrete expansion.

Keywords: Alkali-Silica Reaction (ASR), concrete strength degradation, damage assessment, damage evaluation

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Authors: Juliana Altavista Sagretti Gallo, Susy Frey Sabato

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Despite the poverty in the world, a third of all food produced in the world is wasted. FAO, the United Nations Organization of Agriculture and Food, points out the need to combine actions and new technologies to combat hunger and waste in contrast to the high production of food in the world. The energy of ionizing radiation in food brought many positive results, such as increased validity and insect infestation control. The food banks are organizations that act at various points of the food chain to collect and distribute food to the needy. So, the aim of this study was to initiate a partnership between irradiation and the food bank through the development of a questionnaire to evaluate and disseminate the knowledge and acceptance of individuals in the food bank in Brazil. Also, this study aimed to standardize a basis questionnaire for future research assessment of irradiated foods. For the construction of the questionnaire as a measuring instrument, a comprehensive and rigorous literature review was made. It's covered qualitative research, questionnaires, sensory evaluation, and food irradiated. Three stages of pre - tests were necessary, and related fields of experts were consulted. As a result, the questionnaire has three parts, personal issues, assertive issues and questions of multiple choices and finally an informative question. The questionnaire was applied in Ceagesp food bank in the biggest center of food in Brazil. Conclusions. 30 % of participants of Ceagesp bank had already heard of the Food irradiation but did not know about the mechanism, so they rejected the idea to associate with radioactivity and danger. The video showed in the last question and application of the questionnaire disseminated the idea of security. All individuals declare understand the goal of treatment and accept buy and consume irradiated food after them.

Keywords: bank of food, questionary, irradiated food, acceptance of irradiated food

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Authors: Sirajdin Olagoke Adeshina, Haidi Ibrahim, Akeem Salawu

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large lecture theatres cannot be covered by a single camera but rather by a multicamera setup because of their size, shape, and seating arrangements. Although, classroom capture is achievable through a single camera. Therefore, a design and implementation of a multicamera setup for a large lecture hall were considered. Researchers have shown emphasis on the impact of class attendance taken on the academic performance of students. However, the traditional method of carrying out this exercise is below standard, especially for large lecture theatres, because of the student population, the time required, sophistication, exhaustiveness, and manipulative influence. An automated large classroom attendance system is, therefore, imperative. The common approach in this system is face detection and recognition, where known student faces are captured and stored for recognition purposes. This approach will require constant face database updates due to constant changes in the facial features. Alternatively, face counting can be performed by cropping the localized faces on the video or image into a folder and then count them. This research aims to develop a face localization-based approach to detect student faces in classroom images captured using a multicamera setup. A selected Haar-like feature cascade face detector trained with an asymmetric goal to minimize the False Rejection Rate (FRR) relative to the False Acceptance Rate (FAR) was applied on Raspberry Pi 4B. A relationship between the two factors (FRR and FAR) was established using a constant (λ) as a trade-off between the two factors for automatic adjustment during training. An evaluation of the proposed approach and the conventional AdaBoost on classroom datasets shows an improvement of 8% TPR (output result of low FRR) and 7% minimization of the FRR. The average learning speed of the proposed approach was improved with 1.19s execution time per image compared to 2.38s of the improved AdaBoost. Consequently, the proposed approach achieved 97% TPR with an overhead constraint time of 22.9s compared to 46.7s of the improved Adaboost when evaluated on images obtained from a large lecture hall (DK5) USM.

Keywords: automatic attendance, face detection, haar-like cascade, manual attendance

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Authors: Jay Ananth

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The drug discovery process currently requires numerous years of clinical testing as well as money just for a single drug to earn FDA approval. For drugs that even make it this far in the process, there is a very slim chance of receiving FDA approval, resulting in detrimental hurdles to drug accessibility. To minimize these inefficiencies, numerous studies have implemented computational methods, although few computational investigations have focused on a crucial feature of drugs: lipophilicity. Lipophilicity is a physical attribute of a compound that measures its solubility in lipids and is a determinant of drug efficacy. This project leverages Artificial Intelligence to predict the impact of a drug’s lipophilicity on its performance by accounting for factors such as binding affinity and toxicity. The model predicted lipophilicity and binding affinity in the validation set with very high R² scores of 0.921 and 0.788, respectively, while also being applicable to a variety of target receptors. The results expressed a strong positive correlation between lipophilicity and both binding affinity and toxicity. The model helps in both drug development and discovery, providing every pharmaceutical company with recommended lipophilicity levels for drug candidates as well as a rapid assessment of early-stage drugs prior to any testing, eliminating significant amounts of time and resources currently restricting drug accessibility.

Keywords: drug discovery, lipophilicity, ligand-receptor interactions, machine learning, drug development

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Authors: Cigdem Safak Saglam

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Most thermal power plants use steam as working fluid in their power cycle. Therefore, in addition to fuel, water is the other main input for thermal plants. Water and steam must be highly pure in order to protect the systems from corrosion, scaling and biofouling. Pure process water is produced in water treatment plants having many several treatment methods. Treatment plant design is selected depending on raw water source and required water quality. Although working principle of fossil-fuel fired thermal power plants are same, there is no standard design and equipment arrangement valid for all thermal power plant utility systems. Besides that, there are many other technology evaluation and selection criteria for designing the most optimal water systems meeting the requirements such as local conditions, environmental restrictions, electricity and other consumables availability and transport, process water sources and scarcity, land use constraints etc. Aim of this study is explaining the adopted methodology for technology selection for process water preparation and industrial waste water treatment plant in a thermal power plant project located in Tufanbeyli, Adana Province in Turkey. Thermal power plant is fired with indigenous lignite coal extracted from adjacent lignite reserves. This paper addresses all above-mentioned factors affecting the thermal power plant water treatment facilities (demineralization + waste water treatment) design and describes the ultimate design of Tufanbeyli Thermal Power Plant Water Treatment Plant.

Keywords: thermal power plant, lignite coal, pretreatment, demineralization, electrodialysis, recycling, ash dampening

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Authors: Soumya Mishra, Elena Neiterman

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Aligned with the growing interest in the impact of the pandemic on academic experiences of university students, this study aimed to examine the challenges Canadian undergraduate students experienced during the university closures due to COVID-19. Using qualitative methodological approach, the study utilized semi-structured interviews conducted with 20 undergraduate students enrolled in an Ontario university to explore their thoughts and experience regarding online learning during the peak of the COVID-19 pandemic, from January 2021 to March 2021. The interviews yielded four major themes with the following associated subthemes: Personal Challenges Associated with Adapting to the Pandemic (Change in the Type of Stress Experienced, Unique Impact on Certain Groups of Students, Decreased Motivation, Crucial Role of Resilience), Social Challenges Associated with Adapting to the Pandemic (Increased Loneliness, Challenges Faced while Communicating, Perception of Group work, Role of Living Conditions), Challenges associated with Accessing University Resources (Crucial Role of Professors, Perception of Virtual Events, Importance of Physical Spaces). Overall, the analysis showed that the COVID-19 pandemic fostered resilience and psychological flexibility amongst all students. However, the mental health and social wellbeing of students deteriorated during the COVID-19 pandemic and they reported experiencing chronic stress, anxiety and loneliness. International students, first year and final year students experienced a unique set of challenges. It was hard for participants in our study to make strong new connections with their classmates and maintain existing friendships with their peers. The importance of professors in facilitating learning was amplified in the online environment due to the lack of in-person interaction with other students. Despite these challenges, most participants reported that they received high grades during online learning. The findings from this study could be helpful for organizations and individuals working towards fostering the wellbeing of undergraduate students. They can also help in making post-secondary institutions more resilient to future emergencies by creating contingency plans regarding online instructions and risk management techniques.

Keywords: Canadian, COVID-19, university students, wellbeing

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Authors: Martin H¨ausl, Maximilian Auch, Johannes Forster, Peter Mandl, Alexander Schill

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In order to survive on the market, companies must constantly develop improved and new products. These products are designed to serve the needs of their customers in the best possible way. The creation of new products is also called innovation and is primarily driven by a company’s internal research and development department. However, a new approach has been taking place for some years now, involving external knowledge in the innovation process. This approach is called open innovation and identifies customer knowledge as the most important source in the innovation process. This paper presents a concept of using social media posts as an external source to support the open innovation approach in its initial phase, the Ideation phase. For this purpose, the social media posts are semantically structured with the help of an ontology and the authors are evaluated using graph-theoretical metrics such as density. For the structuring and evaluation of relevant social media posts, we also use the findings of Natural Language Processing, e. g. Named Entity Recognition, specific dictionaries, Triple Tagger and Part-of-Speech-Tagger. The selection and evaluation of the tools used are discussed in this paper. Using our ontology and metrics to structure social media posts enables users to semantically search these posts for new product ideas and thus gain an improved insight into the external sources such as customer needs.

Keywords: idea ontology, innovation management, semantic search, open information extraction

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Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

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The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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Authors: Isaac Benning

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Using technology to expand the learning space is critical for a productive mathematical discourse. This is a case study of two teachers who developed and enacted GeoGebra-based mathematics lessons following their engagement in a two-year professional development. The didactical and semiotic affordance of GeoGebra in widening the learning space for a productive mathematical discourse was explored. The approach of thematic analysis was used for lesson artefact, lesson observation, and interview data. The results indicated that constructing tools in GeoGebra provided a didactical milieu where students used them to explore mathematical concepts with little or no support from their teacher. The prompt feedback from the GeoGebra motivated students to practice mathematical concepts repeatedly in which they privately rethink their solutions before comparing their answers with that of their colleagues. The constructing tools enhanced self-discovery, team spirit, and dialogue among students. With regards to the semiotic construct, the tools widened the physical and psychological atmosphere of the classroom by providing animations that served as virtual concrete to enhance the recording, manipulation, testing of a mathematical idea, construction, and interpretation of geometric objects. These findings advance the discussion of widening the classroom for a productive mathematical discourse within the context of the mathematics curriculum of Ghana and similar Sub-Saharan African countries.

Keywords: GeoGebra, theory of didactical situation, semiotic mediation, mathematics laboratory, mathematical discussion

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Authors: Shital Patil, Surendra Bhosale

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Cardiac diseases are the leading causes of mortality and morbidity in the world, from recent few decades accounting for a large number of deaths have emerged as the most life-threatening disorder globally. Machine learning and Artificial intelligence have been playing key role in predicting the heart diseases. A relevant set of feature can be very helpful in predicting the disease accurately. In this study, we proposed a comparative analysis of 4 different features selection methods and evaluated their performance with both raw (Unbalanced dataset) and sampled (Balanced) dataset. The publicly available Z-Alizadeh Sani dataset have been used for this study. Four feature selection methods: Data Analysis, minimum Redundancy maximum Relevance (mRMR), Recursive Feature Elimination (RFE), Chi-squared are used in this study. These methods are tested with 8 different classification models to get the best accuracy possible. Using balanced and unbalanced dataset, the study shows promising results in terms of various performance metrics in accurately predicting heart disease. Experimental results obtained by the proposed method with the raw data obtains maximum AUC of 100%, maximum F1 score of 94%, maximum Recall of 98%, maximum Precision of 93%. While with the balanced dataset obtained results are, maximum AUC of 100%, F1-score 95%, maximum Recall of 95%, maximum Precision of 97%.

Keywords: cardio vascular diseases, machine learning, feature selection, SMOTE

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Authors: Jiangbo Hu, Frances Hoyte, Haiquan Huang

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Research identifies that mealtime talk can be a significant learning context that provides children with rich experiences to foster their language and cognitive development. Middle-classed parents create an extended learning discourse for their children through sophisticated vocabulary, narrative and explanation genres at dinner table. However, mealtime opportunities vary with some parents having little interaction with their children and some parents focusing on directive of children’s behaviors. This study investigated five Chinese families’ parent-child interaction during mealtime that was rarely reported in the literature. The five families differ in terms of their living styles. Three families are from professional background where both mothers the fathers work in Australian companies and both of them present at dinner time. The other two families own business. The mothers are housemakers and the fathers are always absent at dinner time due to their busy business life. Employing case study method, the five Chinese families’ parent-child interactions at dinner table were recorded using a video camera. More than 3000 clauses were analyzed with the framework of 'systems of clause complexing' from systemic functional linguistic theory. The finding shows that mothers played a critical role in the interaction with their children by initiating most conversations. The three mothers from professional background tended to use more language in extending and expanding pattern that is beneficial for children’s language development and high level of thinking (e.g., logical thinking). The two house making mothers’ language focused more on the directive of their children’s social manners and dietary behaviors. The fathers though seemed to be less active, contributing to the richness of the conversation through their occasional props such as asking open questions or initiating a new topic. In general, the families from professional background were more advantaged in providing learning opportunities for their children at dinner table than the families running business were. The home experiences of Chinese children is an important topic in research due to the rapidly increasing number of Chinese children in Australia and other English speaking countries. Such research assist educators in the education of Chinese children with more awareness of Chinese children experiences at home that could be very unlike the settings in English schools. This study contributes to the research in this area through the analysis of language in parent-child interaction during mealtime, which is very different from previous research that mainly investigated Chinese families through survey and interview. The finding of different manners in language use between the professional families and business families has implication for the understanding of the variation of Chinese children’s home experiences that is influenced not only by parents’ socioeconomic status but their lifestyles.

Keywords: Chinese children, Chinese parents, mealtime talk, parent-child interaction

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Authors: Gwi Hyun Lee, Mun Soo Na

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Solar energy has many advantages of infinite and clean source, and also it can be used for reduction of greenhouse gases and environment pollution. Concentrated solar system is a very useful to achieve reasonably high thermal efficiency. Different types of solar concentrating systems have been developed such as parabolic trough and parabolic dish. Conical solar concentrator is one of the most reliable and promising renewable energy systems for higher temperature applications. The objectives of this study were to investigate the influence of flow rate affecting the thermal efficiency of a conical solar collector, which has a double tube absorber placed at focal axis for collecting solar radiation. A conical solar concentrator consists of a conical reflector, which reflects direct solar radiation into an absorber. A double tube absorber was placed at the center of focal axis for collecting the solar radiation reflected from a conical reflector. A dual tracking system consists of a linear actuator and slew drive with driving cycle of 6 seconds. Water was used as circulating fluid, which flows from inlet to outlet of an absorber for collecting solar radiation. Three identical conical solar concentrator systems were installed side by side at the same place for the accurate performance analysis under the same environmental conditions. Performance evaluations were carried out with different volumetric flow rate of 2, 4 and 6 L/min to find the influence of flow rate affecting on thermal efficiency. The results indicated that average thermal efficiency was 73.24%, 81.96%, and 79.78% for each flow rate of 2 L/min, 4 L/min, and 6 L/min. It shows that the flow rate of circulating water has a significant effect on the thermal efficiency of the conical solar concentrator. It is concluded that an optimum flow rate of conical solar concentrator is 6 L/min.

Keywords: conical solar concentrator, performance evaluation, solar energy, solar energy system

Procedia PDF Downloads 273

Authors: Mahmoud M. Zakaria, Omnia F. Elmoursi, Mahmoud M. Gabr, Camelia A. AbdelMalak, Mohamed A. Ghoneim

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Many protocols were publicized for differentiation of human mesenchymal stem cells (MSCS) into insulin-producing cells (IPCs) in order to excrete insulin hormone ingoing to treat diabetes disease. Our aim is to evaluate relative gene expression for each independent protocol. Human bone marrow cells were derived from three volunteers that suffer diabetes disease. After expansion of mesenchymal stem cells, differentiation of these cells was done by three different protocols (the one-step protocol was used conophylline protein, the two steps protocol was depending on trichostatin-A, and the three-step protocol was started by beta-mercaptoethanol). Evaluation of gene expression was carried out by real-time PCR: Pancreatic endocrine genes, transcription factors, glucose transporter, precursor markers, pancreatic enzymes, proteolytic cleavage, extracellular matrix and cell surface protein. Quantitation of insulin secretion was detected by immunofluorescence technique in 24-well plate. Most of the genes studied were up-regulated in the in vitro differentiated cells, and also insulin production was observed in the three independent protocols. There were some slight increases in expression of endocrine mRNA of two-step protocol and its insulin production. So, the two-step protocol was showed a more efficient in expressing of pancreatic endocrine genes and its insulin production than the other two protocols.

Keywords: mesenchymal stem cells, insulin producing cells, conophylline protein, trichostatin-A, beta-mercaptoethanol, gene expression, immunofluorescence technique

Procedia PDF Downloads 211

Authors: Goulet Marie-Pier, Voyer Dominic, Simoneau Victoria

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In a previous research project (2011-2019) funded by the Quebec Ministry of Education, an educational approach was developed based on the teaching and learning of place value through children's literature. Subsequently, the effect of this approach on the conceptual understanding of the concept among first graders (6-7 years old) was studied. The current project aims to create a series of children's literature to help older elementary school students (8-10 years old) in developing a conceptual understanding of complex mathematical concepts taught at their grade level rather than a more typical procedural understanding. Knowing that there are no educational material or children's books that exist to achieve our goals, four stories, accompanied by mathematical activities, will be created to support students, and their teachers, in the learning and teaching of mathematical concepts that can be challenging within their mathematic curriculum. The stories will also introduce a mathematical dialogue into the characters' discourse with the aim to address various mathematical foundations for which there are often erroneous statements among students and occasionally among teachers. In other words, the stories aim to empower students seeking a real understanding of difficult mathematical concepts, as well as teachers seeking a way to teach these difficult concepts in a way that goes beyond memorizing rules and procedures. In order to choose the concepts that will be part of the stories, it is essential to understand the current landscape regarding the main difficulties experienced by students in third and fourth grade (8-10 years old) and their teacher’s needs. From this perspective, the preliminary phase of the study, as discussed in the presentation, will provide critical insight into the mathematical concepts with which the target grade levels struggle the most. From this data, the research team will select the concepts and develop their stories in the second phase of the study. Two questions are preliminary to the implementation of our approach, namely (1) what mathematical concepts are considered the most “difficult to teach” by teachers in the third and fourth grades? and (2) according to teachers, what are the main difficulties encountered by their students in numeracy? Self-administered online questionnaires using the SimpleSondage software will be sent to all third and fourth-grade teachers in nine school service centers in the Quebec region, representing approximately 300 schools. The data that will be collected in the fall of 2022 will be used to compare the difficulties identified by the teachers with those prevalent in the scientific literature. Considering that this ensures consistency between the proposed approach and the true needs of the educational community, this preliminary phase is essential to the relevance of the rest of the project. It is also an essential first step in achieving the two ultimate goals of the research project, improving the learning of elementary school students in numeracy, and contributing to the professional development of elementary school teachers.

Keywords: children’s literature, conceptual understanding, elementary school, learning and teaching, mathematics

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Authors: B. Adcock, H. van Rensburg

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Education is ever-changing to keep up with innovative technological development and the rapid acceleration of globalisation. This chapter introduces the historical development and transformation of teaching in distance education from correspondence to on-line learning in Queensland universities. It furthermore investigates changes to the delivery models of distance education that have impacted on teaching at tertiary level in Queensland, and reflects on the social changes that have taken place during the past 100 years. This includes an analysis of the following five different periods in time: Foundation period (1911-1919) including World War I; 1920-1939 including the Great Depression; 1940-1970s, including World War II and the post war reconstruction; and the current technological era (1980s to present). In Queensland, the concept of distance education was begun by the University of Queensland (UQ) in 1911, when it began offering extension courses. The introduction of modern technology, in the form of electronic delivery, dramatically changed tertiary distance education due to political initiatives. The inclusion of electronic delivery in education signifies change at many levels, including policy, pedagogy, curriculum and governance. Changes in delivery not only affect the way study materials are delivered, but also the way courses are be taught and adjustments made by academics to their teaching methods.

Keywords: distance education, innovative technological development, on line education, tertiary education

Procedia PDF Downloads 500