Search results for: traditional learning approach

Authors: Joshua Fogel, Rivka Herzog

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Although direct-to-consumer prescription medication advertisements (DTCA) are viewed or heard in many venues, there does not appear to be any research for internet social media DTCA. We study the association of traditional media DTCA and digital media DTCA including internet social media of YouTube, Facebook, and Twitter with three different outcomes. There was one intentions outcome and two different behavior outcomes. The intentions outcome was the agreement level for seeking additional information about a prescription medication after seeing a DTCA. One behavior outcome was the agreement level for obtaining additional information about a prescription medication after seeing a DTCA. The other behavior outcome was the frequency level for obtaining additional information about a prescription medication after seeing a DTCA. Surveys were completed by 635 college students. Predictors included demographic variables, theory of planned behavior variables, health variables, and advertisements seen or heard. Also, in the behavior analyses, additional predictors of intentions and sources for seeking additional prescription drug information were included. Multivariate linear regression analyses were conducted. We found that increased age was associated with increased behavior, women were associated with increased intentions, and Hispanic race/ethnicity was associated with decreased behavior. For the theory of planned behavior variables, increased attitudes were associated with increased intentions, increased social norms were associated with increased intentions and behavior, and increased intentions were associated with increased behavior. Very good perceived health was associated with increased intentions. Advertisements seen in spam mail were associated with decreased intentions. Advertisements seen on traditional or cable television were associated with decreased behavior. Advertisements seen on television watched on the internet were associated with increased behavior. The source of seeking additional information of reading internet print content was associated with increased behavior. No internet social media advertisements were associated with either intentions or behavior. In conclusion, pharmaceutical brand managers and marketers should consider these findings when tailoring their DTCA advertising campaigns and directing their DTCA advertising budget towards young adults such as college students. They need to reconsider the current approach for traditional television DTCA and also consider dedicating a larger advertising budget toward internet television DTCA. Although internet social media is a popular place to advertise, the financial expenditures do not appear worthwhile for DTCA when targeting young adults such as college students.

Keywords: brand managers, direct-to-consumer advertising, internet, social media

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Authors: Leah Lee

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This paper examines the correlation between deep learning models and emotions with noises to see whether or not noises mask emotions. The deep learning models used are plain convolutional neural networks (CNN), auto-encoder, long short-term memory (LSTM), and Visual Geometry Group-16 (VGG-16). Emotion datasets used are Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Crowd-sourced Emotional Multimodal Actors Dataset (CREMA-D), Toronto Emotional Speech Set (TESS), and Surrey Audio-Visual Expressed Emotion (SAVEE). To make it four times bigger, audio set files, stretch, and pitch augmentations are utilized. From the augmented datasets, five different features are extracted for inputs of the models. There are eight different emotions to be classified. Noise variations are white noise, dog barking, and cough sounds. The variation in the signal-to-noise ratio (SNR) is 0, 20, and 40. In summation, per a deep learning model, nine different sets with noise and SNR variations and just augmented audio files without any noises will be used in the experiment. To compare the results of the deep learning models, the accuracy and receiver operating characteristic (ROC) are checked.

Keywords: auto-encoder, convolutional neural networks, long short-term memory, speech emotion recognition, visual geometry group-16

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Authors: Yang Zhuo

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This study explores the integration of MIDI technology as one of the important digital technologies in music teaching, from the perspective of teaching practice, into the process of cultivating students' teaching skills. At the same time, the framework elements of the learning environment for music education students are divided into four aspects: digital technology supported learning space, new knowledge learning, teaching methods, and teaching evaluation. In teaching activities, more attention should be paid to students' subjectivity and interaction between them so as to enhance their emotional experience in teaching practice simulation. In the process of independent exploration and cooperative interaction, problems should be discovered and solved, and basic knowledge of music and teaching methods should be exercised in practice.

Keywords: music education, educational technology, MIDI, teacher training

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Authors: P. Klinkesorn, S. Yordchim, T. Gibbs, J. Achariyopas

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Vocabulary and reading skill were examined in terms of teaching and learning via teacher-created website. The aims of this study are 1) to survey students’ opinions on the teacher-created website for learning vocabulary and reading skill 2) to survey the students’ motivation for learning vocabulary and reading skill through the teacher-created website. Motivation was applied to the results of the questionnaires and interview forms. Finding suggests that Teacher-Created Website can increase students’ motivation to read more, build up a large stock of vocabulary and improve their understanding of the vocabulary. Implications for developing both social engagement and emotional satisfaction are discussed.

Keywords: motivation, teacher-created website, Thai students, vocabulary and reading skill

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Authors: Kolade Olawande Owoeye, George Weir

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Terrorism and extremism activities on the internet are becoming the most significant threats to national security because of their potential dangers. In response to this challenge, law enforcement and security authorities are actively implementing comprehensive measures by countering the use of the internet for terrorism. To achieve the measures, there is need for intelligence gathering via the internet. This includes real-time monitoring of potential websites that are used for recruitment and information dissemination among other operations by extremist groups. However, with billions of active webpages, real-time monitoring of all webpages become almost impossible. To narrow down the search domain, there is a need for efficient webpage classification techniques. This research proposed a new approach tagged: SentiPosit-based method. SentiPosit-based method combines features of the Posit-based method and the Sentistrenght-based method for classification of terrorism and extremism webpages. The experiment was carried out on 7500 webpages obtained through TENE-webcrawler by International Cyber Crime Research Centre (ICCRC). The webpages were manually grouped into three classes which include the ‘pro-extremist’, ‘anti-extremist’ and ‘neutral’ with 2500 webpages in each category. A supervised learning algorithm is then applied on the classified dataset in order to build the model. Results obtained was compared with existing classification method using the prediction accuracy and runtime. It was observed that our proposed hybrid approach produced a better classification accuracy compared to existing approaches within a reasonable runtime.

Keywords: sentiposit, classification, extremism, terrorism

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Authors: Eugenia Vomvoridi-Ivanovic

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It is broadly assumed that participation in field experiences will help pre-service teachers (PSTs) bridge theory to practice. However, this is often not the case since PSTs who are placed in classrooms with large numbers of students from diverse linguistic, cultural, racial, and ethnic backgrounds (culturally diverse students (CDS)) usually observe ineffective mathematics teaching practices that are in contrast to those discussed in their teacher preparation program. Over the past decades, the educational research community has paid increasing attention to investigating out-of-school learning contexts and how participation in such contexts can contribute to the achievement of underrepresented groups in Science, Technology, Engineering, and mathematics (STEM) education and their expanded participation in STEM fields. In addition, several research studies have shown that students display different kinds of mathematical behaviors and discourse practices in out-of-school contexts than they do in the typical mathematics classroom since they draw from a variety of linguistic and cultural resources to negotiate meanings and participate in joint problem solving. However, almost no attention has been given to exploring these contexts as field experiences for pre-service mathematics teachers. The purpose of this study was to explore how participation in a community based after-school field experience promotes understanding of the content pedagogy concepts introduced in elementary mathematics methods courses, particularly as they apply to teaching mathematics to CDS. This study draws upon a situated, socio-cultural theory of teacher learning that centers on the concept of learning as situated social practice, which includes discourse, social interaction, and participation structures. Consistent with exploratory case study methodology, qualitative methods were employed to investigate how a cohort of twelve participating pre-service teacher's approach to pedagogy and their conversations around teaching and learning mathematics to CDS evolved through their participation in the after-school field experience, and how they connected the content discussed in their mathematics methods course with their interactions with the CDS in the after-school. Data were collected over a period of one academic year from the following sources: (a) audio recordings of the PSTs' interactions with the students during the after-school sessions, (b) PSTs' after-school field-notes, (c) audio-recordings of weekly methods course meetings, and (d) other document data (e.g., PST and student generated artifacts, PSTs' written course assignments). The findings of this study reveal that the PSTs benefitted greatly through their participation in the after-school field experience. Specifically, after-school participation promoted a deeper understanding of the content pedagogy concepts introduced in the mathematics methods course and gained a greater appreciation for how students learn mathematics with understanding. Further, even though many of PSTs' assumptions about the mathematical abilities of CDS were challenged and PSTs began to view CDSs' cultural and linguistic backgrounds as resources (rather than obstacles) for learning, some PSTs still held negative stereotypes about CDS and teaching and learning mathematics to CDS in particular. Insights gained through this study contribute to a better understanding of how informal mathematics learning contexts may provide a valuable context for pre-service teacher's learning to teach mathematics to CDS.

Keywords: after-school mathematics program, pre-service mathematical education of teachers, qualitative methods, situated socio-cultural theory, teaching culturally diverse students

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Authors: Annette Cosgrove, Carina Ginty, Tony Hall, Cornelia Connolly

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The objectives of this research study is to examine the impact of professional development in Technology Enhanced Learning (TEL) and the digitization of learning in teaching communities across multiple higher education sites in the ATU (Atlantic Technological University *) ( 2020-2025), including the proposal of an evidence-based digital teaching model for use in a future pandemic. The research strategy undertaken for this study is a multi-site study using mixed methods. Qualitative & quantitative methods are being used in the study to collect data. A pilot study was carried out initially, feedback was collected and the research instrument was edited to reflect this feedback before being administered. The purpose of the staff questionnaire is to evaluate the impact of professional development in the area of TEL, and to capture the practitioner's views on the perceived impact on their teaching practice in the higher education sector across ATU (West of Ireland – 5 Higher education locations ). The phenomenon being explored is ‘ the impact of professional development in the area of technology-enhanced learning and on teaching practice in a higher education institution. The research methodology chosen for this study is an Action based Research Study. The researcher has chosen this approach as it is a prime strategy for developing educational theory and enhancing educational practice. This study includes quantitative and qualitative methods to elicit data that will quantify the impact that continuous professional development in the area of digital teaching practice and technologies has on the practitioner’s teaching practice in higher education. The research instruments/data collection tools for this study include a lecturer survey with a targeted TEL Practice group ( Pre and post covid experience) and semi-structured interviews with lecturers. This research is currently being conducted across the ATU multi-site campus and targeting Higher education lecturers that have completed formal CPD in the area of digital teaching. ATU, a West of Ireland university, is the focus of the study. The research questionnaire has been deployed, with 75 respondents to date across the ATU - the primary questionnaire and semi-formal interviews are ongoing currently – the purpose being to evaluate the impact of formal professional development in the area of TEL and its perceived impact on the practitioners teaching practice in the area of digital teaching and learning. This paper will present initial findings, reflections and data from this ongoing research study.

Keywords: TEL, technology, digital, education

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Authors: Kathaleeya Chanda, Panupong Chanplin, Suppara Charoenpoom

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This purposes of the development of creative instruction model through digital media are to: 1) enable learners to learn from instruction media application; 2) help learners implementing instruction media correctly and appropriately; and 3) facilitate learners to apply technology for searching information and practicing skills to implement technology creatively. The sample group consists of 130 cases of secondary students studying in Bo Kluea School, Bo Kluea Nuea Sub-district, Bo Kluea District, Nan Province. The probability sampling was selected through the simple random sampling and the statistics used in this research are percentage, mean, standard deviation and one group pretest – posttest design. The findings are summarized as follows: The congruence index of instruction media for occupation and technology subjects is appropriate. By comparing between learning achievements before implementing the instruction media and learning achievements after implementing the instruction media, it is found that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. For the learning achievements from instruction media implementation, pretest mean is 16.24 while posttest mean is 26.28. Besides, pretest and posttest results are compared and differences of mean are tested, the test results show that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. This can be interpreted that the learners achieve better learning progress.

Keywords: teaching learning model, digital media, creative instruction model, Bo Kluea school

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Authors: E. Maoz

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Background: As a teaching method, project-based learning is strongly linked to developing students’ critical thinking skills. It combines creative independent thinking, team work, and disciplinary subject-field integration. In the 'Introduction to Nursing Research Methods' course (year 3, Generic Track), project based learning is used to teach the topic of 'Evidence-Based Nursing'. This topic examines a clinical care issue encountered by students in the field. At the end of their project, students present proposals for managing the said issue. Proposals are the product of independent integrative thinking integrating a wide range of factors influencing the issue’s management. Method: Papers by 27 groups of students (165 students) were content analyzed to identify which themes emerged from the students' recommendations for managing the clinical issue. Findings: Five main themes emerged—current management approach; adapting procedures in line with current recent research recommendations; training for change (veteran nursing staff, beginner students, patients, significant others); analysis of 'economic benefit vs. patient benefit'; multidisciplinary team engagement in implementing change in practice. Two surprising themes also emerged: advertising and marketing using new technologies, which reflects how the new generation thinks. Summary and Recommendations: Among the main challenges in nursing education is training nursing graduates to think independently, integratively, and critically. Combining PBL with classical teaching methods stimulates students cognitively while opening new vistas with implications on all levels of the profession: management, research, education, and practice. Advanced students can successfully grasp and interpret the current state of clinical practice. They are competent and open to leading change and able to consider the diverse factors and interconnections that characterize the nurse's work.

Keywords: evidence based nursing, critical thinking skills, project based learning, students education

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Authors: Tony Rizk

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Recent material advances and cost efficiencies are transforming the housing industry away from traditional lumber and gypsum material to alternate fiberboard material that is workable and resistant to fire, mold, and pest infestation. The use of these materials may add to the initial cost of construction. However, the life cycle (cradle to grave) cost of houses using these construction materials and methods are lower than the life cycle costs using traditional housing construction materials and methods. This paper will present four (4) case studies of sustainable house projects. Each project was designed and constructed using earthen-based, sustainable fiberboard material that is resistant to fire, mold, and infestation and fabricated at a very low material calorific value. These house projects have a living space ranging from 625 sq. ft. for an accessory dwelling unit and up to 3,200 sq. ft. 1-story and 2-story homes. For each case study, we will present the house engineering design and construction method, the initial construction costs, a summary of the life cycle costs, and a comparison to the life cycle cost of traditional housing available in the literature.

Keywords: residential housing, sustainable housing, life cycle cost, fire resistance, mold, infestation resistance

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Authors: H. K. Bonsu-Owu

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Media portrayal of women in traditional stereotypical roles such as mothers, or seductress has been the norm for years. However, the changing socioeconomic and political environment and advancement of women in today’s society have given rise to questions on the appropriate portrayal of women in the media today. The purpose of the study is to analyze the portrayal of women in Ghanaian newspapers and find women’s perception on the issue. The study uses a three step approach in gathering data for analysis. Using the stratified sampling method, it analyzes front page images of women from 210 issues of the selected newspapers. Further, it administers questionnaires to 100 female students to find out how they relate to the images of women in the selected newspapers. Finally, editors of the newspapers are interviewed to find their rational for portraying women as seen on their front pages. The findings suggest that the newspapers portray women for varied reasons such as promoting sales and influencing the public agenda. Further, the female students claim that in spite of women’s vast contribution to the growth of society, the media continue to marginalize them. They add that such portrayals promote and reinforce social construct, however, refuse to see themselves through the male gaze concept. The study concludes that the stereotyped portrayal of women is likely to continue if the government, regulatory bodies, the media and society do not make a conscious effort to address this problem.

Keywords: women, newspaper, portrayal, social construct

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Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

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In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

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Authors: Severino Machingambi

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Most academics entering Higher education as lecturers in South Africa do not have qualifications in Education or teaching. This creates serious problems since they are not sufficiently equipped with pedagogical approaches and theories that inform their facilitation of learning strategies. This, arguably, is one of the reasons why higher education institutions are experiencing high student failure rate. In order to mitigate this problem, it is critical that higher education institutions devise internal academic staff development programmes to capacitate academics with pedagogical skills and competencies so as to enhance the quality of student learning. This paper reported on how the Teaching and Learning Development Centre of a university used design-based research methodology to conceptualise and implement an academic staff development programme for new academics at a university of technology. This approach revolves around the designing, testing and refining of an educational intervention. Design-based research is an important methodology for understanding how, when, and why educational innovations work in practice. The need for a professional development course for academics arose due to the fact that most academics at the university did not have teaching qualifications and many of them were employed straight from industry with little understanding of pedagogical approaches. This paper examines three key aspects of the programme namely, the preliminary phase, the teaching experiment and the retrospective analysis. The preliminary phase is the stage in which the problem identification takes place. The problem that this research sought to address relates to the unsatisfactory academic performance of the majority of the students in the institution. It was therefore hypothesized that the problem could be dealt with by professionalising new academics through engagement in an academic staff development programme. The teaching experiment phase afforded researchers and participants in the programme the opportunity to test and refine the proposed intervention and the design principles upon which it was based. The teaching experiment phase revolved around the testing of the new academics professional development programme. This phase created a platform for researchers and academics in the programme to experiment with various activities and instructional strategies such as case studies, observations, discussions and portfolio building. The teaching experiment phase was followed by the retrospective analysis stage in which the research team looked back and tried to give a trustworthy account of the teaching/learning process that had taken place. A questionnaire and focus group discussions were used to collect data from participants that helped to evaluate the programme and its implementation. One of the findings of this study was that academics joining university really need an academic induction programme that inducts them into the discourse of teaching and learning. The study also revealed that existing academics can be placed on formal study programmes in which they acquire educational qualifications with a view to equip them with useful classroom discourses. The study, therefore, concludes that new and existing academics in universities should be supported through induction programmes and placement on formal studies in teaching and learning so that they are capacitated as facilitators of learning.

Keywords: academic staff, pedagogy, programme, staff development

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Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

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High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

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Authors: Bola M. Tunde-Awe

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The study investigated the influence of teacher’s non-verbal communication on secondary school students’ learning outcomes in English language. The study was a survey research. Participants were three hundred Senior Secondary School II students randomly selected from ten schools in Akoko South West Local Government Area of Ondo State, Nigeria. The instrument used for data collection was a questionnaire containing twenty items on a four-point Likert scale which measured teacher’s use of three types of non-verbal communication modes: body movement, eye contact and spatial distance. The data collected was analysed using simple percentage. Findings revealed that teacher’s use of these non-verbal communication modes enhanced learners’ learning outcomes in English language: a total of 271 (90.33%) participants affirmed that teacher’s body language influenced their learning of English; 224 (74.66%) maintained the same stand for eye contact; while 202 (67.33%) affirmed that teacher’s spatial distance had positive influence. Consequent upon these findings, it was recommended that teachers of English language should constantly utilize non-verbal communication in their instructional delivery. Also, non-verbal communication modes should be included in teacher education programme to equip prospective pre-service teachers with the art of non-verbal communication.

Keywords: non-verbal communication, body language, eye contact, spatial distance, learning outcomes

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Authors: Wanlapa Boonsod, Nisachon Yangprasong, Udomsak Kitthawee

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Thermal physics education is a complicated and challenging topic to discuss in any classroom. As a result, most students tend to be uninterested in learning this topic. In the current study, a convection experiment set was devised to show how heat can be transferred by a convection system to a thermoelectric plate until a LED flashes. This research aimed to 1) create a natural convection experimental set, 2) study learning achievement on the convection experimental set with the predict-observe-explain (POE) technique, and 3) study satisfaction for the convection experimental set with the predict-observe-explain (POE) technique. The samples were chosen by purposive sampling and comprised 28 students in grade 11 at Patumkongka School in Bangkok, Thailand. The primary research instrument was the plan for predict-observe-explain (POE) technique on heat transfer using a convection experimental set. Heat transfer experimental set by convection. The instruments used to collect data included a heat transfer achievement model by convection, a Satisfaction Questionnaire after the learning activity, and the predict-observe-explain (POE) technique for heat transfer using a convection experimental set. The research format comprised a one-group pretest-posttest design. The data was analyzed by GeoGebra program. The statistics used in the research were mean, standard deviation and t-test for dependent samples. The results of the research showed that achievement on heat transfer using convection experimental set was composed of thermo-electrics on the top side attached to the heat sink and another side attached to a stainless plate. Electrical current was displayed by the flashing of a 5v LED. The entire set of thermo-electrics was set up on the top of the box and heated by an alcohol burner. The achievement of learning was measured with the predict-observe-explain (POE) technique, with the natural convection experimental set statistically higher than before learning at a 0.01 level. Satisfaction with POE for physics learning of heat transfer by using convection experimental set was at a high level (4.83 from 5.00).

Keywords: convection, heat transfer, physics education, POE

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Authors: Siti Marlia Abd Rahim, Mad Khir Johari Abdullah Sani

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The ever-increasing use of social media applications by library users has raised concerns about the purpose and effectiveness of these platforms in academic libraries. While social media has the potential to revolutionize library services, its usage for non-educational purposes and security concerns have hindered its full potential. This paper aims to address the user behavioral factors affecting social media engagement in academic libraries and examine the impact of social media engagement on user participation. Additionally, it seeks to measure the effect of user participation in social media on the development of powerful learning communities.

Keywords: social media adoption, social media engagement, academic library, social media in academic library, learning community

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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Authors: Gail Joseph

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In the United States, to advance the quality and education requirements of PreK teachers, there are concerns regarding barriers for existing early childhood educators to access formal degrees and ongoing professional development. Barriers exist related to affordability and access. Affordability is a key factor that impacts teachers access to degree programs. The lack of financial resources makes it difficult for many qualified candidates to begin, and complete, degree programs. Even if funding was not an issue, accessibility remains a pressing issue in higher education. Some common barriers include geography, long work hours, lack of professional community, childcare, and clear articulation agreements. Greater flexibility is needed to allow all early childhood professionals to pursue college coursework that takes into consideration the many competing demands on their schedules. For these busy professionals, it is particularly important that professional development opportunities are available “on demand” and are seen as relevant to their work. Courses that are available during non-traditional hours make attendance more accessible, and professional development that is relevant to what they need to know and be able to do to be effective in their current positions increase access to and the impact of ongoing professional education. EarlyEdU at the University of Washington provides institutes of higher education and state professional development systems with free comprehensive, competency based college courses based on the latest science of how to optimize child learning and outcomes across developmental domains. The coursework embeds an intentional teaching framework which requires teachers to know what to do in the moment, see effective teaching in themselves and others, enact these practices in the classroom, reflect on what works and what does not, and improve with thoughtful practices. Reinforcing the Intentional Teaching Framework in EarlyEdU courses is the Coaching Companion, an open source, web-based video annotation learning tool that supports coaching in higher education by enabling students to view and refine their teaching practices. The tool is integrated throughout EarlyEdU courses. With the Coaching Companion, students see upload teaching interactions on video and then reflect on the degree to which they incorporate evidence-based practices. Coaching Companion eliminates the traditional separation of theory and practice in college-based teacher preparation. Together, the Intentional Teaching Framework and the Coaching Companion transform the course instructor into a job-embedded coach. The instructor watches student interactions with children on video using the Coaching Companion and looks specifically for interactions defined in course assignments, readings, and lectures. Based on these observations, the instructor offers feedback and proposes next steps. Developed on federal and philanthropic funds, all EarlyEdU courses and the Coaching Companion are available for free to 2= and 4-year colleges and universities with early childhood degrees, as well as to state early learning and education departments to increase access to high quality professional development. We studied the impact of the Coaching Companion in two courses and demonstrated a significant increase in the quality of teacher-child interactions as measured by the PreK CLASS quality teaching assessment. Implications are discussed related to policy and practice.

Keywords: education technology, distance education, early childhood education, professional development

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Authors: L. Godinho, N. Teixeira

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Nowadays, massification of Internet access represents one of the major challenges to the traditional powers of the State, among which the power to control its external image. The virtual world has also sparked the interest of social sciences which consider it a new field of study, an immense open text where sense is expressed. In this paper, that immense text has been accessed to so as to understand the perception Internet users from all over the world have of Portugal. Ours is a quantitative and qualitative approach, as we have resorted to buzz, thematic and category analysis. The results confirm the predominance of sea stereotype in others' vision of the Portuguese people, and evidence that national image has adapted to network communication through processes of individuation and paganization.

Keywords: national image, internet, self-communication, perception

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Authors: Argyro Maria Skourmalla

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The present paper draws on the example of the University of Luxembourg as a multilingual and international setting. The University of Luxembourg, which is located between France, Germany, and Belgium, has adopted a new multilingualism policy in 2020, establishing English, French, German, and Luxembourgish as the official languages of the Institution. With around 7.000 students, more than half of which are international students, the University is a meeting point for languages and cultures. This paper includes data from an online survey that with undergraduate students from different disciplines at the University of Luxembourg. Students shared their personal experience and opinions regarding language use in this higher education context, as well as practices they use in learning in this multilingual context. Findings show the role of technology in assisting students in different aspects of learning this multilingual context. At the same time, more needs to be done to avoid an exclusively monolingual paradigm in higher education. Findings also show that some languages remain ‘unseen’ in this context. Overall, even though linguistic diversity in this University is seen as an asset, a lot needs to be done towards the recognition of staff and students’ linguistic repertoires for inclusion and education equity.

Keywords: higher education, learning, linguistic diversity, multilingual practices

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Authors: Ali Amin

Abstract:

This paper describes a flipped learning initiative which was trialed in the delivery of the course: structural analysis and modelling. A short series of interactive videos were developed, which introduced the key concepts of each topic. The purpose of the videos was to introduce concepts and give the students more time to develop their thoughts prior to the lecture. This allowed more time for face to face engagement during the lecture. As part of the initial study, videos were developed for half the topics covered. The videos included a short summary of the key concepts ( < 10 mins each) as well as fully worked-out examples (~30mins each). Qualitative feedback was attained from the students. On a scale from strongly disagree to strongly agree, students were rate statements such as 'The pre-class videos assisted your learning experience', 'I felt I could appreciate the content of the lecture more by watching the videos prior to class'. As a result of the pre-class engagement, the students formed more specific and targeted questions during class, and this generated greater comprehension of the material. The students also scored, on average, higher marks in questions pertaining to topics which had videos assigned to them.

Keywords: flipped learning, structural analysis, pre-class videos, engineering education

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Authors: Angely Sim Jia Wun, Sasa Arsovski

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Numerous studies have been conducted on the segmentation of medical images. Segmenting the lungs is one of the common research topics in those studies. Our research stemmed from the lack of solutions for automatic bone, airway, and vessel segmentation, despite the existence of multiple lung segmentation techniques. Consequently, currently, available software tools used for medical image segmentation do not provide automatic lung, bone, airway, and vessel segmentation. This paper presents segmentation techniques along with an interactive software tool architecture for segmenting bone, lung, airway, and vessel tissues. Additionally, we propose a method for creating binary masks from automatically generated segments. The key contribution of our approach is the technique for automatic image thresholding using adjustable Hounsfield values and binary mask extraction. Generated binary masks can be successfully used as a training dataset for deep-learning solutions in medical image segmentation. In this paper, we also examine the current software tools used for medical image segmentation, discuss our approach, and identify its advantages.

Keywords: lung segmentation, binary masks, U-Net, medical software tools

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Authors: Kari Bjorn

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Team learning has been studied and modeled as double loop model and its variations. Also, metacognition has been suggested as a concept to describe the nature of team learning to be more than a simple sum of individual learning of the team members. Team learning has a positive correlation with both individual motivation of its members, as well as the collective factors within the team. Team learning of previously very independent members of two teaching teams is analyzed. Applied Science Universities are training future professionals with ever more diversified and multidisciplinary skills. The size of the units of teaching and learning are increasingly larger for several reasons. First, multi-disciplinary skill development requires more active learning and richer learning environments and learning experiences. This occurs on students teams. Secondly, teaching of multidisciplinary skills requires a multidisciplinary and team-based teaching from the teachers as well. Team formation phases have been identifies and widely accepted. Team role stress has been analyzed in project teams. Projects typically have a well-defined goal and organization. This paper explores team stress of two teacher teams in a parallel running two course units in engineering education. The first is an Industrial Automation Technology and the second is Development of Medical Devices. The courses have a separate student group, and they are in different campuses. Both are run in parallel within 8 week time. Both of them are taught by a group of four teachers with several years of teaching experience, but individually. The team role stress scale items - the survey is done to both teaching groups at the beginning of the course and at the end of the course. The inventory of questions covers the factors of ambiguity, conflict, quantitative role overload and qualitative role overload. Some comparison to the study on project teams can be drawn. Team development stage of the two teaching groups is different. Relating the team role stress factors to the development stage of the group can reveal the potential of management actions to promote team building and to understand the maturity of functional and well-established teams. Mature teams indicate higher job satisfaction and deliver higher performance. Especially, teaching teams who deliver highly intangible results of learning outcome are sensitive to issues in the job satisfaction and team conflicts. Because team teaching is increasing, the paper provides a review of the relevant theories and initial comparative and longitudinal results of the team role stress factors applied to teaching teams.

Keywords: engineering education, stress, team role, team teaching

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

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Authors: Chih-Ping Chen

Abstract:

Despite the increasing popularity of and interest in mobile games, there has been little research that evaluates gender differences in users’ actual preferences for mobile game content, and the factors that influence entertainment and mobile-learning habits. To fill this void, this study examines different gender users’ experience of mobile English learning game adoption in order to identify the areas of development in Taiwan, using Uses and Gratification Theory, Expectation Confirmation Theory and experiential value. The integration of these theories forms the basis of an extended research concept. Users’ responses to questions about cognitive perceptions, confirmation, gratifications and continuous use were collected and analyzed with various factors derived from the theories.

Keywords: expectation confirmation theory, experiential value, gender difference, mobile game, uses and gratification

Procedia PDF Downloads 332

Authors: Lina Sun

Abstract:

Chinese traditional drawings related to buildings and construction apply a unique geometry differentiating with western Euclidean geometry and embrace a collection of special terminologies, under the category of tu (the Chinese character for drawing). This paper will on one side etymologically analysis the terminologies of Chinese traditional architectural drawing, and on the other side geometrically deconstruct the composition of tu and locate the visual narrative language of tu in the pictorial tradition. The geometrical analysis will center on selected series of Yang-shi-lei tu of the construction of emperors’ mausoleums in Qing Dynasty (1636-1912), and will also draw out the earlier architectural drawings and the architectural paintings such as the jiehua, and paintings on religious frescoes and tomb frescoes as the comparison. By doing these, this research will reveal that both the terminologies corresponding to different geometrical forms respectively indicate associations between architectural drawing and the philosophy of Chinese cosmology, and the arrangement of the geometrical forms in the visual picture plane facilitates expressions of the concepts of space and position in the geometrical cosmology. These associations and expressions are the collective intentions of architectural drawing evolving in the thousands of years’ tradition without breakage and irrelevant to the individual authorship. Moreover, the architectural tu itself as an entity, not only functions as the representation of the buildings but also express intentions and strengthen them by using the Chinese unique geometrical language flexibly and intentionally. These collective cosmological spatial intentions and the corresponding geometrical words and languages reveal that the Chinese traditional architectural drawing functions as a unique architectural site with subjectivity which exists parallel with buildings and express intentions and meanings by itself. The methodology and the findings of this research will, therefore, challenge the previous researches which treat architectural drawings just as the representation of buildings and understand the drawings more than just using them as the evidence to reconstruct the information of buildings. Furthermore, this research will situate architectural drawing in between the researches of Chinese technological tu and artistic painting, bridging the two academic areas which usually treated the partial features of architectural drawing separately. Beyond this research, the collective subjectivity of the Chinese traditional drawings will facilitate the revealing of the transitional experience from traditions to drawing modernity, where the individual subjective identities and intentions of architects arise. This research will root for the understanding both the ambivalence and affinity of the drawing modernity encountering the traditions.

Keywords: Chinese traditional architectural drawing (tu), etymology of tu, collective subjectivity of tu, geometrical cosmology in tu, geometry and composition of tu, Yang-shi-lei tu

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Authors: Vasudeva Murthy Challakere Ramaswamy

Abstract:

Background: Conventionally forensic pathology is learnt through autopsy demonstrations which carry various limitations such as unavailability of cases in the mortuary, medico-legal implication and infection. Over the years forensic pathology and science has undergone significant evolution in this digital world. Forensic imaging is a technology which can be effectively utilized for overcoming the current limitations in the undergraduate learning of forensic curriculum. Materials and methods: demonstration of forensic imaging was done using a novel technology of autopsy which has been recently introduced across the globe. Three sessions were conducted in international medical university for a total of 196 medical students. The innovative educational tool was evacuated by using quantitative questionnaire with the scoring scales between 1 to 10. Results: The mean score for acceptance of new tool was 82% and about 74% of the students recommended incorporation of the forensic imaging in the regular curriculum. 82% of students were keen on collaborative research and taking further training courses in forensic imaging. Conclusion: forensic imaging can be an effective tool and also a suitable alternative for teaching undergraduate students. This feedback also supports the fact that students favour the use of contemporary technologies in learning medicine.

Keywords: forensic imaging, forensic pathology, medical students, learning tool

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Authors: Pradeep Joshi, Prashant Dhiman, Shiv Dayal Dhakad

Abstract:

Inconel 718 is a family if Nickel-Chromium based Superalloy; it has very high oxidation and corrosion resistance. Inconel 718 is widely being used in aerospace, engine, turbine etc. due to its high mechanical strength and creep resistance. Being widely used, its machining should be easy but in real its machining is very difficult, especially by using traditional machining methods. It becomes easy to machine only by using non Traditional machining such as EDM. During EDM machining there is wear of both tool and workpiece, the tool wear is undesired because it changes tool shape, geometry. To reduce the tool wear rate (TWR) cryogenic treatment is performed on tool before the machining operation. The machining performances of the process are to be evaluated in terms of MRR, TWR which are functions of Discharge current, Pulse on-time, Pulse Off-time.

Keywords: EDM, cyrogenic, TWR, MRR

Procedia PDF Downloads 459