Search results for: distance learning education

Authors: Guan-Ying Chen, Han-Tsung Liou, Shou-Ren Hu

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To address traffic congestion problems and encourage the use of public transportation systems in the Taipei metropolitan area, the Taipei City Government and the New Taipei City Government implemented a monthly ticket policy on April 16, 2018. This policy offers unlimited rides on the Taipei MRT, Taipei City Bus, New Taipei City Bus, Danhai Light Rail, and Public Bike (YouBike) on a monthly basis. Additionally, both city governments replaced the smart card discount policy with a new frequent flyer discount program (referred to as the loyal customer program) on February 1, 2020, introducing a differential pricing policy. Specifically, the more frequently the Taipei MRT system is used, the greater the discounts users receive. To analyze the impact of the Taipei public transport monthly ticket policy and the frequent user discount program on the passenger volume of the Taipei MRT system and the transferring behaviors of MRT users, this study conducts a trip-chain analysis using transaction data from Taipei MRT smart cards between September 2017 and December 2020. To achieve these objectives, the study employs four indicators: 1) number of passengers, 2) average number of rides, 3) average trip distance, and 4) instances of multiple consecutive rides. The study applies the t-test and Mann-Kendall trend test to investigate whether the proposed indicators have changed over time due to the implementation of the discount policy. Furthermore, the study examines the travel behaviors of passengers who use monthly tickets. The empirical results of the study indicate that the implementation of the Taipei public transport monthly ticket policy has led to an increase in the average number of passengers and a reduction in the average trip distance. Moreover, there has been a significant increase in instances of multiple consecutive rides, attributable to the unlimited rides offered by the monthly tickets. The impact of the frequent user discount program on changes in MRT passengers is not as pronounced as that of the Taipei public transportation monthly ticket policy. This is partly due to the fact that the frequent user discount program is only applicable to the Taipei MRT system, and the passenger volume was greatly affected by the COVID-19 pandemic. The findings of this research can serve as a reference for Taipei MRT Corporation in formulating its fare strategy and can also provide guidance for the Taipei and New Taipei City Governments in evaluating differential pricing policies for public transportation systems.

Keywords: frequent user discount program, mass rapid transit, monthly ticket, smart card

Procedia PDF Downloads 83

Authors: Oyetunji John Adenuga

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This study on the comparative analysis of the performance of teachers in private and public schools was carried out in Ibadan North West Local Government Area of Oyo State. This study examined the justification for the claim that there is difference in the performance of teachers in private and public primary schools and at the same time identified factors responsible for the difference in the performance of these teachers. A descriptive survey research design was used for the study. Data generated were analysed using t-test and regression analysis. The findings of the study revealed that there is significant difference in the performance of teachers in private and private primary schools in Ibadan North West Local Government Area of Oyo State (t=64.09; df=459; p,.05). The findings also revealed that the method of teaching in private primary schools is significantly different from the method of teaching in public primary schools in Ibadan North West Local Government Area of Oyo State (t=73.08; df=459; p,.05). Findings revealed that school leadership and management have significant contribution on the performance of private and public primary school teachers in Ibadan North West Local Area of Oyo State. Based on the finding, the following recommendations were made: Primary school teachers need to be motivated and rewarded for excellent performance. Primary schools should be properly equipped with teaching-aid facilities, laboratories and libraries. Government should use the findings of this study to improve on teaching materials provided to the primary school teachers in Nigeria. Public primary schools should be designed by education planners, administrators and government. Headmasters, proprietors and teachers of primary schools should look inward and give a performance appraisal and evaluation of themselves form time to time based on subject they taught. Finally, school administrators should be conscious of the way they manage the teachers in schools not only in informal situations but also in formal settings.

Keywords: private education, public education, school leadership, school management, teachers performance

Procedia PDF Downloads 342

Authors: Mangesh Govindrao Acharya

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It’s a matter of regret that rule began by causing social divisions in slave India. Even after independence, gender inequality persisted in Indian society; however, as social consciousness, awareness of governance, and political participation increased, this disparity gradually decreased. Technological advancement played an important role in awakening women. Today, a large number of women are able to address their problems in relevant places. The sense of honour for women in the family has also increased. Education, health, and food are indispensable for a strong society. Society's attitude towards the education of women and girls has become positive. Today, women have set their records in many important places. Women still face many challenges. Health awareness among rural women is a big challenge. Equality between men and women is the biggest social reform campaign implemented in our country. It has been going on endlessly for years, but the expected success does not seem to have been achieved. On the contrary, the issue of equality between men and women keeps coming before society in a new form. An attempt has been made in the present research essay to give an account of India's performance in this regard at the global level.

Keywords: gender sensitization, gender equality, women's dignity, women's safety

Procedia PDF Downloads 137

Authors: Tamas Madl

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Sudden cardiac death (SCD) constitutes a large proportion of cardiovascular mortalities, provides little advance warning, and the risk is difficult to recognize based on ubiquitous, low cost medical equipment such as the standard, 12-lead, ten second ECG. Autonomic abnormalities have been shown to be strongly predictive of SCD risk; yet current methods are not trivially applicable to the brevity and low temporal and electrical resolution of standard ECGs. Here, we build horizontal visibility graph representations of very short inter-beat interval time series, and perform unsuper- vised representation learning in order to convert these variable size objects into fixed-length vectors preserving similarity rela- tions. We show that such representations facilitate classification into healthy vs. at-risk patients on two different datasets, the Mul- tiparameter Intelligent Monitoring in Intensive Care II and the PhysioNet Sudden Cardiac Death Holter Database. Our results suggest that graph representation learning of heartbeat interval time series facilitates robust classification even in sequences as short as ten seconds.

Keywords: sudden cardiac death, heart rate variability, ECG analysis, time series classification

Procedia PDF Downloads 234

Authors: Tahsien Okasha

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Transplantation medicine is one of the most challenging and complex areas of modern medicine. Some of the key areas for medical management are the problems of transplant rejection, during which the body has an immune response to the transplanted organ, possibly leading to transplant failure and the need to immediately remove the organ from the recipient. When possible, transplant rejection can be reduced through serotyping to determine the most appropriate donor-recipient match and through the use of immunosuppressant drugs. Postoperative care actually begins before the surgery in terms of education, discharge planning, nutrition, pulmonary rehabilitation, and patient/family education. This also allows for expectations to be managed. A multidisciplinary approach is the key, and collaborative team meetings are essential to ensuring that all team members are "on the same page.". The following clinical pathway map and guidelines with the aim to decrease alteration in clinical practice and are intended for those healthcare professionals who look after organ transplant patients. They are also intended to be useful to both medical and surgical trainees as well as nurse specialists and other associated healthcare professionals involved in the care of organ transplant patients. This pathway is general pathway include the general guidelines that can be applicable for all types of organ transplant with special considerations to each organ.

Keywords: organ transplant, clinical pathway, postoperative care, same page

Procedia PDF Downloads 437

Authors: Ricky Leung

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Artificial intelligence (AI) and machine learning (ML) have revolutionized the way health organizations approach social media. The sheer volume of data generated through social media can be overwhelming, but AI and ML can help organizations effectively manage this information to improve the health and well-being of individuals and communities. One way AI can be used to enhance social media in health organizations is through sentiment analysis. This involves analyzing the emotions expressed in social media posts to better understand public opinion and respond accordingly. This can help organizations gauge the impact of their campaigns, track the spread of misinformation, and improve communication with the public. While social media is a useful tool, researchers and practitioners have expressed fear that it will be used for the spread of misinformation, which can have serious consequences for public health. Health organizations must work to ensure that AI systems are transparent, trustworthy, and unbiased so they can help minimize the spread of misinformation. In conclusion, AI and ML have the potential to greatly enhance the use of social media in health organizations. These technologies can help organizations effectively manage large amounts of data and understand stakeholders' sentiments. However, it is important to carefully consider the potential consequences and ensure that these systems are carefully designed to minimize the spread of misinformation.

Keywords: AI, ML, social media, health organizations

Procedia PDF Downloads 89

Authors: Mahesh Vishwakarma, Sadhana Vishwakarma

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Vocational education includes all kind of education which can help students to acquire skills related to a certain profession, art, or activity so that they are able to exercise that profession, art or activity after acquiring such qualification. However, in this global economy of the modern world, job seekers are expected to have certain soft skills over and above the technical knowledge and skills acquired in their areas of expertise. These soft skills include but not limited to interpersonal communication, understanding, personal attributes, problem-solving, working in team, quick adaptability to the workplace environment, and other. Not only the hands-on, job-related skills, and competencies are now being sought by the employers, but also a complex of attitudinal dispositions and affective traits are being looked by them in their prospective employees. This study was performed to identify the employability skills of technical students from an Industrial Training Centre (ITC) in central India. It also aimed to convey a message to the students currently on the role, that for them to remain relevant in the job market, they would need to constantly adapt to changes and evolving requirements in the work environment, including the use of updated technologies. Five hypotheses were formulated and tested on the employability skills of students as a function of gender, trade, work experience, personal attributes, and IT skills. Data were gathered with the help of center’s training officers who approached 200 recently graduated students from the center and administered the instrument to students. All 200 respondents returned the completed instrument. The instrument used for the study consisted of 2 sections; demographic details and employability skills. To measure the employability skills of the trainees, the instrument was developed by referring to the several instruments developed by the past researchers for similar studies. The 1st section of the instrument of demographic details recorded age, gender, trade, year of passing, interviews faced, and employment status of the respondents. The 2nd section of the instrument on employability skills was categorized into seven specific skills: basic vocational skills; personal attributes; imagination skills; optimal management of resources; information-technology skills; interpersonal skills; adapting to new technologies. The reliability and validity of the instrument were checked. The findings revealed valuable information on the relationship and interdependence of vocational education and employability skills of students in the central Indian scenario. The findings revealed a valuable information on supplementing the existing vocational education programs with few soft skills and competencies so as to develop a superior workforce much better equipped to face the job market. The findings of the study can be used as an example by the management of government and private industrial training centers operating in the other parts of the Asian region. Future research can be undertaken on a greater population base from different geographical regions and backgrounds for an enhanced outcome.

Keywords: employability skills, vocational education, industrial training centers, students

Procedia PDF Downloads 132

Authors: Sunitha Thappa

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Business environment is a set of complex interdependent dimensions that corporates have to always be vigil in identifying the influential waves. Over the year business environment has evolved into a basket of uncertainties. Every organization strives to counter this dynamic nature of business environment by recurrently evaluating the primary and support activities of its value chain. This has led to companies redesigning their business models, reinvent business processes and operating procedure on unremitting basis. A few specific issues that are placed before the present day managers are breaking down the functional interpretation of any challenge that organizations confronts, reduction in organizational hierarchy and tackling the components of the value chain to retain their competitive advantage. It is how effectively managers detect the changes and swiftly reorient themselves to these changes that define their success or failure. Given the complexity of decision making in this dynamic environment, two important question placed before the B-schools of today. Firstly, are they grooming and nurturing managerial talent proficient enough to thrive in this multifaceted business environment? Secondly, are the management graduates walking through their portals, able to view challenges from a cross-functional perspective with emphasis to customer and process rather than hierarchy and functions. This paper focuses on the need for a process oriented approach to management education.

Keywords: management education, pedagogy, functional, process

Procedia PDF Downloads 332

Authors: Hyeong-Jin Kim, Jong Kook Lee

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Zirconia has biological, mechanical and optical properties, so, it used as a dental implant material in human body. But, it is difficult to form directly bonding with living tissues after the procedure and induces the falling away from implanted parts of the body. To improve this phenomenon, it is essential to increase the surface roughness of zirconia implants and induce a forming-ability of strong bonds. In this study, we performed a room temperature spray coating on zirconia specimen to obtain a highly roughened zirconia surface. To get optimal surface roughness, we controlled the distance between the nozzle and the substrate, coating times and powder condition. Bonding microstructure, surface roughness, and chemical composition of the coating layer were observed by SEM, XRD and roughness tester.

Keywords: implant, aerosoldeposition, zirconia, dental

Procedia PDF Downloads 212

Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: D. Naranchimeg, G. Ulziisaikhan

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Student dropout problem has not been recently investigated within the Mongolian higher education. A student dropping out is a personal decision, but it may cause unemployment and other social problems including low quality of life because students who are not completed a degree cannot find better-paid jobs. The research aims to determine percentage of at-risk students, and understand reasons for dropouts and to find a way to predict. The study based on the students of the Mongolian National University of Education including its Arkhangai branch school, National University of Mongolia, Mongolian University of Life Sciences, Mongolian University of Science and Technology, Mongolian National University of Medical Science, Ikh Zasag International University, and Dornod University. We conducted the paper survey by method of random sampling and have surveyed about 100 students per university. The margin of error - 4 %, confidence level -90%, and sample size was 846, but we excluded 56 students from this study. Causes for exclusion were missing data on the questionnaire. The survey has totally 17 questions, 4 of which was demographic questions. The survey shows that 1.4% of the students always thought to dropout whereas 61.8% of them thought sometimes. Also, results of the research suggest that students’ dropouts from university do not have relationships with their sex, marital and social status, and peer and faculty climate, whereas it slightly depends on their chosen specialization. Finally, the paper presents the reasons for dropping out provided by the students. The main two reasons for dropouts are personal reasons related with choosing wrong study program, not liking the course they had chosen (50.38%), and financial difficulties (42.66%). These findings reveal the importance of early prevention of dropout where possible, combined with increased attention to high school students in choosing right for them study program, and targeted financial support for those who are at risk.

Keywords: at risk students, dropout, faculty climate, Mongolian universities, peer climate

Procedia PDF Downloads 397

Authors: Yeong-cheng Wang, Jin-Yinn Wang, Ming-Shan Lin, Jian-Li Dong

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To universalize the adoption of sustainable energy, the R.O.C. government encourages public buildings to introduce the PV power station on the building roof, whereas most old buildings did not include the considerations of photovoltaic (PV) power facilities in the design phase. Several factors affect the PV electricity output, the temperature is the key one, different PV technologies have different temperature coefficients. Other factors like PV panel azimuth, panel inclination from the horizontal plane, and row to row distance of PV arrays, mix up at the beginning of system design. The goal of this work is to maximize the annual energy output of a roof mount PV system. Tables to simplify the design work are developed; the results can be used for engineering project quote directly.

Keywords: optimal inclination, array azimuth, annual output

Procedia PDF Downloads 677

Authors: Valery Yakubovich, Shuping wu

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Organization theorists have long claimed that organizational innovations are nontechnological, in part because they are unpatentable. The claim rests on the assumption that organizational innovations are abstract ideas embodied in persons and contexts rather than in context-free practical tools. However, over the last three decades, organizational knowledge has been increasingly embodied in digital tools which, in principle, can be patented. To provide the first empirical evidence regarding the patentability of organizational innovations, we trained two machine learning algorithms to identify a population of 205,434 patent applications for organizational technologies (OrgTech) and, among them, 141,285 applications that use organizational innovations accumulated over the 20th century. Our event history analysis of the probability of patenting an OrgTech invention shows that ideas from organizational innovations decrease the probability of patent allowance unless they describe a practical tool. We conclude that the present-day digital transformation places organizational innovations in the realm of high tech and turns the debate about organizational technologies into the challenge of designing practical organizational tools that embody big ideas about organizing. We outline an agenda for patent-based research on OrgTech as an emerging phenomenon.

Keywords: organizational innovation, organizational technology, high tech, patents, machine learning

Procedia PDF Downloads 122

Authors: Jan Schmitt, Sophie Fischer

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After the Corona pandemic, climate change is a further, long-lasting challenge the society must deal with. An ongoing climate change need to be prevented. Nevertheless, the adoption tothe already changed climate conditionshas to be focused in many sectors. Recently, the decisive role of the economic sector with high value added can be seen in the Corona crisis. Hence, manufacturing industry as such a sector, needs to be prepared for climate change and adaption. Several examples from the manufacturing industry show the importance of a strategic effort in this field: The outsourcing of a major parts of the value chain to suppliers in other countries and optimizing procurement logistics in a time-, storage- and cost-efficient manner within a network of global value creation, can lead vulnerable impacts due to climate-related disruptions. E.g. the total damage costs after the 2011 flood disaster in Thailand, including costs for delivery failures, were estimated at 45 billion US dollars worldwide. German car manufacturers were also affected by supply bottlenecks andhave close its plant in Thailand for a short time. Another OEM must reduce the production output. In this contribution, a game-based learning approach is presented, which should enable manufacturing companies to derive their own strategies for climate adaption out of a mix of different actions. Based on data from a regional study of small, medium and large manufacturing companies in Mainfranken, a strongly industrialized region of northern Bavaria (Germany) the game-based learning approach is designed. Out of this, the actual state of efforts due to climate adaption is evaluated. First, the results are used to collect single actions for manufacturing companies and second, further actions can be identified. Then, a variety of climate adaption activities can be clustered according to the scope of activity of the company. The combination of different actions e.g. the renewal of the building envelope with regard to thermal insulation, its benefits and drawbacks leads to a specific strategy for climate adaption for each company. Within the game-based approach, the players take on different roles in a fictionalcompany and discuss the order and the characteristics of each action taken into their climate adaption strategy. Different indicators such as economic, ecologic and stakeholder satisfaction compare the success of the respective measures in a competitive format with other virtual companies deriving their own strategy. A "play through" climate change scenarios with targeted adaptation actions illustrate the impact of different actions and their combination onthefictional company.

Keywords: business strategy, climate change, climate adaption, game-based learning

Procedia PDF Downloads 207

Authors: Łukasz Ambroziak

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Although the impact of the production fragmentation on trade flows has been examined many times since the 1990s, the research was not comprehensive because of the limitations in traditional trade statistics. Early 2010s the complex databases containing world input-output tables (or indicators calculated on their basis) has made available. It increased the possibilities of examining the production sharing in the world. The trade statistic in value-added terms enables us better to estimate trade changes resulted from the internationalisation and globalisation as well as benefits of the countries from international trade. In the literature, there are many research studies on this topic. Unfortunately, trade in value added of the Central and Eastern European Countries (CEECs) has been so far insufficiently studied. Thus, the aim of the paper is to present changes in value added trade of the CEECs (Bulgaria, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia and Slovenia) in the period of 1995-2011. The concept 'trade in value added' or 'value added trade' is defined as the value added of a country which is directly and indirectly embodied in final consumption of another country. The typical question would be: 'How much value added is created in a country due to final consumption in the other countries?' The data will be downloaded from the World Input-Output Database (WIOD). The structure of this paper is as follows. First, theoretical and methodological aspects related to the application of the input-output tables in the trade analysis will be studied. Second, a brief survey of the empirical literature on this topic will be presented. Third, changes in exports and imports in value added of the CEECs will be analysed. A special attention will be paid to the differences in bilateral trade balances using traditional trade statistics (in gross terms) on one side, and value added statistics on the other. Next, in order to identify factors influencing value added exports and value added imports of the CEECs the generalised gravity model, based on panel data, will be used. The dependent variables will be value added exports and imports. The independent variables will be, among others, the level of GDP of trading partners, the level of GDP per capita of trading partners, the differences in GDP per capita, the level of the FDI inward stock, the geographical distance, the existence (or non-existence) of common border, the membership (or not) in preferential trade agreements or in the EU. For comparison, an estimation will also be made based on exports and imports in gross terms. The initial research results show that the gravity model better explained determinants of trade in value added than gross trade (R2 in the former is higher). The independent variables had the same direction of impact both on value added exports/imports and gross exports/imports. Only value of coefficients differs. The most difference concerned geographical distance. It had smaller impact on trade in value added than gross trade.

Keywords: central and eastern European countries, gravity model, input-output tables, trade in value added

Procedia PDF Downloads 239

Authors: Yu-Lin Chen, Kimberly Koester, Marissa Raymond-Flesh, Anika Thapar, Jay Thapar

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Purpose: Effectively communicating adolescent health topics to teens and their parents is crucial. This study emphasizes critically evaluating the optimal use of artificial intelligence tools (AI), which are increasingly prevalent in disseminating health information. By fostering a deeper understanding of AI voice preference in the context of health, the research aspires to have a ripple effect, enhancing the collective health literacy and decision-making capabilities of both teenagers and their parents. This study explores AI voices' potential within health learning modules for annual well-child visits. We aim to identify preferred voice characteristics and understand factors influencing perceived trustworthiness, ultimately aiming to improve health literacy and decision-making in both demographics. Methods: A cross-sectional study assessed preferences and trust perceptions of AI voices in learning modules among teens (11-18) and their parents/guardians in Northern California. The study involved the development of four distinct learning modules covering various adolescent health-related topics, including general communication, sexual and reproductive health communication, parental monitoring, and well-child check-ups. Participants were asked to evaluate eight AI voices across the modules, considering a set of six factors such as intelligibility, naturalness, prosody, social impression, trustworthiness, and overall appeal, using Likert scales ranging from 1 to 10 (the higher, the better). They were also asked to select their preferred choice of voice for each module. Descriptive statistics summarized participant demographics. Chi-square/t-tests explored differences in voice preferences between groups. Regression models identified factors impacting the perceived trustworthiness of the top-selected voice per module. Results: Data from 104 participants (teen=63; adult guardian = 41) were included in the analysis. The mean age is 14.9 for teens (54% male) and 41.9 for the parent/guardian (12% male). At the same time, similar voice quality ratings were observed across groups, and preferences varied by topic. For instance, in general communication, teens leaned towards young female voices, while parents preferred mature female tones. Interestingly, this trend reversed for parental monitoring, with teens favoring mature male voices and parents opting for mature female ones. Both groups, however, converged on mature female voices for sexual and reproductive health topics. Beyond preferences, the study delved into factors influencing perceived trustworthiness. Interestingly, social impression and sound appeal emerged as the most significant contributors across all modules, jointly explaining 71-75% of the variance in trustworthiness ratings. Conclusion: The study emphasizes the importance of catering AI voices to specific audiences and topics. Social impression and sound appeal emerged as critical factors influencing perceived trustworthiness across all modules. These findings highlight the need to tailor AI voices by age and the specific health information being delivered. Ensuring AI voices resonate with both teens and their parents can foster their engagement and trust, ultimately leading to improved health literacy and decision-making for both groups. Limitations and future research: This study lays the groundwork for understanding AI voice preferences for teenagers and their parents in healthcare settings. However, limitations exist. The sample represents a specific geographic location, and cultural variations might influence preferences. Additionally, the modules focused on topics related to well-child visits, and preferences might differ for more sensitive health topics. Future research should explore these limitations and investigate the long-term impact of AI voice on user engagement, health outcomes, and health behaviors.

Keywords: artificial intelligence, trustworthiness, voice, adolescent

Procedia PDF Downloads 55

Authors: Yael Leibovitch

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Teaching academic writing is a source of concern for secondary schools. Many students struggle to meet the basic standards of literacy while teacher confidence in this arena remains low. These issues are compounded by the conventionally prescriptive character of writing instruction, which fails to engage student writers. At the same time, a growing body of research on dialogic teaching has highlighted the powerful role of talk in student learning. With the intent of enhancing pedagogical capability, this paper shares finding from a co-inquiry case study that investigated how teachers think about and negotiate classroom discourse to position students as effective academic writers and thinkers. Using a range of qualitative methods, this project closely documents the iterative collaboration of educators as they sought to create more opportunities for dialogic engagement. More specifically, it triangulates both teacher and student data regarding the efficacy of interdependent thinking and collaborative reasoning as organizing principals for literacy learning. Findings indicate that a dialogic teaching repertoire helps to develop the cognitive and metacognitive skills of adolescent writers. In addition, they underscore the importance of sustained professional collaboration to the uptake of new writing pedagogies.

Keywords: dialogic teaching, writing, teacher professional development, student literacy

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Authors: Amir Hossein Ashari, Sedighe Erfan Manesh

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One of the problems in developing countries is renovating the historical context and inducing behaviors appropriate to modern life to such a context. This study was conducted using field and library methods in 2012. Similar cases carried out in Iran and developing countries were compared to unveil the strengths and weaknesses of these projects. At present, in the historical context of Shiraz, the distance between two religious shrines of Shahcheragh (Ahmad ibn Musa) and Astaneh (Sayed Alaa al-Din Hossein), which are significant places in religious, cultural, social, and economic terms, is an area full of historic places called Bein Al-Haramein. Unfortunately, some of these places have been worn out and are not appropriate for common uses. The basic strategy of Bein Al-Haramein was to improve social development of Shiraz, to enhance the vitality and dynamism of the historical context of Bein Al-Haramein and to create tourist attractions in order to boost the city's economic and social stability. To this end, the project includes the huge Bein Al-Haramein Commercial Complex which is under construction now. To construct the complex, officials have decided to demolish places of historical value which can lead to irreparable consequences. Iranian urban design has always been based on three elements of bazaars, mosques and government facilities with bazaars being the organic connector of the other elements. Therefore, the best strategy in the above case is to provide for a commercial connection between the two poles. Although this strategy is included in the project, lack of attention to renovation principles in this area and complete destruction of the context will lead to its irreversible damage and will destroy its cultural and historical identity. In urban planning of this project, some important issues have been neglected including: preserving valuable buildings and special old features of the city, rebuilding worn buildings and context to attract trust and confidence of the people, developing new models according to changes, improving the structural position of old context with minimal degradation, attracting partnerships of residents and protecting their rights and finally using potential facilities of the old context. The best strategy for achieving sustainability in Bein Al-Haramein can be the one used in the distance between Santa Maria Novella and Santa Maria Del Fiore churches in historical context where while protecting the historic context and constructions, old buildings were renovated and given different commercial and service uses making them sustainable and dynamic places. Similarly, in Bein Al-Haramein, renovating old constructions and monuments and giving different commercial and other uses to them can help improve the economic and social sustainability of the area.

Keywords: Bein Al-Haramein, sustainability, historical context, historical context

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Authors: Belayneh Matebie, Michael Melese

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The study focuses on addressing the challenges in classifying and ensuring the quality of Eragrostis Teff, a small and round grain that is the smallest cereal grain. Employing a traditional classification method is challenging because of its small size and the similarity of its environmental characteristics. To overcome this, this study employs a machine learning approach to develop a source and quality classification system for Teff cereal. Data is collected from various production areas in the Amhara regions, considering two types of cereal (high and low quality) across eight classes. A total of 5,920 images are collected, with 740 images for each class. Image enhancement techniques, including scaling, data augmentation, histogram equalization, and noise removal, are applied to preprocess the data. Convolutional Neural Network (CNN) is then used to extract relevant features and reduce dimensionality. The dataset is split into 80% for training and 20% for testing. Different classifiers, including FVGG16, FINCV3, QSCTC, EMQSCTC, SVM, and RF, are employed for classification, achieving accuracy rates ranging from 86.91% to 97.72%. The ensemble of FVGG16, FINCV3, and QSCTC using the Max-Voting approach outperforms individual algorithms.

Keywords: Teff, ensemble learning, max-voting, CNN, SVM, RF

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Authors: Neha Singh, Ananya Arora

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Facial expression measurement plays a crucial role in the identification of emotion. Facial expression plays a key role in psychophysiology, neural bases, and emotional disorder, to name a few. The Facial Action Coding System (FACS) has proven to be the most efficient and widely used of the various systems used to describe facial expressions. Coders can manually code facial expressions with FACS and, by viewing video-recorded facial behaviour at a specified frame rate and slow motion, can decompose into action units (AUs). Action units are the most minor visually discriminable facial movements. FACS explicitly differentiates between facial actions and inferences about what the actions mean. Action units are the fundamental unit of FACS methodology. It is regarded as the standard measure for facial behaviour and finds its application in various fields of study beyond emotion science. These include facial neuromuscular disorders, neuroscience, computer vision, computer graphics and animation, and face encoding for digital processing. This paper discusses the conceptual basis for FACS, a numerical listing of discrete facial movements identified by the system, the system's psychometric evaluation, and the software's recommended training requirements.

Keywords: facial action, action units, coding, machine learning

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Authors: S. M. Rashed Ul Islam, Shahina Tabassum, Afsana Anwar Miti

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Objective: HIV testing and counseling center (HTC) is an important component of the HIV/AIDS detection, prevention and control interventions. The service was first initiated at the Department of Virology, Bangabandhu Sheikh Mujib Medical University (BSMMU) since the first case detection in 1989. The present study aimed to describe the demographic profile among the attendees tested HIV positive. Methods: The present study was carried out among 219 HIV positive cases detected through screening at the Department of Virology of BSMMU during the year of 2012-2016. Data were collected through pre-structured written questionnaire during the counseling session. Data were expressed as frequency and percentages and analyzed using SPSS v20.0 program. Results: Out of 219 HIV cases detected, 77.6% were males, and 22.4% were females with a mean age (mean±SD) of 35.46±9.46 years. Among them, 70.7% belonged to the 26-45 age groups representing the sexually active age. The majority of the cases were married (86.3%) and 49.8% had primary level of education whereas, 8.7% were illiterate. Nearly 42% of cases were referred from Chittagong division (south-east part of the country) followed by Dhaka division (35.6%). The bulk of study population admitted to involvement in high-risk behaviour (90%) in the past and 42% of them had worked overseas. The Pearson Chi-square (χ2) analysis revealed significant relationship of gender with marital (χ2=7.88 at 2% level) and occupation status (χ2=120.48 at 6% level); however, no association was observed with risk behaviour and educational status. Recommendations: HIV risk behavior was found to be a prime source for HIV infection among the study population. So, there is need for health education and awareness program to bring about behavioral changes to halt the yearly increase of new cases in the country with special attention to our overseas workers on HIV/AIDS risk and safety.

Keywords: Bangladesh, health education, HIV testing and counseling (HTC), HIV/AIDS, risk behavior

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Authors: Dan Geneau, Mary Claire Geneau, Seth Lenetsky, Ming -Chang Tsai, Marc Klimstra

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Introduction— Horizontal force-velocity profiling (HFVP) involves modeling an athletes linear sprint kinematics to estimate valuable maximum force and velocity metrics. This approach to performance modeling has been used in field-based team sports and has recently been introduced to ice-hockey as a forward skating performance assessment. While preliminary data has been collected on ice, distance constraints of the on-ice test restrict the ability of the athletes to reach their maximal velocity which result in limits of the model to effectively estimate athlete performance. This is especially true of more elite athletes. This report explores whether athletes on-ice are able to reach a velocity plateau similar to what has been seen in overground trials. Fourteen male Major Junior ice-hockey players (BW= 83.87 +/- 7.30 kg, height = 188 ± 3.4cm cm, age = 18 ± 1.2 years n = 14) were recruited. For on-ice sprints, participants completed a standardized warm-up consisting of skating and dynamic stretching and a progression of three skating efforts from 50% to 95%. Following the warm-up, participants completed three on ice 45m sprints, with three minutes of rest in between each trial. For overground sprints, participants completed a similar dynamic warm-up to that of on-ice trials. Following the warm-up participants completed three 40m overground sprint trials. For each trial (on-ice and overground), radar was used to collect instantaneous velocity (Stalker ATS II, Texas, USA) aimed at the participant’s waist. Sprint velocities were modelled using custom Python (version 3.2) script using a mono-exponential function, similar to previous work. To determine if on-ice tirals were achieving a maximum velocity (plateau), minimum acceleration values of the modeled data at the end of the sprint were compared (using paired t-test) between on-ice and overground trials. Significant differences (P<0.001) between overground and on-ice minimum accelerations were observed. It was found that on-ice trials consistently reported higher final acceleration values, indicating a maximum maintained velocity (plateau) had not been reached. Based on these preliminary findings, it is suggested that reliable HFVP metrics cannot yet be collected from all ice-hockey populations using current methods. Elite male populations were not able to achieve a velocity plateau similar to what has been seen in overground trials, indicating the absence of a maximum velocity measure. With current velocity and acceleration modeling techniques, including a dependency of a velocity plateau, these results indicate the potential for error in on-ice HFVP measures. Therefore, these findings suggest that a greater on-ice sprint distance may be required or the need for other velocity modeling techniques, where maximal velocity is not required for a complete profile.   

Keywords: ice-hockey, sprint, skating, power

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Authors: Şakir Bingöl, Abdullah Emre Aydemir, Abdullah Saado, Ahmet Akıl, Elif Canbaz, Feyza Nur Bulgurcu, Gizem Uzun, Günsu Bilge Dal, Muhammedcan Pirinççi

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Smart contracts, which can be applied in many different areas, from financial applications to the internet of things, come to the fore with their security, low cost, and self-executing features. In this paper, it is focused on peer-to-peer (P2P) energy trading and the implementation of the smart contract on the Ethereum blockchain. It is assumed a microgrid consists of consumers and prosumers that can produce solar and wind energy. The proposed architecture is a system where the prosumer makes the purchase or sale request in the smart contract and the maximum price obtained through the distribution system operator (DSO) by forecasting. It is aimed to forecast the hourly maximum unit price of energy by using deep learning instead of a fixed pricing. In this way, it will make the system more reliable as there will be more dynamic and accurate pricing. For this purpose, Istanbul's energy generation, energy consumption and market clearing price data were used. The consistency of the available data and forecasting results is observed and discussed with graphs.

Keywords: energy trading smart contract, deep learning, microgrid, forecasting, Ethereum, peer to peer

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Masanori Kimura

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Due to the decline of the 18-year-old population, Japanese universities have a tendency to convert their form of employment from tenured positions to fixed-term positions for newly hired teachers. The advantage of this is that universities can be more flexible in their employment plans in case they fail to fill the enrollment of quotas of prospective students or they need to supplement teachers who can engage in other academic fields or research areas where new demand is expected. The most serious disadvantage of this, however, is that if secure positions cannot be provided to faculty members, there is the possibility that coherence of education and continuity of research supported by the university cannot be achieved. Therefore, the question of this presentation is as follows: Are universities aiming to give first priority to management, or are they trying to prioritize educational and research rather than management? To answer this question, the author examined the number of job offerings for college foreign language teachers posted on the JREC-IN (Japan Research Career Information Network, which is run by Japan Science and Technology Agency) website from April 2012 to October 2015. The results show that there were 1,002 and 1,056 job offerings for tenured positions and fixed-term contracts respectively, suggesting that, overall, today’s Japanese universities show a tendency to give first priority to management. More detailed examinations of the data, however, show that the tendency slightly varies depending on the types of universities. National universities which are supported by the central government and state universities which are supported by local governments posted more job offerings for tenured positions than for fixed-term contracts: national universities posted 285 and 257 job offerings for tenured positions and fixed-term contracts respectively, and state universities posted 106 and 86 job offerings for tenured positions and fixed-term contracts respectively. Yet the difference in number between the two types of employment status at national and state universities is marginal. As for private universities, they posted 713 job offerings for fixed-term contracts and 616 offerings for tenured positions. Moreover, 73% of the fixed-term contracts were offered for low rank positions including associate professors, lectures, and so forth. Generally speaking, those positions are offered to younger teachers. Therefore, this result indicates that private universities attempt to cut their budgets yet expect the same educational effect by hiring younger teachers. Although the results have shown that there are some differences in personal strategies among the three types of universities, the author argues that all three types of universities may lose important human resources that will take a pivotal role at their universities in the future unless they urgently review their employment strategies.

Keywords: higher education, management, employment status, foreign language education

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Authors: Selen Muftuoglu, Dilara Kefeli

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The present study was conducted by using the cross-sectional study design and to determine the relationship between body image, eating behavior and nutritional status in 80 female athletes who were basketball, volleyball, flag football, indoor soccer, and ice hockey players. This study demonstrated that 70.0% of the female athletes had skipped meal. Also, female athletes had a normal body mass index (BMI), but 65.0% of them indicated that want to be thinner. On the other hand, we analyzed that their daily nutrients intake, so we observed that 43.4% of the energy was from the fatty acids, especially saturated fatty acids, and they had lower fiber, calcium and iron intake. Also, we found that BMI, waist circumference, waist to hip ratio were negatively correlated with Multidimensional Body-Self Relations Questionnaire and The Dutch Eating Behavior Questionnaire score and they were lower in who had meal skipped or not received diet therapy. As a conclusion, nutrition education is frequently neglected in sports programs. There is a paucity of nutrition education interventions among different sports.

Keywords: body image, eating behavior, eating disorders, female athletes, nutritional status

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Authors: Rajender Dahiya

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Investigation outcomes of major process incidents have been consistent for decades and validate that the causes and consequences are often identical. The debate remains as we continue to experience similar process incidents even with enormous development of new tools, technologies, industry standards, codes, regulations, and learning processes? The objective of this paper is to investigate the most common causes of major industrial incidents and reveal industry challenges and best practices to prevent such incidents. The author, in his current role, performs audits and inspections of a variety of high-hazard industries in North America, including petroleum refineries, chemicals, petrochemicals, manufacturing, etc. In this paper, he shares real life scenarios, examples, and case studies from high hazards operating facilities including key challenges and best practices. This case study will provide a clear understanding of the importance of near miss incident investigation. The incident was a Safe operating limit excursion. The case describes the deficiencies in management programs, the competency of employees, and the culture of the corporation that includes hazard identification and risk assessment, maintaining the integrity of safety-critical equipment, operating discipline, learning from process safety near misses, process safety competency, process safety culture, audits, and performance measurement. Failure to identify the hazards and manage the risks of highly hazardous materials and processes is one of the primary root-causes of an incident, and failure to learn from past incidents is the leading cause of the recurrence of incidents. Several investigations of major incidents discovered that each showed several warning signs before occurring, and most importantly, all were preventable. The author will discuss why preventable incidents were not prevented and review the mutual causes of learning failures from past major incidents. The leading causes of past incidents are summarized below. Management failure to identify the hazard and/or mitigate the risk of hazardous processes or materials. This process starts early in the project stage and continues throughout the life cycle of the facility. For example, a poorly done hazard study such as HAZID, PHA, or LOPA is one of the leading causes of the failure. If this step is performed correctly, then the next potential cause is. Management failure to maintain the integrity of safety critical systems and equipment. In most of the incidents, mechanical integrity of the critical equipment was not maintained, safety barriers were either bypassed, disabled, or not maintained. The third major cause is Management failure to learn and/or apply learning from the past incidents. There were several precursors before those incidents. These precursors were either ignored altogether or not taken seriously. This paper will conclude by sharing how a well-implemented operating management system, good process safety culture, and competent leaders and staff contributed to managing the risks to prevent major incidents.

Keywords: incident investigation, risk management, loss prevention, process safety, accident prevention

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Authors: Tahsien Okasha

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Transplantation medicine is one of the most challenging and complex areas of modern medicine. Some of the key areas for medical management are the problems of transplant rejection, during which the body has an immune response to the transplanted organ, possibly leading to transplant failure and the need to immediately remove the organ from the recipient. When possible, transplant rejection can be reduced through serotyping to determine the most appropriate donor-recipient match and through the use of immunosuppressant drugs. Postoperative care actually begins before the surgery in terms of education, discharge planning, nutrition, pulmonary rehabilitation, and patient/family education. This also allows for expectations to be managed. A multidisciplinary approach is the key, and collaborative team meetings are essential to ensuring that all team members are "on the same page." .The following clinical pathway map and guidelines with the aim to decrease alteration in clinical practice and are intended for those healthcare professionals who look after organ transplant patients. They are also intended to be useful to both medical and surgical trainees as well as nurse specialists and other associated healthcare professionals involved in the care of organ transplant patients. This pathway is general pathway include the general guidelines that can be applicable for all types of organ transplant with special considerations to each organ.

Keywords: postoperative care, organ transplant, clinical pathway, patient

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Authors: Federica Marangio

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This study looks at the triangle of knowledge: research-education-innovation as growth engine of an inclusive and sustainable society, where the research is the strategic process which allows the acquisition of knowledge, innovation appraises the knowledge acquired and the education is the enabling factor of the human capital to create entrepreneurial capital. Where does Italy and China stand in the global geography of innovation? Europe is calling on a smart, inclusive and sustainable growth through a specializing process that looks at the social and economic challenges, able to understand the characteristics of specific geographic areas. It is easily questionable why it is not as simple as it looks to come up with entrepreneurial ideas in all the geographic areas. Seen that the technology plus the human capital should be the means through which is possible to innovate and contribute to the boost of innovation culture, then the young educated people can be seen as the society changing agents and it becomes clear the importance of investigating the skills and competencies that lead to innovation. By starting innovation-based activities, other countries on an international level, are able now to be part of an healthy innovative ecosystem which is the result of a strong growth policy which enables innovation. Analyzing the geography of the innovation on a global scale, comes to light that the innovative entrepreneurship is the process which portrays the competitiveness of the regions in the knowledge-based economy as strategic process able to match intellectual capital and market opportunities. The level of innovative entrepreneurship is not only the result of the endogenous growth ability of the enterprises, but also by significant relations with other enterprises, universities, other centers of education and institutions. To obtain more innovative entrepreneurship is necessary to stimulate more synergy between all these territory actors in order to create, access and value existing and new knowledge ready to be disseminate. This study focuses on individual’s lived experience and the researcher believed that she can’t understand the human actions without understanding the meaning that they attribute to their thoughts, feelings, beliefs and so given she needed to understand the deeper perspectives captured through face-to face interaction. A case study approach will contribute to the betterment of knowledge in this field. This case study will represent a picture of the innovative ecosystem and the entrepreneurial mindset as a key ingredient of endogenous growth and a must for sustainable local and regional development and social cohesion. The case study will be realized analyzing two Chinese companies. A structured set of questions will be asked in order to gain details on what generated success or failure in the different situations with the past and at the moment of the research. Everything will be recorded not to lose important information during the transcription phase. While this work is not geared toward testing a priori hypotheses, it is nevertheless useful to examine whether the projects undertaken by the companies, were stimulated by enabling factors that, as result, enhanced or hampered the local innovation culture.

Keywords: Entrepreneurship, education, geography of innovation, education.

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Authors: Giorgia Zotti

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This research comprehensively investigates the multifaceted interplay determining school performance, individual backgrounds, and regional disparities within the landscape of Italian secondary education. Leveraging data gleaned from the INVALSI 2021-2022 database, the analysis meticulously scrutinizes two fundamental distributions of educational achievements: the standardized Invalsi test scores and official grades in Italian and Mathematics, focusing specifically on final-year secondary school students in Italy. Applying a comprehensive methodology, the study initially employs Data Envelopment Analysis (DEA) to assess school performances. This methodology involves constructing a production function encompassing inputs (hours spent at school) and outputs (Invalsi scores in Italian and Mathematics, along with official grades in Italian and Math). The DEA approach is applied in both of its versions: traditional and conditional. The latter incorporates environmental variables such as school type, size, demographics, technological resources, and socio-economic indicators. Additionally, the analysis delves into regional disparities by leveraging the Theil Index, providing insights into disparities within and between regions. Moreover, in the frame of the inequality of opportunity theory, the study quantifies the inequality of opportunity in students' educational achievements. The methodology applied is the Parametric Approach in the ex-ante version, considering diverse circumstances like parental education and occupation, gender, school region, birthplace, and language spoken at home. Consequently, a Shapley decomposition is applied to understand how much each circumstance affects the outcomes. The outcomes of this comprehensive investigation unveil pivotal determinants of school performance, notably highlighting the influence of school type (Liceo) and socioeconomic status. The research unveils regional disparities, elucidating instances where specific schools outperform others in official grades compared to Invalsi scores, shedding light on the intricate nature of regional educational inequalities. Furthermore, it emphasizes a heightened inequality of opportunity within the distribution of Invalsi test scores in contrast to official grades, underscoring pronounced disparities at the student level. This analysis provides insights for policymakers, educators, and stakeholders, fostering a nuanced understanding of the complexities within Italian secondary education.

Keywords: inequality, education, efficiency, DEA approach

Procedia PDF Downloads 75