Effective Data Collection Method Research Articles

Accuracy of Determination of Corresponding Points from Available Providers of Spatial Data—A Case Study from Slovakia

Mapping the terrain and the Earth’s surface can be performed through non-contact methoYes, that is correct.ds such as laser scanning. This is one of the most dynamic and effective data collection methods. This case study aims to analyze the usability of spatial data from available sources and to choose the appropriate solutions and procedures for processing the point cloud of the area of interest obtained from available web applications. The processing of the point cloud obtained by airborne laser scanning results in digital terrain models created in selected software. The study also included modeling of different types of residential development, and the results were evaluated. Different data sources may have compatibility issues, which means that the position of the same object from different spatial data databases may not be identical. To address this, deviations of the corresponding points were determined from various data sources such as Real Estate Cadaster, ZBGIS Buildings, LiDAR point cloud, orthophoto mosaic, and geodetic measurements. These deviations were analyzed according to their size and orientation, with the average deviations ranging from 0.22 to 0.34 m and standard deviations from 0.11 to 0.20 m. The Real Estate Cadaster was used as the correct basis for comparison. The area of the building was also compared, with the slightest difference being present between the Real Estate Cadaster and geodetic measurement. The difference was zero after rounding the area to whole numbers. The maximum area difference was +5 m2 for ZBGIS Buildings.

The “Ins and Outs” of APCs: An Overview of Automatic Passenger Counters

Experience has shown that manual data collection via ridechecks is one of the most cost effective data collection methods for most transit systems when evaluating ridership levels and system performance. Unfortunately, this manual method of collecting ridership data and system operational information produces both limited system wide and route specific reports due to the amount of manual ride checking required and the manual data processing involved. This is especially true for huger transit systems. One possible alternate solution for a transit system to meet its need for reliable, accurate, detailed, up-to-date, and cost-effectively-obtained ridership data is through the use of automatic passenger counters, or APCs. Unlike manual ridechecks, an APC system provides a transit system with an automated method for collecting information on the number of passenger boardings and alightings at a variety of system levels including route, route segment, or specific bus stops by time of day and by day of week, for example. This paper provides a general overview of AFC systems. Included is a discussion of APC components, a review of typical transit system data needs, a list of current worldwide APC vendors, the results of a survey of North American transit systems related to APC usage, and a summarization of important issues for transit systems to consider when contemplating integrating APC systems on board their vehicles.

High-risk pregnant women\u2019s experiences of the receiving prenatal care in COVID-19 pandemic: a qualitative study

BackgroundWomen with high-risk pregnancies are among the most vulnerable groups that require additional precautionary measures against the spread of COVID-19 plus receiving prenatal care. Yet, there is limited information on the status of prenatal care in women with high-risk pregnancies. The purpose of this study was to explore the experiences of women with high-risk pregnancies who were receiving prenatal care during the COVID-19 pandemic.MethodsThe present qualitative study was conducted on mothers with high-risk pregnancies from September 2020 to March 2021. Purposeful sampling continued until achieving data saturation. Ghaem, Ommolbanin, and Imam Reza in Mashhad, Iran served as the research environment. Face-to-face and semi-structured interviews were effective data collection methods. Each interview lasted between 20 to 45 min (on average 30). The total number of participants was 31. Data analysis was carried out simultaneously with data collection using the qualitative content analysis method developed by Granheim and Landman (2004).ResultsFollowing the reduction and analysis of data from women in high-risk pregnancies, as well as their perceptions and experiences with health services during the COVID-19 pandemic, eight subcategories and three main categories were identified, including 1) “Negative psychology responses,” 2) “Adoption behavior,” and 3) “Adjustment of health services in mutual protection.”Fear, anxiety, stress, feelings of loneliness, sadness, depression, guilt, doubt and conflict in receiving services were examples of negative psychological responses. The adaptive behaviors’ category reflected the behaviors of women with high-risk pregnancies in the context of the COVID COVID-19 pandemic. The Adjustment of health services in mutual protection indicated that health workers took preventive and protective measures against COVID-19, which, in addition to protecting themselves and their clients against COVID-19, gave women a sense of security.ConclusionReceiving prenatal care during the COVID-19 pandemic presents challenges for women with high-risk pregnancies, negatively impacting their psychological state and health-seeking behavior. Supportive and preventive care can ensure that women with high-risk pregnancies receive optimal prenatal care that focuses on COVID-19 prevention. We recommend implementing screening, psychological counseling, and education for women with high-risk pregnancies, as well as ensuring that they have access to women-centered health care services.

The Effect of Direct Learning Model with Routine Practice on Self-Efficacy and Student Learning Outcomes

This research was conducted because Self-Efficacy and Student Learning Outcomes are still weak. The direct learning model with routine practice is thought to be a factor influencing the Self-Efficacy and Student Learning Outcomes of students in higher education. This study aims to determine how the direct learning model with regular practice affects student self-efficacy and swimming learning outcomes. This type of research is a quantitative correlation with the research population is 90 students who take swimming courses in Higher Education. The research sample was selected by purposive random sampling. The instrument used is a questionnaire, because it is an effective data collection method to test the variables to be measured and the answers expected by the respondents. The questionnaire uses a Likert scale by providing an opportunity to answer each item. Hypothesis testing was carried out with the SPSS 26.0 program using correlational analysis. The results showed that the use of a direct learning model with regular practice will increase students' self-efficacy, as well as improve learning outcomes in swimming lessons.

The effect of hypnotherapy methods on understanding and readiness on swimming learning in higher education

This research was conducted because understanding and readiness for swimming learning are still problematic. Hypnotherapy methods are assumed to be the factors that influence the understanding and readiness of swimming learning of students in higher education. This study aims to determine the effect of using hypnotherapy methods on the understanding and readiness of swimming lessons in higher education. This research uses the quantitative correlation method. The population is 150 students who take swimming lessons in higher education, and a sample of 50 students who were selected using purposive random sampling. The questionnaire is an effective data collection method to test the variables to be measured and the answers expected by the respondents. The questionnaire applies a Likert scale by providing an opportunity to answer each item. Data were analyzed using regression analysis. The results showed that (1) there was an increase in students' understanding of swimming lessons using hypnotherapy methods, (2) there was an increase in student readiness in swimming lessons using hypnotherapy methods.

Differences in the three swimming style learning outcomes from gender

This research was conducted because swimming style learning outcomes are still weak in terms of gender. This study aims to determine the interaction between gender and swimming style learning outcomes. This type of research is quasi-experimental using a 2x3 factorial design. The research method used is descriptive-comparative, with a sample of 100 sports education students. The questionnaire is an effective data collection method to test the variables to be measured and the answers expected by the respondents. The questionnaire applies a Likert scale by providing an opportunity to answer each item. Hypothesis testing was carried out with the SPSS 22.0 program using one-way ANOVA, and two-way ANOVA analysis. The results showed that (1) there were differences in the learning outcomes of swimming style in terms of gender, (2) there was an interaction between gender and swimming style. The learning outcomes of male students' swimming styles were higher than female students, both in the breaststroke, butterfly, and freestyle.

Utilization of Data Analysis and Decision Support System in the Chinese General Hospitals

Abstract With the deepening of medical system reform, there are unprecedented challenges for China’s medical industry. In order to promote hospital core competitiveness, medical enterprises urgently need to be based on industry demand. The establishment of a unified data platform is an important aspect of this process, however the hospital’s data inherent characteristics, makes the effective management a difficult task. This difficulty creates a hurdle for the implementation of an integrated information technology. Considering these obstacles, opting an effective method of data collection, data analysis and data management has become a concern for hospital staff. The hospital data analysis and decision support system make full use of the massive data deposited in the existing digital information system of the hospital. This cannot only facilitate the manager to monitor the operation and management of the hospital, but also predict its future development direction based on the historical data. This article mainly focuses on the characteristics of hospital data analysis and decision support, and application. We studied the hospital’s data analysis and decision support system for advanced technology as our guide.

Teacher-reported IEP goal data collection methods

Utilizing effective data collection methods to track student progress on Individual Education Program (IEP) goals is essential to quality programming and meeting each student’s specific needs. This study surveyed special education teachers in four midwestern states to understand IEP data collection methods and assessment training. Results indicated that IEP data collection methods varied by state and teaching level (elementary, middle, and high school), with the most frequently reported methods as observation (elementary and middle levels) and grades (high school level). Teachers reported lack of time, resources, and training as barriers to data collection. Recommendations provide specific areas of focus for professional development, educator preparation programs, and mentoring based on the results of this research. Supplemental data for this article is available online at https://doi.org/10.1080/1045988X.2021.1980849.

The empirical analysis of production-based entrepreneurship training model, readiness and locus of control towards students entrepreneurship self efficacy

This research was conducted because the students' self-efficacy in entrepreneurship is still low. Production-based entrepreneurship training model, learning readiness is assumed to be a factor that affects student entrepreneurship self-efficacy. The purpose of this study was to examine the contribution of the production-based entrepreneurship training model, learning readiness, and locus of control to student entrepreneurship self-efficacy. This study uses quantitative methods with multiple regression. The population is all students who take the general course of entrepreneurship in Higher Education as many as 500 people, and a sample of 200 students who are selected using proportional stratified random sampling. The questionnaire stands as an effective data collection method to examine the variables to be measured and the answers expected by the respondents. The questionnaire applied the Likert scale by providing opportunities to answer each item. Data were analyzed using multiple regression. The research findings show that there is a joint contribution of the production-based entrepreneurship training model, learning readiness, and locus of control to the entrepreneurial self-efficacy of students

Development of an Effective Method of Data Collection for Advertising and Marketing on the Internet

Development of an Effective Method of Data Collection for Advertising and Marketing on the Internet

ANNMDD: Strength of Artificial Neural Network Types for Medical Diagnosis Domain

The abundance of medical evidence in health institutions necessitates the creation of effective data collection methods for extracting valuable information. For several years, scholars focused on the use of computational techniques and data processing techniques in order to enhance the study of broad historical datasets. There is a deficiency to investigate the collected data of health disease in the data sources such as COVID-19, Chronic Kidney, Epileptic Seizure, Parkinson, Hard diseases, Hepatitis, Breast Cancer and Diabetes, where millions of people are killed in the world by these diseases. This research aims to investigate the neural network algorithms for different types of medical diseases in order to select the best type of neural network suitable for each disease. The data mining process has been applied to investigate the mentioned medical disease datasets. The related works and literature review of machine learning in the medical domain were studied in the initial stage of this research. Then, the experiments behind the initial stage have been designed with six neural network algorithm styles which are Multiple, Radial Based Function Network (RBFN), Dynamic, Quick and Prune algorithms. The extracted results for each algorithm have been analyzed and compared with each other to select the perfect neural network algorithm for each disease. T-test statistical significance test has been applied as one of the investigation strategies for the NN optimal selection. Our findings highlighted the strong side of the Multiple NN algorithm in terms of training and testing phases in the medical domain.

Anonymous Authentication on Trust in Blockchain-Based Mobile Crowdsourcing

Mobile crowdsourcing (MCS) has become an effective data collection method due to its mobility, low cost, and flexibility. However, since centralized MCS confronts severe security and privacy risks in reality, many researchers are devoted to building a decentralized MCS system based on blockchain. Despite the effectiveness of these schemes, they fail to offer anonymous authentication on the trust of MCS nodes, although privacy is a main concern in MCS and trust plays an important role in a series of MCS activities, such as worker selection and truth discovery. Nevertheless, anonymous authentication on trust is not a trivial issue since trust evaluation usually conflicts with anonymity, which is a necessary privacy requirement in an open MCS environment. To tackle this problem, we leverage Intel software guard extension (SGX) and propose a scheme to anonymously authenticate trust with trustworthy trust evaluation in a blockchain-based MCS system. The scheme employs an SGX-enabled cloud server to periodically alter user public/private key pairs and mix newly altered keys among a number of faked keys in order to ensure unlinkability. Besides, we consider the unique features of MCS and work out a novel trust evaluation method by aggregating both subjective feedback and objective behaviors. Finally, we conduct several analyses and experiments to illustrate its security and efficiency.

Forecasting Chinese Stock Market Prices using Baidu Search Index with a Learning-Based Data Collection Method

In this study, to address search index selection and volatility problems, we propose a learning-based search index collection method that collects the search data fraction for modeling by learning the best criteria from robust statistics. Based on the fraction of collected search index from internet search engine ( Baidu.com ) data sources, a novel model is formulated for Chinese stock market price forecasting. We empirically test our method on the two main Chinese stock market price indexes and discover that the prediction accuracy is equivalent or superior to the benchmarks from previous studies that used alternative search index collection methods or lagged data prediction models. All prediction results outstand the importance of an effective data collection method for the robustness of forecast models and demonstrate the utility of a learning-based collection method for addressing search index collection problem, leading to a significant improvement in Chinese stock market price prediction accuracy.

МІСЦЕ І РОЛЬ СОЦІАЛЬНО-ПСИХОЛОГІЧНИХ РЕСУРСІВ В ОСВІТІ ДІТЕЙ З ОСОБЛИВИМИ ОСВІТНІМИ ПОТРЕБАМИ

У статті висвітлено поняття «соціально-психологічні ресурси» як одна з трьох груп ресурсів середовища. Розкрито визначальну роль цієї групи ресурсів у контексті впровадження освіти для дітей з особливими освітніми потребами, а також її структура, що має три компоненти: соціальні потреби, соціальні ролі та соціальні відносини. З'ясовано зв'язок структурних компонентів групи соціально-психологічних ресурсів з таким компетентціями педагогів, як пізнавально-інтелектуальна, оцінно-контрольна, комунікативна, аналітична та іншими. Проаналізовано діяльність педагогічних колективів чотирьох закладів освіти з інклюзивними класами щодо фахового супроводу дітей з особливими потребами (методів анкетування та самооцінки за методикою «Інструмент професійного розвитку педагогів», розробленою міжнародною спільнотою педагогів ISSА). Представлено тренінгову програму «Соціально-психологічні ресурси в контексті становлення особистості дитини з ООП», за якою відбувалося навчання педагогічних колективів. Проаналізовано результати, отримані після повторного вивчення стану сформованості компетенцій педагогів. Визначено орієнтир подальшої діяльності щодо удосконалення компетентності фахівців та набуття ними характеристик лідера в освіті.  &nbsp

Conducting qualitative video research with young children

PurposeThe purpose of this paper is to explore the practical use of video cameras during a study with young children.Design/methodology/approachThis paper investigates the use of video cameras in a research study of young children’s utilisation of semiotic tools to communicate during play interactions in a Francophone preschool classroom in British Columbia. It examines the practical in-the-moment decision making of the researcher to support children’s accommodation of the video camera in their play space and ensure rich data were recorded.FindingsChildren accommodated the video cameras in four distinct ways. These included: curiosity and investigation of the video cameras; engagement in the video recording process with the researcher; incorporation of the video cameras into their play; and disregard of it.Practical implicationsThe findings suggest that video recordings can be an effective method of data collection with young children and provide rich sources of data of the children and their learning through play when the researcher is flexible and responsive and supports children’s accommodation of it.Originality/valueRecent advances in recording technology have resulted in the increased use of video recordings as a resource for gathering empirical data in qualitative research. Whilst the ethical considerations related to the use of video recordings as data for analysis in research with young children have been the subject of some discussion (Flewitt, 2005), the practical experience of using video cameras has received less attention.

Data collection framework for understanding UFT within city logistics solutions

Abstract Urban Freight Transport (UFT) is a fundamental component of city life. It involves a vast range of activities resulting from relationships among different actors with conflicting needs and goals. Manufacturers are interested in fast and on-time deliveries, retailers require complete assortment and frequent deliveries, citizens wish to have easy access to goods while not losing their quality of life and City Authorities have to face negative externalities related to UFT (i.e. congestion, air and noise pollution, and safety). Concretely, few cities have a well-developed and comprehensive city logistics strategy because authorities generally focus their attention on passenger transport. When city logistics measures have been conceived and implemented, frequently private requirements have not been considered sufficiently. The European Commission includes the lack of data and understanding of freight flows among the main obstacles to the improvement of operational efficiency and planning process for a sustainable UFT in economic, social and environmental terms. Also, the research community raises the issue of the unavailability or the low quality of data on urban freight and the need to identify effective data collection methods in order to understand processes and actors’ behavior and then define appropriate city logistics solutions. The NOVELOG EU project is providing city authorities and practitioners with a new framework aimed at systematizing all data to be collected, directly or indirectly, and to be elaborated in order to understand and represent the different aspects of the UFT sector. In order to achieve a complete knowledge, the framework approaches this sector according to four main thematic pillars: 1) profile of major supply chains served in the urban area under study; 2) mapping of urban freight and service trips activity; 3) organizational and legal framework; 4) procedural and technological methods and innovations. The present paper introduces the framework and the guidance it provides to its target audiences.

Perceptions of zoonotic and animal diseases in the Van Gujjar community of North India

Humans living in and around forest areas are at increased risk of zoonotic disease transmission. The transhumant Van Gujjars of North India are one such population, but there is an absence of health data, including evidence of zoonotic diseases, in this community. Pastoral communities can have a wide breadth of knowledge of livestock diseases, but not necessarily of human diseases. This study investigated the perceptions that the Van Gujjars have specifically of zoonotic diseases, using participatory epidemiological methods, including semi-structured interviews, ranking, proportional piling, transect walks and direct observation, triangulated by informal interviews with local veterinarians. The community did not have a wide appreciation of zoonotic diseases, apart from rabies and potentially zoonotic skin diseases. In contrast, animal diseases were of much greater concern to the community; the locally-named surra (trypanosomiasis), ajar, khuriya (foot-and-mouth disease), dakhutra, gheru, taku, and ‘blood in urine’ (possibly babesiosis), being of most concern. A participatory epidemiological approach was found to be an effective method of data collection and analysis; and the findings suggest that access to health services, particularly veterinary health services, should be improved for Van Gujjars.

Data collection methods in health services research: hospital length of stay and discharge destination.

Hospital length of stay and discharge destination are important outcome measures in evaluating effectiveness and efficiency of health services. Although hospital administrative data are readily used as a data collection source in health services research, no research has assessed this data collection method against other commonly used methods. Determine if administrative data from electronic patient management programs are an effective data collection method for key hospital outcome measures when compared with alternative hospital data collection methods. Prospective observational study comparing the completeness of data capture and level of agreement between three data collection methods; manual data collection from ward-based sources, administrative data from an electronic patient management program (i.PM), and inpatient medical record review (gold standard) for hospital length of stay and discharge destination. Manual data collection from ward-based sources captured only 376 (69%) of the 542 inpatient episodes captured from the hospital administrative electronic patient management program. Administrative data from the electronic patient management program had the highest levels of agreement with inpatient medical record review for both length of stay (93.4%) and discharge destination (91%) data. This is the first paper to demonstrate differences between data collection methods for hospital length of stay and discharge destination. Administrative data from an electronic patient management program showed the highest level of completeness of capture and level of agreement with the gold standard of inpatient medical record review for both length of stay and discharge destination, and therefore may be an acceptable data collection method for these measures.

Online snowballing: An effective method of data collection in australian young adults

Online snowballing: An effective method of data collection in australian young adults

Text Messaging Data Collection for Monitoring an Infant Feeding Intervention Program in Rural China: Feasibility Study

BackgroundAn effective data collection method is crucial for high quality monitoring of health interventions. The traditional face-to-face data collection method is labor intensive, expensive, and time consuming. With the rapid increase of mobile phone subscribers, text messaging has the potential to be used for evaluation of population health interventions in rural China.ObjectiveThe objective of this study was to explore the feasibility of using text messaging as a data collection tool to monitor an infant feeding intervention program.MethodsParticipants were caregivers of children aged 0 to 23 months in rural China who participated in an infant feeding health education program. We used the test-retest method. First, we collected data with a text messaging survey and then with a face-to-face survey for 2 periods of 3 days. We compared the response rate, data agreement, costs, and participants’ acceptability of the two methods. Also, we interviewed participants to explore their reasons for not responding to the text messages and the reasons for disagreement in the two methods. In addition, we evaluated the most appropriate time during the day for sending text messages.ResultsWe included 258 participants; 99 (38.4%) participated in the text messaging survey and 177 (68.6%) in the face-to-face survey. Compared with the face-to-face survey, the text messaging survey had much lower response rates to at least one question (38.4% vs 68.6%) and to all 7 questions (27.9% vs 67.4%) with moderate data agreement (most kappa values between .5 and .75, the intraclass correlation coefficients between .53 to .72). Participants who took part in both surveys gave the same acceptability rating for both methods (median 4.0 for both on a 5-point scale, 1=disliked very much and 5=liked very much). The costs per questionnaire for the text messaging method were much lower than the costs for the face-to-face method: ¥19.7 (US $3.13) versus ¥33.9 (US $5.39) for all questionnaires, and ¥27.1 (US $4.31) versus ¥34.4 (US $5.47) for completed questionnaires. The main reasons for not replying were that participants did not receive text messages, they were too busy to reply, or they did not see text messages in time. The main reasons for disagreement in responses were that participants forgot their answers in the text messaging survey and that they changed their minds. We found that participants were more likely to reply to text messages immediately during 2 time periods: 8 AM to 3 PM and 8 PM to 9 PM.ConclusionsThe text messaging method had reasonable data agreement and low cost, but a low response rate. Further research is needed to evaluate effectiveness of measures that can increase the response rate, especially in collecting longitudinal data by text messaging.