Education

Dataset is intended for studying how student programming styles and usage of IDE differs between students who plagiarise their homework and students who solve them honestly.
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The project is conceptualized to 'Geo Web-Based Facility Mapping for Zone-2 in Greater Visakhapatnam Municipal Corporation- GVMC in Visakhapatnam, India'. The main objective is to share the spatial data to the public to help them find the information about the nearest Hospital, ATM, Educational institutions, petrol filling stations, and supermarkets by providing both web map services and web coverage services using QGIS Cloud.
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Accurate information about crop rotation is essential for administrators, managers and various government departments for assessment, monitoring, and management of various resources for crop escalation. Radar remote sensing, because of its all-weather capability and assured uninterrupted data supply can show a substantial part in the evaluation of crop rotation.
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This dataset contains the images used in the paper "Fine-tuning a pre-trained Convolutional Neural Network Model to translate American Sign Language in Real-time".
M. E. Morocho Cayamcela and W. Lim, "Fine-tuning a pre-trained Convolutional Neural Network Model to translate American Sign Language in Real-time," 2019 International Conference on Computing, Networking and Communications (ICNC), Honolulu, HI, USA, 2019, pp. 100-104.
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In this paper, the influencing factors of university teachers' intention to flow in Hebei Province are taken as the research object. The universities in the province are divided into public undergraduates, private undergraduates, public colleges, and private colleges. Questionnaires are sent to 39 colleges.
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The correlation matrix and the survey items are provided for the design and validation of an instrument to evaluate the implementation of six sigma critical success factors during the realization of improvement projects in higher education institutions.
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Archival bundle of District Information System for Education (DISE) Delhi primary to upper-primary level schools in academic session 2012-2013. DISE is a school-level dataset consisting of government-recognized schools. It is a joint initiative of the Government of India, UNICEF and the National University of Education and Planning (NUPEA).
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The database was created with records of psychosocial risk level colombian teachers school using physiological variables from May 2016 to December 2017 in five municipalities of a metropolitan area of city in Colombia. The application of physiological variables was made to the people who voluntarily participated in the study. The names and personal data were kept by the researcher.
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Datasets contain survey data of 873 rural poor households in the states of Maharashtra, Odisha, Madhya Pradesh, and Rajasthan.
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Abstract
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