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Dataset results
52 results for “Educational Resources”
Big Data to Knowledge (BD2K) Training Coordinating Center (TCC) Educational Resource Discovery Index (ERuDIte) as Linked Data
<p>This is a release of the Big Data to Knowledge (BD2K) Training Coordinating Center (TCC) Educational Resource Discovery Index (ERuDIte) as Linked Data.<br> <br> ERuDIte contains over 11,000 training resources on data science including courses (MOOCs), video tutorials, conference talks, and other materials. The metadata of these resources is described uniformly using schema.org. In addition, we use machine learning techniques to tag each resource with concepts from the Data Science Education Ontology (DSEO), which we developed to further describe the contents of the training resources. Resource relevance and tags are curated by experts to ensure high quality. Finally, we map the references to people and organizations in the learning resource metadata to entities in DBpedia, DBLP, and ORCID, thus embedding our collection in the web of linked data. Our collection is continually growing. We hope that ERuDIte will provide a framework to foster open linked educational resources on the web.<br> <br> Distributed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-nc-sa/4.0/)</p>
Umfragedaten: Studentische Perspektiven auf Open Educational Resources in der Rechtswissenschaft
<p>Der Datensatz enthält die Rohdaten, ausgewerteten Daten und das dazugehörige R-Skript für eine 2022 durchgeführte Umfrage unter Studierenden der Rechtswissenschaft in Deutschland zu Chancen und Grenzen von Open Educational Resources. Für weitere Fragen zu der Umfrage wenden Sie sich bitte an <a href="https://www.jura.uni-muenster.de/de/institute/lehrstuhl-fuer-oeffentliches-recht-voelker-und-europarecht-sowie-empirische-rechtsforschung/team/weitere-personen/max-milas/">Max Milas</a> oder <a href="https://www.jura.fu-berlin.de/fachbereich/einrichtungen/oeffentliches-recht/lehrende/calliessc/Mitarbeiterinnen-und-Mitarbeiter/Wissenschaftliche_Mitarbeiter_innen/Valentina-Chiofalo/index.html">Valentina Chiofalo</a>. </p>
South African higher education data 1 - Data resources
<p>GIS-based map visualisation of the data resources providing open data on South African higher education data. Generated as part of research conducted for the 'Use of open data in the governance of South African higher education' research project, in the IDRC/WWWF 'Exploring Emerging Impacts of Open Data in the South' initiative.</p> <p> </p>
Data from: Work-Life Conflict Among Higher Education Institution Workers' During COVID-19: A Demands-Resources Approach
<p>Dataset from: Work-Life Conflict Among Higher Education Institution Workers' During COVID-19: A Demands-Resources Approach</p>
The use of lexicographic resources in Croatian primary and secondary education - Survey Data
<p>The dataset contains the data collected in the survey on the use of dictionaries and other lexicographic resources in Croatian primary and secondary education, which was conducted from 1 February to 17 February 2023.</p>
Resources for the article "Investigating the role of educational robotics in formal mathematics education"
<p>This repository contains the material required to reproduce the study looking to investigate the role of educational robotics in formal mathematics education for 15 year old students in the French speaking region of Switzerland. This includes :</p> <ul> <li> <p>Pedagogical content in the form of both teacher and student resources</p> </li> <li> <p>Data collection ressources (surveys and tests)</p> </li> </ul> <p>If you use any of the resources provided in this repository, please cite the following</p> <p>• The Zenodo repository, DOI: 10.5281/zenodo.4649842</p> <p>• The corresponding article : Brender, J., El-Hamamsy, L., Bruno, B., Chessel-Lazzarotto, F., Zufferey, J.D., Mondada, F. (2021). Investigating the Role of Educational Robotics in Formal Mathematics Education: The Case of Geometry for 15-Year-Old Students. In: De Laet, T., Klemke, R., Alario-Hoyos, C., Hilliger, I., Ortega-Arranz, A. (eds) Technology-Enhanced Learning for a Free, Safe, and Sustainable World. EC-TEL 2021. Lecture Notes in Computer Science(), vol 12884. Springer, Cham. https://doi.org/10.1007/978-3-030-86436-1_6</p> <p>• Licence : CC-BY</p>
South African Open Data in Higher Education: Sources, resources and providers
<p>Spreadsheet of data sourced on South African sources, resources and providers of higher education open data. Composed through desk review as principle component of the situational analysis conducted for the 'Use of open data in the governance of South African higher education' research project, in the IDRC/WWWF 'Exploring Emerging Impacts of Open Data in the South' initiative.</p>
Finding Open Educational Resources and Courses
<p>This is a flyer designed for the CLARIN Annual Conference 2023 to raise awareness about the platforms available within the CLARIN and DARIAH research infrastructures to create, host and disseminate <strong>open learning and training resources</strong>, such as the <a href="https://www.clarin.eu/content/learning-hub"><i>CLARIN Learning Hub</i></a><i>, </i><a href="https://campus.dariah.eu/"><i>DARIAH Campus</i></a><i>,</i><a href="https://teach.dariah.eu/"><i> #dariahTeach</i></a><i>, </i><a href="https://marketplace.sshopencloud.eu/"><i>SSH Open Marketplace</i></a><i>, </i><a href="https://dhcr.clarin-dariah.eu/info"><i>DH Course Registry</i></a> and the learning resources developed in the <a href="https://upskillsproject.eu/deliverables/io3/upskills_learning_materials/"><i>UPSKILLS project</i></a>.</p>
Figures 2 and 3 in HighRes for Springer book chapter "Online Infrastructures For Open Educational Resources"
<p>Figure 2 and Figure 3 in high resolution for the book chapter:</p> <p>Marín, V. I., & Villar-Onrubia, D. (in press, 2022). Online Infrastructures For Open Educational Resources. In I. Jung & O. Zawacki-Richter (Eds.), <em>Handbook of Open, Distance and Digital Education</em> (Global Perspectives and Internationalization). Springer. <a href="https://doi.org/10.1007/978-981-19-0351-9_18-1">https://doi.org/10.1007/978-981-19-0351-9_18-1</a></p> <p>----</p> <p>Details for the figures:</p> <p>Fig. 2 Examples of national and regional digital infrastructures in Europe. (Note: The original figure of the Europe map was created by Commons user Alexrk2, CC BY-SA 3.0, shared via Wikimedia Commons)</p> <p>Figure 3. Examples of national and regional digital infrastructures in South America. (Note: The original figure of the South America map was created by TUBS, CC BY-SA 3.0, shared via Wikimedia Commons)</p>
Data from: Building communities of teaching practice and data-driven open education resources with NEON faculty mentoring networks
<p>With the growing availability and accessibility of big data in ecology, we face an urgent need to train the next generation of scientists in data science practices and tools. One of the biggest barriers for implementing a data-driven curriculum in undergraduate classrooms is the lack of training and support for educators to develop their own skills and time to incorporate these principles into existing courses or develop new ones. Alongside the research goals of the National Ecological Observatory Network (NEON), providing education and training are key components for building a community of scientists and users equipped to utilize large-scale ecological and environmental data. To address this need, the NEON Data Education Fellows program formed as a collaborative Faculty Mentoring Network (FMN) between scientists from NEON and university faculty interested in using NEON data and resources in their ecology classrooms. Like other FMNs, this group has two main goals: 1) to provide tools, resources, and support for faculty interested in developing data-driven curriculum, and (2) to make teaching materials that have been implemented and tested in the classroom available as open educational resources for other educators. We hosted this program using an open education and collaboration platform from the Quantitative Undergraduate Biology Education and Synthesis (QUBES) project. Here, we share lessons learned from facilitating five FMN cohorts and emphasize the successes, pitfalls, and opportunities for developing open education resources through community-driven collaborations.</p>
Resources for BMF CP72: The effectiveness of knowledge management systems in motivation and satisfaction in Vietnamese higher education institutions
<p>Code and data for reproducing the results in "BMF CP72: The effectiveness of knowledge management systems in motivation and satisfaction in Vietnamese higher education institutions" are available here.</p>
The Use of Open Educational Resources (OERs) in Teaching and Learning in Higher Education Distance Learning Programmes in Cameroon
<p>A cross sectional descriptive analysis was adopted for this study. The goal was to was find out the use OERs in teaching and learning in higher education distance learning by taking a snapshot from a cross-section of the population. The institution under study is the University of Buea. The research targeted all 25 students at the master level of the Distance Education Program in the Faculty of Education, University of Buea. All the students were purposively sampled due to the small nature of the target population. A carefully designed questionnaire was used for data collection. The questionnaire had both closed and opened-ended questions which required respondents to select from a variety of responses to cover the research questions. Data was calculated and presented using frequencies tables and bar charts. After getting description of student’s responses, an analysis was done to show the situation of the use of OERs and in teaching and learning.</p>
OpenIng - Open Access und Open Educational Resources in den Ingenieurwissenschaften : Fragebogen zur bundesweiten Umfrage
<p>Im Rahmen eines vom Bundesministerium für Bildung und Forschung (BMBF) geförderten Verbundprojekts der TU Darmstadt, TU Braunschweig und der Universität Stuttgart startete im Oktober 2018 eine Befragung zum Publikationsverhalten in den Ingenieurwissenschaften im deutschsprachigen Raum. Ziel des Projekts OpenIng ist, nach den Ergebnissen einer Bedarfsermittlung zielgerichtete Services zu etablieren, die das Publizieren in Open Access erleichtern sollen. Forscherinnen und Forscher waren aufgerufen, sich an der Umfrage zu beteiligen und hiermit an ihr Fach angepasste Services mit zu entwickeln und so den Prozess Richtung freie Verfügbarkeit von Wissenschaft mit zu gestalten. Grundlage für eine Entwicklung neuer Angebote sind die Ergebniss aus den Online-Fragebögen.</p>
A Systematic Mapping of the Classification of Open Educational Resources for Computer Science Education in Digital Sources (Data)
<p>Data from a Systematic Mapping of the classification of Open Educational Resources for Computer Science Education.</p> <p>Content:</p> <ul> <li>Studies selected</li> <li>Digital sources used to classify Open Educational Resources for Computer Science Education</li> <li>Computer Science domains explored by Open Educational Resources</li> <li>Approaches for the classification of Open Educational Resources for Computer Science Education</li> </ul>
DIALLS Dataset of evaluations of Open Educational Resources – The Cultural Literacy Learning Programme resources
<p>This dataset was used to support the development of the DIALLS project’s (Dialogue and Argumentation for cultural Literacy Learning in Schools, www.dialls2020.eu/) teaching and learning materials as open access online educational resources (OER). It consists of quantitative data (i) evaluating the three OER (i.e., professional development (PD) materials, lesson plans (LP), Scale of Progression for Cultural Literacy Learning (SPCLL)) and (ii) assessing the discussion forum as a platform for building a DIALLS community of practice. <em> N</em> = 140 teachers from Germany, UK, Portugal, and Israel participated in the surveys over the course of six months (September 2020 to February 2021). </p> <p>For each country, there are four datasets from the surveys. For data collection, the surveys have been translated into the partner countries’ language, open feedback is translated from the respective languages and now in English (i.e., Translation from German, English, Portuguese, Hebrew). </p> <p>Based on Kirkpatrick and Kirkpatrick’s (2006) evaluation model and the Value Creation Framework (VCF) (Wenger et al., 2011), the surveys have been developed and the discussion forum designed. From this, items regarding the materials’ application, content, design, and value were included in the assessment of the quality of PD materials, lesson plans, and SPCLL. The quality of the discussion forum was assessed regarding its motivation, participation, topic, and value. </p> <p>Considering the context, the dataset is relevant to the following areas of research: Communities of Practice, OER, Teachers’ professional development. </p> <p>The dataset is organised in 1 file (merged quantitative data from all four surveys and all four partners). A detailed description of the dataset can be accessed in a PDF file. Further, the provided codebook in the "variable view window" in SPSS explains the variables and values. </p>
CLARA Knowledge Graph of licensed educational resources (using RDF-star, Standard reification, Singleton properties, or Named graphs)
<p><strong>CLARA</strong><br>This deposit is part of the <a href="https://project.inria.fr/clara/">CLARA project</a>. The CLARA project aims to empower teachers in the task of creating new educational resources. And in particular with the task of handling the licenses of reused educational resources.</p> <p>The present deposit contains the RDF files created using an RDF mapping (<a href="https://rml.io/">RML</a>) and a mapper (<a href="https://github.com/morph-kgc/morph-kgc">Morph-KGC</a>). It also contains the files JSON used as input. The corresponding pipeline can be found on <a href="https://gitlab.univ-nantes.fr/clara/pipeline">Gitlab</a>. The data used in that pipeline originate from <a href="https://www.x5gon.org/">X5GON</a>, a European project aiming to generate and gather open educational resources.</p> <p><strong>Knowledge graph content</strong><br>The present Knowledge Graph contains information about 45K Educational Resources (ERs) and 135K subjects (extracted from DBpedia).<br>That information contains </p> <ul> <li>the author,</li> <li>its title and description</li> <li>the license,</li> <li>a URL to the resource itself,</li> <li>the language of the ER,</li> <li>its mimetype,</li> <li>and finally which subject it talks about, and to what extent.</li> </ul> <p><br>That extent is given by two scores: a PageRank score and a Cosinus score.</p> <p>A particularity of the knowledge graph is its heavy use of RDF reification, across large multi-valued properties.<br>Thus four versions of the knowledge graph exist, using Standard reification, Singleton property, Named graphs, and RDF-star.</p> <p>The Knowledge Graph also contains <a href="https://databus.dbpedia.org/dbpedia/generic/categories">categories</a> originating from DBpedia. They help precise the subjects that are also extracted from DBpedia.</p> <p>The KG.zip files contain five types of files:</p> <ul> <li><strong>Authors_[</strong>X<strong>].nt</strong> - Those contain the authors' nodes, their type, and name.</li> <li><strong>ER_[</strong>X<strong>].nt/nq/ttl</strong> - Those contain the ERs and their information using the respective RDF reification model.</li> <li><strong>categories_skos_[</strong>X<strong>].ttl</strong> - Those contain the hierarchy of DBpedia categories.</li> <li><strong>categories_labels.ttl </strong>- This file contains additional information about the categories.</li> <li><strong>categories_article.ttl</strong> - This file contains the RDF triples that link the DBpedia subjects to the DBpedia categories.</li> </ul> <p> </p> <p><strong>JSON content</strong></p> <p>The original dataset was cut into multiple JSON files in order to make its processing easier. DBpedia categories were extracted as RDF and aren't present in the JSON files.<br><br>There are two types of files in the input-json.zip file:</p> <ul> <li><strong>authors_[</strong>X<strong>].json</strong> - Which lists the authors names</li> <li><strong>ER_[</strong>X<strong>].json</strong> - Which lists the ERs and their related information.<br>That information contains: <ul> <li>their <em>title.</em></li> <li>their <em>description.</em></li> <li>their <em>language</em> (and <em>language_detected</em>, only the first one is used in the pipeline here).</li> <li>their <em>license.</em></li> <li>their <em>mimetype.</em></li> <li>the <em>authors.</em></li> <li>the <em>date</em> of creation of the resource.</li> <li>a <em>url</em> linking to the resource itself.</li> <li>the subjects (named <em>concepts</em>) associated with the resource. With the corresponding scores.</li> </ul> </li> </ul> <p> </p> <p>If you do use this dataset, you can cite the corresponding paper:</p> <ul> <li>Kieffer, M., Fakih, G. & Serrano-Alvarado, P. (2023). Evaluating Reification with Multi-valued Properties in a Knowledge Graph of Licensed Educational Resources. Semantics, Leipzig, Germany.</li> </ul>
Pilot Evaluation of AboutFace: Novel Peer Education Resource for Veterans
ClinicalTrials.gov study NCT02486692. IPD Sharing: NO. Countries: 1. Publications: 3.
The Resource Information Program for Parents on Lifestyle and Education
ClinicalTrials.gov study NCT02330588. IPD Sharing: NO. Countries: 1. Publications: 2.
Data from: Building communities of teaching practice and data-driven open education resources with NEON faculty mentoring networks
Open the record for dataset details and reuse information.
Conformity of E-Learning for Teaching and Learning in Ethiopian Higher Education: Analysis on User-Friendliness of E-Resources
<p>The study investigated the practicability of e-learning for teaching and learning in Ethiopian higher education in terms of availability, clarity, accessibility in terms of accommodation and economy. The research looked into the roles of e-provisions based on the country’s Information and Communication Technology (ICT) in education policy guidelines as benchmark. Descriptive survey research design was used in the research since the study focused on indicating status than in-depth institution-based analysis of technology-use in education. Two higher institutions were selected for their relative proximity and viability for data collection. Data for the research were collected from 150 students, 4 technical support renderers and 30 teachers. Instruments of data collection were binary mode questionnaires and semi-structured interviews. Findings indicated shortage in a purpose-orientation, weak cross-institutional interchange and low mainstreaming of e-resources for course-provision. Though initiatives were high to use e-resources across lessons, shortage in internet access and prevailing digital divides were common barriers. Selective use of e-learning was witnessed on the part of technical support providers. multiplier effects in sharing experiences were not practiced among the teachers. Purpose-conformity was met on highly individualized bases. inter-institutional experiential exchange was insufficient though there was high emphasis on supporting selected instructional strings.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.