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100 results for “educational practices”
Stories on Open Educational Practices in German Higher Education
<p><strong>Stories on Open Educational Practices in German Higher Education by Sigrid Fahrer, </strong><a href="#_oewao57q7xt8"><strong>Tamara Heck</strong></a><strong>, </strong><a href="#_fronuh2cauex"><strong>Ronny Röwert</strong></a><strong>, </strong><a href="#_oshco7u6xx6k"><strong>Naomi Truan</strong></a></p> <p><em>citation suggestion: </em>Fahrer, S., Heck, T., Röwert, R., Truan, N. (2022). Stories on Open Educational Practices in German Higher Education. Data set on autoethnographic reflections. <a href="https://doi.org/10.5281/zenodo.7326390">https://doi.org/10.5281/zenodo.7326390</a></p> <p>The stories are part of the autoethnographic reflections of the four practitioners. They are based on the following research papers:</p> <ul> <li>Cronin, C. (2017). Openness and Praxis: Exploring the Use of Open Educational Practices in Higher Education. The International Review of Research in Open and Distributed Learning, 18(5). <a href="https://doi.org/10.19173/irrodl.v18i5.3096">https://doi.org/10.19173/irrodl.v18i5.3096</a></li> <li>Hegarty, B. (2015). Attributes of Open Pedagogy: A Model for Using Open Educational Resources. Educational Technology, 55(4), 3–13. <a href="https://upload.wikimedia.org/wikipedia/commons/c/ca/Ed_Tech_Hegarty_2015_article_attributes_of_open_pedagogy.pdf">https://upload.wikimedia.org/wikipedia/commons/c/ca/Ed_Tech_Hegarty_2015_article_attributes_of_open_pedagogy.pdf</a></li> <li>Mayrberger, K. (2020). Open Educational Practices (OEP) in Higher Education. In M. A. Peters (Ed.), Springer eBook Collection. Encyclopedia of Educational Philosophy and Theory (pp. 1–7). Springer. <a href="https://doi.org/10.1007/978-981-287-532-7_710-1">https://doi.org/10.1007/978-981-287-532-7_710-1</a>.</li> <li>Wiley, D., & Hilton III, J. L. (2018). Defining OER-Enabled Pedagogy. The International Review of Research in Open and Distributed Learning, 19(4). <a href="https://doi.org/10.19173/irrodl.v19i4.3601">https://doi.org/10.19173/irrodl.v19i4.3601</a></li> </ul>
A Questionnaire to Assess the Research Practices and Services Related to the Academic and Research Staff at the Institutions of Higher Education in Palestine - Survey Data
<p>Data generated as part of a needs assessment survey conducted as part of ROMOR, a project funded by the Erasmus Plus Programme of the European Union in the period from October 2016 to October 2019. A questionnaire was prepared under the supervision of Palestinian Universities participating in the project. The results of the study will be used to create and develop institutional repositories to store the digital outputs of scientific research at the institutions of higher education in Palestine. The results will be also used to provide the vocational and academic training, and the institutional policies required to manage, organize the use, and populate the prospective repositories. This objective will contribute in promoting the access to and benefit of the results of scientific research in Palestine, and increase its impact at the local and international levels. This questionnaire was distributed to the representative of each institution, who in turn forwarded it to the suitable persons in the institution. Data was collected between January 4th and February 19th 2017. Paper and electronic versions of a questionnaire were prepared in both Arabic and English. The project coordinators at partner PS HEIs were requested to circulate the electronic questionnaire to all researchers and members of academic staff. Data was collected by ROMOR partners at:</p> ● The Islamic University of Gaza (IUG) ● Al-Quds Open University (QOU) ● Birzeit University (BZU) ● Palestine Technical University-Kadoori (KAD)
A Questionnaire to Assess the Research Practices and Services Related to the Academic and Research Staff at the Institutions of Higher Education in Palestine - Survey Data with Pie Charts
<p>Data generated as part of a needs assessment survey conducted as part of ROMOR, a project funded by the Erasmus Plus Programme of the European Union in the period from October 2016 to October 2019. A questionnaire was prepared under the supervision of Palestinian Universities participating in the project. The results of the study will be used to create and develop institutional repositories to store the digital outputs of scientific research at the institutions of higher education in Palestine. The results will be also used to provide the vocational and academic training, and the institutional policies required to manage, organize the use, and populate the prospective repositories. This objective will contribute in promoting the access to and benefit of the results of scientific research in Palestine, and increase its impact at the local and international levels. This questionnaire was distributed to the representative of each institution, who in turn forwarded it to the suitable persons in the institution. Data was collected between January 4th and February 19th 2017. Paper and electronic versions of a questionnaire were prepared in both Arabic and English. The project coordinators at partner PS HEIs were requested to circulate the electronic questionnaire to all researchers and members of academic staff. Data was collected by ROMOR partners at:</p> <p>● The Islamic University of Gaza (IUG)</p> <p>● Al-Quds Open University (QOU)</p> <p>● Birzeit University (BZU)</p> <p>● Palestine Technical University-Kadoori (KAD)</p> <p>[Data visualised as pie charts]</p> <p> </p>
Dataset for an article "Developing best practices for conducting STEM engineering projects in higher education"
<p>These articles are part of the dataset used in the article. </p> <p>These articles are anonymized manuscript drafts that were not published in the journal with other articles.</p> <p>Read more from LUMAT-B:<span> <a href="https://urn.fi/urn:nbn:fi:hulib:editori:lumatb.v9i17"> https://urn.fi/urn:nbn:fi:hulib:editori:lumatb.v9i17 </a> </span></p>
Figure 1 in Novel tools and best practices for education about invasive alien species
Figure 1. On the right: Franz Josef Glacier School student recording a European alder (Alnus glutinosa) sapling using the iNat app, New Zealand (Photo: Murray Dawson). On the left: High school students measuring tree diameter in an urban park, Portugal (Photo: Hélia Marchante) and the excavation of Bohemian knotweed (Fallopia bohemica) during a KORINA science camp, Germany (Photo: Katrin Schneider).
Dataset for the exploration of data practices in Higher Education
<p>The present dataset contains the results of a survey distributed to all the professoriate of two universities, between January and March 2020.</p> <p>The several variables present in the dataset relate to the professional areas of knowledge and activity; the ongoing data practices in relation to six scales (as published in Raffaghelli. (2019) and theoretically explored in Raffaghelli (2019b); professional learning ecologies relating data practices in teaching and research.</p> <p>The script 1 covers some analysis relating specific scales.</p> <p>Other scripts might be added /welcomed as far as successive analysis are done over the shared data.</p> <p>========</p> <p>Raffaghelli, J. (2019) Delphi Study to validate the survey exploring academic awareness and engagement with data-driven practices. Zenodo. https://doi.org/10.5281/zenodo.3581290</p> <p>Raffaghelli, J. E. (2019b). Developing a framework for educators’ data literacy in the European context: Proposal, Implications and debate. In <em>International Conference on Education and New Learning Technologies EDULEARN</em> (pp. 10520–10530). Palma de Mallorca: IATED. https://doi.org/10.21125/edulearn.2019.2655</p>
Structure of the complete review matrix developed in the context of the "Reviewing Computational Thinking in Compulsory Education: State of Play and Practices from the Field" research study
<p>This is the structure of the complete review matrix used to analyse in-depth <strong>98 selected publications from between 2016 and 2021 </strong>in the context of the "<a href="https://publications.jrc.ec.europa.eu/repository/handle/JRC128347">Reviewing Computational Thinking in Compulsory Education: State of Play and</a> <a href="https://publications.jrc.ec.europa.eu/repository/handle/JRC128347"> Practices from the Field</a>" research study. The <a href="https://computhink2study.eu/">study </a>was designed, funded, and followed by the European Commission’s Joint Research Centre (JRC) to investigate <strong>how Computational Thinking (CT) is currently positioned within compulsory school education in Europe’s various Member States, as well as outside the EU</strong>. The study was carried out from April to December 2021 by the Institute for Educational Technology of the Italian National Research Council (CNR-ITD), together with European Schoolnet (EUN) and Vilnius University (VU).</p>
General Education Teachers Use of Evidence-Based Practices in Autism Education- V1
<p>This dataset was developed to examine factors that impact teacher's use of EBPs with students with autism in mainstream schools in Ireland. </p>
Teacher Characteristics, Knowledge and Use of Evidence-Based Practices in Autism Education in Ireland_Dataset_V1
<p>Dataset to accompany the paper "<strong>Teacher Characteristics, Knowledge and Use of Evidence-Based Practices in Autism Education in Ireland". </strong>The purpose of this paper was to identify differences in teachers knowledge and use of evidence-based practices across different teacher characteristics. </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>
Open Educational Practice (OEP): collection of scenarios
<p>This diagram visualizes an exemplary selection of applications of the paradigm of open educational practices.</p> <p>Beginning with the stage of preparing a teaching unit (seminar, school lesson, etc. ) with corresponding open material (e.g. OER) (<em>light red</em>), we then move to the stage of sharing this unit and its content with the seminar, class, etc. online (<em>orange</em>). The next stage comprises making active use of the introduced content/material in a collaborative learning context as part of this seminar or working group) (<em>yellow</em>). This then might include, or be followed up by, shared instances of revising and optimization of the materials used, based on the experiences made and feedback gained during the session (<em>green</em>). Further contemplating on the experiences made, the teacher and/or the learners involved share their thoughts on these practices and examples online (<em>blue</em>).</p> <p>The diagram lists the described stages' scenarios (<em>text on the right</em>) and corresponding open tools (ideally open source) (<em>icons below the rainbow</em>).</p> <p>What needs to be emphasized here is the possibility of an iterative process optimization. This points towards the possibility of not necessarily going through Stage 1 (<em>light red</em>) in a linear way up to the last stage (<em>blue</em>), but rather making use of continuous back- and cross-referencing of neighbouring stages (<em>indicated in the graphic via fluid color transitions</em>).</p> <p>***</p> <p>The graphic is provided in various formats (ai, psd, png, jpg, eps, svg) and released as Creative Commons Zero (CC0), so as to be open for further remixing ;)</p> <p>***</p> <p><em>To the extent possible under law, <a href="https://zenodo.org/record/1183806"> Tobias Steiner</a> has waived all copyright and related or neighboring rights to '</em>Open Educational Practice (OEP): collection of scenarios<em>'. This work is published from: Germany.</em></p>
Is there a social life in Open Data? Open datasets exploring practices in Educational Technology Research
<p>In the landscape of Open Science, Open Data [OD] plays a crucial role as data are one of the most basic components of research despite their diverse formats across scientific disciplines. Opening up data is a recent concern for policy makers and researchers as the basis for good open science practices. The common factor underlying these new practices – the relevance of promoting open data circulation and reuse – is mostly a social form of knowledge sharing and construction. However, while data sharing is being strongly promoted by policy making and is becoming a frequent practice in some disciplinary fields, open data sharing is much less developed in social sciences and in educational research.</p> <p>The Open Data hereby introduced is composed of two integrated datasets which collect data relating practices of Open Data publication and sharing in the field of Educational Thecnologies. This data was collected to suport the aim of investigating open data sharing in a selection of open data repositories as well as in the academic social network site ResearchGate.</p> <p>The research questions addressing this study are:</p> <ol> <li>Do researchers in the field of Educational Technology publish Open Datasets [ODs]?</li> <li>To which extent are ODs compliant with the FAIR data principles?</li> <li>What is the social life relating to the ODs in terms of the metrics provided by the OD portals? As a subsidiary question: 3.a- To what extent do open data portals allow researchers to cultivate social practices around OD?</li> </ol> <p> </p> <p>In order to investigate OD presence in ResearchGate, the following research aim guided the second part of the study: Analysis of the presence of the same selected OD in ResearchGate and of the type of social activity OD exhibited by OD according to ResearchGate mètrics.</p> <p>The Open Data here presented is composed by two datasets.</p> <ol> <li>23 datasets extracted out from 82 randomly selected datasets, from an inital total of 633. The data set presents a Codebook explaining the several categories of analysis or variables and the values assigned to the same. Since the analysis was performed in two phases (first selection and screening, second selection and classification) the codebook is divided in two tables. Moreover, the data set contains 6 Worksheets, ordered taking the workflow as reference: Codebook, Dataset_Extraction, Analysis_Workflow, Selected_Analysis. This dataset has been produced and curated by J.E.Raffaghelli</li> <li>The analysis of correspondance for the 23 datasets in ResearchGate. The data set presents a Codebook, and is divided into two worksheets: Codebook, ODT&RG. The last worksheet introduces the comparison between the social mètrics within RG of the found datasets and the relating papers. This dataset has been produced and curated by S. Manca and J.E. Raffaghelli.</li> </ol>
Education of Providers on Prescribing Best Practices
ClinicalTrials.gov study NCT03771482. IPD Sharing: YES. Countries: 1. Publications: 2.
Assessing the Impact of a Social Media-Based Educational Intervention Using WhatsApp Video Messages on Dental Caries Prevention Knowledge, Oral Hygiene Practices, and Attitudes Toward Dental Health Am
ClinicalTrials.gov study NCT07363317. IPD Sharing: NO. Countries: 1. Publications: 3.
Effect of Health Education on Female Teachers' Knowledge and Practices Regarding Early Breast Cancer Detection and Screening in the Jazan Area: A Quasi-Experimental Study
ClinicalTrials.gov study NCT03398057. IPD Sharing: NO. Countries: 1. Publications: 1.
Data for: Integrating open education practices with data analysis of open science in an undergraduate course
Open the record for dataset details and reuse information.
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.
Needs assessment of advanced practice provider education in allergy & immunology
Open the record for dataset details and reuse information.
Interprofessional education in geriatric medicine: towards best practice. A controlled before-after study of medical and nursing student attitudes
<p>Objectives To investigate nursing and medical students' readiness for interprofessional learning before and after implementing geriatric Interprofessional education (IPE), based on interactive case scenarios Problem Based Learning (PBL). To determine optimal number of geriatric IPE sessions, the size and the ratio of participants in the learner groups, the outcomes related to the Kirkpatrick four-level typology of learning evaluation, students' concerns about joint learning, perception of roles of the "other" profession and students choice of topic.</p> <p>The strength:</p> <p>• This is a novel evidence regarding good practice for geriatric undergraduate Interprofessional education derived from a large unselected (inclusive) cohort of medical and nursing students</p> <p>• A controlled before-after study, with students randomly assigned to the intervention and control groups</p> <p>The limitations:</p> <p>• The overall number of nursing students was smaller, so the control group consisted of only medical students</p> <p>• The nursing students had more clinical experience than the medical students at the time of the geriatric IPE</p> <p>• Not all students returned the feedback forms, complaining that completing both questionnaires was time-consuming</p>
The Fourth International Scientific – Practical Virtual Conference in "Green Energy: New Conceptual Vision and Multiplicative Effects" Organizers of the conference: MTÜ. The International Center for Research Education & Training. (Estonia Tallinn)
<p>The Fourth International Scientific – Practical Virtual Conference in "Green Energy: New Conceptual Vision and Multiplicative Effects" Organizers of the conference: MTÜ. The International Center for Research Education & Training. (Estonia Tallinn</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.