Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
152
datasets available to search
ShareScore release 0.9.0
Dataset results
152 results for “Higher education”
Supplementary Materials: A primer on gathering and analysing multi-level quantitative evidence for differential student outcomes in higher education
<p>Example data sets, syntax files and macros for the tutorials in: Balloo, K., & Winstone, N. E. (2021). A primer on gathering and analysing multi-level quantitative evidence for differential student outcomes in higher education.<em> Frontline Learning Research</em>. <a href="https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.14786%2Fflr.v9i2.675&data=04%7C01%7Ck.balloo%40surrey.ac.uk%7C50bb47bb433744dc8da208d8c2116202%7C6b902693107440aa9e21d89446a2ebb5%7C0%7C0%7C637472728228002863%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=fyA0y2hUkHESUJ7sVJ3s42Re4Yqa5XbgwW7AvEyGDdk%3D&reserved=0">https://doi.org/10.14786/flr.v9i2</a><a href="https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.14786%2Fflr.v9i2.675&data=04%7C01%7Ck.balloo%40surrey.ac.uk%7C50bb47bb433744dc8da208d8c2116202%7C6b902693107440aa9e21d89446a2ebb5%7C0%7C0%7C637472728228002863%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=fyA0y2hUkHESUJ7sVJ3s42Re4Yqa5XbgwW7AvEyGDdk%3D&reserved=0">.675</a> </p> <p><strong>The data for all examples are fictional, and have only been designed to simulate the possible behaviour of institutional data for the purposes of demonstrating the analytical approaches in the primer. No inferences or conclusions should be drawn from the findings of these examples, because the results are not real. </strong></p> <p>We anticipate that readers can use the example data sets as templates and substitute in their own data.</p>
Results of Survey on Playertypes by Gamification User Types Hexad Framework in Higher Education
<p>Survey on playertypes via the validated quesitonaire published in Krath, J., von Korflesch, H.F.O. (2021). Player Types and Game Element Preferences: Investigating the Relationship with the Gamification User Types HEXAD Scale. In: Fang, X. (eds) HCI in Games: Experience Design and Game Mechanics. HCII 2021. Lecture Notes in Computer Science(), vol 12789. Springer, Cham. https://doi.org/10.1007/978-3-030-77277-2_18</p> <p>Between 25.01.23 and 08.02.23 students of the University of Lübeck, Germany were invited to fill out an online questionnaire. The acquisition was done by sending an email to the students. No incentive was offered for participation, except to find out at one's own expression at the end of the survey. In addition to the validated questions, this also included questions about gender and study area. All participants agreed to anonymous data collection and publication. Participants were also asked to confirm that they were completing the survey for the first time, otherwise the return was removed from the result set. </p> <p>The result set is formatted as CSV. Questions and identifiers of the data are shown in the first line.</p>
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>
How can higher education stakeholders support Edtech?
<p>This video outlines policy recommendations for cross-sector digital transformation in higher education. It highlights the importance of collaboration between policy-makers, stakeholders, EdTech companies, and universities to advance digital technologies in higher education. The findings derive from the ESRC-funded project 'Universities and Unicorns: building digital assets in the higher education industry'.</p>
Open Education in European Libraries of Higher Education 2023 Dataset
<p>This is the dataset that appends the 2023 edition of the SPARC Europe Open Education Survey amongst Higher Education institutions in Europe, in consultation with the European Network of Open Education Librarians (ENOEL). The report is for policymakers and practitioners who support or intend to support OE and OER in higher education institutions and academic libraries. </p>
Student discourse in small-group collaborative contexts in real-world higher education
<p>This dataset contains anonymised student discourse in small-group collaborative contexts in real-world higher education settings.</p> <p>There are 28 sessions, composed of 10799 utterances.</p> <p>The columns consist of 13 columns:</p> <ul> <li>session: the session number</li> <li>start: the starting time of the utterance</li> <li>end: the ending time of the utterance</li> <li>speaker: anonymised speaker name</li> <li>content: the content of the utterance</li> <li>ep: the episode number of the utterance. An episode refers to a single topic of discussion with multiple utterances.</li> <li>C: a binary value indicating the presence or absence of a cognitive challenge, where 0 means no challenge, and 1 means there is a cognitive challenge.</li> <li>E: a binary value indicating the presence or absence of an emotional/motivational challenge, where 0 means no challenge, and 1 means there is an emotional/motivational challenge.</li> <li>M: a binary value indicating the presence or absence of a metacognitive challenge, where 0 means no challenge, and 1 means there is a metacognitive challenge.</li> <li>T: a binary value indicating the presence or absence of a technical/other challenge, where 0 means no challenge, and 1 means there is a technical/other challenge.</li> <li>TA: a binary value indicating the presence or absence of the regulatory process "task analysis," where 0 means no regulation and 1 means task analysis is present.</li> <li>MC: a binary value indicating the presence or absence of the regulatory process "monitoring/control," where 0 means no regulation and 1 means monitoring/control is present.</li> <li>RA: a binary value indicating the presence or absence of the regulatory process "reflection/adaptation," where 0 means no regulation and 1 means reflection/adaptation is present.</li> </ul> <p>This annotated dataset was used in the following paper to model challenge moments.</p> <p>For more details on how the dataset was generated, please refer to the paper.</p> <div> <div>Suraworachet, W., Seon, J., & Cukurova, M. (2024). Predicting challenge moments from students’ discourse: A comparison of GPT-4 to two traditional natural language processing approaches. <em>Proceedings of the 14th Learning Analytics and Knowledge Conference</em>, 473–485. <a href="https://doi.org/10.1145/3636555.3636905">https://doi.org/10.1145/3636555.3636905</a></div> <div> </div> </div>
Indices of the supply of Chinese Higher Education
<p>The higher education indices for 31 Chinese provinces proposed by Borsi, Valerio Mendoza, and Comim (2021). </p>
SCoRe-LFC: Platform data on crowd collaboration in higher education
<p>SCoRe (short for Student Crowd Research) was a joint research project between the Universities of Bremen (UB), Hamburg (UHH) and Kiel (CAU), the Macromedia University of Applied Sciences (HMM) and the Ghostthinker GmbH (GT). The overall aim of the project was to develop a digital learning and research environment as well as didactic scenarios that foster collaborative processes of research-based learning in large groups of students (crowd). The main subject area was research for sustainable development. Towards this end, the project consortium drew on the partners’ expertise on advanced video-technologies (HHM), virtual collaboration in interdisciplinary and largescale groups (CAU), research-based learning (UHH) and education and research for sustainable development (UB). To achieve its goals, the project adopted a design-based research approach. The Project started in Oct. 2018 and was funded for 3.5 years by the Federal Ministry of Education and Research (BMBF) in a funding scheme on digital higher education.</p> <p>The work in the department of media-pedagogy and educational computer sciences at Kiel University was focused on the sub-project „SCoRe - learning and researching in the crowd“. The sub-project was aimed at the development, implementation and evaluation of pedagogical and organizational measures for the seeding, coordination and orchestration of collaborative research and learning processes in crowd scenarios. Particular emphasis was placed on crowd-specific characteristics of productive knowledge work in large and interdisciplinary groups.</p> <p>This dataset contains interaction data as well as textual content data. As ongoing development of the software platform led to a continuous integration of new features into the platform itself as well as changes to the data collection functions, making this an evolving dataset. Some inconsistencies exist due to software bugs.</p> <p><strong><a href="https://scorelfc.github.io/gestaltungsbericht3/img/datastructure.png">Platform data structure diagram</a> </strong></p> <p>Further Readings to gain an understanding of the platform and its interaction posbilities (in german):</p> <p><a href="https://scorelfc.github.io/gestaltungsbericht2">Design Report Prototype 2</a></p> <p><a href="https://scorelfc.github.io/gestaltungsbericht3">Design Report Prototype 3</a></p> <p> </p> <p><strong>Contained Files</strong></p> <table> <tbody> <tr> <td> <p><strong>Filename</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>annotations.csv</p> </td> <td> <p>Annotations (comment and/or drawings on the video) of video files</p> </td> </tr> <tr> <td> <p>content.csv</p> </td> <td> <p>Content of <a href="https://scorelfc.github.io/gestaltungsbericht3/umsetzungen/u03/">sections</a></p> </td> </tr> <tr> <td> <p>events.csv</p> </td> <td> <p>All events triggered by user interaction</p> </td> </tr> <tr> <td> <p>media.csv</p> </td> <td> <p>Uploaded <a href="https://scorelfc.github.io/gestaltungsbericht3/umsetzungen/u03/">images and videos</a></p> </td> </tr> <tr> <td> <p>messages.csv</p> </td> <td> <p><a href="https://scorelfc.github.io/gestaltungsbericht3/umsetzungen/u08/">Chat messages</a></p> </td> </tr> <tr> <td> <p>sequences.csv</p> </td> <td> <p><a href="https://scorelfc.github.io/gestaltungsbericht3/umsetzungen/u21/">Sequences</a> of video files</p> </td> </tr> </tbody> </table> <p> </p> <p><strong>Columns</strong></p> <p>(not all are present in each file. 0, “null” or “none” might mean not applicable)</p> <table> <tbody> <tr> <td> <p><strong>Column name</strong></p> </td> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Format</strong></p> </td> </tr> <tr> <td> <p>Index (empty column name) </p> </td> <td> <p>unique identifier of the corresponding event in the original dataset</p> </td> <td> <p>UUID (int on rare occasions)</p> </td> </tr> <tr> <td> <p>Actor-Name</p> </td> <td> <p>Unique identifier of an actor – “MA” identifies project staff </p> </td> <td> <p>string</p> </td> </tr> <tr> <td> <p>Annotation-ID</p> </td> <td> <p>Unique identifier of an annotation</p> </td> <td> <p>int</p> </td> </tr> <tr> <td> <p>Annotation-Text</p> </td> <td> <p>Label of an annotation</p> </td> <td> <p>string</p> </td> </tr> <tr> <td> <p>Version-ID</p> </td> <td> <p>Unique identifier of a version of an auditable object (e.g. a section)</p> </td> <td> <p>int</p> </td> </tr> <tr> <td> <p>Version-Changelog</p> </td> <td> <p>Changelog message on saving a new version of a section</p> </td> <td> <p>string</p> </td> </tr> <tr> <td> <p>Case-ID</p> </td> <td> <p>Unique identifier of a case (if applicable, coded by research team)</p> </td> <td> <p>String </p> </td> </tr> <tr> <td> <p>Media-Caption</p> </td> <td> <p>Title of a media file (image, video)</p> </td> <td> <p>string</p> </td> </tr> <tr> <td> <p>Media-ID</p> </td> <td> <p>Unique identifier of a media file (image, video)</p> </td> <td> <p>int</p> </td> </tr> <tr> <td> <p>Media-Timestamp</p> </td> <td> <p>Timestamp in a video</p> </td> <td> <p>int</p> </td> </tr> <tr> <td> <p>Message-ID</p> </td> <td> <p>Unique identifier of a chat message</p> </td> <td> <p>int</p> </td> </tr> <tr> <td> <p>Message-Text</p> </td> <td> <p>Content of a chat-message</p> </td> <td> <p>string</p> </td> </tr> <tr> <td> <p>Object-Type</p> </td> <td> <p>Type of an object an action refers to</p> </td> <td> <p>string</p> </td> </tr> <tr> <td> <p>Project-ID</p> </td> <td> <p>Unique identifier of a project</p> </td> <td> <p>int</p> </td> </tr> <tr> <td> <p>Research-Task-Type</p> </td> <td> <p>Type of research task (if applicable, coded by research team, see table below)</p> </td> <td> <p>string</p> </td> </tr> <tr> <td> <p>Section-Content</p> </td> <td> <p>Content of a section (in a specific version) </p> </td> <td> <p>string</p> </td> </tr> <tr> <td> <p>Section-Outline-Level</p> </td> <td> <p>Outline level of a section (in a specific version)</p> </td> <td> <p>int</p> </td> </tr> <tr> <td> <p>Section-ID</p> </td> <td> <p>Unique identifier of a section</p> </td> <td> <p>int</p> </td> </tr> <tr> <td> <p>Section-Index</p> </td> <td> <p>Position of a section in the project (in a specific version)</p> </td> <td> <p>int</p> </td> </tr> <tr> <td> <p>Section-Status</p> </td> <td> <p>Status of a section</p> </td> <td> <p>int</p> </td> </tr> <tr> <td> <p>Section-Title</p> </td> <td> <p>Title of a section (in a specific version)</p> </td> <td> <p>string</p> </td> </tr> <tr> <td> <p>Sequence-Description</p> </td> <td> <p>Description of a video sequence</p> </td> <td> <p>string</p> </td> </tr> <tr> <td> <p>Sequence-Duration</p> </td> <td> <p>Length of a video sequence</p> </td> <td> <p>int</p> </td> </tr> <tr> <td> <p>Sequence-ID</p> </td> <td> <p>Unique identifier of a sequence</p> </td> <td> <p>int</p> </td> </tr> <tr> <td> <p>Sequence-Timestamp</p> </td> <td> <p>Timestamp of the start of a sequence in a video</p> </td> <td> <p>int</p> </td> </tr> <tr> <td> <p>timestamp</p> </td> <td> <p>timestamp of an event</p> </td> <td> <p>datetime</p> </td> </tr> <tr> <td> <p>Verb</p> </td> <td> <p>Action type of an event (see table below)</p> </td> <td> <p>string</p> </td> </tr> </tbody> </table> <p> </p> <p><strong>Verbs</strong></p> <table> <tbody> <tr> <td> <p><strong>Value</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>canceled editing of</p> </td> <td> <p>Actor canceled editing of a section</p> </td> </tr> <tr> <td> <p>clicked</p> </td> <td> <p>Actor clicked a link</p> </td> </tr> <tr> <td> <p>collapsed</p> </td> <td> <p>Actor collapsed a section (hides its content form being viewed)</p> </td> </tr> <tr> <td> <p>compared versions of</p> </td> <td> <p>Actor compared two versions of a section</p> </td> </tr> <tr> <td> <p>created</p> </td> <td> <p>Actor created a new section, video sequence, video annotation, video playback command, project or news</p> </td> </tr> <tr> <td> <p>deleted</p> </td> <td> <p>Actor deleted a section, video sequence, video annotation, video playback command, project or news</p> </td> </tr> <tr> <td> <p>ended</p> </td> <td> <p>Actor played a video hitting its end</p> </td> </tr> <tr> <td> <p>expanded</p> </td> <td> <p>Actor expanded a collapsed section</p> </td> </tr> <tr> <td> <p>inserted</p> </td> <td> <p>Actor inserted a video comment (on occasions instead of created)</p> </td> </tr> <tr> <td> <p>left</p> </td> <td> <p>Actor left a context (e.g. a project, a chat window) by e.g. closing it using platform functions, changing a browser tab, etc.</p> </td> </tr> <tr> <td> <p>mentioned</p> </td> <td> <p>Actor mentioned another actor in a chat message</p> </td> </tr> <tr> <td> <p>opened</p> </td> <td> <p>Actor opened a context (e.g. a project, a chat window) by e.g. accessing it using platform functions or changing a browser tab</p> </td> </tr> <tr> <td> <p>paused</p> </td> <td> <p>Actor paused a video</p> </td> </tr> <tr> <td> <p>played</p> </td> <td> <p>Actor played a video</p> </td> </tr> <tr> <td> <p>read</p> </td> <td> <p>Actor read an activity message or news</p> </td> </tr> <tr> <td> <p>read all messages and activities of</p> </td> <td> <p>Actor used switch to mark all chat and activity messages read</p> </td> </tr> <tr> <td> <p>restored</p> </td> <td> <p>Actor restored a deleted section</p> </td> </tr> <tr> <td> <p>reverted</p> </td> <td> <p>Actor restored a deleted section</p> </td> </tr> <tr> <td> <p>reverted version of</p> </td> <td> <p>Actor reverted a section to an earlier version</p> </td> </tr> <tr> <td> <p>seeked</p> </td> <td> <p>Actor seeked on a video timeline</p> </td> </tr> <tr> <td> <p>sent</p> </td> <td> <p>Actor sent a chat message</p> </td> </tr> <tr> <td> <p>started editing of</p> </td> <td> <p>Actor started editing of a section</p> </td> </tr> <tr> <td> <p>switched</p> </td> <td> <p>Actor switched chat focus between project and section chat</p> </td> </tr> <tr> <td> <p>typed</p> </td> <td> <p>Actor typed into the chat</p> </td> </tr> <tr> <td> <p>updated</p> </td> <td> <p>Actor updated an existing section (changing content, heading, heading-depth or status), video sequence, video annotation, video playback command, project or news</p> </td> </tr> <tr> <td> <p>uploaded</p> </td> <td> <p>Actor uploaded an image or video</p> </td> </tr> <tr> <td> <p>viewed</p> </td> <td> <p>Actor viewed an entity (had it on screen for 5 seconds), e.g. a section or video comment</p> </td> </tr> <tr> <td> <p>viewed history of</p> </td> <td> <p>Actor viewed history of a section</p> </td> </tr> </tbody> </table> <p> </p> <p><strong>Project-ID</strong></p> <table> <tbody> <tr> <td> <p><strong>Project-ID</strong></p> </td> <td> <p><strong>Case-IDs</strong></p> </td> <td> <p><strong>Title</strong></p> </td> <td> <p> </p> <p><strong>Type</strong></p> </td> <td> <p><strong>Period</strong></p> </td> </tr> <tr> <td> <p>2</p> </td> <td> <p>a1-a*</p> </td> <td> <p>Urbane Grünflächen</p> </td> <td> <p>Research project</p> </td> <td> <p>1.11.20-31.3.21</p> </td> </tr> <tr> <td> <p>4</p> </td> <td> <p>b1-b*</p> </td> <td> <p>Nachhaltiger Verkehr</p> </td> <td> <p>Research project</p> </td> <td> <p>1.11.20-31.3.21</p> </td> </tr> <tr> <td> <p>166</p> </td> <td> <p>c1-c*</p> </td> <td> <p>UGF - Urbane Grünflächen</p> </td> <td> <p>Research project</p> </td> <td> <p>1.4.21-30.09.21</p> </td> </tr> <tr> <td> <p>168</p> </td> <td> <p> </p> </td> <td> <p>LGS - Foyer</p> </td> <td> <p>Onboarding of students in LGS Projects</p> </td> <td> <p>1.4.21-30.09.21</p> </td> </tr> <tr> <td> <p>188</p> </td> <td> <p> </p> </td> <td> <p>LGS - Reflexionsraum</p> </td> <td> <p>Reflection project for students in LGS Projects</p> </td> <td> <p>1.4.21-30.09.21</p> </td> </tr> <tr> <td> <p>207</p> </td> <td> <p> </p> </td> <td> <p>LGS - Nachhaltiger Konsum</p> </td> <td> <p>Research project</p> </td> <td> <p>1.4.21-30.09.21</p> </td> </tr> <tr> <td> <p>210</p> </td> <td> <p> </p> </td> <td> <p>LGS - Bildungsangebote für nachhaltige Entwicklung</p> </td> <td> <p>Research project</p> </td> <td> <p>1.4.21-30.09.21</p> </td> </tr> <tr> <td> <p>264</p> </td> <td> <p> </p> </td> <td> <p>LGS - Fahrradmobilität in Städten</p> </td> <td> <p>Research project</p> </td> <td> <p>1.4.21-30.09.21</p> </td> </tr> <tr> <td> <p>271</p> </td> <td> <p> </p> </td> <td> <p>Fahrradmobilität in Städten</p> </td> <td> <p>Research project</p> </td> <td> <p>1.10.21-30.11.21</p> </td> </tr> <tr> <td> <p>269</p> </td> <td> <p>e1-e*</p> </td> <td> <p>Kaufentscheidung vs. Nachhaltigkeit</p> </td> <td> <p>Research project</p> </td> <td> <p>1.10.21-30.11.21</p> </td> </tr> <tr> <td> <p>262</p> </td> <td> <p>d1-d*</p> </td> <td> <p>Urbane Grünflächen</p> </td> <td> <p>Research project</p> </td> <td> <p>1.10.21-30.11.21</p> </td> </tr> <tr> <td> <p>199</p> </td> <td> <p> </p> </td> <td> <p>Basiskurs</p> </td> <td> <p>Basic course for onboarding of students on the platform</p> </td> <td> <p>1.10.21-30.11.21</p> </td> </tr> <tr> <td> <p>5</p> </td> <td> <p> </p> </td> <td> <p>Glossar</p> </td> <td> <p>Glossar of definitions</p> </td> <td> <p>persistent</p> </td> </tr> <tr> <td> <p>6</p> </td> <td> <p> </p> </td> <td> <p>Erste Schritte</p> </td> <td> <p>How to start using score-docs platform</p> </td> <td> <p>persistent</p> </td> </tr> <tr> <td> <p>8</p> </td> <td> <p> </p> </td> <td> <p>Testbereich</p> </td> <td> <p>Area for testing score-docs functionalities</p> </td> <td> <p>persistent</p> </td> </tr> <tr> <td> <p>7</p> </td> <td> <p> </p> </td> <td> <p>Hilfestellungen</p> </td> <td> <p>Helpful links </p> </td> <td> <p>persistent</p> <p> </p> </td> </tr> </tbody> </table> <p>Other Project-IDs refer to personal assessment documents of individual students which are not included in content.csv</p> <p><strong>Research-Task-Type</strong></p> <table> <tbody> <tr> <td> <p><strong>Value</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>Erheben</p> </td> <td> <p>Data collection</p> </td> </tr> <tr> <td> <p>Analysieren</p> </td> <td> <p>Case-specific data analysis and sensemaking</p> </td> </tr> <tr> <td> <p>Synthetisieren</p> </td> <td> <p>Cross-case data analysis and sensemaking</p> </td> </tr> <tr> <td> <p>Sonstiges</p> </td> <td> <p>Other, e.g. communication between participants</p> </td> </tr> </tbody> </table>
Unpacking the concept of "educators' data literacy in Higher Education" - Systematic Review of the literature and Keyword Map
<p>As algorithmic decision-making and data collection become pervasive within higher education, how can educators make sense of the systems that shape life and learning in the 21st century? Through a systematic review of the literature, the paper investigates the gaps in the literature, which prevent the formulation of potential pathways and principles on which educators’ data literacy can - and should - be developed and fostered. The analysis of 137 papers through the methods of classification under relevant categories, and key words mapping, showed that there is little attention on HE teachers, and most approaches to educators’ data literacy address management and technical abilities for data processing, with less concern on critical, ethical and personal approaches to datafication in education.</p> <p>The present dataset shows the full list of articles analysed.</p> <p>The dataset, and ods file, is composed by the following sheets:</p> <ol> <li>Codebook</li> <li>List of articles extracted from SCOPUS</li> <li>List of articles extracted from WOS</li> <li>List of articles extracted from ERIC</li> <li>List of articles extracted from DOAJ</li> <li>Interrater Agreement</li> <li>PRISMA workflow</li> <li>Analysis - First Level (classification of 137 articles selected)</li> <li>Analysis - Second Level (List of articles relating faculty development)</li> <li>Supplementary tables (counting articles in relation to the categories of analysis).</li> </ol> <p>As for the Keywords' Map, a second file .csv displays the text over which basis was performed the keyword maps analysis. A .txt file shows notes relating the analysis procedures using the software VOS-Viewer <a href="http://www.vosviewer.com/">http://www.vosviewer.com/</a></p> <p> </p>
Data and code for "Carbon neutrality should not be the end goal: Lessons for institutional climate action from U.S. higher education"
<p>Code and data for the paper "Carbon neutrality should not be the end goal: Lessons for institutional climate action from U.S. higher education"</p> <p>File descriptions:</p> <p>'HEI_analysis_OneEarth.Rmd' is the code with improved annotation and colorblind-friendly figures.</p> <p>All other data files are provided as excel and csv for convenience.</p> <p>'working_master_data' contains data from the Second Nature reporting platform on emissions by category for each institution analyzed in the paper (measured in metric tons). All adjustments necessary to fill in the data gaps in this file are documented at the beginning of 'HEI_analysis'.</p> <p>'offsets' contains data on the type(s) of offsets purchased by each school in their carbon neutral year (measured in metric tons). This data was assembled from a variety of sources which are documented at the beginning of 'HEI_analysis'.</p> <p>'carbon_neutral_years' contains yearly counts of higher education neutrality goals that were reported to Second Nature as of November 2020.</p>
Higher Education Institutions in Poland Dataset
<p><strong>Higher Education Institutions in Poland Dataset</strong></p> <p>This repository contains a dataset of higher education institutions in Poland. The dataset comprises 131 public higher education institutions and 216 private higher education institutions in Poland. The data was collected on 24/11/2022. <br> This dataset was compiled in response to a cybersecurity investigation of Poland's higher education institutions' websites [1]. The data is being made publicly available to promote open science principles [2].</p> <p><strong>Data</strong></p> <p>The data includes the following fields for each institution:</p> <ul> <li>Id: A unique identifier assigned to each institution.</li> <li>Region: The federal state in which the institution is located.</li> <li>Name: The original name of the institution in Polish.</li> <li>Name_EN: The international name of the institution in English.</li> <li>Category: Indicates whether the institution is public or private.</li> <li>Url: The website of the institution.</li> </ul> <p><strong>Methodology</strong></p> <p>The dataset was compiled using data from two primary sources:</p> <ul> <li>Public Higher Education Institutions: Data was sourced from the official website of the Ministry of Education and Science of Poland [3].</li> <li>Private Higher Education Institutions: Data was obtained from the RAD-on system, which is part of the Integrated Information Network on Science and Higher Education [4].</li> </ul> <p>For the international names in English, the following methodology was employed:</p> <p>Both Polish and English names were retained for each institution. This decision was based on the fact that some universities do not have their English versions available in official sources.</p> <p>English names were primarily sourced from:</p> <ul> <li>The Polish National Agency for Academic Exchange's official document [5].</li> <li>The website Studies in English [6].</li> <li>Official websites of the respective Higher Education Institutions.</li> </ul> <p>In instances where English names were not readily available from the aforementioned sources, the GPT-3.5 model was employed to propose suitable names. These proposed names are distinctly marked in blue within the dataset file (hei_poland_en.xls).</p> <p><strong>Usage</strong></p> <p>This data is available under the Creative Commons Zero (CC0) license and can be used for academic research purposes. We encourage the sharing of knowledge and the advancement of research in this field by adhering to open science principles [2].</p> <p>If you use this data in your research, please cite the source and include a link to this repository. To properly attribute this data, please use the following DOI:<br> <strong>10.5281/zenodo.8333573</strong></p> <p><strong>Contribution</strong></p> <p>If you have any updates or corrections to the data, please feel free to open a pull request or contact us directly. Let's work together to keep this data accurate and up-to-date.</p> <p><strong>Acknowledgment</strong></p> <p>We would like to express our gratitude to the Ministry of Education and Science of Poland and the RAD-on system for providing the information used in this dataset.</p> <p>We would like to acknowledge the support of the Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), within the project "Cybers SeC IP" (NORTE-01-0145-FEDER-000044). This study was also developed as part of the Master in Cybersecurity Program at the Polytechnic University of Viana do Castelo, Portugal.</p> <p><strong>References</strong></p> <ol> <li>Pending.</li> <li>S. Bezjak, A. Clyburne-Sherin, P. Conzett, P. Fernandes, E. Görögh, K. Helbig, B. Kramer, I. Labastida, K. Niemeyer, F. Psomopoulos, T. Ross-Hellauer, R. Schneider, J. Tennant, E. Verbakel, H. Brinken, and L. Heller, Open Science Training Handbook. Zenodo, Apr. 2018. [Online]. Available: [<a href="https://doi.org/10.5281/zenodo.1212496">https://doi.org/10.5281/zenodo.1212496</a>]</li> <li>Ministry of Education and Science of Poland. "Wykaz uczelni publicznych nadzorowanych przez Ministra właściwego ds. szkolnictwa wyższego - publiczne uczelnie akademickie." Nov 2022. [Online]. Available: <a href="https://www.gov.pl/web/edukacja-i-nauka/wykaz-uczelni-publicznych-nadzorowanych-przez-ministra-wlasciwego-ds-szkolnictwa-wyzszego-publiczne-uczelnie-akademickie">https://www.gov.pl/web/edukacja-i-nauka/wykaz-uczelni-publicznych-nadzorowanych-przez-ministra-wlasciwego-ds-szkolnictwa-wyzszego-publiczne-uczelnie-akademickie</a></li> <li>RAD-on System. "Dane instytucji systemu szkolnictwa wyższego i nauki." Nov 2022. [Online]. Available: <a href="https://radon.nauka.gov.pl/dane/instytucje-systemu-szkolnictwa-wyzszego-i-nauki">https://radon.nauka.gov.pl/dane/instytucje-systemu-szkolnictwa-wyzszego-i-nauki</a></li> <li>Polish National Agency for Academic Exchange. "List of the university-type HEIs." 2023. [Online]. Available: <a href="https://nawa.gov.pl/images/Aktualnosci/2023/Att.-2.-List-of-the-university-type-HEIs.pdf">https://nawa.gov.pl/images/Aktualnosci/2023/Att.-2.-List-of-the-university-type-HEIs.pdf</a></li> <li>Studies in English. [Online]. Available: <a href="http://www.studies-in-english.pl/">www.studies-in-english.pl</a></li> </ol>
Data for D7.1 FAIR in European Higher Education
<p>As part of the EOSC project family the FAIRsFAIR - Fostering Fair Data Practices in Europe - project aims to supply practical solutions for the use of the FAIR data principles throughout the research data life cycle. The FAIRsFAIR project runs from March 2019-February 2022.</p> <p>FAIRsFAIR Work Package 7 “FAIR Data Science and Professionalisation” aims to develop resources and build communities that support the uptake of RDM and FAIR practice within higher education curricula.</p> <p>The data published here stems from a both a web-based questionnaire with 90 responses conducted within FAIRsFAIR WP7 between 19 September and 15 November 2019.</p> <p>The questionnaire covered several dimensions of research data management at HEIs relevant for the implementation of FAIRsFAIR WP7, as well as WP3 “FAIR Data Policy Practice” and WP6 “FAIR Competence Centre”. These dimensions included:</p> <ul> <li>Institutional research data management policies </li> <li>Support services for research data management</li> <li>Competence development of students and graduates</li> <li>Universities and EOSC</li> <li>FAIRsFAIR support for universities</li> </ul> <p>The data resulting from the survey has been used as the basis for <a href="http://doi.org/10.5281/zenodo.3629683">D7.1 FAIR in European Higher Education</a>.</p> <p>The following files are available:</p> <ul> <li>Codebook including original questionnaire</li> <li>Dataset</li> </ul>
Higher Education Research: A Compilation of Journals and Abstracts 2016
<p>Revised dataset to original publication:</p> <p>Hertwig, Alexandra (2017): Higher Education Research: A Compilation of Journals and Abstracts 2016. Kassel: INCHER-Kassel. <a href="http://www.uni-kassel.de/einrichtungen/fileadmin/datas/einrichtungen/incher/Higher_Education_Research_-_A_Compilation_of_Journals_and_Abstracts_2016.pdf">http://www.uni-kassel.de/einrichtungen/fileadmin/datas/einrichtungen/incher/Higher_Education_Research_-_A_Compilation_of_Journals_and_Abstracts_2016.pdf</a> (accessed November 04, 2020)</p> <p>Datasets to volume 2013 to 2018 might vary with regard to covered journals of the original publication. The datasets include journals and respective publication data providing persistent identifiers, explicitly.</p> <p>The Research Information Service (RIS) of INCHER-Kassel, Germany provides annual compilation of academic journals since 2013. The datasets allow for further evaluation of single or multiple volumes. For more information on original publications and available datasets please visit INCHER’s RIS websites.</p> <p>http://www.uni-kassel.de/einrichtungen/en/incher/risspecial-research-library/ris-documents.html</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>
Relevance of national policy in the provision of open data on South African higher education sector
<p>Spreadsheet providing breakdown of the national Acts, Bills and Standards relevant to sharing open data on the governance of higher education in South Africa. Data generated as a 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>
South Africa higher education data 2 - Data sources
<p>GIS-based map visualisation of the data sources 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>
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>
Transforming Higher Education Institutions through EDI Leadership: A Bibliometric Exploration
<p>Bibliometric data for article titled "Transforming Higher Education Institutions through EDI Leadership: A Bibliometric Exploration"</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>
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.