Research Dataset Catalog and ShareScore Ratings | ScienceDex

zenodo40/100

Dataset related to article "How Academics and the Public Experienced Immersive Virtual Reality for Geo-education"

The dataset is associated with the paper entitled: How Academics and the Public Experienced Immersive Virtual Reality for Geo-education. It contains feedback regarding users’ experience with Immersive Virtual Reality for geological exploration, through a tailored approach developed by Tibaldi et al. (2020) where the Virtual Landscape is based on 3D photogrammetry-based high-resolution models. Such feedback has been acquired through anonymous questionnaires during nine dissemination events held in 2018 and 2019 in various locations (Vienna in Austria, Milan and Catania in Italy and Santorini in Greece), in the framework of the following projects: i) the MIUR project ACPR15T4_00098–Argo3D (http://argo3d.unimib.it/); ii) 3DTeLC Erasmus+Project 2017-1-UK01-KA203-036719 (<a href="http://www.3dtelc.com">http://www.3dtelc.com</a>); iii) EGU 2018 Public Engagement Grant (https://www.egu.eu/outreach/peg/) . In the dataset, feedback has been grouped into categories, based on users age and background: i) Middle and High School Students (Schools students, results in Sheet 1); ii) MSc Students in Earth Sciences (MSc, results in Sheet 2); iii) Academics/Researchers in Earth Sciences, that include PhD students and postdocs (Academics, results in Sheet 3); iv) Lay Public (i.e. participants that do not belong to the other groups, results in Sheet 4). It lists a total of 459 records; further details are available in the manuscript. If you use this dataset, please do cite the following papers: Bonali et al., How Academics and the Public Experienced Immersive Virtual Reality for Geo-education. Geosciences. Tibaldi, A.; Bonali, F.L.; Vitello, F.; Delage, E.; Nomikou, P.; Antoniou, V.; Becciani, U.; Van Wyk de Vries, B.; Krokos, M.; Whitworth, M. Real world–based immersive Virtual Reality for research, teaching and communication in volcanology. Bull. Volcanol. 2020, 82, 1–12.

opencc-by-4.0Dec 2021View details →

zenodo40/100

Dataset: Applications of Educational Data Mining and Learning Analytics on Data From Cybersecurity Training

This repository contains supplementary materials for the following journal paper: Valdemar &Scaron;vábenský, Jan Vykopal, Pavel Čeleda, Lydia Kraus. Applications of Educational Data Mining and Learning Analytics on Data From Cybersecurity Training. In Springer Education and Information Technologies. 2022. <a href="https://doi.org/10.1007/s10639-022-11093-6">https://doi.org/10.1007/s10639-022-11093-6</a> Preprint available at: <a href="https://arxiv.org/abs/2307.08582">https://arxiv.org/abs/2307.08582</a> <ul> </ul> How to cite If you use or build upon the materials, please use the BibTeX entry below to cite the original paper (not only this web link). <pre><code>@article{Svabensky2022applications, author = {\v{S}v\'{a}bensk\'{y}, Valdemar and Vykopal, Jan and \v{C}eleda, Pavel and Kraus, Lydia}, title = {{Applications of Educational Data Mining and Learning Analytics on Data From Cybersecurity Training}}, journal = {Education and Information Technologies}, publisher = {Springer}, volume = {27}, year = {2022}, issn = {1360-2357}, url = {https://doi.org/10.1007/s10639-022-11093-6}, doi = {10.1007/s10639-022-11093-6}, }</code></pre> Attached content The files included in the ZIP archive are: <ul> <li>`All-discovered-papers.bib` -- a BibTeX export of the Mendeley database of all considered papers discovered by the automated search.</li> <li>`Candidate-papers-reviewer1.bib` -- a BibTeX export of the Mendeley database of the candidate papers suggested by the first investigator.</li> <li>`Candidate-papers-reviewer2.bib` -- a BibTeX export of the Mendeley database of the candidate papers suggested by the second investigator.</li> <li>`Selected-papers.bib` -- a BibTeX export of the Mendeley database of the 35 papers selected for the literature review.</li> <li>`Selected-papers.xlsx` -- an Excel spreadsheet with the extracted information about the selected papers.</li> <li>`Selected-papers.csv` -- a CSV equivalent of the Excel spreadsheet.</li> </ul>

opencc-by-4.0May 2022View details →

zenodo40/100

Dataset: Skillful Craftsman Education Technology Limited (EDTK) Stock Performance

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.