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27 results for “Data Literacy”
Daten der Data Literacy Bedarfserhebung für die historisch arbeitenden Disziplinen (Erhebungszeitraum: August-Oktober 2023)
<p>Bei dieser Publikation handelt es sich um Daten aus der NFDI4Memory Data Literacy Bedarfserhebung, die von August bis Oktober 2023 durchgeführt wurde. Der Datensatz beinhaltet die Rohdaten, wie sie aus dem Fragebogentool SoSciSurvey heruntergeladen wurden und die aufbereiteten Daten, die die Grundlage für die Auswertung waren.</p> <p><strong>Rohdaten aus SoSciSurvey:</strong></p> <p>.xlsx-Format: </p> <ul> <li><a href="../api/records/12166939/draft/files/codebook_4memory-data-literacy_2024-06-19_11-28.xlsx/content" target="_blank" rel="noopener noreferrer">codebook_4memory-data-literacy_2024-06-19_11-28.xlsx</a></li> <li><a href="../api/records/12166939/draft/files/data_4memory-data-literacy_2024-06-19_11-28.xlsx/content" target="_blank" rel="noopener noreferrer">data_4memory-data-literacy_2024-06-19_11-28.xlsx</a></li> </ul> <p>.csv-Format:</p> <ul> <li><a href="../api/records/12166939/draft/files/data_4memory-data-literacy_2024-06-19_11-30.csv/content" target="_blank" rel="noopener noreferrer">data_4memory-data-literacy_2024-06-19_11-30.csv</a></li> <li><a href="../api/records/12166939/draft/files/variables_4memory-data-literacy_2024-06-19_11-30.csv/content" target="_blank" rel="noopener noreferrer">variables_4memory-data-literacy_2024-06-19_11-30.csv</a></li> <li><a href="../api/records/12166939/draft/files/rdata_4memory-data-literacy_2024-06-19_11-33.csv/content" target="_blank" rel="noopener">rdata_4memory-data-literacy_2024-06-19_11-33.csv</a></li> <li><a href="../api/records/12166939/draft/files/sdata_4memory-data-literacy_2024-06-19_11-32.csv/content" target="_blank" rel="noopener">sdata_4memory-data-literacy_2024-06-19_11-32.csv</a></li> <li><a href="../api/records/12166939/draft/files/values_4memory-data-literacy_2024-06-19_11-30.csv/content" target="_blank" rel="noopener noreferrer">values_4memory-data-literacy_2024-06-19_11-30.csv</a></li> <li><a href="../api/records/12166939/draft/files/Codebuch.csv/content" target="_blank" rel="noopener noreferrer">Codebuch.csv</a></li> <li><a href="../api/records/12166939/draft/files/Ausgangsdatensatz.csv/content" target="_blank" rel="noopener noreferrer">Ausgangsdatensatz.csv</a></li> </ul> <p>.sql-Format:</p> <ul> <li><a href="../api/records/12166939/draft/files/data_4memory-data-literacy_2024-06-19_11-33.sql/content" target="_blank" rel="noopener noreferrer">data_4memory-data-literacy_2024-06-19_11-33.sql</a></li> </ul> <p>.sps-Fromat:</p> <ul> <li><span><a href="../api/records/12200702/draft/files/spss_4memory-data-literacy_2024-06-19_11-31.sps/content" target="_blank" rel="noopener noreferrer">spss_4memory-data-literacy_2024-06-19_11-31.sps</a></span></li> </ul> <p><span>.do-Format:</span></p> <div> <ul> <li><a href="../api/records/12200702/draft/files/import_4memory-data-literacy_2024-06-19_11-32.do/content" target="_blank" rel="noopener noreferrer">import_4memory-data-literacy_2024-06-19_11-32.do</a></li> </ul> <p>.r-Format:</p> <div> <ul> <li><a href="../api/records/12200702/draft/files/import_4memory-data-literacy_2024-06-19_11-33.r/content" target="_blank" rel="noopener noreferrer">import_4memory-data-literacy_2024-06-19_11-33.r</a></li> </ul> </div> </div> <p><strong>Aufbereitete Daten:</strong></p> <p>.xlsx-Format:</p> <ul> <li><span><a href="../api/records/12200702/draft/files/2024-06-06-aufbereitete_Daten.xlsx/content" target="_blank" rel="noopener noreferrer">2024-06-06-aufbereitete_Daten.xlsx</a></span> (enthalten sind die Tabellenblätter Ausgangsdatensatz (unbearbeitet), Codebuch (unbearbeitet), überarbeiteter Datensatz und Zusatztabelle Fachbereich</li> </ul> <p>.csv-Format:</p> <ul> <li> <div><a href="../api/records/12166939/draft/files/Dokumentation.csv/content" target="_blank" rel="noopener noreferrer">Dokumentation.csv</a></div> </li> <li><a href="../api/records/12166939/draft/files/Zusatztabelle_Fachbereich.csv/content" target="_blank" rel="noopener noreferrer">Zusatztabelle_Fachbereich.csv</a></li> <li><span><a href="../api/records/12200702/draft/files/%C3%BCberarbeiteter%20Datensatz.csv/content" target="_blank" rel="noopener noreferrer">überarbeiteter Datensatz.csv</a></span></li> </ul>
Behavioral and fMRI Data: Nurturing the reading brain: Home literacy practices are associated with children's neural response to printed words through vocabulary skills
<p>This is the behavioral and fMRI dataset described in "Nurturing the reading brain: Home literacy practices are associated with children’s neural response to printed words through vocabulary skills". </p> <p>Because of anonymization concerns within the framework of EU privacy regulations (<a href="https://gdpr-info.eu">GDPR</a>), we cannot provide raw MRI data. Therefore, the fMRI data consists of individual pre-processed volumes, normalized into the MNI template (see paper for details about the preprocessing pipeline). Anonymized behavioral data and first level analyses are also provided for each participant (SPM.mat file as well as beta, con, spmT, RPV and ResMS files). Note that the dataset also include runs and GLM results for a third task (Dots) that was not analyzed in the paper. Finally, the <a href="https://www.psychopy.org">PsychoPy</a> implementation of the tasks is also provided. If you have any questions, please send an email to jerome.prado [at] univ-lyon1.fr. </p> <p><strong>IMPORTANT:</strong></p> <p>In accordance with EU privacy regulations, we ask that you sign and return a Data Use Agreement (DUA) before downloading the data. You can download the DUA <a href="https://zenodo.org/record/4965716/files/DUA.pdf?download=1">here</a>. Please, sign it and send it to jerome.prado [at] univ-lyon1.fr.</p>
Survey data on financial literacy, financial inclusion, informal financial business practices, and intentions towards formalization of female small vendors in Lima, Peru
<p><span>This dataset encapsulates a comprehensive survey aimed at understanding informal business practices and financial literacy among small business vendors in Peru. The dataset comprises three key components: the survey questionnaire, raw survey data, and a detailed codebook. Researchers interested in the dynamics of financial practices in emerging markets may find this dataset particularly valuable, as it allows for the exploration of factors influencing financial decisions in small enterprises, with potential modifications suggested for adapting the survey to different national or cultural contexts. This dataset not only contributes to empirical research in financial behavior but also supports gender-specific studies by allowing the variable 'sex' to be adapted to 'gender' with multiple response options. </span></p> <p><span>The data and supplementary material is divided in tree files:</span></p> <p><span>The survey, presented in "Survey IFE.docx," includes questions across various domains such as informal business practices, financial literacy, financial inclusion, intentions towards financial formalization, and the formality of business ventures, along with demographic variables like age, sex, business age, and number of employees. </span></p> <p><span>The raw data, stored in "Dataset.csv," records responses from 118 participants, mapped against 31 indicators. </span></p> <p><span>The "Codebook.doc" provides exhaustive details about the survey variables, coding of responses, and the methodology employed, facilitating the replication of the study and application of the dataset in varied research contexts.</span></p>
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>
Research generated data supporting the article manuscript "Setting Grounds for Data Literacy in the Sector of Agriculture: Learning About and with Open Data"
<p>In the research 345 MS courses and 216 MS courses data from the ECTS catalogue (2019) of University of Zagreb Faculty of Agriculture were mapped onto the data literacy competence areas (theme) and DL competence areas sub-themes adapted ODI Data Skills Framework (2020) expanding the term “skill” to “competence” to include knowledge and attitudes. Teaching staff was interviewed in semi-structured interviews on the data literacy competences covered in their courses and open data use and teaching in their courses as well as their perceived importance for the sector of the course.</p> <p>The upload consists of the following .csv files:</p> <table> <tbody> <tr> <td>readme_DL_OD_Salamonetal.csv</td> </tr> <tr> <td>01DL_OD_Salamonetal.csv</td> </tr> <tr> <td>02DL_OD_Salamonetal.csv</td> </tr> <tr> <td>03DL_OD_Salamonetal.csv</td> </tr> <tr> <td>04DL_OD_Salamonetal.csv</td> </tr> <tr> <td>05DL_OD_Salamonetal.csv</td> </tr> <tr> <td>06DL_OD_Salamonetal.csv</td> </tr> <tr> <td>07DL_OD_Salamonetal.csv</td> </tr> </tbody> </table> <p> </p> <p> </p> <p> </p>
Icons illustrating aspects of data organization from the Data Literacy Initiative (DaLI) at TH Köln
<p>Icons created as part of the research project Data Literacy Initiative (DaLI) at TH Köln - University of Applied Sciences in Cologne, Germany. They illustrate aspects of best practices for data organization as recommended in Karl W. Broman & Kara H. Woo (2018) Data Organization in Spreadsheets, The American Statistician, 72:1, 2-10, DOI: 10.1080/00031305.2017.1375989.<br> </p> <p>When using any of the images please include the following attribution together with the DOI: This image was created by Jule Marie Schacht and Juliane Piecha for the Data Literacy Initiative (DaLI) at TH Köln and is used under a CC-BY license.</p> <p>The Data Literacy Initiative (DaLI) at TH Köln develops an interdisciplinary, modular program offering data literacy training to students from all fields.</p> <p>More information on the Data Literacy Initiative (DaLI) (in German): https://www.th-koeln.de/dali</p> <p>Illustrations created by: Jule Marie Schacht</p>
(Open) Data literacy: Dataset for a systematic review of the literature
<p>This dataset presents data used for a systematic review of the literature.</p><p>We conducted a comprehensive literature review, in which we identified the following: a) the role of data literacy as one of several barriers to use; and b) open data-related activities that foster informal learning by assisting in the development of critical data literacy as a surrogate for citizens' continued engagement with open data. Following the screening and selection of 66 articles through the use of keyword mapping, the articles were coded and subjected to quantitative analysis. On the one hand, our findings demonstrate that inadequate data literacy hinders the utilisation of open data. Conversely, it seems that open data initiatives create pertinent prospects for fostering technical data literacy among the general public, enabling them to comprehend and engage with decision-making processes that are informed by data. However, critical data literacy as a primary catalyst for the strategic and transformative utilisation of open government data receives scant attention. In conclusion, this research has the potential to provide a foundation for interventions that promote open data literacy and lifelong learning.</p>
(open) data literacy as barrier and enabler of open government data enhancement. A systematic review of the literature.
<p>This systematic review of the literatu was conducted with the PRISMA method, to explore the contexts in which the use of open government data germinates, identifying barriers to its use and identifying, the role of data literacy among those barriers to use; and the role of open data in promoting informal learning that supports the development of critical data literacy. This file includes a codebook of the main characteristics that were studied in a systematic literature review, where data from 66 articles related to Open Data Usage were identified and coded. Also, the file includes an analysis of Cohen's Kappa, a concordance statistic used to measure the level of agreement among researchers in classifying articles on the characteristics defined in the Codebook. Finally, it includes main tables of the results' analysis.</p>
Open Data as driver of critical data literacies in Higher Education: Which Data, Which Openness, Which Care?
<p>This Zenodo item contains the Report and subsidiary resources and dataset on the results of the workshop undertaken by the authors: "Open Data as driver of critical data literacies in Higher Education".</p> <p>Workshop Details:</p> <ul> <li>A workshop session offered at the OER20 [online] conference</li> <li><a href="https://oer20.oerconf.org/sessions/o-060/">https://oer20.oerconf.org/sessions/o-060/</a></li> <li>Wed, Apr 1 2020</li> <li>Theme: <a href="https://oer20.oerconf.org/tracks/open-education-for-civic-engagement-and-democracy/">Open education for civic engagement and democracy</a></li> <li>Access to the <a href="https://eu.bbcollab.com/collab/ui/session/playback/load/0983399114454947ba11426abbb3e17e">Recorded Session</a></li> </ul> <p>The workshop explored the educational potential of Open Data as a driver of interdisciplinary dialogue in learning design and pedagogical practices. It offered instruments for designing educational interventions in two simple phases:</p> <ol> <li>A conceptual (but dialogical!) introduction</li> <li>A “hands on” exercise</li> </ol> <p>The virtual environment used was Blackboard Collaborate as organized and supported by ALT and the OER20 Committee. In these conditions, 73 participants (conference attendees and external participants) engaged in the activity. The participants that expressed their geographical positions (when introducing themselves via the chat in the virtual conference environment) showed diversity, though most participants came from the UK, elsewhere in Europe, and some from Latin America.</p>
Why should we care about datafication? Critical data literacies in higher education
<p>This Zenodo item contains the Report and subsidiary resources and dataset on the results of the workshop undertaken by the authors: "Why should we care about datafication? Critical data literacies in higher education".</p> <p>Workshop Details:</p> <ul> <li>A workshop session offered at the OER20 [online] conference</li> <li><a href="https://oer20.oerconf.org/sessions/o-023/">https://oer20.oerconf.org/sessions/o-023/</a></li> <li>Wed, Apr 1 2020</li> <li>Theme: <a href="https://oer20.oerconf.org/tracks/openness-in-the-age-of-surveillance/">Openness in the age of surveillance</a></li> <li>Access to the <a href="https://eu.bbcollab.com/collab/ui/session/playback/load/7cadbebcf3cf499d8616529c880eacde">Recorded Session</a></li> </ul> <p>Through a hands-on Open Space conversation, facilitated via Mentimeter and Blackboard Collaborate we explored the challenges datafication poses for educators in our contemporary information ecosystem, and why all of us should care. The session tried to scaffold frameworks that offer participants a critical lens to analyse their own data literacies and explore pathways to data literacy and data activism in institutions and networks.</p> <p>The workshop was technically implemented with success, and all the interactions were undertaken without any imprevist, due to the great support given by the OER20 committee. The OER20 community got engaged with our proposal: 94 participants were visible in the chat side and actively contributing.</p>
Strategies for Inclusion in Data Literacy Programming
<p>Jonathan Cain founded the Data Services Department at the University of Oregon with a goal of to prioritizing the needs of under-served students. The focus of our statistical consulting service and data literacy workshops has been to fulfill that vision. In this talk we discuss some of our strategies for reaching under-served students (students of color, immigrants, non-traditional students, and women in male-dominated fields), including the following: hiring students of color, international, and non-traditional students to provide peer consulting services and help lead workshops, and creating a welcoming environment for all students. This has meant, for example, offering a workshop sequence teaching R in Chinese (not common at a US university), and hiring a student specifically to liaise with and offer services to the McNair Scholars Program, a program for underrepresented undergraduate students who intend to pursue a PhD. As time allows, we will also address the limitations of our strategies and invite feedback from audience members about what strategies have worked at their institutions.</p>
FAIR data literacy project
<p>Data obtained from FAIR data study</p>
Survey data of the health literacy on COVID-19 and COVID-19 vaccination in Indonesia
<p><span><strong>Introduction</strong>: </span><span>Health literacy on COVID-19 and COVID-19 vaccination is valuable during the pandemic. The objective of this study was to determine the levels of health literacy about the COVID-19 vaccine and vaccination (Vaccine and Vaccination literacy—VL) in the Indonesian adult general population, assessing the perceptions of the respondents/interviewees about current adult immunization and beliefs about vaccination in general, and analyzing correlations of these variables with the VL levels.</span><span> </span></p> <p><span><strong>Methods</strong>: </span><span>A rapid survey was administered via the web. Data were analyzed using descriptive and inferential stats; the internal consistency of the VL scales was assessed through Cronbach's alpha coefficient, and a Principal Component Analysis (PCA) was conducted to investigate how the questions of the functional and interactive-critical VL scales were related to one another and whether the underlying components (factors) and each question's load on the components could be identified as anticipated. An alpha level lesser than 0.05 was considered significant.</span></p> <p><span><strong>Results</strong>: </span><span>Answers to functional- and interactive/ critical- VL questions showed good/ acceptable internal consistency (Cronbach's alpha = 0.817 and 0.699, respectively), lowest values observed were 0.806 for functional scale and 0.640 for the interactive-critical scale. PCA showed two components accounting for 52.45% of the total variability. Approximately 60% of respondents were females (n=686). Almost all respondents used the internet to seek information regarding COVID-19 and COVID-19 vaccination. Many used at least one social media actively with 74.4% of respondents sometimes believing the validity of this information.</span></p> <p><span><strong>Conclusions:</strong> </span><span>High scores were observed in both functional- and interactive/ critical-VL, and were quite balanced between genders in the prior VL and higher in females for the latter; these were also closely related to the educational level and age group. It is crucial to increase public health literacy on managing the pandemic.</span></p>
Survey data of the health literacy on COVID-19 and COVID-19 vaccination in Indonesia
Open the record for dataset details and reuse information.
Data literacy and research data management survey
<p>Data from Czech version of Data literacy and research data management multinational study.</p>
Data from: Evaluation of the psychometric properties of the Brazilian version of the Oral Health Literacy Assessment in Spanish and development of a shortened form of the instrument
Objective: The objective of this study was to investigate the psychometric properties of the Oral Health Literacy Assessment in Spanish (OHLA-S) for the Brazilian-Portuguese language using robust analysis and with the results disclose possibilities to develop a shorter and more valid instrument. Methods: OHLA-S is an oral health literacy instrument comprising a word recognition section and a comprehension section. It consists of 24 dental words. It was translated into the Brazilian-Portuguese language (OHLA-B) and its psychometric properties were evaluated in a random sample of 250 adults aged 20–59 years. To assess the dimensionality and factor structure were tested by means of Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Reliability was assessed using two indicators: Cronbach's alpha and McDonald's Omega. Results: EFA and CFA demonstrated that the OHLA-B with 24 items did not present an adequate adjustment of the model, compromising its validity. In addition, reliability values at 0.50 for Cronbach's alpha and 0.67 for McDonald's omega were below the minimum acceptable rate of 0.70. As no support was found for the original structure, we decided to proceed with the withdrawal of individual items and successive reanalysis of the model until the indicators were adjusted in a shorter instrument. A new structure with 15 items produced an instrument with two dimensions and a better goodness of fit than the original instrument. The Alpha and Omega reliability index values increased to 0.83 and 0.80, respectively, and all scores were better in the OLHA-B with 15 items than in the instrument with 24 items. Conclusion: OLHA-B with the original structure composed by 24 items did not show acceptable construct validity. The shorter version with 15 items showed more promising results for assessing oral health literacy levels in the Brazilian population.
Data from: Abortion legislation, maternal healthcare, fertility, female literacy, sanitation, violence against women, and maternal deaths: a natural experiment in 32 Mexican states
Open the record for dataset details and reuse information.
Data from: Evaluation of the psychometric properties of the Brazilian version of the Oral Health Literacy Assessment in Spanish and development of a shortened form of the instrument
Open the record for dataset details and reuse information.
Data Literacies & Practices in Higher Education: Educators' Perspectives
<p>Results from a summer 2020 survey exploring university educators' perspectives on educational technology and datafication in their classrooms. During COVID-19, the educational technologies we rely on for teaching are designed to translate digital experience into behavioural data, and this study seeks to establish a baseline understanding of what educators understand about this data and what they believe should happen with it, as well as how their perspectives and experiences related to teaching influence their responses to data.</p>
Data from: A qualitative study exploring the health literacy issues in the care of Chinese American immigrants with diabetes
Objectives: To investigate why first-generation Chinese immigrants with diabetes have difficulty obtaining, processing and understanding diabetes related information despite the existence of translated materials and translators. Design: This qualitative study employed purposive sampling. Six focus groups and two individual interviews were conducted. Each group discussion lasted approximately 90 min and was guided by semistructured and open-ended questions. Setting: Data were collected in two community health centres and one elderly retirement village in Los Angeles, California. Participants: 29 Chinese immigrants aged ≥45 years and diagnosed with type 2 diabetes for at least 1 year. Results: Eight key themes were found to potentially affect Chinese immigrants' capacity to obtain, communicate, process and understand diabetes related health information and consequently alter their decision making in self-care. Among the themes, three major categories emerged: cultural factors, structural barriers, and personal barriers. Conclusions: Findings highlight the importance of cultural sensitivity when working with first-generation Chinese immigrants with diabetes. Implications for health professionals, local community centres and other potential service providers are discussed.
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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.