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35 results for “computing education”
Dataset for Paper "Towards Increased Diversity in STEM Education: Five archetypes Derived through a Data-Driven Approach Examining a Computer Science Student Cohort
<p># Dataset for Paper "Towards Increased Diversity in STEM Education: Five archetypes Derived through a Data-Driven Approach Examining a Computer Science Student Cohort" - Rev #1</p> <p>This is the dataset for the paper titled "Towards Increased Diversity in STEM Education: Five archetypes Derived through a Data-Driven Approach Examining a Computer Science Student Cohort".</p> <p>In case of questions, feel free to contact the authors, *anonymised*, ORCID: https://orcid.org/*anonymised*, current affiliation and email: *anonymised*</p> <p>## Survey 2019 ##<br> The raw survey data for the initial 2019 survey is available in the file *survey2019_anon.csv*. Note that the data is anonymised as free-text comments have been removed. Explanations on the variables and their levels are given in the files *variables_survey2019.csv* and *values_survey2019.csv*.<br> The questionnaire for the 2019 survey is contained in *survey2019_instrument.pdf*.</p> <p>## Survey 2020 ##<br> The raw survey data for the 2020 survey is available in the file *rdata_anon_survey2020.csv*. Additional scripts are supplied to reproduce the exploratory factor analysis. The main entry is the file *EFA.R*, which imports the data. The file contains some comments on the process.<br> The questionnaire for the 2020 survey is contained in *survey2020_instrument.pdf*.</p> <p>## Interviews ##<br> The interview guide used for the five interviews is available in the file *interview_instrument.pdf*.</p>
Participant survey for the article: More than Formulas - Integrity, Communication, Computing and Reproducibility in Statistics Education
<p>The artcile More than Formulas - Integrity, Communication, Computing and Reproducibility in Statistics Education concerns the introduction of a new course format in the Master Program in Biostatistics at the University of Zurich. This data set contains the results fo a survey among the participants in this new course.</p> <p>Sepcifically it contains the answers of 22 participants to the following questions:</p> <p>1) Did you use the following concepts or tools since you took STA472? <br>Good practice for...</p> <p>... spreadsheets<br>... file and folder organization<br>... version control<br>... dynamic reporting<br>... LaTeX<br>... presentation slide design <br>... oral presentations<br>... designing graphs<br>... designing tables<br>... structure for manuscript<br>... logic of a paragraph<br>... writing style<br>... writing R functions<br>... using unit tests<br>... setting up simulations<br>... code styling<br>... writing vectorized code<br>... writing parallelized code<br>... containerizing code</p> <p>Answers are in the scale: never since, rarely, sometimes, often, frequently, I do not know</p> <p>2) If you used the above concepts at least rarely, did the training of STA472 help you?</p> <p>Good paractice for...</p> <p>... spreadsheets<br>... file and folder organization<br>... version control<br>... dynamic reporting<br>... LaTeX<br>... presentation slide design <br>... oral presentations<br>... designing graphs<br>... designing tables<br>... structure for manuscript<br>... logic of a paragraph<br>... writing style<br>... writing R functions<br>... using unit tests<br>... setting up simulations<br>... code styling<br>... writing vectorized code<br>... writing parallelized code<br>... containerizing code</p> <p>Answers are in the scale: Not really Somewhat Definitively I do not know I do not use this concept</p>
How Creatively Are We Teaching and Assessing Creativity in Computing Education: A Systematic Literature Review
<p>Data from:</p> <p>Wouter Groeneveld, Brett A. Becker, and Joost Vennekens. 2022. How Creatively Are We Teaching and Assessing Creativity in Computing Education: A Systematic Literature Review. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE 2022),March 3–5, 2022, Providence, RI, USA. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3478431.349936</p> <p><strong>When referring to this dataset, please cite the above article. That contains the DOI of this dataset. Please do not cite this dataset directly without citing the article.</strong></p>
Data sets - The attitude of computer science teachers to inclusive education, Motivation to teach, Perception of the possible impact of computer science on students with mental disabilities
<p>Data sets </p> <p>The attitude of computer science teachers to inclusive education, Motivation to teach, Perception of the possible impact of computer science on students with mental disabilities. <br>In the period from February to October 2024, a survey of 112 computer science teachers in Kazakhstan (Pavlodar region) was conducted to determine attitudes to inclusive education, motivation to teach, and perception of the possible impact of computer science on students with mental disabilities.</p> <p>Questionnaire <br>https://docs.google.com/document/d/1LzukKSqW_mHMZXbMtN0ecmmU4cKJiwgf0laTWBHQSng/edit?usp=sharing</p> <p><strong>This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP14872400).</strong></p>
98 selected publications analysed in-depth in the context of a systematic literature review on Computational Thinking in compulsory education
<p>This is the list of the <strong>98 publications from between 2016 and 2021 </strong>analysed in-depth through a review matrix in the context of the <strong>"</strong><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><strong>"</strong> <strong>research study.</strong> 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> <p>Bocconi, S., Chioccariello, A., Kampylis, P., Dagienė, V., Wastiau, P., Engelhardt, K., Earp, J., Horvath, M.A., Jasutė, E., Malagoli, C., Masiulionytė-Dagienė, V., & Stupurienė, G. (2022). <em>Reviewing Computational Thinking in Compulsory Education</em>. Publications Office of the European Union. <a href="https://doi.org/10.2760/126955">https://doi.org/10.2760/126955</a></p> <p> </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>
Additional Data: Mapping the Evolution of Computational Thinking in Education: A Bibliometrics Analysis of Scopus Database from 1987 to 2023
<p>The following is a selection of figures and tables from a bibliometric study that will be released later. The title of this study is Mapping the Evolution of Computational Thinking in Education: A Bibliometrics Analysis of Scopus Database from 1987 to 2023.</p> <p>In the online listing of the appendix, we will find three figures (Figure 5, Figure 6, and Figure 12) and three tables (Table 3, Table 4, and Table 4), also several references related to this research. It was important to us that the core of the study that is now being carried out not be diminished in any way, which is why we chose the photos and tables we did. This study was conceived and supported by the Indonesia Endowment Fund for Education (LPDP), which the Ministry of Finance administers in the Republic of Indonesia, to evaluate current trends and research problems in computational thinking for education. The Scopus database was used, and its range of coverage was from 1987 to 2023.</p> <p> </p>
A Bibliometrics Analysis of Australian Computing Education Conference Proceedings
<p>The bib file includes the bib records of all research publications of Australasian Computing Education Conference prior to 2022.</p>
Supplementary Material - Women's Journey in STEM Education in Brazil: A Rapid Review on Engineering and Computer Science
<p>Supplementary Material for the Rapid Review - Women's Journey in STEM Education in Brazil in Engineering and Computer Science courses</p>
Comparing LLM-Generated Tips and Expert-Created Tips in Quantum Computing Education
<p>This dataset includes the anonymized data from two studies with the goal to evaluate if LLM-generated tips can be used instead of expert-created tips to help students answer quantum computing questions. <br>For the main study (<em>main_test_anonymous.csv</em>) a between-subject design was used to quizz participants of the QUIKSTART 2024 summer school, giving them four multiple-choice quantum physics questions and one tip per question. Each participant was assigned one of four conditions represented by the combination of "creator" and "labeled_as" column in the csv file. In addition we asked to rate quality, correctness and helpfulness for each tip and to rate the perceived difficulty of the question. We removed demographics for anonymities sake.</p> <p>Additionally, we conducted a study directly comparing the LLM-generated and expert-created tips (<em>tip_eval_anonymous.csv</em>). Where we let experts and students rate the tips helpfulness, correctness, if they gave away the answer and if they pointed to relevant concepts. Furthermore, participants had to decide for each question which tip they preferred and were able to leave a comment to give their reasoning. We removed demographics for anonymities sake.<br><br>These datasets were evaluated in the paper "LLM-Generated Tips Rival Expert-Created Tips in Helping Students Answer Quantum-Computing Questions" by Lars Krupp, Jonas Bley, Isacco Gobbi, Alexander Geng, Sabine Müller, Sungho Suh, Ali Moghiseh, Arcesio Castaneda Medina, Valeria Bartsch, Artur Widera, Herwig Ott, Paul Lukowicz, Jakob Karolus, Maximilian Kiefer-Emmanouilidis</p>
A Systematic Mapping of the Classification of Open Educational Resources for Computer Science Education in Digital Sources (Data)
<p>Data from a Systematic Mapping of the classification of Open Educational Resources for Computer Science Education.</p> <p>Content:</p> <ul> <li>Studies selected</li> <li>Digital sources used to classify Open Educational Resources for Computer Science Education</li> <li>Computer Science domains explored by Open Educational Resources</li> <li>Approaches for the classification of Open Educational Resources for Computer Science Education</li> </ul>
98 selected publications analysed in-depth in the context of a systematic literature review on Computational Thinking in compulsory education
<p>This is the list of the <strong>98 publications from between 2016 and 2021 </strong>analysed in-depth through a review matrix in the context of the <strong>"</strong><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><strong>"</strong> <strong>research study.</strong> 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> <p>Bocconi, S., Chioccariello, A., Kampylis, P., Dagienė, V., Wastiau, P., Engelhardt, K., Earp, J., Horvath, M.A., Jasutė, E., Malagoli, C., Masiulionytė-Dagienė, V., & Stupurienė, G. (2022). <em>Reviewing Computational Thinking in Compulsory Education</em>. Publications Office of the European Union. <a href="https://doi.org/10.2760/126955">https://doi.org/10.2760/126955</a></p> <p> </p>
Dataset for the paper "How to Work on Equality and Inclusion when Introducing Computational Thinking and Educational Robotics in Early Childhood Education: A Systematic Review"
<p>Resources for the Systematic Literature Review (SLR) about Computational Thinking and Educational Robotics in Early Childhood Education for fostering equality and inclusion. The SLR is related to the project "COEDUIN-Alfabetización digital y STEAM en edades tempranas: propuesta co-educativa inclusiva" funded by Fundación Caja Canarias and Fundación La Caixa (ref. 2020EDU08).</p> <p>The SLR covers papers in WoS and Scopus from 2011 to 2022.</p>
Computer Based Treatment for Cognitive Behavioral Therapy and Cooperative Pain Education and Self-Management
ClinicalTrials.gov study NCT05204576. IPD Sharing: NO. Countries: 1. Publications: 1.
Feasibility of a Touch Screen Computer Based Breast-feeding Educational Support Program
ClinicalTrials.gov study NCT03308058. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Interactive Computer-adaptive Chronic Kidney Disease Education Program
ClinicalTrials.gov study NCT06364358. IPD Sharing: YES. Countries: 1. Publications: 1.
Data from: Is computer-assisted instruction more effective than other educational methods in achieving ECG competence amongst medical students and residents? A systematic review and meta-analysis.
Objectives It remains unclear whether computer-assisted instruction (CAI) is more effective than other teaching methods in acquiring and retaining ECG competence amongst medical students and residents. Design This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Data sources Electronic literature searches of PubMed, databases via EBSCOhost, Scopus, Web of Science, Google Scholar and grey literature were conducted on 28 November 2017. We subsequently reviewed the citation indexes of articles identified by the search. Eligibility criteria Studies were included if a comparative research design was used to evaluate the efficacy of CAI versus other methods of ECG instruction, as determined by the acquisition and/or retention of ECG competence of medical students and/or residents. Data extraction and synthesis Two reviewers independently extracted data from all eligible studies and assessed the risk of bias. After duplicates were removed, 559 papers were screened. Thirteen studies met the eligibility criteria. Eight studies reported sufficient data to be included in the meta-analysis. Results In all studies, CAI was compared to face-to-face ECG instruction. There was a wide range of computer-assisted and face-to-face teaching methods. Overall, the meta-analysis found no significant difference in acquired ECG competence between those who received computer-assisted or face-to-face instruction. However, sub-analyses showed that CAI in a blended learning context was better than face-to-face teaching alone, especially if trainees had unlimited access to teaching materials and/or deliberate practice with feedback. There was no conclusive evidence that CAI was better than face-to-face teaching for longer-term retention of ECG competence. Conclusion CAI was not better than face-to-face ECG teaching. However, this meta-analysis was constrained by significant heterogeneity amongst studies. Nevertheless, the finding that blended learning is more effective than face-to-face ECG teaching is important in the era of increased implementation of e-learning. PROSPERO registration number CRD42017067054
Fostering Inclusivity and Equality in Early Childhood Education via Computational Thinking and Robotics: A Systematic Review
<p>Resources for the Systematic Literature Review (SLR) about Computational Thinking and Educational Robotics in Early Childhood Education for fostering equality and inclusion. The SLR is related to the project "COEDUIN-Alfabetización digital y STEAM en edades tempranas: propuesta co-educativa inclusiva" funded by Fundación Caja Canarias and Fundación La Caixa (ref. 2020EDU08).</p> <p>The SLR covers papers in WoS and Scopus from 2011 to 2023.</p>
STEM CO-EDUCATIONAL ENVIRONMENTS COMBINING EDUCATIONAL ROBOTICS AND COMPUTATIONAL THINKING
<h1><span>AMBIENTES COEDUCATIVOS STEM QUE COMBINAN ROBÓTICA EDUCATIVA Y PENSAMIENTO COMPUTACIONAL </span></h1> <p><span> </span></p> <p><strong><span>STEM CO-EDUCATIONAL ENVIRONMENTS COMBINING EDUCATIONAL ROBOTICS AND COMPUTATIONAL THINKING</span></strong></p> <p> </p> <p> </p> <p> </p> <p><span>Resumen en español </span></p> <p><span>El presente artículo de investigación se enfoca en abordar las desigualdades de género en el ámbito educativo, especialmente en las disciplinas STEM, mediante el uso de la robótica educativa y el pensamiento computacional. Para ello se realiza una revisión sistemática de literatura, con el objetivo de analizar tendencias, desafíos y oportunidades en la implementación de estas estrategias en Colombia y su impacto en el cierre de brechas de género. Aunque no se encontró una revisión que sintetice la evidencia de estos temas de manera conjunta, el estudio actual busca llenar ese vacío y contribuir a intervenciones educativas futuras más equitativas.</span></p> <p><span>Palabras clave (en español): </span><span>Educación STEM, Robótica educativa, Pensamiento computacional, Brechas de género, Vocaciones científicas</span><span>.</span><span> </span></p> <p>Resumen en inglés</p> <p><span>This research article focuses on addressing gender inequalities in education, especially in STEM disciplines, through the use of educational robotics and computational thinking. To this end, a systematic literature review is conducted, with the aim of analyzing trends, challenges and opportunities in the implementation of these strategies in Colombia and their impact on closing gender gaps. Although no review was found that synthesizes the evidence on these topics together, the current study seeks to fill this gap and contribute to more equitable future educational interventions.</span></p> <p><span>Palabras clave (en inglés): STEM education, educational robotics, Computational thinking, Gender gaps, Scientific vocations. </span></p>
Dataset for CIIE 2018 folio number 2018062802133: A Computational Literature Review of Educational Innovation
<p>Dataset for CIIE 2018 folio number 2018062802133: A Computational Literature Review of Educational Innovation</p>
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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.