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54 results for “textbooks”
Sampling bias exaggerates a textbook example of a trophic cascade
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Social data from "Ecology, The Economy of Nature" (10th edition, 2025): Addressing diversity in undergraduate ecology textbooks"
This data package includes social data on the diversity and composition of people depicted in the text, photographs, and illustrations of the ecology textbook Ecology: The Economy of Nature (10th ed.) by Relyea (2025). The data were utilized in an article published in Frontiers in Ecology and the Environment, which explores the use of undergraduate textbooks as tools for building a diverse community of ecologists (Richards et al., 2025). Relyea, R. (2025). Ecology: The Economy of Nature (10th ed.). W.H. Freeman. ISBN 9781319524838 Richards JH, Charton KT, McFarlane SL, Widell AF, Haddad NM, Wyer MB, Damschen EI (2025) Rethinking the undergraduate textbook as a tool to build a diverse community of ecologists. Frontiers in Ecology and the Environment 23(3), e2819, https://doi.org/10.1002/fee.2819.
Test Data from a Study on Latin Vocabulary Acquisition with Beginners (Textbook)
<p>The dataset contains test results from an intervention study with beginners in the 5th grade of a high school in Berlin. In total, 103 students participated in four groups (= classes). The intervention materials and tests are published as well.</p> <p>A key question of the still ongoing research project is: How can vocabulary competence in a historical language such as Latin be acquired and deepened by using corpus-based, i.e. context-based, methods? This question is based on a broad understanding of vocabulary that refers back to theories of the mental lexicon.</p>
CATCH-EyoU: Representation of the EU and Youth Active Citizenship in Educational Contexts: Cross-national Textbook Analysis
<p>The data set contains the results of the quantitative and qualitative content analysis of local textbooks from different subjects (e.g. ESL, EFL, History, Social Sciences, Civic Education) at ISCED 3 level (upper secondary schools as well as vocational schools). Data collection was carried out using a specifically designed analytical grid (Ribeiro; Ferreira & Menezes, 2016). The grid was tested and applied by national research teams (Portugal, Czechia, Estonia, Germany, Italy and Sweden) participating to Catch-EyoU project – each textbook analysis implied filling one grid. In total, 34 textbooks were analysed across the participating countries. All grids include excerpts of the textbooks (text or images, whenever legally possible). Quantitative analysis data and bibliographical metadata are also included.</p> <p>Data collection and analysis was aimed at getting an overall picture of school texts, including the analysis of number of paragraphs, pages and exercises about topics such as the EU, active citizenship, intercultural awareness, political involvement.</p> <p>Although textbook analysis is relatively common and there are other European projects that include it, the data analysis grid is original (and relatively innovative in the area) as it directly relates to the project topics.</p> <p>The potential users can be other researchers who might be interested not only in the grid but also in the analysis itself, either to use it with other textbooks or compare it with existing research or with similar data collected in different countries; teachers might also find it useful to explore the analysis as a basis for their practice. Also other stakeholders may be interested in reanalyzing our data for comparative aims.</p>
dataset of paper Bibliometric Analysis of Veterinary Medicine on Embryo of Animals in Textbook in Conceptualizing Disease
<p>this is the dataset of meta-data of books and book chapter downloaded from scopus website using subscription service</p>
Extracting Educational Code Scenarios from Python Textbooks
<p><strong>Dataset Overview:</strong> This dataset complements the research project titled "Extracting Learning Scenarios from Python Textbooks." It consists of 1,017 chapter titles collected from 76 Python textbooks.</p><p><strong>Research Findings:</strong> Our analysis revealed that learning scenarios (referred to as "Scenarios") are a prevalent theme, constituting approximately 39.5% of the total chapter titles in comparison to other content categories. We further categorized these scenarios into four types, including Application Programming Interfaces, Data and Processing, Graphical User Interfaces, and other scenarios. Additionally, we identified a list of 19 Python modules commonly used within these scenarios.</p><p><strong>Purpose:</strong> We envision that this work and its insights can serve as stepping stones and lay the groundwork for further extraction and the effective application of how Python can be utilized for its diverse audience.</p>
Russian physics textbook
textbook of physics from Russia, the usual one in which I studied Source: Objaverse 1.0 / Sketchfab
Climate change in textbooks
<p>Climate change is a potent threat to human society, biodiversity, and ecosystem stability. Yet a 2021 Gallup poll found that only 43% of Americans see climate change as a serious threat over their lifetimes. In this study, we analyze college biology textbook coverage of climate change from 1970 to 2019. We focus on four aspects for document analysis: 1) the amount of coverage, determined by counting the number of sentences within the climate change passage, 2) the start location of the passage in the book, 3) the categorization of sentences as addressing a description of the greenhouse effect, impacts of global warming, or actions to ameliorate climate change, and 4) the presentation of data in figures. We analyzed 57 textbooks. Our findings show that coverage of climate change has continually increased. However, the greatest increase occurred during the 1990s, despite the growing threats of climate change. The position of the climate change passage moved further back in the book, from the last 15% to the last 2.5% of pages. Over time, coverage shifted from a description of the greenhouse effect to focus mostly on effects of climate change; the most addressed impact was shifting ecosystems. Sentences dedicated to actionable solutions to climate change peaked in the 1990s at over 15% of the passage, then decreased in recent decades to 3%. Data figures present only global temperatures and CO2 levels prior to the year 2000, then include photographic evidence and changes to species distributions after 2000. We hope this study will alert curriculum designers and instructors to consider implicit messages communicated in climate change lessons.</p>
Incentivizing Textbooks for Self-Study: Experimental Evidence from the Democratic Republic of the Congo
<p>The package contains the code and data for generating the tables, figures, and other statistical details included in the paper "Incentivizing Textbooks for Self-Study: Experimental Evidence from the Democratic Republic of the Congo."</p>
CATCH-EyoU: Representation of the EU and Youth Active Citizenship in Educational Contexts: Textbook Analysis: Portugal
<p>This dataset consists of the underlying data of the following scientific paper accepted for publication by the Journal of Social Science Education (<a href="http://www.jsse.org/">http://www.jsse.org/</a>):</p> <p>Piedade, Filipe; Ribeiro, Norberto; Loff, Manuel; Neves, Tiago & Menezes, Isabel (2018). Learning about the European Union in times of crisis: Portuguese textbooks’ normative visions of European citizenship. <em>Journal of Social Science Education</em>.</p> <p>This data has been collected from five Portuguese upper secondary education books, from the disciplines of History and English as a Foreign Language (EFL).</p> <p>In particular, the files constituting this data set contain data that are specifically concerned with those Portuguese textbooks’ contents that are related with the European Union (partial data). These contents were analysed by members of the Portuguese research team and presented in the paper.</p> <p>Additional data is still under analysis by the Portuguese research team and will be made openly available in successive versions of the data set.</p> <p>This data is made available for open access in compliance with H2020 Program regulation, following the guidelines stipulated by the Data Management Plan adopted by the CATCH-EyoU research project.</p>
Textbook Outcomes After Oesophagectomy in Regional Australia
ClinicalTrials.gov study NCT06721715. IPD Sharing: NO. Countries: 1. Publications: 5.
Textbook Outcome in Adrenal Neoplasms
ClinicalTrials.gov study NCT05888753. IPD Sharing: NO. Countries: 1. Publications: 1.
Design and Validation of a Preoperative Calculator for "Textbook Outcome" After Bariatric Surgery (BARCINO)
ClinicalTrials.gov study NCT06044116. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Gastric Cancer' Textbook Oncological Outcome and Tumor Board Performance
ClinicalTrials.gov study NCT06923449. IPD Sharing: NO. Countries: 1. Publications: 8.
Textbook Outcome as a Composite Outcome Measure in Laparoscopic Pancreaticoduodenectomy
ClinicalTrials.gov study NCT05616403. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Climate change in textbooks
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Study of terminological subsystems of modern school textbooks in Russian with the help of word embedding models Word2Vec and neural networks
<p>The aim of the project is to analyse the inventory and functioning of scientific terms and special lexemes in textbooks for secondary schools of the Russian Federation with the help of modern methods of natural language processing and deep learning. The number of terms from different fields of knowledge that a pupil should learn during secondary school studies has never been evaluated. According to the preliminary evaluations made on the basis of the Model Basic Curriculum for General and Secondary Education in 2015 only the subject "Russian language" presupposes that a pupil finishing the 11th grade of secondary school should be able to understand, recognise and use about 1000 terms and terminological combinations. Thus, taking into account the number of school subjects, the total number of special vocabulary units studied in general education schools is measured in thousands. At the same time, the comparative characteristics of the inventory and functioning of terms in textbooks for different school subjects are not studied and remain unknown. The correlation between the terminological density of the text in school textbooks for different subjects and the place occupied by these subjects in the curriculum is not clear. The traditional way of compiling lists of scientific terms is simply by gleaning them from special texts and writing down manually. If this method is reliable in terms of intellectualisation of selection principles, it cannot be applied to large data sets and does not reflect either the frequency of use of terms, or the specificity of their syntagmatic connections, or the systemic relationship between terms. The current project is aimed at filling this gap by means of 1) creating a full-text corpus of school textbooks for 5–11 classes included in the Federal List compiled by the Ministry of Education, 2) automatic extraction, stratification, and mapping of terms with the help of distribution semantics algorithms, 3) creation and training of a deep neural network capable of predicting the subject, level of education and educational topic given a group of vector representations of terms as input. The results of the research can be of fundamental interest in the perspective of terminology science development and also have practical applications in the creation of different types of educational literature.</p> <p><em>Funding: The reported study was funded by RFBR, project number 19-29-14032</em></p>
Faulconer 2024 ERAU Textbook Affordability Champion Certificate
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PROVIDING KNOWLEDGE ABOUT SYLLABLES IN THE MOTHER TONGUE TEXTBOOK FOR CLASS 2
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Study of terminological subsystems of modern school textbooks in Russian with the help of word embedding models Word2Vec and neural networks
<p>The reported study was funded by RFBR, project number 19-29-14032 mk.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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International Brain Laboratory public data
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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.