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633 results for “teaching”
Dataset for "The effects of teaching strategies on learning to think critically in primary and secondary schools: an overview of systematic reviews"
<p>A dataset for the overview of systematic reviews entitled "The effects of teaching strategies on learning to think critically in primary and secondary schools: an overview of systematic reviews". </p>
Figure 1 in Are goldish spiders able to teach naïve predators to avoid bullet ants? A possible case of Müllerian mimicry in spiders and ants
Figure 1. Sphecotypus niger (Perty, 1833), live female (body length 12 mm): (a) lateral; (b) dorsal; (c) Neoponera villosa (Fabricius, 1804), live worker, dorsal; (d) Area of bite from S. niger shortly after incident, with mild swelling and erythema.
West Spitsbergen Fold and Thrust Belt: a digital educational data package for teaching structural geology
<p>The following digital educational data package is provided as part of the submission of the publication Horota et al. (2022) <em>West Spitsbergen Fold and Thrust Belt: a digital educational data package for teaching structural geology</em>, considered for publication in the Journal of Structural Geology. The dataset contains a QGIS, ArcGIS Pro and a Petrel projects with all the associated data.</p>
Teaching the process of science with primary literature: Using the CREATE pedagogy in ecological courses
<p>There have been numerous calls for improved pedagogical practices in biological education, and there is a clear need for such improvements in ecology and related curricula. Most ecology-related texts lack pedagogy and are designed to be content-rich. National initiatives, such as Vision & Change, provide guidance on undergraduate biology education, including increasing use of evidence-based active learning, and taking a more conceptual and science practice skills approach. Biology education research is rich with evidence-based teaching practices, which reveal that active learning approaches implemented in thoughtful ways lead to strong learning gains relative to lecture-based course delivery. CREATE (Consider, Read, Elucidate the hypothesis, Analyze and interpret data, Think of the next Experiment) integrates evidence-based active pedagogical practices into one approach to STEM education that focuses heavily on the process of science and science practice skills rather than content delivery by replacing the textbook with selected journal articles. The approach focuses on deep reading and analysis of primary literature; immersing students in the literature is an advantage of the pedagogy. CREATE was developed and tested in other biological disciplines (genetics, molecular biology) that have long been at the forefront of pedagogical best practices in biology. We transformed two upper-level undergraduate ecological courses (Conservation Biology & Biodiversity and Ecology) into CREATE courses. We provide examples of assignments, student work, and assessments of the approach, illustrating the various ways CREATE can be successfully implemented. The approach can be adopted in part, to ease into it and test it out, or in whole. We recommend that ecology teachers consider making their courses more active if they have not already done so; adopting pedagogical practices embedded within CREATE can be a way to achieve active learning. The CREATE approach and other evidence-based pedagogical best practices lead to strong learning gains and more inclusive learning environments.</p>
Overcoming Challenges in DevOps Education through Teaching Methods
<p>DevOps is a set of practices that deals with coordination between development and operation teams and ensures rapid and reliable new software releases that are essential in industry. DevOps education assumes the vital task of preparing new professionals in these practices using appropriate teaching methods. However, there are insufficient studies investigating teaching methods in DevOps. We performed an analysis based on interviews to identify teaching methods and their relationship with educational challenges. Our findings show that <strong>project-based learning</strong> and <strong>collaborative learning</strong> are emerging as the most relevant teaching methods.</p>
Adaptation and evolution of teaching method for university programming subject to the online learning environment - Commit Data
<p>This dataset contains commit UNIX timestamps for Copymaster assignment git repositories of students studying Operating Systems class at Technical University of Košice in the span of years 2017/2018 - 2020/2021.</p>
Adaptation and evolution of teaching method for university programming subject to the online learning environment - Student surveys dataset
<p>This dataset contains anonymized survey data of students studying Operating Systems class at the Technical University of Košice in the span of school years 2017/2018 to 2020/2021.</p>
Adaptation and evolution of teaching method for university programming subject to the online learning environment - Student point gain dataset
<p>This dataset contains anonymized study results of students studying Operating Systems class at the Technical University of Košice in the span of school years 2015/2016 to 2020/2021.</p>
FIG. 10 in Teaching Ichthyology Online with a Virtual Specimen Collection
FIG. 10. Annotated skull model of Artedius lateralis (OS6720) from CT scan data collected at the Karel F. Liem Imaging Facility at Friday Harbor, Washington. See the supplementary videos to view this model in motion (see Data Accessibility). (Credit: T. Buser and A. Summers).
FIG. 8 in Teaching Ichthyology Online with a Virtual Specimen Collection
FIG. 8. Still images of 3D models for Leptagonus frenatus (OS17247) and Chaetodon fremblii (OS5698). See the supplementary videos for examples of these and other models being manipulated in three dimensions (see Data Accessibility). (Credit: L. Carr, N. Harper, and M. Leppin).
FIG. 6 in Teaching Ichthyology Online with a Virtual Specimen Collection
FIG. 6. Examples of worksheet pages completed by students in the online version of FW316, Systematics of Fishes. Drawings 2020 K. Webber (upper panel) and 2020 T. Chapman (lower panel), used with permission of their creators.
FIG. 7 in Teaching Ichthyology Online with a Virtual Specimen Collection
FIG. 7. Two-dimensional images from the virtual specimen collection. Species and specimens pictured: Cymatogaster aggregata (OS5910), Dendrochirus sp. (OS teaching collection), Lepomis macrochirus (OS18438), Oncorhynchus tshawytscha (OS16943), Parophrys vetulus (OS898), Hydrolagus colliei (OS1942), Percopsis transmontana (OS17965), Catostomus bondi (OS16985), and Lepisosteus oculatus (OS teaching collection). (Credit: M. Burns, K. Knight, and M. Vazquez).
FIG. 4 in Teaching Ichthyology Online with a Virtual Specimen Collection
FIG. 4. Paired lateral and ventral views of a Pacific Spiny Lumpsucker specimen (Eumicrotremus orbis, OS6725). (Credit: K. Knight).
FIG. 1 in Teaching Ichthyology Online with a Virtual Specimen Collection
FIG. 1. Tiered application architecture diagram outlining the design of the virtual specimen collection. The collection's middleware processes user queries to retrieve relevant data and images from cloud storage, and then constructs a dynamic webpage displaying those data or allowing the user to modify the desired section of the database. (Credit: M. Kindred).
FIG. 3 in Teaching Ichthyology Online with a Virtual Specimen Collection
FIG. 3. The photography room at the Oregon State Ichthyology Collection, including photo tanks, LED arrays, camera, and tripod. (Credit: B. Sidlauskas).
FIG. 2 in Teaching Ichthyology Online with a Virtual Specimen Collection
FIG. 2. The species page for Ptychocheilus oregonensis from the virtual specimen collection, including links to lateral views of alcohol-preserved specimens, a closeup of the gill rakers, and cleared and stained material. Clicking on any image pulls up a full-size version and some accompanying metadata, such as the species identification and the specimen's catalog number. Scrolling down reveals more textual information. (Credit: B. Sidlauskas).
Effectiveness of Using 2D Atlas and 3D PDF as a Teaching Tool in Anatomy Lectures in Initial Learner Medical Students: A Randomized Controlled Trial
<p><strong>Dataset Info</strong></p> <p><strong>1) Immediate Test</strong></p> <p># The first row of the dataset identifies the columns.<br> # The first column represents the participant ids.<br> # The second column represents the participants' assigned group.<br> # The third column represents represents the genders of participants (1: Female, 2: Male)<br> # The fourth column represents the years of participants' in their six-year-long medical schools (1: Year-1 students, 2: Year-2 students).<br> # The fifth column represents participants' repeating year status. (0: No, 1: Yes)<br> # The sixth to the fifteenth columns (liver_q1_max2points to liver_q10_max2points) represent the scores in the first to tenth questions of the liver test. Maximum points of the questions can be seen on the first row of the relevant column.<br> # The sixteenth column (livertotalscore_max20points) represents the total score in the liver test.<br> # The seventeenth to the thirty fifth columns (genitalia_q1_max3points to genitalia_q19_max2points) represent the scores in the first to nineteenth questions of the genitalia test. Maximum points of the questions can be seen on the first row of the relevant column.<br> # The thirty sixth column (genitaliatotalscore_max40points) represents the total score in the genitalia test.</p> <p> </p> <p><strong>2) Delayed Test</strong></p> <p># The first row of the dataset identifies the columns.<br> # The first column represents the participant ids.<br> # The second column represents the participants' assigned group.<br> # The third column represents represents the genders of participants (1: Female, 2: Male)<br> # The fourth column represents the years of participants' in their six-year-long medical schools (1: Year-1 students, 2: Year-2 students).<br> # The fifth column represents participants' repeating year status. (0: No, 1: Yes)<br> # The sixth to the fifteenth columns (liver_q1_max2points to liver_q10_max2points) represent the scores in the first to tenth questions of the liver test. Maximum points of the questions can be seen on the first row of the relevant column.<br> # The sixteenth column (livertotalscore_max20points) represents the total score in the liver test.<br> # The seventeenth to the thirty fifth columns (genitalia_q1_max3points to genitalia_q19_max2points) represent the scores in the first to nineteenth questions of the genitalia test. Maximum points of the questions can be seen on the first row of the relevant column.<br> # The thirty sixth column (genitaliatotalscore_max40points) represents the total score in the genitalia test.</p>
Distance learning and face-to-face learning in medical PBL course during COVID-19 pandemic: an investigation and teaching experience
<p>Our research provides an experience for the PBL class focusing on discussion and communication. In the post-pandemic era, whether face-to-face or distance learning, classes should be adjusted properly to let students conduct effective communication in time.</p>
Active Learning Prototypes for Teaching Game AI
<p><strong>Supplementary materials for “Active Learning Prototypes for Teaching Game AI”</strong></p> <p><em>Overview</em></p> <p>This package contains the following files and folders:</p> <ul> <li><code>LICENSE_CODE.txt</code> - The license for the included code.</li> <li><code>LICENSE_DATA.txt</code> - The license for the included data.</li> <li><code>README.md</code> - Package description.</li> <li><code>requirements.txt</code>- Specifies the Python dependencies required for running the included notebook.</li> <li><code>survey_analysis.ipynb</code> - Notebook used for analyzing the survey data.</li> <li><code>survey_data.ods</code>- Fully anonymized survey data.</li> </ul> <p><em>Reproducibility of results</em></p> <p>The results presented in the research paper “Active Learning Prototypes for Teaching Game AI”, published in the Proceedings of the IEEE Conference on Games 2023, and authored by Nuno Fachada, Filipa F. Barreiros, Phil Lopes and Micaela Fonseca, can be reproduced with the Jupyter notebook included in this package.</p> <p><em>Licenses</em></p> <ul> <li>The code in the Jupyter Notebook is made available under the <a href="https://opensource.org/licenses/MIT">MIT</a> license (see <code>LICENSE_CODE.txt</code>).</li> <li>The non-code materials are made available under a <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license (see <code>LICENSE_OTHER.txt</code>).</li> </ul>
Predictor variables of context and teaching strategies
<p>Table A1. Predictor variables of context (students, teachers, school)</p> <p>Table A2. Predictor variables of teaching strategies (students, teachers, school)</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.