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189 results for “conceptualization”
Conceptual Change Texts in Computer Science to Expand Students' Conceptions on the Topic of Artificial Intelligence
<p><strong><span>General information on the survey and cohort</span></strong></p> <p><span>The present data were collected in 2023 at a secondary school in Hamburg. A questionnaire was used as a pre- and post-test in computer science courses in years 10 and 11 to investigate the agreement with various items and how this changed. The questionnaires were transferred to SPSS for analysis.</span></p> <p><span>76 students aged 15-17 took part in the survey and the teaching intervention. This data set only contains the data that is available in full. It therefore includes the responses of 69 students, of which a total of 22 felt assigned to the female gender and 47 to the male gender.</span></p> <p> </p> <h3><span>Data set</span></h3> <p><span>The data is purely quantitative, as this is only the evaluation of the pre- and post-test and not the evaluation of the conceptual change texts themselves. The item list is made up of 20 items relating to artificial intelligence, which were drawn up according to the Big Ideas of the AI4K12 initiative [1]. The students' perceptions of the items come from various past studies that have surveyed students' conceptions of AI.</span></p> <p><span>The data has a pseudonymized code that can be linked to the conceptual change text of the experimental group and the data can be assigned accordingly. The data is also divided into the experimental group (abbreviation 2) and the control group (abbreviation 1) so that a comparison between the groups is quickly possible. The abbreviation W in front of the items stands for a “true” statement and SV for “student conception”. A Likert scale from 0 - does not apply at all to 3 - applies completely was used.</span></p> <p><span>The data set is cleansed data. All data sets that were not complete or that were given different codes in the pre-test and post-test and therefore could no longer be clearly assigned were removed.</span></p> <p><strong><span>Literature</span></strong></p> <p><span>[1]</span><span> </span>AI<span> </span>for<span> </span>K12<span> </span>(Hrsg.)<span> </span><span>(2020):<span> </span><em>AI4K12.org.<span> </span></em>Available online at:<span> </span>https://ai4k12.org/<span> </span>[last checked 12.03.2023]</span></p>
Conceptual illustration of particle emission in azimuth and relationship to elliptic flow and collectivity
<p>This set of images represents, in a schematic and simplified manner, the various scenarios for particle emission in high-energy interactions (heavy ions but also others). Individual images can be used alone or also in an animation explanatory sequence. The various versions are:</p> <ol> <li>The file `1-initialConditionIncoherentColored` shows how a number of particle-emitting sources will ultimately populate azimuth uniformly in case they emit incoherently. </li> <li>The file `2-initialConditionCoherentColored` shows how particle-emitting sources might generate a polar pattern in their particle emission provided any kind of overlap (e.g. strong interaction) leads to coherent emission. </li> <li>The file `3-initialConditionVelocityField` illustrates the concept of a common velocity field at the edges of the system. This is to be used, for instance, in a transition slide in which a speaker introduces some various limiting options of which entities actually have a common velocity. </li> <li>The file `4-initialConditionMassOrdering` illustrates the possibility that hadrons are emitted in a common velocity field, leading to mass-ordered elliptic flow such as the one observed at low transverse momentum in heavy-ion collisions. This serves to directly illustrate the patterns that are numerically created by e.g. the blast-wave model or the Cooper-Frye formalism.</li> <li>The file `5-initialConditionCoalescenceNCQ` illustrates the possibility that quarks are in a common velocity field just prior to hadronization via coalescence, leading to baryon/meson grouping of anisotropic flow. </li> <li>The file `6-combined-incoherent-vs-ncq` illustrates the incoherent scenario vs the coalescence scenario without the polar graph for simplicity.</li> <li>The file `7-combined-incoherent-vs-massordering-vs-ncq` illustrates the incoherent scenario, the mass ordering and the coalescence scenarios without the polar graph for simplicity.</li> </ol>
ySKILLS conceptual model
<p>This conceptual model which is a starting point for the different studies within the ySKILLS project, will be updated and revised based on new findings throughout the project. At the end of 2023, we will propose an updated version of this model.</p>
Validation of STS Conceptual Model Designing Approach. DMI374 and DMI747 Data Sets.
<p>Surveys of DMI374 and DMI747 student groups were conducted for the purpose of validating the STS conceptual model designing method. A 5-point and dichotomous Likert questionnaire was used for the survey. The files contain response datasets used in statistical processing.</p>
A Conceptual Model to Support Teaching of Software Engineering Controlled (Quasi-)Experiments - Evaluation of the Concept Model
<p>A Conceptual Model to Support Teaching of Software Engineering Controlled (Quasi-)Experiments - Evaluation of the Concept Model</p>
Supplementary Material to 'Exploring the power of data-driven models for groundwater system conceptualization: A case study of the Grazer Feld Aquifer, Austria'
<p>This folder contains the supplementary materials to reproduce the results, tables, and figures from the following publication submitted to the Hydrogeology Journal: </p> <p>Kokimova A., Collenteur, R.A. & Birk, S. Exploring the power of data-driven models for groundwater system conceptualization: A case study of the Grazer Feld Aquifer, Austria.</p>
Data from: Can extreme climatic events induce shifts in adaptive potential? A conceptual framework and empirical test with Anolis lizards
Open the record for dataset details and reuse information.
Dataset for paper titled: Conceptual preferences can be transmitted via selective social information use between competing wild bird species
Open the record for dataset details and reuse information.
Figures of the paper"A Conceptual Model of Chinese Oral Memory Based on Digital Humanities"
<p>Those are the figures used for the paper "A Conceptual Model of Chinese Oral Memory Based on Digital Humanities".</p>
The overview of the conceptual design of the app
<p>This overview of a conceptual design of the app was derived through Co-design Activity 1. It illustrated the "sitemap" of the app which a Deaf patient could use to accomplish communication with healthcare personnel at a primary health center.</p>
Accreditation Frameworks - conceptual view
<p>A conceptual view of how accreditation frameworks allow members to access content and stop non-members from accessing content.</p>
Conceptual model of uptake of inorganic carbon by the sulfur-oxidizing γ1-symbionts and transfer to their host, the gutless marine worm Olavius algarvensis
<p>Conceptual model of uptake of inorganic carbon by the sulfur-oxidizing γ1-symbionts and transfer to their host, the gutless marine worm <em>Olavius algarvensis.</em></p>
Conceptual map.
<p>Part of the thesis of Sonia Verdugo Castro (USAL, Spain). <br> Title of the article: "The gender gap in STEM higher education studies: visualisation of literature".<br> Authors of the publication: Sonia Verdugo-Castro, Mª Cruz Sánchez-Gómez, Alicia García-Holgado, Francisco J. García-Peñalvo</p>
Conceptualizing relationships among hyporheic exchange, storage, and water age: data represented in published figures
<p>Hyporheic exchange is a key driver of ecosystem processes in streams, yet stream ecologists often fail to leverage detailed conceptual models developed by engineers and hydrologists describing the relationship between water storage, water balance, and water age (time elapsed since a conceptual parcel of water entered the hyporheic zone) in hyporheic zones. In a companion paper (G.C. Poole et al. <em>Hyporheic Hydr</em><em>au</em><em>lic Geometry: Conceptualizing relationships among hyporheic exchange, storage, and water age</em>, published in PLoS ONE; doi:<a href="https://doi.org/10.1371/journal.pone.0262080">10.1371/journal.pone.0262080</a>), we provide visualizations of these relationships in an effort to allow non-hydrologists to grasp four primary concepts along with associated research and management implications: 1) the rate of hyporheic exchange, size of the hyporheic zone, and hyporheic water age are inexorably linked; 2) such linkages can be leveraged to build understanding of hyporheic processes; 3) the age distribution of hyporheic water and hyporheic discharge is heavily skewed toward young water ages -- at any temporal scale of observation (minutes, hours, days, or months) older hyporheic water is rare relative to younger water; 4) the age distribution of water discharged from any hyporheic zone is not the same as the age distribution of water stored within that hyporheic zone. The data set presented here represents the numerical values represented by the figures published in the companion paper.</p>
Example of Surabaya COPACR Business Process Architecture and Conceptual Data Model
<p>In this repository consist of three diagrams. Two diagrams are part of Surabaya COPACR Business Process Architecture (BPA), they are:</p> <p>1. Fig 1. Shows six value chains that become BPA Level 0 of the Surabaya COPACR. <br> 2. Fig 2. Shows Electronic ID card printing services as PBA Level 5</p> <p>And one diagram, Fig. 3 show Conceptual Data Model for Surabaya COPACR Core Process</p>
Schematic and adapted figures from IPBES Sustainable Use of Wild Species Assessment - Chapter 2. Conceptualizing the sustainable use of wild species
<p>Schematic and adapted figures from Chapter 2 of the thematic assessment of the sustainable use of wild species of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.</p>
Identifying conceptual neural responses to symbolic numerals
<p>The goal of measuring conceptual processing in numerical cognition is distanced by the possibility that neural responses to symbolic numerals are influenced by physical stimulus confounds. Here, we targeted conceptual responses to parity (even <em>vs. </em>odd), using electroencephalographic (EEG) frequency-tagging with a symmetry/asymmetry design. Arabic numerals (2–9) were presented at 7.5 Hz in 50-s sequences; odd and even numbers were alternated to target differential, "asymmetry" responses to parity at 3.75 Hz (7.5 Hz/2). Parity responses were probed with four different stimulus sets, increasing in intra-numeral stimulus variability, and with two control conditions comprised of non-conceptual numeral alternations. Significant asymmetry responses were found over the occipitotemporal cortex to all conditions, even for the arbitrary controls. The large physical-differences control condition elicited the largest response in the stimulus set with the lowest level of variability (1 font). Only in the stimulus set with the highest level of variability (20 drawn, colored exemplars/numeral) did the response to parity surpass both control conditions. These findings show that physical differences across small sets of Arabic numerals can strongly influence, and even account for, automatic brain responses. However, carefully designed control conditions and highly variable stimulus sets may be used towards identifying truly conceptual neural responses.</p>
Fig.2 in Conceptual Application Of Dytiscus Latissimus Linnaeus, 1758 (Dytiscidae, Coleoptera) Gathering Methods In Natural Habitat
Fig.2. Fishing tackle bought in a shop: A – standard; B – modernized
Conceptual Coupling Values - Github Projects Dataset
<p>A Dataset that contains conceptual coupling measures obtained on 61 opensource projects hosted in github.The conceptual coupling measure was calculated by 18 diferent ways. A way is called model. There are 299 software major version colected to calculate these values.</p> <p>To understand how each model was applyed, see the label meaning:</p> <ul> <li>Yco: Use code comment</li> <li>Nco: No use code comment</li> <li>Yca: Divide tokens by CamelCase</li> <li>Nca: no divide tokens by CamelCase</li> <li>Ns: no stemming tokens low frequency occurrence</li> <li>Ys: stemming tokens low frequeny occurrence</li> <li>Qth: remove third quantile </li> <li>Qfi: remove first quantile</li> <li>Lsi: Latent Semantic Indexing</li> <li>TFIDF: term frequency - inverse document frequency</li> <li>Naive: Term-Frequency</li> </ul> <p>All projects are from github and developed in the following language:</p> <ul> <li>C++</li> <li>Java</li> <li>Javascript</li> <li>Python</li> <li>Ruby</li> </ul> <p>This dataset also contains the following resources:</p> <ul> <li>Commits between those project versions</li> <li>List of versions used in this study</li> <li>Scripts used in some works</li> </ul>
Supporting data for: Výpočtová propaganda: konceptuálna diskusia a prehľad (eng. Computational propaganda: a conceptual discussion and review)
<p><em>Supporting data for a Literature Review.</em></p> <p><em>Abstract: Computational propaganda is a relatively new term introduced by P.N. Howard and S. C. Woolley. The term is nowadays being mainly discussed in the context of shaping public opinion during various political events in the United States, the United Kingdom, France, as well as in other countries. This article represents a literature review of computational propaganda using a quantitative research design. In the article we also present the first Slovak definition of computational propaganda as using Information and communication technologies for mass production and mass distribution of misleading information. </em></p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.