Skip to main content
Powered by ShareScore

Find research datasets worth reusing

Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.

14

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

14 results for “student conceptions”

Learn how ShareScore rates datasets ↗
zenodo40/100

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>&nbsp;</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 &ldquo;true&rdquo; statement and SV for &ldquo;student conception&rdquo;. 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>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; </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>

opencc-by-4.0Oct 2024View details →
zenodo36/100

Psycholinguistic features of verbal representation of the concept of "gender inequality" by student youth

<p><strong><em>Goal. </em></strong><em>To present the results of a psycholinguistic experiment devoted to the study of verbal representations of the concept of &quot;gender inequality&quot; in the linguistic consciousness of young people.</em></p> <p><strong><em>Methods: </em></strong><em>a</em><strong><em>&nbsp;</em></strong><em>systematic analysis and generalization of literature on gender aspects of psycholinguistic research. Directed associative experiment (DAE) with the word-stimulus &quot;gender inequality&quot;; method of cognitive interpretation; questionnaire: to clarify the characteristics of the sample, comparative-descriptive and mathematical-statistical methods.</em></p> <p><strong><em>Results. </em></strong><em>The concept of &quot;gender inequality&quot; in the linguistic consciousness of student youth is represented by such frequent associations as: humiliate (6.8%), fight (4.5%), suppress (3.7%), insult (2.6%) and limit (2.3%). Differences in the most frequent reactions of women and men were revealed: women - to humiliate 42 (7.9%), to fight 32 (6%), to suppress 19 (3.6%), to limit 16 (3%), to insult 15 (2.8%) ), respect 11 (2.1%), solve 11 (2.1%); men: humiliate 11 (4.5%), oppress 10 (4.1%), insult 5 (2%), defend 5 (2%). </em></p>

opencc-by-4.0Aug 2021View details →
dryad36/100

Following Darwin's footsteps: Evaluating the impact of an activity designed for elementary school students to link historically important evolution key concepts on their understanding of natural selection

<p>While several researchers have suggested that evolution should be explored from the initial years of schooling, little information is available on effective resources to enhance elementary school students' level of understanding of evolution by natural selection (LUENS). For the present study, we designed, implemented and evaluated an educational activity planned for fourth graders to explore concepts and conceptual fields that were historically important for the discovery of natural selection. Observation field notes and students' productions were used to analyse how the students explored the proposed activity. Additionally, an evaluation framework consisting of a test, the evaluation criteria and the scoring process was applied in two fourth-grade classes to estimate elementary school students' LUENS before and after engaging in the activity. Our results suggest that our activity allowed students to effectively link all of the key concepts in the classroom and produced a significant increase in their LUENS. These results indicate that our activity had a positive impact on students' understanding of natural selection. They also reveal that additional activities and minor fine-tuning of the present activity are required to further support students' learning about the concept of differential reproduction. We also observed a low level of teleological predictions for both pre- and post-tests. --</p>

opencc-zeroJun 2022View details →
zenodo36/100

Data for Reserach titled "Exploring Scientific Reasoning and Genetics Self-efficacy as Predictors of Secondary School Students' Achievement in Genetics Concepts"

<p>This dataset&nbsp;is for the research article titled&nbsp;Exploring Scientific Reasoning and Genetics Self-efficacy as Predictors of Secondary School Students&rsquo; Achievement in Genetics Concepts. The data were collected using three instruments (Lawson&rsquo;s Classroom Test of Scientific Reasoning (r = 0.76), adopted from the Lawson&#39;s Classroom Test of Scientific Reasoning designed by Lawson in 2000; Self-efficacy in Genetics Concepts Scale (@ = 0.88),adapted from Schwarzer and Jerusalem (1995) General Self Efficacy Scale and Biology Self-Efficacy developed by Baldwin, Ebert-May and Burns (1999); and Students&rsquo; Achievement Test in Genetics Concepts (r = 0.78), self-designed by the athors) from&nbsp;336 Secondary School Two (SS2) biology students selected from nine secondary schools randomly selected from three local government areas in Oyo State. SPSS version 26 was employed as the statitsical software, while data collected were subjected to mean, standard deviation, percentages, ANOVA and Multiple regression analysis at 0.05 level of significance.</p>

opencc-by-4.0Sep 2023View details →
dryad36/100

Following Darwin’s footsteps: Evaluating the impact of an activity designed for elementary school students to link historically important evolution key concepts on their understanding of natural selection

Open the record for dataset details and reuse information.

publicJun 2022View details →
dryad32/100

Data from: Redesign of a life cycle figure improves student conceptions of ecology and evolution

<p>Life cycle diagrams communicate the developmental life stages of an organism. Design choices may inadvertently communicate additional information about survivorship rates, genetic variation, and microevolutionary change. In this controlled experiment, we randomly assigned one of three life cycle diagrams to 684 college students. Each figure included identical life stages of a fictitious organism's development but differed in 1) number of offspring (single or multiple) and 2) layout (cyclical or linear). Each participant could reference the figure when answering questions about organism survival, variation among offspring, and variation between generations. Students scored 21–37% higher on questions about survivorship when the available diagram included multiple offspring. Students scored 19–30% higher on questions about microevolution when the diagram layout was linear. Overall, students who received the figure with a linear layout and multiple offspring earned the highest average score (54.5%, or 3.3 of 6 questions) on the assessment, while students with the traditional figure (cyclical layout with single offspring) scored the lowest average (26.1%, or 1.6 of 6 questions). These results suggest that figure design affects student interpretations and may assist student learning about ecology and evolution concepts and common misconceptions.</p>

opencc-zeroApr 2024View details →
zenodo32/100

A dataset for assessing ChatGPT capabilities to create concept maps for secondary school students

<p>The dataset was compiled to examine the use of ChatGPT 3.5 in educational settings, particularly for creating and personalizing concept maps.&nbsp;<br>The data has been organized into three folders: Maps, Texts, and Questionnaires. The Maps folder contains the graphical representation of the concept maps and the PlanUML code for drawing them in Italian and English. The Texts folder contains the source text used as input for the map's creation&nbsp; The Questionnaires folder includes the students' responses to the three administered questionnaires and the submitted questionnaires.</p>

opencc-by-4.0Jun 2024View details →
zenodo32/100

Associated data underlying the publication "Introducing Open Data Concepts to STEM Students Using Real-World Open Datasets"

<p>While open data concepts become more important in our society, education about its benefits and technical issues is still behind the practice. Students of STEM disciplines should be introduced to open data during their education. The Open Computing course, completely redesigned in the new Computing curriculum, introduces open data concepts, providing both the basics and advanced topics, from technical to social and legal viewpoints. Among the several educational activities, one was particularly useful for understanding the needs and implications of using open data: a synchronous group activity where students had to choose a societal issue, find and analyze two open datasets that would help gaining insight into this issue, assess interdisciplinarity approaches and stakeholders, and finally propose the added value emerging from the solution. In a short amount of time needed, this activity &ndash; which tackled multiple aspects of the problem - brought a clearer insight into the topic, building upon the conventional lectures. Students highly graded such an approach to their education, where they had to construct their knowledge by the group experience. A similar group activity appeared to be useful in the context of open data PhD training and might also be used in other disciplines and domains.</p>

opencc-by-4.0Jul 2023View details →
dryad32/100

Data from: Redesign of a life cycle figure improves student conceptions of ecology and evolution

Open the record for dataset details and reuse information.

publicApr 2024View details →
zenodo28/100

ENHANCING STUDENT ENGAGEMENT IN MATHEMATICAL CONCEPTS THROUGH STORIES AND NARRATIVES: AN INVESTIGATION

Open the record for dataset details and reuse information.

opencc-by-4.0Dec 2023View details →
zenodo28/100

FEATURES OF UKRAINIAN STUDENTS` VERBAL REPRESENTATION OF THE GENDER INEQUALITY`S CONCEPT

<p>The study aimed to determine Ukrainian students&#39; verbal representation of the gender inequality&#39;s concept. Verbal representations were obtained based on the use of a directed associative experiment. The study involved 309 students (199 females and 110 males) from 17 to 25 years. Gender analysis showed: women provided 539 reactions, including 530 verbal (176 originals) reactions and nine rejections; men provided 319 reactions: 310 verbal reactions (103 original) and nine rejections. The most frequent reactions to the stimulus &ldquo;gender inequality&quot; were revealed: жінка / woman (10,6%), чоловік / man (9,4%), фемінізм / feminism (4,3%), несправедливість / injustice (3,7%), права / rights (2,9%), нерівність / inequality (2,8%), стать / gender (2,7%), сексизм / sexism (2,4%), дискримінація / discrimination (2,3%), насильство / violence (2%). It was determined that the concept of &quot;gender inequality&quot; has a negative connotation among Ukrainian students. Cognitive interpretation of the data showed that the concept has a more negative emotional connotation for women than for men. For a significant number of women, gender inequality includes experiences associated with sexism, discrimination, and violence. Analysis of male associations has shown that men&#39;s concept has a less emotional response and is presented at a more abstract (theoretical) level.</p>

opencc-by-4.0Sep 2021View details →
ClinicalTrials.gov24/100

The Effect of Puzzles on Concept Learning in Nursing Students

ClinicalTrials.gov study NCT06170567. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

Effect of Concept Mapping Teaching Method on Critical Thinking Skills of Medical Students

ClinicalTrials.gov study NCT02816242. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
zenodo20/100

A dataset to investigate ChatGPT for enhancing Students' Learning Experience via Concept Maps

<p>The dataset was compiled to examine the use of ChatGPT 3.5 in educational settings, particularly for creating and personalizing concept maps.&nbsp;<br>The data has been organized into three folders: Maps, Texts, and Questionnaires. The Maps folder contains the graphical representation of the concept maps and the PlanUML code for drawing them in Italian and English. The Texts folder contains the source text used as input for the map's creation&nbsp; The Questionnaires folder includes the students' responses to the three administered questionnaires.</p>

restrictedcc-by-4.0Jun 2024View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record