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41 results for “Online assessment”

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zenodo40/100

Conclusions of the online assessment debate held on July 2, 2020, at the University of Salamanca (Spain)

<p>Conclusions of the online assessment debate held on July 2, 2020, at the University of Salamanca (Spain)</p>

opencc-by-4.0Oct 2020View details →
zenodo40/100

BRAIN Journal-Auto-generative Learning Objects in Online Assessment of Data Structures Disciplines-Figure 3. Symbols definition for a graph-based test

<p>In this scenario, we intend to generate a random graph and compute a deep first-search node list. The first defined random symbol is n, namely the number of nodes in the graph as an integer from 5 to 9. The next symbol is named g and denotes the graph object created randomly using 3 parameters: the number of nodes, the minimum, and the maximum value for the weight. For the number of nodes, we used the previously computed value of n, whereas for the weights, we used two constants 0 and 1 since the graph is not weighted</p>

opencc-by-4.0Sep 2017View details →
zenodo40/100

BRAIN Journal-Auto-generative Learning Objects in Online Assessment of Data Structures Disciplines-Figure 2. Auto-generative Learning Object Model Definition

<p>In this section, we will present the structure of AGLOs in the context of our approach. The AGLO meta-model is structured in XML as in Figure 2,a refinement from Chirila, Ciocarlie, and Stoicu (2015). The AGLO definition contains several sections like name, scenario, theory, question, answers, and feedback (line 01). The name element contains the name of the AGLO, possibly a small description in the human language (line 02). The section of the scenario (line 03) contains a comment (line 04) followed by a set of symbol definitions. The comment should describe the imagined scenario in details and it has the same role as code comments. The symbol is the central element of the AGLO model. The symbol has a name and is very similar to programming language variables. Symbols may be called also parameters since they control the content of the AGLO content in the process of instantiation.&nbsp;</p>

opencc-by-4.0Apr 2017View details →
zenodo40/100

BRAIN Journal-Auto-generative Learning Objects in Online Assessment of Data Structures Disciplines-Figure 1. The AGLO online assessment approach

<p>In Figure 1, we present the lifetime of AGLOs in the context of online student assessment following a set of steps. In the backend, the tutor develops an AGLO model respecting a predefined meta-model. The model is intuitive, it has a few sections where symbols are defined using formulas and random numbers and then used in a section of a presentation for the student. When such models are created they are stored in a storage facility like a database to be selected by the student through the web application frontend. In the frontend, the students access the web application using a web browser from a workstation, tablet or smartphone. In the assessment process, the student will access several AGLOs. At this step, the accessed AGLOs are instantiated with random numbers, formulas are evaluated to fulfill the designed learning or testing scenario and to create the presentation content for the student. Nevertheless, the instantiated symbols will be used for the automatic assessment of the answers correctness</p>

opencc-by-4.0Apr 2017View details →
zenodo40/100

BRAIN Journal-Auto-generative Learning Objects in Online Assessment of Data Structures Disciplines-Figure 4. Online test assessment example

<p>Thus, applying these restrictions the computed solution is C, E, G, J, L, H, I and is unique. Node C is the starting node since it is the first from the lexicographical point of view. The first step CE is the only choice coping with the restrictions from the [CE, CG, and CJ] edges. Next, EG is the first edge in the list of [EG, EJ]. The next step is GJ which is the only choice. Edge JL is another unique choice. Edge LH is the next step from the list [LH, LI]. Finally, the last edge is obtained by backtracking to node L and then taking edge LI. These restrictions allow us to drive the student to build only one solution from the possible set of solutions. This will determine an easier way of comparing the student&rsquo;s answer with the answer of the computer. Another more general solution is to use validation functions which require implementation in domain libraries written in JavaScript.&nbsp;</p>

opencc-by-4.0Sep 2017View details →
zenodo40/100

An Online Integrated Development Environment for Automated Programming Assessment Systems Open Source Data

<p>This dataset accompanies the paper <em>"An Online Integrated Development Environment for Automated Programming Assessment Systems"</em>. It contains data from the usability evaluation of a feature-rich online IDE designed for integration into Automated Programming Assessment Systems (APASs). The dataset includes survey responses from 27 participants based on the Technology Acceptance Model (TAM), performance metrics such as memory usage, and qualitative user feedback. The study highlights challenges in integrating online IDEs with APASs, such as memory efficiency, load balancing, and user experience. The dataset supports further research in developing scalable, effective, and user-friendly programming education tools.<br><br>Here you can find the code changes required for the online IDE in Artemis: <a href="https://github.com/ls1intum/Artemis/pull/6706/files" target="_blank" rel="noopener">Github</a></p>

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

Emergency adaptations in online assessment in usually face-to-face environments

<p>Emergency adaptations in online assessment in usually face-to-face environments</p>

opencc-by-4.0May 2020View details →
zenodo36/100

Accuracy of online survey assessment of mental disorders and suicidal thoughts and behaviors in Spanish university students. Results of the WHO World Mental Health-International College Student initiative.

<p>This dataset contains clinical data about 287 university students that participated in a clinical reappraisal study with the objective of examining the accuracy of WMH-ICS online screening scales for evaluating four common mental disorders (Major Depressive Episode, Mania/Hypomania, Panic Disorder, Generalized Anxiety Disorder) and suicidal thoughts and behaviors used in a survey of Spanish university students(UNIVERSAL project).</p>

opencc-by-4.0Aug 2019View details →
ClinicalTrials.gov36/100

Assessing Mental Health Providers' Clinical Knowledge and Skills Via an Online Training on LGBTQ-affirmative Cognitive-behavioral Therapy

ClinicalTrials.gov study NCT04559698. IPD Sharing: NO. Countries: 1. Publications: 5.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov36/100

Skin Health Online for Melanoma: Better Risk Assessment

ClinicalTrials.gov study NCT03130569. IPD Sharing: NO. Countries: 1. Publications: 25.

closedIPD-NOFeb 2026View details →
zenodo32/100

Dataset - No Reference Image Quality assessment Scores for Humanities Online Repositories

<p>The dataset contains data on No-Reference Image Quality Assessment (NR-IQA) scores for online repositories in the humanities.</p>

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

Ethical Impact Assessment of sharing nanosafety data: raw data of the online survey among participants in the XX Seminar on Nanotechnology, Society and Environment in Brazil and online, on 18 October 2023

<p>One excel sheet includes the responses to the online survey on Ethical Impact Assessment of sharing nanosafety data of participants in the XX Seminar on Nanotechnology, Society and Environment in Brazil and online, on 18 October 2023, in Portuguese, and the other the translated responses in English.</p>

opencc-by-4.0Jul 2024View details →
ClinicalTrials.gov32/100

Online Videodensitometric Assessment of Aortic Regurgitation in the Cath-Lab

ClinicalTrials.gov study NCT04047082. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Online Noninvasive Assessment of Human Brain Death and Deep Coma by Near-infrared Spectroscopy

ClinicalTrials.gov study NCT04623294. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Pragmatic RCT to Assess the Effectiveness of an Online Self-help Programme for Older Adults After Spousal Bereavement

ClinicalTrials.gov study NCT05156346. IPD Sharing: NO. Countries: 1. Publications: 16.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Assess Extent of Agreement Between Online 24-hr Dietary Recall and Interviewer-administered 24-hr Dietary Recall on the Same Day for 2 Non-consecutive 2 Days 1 wk Apart to Adults and School Age Childr

ClinicalTrials.gov study NCT04372160. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

RCT Assessing the Impact of Online Training on Doctors' Prescribing for Older Patients

ClinicalTrials.gov study NCT02405975. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Assessing Online Interventions for Men's' Mental Health and Wellbeing

ClinicalTrials.gov study NCT02785471. IPD Sharing: NO. Countries: 1. Publications: 2.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

International Online Survey Assessing Secondary Traumatic Stress, Burnout, Compassion Satisfaction and Turnover Intentions Among Youth Care (Para)Professionals in Flanders, Wallonia, France and The Ne

ClinicalTrials.gov study NCT07384026. IPD Sharing: NO. Countries: 1. Publications: 11.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Investigating the Effects of Cocoa Flavanol on Cognition Assessed Online

ClinicalTrials.gov study NCT04582617. IPD Sharing: YES. Countries: 1. Publications: 5.

controlledIPD-YESFeb 2026View details →

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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.

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