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142 results for “user evaluation”
MEDIATOR Driving Simulator Study Germany: Questionnaire Data User Evaluation HMI
<p>The dataset provided resulted from a driving simulator study conducted by Chemnitz University of Technology (TUC) within work package 3 of the MEDIATOR project. The study focused on the user evaluation of the Mediator system and its functionalities, including the innovative Human Machine interface (HMI). The user evaluation centred on acceptance, trust, usability, comfort and the experience of Transitions of Control (TOCs). The core idea of the Mediator system is to mediate between the human driver and the automated system. Thereby, the Mediator system aims at establishing both as a team that is aware of each other’s strengths, limitations as well as current states in order to achieve safe TOCs, which are actively proposed by the HMI. The main focus of the driving simulator study was on comfort TOCs from manual to automated driving, simulated automation degradation and related TOCs by the human driver, comfort critical situations (i.e., close approach to the rear-end of a traffic jam) as well as the influence of driver characteristics. The provided dataset contains the questionnaire data of 74 German-speaking participants.</p> <p> </p> <p>This document contains information about the study methodology and coding of the variables. For a detailed description, please consult Mediator deliverable D3.3 ‘Results of the MEDIATOR driving simulator evaluation studies’ (Part II – Driving simulator study Germany). Please note that selected passages of this deliverable were adopted (partly in a slightly modified manner) in this document.</p> <p> </p> <p>This dataset is licensed under a <a href="https://spdx.org/licenses/CC-BY-4.0.html">Creative Commons Attribution 4.0 International</a> License.</p> <p> </p> <p>The research leading to this dataset received funding from the European Commission Horizon 2020 programme under the project MEDIATOR (<a href="https://mediatorproject.eu/">https://mediatorproject.eu/</a>), grant agreement number 814735.</p> <p> </p> <p>If you use the dataset, please cite it as: MEDIATOR (2023). MEDIATOR Driving Simulator Study Germany: Questionnaire Data User Evaluation HMI. <a href="https://doi.org/10.5281/zenodo.7638299">https://doi.org/10.5281/zenodo.7638299</a></p> <p> </p> <p>For further information, please contact: <a href="mailto:cornelia.hollander@psychologie.tu-chemnitz.de">cornelia.hollander@psychologie.tu-chemnitz.de</a>.</p>
SciKGTeX Scientific Contribution Metadata LaTeX Package User Evaluation Results & Analysis
<p>The responses and measured variables from 26 participants of the first user test of the SciKGTeX package.</p> <p><a href="https://github.com/Christof93/SciKGTeX">https://github.com/Christof93/SciKGTeX</a></p> <p>Also the raw text source for the evaluation tasks and the result analysis notebook with the results saved as tsv file.</p>
Supporting information of a study for the definition and evaluation of a graphical user interface for housing co-design
<p>This dataset is from a study that intends to define, prototype and test a graphical user interface for a housing co-design system. To define the requirements of the interface, we conducted interviews with professionals of architecture, urbanism and social sciences areas, as well as with housing cooperatives and inhabitants of these institutions. An interface solution was prototyped, tested and refined. Then we conducted a heuristic evaluation and a summative evaluation. Such evaluations involved the testing of a high-fidelity prototype, to receive feedback from UX/UI experts, potential users (inhabitants) and architects.</p> <p>S1_File refers to the interview protocol used with the three groups of interviewees. We share the English and Portuguese versions of the interviews with professionals and the original (Portuguese) and translated versions of the remaining ones since these were conducted in Portuguese.</p> <p>S2_File is a dataset reporting the results of the interviews. Each question includes the answers given and the identification (anonymized) of the interviewees who responded to that question.</p> <p>S3_File describes the usability issues identified by the experts during the heuristic evaluation of the high-fidelity prototype. The first page organizes the issues by severity (left) and priority (right). The remaining pages have a table for each issue, including rows for problem designation, heuristic violated, problem description, solution proposal, severity degree, and an image of the interface pointing to the referred issue.</p> <p>S4_File refers to the results of the heuristic evaluation. It includes the identification of each issue, which expert (anonymized) identified such issue, and the heuristic it violates, with the sum of the times each heuristic was violated at the end of each column. At the right, a table presents the consolidation of issues, organized by priority, with columns identifying the issue, severity level, frequency, and priority.</p> <p>S5_File is the script given to potential users to experiment with the interface during the summative evaluation. This script guides the user through the tasks to perform since the prototype does not have all the features functioning.</p> <p>S6_File refers to the questionnaires applied during the summative evaluation with inhabitants. It includes a preliminary questionnaire, a Single Ease Question (SEQ) questionnaire, a System Usability Scale (SUS) questionnaire, and a Graphical User Interface (GUI) questionnaire.</p> <p>S7_File refers to the results of the summative evaluation with inhabitants (potential users).</p> <ul> <li>Page A refers to the preliminary questionnaire with demographic information such as age, gender, education, relationship with digital technologies, etc. Each field corresponds with each inhabitant (anonymised) and the sum and percentage. In the middle, a table presents a summary of the consolidation. In the right possible relations are presented. </li> <li>Page B presents the results of the SEQ questionnaire, identifying the ratings each inhabitant (anonymized) gave each task. A summary of such values is at the right. </li> <li>On page C, the result of each rating for the SUS questionnaire given by each inhabitant (anonymized) is shown. At the bottom is the calculation of the SUS score.</li> <li>Page D presents the GUI questionnaire results for each inhabitant (anonymized), with the average and SD identified for each question. A summary of such results is on the right.</li> <li>Page E holds the notes taken by the researchers based on their observations regarding task performance. The information is organized in tables for each step of each task and includes the completeness, attempts, and time taken for each inhabitant (anonymized) to complete such task. Also, the sum, percentage, average, and SD are registered. Next to each task is a table identifying how many participants accomplished the task at the first attempt.</li> <li>Page F refers to the strong and weak aspects identified by the inhabitants. Strong and weak aspects are identified, as well as which inhabitant (anonymized) has identified them. The sum and percentage are also given. At the right, there is a table with the consolidation of results by combining similar answers. </li> </ul> <p>S8_File refers to the results of the discussion with architects after experiencing the interface. Such results relate to the positive and negative aspects that the architects identified in the interface and its usefulness for architecture. The left table identifies the strong and weak aspects that architects (anonymized) identified and the sum and percentage associated with them. The table on the right consolidates such results, with similar responses combined.</p>
User Interaction Evaluation of 3D Handicraft Products Application
<p>The dataset for analysis during the study for evaluation of 3D handicraft products application for smartphones usage</p>
User participation in digital accessibility evaluations: reviewing methods and objectives
<p><span>Although laws and standardization bodies promote user participation in digital accessibility evaluations, people with disabilities still consider themselves excluded from this process. One reason could be the lack of systematized knowledge about evaluation methods involving users. This article seeks to understand how and for what purpose digital accessibility evaluations with user participation were conducted in the scientific literature from 2018 to 2021. Three types of user participation emerged: 1) user-based usability testing to evaluate task accomplishment, user reactions and interface qualities; 2) interviewing users to assess the local and social factors impacting digital service accessibility; 3) using questionnaires or crowdsourcing to check the compliance of certain interfaces with accessibility standards. Participants are primarily chosen based on their functional impairments and, to a lesser degree, their project-related skills, biographical information, technology habits, among other criteria. The comprehensive user insights gained with these methods are judged to be positive whereas the lack of representativeness of the selected user samples is found to be regrettable. The article finally discusses the definitions of accessibility and disability that underpin these methodologies.</span></p>
User Experience Evaluation of BRI Smart Billing Mobile Application Using System Usability Scale and Heuristic Evaluation
<p>This research aims to evaluate user perceptions of the design and functionality of the BRI Smart Billing Mobile app. Through a questionnaire distributed to active BRI Smart Billing users, this study will identify factors that influence user satisfaction with the visual appearance, layout of elements, and ease of use of features available on the dashboard. The results of this research are expected to provide input to the application developers regarding efforts to improve the quality of digital application services and provide recommendations for improving the design of the BRI Smart Billing Mobile dashboard to be more user-friendly and meet user needs.</p>
Evaluation notebook and files for FAIR Workbench user evaluation
<p>This archive contains the Jupyter notebook and associated (image) files used in the June 2021 evaluation of the FAIR Workbench.</p>
Study Dataset: Shedding Light on CVSS Scoring Inconsistencies: A User- Centric Study on Evaluating Widespread Security Vulnerabilities
<p>This record contains the <strong>study datasets, descriptive results and questionnaires</strong> from the paper "Shedding Light on CVSS Scoring Inconsistencies: A User-Centric Study on Evaluating Widespread Security Vulnerabilities" by Julia Wunder, Andreas Kurtz, Christian Eichenmüller, Freya Gassmann and Zinaida Benenson to appear in Proceedings of the 45th IEEE Symposium on Security and Privacy (2024).</p> <p>The pseudonymous <strong>datasets</strong> contain data from the online surveys (main study with 196 participants and follow-up study with 59 participants). The first row gives the question codes and questions, the following rows gives the answers from the participants (see also README.md).</p> <p>We also provide <strong>descriptive results</strong> from the online surveys as PDF and the questionnaires.</p> <p>Please refer to the README.md file and our paper for further details about the data set and study.</p>
Data for: Evaluation of Methods for Eliciting and Specifying Usability Requirements using User Stories: A Controlled Experiment
<p>Este projeto contém os materiais utilizados na pesquisa intitulada Evaluation of Methods for Eliciting and Specifying Usability Requirements using User Stories: A Controlled Experiment: TCLE, Formulário de Caracterização, Cenário, Oráculo, User Stories, Protótipo, Storyboards, Avaliação de ferramentas em escala de Likert e Dados coletados do formulário.</p>
Technical and user evaluation of mobile application for pedestrian safety
<p>This file contains the evaluation results of the tests carried out a Versailles during the Show project with external participants:</p> <ul> <li>Technical indicators have been collected in one sheet</li> <li>Feedbacks from the user questionnaires have been collected in one other sheet</li> </ul>
User evaluation results for a Wikidata-centric tool for temporal data in Humanities and Cultural Heritage (June 2024): raw tabular result data and web forms for two questionnaires from five online focus group workshops
<p><strong>Introduction</strong></p> <p>This resource is created for the article: "Wikidata Visualization for Event and Temporal Data Exploration in Digital Humanities and Cultural Heritage" in Semantic Web Journal Special issue on the Semantic Web and Ontology Design for Cultural Heritage. It contains materials use for the user evaluation (June 2024) of a Wikidata visualization tool (<a title="ReKisstory" href="https://rekisstory.labs.vu.nl/" target="_blank" rel="noopener">ReKisstory</a>) described in the article. </p> <p><strong>Summary of the user evaluation</strong></p> <p>The structrue of the user evalution is summarized in the table below:</p> <table style="border-collapse: collapse; width: 99.9708%;"><colgroup><col style="width: 28.0622%;"><col style="width: 26.893%;"><col style="width: 27.0309%;"><col style="width: 17.9856%;"></colgroup> <tbody> <tr> <td> </td> <td>Objectives</td> <td>Setup </td> <td># of people participating</td> </tr> <tr> <td>Pre-workshop survey</td> <td>Understanding potential user profiles before workshop</td> <td>Online questionnaire (Q1)</td> <td>51</td> </tr> <tr> <td>Workshop (Focus Group)</td> <td>Introducing and testing the tool. Obtaining feedback about it</td> <td>Online demo, testing, discussion</td> <td>16</td> </tr> <tr> <td>Post-workshop survey</td> <td>Understanding user needs after testing</td> <td>Online questionnaire (Q2)</td> <td>11</td> </tr> </tbody> </table> <p> </p> <p><strong>The structure of the data is as follows:</strong></p> <p>1. The PDF and PPTX files, containing materials prepared for the pre-workshop survey, workshop, and post-workshop survey:</p> <ul> <li>Pre-workshop survey: Questionnaire (Q1) screenshot from GoogleForms <a href="https://zenodo.org/records/14960584/files/1stQuestionnaire.pdf?download=1&preview=1">1stQuestionnaire.pdf</a></li> <li>Post-workshop survey: Questionnaire (Q2) screenshot from GoogleForms <a href="https://zenodo.org/records/14960584/files/2ndQuestionnaire.pdf?download=1&preview=1">2ndQuestionnaire.pdf</a></li> <li>Documents distributed to the participants of the Focus Group Workshop: <ul> <li>ReKisstory Compare section manual <a href="https://zenodo.org/records/14960584/files/rekisstory_compare_manual.pdf?download=1&preview=1">rekisstory_compare_manual.pdf</a></li> <li>ReKisstory Find section manual <a href="https://zenodo.org/records/14960584/files/rekisstory_find_manual.pdf?download=1&preview=1">rekisstory_find_manual.pdf</a></li> <li>ReKisstory Find example search patterns <a href="https://zenodo.org/records/14960584/files/rekisstory_group_search_example_search_patterns.pdf?download=1&preview=1">rekisstory_group_search_example_search_patterns.pdf</a></li> <li>Workshop slides <a href="https://zenodo.org/records/14960584/files/Focus_Group_Workshop_slides.pptx?download=1&preview=1">Focus_Group_Workshop_slides.pptx</a></li> </ul> </li> </ul> <p>2. The Excel spreadsheets consists of the results of two questionnaires (Q1 and Q2) (<a href="https://zenodo.org/records/14960584/files/Two_questionnaires_online_workshops.xlsx?download=1&preview=1">Two_questionnaires_online_workshops.xlsx</a>): </p> <ul> <li>Pre-workshop survey: Questionnaire (Q1), containing information about potential users: <ul> <li>Demographics</li> <li>Experience of <ul> <li>Time-related data</li> <li>Wikidata</li> <li>SPARQL</li> </ul> </li> </ul> </li> <li>Post-workshop survey: Questionnaire (Q2), containing information about feedback from the Workshop participants : <ul> <li>Comparison with Q1</li> <li>Questions about time-related functionalities</li> <li>Questions about Compare and Find searches</li> <li>Overall comment</li> </ul> </li> </ul> <p><em>Please see "Wikidata Visualization for Event and Temporal Data Exploration in Digital Humanities and Cultural Heritage" for more details</em></p>
Questionnaire used in FAIR Workbench user evaluation
<p>A pdf copy of the Questionnaire filled out by users at the end of the FAIR Workbench user evaluation study. The questions regarded the evaluation notebook, published here: http://doi.org/10.5281/zenodo.5045448</p>
Experimental results and the user questionnaires for KG profiling tool (ABSTAT vs Protégé) evaluation
<p>Experimental results and the user questionnaires for KG profiling tool (ABSTAT vs Protégé) evaluation</p>
User Requirements and Evaluation Survey
<p>This is the survey used to elicitate the user requirements.</p> <p>Also, the results are included.</p>
# Blocks? Graphs? Why Not Both? Designing and Evaluating a Hybrid Programming Environment for End-users: Replication Package
<p><strong>Blocks? Graphs? Why Not Both? Designing and Evaluating a Hybrid Programming Environment for End-users: Replication Package</strong></p> <p>This repository contains supplementary materials for the paper "Blocks? Graphs? Why Not Both? Designing and Evaluating a Hybrid Programming Environment for End-users". We provide this data for transparency reasons and to support replications of our experiemnts.</p> <p><em>Note: This package is anonymized for peer review purposes. We will provide contact information for the authors at a later date. We also plan to add interactive versions of our tasks and tutorials in an updated version to allow readers easier exploration/experimentation.</em></p> <p><strong>Summary of files contained in this package</strong></p> <p>This package contains two parts:</p> <ul> <li> <p>The <code>data-analysis/</code> folder contains the raw dataset we collected for our experiment in CSV format, as well as scripts we used for our analyses.</p> <ul> <li>Column <code>ID</code> contains a unique 4-digit identifier for each participant that they were assigned throughout our study.</li> <li>Column <code>Group</code> contains the group (Blocks/Graph) that participants were randomly assigned to.</li> <li>Columns <code>Task1Time</code> and <code>Task2Time</code> contain the time participants spent to complete the two programming tasks of our study in minutes.</li> <li>Columns <code>Task1Success</code> and <code>Task2Success</code> contain a boolean value indicating whether the participants successfully completed the given task. Note that participants had unlimited attempts until they timed out after a strict time limit of 30 minutes, so if a participant was unsuccessful the corresponding time value is 30.</li> <li>Columns <code>Task1Tests</code> and <code>Task2Tests</code> contain the number of times a participant executed their code throughout a task, including their final submission if they were successful.</li> <li>Columns <code>LearnTask</code>, <code>ReadTask</code> and <code>WriteTask</code> contain the scores that participants gave to the task editor component of their assigned programming environment. There are 3 scores for the categories "learnability", "readability" and "writability". Scores are on a 5-point scale from 1 (worst) to 5 (best).</li> <li>Columns <code>LearnTrig</code>, <code>ReadTrig</code> and <code>WriteTrig</code> contain the scores that participants gave to the trigger editor component of their assigned programming environment. There are 3 scores for the categories "learnability", "readability" and "writability". Scores are on a 5-point scale from 1 (worst) to 5 (best).</li> <li>Columns <code>LearnComp</code>, <code>ReadComp</code> and <code>WriteComp</code> contain the scores that participants gave to their assigned assigned programming environment in direct comparison to the other alternative. There are 3 scores for the categories "learnability", "readability" and "writability". Unlike in the paper, where scores are on a scale from -2 to 2, the raw scores here are on a 5-point scale from 1 (strong preference for other environment) to 5 (strong preference for own environment).</li> <li>The script <code>survival.py</code> was used to perform the survival analysis presented in the paper and generate the related figure.</li> <li>The script <code>batplot.py</code> was used to generate the 3x3 grid of ratings used in a figure in the paper.</li> </ul> </li> <li> <p>The <code>materials/</code> folder contains the tutorials and task descriptions we presented to study participants. It also contains the exact wording of pre-screening and post-experiemental survey questions.</p> <ul> <li>The image <code>pre-screening.png</code> shows the three pre-screening questions we used to determine whether our participants could be included in our study.</li> <li>The images <code>tutorial1_instructions.png</code> and <code>tutorial1_sim.png</code> contain the instructions and initial simulator state we provided to participants for the first programming tutorial. This tutorial did not provide starter code and was identical for both participant groups.</li> <li>The images <code>tutorial2_instructions.png</code> and <code>tutorial2_sim.png</code> contain the instructions and initial simulator state we provided to participants for the second programming tutorial. This tutorial was identical for both participant groups and provided participants with starter code, which is shown in the images: <ul> <li><code>tutorial2_code_main.png</code> for the main program in the left canvas</li> <li><code>tutorial2_code_move.png</code> for the definition of "Move box to the right".</li> </ul> </li> <li>The images <code>tutorial3_instructions_blocks.png</code>/<code>tutorial3_instructions_graph.png</code> and <code>tutorial3_sim.png</code> contain the instructions and initial simulator state we provided to participants for the third programming tutorial. This tutorial also provided participants with starter code, which is shown in the images: <ul> <li><code>tutorial3_code_main.png</code> for the main program in the left canvas</li> <li><code>tutorial3_code_pick.png</code> for the definition of "Pick up box"</li> <li><code>tutorial3_code_place.png</code> for the definition of "Place box"</li> </ul> </li> <li>The images <code>task1_instructions.png</code> and <code>task1_sim.png</code> contain the instructions and initial simulator state we provided to participants for the first programming task. The task did not provide starter code and the instructions were identical for both participant groups.</li> <li>The images <code>task2_instructions.png</code> and <code>task2_sim.png</code> contain the instructions and initial simulator state we provided to participants for the second programming task. The instructions were identical for both groups. This task also provided participants with starter code, which is shown in the images: <ul> <li><code>task2_code_main.png</code> for the main program in the left canvas</li> <li><code>task2_code_pick_prog.png</code> for the definition of "Pick up block"</li> <li><code>task2_code_load_trig_blocks.png</code>/<code>task2_code_load_trig_graph.png</code> for the definition of the trigger "Ready to load machine"</li> <li><code>task2_code_load_prog.png</code> for the definition of "Load and activate machine"</li> <li><code>task2_code_finished_trig_blocks.png</code>/<code>task2_code_finished_trig_graph.png</code> for the definition of the trigger "Machine finished"</li> <li><code>task2_code_finished_prog1.png</code> for the definition of "Get block from machine"</li> <li><code>task2_code_finished_prog2.png</code> for the definition of "Place block in bin"</li> </ul> </li> <li>The image <code>usability.png</code> shows the usability questions we used to determine a participant's rating of their assigned programming environment. The questions were identical for both participant groups.</li> <li>The images <code>comprehension_blocks_1.png</code> and <code>comprehension_blocks_2.png</code> show the program comprehension questions we used to determine whether participants in the Blocks group could understand more complex triggers.</li> <li>The images <code>comprehension_graph_1.png</code> and <code>comprehension_graph_2.png</code> show the program comprehension questions we used to determine whether participants in the Graph group could understand more complex triggers.</li> <li>The images <code>comparison_blocks.png</code> and <code>comparison_graph.png</code> show the images of triggers in the alternative environment that we showed to our participants before choosing their preferred environment. The questions were identical for both participant groups.</li> <li>The image <code>comparison.png</code> shows the questions we used to determine a participant's preference between the two programming environment alternatives.</li> </ul> </li> </ul>
Assessing the Maturity level of Wearable Sensors for Home Monitoring in Parkinson's Disease through Evidence Evaluation Levels (EEL) and User Experience: A Comprehensive Review
<p>Source files for the PRISMA diagram and Figure 1 of the comprehensive review: Assessing the Maturity level of Wearable Sensors for Home Monitoring in Parkinson’s Disease through Evidence Evaluation Levels (EEL) and User Experience</p>
Evaluation of Doxycycline Post-exposure Prophylaxis to Reduce Sexually Transmitted Infections in PrEP Users and HIV-infected Men Who Have Sex With Men
ClinicalTrials.gov study NCT03980223. IPD Sharing: NO. Countries: 1. Publications: 13.
Evaluation of Cogmed Working Memory Training for Adult Hearing Aid Users
ClinicalTrials.gov study NCT01892007. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Evaluating the User Performance and Experience of Nucleus Pen vs. Commercially Available Pen Needle
ClinicalTrials.gov study NCT03267264. IPD Sharing: NO. Countries: 1. Publications: 1.
United Kingdom User Evaluation, MiniMed Paradigm® X54 System
ClinicalTrials.gov study NCT01267175. IPD Sharing: Not stated. Countries: 1. Publications: 1.
ScienceDex guides
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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.