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61 results for “learning strategies”
Impact of Motivation, Learning Strategy and Intelligence Quotient on Medical Students Grades during first semester
<p>Rekapitulasi data MSLQ dan IQ </p>
Embracing Experiential Learning: Hackathons as an Educational Strategy for Shaping Soft Skills in Software Engineering
<div> <p>This public dataset covers the answers to both pre-hackathon and post-hackathon questionnaires. Additionally, we offer basic descriptive statistics related to the provided data.</p> </div>
The P3 event-related potential increases when humans learn a strategy for motor adaptation
<p>This publication contains the raw EEG and kinematics datasets along with the PCA solutions for experiments 1 and 2 presented in the manuscript entitled The <em>P3 event-related potential increases when humans learn a strategy for motor adaptation</em> by Betina Korka and Max-Philipp Stenner.</p>
DataSet for article: TEAM BASED LEARNING AS A STRATEGY OF WORKING IN THE CLASSROOM
<p>Archive with the references of the RSL carried out in the article TEAM BASED LEARNING AS A STRATEGY OF WORKING IN THE CLASSROOM.</p>
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>
Persistence of Learning Style, Learning Strategy, and Personality Traits
<p>This dataset contains the result of the survey to learning styles, learning strategies, and personality traits.</p> <p>The survey was executed in winter term 2023/24 and summer term 2023 in a German university (OTH Regensburg) during the course "Software Engineering".</p> <p>Examined questionnaires are ILS (learning styles), LIST-K (learning strategies), and BFI-10 (personality traits).</p> <p> </p> <p>The same three questionnaires were asked at two different survey periods three to four months apart while each survey period lasts one to two weeks. Pretest data were examined at the start of the term, while posttest data at the end.</p> <p> </p> <p>Files:</p> <ul> <li>answer_comparison.xlsx</li> <li>persistence.xlsx</li> <li>value_comparison.xlsx</li> </ul> <table> <tbody> <tr> <td>Abbreviation LIST-K</td> <td>Full name</td> </tr> <tr> <td>CS</td> <td>Cognitive strategies</td> </tr> <tr> <td>MCS</td> <td>Metacognitive strategies</td> </tr> <tr> <td>MIR</td> <td>Strategies for managing internal resources</td> </tr> <tr> <td>MER</td> <td>Strategies for managing external resources</td> </tr> <tr> <td>CSORG</td> <td>Cognitive strategies - organizing</td> </tr> <tr> <td>CSELA</td> <td>Cognitive strategies - elaborating</td> </tr> <tr> <td>CSCCH</td> <td>Cognitive strategies - critical checking</td> </tr> <tr> <td>CSREP</td> <td>Cognitive strategies - repeating</td> </tr> <tr> <td>MCSGOP</td> <td>Metacognitive strategies - goals & plans</td> </tr> <tr> <td>MCSMON</td> <td>Metacognitive strategies - monitoring</td> </tr> <tr> <td>MCSREG</td> <td>Metacognitive strategies - regulating</td> </tr> <tr> <td>MIRATT</td> <td>Strategies for managing internal resources - attention</td> </tr> <tr> <td>MIREFF</td> <td>Strategies for managing internal resources - effort</td> </tr> <tr> <td>MIRTIM</td> <td>Strategies for managing internal resources - time</td> </tr> <tr> <td>MERLEE</td> <td>Strategies for managing external resources - learning environment</td> </tr> <tr> <td>MERLIT</td> <td>Strategies for managing external resources - literature research</td> </tr> <tr> <td>MERLWP</td> <td>Strategies for managing external resources - learning with peers</td> </tr> </tbody> </table> <p> </p> <table> <tbody> <tr> <td>Abbreviation ILS</td> <td>Full name</td> </tr> <tr> <td>VV</td> <td>Visual Verbal</td> </tr> <tr> <td>SG</td> <td>Sequential Global</td> </tr> <tr> <td>AR</td> <td>Active Reflective</td> </tr> <tr> <td>SI</td> <td>Sensing Intuitive</td> </tr> </tbody> </table> <p> </p> <table> <tbody> <tr> <td>Abbreviation BFI-10</td> <td>Full name</td> </tr> <tr> <td>A</td> <td>Agreeableness</td> </tr> <tr> <td>C</td> <td>Conscientiousness</td> </tr> <tr> <td>E</td> <td>Extraversion</td> </tr> <tr> <td>N</td> <td>Neuroticism</td> </tr> <tr> <td>O</td> <td>Openness</td> </tr> </tbody> </table> <p> </p> <p> </p> <p>The presented work is supported by the ‘German Federal Ministry of Research, Technology and Space’ (BMFTR) through the granting of the funding project HASKI (FKZ: 16DHBKI035).</p>
All data support the published articel "Loop-optimization of Trichoderma reesei endoglucanases for balancing the activity–stability trade-off through cross-strategy between machine learning and the B-factor analysis"
<p><em>Trichoderma reesei</em> endoglucanases (EGs) have limited industrial applications due to its low thermostability and activity. Here, we aimed to improve the thermostability of EGs from<em> T.reesei</em> without reducing its activity counteracting the activity-stability trade-off. A cross-strategy combination of machine learning and B-factor analysis was used to predict beneficial amino acid substitution in EG loop optimization. Experimental validation showed single-site mutated EG concomitantly improved enzymatic activity and thermal properties by 17.21%–18.06% and 49.85%–62.90%, respectively, compared with wild-type EGs. Furthermore, the mechanism explained mutant variants had lower RMSD values and a more stable overall structure than the wild type. According to this study, EGs loop optimization is crucial for balancing the activity-stability trade-off, which may provide new insights into how loop region function interacts with enzymatic characteristics. Moreover, the cross-strategy between machine learning and B-factor analysis improved superior enzyme activity-stability performance, which integrated structure-dependent and sequence-dependent information.</p>
Apple orchard production estimation using deep learning strategies: a comparison of tracking-by-detection algorithms - SensitivityAnalysis
<p>The dataset "Sensitivity Analysis" consists of image sequences (videos) for apple detection and tracking and its corresponding ground truth. The ground truth is presented in MOT format. This dataset is part of the paper:</p> <p>Villacrés, J., Viscaino, M., Delpiano, J., Vougioukas, S. & Cheein, F. A. (2022). Apple orchard production estimation using deep learning strategies: a comparison of tracking-by-detection algorithms. <em>Computers and Electronics in Agriculture</em>.</p> <p>The article is currently accepted. For a better reference format, please refer to the journal's official website.</p> <p>If you have used the material presented in this data set, please cite the previous article.</p> <p>For more information regarding the dataset, please refer to the paper mentioned below.</p>
FIG. 1 in A novel food preference in the greater short-nosed fruit bat, Cynopterus sphinx: mother-pup interaction a strategy for learning
FIG. 1. Out-flying activity of different groups of C. sphinx pups during novel food preference test. The recorded number of out-flying activity did not significantly vary between the groups of pups. Data were shown as 0 ± SEM
FIG. 2 in A novel food preference in the greater short-nosed fruit bat, Cynopterus sphinx: mother-pup interaction a strategy for learning
FIG. 2. Behavioural responses of C. sphinx pups to the novel food during preference test. Pups feeding attempts (A), and feeding bouts (B) to the known and novel fruits, pups trained with mother showed more number of feeding attempts and bouts towards the novel fruits than other group pups. Data were shown as 0 ± SEM; *** — P <0.001
Priming Through Timing. Using Opposing Strategies to Enhance Motor Learning for Individuals With Parkinson's Disease
ClinicalTrials.gov study NCT03660605. IPD Sharing: NO. Countries: 1. Publications: 1.
Effect of Learning and Coping Strategies in Cardiac Rehabilitation - Group Study
ClinicalTrials.gov study NCT01668394. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Identifying Learning Strategies to Improve Blood Pressure Measurement in Physical Therapy Education Programs
ClinicalTrials.gov study NCT04976452. IPD Sharing: UNDECIDED. Countries: 1. Publications: 23.
Data from: Brain size does not predict learning strategies in a serial reversal learning test
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Data from: From strategy to action: A qualitative study on salient factors influencing knowledge transfer in project-based experiential learning in healthcare organizations in Kenya
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Learning strategies and long-term memory in Asian short-clawed otters (Aonyx cinereus) data
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Current Challenges In School Administration: Developing Strategies For A Resilient Learning Environment
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EXPLORING STRATEGIES TO OVERCOME BARRIERS IN UTILIZING BLENDED LEARNING IN HIGHER EDUCATION.
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QUALITY MANAGEMENT STRATEGIES FOR EDUCATIONAL INSTITUTIONS Promoting excellence in teaching and learning
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INTEGRATION OF TECHNOLOGY IN COLLABORATIVE LEARNING Strategies and impacts on modern education
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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.
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.