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87 results for “Learning Design”
Functional Optimization of Designer Cardiac Organoids Enabled by Machine Learning Techniques
GEO Series GSE267438. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Dataset used in Design Analytics for Mobile Learning: Scaling up theClassification of Learning Designs based onCognitive and Contextual Elements
<p>The following dataset has been used for the paper entitled "Design Analytics for Mobile Learning: Scaling up theClassification of Learning Designs based onCognitive and Contextual Elements".</p> <p>Abstract</p> <p>This research was triggered by the identified need in literature for large-scale studies about the kind of designs that teachers create for Mobile Learning (m-learning). These studies require analyses of large datasets of learning designs. The common approach followed by researchers when analysing designs has been to manually classify them following high-level pedagogically-guided coding strategies, which demands extensive work. Therefore, the first goal of this paper is to explore the use of Supervised Machine Learning (SML) to automatically classify the textual content of m-learning designs, through pedagogically-relevant classifications, such as the cognitive level demanded by students to carry out specific designed tasks, the phases of inquiry learning represented in the designs, or the role that the situated environment has in them. As not all the SML models are transparent, while often researchers need to understand the behaviour behind them, the second goal of this paper considers the trade-off between models’ performance and interpretability in the context of design analytics for m-learning. To achieve these goals we compiled a dataset of designs deployed through two tools, Avastusrada and Smartzoos. With it, we trained and compared different models and feature extraction techniques. We further optimized andcompared the best-performing and most interpretable algorithms (EstBERT and Logistic Regression) to consider the second goal through an illustrative case. We found that SML can reliably classify designs, with accuracy>0.86and Cohen’s kappa>0.69.</p>
A systematic literature review on design typology of informal learning space in higher education
Open the record for dataset details and reuse information.
Gene expression profile Predictor on chemical Structures (GPS): Deep Learning-based platform to screen and design novel therapeutics
GEO Series GSE291867. Homo sapiens. 27 samples. Type: Expression profiling by high throughput sequencing.
Understanding collective behavior of learning design communities
<p>The following dataset has been used for the paper entitled "Understanding collective behavior of learning design communities".</p> <p>Michos, K., & Hernández-Leo, D. (2016). Understanding collective behavior of learning design communities. In <em>Proceedings of the 11th European Conference on Technology Enhanced Learning, 614-617. </em><a href="https://doi.org/10.1007/978-3-319-45153-4_75">https://doi.org/10.1007/978-3-319-45153-4_75</a></p> <p>Abstract</p> <p>Social computing enables collective actions and social interaction with rich exchange of information. In the context of educators’ networks where they create and share learning design artifacts, little is known about their collective behavior. Learning design tooling focuses on supporting educators (learning designers) in making explicit their design ideas and encourages the development of “learning design communities”. Building on social elements, this paper aims to identify the level of engagement and interactions in three communities using an Integrated Learning Design Environment (ILDE). The results show a relationship between the exploration of different artifacts and creation of content in all the three communities confirming that browsing influence the community's outcomes. Different patterns of interaction suggest specific impact of language and length of support for users.</p>
Supporting awareness in communities of learning design practice
<p>The following dataset has been used for the paper:</p> <p>Michos, K., & Hernández-Leo, D. (2018). Supporting awareness in communities of learning design practice. <em>Computers in Human Behavior, </em>85, 255-270. <a href="https://doi.org/10.1016/j.chb.2018.04.008">https://doi.org/10.1016/j.chb.2018.04.008</a></p> <p>Abstract</p> <p>The field of learning design has extensively studied the use of technology for the authoring of learning activities. However, the social dimension of the learning design process is still underexplored. In this paper, we investigate communities of teachers who used a social learning design platform (ILDE). We seek to understand how community awareness facilitates the learning design activity of teachers in different educational contexts. Following a design-based research methodology, we developed a community awareness dashboard (inILDE) based on the Cultural Historical Activity Theory (CHAT) framework. The dashboard displays the activity of teachers in ILDE, such as their interactions with learning designs, other members, and with supporting learning design tools. Evaluations of the inILDE dashboard were carried out in four educational communities – two secondary schools, a master programme for pre-service teachers, and in a Massive Open Online Course (MOOC) for teachers. The dashboard was perceived to be useful in summarizing the activity of the community and in identifying content and members’ roles. Further, the use of the dashboard increased participants’ interactions such as profile views and teachers showed a willingness to build on the contributions of others. As conclusions of the study, we propose five design principles for supporting awareness in learning design communities, namely community context, practice-related insights, visualizations and representations, tasks and community interests.</p>
A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers
<p>Trained models and basecalled reads.</p>
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.