Sökning: "Learning analytics"

Visar resultat 1 - 5 av 57 avhandlingar innehållade orden Learning analytics.

1. 1. Visual Analytics for Explainable and Trustworthy Machine Learning

   Författare :Angelos Chatzimparmpas; Andreas Kerren; Rafael M. Martins; Ilir Jusufi; Alex Endert; Linnéuniversitetet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; visualization; interaction; visual analytics; explainable machine learning; XAI; trustworthy machine learning; ensemble learning; dimensionality reduction; supervised learning; unsupervised learning; ML; AI; tabular data; visualisering; interaktion; visuell analys; förklarlig maskininlärning; XAI; pålitlig maskininlärning; ensembleinlärning; dimensionesreducering; övervakad inlärning; oövervakad inlärning; ML; AI; tabelldata; Computer Science; Datavetenskap; Informations- och programvisualisering; Information and software visualization;

   Sammanfattning : The deployment of artificial intelligence solutions and machine learning research has exploded in popularity in recent years, with numerous types of models proposed to interpret and predict patterns and trends in data from diverse disciplines. However, as the complexity of these models grows, it becomes increasingly difficult for users to evaluate and rely on the model results, since their inner workings are mostly hidden in black boxes, which are difficult to trust in critical decision-making scenarios. LÄS MER

3. 2. Using Learning Analytics to Understand and Support Collaborative Learning

   Författare :Mohammed Saqr; Uno Fors; Jalal Nouri; Barbara Wasson; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Learning analytics; Social Network Analysis; Collaborative Learning; Medical Education; Interaction Analysis; Machine Learning; Information Society; informationssamhället;

   Sammanfattning : Learning analytics (LA) is a rapidly evolving research discipline that uses insights generated from data analysis to support learners and optimize both the learning process and learning environment. LA is driven by the availability of massive data records regarding learners, the revolutionary development of big data methods, cheaper and faster hardware, and the successful implementation of analytics in other domains. LÄS MER

4. 3. Advancing Clinical Decision Support Using Machine Learning & the Internet of Medical Things : Enhancing COVID-19 & Early Sepsis Detection

   Författare :Mahbub Ul Alam; Rahim Rahmani; Jaakko Hollmén; Sadok Ben Yahia; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Internet of Medical Things; Patient-Centric Healthcare; Clinical Decision Support System; Predictive Modeling in Healthcare; Health Informatics; Healthcare analytics; COVID-19; Sepsis; COVID-19 Detection; Early Sepsis Detection; Lung Segmentation Detection; Medical Data Annotation Scarcity; Medical Data Sparsity; Medical Data Heterogeneity; Medical Data Security Privacy; Practical Usability Enhancement; Low-End Device Adaptability; Medical Significance; Interpretability; Visualization; LIME; SHAP; Grad-CAM; LRP; Electronic Health Records; Thermal Image; Tabular Medical Data; Chest X-ray; Machine Learning; Deep Learning; Federated Learning; Semi-Supervised Machine Learning; Multi-Task Learning; Transfer Learning; Multi-Modality; Natural Language Processing; ClinicalBERT; GAN; data- och systemvetenskap; Computer and Systems Sciences;

   Sammanfattning : This thesis presents a critical examination of the positive impact of Machine Learning (ML) and the Internet of Medical Things (IoMT) for advancing the Clinical Decision Support System (CDSS) in the context of COVID-19 and early sepsis detection.It emphasizes the transition towards patient-centric healthcare systems, which necessitate personalized and participatory care—a transition that could be facilitated by these emerging fields. LÄS MER

5. 4. Visual Storytelling Interacting in School : Learning Conditions in the Social Science Classroom

   Författare :Linnéa Stenliden; Jörgen Nissen; Eva Reimers; Mikael Jern; Monika Vinterek; Linköpings universitet; []
   Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Data visualization; geovisual analytics; visual storytelling; interaction; learning activities; learning conditions; social science education; Data visualisering; geovisual analytics; visual storytelling; interaktion; läraktivitet; lärandevillkor; samhällsorienterande undervisning;

   Sammanfattning : The aim of this compilation thesis is to understand how technology for visual storytelling can be shaped and used in relation to social science education in primary school, but also how social dimensions, technical and other matters create emerging learning conditions in such an educational setting. The visual storytelling technology introduced and used in the study is ‘the Statistics eXplorer platform, a geovisual analytics. LÄS MER

7. 5. Artificial Intelligence-Based Characterization and Classification Methods for Power Quality Data Analytics

   Författare :Azam Bagheri; Math Bollen; Surya Santoso; Luleå tekniska universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Power System; power Quality; Voltage Dip; Big Data; Deep Learning; Machine Learning; Active Learning; Consensus Contriol; Electric Power Engineering; Elkraftteknik;

   Sammanfattning : One of the important developments in the electric power system is the fast increasing amount of data. An example of such data is formed by the voltages and currents coming from power-quality measurements. LÄS MER