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Learning Analytics for Adaptive and Self-Improving Learning Environments for Inductive Teaching

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Temporally Coherent Clustering of Student Data

The extraction of student behavior is an important task in educational data mining. A common approach to detect similar behavior patterns is to cluster sequential data. Standard approaches identify clusters at each time step separately and typically show l ...

EDM2016

Smart Environments and Analytics on Video-Based Learning

Lukasz Kidzinski

The International Workshop of Smart Environments and Analytics on Video-Based Learning (SE@VBL) aims to connect research efforts on Video-Based Learning with Smart Environments and Analytics to create synergies between these fields. The main objective is t ...

Assoc Computing Machinery2016

Wiki-LDA: A Mixed-Method Approach for Effective Interest Mining on Twitter Data

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Learning analytics (LA) and Educational data mining (EDM) have emerged as promising technology-enhanced learning (TEL) research areas in recent years. Both areas deal with the development of methods that harness educational data sets to support the learnin ...

Scitepress2016

Teaching Analytics: Towards Automatic Extraction of Orchestration Graphs Using Wearable Sensors

Pierre Dillenbourg, Maria Jesus Rodriguez Triana, Kshitij Sharma, Luis Pablo Prieto Santos

"Teaching analytics" is the application of learning analytics techniques to understand teaching and learning processes, and eventually enable supportive interventions. However, in the case of (often, half-improvised) teaching in face-to-face classrooms, su ...

Assoc Computing Machinery2016

Personal Learning with Social Media

Na Li

Social media platforms are increasingly used in recent years to support learning activities, especially for the construction of activity- and learner-centric personal learning environments (PLEs). This thesis investigates the solutions to four essential de ...

EPFL2015

Induction for SMT Solvers

Viktor Kuncak, Andrew Joseph Reynolds

Satisfiability modulo theory solvers are increasingly being used to solve quantified formulas over structures such as integers and term algebras. Quantifier instantiation combined with ground decision procedure alone is insufficient to prove many formulas ...

Springer-Verlag Berlin2015

Adaptation, Learning, and Optimization over Networks

Ali H. Sayed

This work deals with the topic of information processing over graphs. The presentation is largely self-contained and covers results that relate to the analysis and design of multi-agent networks for the distributed solution of optimization, adaptation, and ...

NOW Publishers2014

Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

Frank Grégoire Jean de Morsier

The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...

EPFL2014

Scalable Collaborative Bayesian Preference Learning

Matthias Seeger, Mohammad Emtiyaz Khan, Young Jun Ko

Learning about users’ utilities from preference, discrete choice or implicit feedback data is of integral importance in e-commerce, targeted advertising and web search. Due to the sparsity and diffuse nature of data, Bayesian approaches hold much promise, ...

2014

On Induction for SMT Solvers

Viktor Kuncak, Andrew Joseph Reynolds

2014