Semi-Markov model for simulating MOOC students

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Publications associées (31)

Integrated Model for Comprehensive Digital Education Platforms

Denis Gillet, Isabelle Barbara Marie-Hélène Cardia, Kim Lan Phan Hoang, Maria Jesus Rodriguez Triana, Juan Carlos Farah

The trend towards generalized blended and active learning approaches in engineering education is redefining the requirements and the deployment schemes for digital education platforms. This paper presents a quadriptych techno- pedagogical model highlightin ...

IEEE2022

Supporting Developers in Creating Web Apps for Education via an App Development Framework

Denis Gillet, Sandy Ingram, Juan Carlos Farah

As more educational activities are conducted online, the need for interactive applications (apps) that can effectively support educators in their practice is increasing. These apps are often created by web developers or by researchers, educators, and even ...

Editorial Universitat Politècnica de València2022

Single photon detection with amorphous silicon-based microchannel plates: A Monte Carlo model

Christophe Ballif, Nicolas Würsch, Jonathan Emanuel Thomet, Janina Christine Isabelle Löffler, Samira Alexandra Frey

Microchannel plates based on amorphous silicon have the inherent capability to overcome the existing spatial and temporal resolution limitations of single photon detectors. A Monte Carlo model-based study is presented here that serves to exploit their full ...

2022

Re-focusing explainability in medicine

Using artificial intelligence to improve patient care is a cutting-edge methodology, but its implementation in clinical routine has been limited due to significant concerns about understanding its behavior. One major barrier is the explainability dilemma a ...

2022

Hiding in Plain Sight: The Issue of Hidden Variables

Yimon Aye, Mahdi Assari

Here we discuss "hidden variables", which are typically introduced during an experiment as a consequence of the application of two independent variables together to create a stimulus. With increased sophistication in modern chemical biology tools and relat ...

AMER CHEMICAL SOC2022

Distributionally Robust Optimization with Markovian Data

Daniel Kuhn, Tobias Sutter, Mengmeng Li

We study a stochastic program where the probability distribution of the uncertain problem parameters is unknown and only indirectly observed via finitely many correlated samples generated by an unknown Markov chain with d states. We propose a data-driven d ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

Fast Bayesian estimation of spatial count data models

Prateek Bansal, Rico Krüger

Spatial count data models are used to explain and predict the frequency of phenomena such as traffic accidents in geographically distinct entities such as census tracts or road segments. These models are typically estimated using Bayesian Markov chain Mont ...

2021

Unbiased Monte Carlo cluster updates with autoregressive neural networks

Giuseppe Carleo, Dian Wu, Riccardo Rossi

Efficient sampling of complex high-dimensional probability distributions is a central task in computational science. Machine learning methods like autoregressive neural networks, used with Markov chain Monte Carlo sampling, provide good approximations to s ...

AMER PHYSICAL SOC2021

Equality of Learning Opportunity via Individual Fairness in Personalized Recommendations

Mirko Marras

Online education platforms play an increasingly important role in mediating the success of individuals' careers. Therefore, while building overlying content recommendation services, it becomes essential to guarantee that learners are provided with equal re ...

SPRINGER2022

An End-to-End Data Pipeline for Managing Learning Analytics

Denis Gillet, Sandy Ingram, Joana Catarina Soares Machado, Juan Carlos Farah

Despite the importance of learning analytics in digital education, there is limited support for researchers in education to generate, access, and share experimental data while complying with ethical and privacy legislation. We propose a set of related tool ...

2021

L2D 2021: First International Workshop on Enabling Data-Driven Decisions from Learning on the Web

Tanja Christina Käser Jacober, Mirko Marras

By offering courses and resources, learning platforms on the Web have been attracting lots of participants, and the interactions with these systems have generated a vast amount of learning-related data. Their collection, processing and analysis have promot ...

Association for Computing Machinery2021

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