Publications de Mirko Marras | EPFL Graph Search

Trusting the Explainers: Teacher Validation of Explainable Artificial Intelligence for Course Design

Vinitra Swamy, Tanja Christina Käser Jacober, Mirko Marras, Sijia Du

Deep learning models for learning analytics have become increasingly popular over the last few years; however, these approaches are still not widely adopted in real-world settings, likely due to a lack of trust and transparency. In this paper, we tackle th ...

2023

Evolutionary Clustering of Apprentices' Self- Regulated Learning Behavior in Learning Journals

Paola Mejia Domenzain, Tanja Christina Käser Jacober, Christian Giang, Mirko Marras

Learning journals are increasingly used in vocational education to foster self-regulated learning and reflective learning practices. However, for many apprentices, documenting working experiences is a difficult task. In this paper, we profile apprentices' ...

2022

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

Identifying and Comparing Multi-dimensional Student Profiles Across Flipped Classrooms

Paola Mejia Domenzain, Tanja Christina Käser Jacober, Christian Giang, Mirko Marras

Flipped classroom (FC) courses, where students complete pre-class activities before attending interactive face-to-face sessions, are becoming increasingly popular. However, many students lack the skills, resources, or motivation to effectively engage in pr ...

Springer2022

Guest editorial of the IPM special issue on algorithmic bias and fairness in search and recommendation

Mirko Marras

ELSEVIER SCI LTD2022

Guest Editorial of the FGCS Special Issue on Advances in Intelligent Systems for Online Education

Mirko Marras

ELSEVIER2022

Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs

Vinitra Swamy, Tanja Christina Käser Jacober, Bahar Radmehr, Mirko Marras, Natasa Krco

Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainability of their decisions, especially relevant in human-centric fields. We im ...

2022

Meta Transfer Learning for Early Success Prediction in MOOCs

Vinitra Swamy, Tanja Christina Käser Jacober, Mirko Marras

Despite the increasing popularity of massive open online courses (MOOCs), many suffer from high dropout and low success rates. Early prediction of student success for targeted intervention is therefore essential to ensure no student is left behind in a cou ...

ACM2022

Ripple: Concept-Based Interpretation for Raw Time Series Models in Education

Vinitra Swamy, Tanja Christina Käser Jacober, Mirko Marras, Jibril Albachir Frej

Time series is the most prevalent form of input data for educational prediction tasks. The vast majority of research using time series data focuses on hand-crafted features, designed by experts for predictive performance and interpretability. However, extr ...

2022

Advances in Bias-aware Recommendation on the Web

Mirko Marras

The goal of this tutorial is to provide the WSDM community with recent advances on the assessment and mitigation of data and algorithmic bias in recommender systems. We first introduce conceptual foundations, by presenting the state of the art and describi ...

ASSOC COMPUTING MACHINERY2021