most citedIs More Always Better? The Effects of Personal Characteristics and Level of Detail on the Perception of Explanations in a Recommender System

36 citations · 48 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR20231 cited

Justification vs. Transparency: Why and How Visual Explanations in a Scientific Literature Recommender System

Mouadh Guesmi, Mohamed Amine Chatti, Shoeb Joarder +4

Significant attention has been paid to enhancing recommender systems (RS) with explanation facilities to help users make informed decisions and increase trust in and satisfaction w…

cs.AI202336 cited

Is More Always Better? The Effects of Personal Characteristics and Level of Detail on the Perception of Explanations in a Recommender System

Mohamed Amine Chatti, Mouadh Guesmi, Laura Vorgerd +4

Despite the acknowledgment that the perception of explanations may vary considerably between end-users, explainable recommender systems (RS) have traditionally followed a one-size-…

cs.CY2023

Open Learning Analytics: A Systematic Literature Review and Future Perspectives

Arham Muslim, Mohamed Amine Chatti, Mouadh Guesmi

Open Learning Analytics (OLA) is an emerging research area that aims at improving learning efficiency and effectiveness in lifelong learning environments. OLA employs multiple meth…

cs.CY2023

The LAVA Model: Learning Analytics Meets Visual Analytics

Mohamed Amine Chatti, Arham Muslim, Manpriya Guliani +1

Human-Centered learning analytics (HCLA) is an approach that emphasizes the human factors in learning analytics and truly meets user needs. User involvement in all stages of the de…

cs.CY202311 cited

Designing Theory-Driven Analytics-Enhanced Self-Regulated Learning Applications

Mohamed Amine Chatti, Volkan Yücepur, Arham Muslim +2

There is an increased interest in the application of learning analytics (LA) to promote self-regulated learning (SRL). A variety of LA dashboards and indicators were proposed to su…