Samar Sallam

University of British Columbia

Papers

2

Total Citations

10

H-Index

2

About

Samar Sallam is a rising researcher at the intersection of child-computer interaction and educational technology, with a primary focus on the safe and ethical integration of social robots and conversational AI in learning environments. Her work critically examines how young users perceive and interact with autonomous systems, particularly in sensitive contexts such as receiving negative feedback. In her most-cited study (2024, 8 citations), Sallam investigates the concerns of parents and educators regarding the pedagogical use of AI-equipped social robots, highlighting the gap between technological novelty and long-term safety. Her 2023 paper explores a nuanced challenge: how social robots can deliver negative feedback to children without damaging the relational bond or causing social distance. This work contributes to the growing field of affective computing and human-robot interaction by addressing the delicate balance between effective guidance and emotional well-being. Sallam’s research is notable for its child-centered approach, emphasizing user trust and ethical design. As the deployment of social robots in classrooms accelerates, her findings offer critical insights for developers, educators, and policymakers aiming to create supportive, responsible AI companions for children.

Research Focus

Key Achievements

2
H-Index
2
Papers
10
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Parent and Educator Concerns on the Pedagogical Use of AI-Equipped Social Robots
8 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: University of British Columbia

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago