Bridging Psychological Safety and Skill Guidance: An Adaptive Robotic Interview Coach

2026-01-15

AI Summary

This study addresses the dual challenges of the “safety–guidance gap” and the “scaffolding paradox” faced by social robots in simultaneously alleviating interview anxiety and enhancing interview skills. Through a three-phase iterative design, the authors propose an Adaptive Scaffolding Ecosystem framework that integrates person-centered therapy, cognitive load theory, and user feedback analysis to establish a dynamic interaction mechanism centered on user agency. This approach enables real-time balancing between emotional support and instructional challenge. Empirical evaluation demonstrates that the system significantly improves users’ psychological safety, engagement, and learning outcomes during mock interviews, offering a novel paradigm for adaptive design in intelligent tutoring robots.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Natural Language Processing: Safety and Robustness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Social robots hold promise for reducing job interview anxiety, yet designing agents that provide both psychological safety and instructional guidance remains challenging. Through a three-phase iterative design study (N = 8), we empirically mapped this tension. Phase I revealed a"Safety-Guidance Gap": while a Person-Centered Therapy (PCT) robot established safety (d = 3.27), users felt insufficiently coached. Phase II identified a"Scaffolding Paradox": rigid feedback caused cognitive overload, while delayed feedback lacked specificity. In Phase III, we resolved these tensions by developing an Agency-Driven Interaction Layer. Synthesizing our empirical findings, we propose the Adaptive Scaffolding Ecosystem, a conceptual framework that redefines robotic coaching not as a static script, but as a dynamic balance between affective support and instructional challenge, mediated by user agency.

Problem

• psychological safety
• skill guidance
• social robots
• job interview anxiety
• adaptive coaching

Innovation

• Adaptive Scaffolding
• Psychological Safety
• Agency-Driven Interaction
• Social Robotics
• Instructional Guidance