Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

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

Wanqi Zhang, Jiangen He, Marielle Santos

TL;DR

This study tackles the challenge of reconciling psychological safety with instructional coaching in robotic interview training by conducting a three-phase, within-subject design with $N=8$ participants. It identifies a Safety--Guidance Gap in purely empathetic PCT coaching ($d=3.27$) and a Scaffolding Paradox from rigid feedback, then resolves these tensions with an Agency-Driven Interaction Layer that uses a conditional feedback loop and streamlined empathy to balance affective support and instructional challenge. The resulting Adaptive Scaffolding Ecosystem dynamically tunes affective tone and intervention intensity based on user agency, achieving significant reductions in social and communication anxiety while preserving safety and perceived warmth; participants report high usefulness and readiness for human interviews, despite some preference for deeper personalization. These findings offer a practical blueprint for next-generation robotic coaches that adaptively navigate autonomy, coaching, and emotional safety in high-stakes preparatory contexts, with potential to generalize beyond interview training.

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.

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

TL;DR

This study tackles the challenge of reconciling psychological safety with instructional coaching in robotic interview training by conducting a three-phase, within-subject design with participants. It identifies a Safety--Guidance Gap in purely empathetic PCT coaching () and a Scaffolding Paradox from rigid feedback, then resolves these tensions with an Agency-Driven Interaction Layer that uses a conditional feedback loop and streamlined empathy to balance affective support and instructional challenge. The resulting Adaptive Scaffolding Ecosystem dynamically tunes affective tone and intervention intensity based on user agency, achieving significant reductions in social and communication anxiety while preserving safety and perceived warmth; participants report high usefulness and readiness for human interviews, despite some preference for deeper personalization. These findings offer a practical blueprint for next-generation robotic coaches that adaptively navigate autonomy, coaching, and emotional safety in high-stakes preparatory contexts, with potential to generalize beyond interview training.

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.
Paper Structure (24 sections)

This paper contains 24 sections.

Table of Contents

  1. Introduction
  2. System Implementation and Methodology
  3. System Architecture
  4. Iterative Design Study Design
  5. Participants
  6. Data Collection and Analysis
  7. Iterative Design and Findings
  8. Phase I: The Safety--Guidance Gap
  9. Findings
  10. Phase II: The Scaffolding Paradox
  11. Findings: Critical Design Tensions
  12. Phase III: The Interaction Layer: Agency-Driven Mode
  13. The Final Version: The Agency-Driven Interaction Layer
  14. Phase 3 Testing and Analysis
  15. Findings: Agency as an Anxiety Buffer
  16. ...and 9 more sections