mlsanityData to 14 Oct 2026

Designing Conversational AI to Support Think-Aloud Practice in Technical Interview Preparation for CS Students

arXiv 2507.14418 ↗First posted 19 Jul 2025cs.HC cs.AIcited by 2

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

One challenge in technical interviews is the think-aloud process, where candidates verbalize their thought processes while solving coding tasks. Despite its importance, opportunities for structured practice remain limited. Conversational AI offers potential assistance, but limited research explores user perceptions of its role in think-aloud practice. To address this gap, we conducted a study with 17 participants using an LLM-based technical interview practice tool. Participants valued AI's role in simulation, feedback, and learning from generated examples. Key design recommendations include promoting social presence in conversational AI for technical interview simulation, providing feedback beyond verbal content analysis, and enabling crowdsourced think-aloud examples through human-AI collaboration. Beyond feature design, we examined broader considerations, including intersectional challenges and potential strategies to address them, how AI-driven interview preparation could promote equitable learning in computing careers, and the need to rethink AI's role in interview practice by suggesting a research direction that integrates human-AI collaboration.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 18 of its 130 references that are in the map. First posted on arXiv 19 Jul 2025.

Builds on

18 of 130 references.

References · 18

  1. 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,601
  2. 2022Discovering Language Model Behaviors with Model-Written Evaluationscited by 836
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6 more
  1. 2015Automated Analysis and Prediction of Job Interview Performancecited by 15
  2. 2023Exploring the Role of AI Assistants in Computer Science Education: Methods, Implications, and Instructor Perspectivescited by 12
  3. 2023EZInterviewer: To Improve Job Interview Performance with Mock Interview Generatorcited by 6
  4. 2024Conversate: Supporting Reflective Learning in Interview Practice Through Interactive Simulation and Dialogic Feedbackcited by 5
  5. 2024VIVID: Human-AI Collaborative Authoring of Vicarious Dialogues from Lecture Videoscited by 3
  6. 2025How do Software Engineering Candidates Prepare for Technical Interviews?cited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025Evaluating LLMs for Career Guidance: Comparative Analysis of Computing Competency Recommendations Across Ten African Countriescited by 1
  2. 2026Human-Human-AI Triadic Programming: Uncovering the Role of AI Agent and the Value of Human Partner in Collaborative Learningcited by 1

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