PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 3, 2026Psicothema3 citationsOpen Access

Using Artificial Intelligence in Test Construction: A Practical Guide

View Full Paper
JSJavier Suárez‐ÁlvarezUniversity of Massachusetts AmherstQHQiwei HeGeorgetown UniversityNGNigel GuenoleUniversidad de Londres

Key Points

  • Validity, reliability, and fairness are critical for effective test development using artificial intelligence.
  • Specific guidelines link each challenge to practices that promote responsible implementation of AI in tests.
  • The approach emphasizes the importance of calibration to maintain quality in AI-generated tests.
  • Implementing these practical guidelines can improve overall test integrity and stakeholder confidence.

Abstract

We propose a practical guide for using generative AI in test development and calibration, targeting challenges related to validity, reliability, and fairness by linking each issue to specific guidelines that promote responsible, effective implementation.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Suárez‐Álvarez et al. (2026) studied this question.

synapsesocial.com/papers/69a7661bbadf0bb9e87dbb92https://doi.org/10.70478/psicothema.2026.38.01
Ask AI
Helpful
Bookmark
Share
View Full Paper