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Exploring AI-Enabled Test Practice, Affect, and Test Outcomes in Language Assessment

Authors
Jill Burstein,
Ramsey Cardwell,
Ping-Lin Chuang,
Allison Michalowski,
Steven Nydick
Date
Publisher
arXiv
Practice tests for high-stakes assessment are intended to build test familiarity, and reduce construct-irrelevant variance which can interfere with valid score interpretation. Generative AI-driven, automated item generation (AIG) scales the creation of large item banks and multiple practice tests, enabling repeated practice opportunities. We conducted a large-scale observational study (N = 25,969) using the Duolingo English Test (DET) -- a digital, high-stakes, computer-adaptive English language proficiency test to examine how increased access to repeated test practice relates to official DETscores, test-taker affect (e.g., confidence), and score-sharing for university admissions. To our knowledge, this is the first large-scale study exploring the use of AIG-enabled practice tests in high-stakes language assessment. Results showed that taking 1-3 practice tests was associated with better performance (scores), positive affect (e.g., confidence) toward the official DET, and increased likelihood of sharing scores for university admissions for those who also expressed positive affect. Taking more than 3 practice tests was related to lower performance, potentially reflecting washback -- i.e., using the practice test for purposes other than test familiarity, such as language learning or developing test-taking strategies. Findings can inform best practices regarding AI-supported test readiness. Study findings also raise new questions about test-taker preparation behaviors and relationships to test-taker performance, affect, and behaviorial outcomes.
Study at a glance
  • Question: How does repeated AI test practice relate to test scores, student confidence, and university score-sharing?
  • Setting and data: 25,969 test-takers taking the Duolingo English Test, a digital English language proficiency test.
  • Method: Observational study.
Why it matters

Generative AI can scale repeated practice tests to build familiarity for high-stakes assessments. However, no prior large-scale study has explored how AI-enabled practice relates to test scores, test-taker affect, and score-sharing for university admissions.

Key findings
  • Among 25,969 English proficiency test-takers, completing one to three AI-generated practice tests was associated with higher official exam scores and greater confidence.
  • Taking more than three practice tests was related to lower performance on the official exam.
  • Test-takers who practiced one to three times and expressed positive feelings were more likely to share their scores for university admissions.

Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.

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