The Einstellung effect in anagram problem solving: evidence from eye movements
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Einstellung effect is the counterintuitive finding that prior experience or domain-specific knowledge can under some circumstances interfere with problem solving performance. This effect has been demonstrated in several domains of expertise including medicine and chess. In the present study we explored this effect in the context of a simplified anagram problem solving task. Participants solved anagram problems while their eye movements were monitored. Each problem consisted of six letters: a central three-letter string whose letters were part of the solution word, and three additional individual letters. Participants were informed that one of the individual letters was a distractor letter and were asked to find a five-letter solution word. In order to examine the impact of stimulus familiarity on problem solving performance and eye movements, the central letter string was presented either as a familiar three-letter word, or the letters were rearranged to form a three-letter nonword. Replicating the classic Einstellung effect, overall performance was better for nonword than word trials. However, participants' eye movements revealed a more complex pattern of both interference and facilitation as a function of the familiarity of the central letter string. Specifically, word trials resulted in shorter viewing times on the central letter string and longer viewing times on the individual letters than nonword trials. These findings suggest that while participants were better able to encode and maintain the meaningful word stimuli in working memory, they found it more challenging to integrate the individual letters into the central letter string when it was presented as a word.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it