The Abacus: Teachers’ Preparation and Beliefs about their Abacus Preservice Preparation
Bibliographic record
Abstract
Introduction This article reports on a study of 196 teachers who shared their experiences and opinions related to how they were taught to use the Cranmer abacus. Methods In February and March 2012, the participants completed an online survey to gather information about their preparation in using and beliefs about computation with the Cranmer abacus. Results The participants resided in both the United States and Canada and had various years of experience. The majority (n = 112) reported learning computation with an abacus in their personnel preparation programs. The participants rated their level of agreement with belief statements. Statements with the highest level of agreement included one that indicated that when sighted individuals use pencil and paper for computation, an individual with a visual impairment should be allowed to use an abacus, and another that an abacus is an accessible and inexpensive tool. Discussion The self-report data from 196 participants indicated that computation with an abacus is taught in university programs, although there is variability in what computational skills are taught and what methods are used. There was a higher level of agreement with statements that implied the positive attributes of using an abacus for computation than with those that implied negative attributes (for example, the abacus is obsolete). Implications for practitioners University preparation programs are continuing to teach some level of abacus computation skills to their students. It is not clear if the level of instruction is adequate. Further studies are warranted that examine what pre- and in-service teachers of students with visual impairments are learning and how they are learning in their university preparation programs and through other methods.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".