The Corpus as Tutor: Data-driven Persuasive Language Learning
What it is about
The paper describes PLOTLearner and its successor Bible Online Learner, which generate Hebrew exercises directly from the annotated ETCBC database (Emdros objects: word, phrase, clause, with features). The design rests on Fogg's persuasive technology: an "ability" branch (reduction to quizzes, tunnelling through a curriculum, tailoring to the learner) and a "motivation" branch (tests, monitoring by others, self-monitoring). It replaces present–practice–produce teaching with a loop: the learner explores the corpus, practises on generated exercises, and a learning journey logs every answer, its time, and every wrong answer; exercises with the highest error rate are recommended for more practice. No learning outcomes are measured in the paper.
Ideas
- I1. Generate Torah course exercises from the trees rather than writing them: pick a feature (binyan, stem, person, suffix, relation) and real verses that show it, the answer being the tree's value.
- I2. Log every learner answer with time and error, and order the next exercises by error rate per feature; the same log tells which features the SLM itself gets wrong when it is the learner.
- I3. Graded progression ("tunnelling") by feature frequency in the Torah: first the commonest forms (wayyiqtol 3ms, the article, אֵת), then the rarer.
For Mova
I1 and I3 apply to the Torah course (world/data/school/torah/*.lesson, 13. Biblical Hebrew in Mova: the tools §10). I2 is the course's error log and a measure of the SLM on Hebrew forms, read per feature.
Cite
@inproceedings{winthernielsen2017corpus,
title = {{The Corpus as Tutor: Data-driven Persuasive Language Learning}},
author = {Winther-Nielsen, Nicolai},
booktitle = {HIPHIL Novum 4},
year = {2017},
doi = {10.7146/hn.v4i1.142165},
url = {https://doi.org/10.7146/hn.v4i1.142165}
}References
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