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Research on Automated Essay Scoring has become increasing important because it serves as a method for evaluating students’ written responses at scale. Scalable methods for scoring written responses are needed as students migrate to online learning environments resulting in the need to evaluate large numbers of written-response assessments. The purpose of this study is to describe and evaluate three active learning methods that can be used to minimize the number of essays that must be scored by human raters while still providing the data needed to train a modern Automated Essay Scoring system. The three active learning methods are the uncertainty-based, the topological-based, and the hybrid method. These three methods were used to select essays included in the Automated Student Assessment Prize competition that were then classified using a scoring model that was trained with the bidirectional encoder representations from a transformer language model. All three active learning methods produced strong results, with the topological-based method producing the most efficient classification. Growth rate accuracy was also evaluated. The active learning methods produced different levels of efficiency under different sample size allocations but, overall, all three methods were highly efficient and produced classifications that were similar to one another. 相似文献
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David Nicholas Cherifa Boukacem-Zeghmouri Blanca Rodríguez-Bravo Eti Herman Abdullah Abrizah David Clark Galina Serbina David Sims Marzena Świgoń Jie Xu Anthony Watkinson Hamid R. Jamali Carol Tenopir Suzie Allard 《Learned Publishing》2023,36(2):319-322
- 170 early career researchers interviewed three times over 2 years, have uniquely contributed towards a stress test of scholarly communications and cracks have been identified.
- The perfect storm created by the convergence of millennial values and the pandemic appears to have fast-forwarded the cracking process, perhaps, for the good.
- The cracks in question are: (1) peer review; (2) reputational assessment; (3) unethical/questionable practices; (4) collaboration; (5) networking.