2 Search Results for "Huber, Anja"

Document
DOI: 10.4230/OASIcs.SLATE.2025.1
From Prediction to Precision: Leveraging LLMs for Equitable and Data-Driven Writing Placement in Developmental Education

Authors: Miguel Da Corte and Jorge Baptista

Published in: OASIcs, Volume 135, 14th Symposium on Languages, Applications and Technologies (SLATE 2025)

Abstract
Accurate text classification and placement remain challenges in U.S. higher education, with traditional automated systems like Accuplacer functioning as "black-box" models with limited assessment transparency. This study evaluates Large Language Models (LLMs) as complementary placement tools by comparing their classification performance against a human-rated gold standard and Accuplacer. A 450-essay corpus was classified using Claude, Gemini, GPT-3.5-turbo, and GPT-4o across four prompting strategies: Zero-shot, Few-shot, Enhanced, and Enhanced+ (definitions with examples). Two classification approaches were tested: (i) a 1-step, 3 class classification task, distinguishing DevEd Level 1, DevEd Level 2, and College-level texts in one single run; and (ii) a 2-step classification task, first separating College vs. Non-College texts before further classifying Non-College texts into DevEd sublevels. The results show that structured prompt refinement improves the precision of LLMs' classification, with Claude Enhanced + achieving 62.22% precision (1 step) and Gemini Enhanced + reaching 69.33% (2 step), both surpassing Accuplacer (58.22%). Gemini and Claude also demonstrated strong correlation with human ratings, with Claude achieving the highest Pearson scores (ρ = 0.75; 1-step, ρ = 0.73; 2-step) vs. Accuplacer (ρ = 0.67). While LLMs show promise for DevEd placement, their precision remains a work in progress, highlighting the need for further refinement and safeguards to ensure ethical and equitable placement.
Cite as

Miguel Da Corte and Jorge Baptista. From Prediction to Precision: Leveraging LLMs for Equitable and Data-Driven Writing Placement in Developmental Education. In 14th Symposium on Languages, Applications and Technologies (SLATE 2025). Open Access Series in Informatics (OASIcs), Volume 135, pp. 1:1-1:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{dacorte_et_al:OASIcs.SLATE.2025.1,
  author =	{Da Corte, Miguel and Baptista, Jorge},
  title =	{{From Prediction to Precision: Leveraging LLMs for Equitable and Data-Driven Writing Placement in Developmental Education}},
  booktitle =	{14th Symposium on Languages, Applications and Technologies (SLATE 2025)},
  pages =	{1:1--1:18},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-387-4},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{135},
  editor =	{Baptista, Jorge and Barateiro, Jos\'{e}},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2025.1},
  URN =		{urn:nbn:de:0030-drops-236817},
  doi =		{10.4230/OASIcs.SLATE.2025.1},
  annote =	{Keywords: Large Language Models (LLMs), Developmental Education (DevEd), writing assessment, text classification, English writing proficiency}
}
Document
DOI: 10.4230/LIPIcs.ICALP.2018.154
Efficient Black-Box Reductions for Separable Cost Sharing

Authors: Tobias Harks, Martin Hoefer, Anja Huber, and Manuel Surek

Published in: LIPIcs, Volume 107, 45th International Colloquium on Automata, Languages, and Programming (ICALP 2018)

Abstract
In cost sharing games with delays, a set of agents jointly uses a finite subset of resources. Each resource has a fixed cost that has to be shared by the players, and each agent has a non-shareable player-specific delay for each resource. A prominent example is uncapacitated facility location (UFL), where facilities need to be opened (at a shareable cost) and clients want to connect to opened facilities. Each client pays a cost share and his non-shareable physical connection cost. Given any profile of subsets used by the agents, a separable cost sharing protocol determines cost shares that satisfy budget balance on every resource and separability over the resources. Moreover, a separable protocol guarantees existence of pure Nash equilibria in the induced strategic game for the agents. In this paper, we study separable cost sharing protocols in several general combinatorial domains. We provide black-box reductions to reduce the design of a separable cost sharing protocol to the design of an approximation algorithm for the underlying cost minimization problem. In this way, we obtain new separable cost sharing protocols in games based on arbitrary player-specific matroids, single-source connection games without delays, and connection games on n-series-parallel graphs with delays. All these reductions are efficiently computable - given an initial allocation profile, we obtain a profile of no larger cost and separable cost shares turning the profile into a pure Nash equilibrium. Hence, in these domains any approximation algorithm can be used to obtain a separable cost sharing protocol with a price of stability bounded by the approximation factor.
Cite as

Tobias Harks, Martin Hoefer, Anja Huber, and Manuel Surek. Efficient Black-Box Reductions for Separable Cost Sharing. In 45th International Colloquium on Automata, Languages, and Programming (ICALP 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 107, pp. 154:1-154:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{harks_et_al:LIPIcs.ICALP.2018.154,
  author =	{Harks, Tobias and Hoefer, Martin and Huber, Anja and Surek, Manuel},
  title =	{{Efficient Black-Box Reductions for Separable Cost Sharing}},
  booktitle =	{45th International Colloquium on Automata, Languages, and Programming (ICALP 2018)},
  pages =	{154:1--154:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-076-7},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{107},
  editor =	{Chatzigiannakis, Ioannis and Kaklamanis, Christos and Marx, D\'{a}niel and Sannella, Donald},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2018.154},
  URN =		{urn:nbn:de:0030-drops-91587},
  doi =		{10.4230/LIPIcs.ICALP.2018.154},
  annote =	{Keywords: Cost Sharing, Price of Stability, Matroids, Connection Games}
}
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