Reading in the Disciplines: The Challenges of Adolescent Literacy

A companion report to Carnegie's Time to Act, focuses on the specific skills and literacy support needed for reading in academic subject areas in higher grades. Outlines strategies for teaching content knowledge and reading strategies together

Teaching Shakespeare in the 21St Century: a Guide for Secondary Educators

This project explains how the integration of innovative methods for teaching Shakespeare\u27s works, and the works of other canonical authors, can increase motivation and achievement among 21st century students in the secondary classroom. It provides a rationale for the continued use of Shakespeare\u27s works as part of the secondary curriculum, as well as an overview of common problems associated with teaching Shakespeare today. Issues addressed include cross generational, sociocultural translation and modern-day relevance, as well as assessment authenticity. The project consists of a research paper and unit guide constructed for the purpose of bridging the gap that often exists between modern secondary students and the traditional, secondary English curriculum; both pieces contain explicit examples of research based activities and assessments that address these issues

Answering Complex Questions by Joining Multi-Document Evidence with Quasi Knowledge Graphs

Direct answering of questions that involve multiple entities and relations is a challenge for text-based QA. This problem is most pronounced when answers can be found only by joining evidence from multiple documents. Curated knowledge graphs (KGs) may yield good answers, but are limited by their inherent incompleteness and potential staleness. This paper presents QUEST, a method that can answer complex questions directly from textual sources on-the-fly, by computing similarity joins over partial results from different documents. Our method is completely unsupervised, avoiding training-data bottlenecks and being able to cope with rapidly evolving ad hoc topics and formulation style in user questions. QUEST builds a noisy quasi KG with node and edge weights, consisting of dynamically retrieved entity names and relational phrases. It augments this graph with types and semantic alignments, and computes the best answers by an algorithm for Group Steiner Trees. We evaluate QUEST on benchmarks of complex questions, and show that it substantially outperforms state-of-the-art baselines

What’s the Meaning of Superhuman Performance in Today’s NLU?

In the last five years, there has been a significant focus in Natural Language Processing (NLP) on developing larger Pretrained Language Models (PLMs) and introducing benchmarks such as SuperGLUE and SQuAD to measure their abilities in language understanding, reasoning, and reading comprehension. These PLMs have achieved impressive results on these benchmarks, even surpassing human performance in some cases. This has led to claims of superhuman capabilities and the provocative idea that certain tasks have been solved. In this position paper, we take a critical look at these claims and ask whether PLMs truly have superhuman abilities and what the current benchmarks are really evaluating. We show that these benchmarks have serious limitations affecting the comparison between humans and PLMs and provide recommendations for fairer and more transparent benchmarks.</p