Predicting Comprehension from Students’ Summaries

International audienceComprehension among young students represents a key component of their formation throughout the learning process. Moreover, scaffolding students as they learn to coherently link information, while organically construct- ing a solid knowledge base, is crucial to students’ development, but requires regular assessment and progress tracking. To this end, our aim is to provide an automated solution for analyzing and predicting students’ comprehension levels by extracting a combination of reading strategies and textual complexity factors from students’ summaries. Building upon previous research and enhancing it by incorporating new heuristics and factors, Support Vector Machine classification models were used to validate our assumptions that automatically identified reading strategies, together with textual complexity indices applied on students’ summaries, represent reliable estimators of comprehension

Reciprocal Teaching: One of the Methods for Poor Comprehenders

Reciprocal teaching is a method which emphasizes the students' cognitive and meta cognitive domains for it covers the structural process of the instruction. The whole elements within the procedure enable the students to choose the strategy, plan, monitor, and evaluate their own activities. Furthermore, the procedures integrated in this method are believed to enhance the students' thinking process. The method, introduced by Palinscar and Brown, belongs to cooperative learning in that the students' thinking process in learning is expressed through a natural dialogue. This method is designed to improve the students' competency in text reading while those students find it difficult to comprehend the content of the text. The method also encourages the students to apply such four strategies as predicting, summarizing, questioning, and clarifying

The SLS-Berlin: Validation of a German Computer-Based Screening Test to Measure Reading Proficiency in Early and Late Adulthood

Reading proficiency, i.e., successfully integrating early word-based information and utilizing this information in later processes of sentence and text comprehension, and its assessment is subject to extensive research. However, screening tests for German adults across the life span are basically non-existent. Therefore, the present article introduces a standardized computerized sentence-based screening measure for German adult readers to assess reading proficiency including norm data from 2,148 participants covering an age range from 16 to 88 years. The test was developed in accordance with the children’s version of the Salzburger LeseScreening (SLS, Wimmer and Mayringer, 2014). The SLS-Berlin has a high reliability and can easily be implemented in any research setting using German language. We present a detailed description of the test and report the distribution of SLS-Berlin scores for the norm sample as well as for two subsamples of younger (below 60 years) and older adults (60 and older). For all three samples, we conducted regression analyses to investigate the relationship between sentence characteristics and SLS-Berlin scores. In a second validation study, SLS-Berlin scores were compared with two (pseudo)word reading tests, a test measuring attention and processing speed and eye-movements recorded during expository text reading. Our results confirm the SLS-Berlin’s sensitivity to capture early word decoding and later text related comprehension processes. The test distinguished very well between skilled and less skilled readers and also within less skilled readers and is therefore a powerful and efficient screening test for German adults to assess interindividual levels of reading proficiency

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

An exploratory study into automated précis grading

Automated writing evaluation is a popular research field, but the main focus has been on evaluating argumentative essays. In this paper, we consider a different genre, namely précis texts. A précis is a written text that provides a coherent summary of main points of a spoken or written text. We present a corpus of English précis texts which all received a grade assigned by a highly-experienced English language teacher and were subsequently annotated following an exhaustive error typology. With this corpus we trained a machine learning model which relies on a number of linguistic, automatic summarization and AWE features. Our results reveal that this model is able to predict the grade of précis texts with only a moderate error margin

Reciprocal Teaching: Improving Students Reading Comprehension

The research question addressed in this project is: How can reciprocal teaching be used to increase comprehension skills with fluent readers in the primary grades? Reading comprehension has been highlighted as a problem among students. While many students can read the words, they lack the proper strategies in order to comprehend the text. This capstone provides current research on fluency and comprehension instruction including the connection between the two. Additionally, research on reciprocal teaching is examined. It will discuss how to incorporate this strategy into classroom instruction to increase comprehension. Included in this capstone is a reciprocal teaching curriculum to be used with third graders. This unit consists of 15 lessons aligned with social studies standards to be used during the literacy bloc

Argument Strength is in the Eye of the Beholder: Audience Effects in Persuasion

Americans spend about a third of their time online, with many participating in online conversations on social and political issues. We hypothesize that social media arguments on such issues may be more engaging and persuasive than traditional media summaries, and that particular types of people may be more or less convinced by particular styles of argument, e.g. emotional arguments may resonate with some personalities while factual arguments resonate with others. We report a set of experiments testing at large scale how audience variables interact with argument style to affect the persuasiveness of an argument, an under-researched topic within natural language processing. We show that belief change is affected by personality factors, with conscientious, open and agreeable people being more convinced by emotional arguments.Comment: European Chapter of the Association for Computational Linguistics (EACL 2017