Beata Beigman Klebanov
Biographic Data
| ID | 4104466 |
|---|---|
| NAME | Beata Beigman Klebanov |
| GIVEN NAMES | Beata Beigman |
| FAMILY NAME | Klebanov |
| SIGNATURE | KLEBANOV B B |
| AFFILIATIONS | Educational Testing Service |
| ORCID | 0000-0002-5009-3992 |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 22 |
| WORKS AS AUTHOR | 11 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2008 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 3 |
Toward stealth assessment of reading comprehension
Reading comprehension is a critical skill that enables us to use text for learning, work, and pleasure. It is typically assessed through multiple choice or open-ended questions based on the text. In this article, we explore a novel machine-learning approach to assessing comprehension based on the properties of the text and of its oral reading that are known to be connected to comprehension. This method of assessing comprehension can potentially f…
Stealth assessment of oral reading fluency during interactive book reading
Oral reading fluency (ORF) assessments are widely used to predict students’ reading proficiency and signal the need for additional instruction. Standardized ORF assessments require substantial resources to develop and take time from instruction to administer; they may also increase test anxiety. To address these concerns, we explored stealth assessment of ORF during book reading. Eighty students (grades 4–5) engaged in interactive book reading th…
Unveiling Patterns of Interaction With Automated Feedback in Writing Mentor and Their Relationships With Use Goals and Writing Outcomes
How Much Should I Read? An Analysis of Word Learning Opportunities in Children's Novels
With only about a third of students in US public schools achieving the NAEP Proficient level, many educators believe students are not getting enough reading practice. However, how much reading practice is enough? This study quantifies the relationship between the amount of book reading and the expected number of words learned. We collected 45 children's novels, M(Lexile) = 994 L, or Grade 6, and assembled a corpus of 3.2 million words. When readi…
Beyond text complexity
Advancing the validity argument for standardized writing tests using quantitative rhetorical analysis
Essay writing is a common type of constructed-response task used frequently in standardized writing assessments. However, the impromptu timed nature of the essay writing tests has drawn increasing criticism for the lack of authenticity for real-world writing in classroom and workplace settings. The goal of this paper is to contribute evidence to a validity argument for standardized writing tests. Using measurements of distances between rhetorical…
Associative lexical cohesion as a factor in text complexity
In this paper we present an application of associative lexical cohesion to the analysis of text complexity as determined by expert-assigned US school grade levels. Lexical cohesion in a text is represented as a distribution of pairwise positive normalized mutual information values. Our quantitative measure of lexical cohesion is Lexical Tightness (LT), computed as average of such values per text. It represents the degree to which a text tends to …
The “image bite,” political language, and the public/private divide
Voice-overs with muted images, often known as the “image bite,” have become an increasingly used but understudied format of political language by the television news media. Because the media can use images to fit many contexts and purposes of commentary, the media images are susceptible to continuous de-contextualization and re-contextualization. Drawing from theories of feminist critical discourse analysis and gender performance as well as schol…
From Annotator Agreement to Noise Models
This article discusses the transition from annotated data to a gold standard, that is, a subset that is sufficiently noise-free with high confidence. Unless appropriately reinterpreted, agreement coefficients do not indicate the quality of the data set as a benchmarking resource: High overall agreement is neither sufficient nor necessary to distill some amount of highly reliable data from the annotated material. A mathematical framework is develo…
Automatic Annotation of Semantic Fields for Political Science Research
This article discusses methods for automatic annotation of political texts for semantic fields—groups of words with related meanings. This type of annotation is useful when studying political communication, such as legislative debate or political speeches. We present three types of automatic annotation: unsupervised clustering, dictionary-based approaches, and a method based on relevant experimental data. All methods are applied to analyzing Marg…
Lexical Cohesion Analysis of Political Speech
This article presents a novel automatic method of text analysis aimed at discovering patterns of lexical cohesion in political speech. The unit of analysis are groups of words with related meanings; the software is based on the results of a multiperson annotation experiment that captures reliably identified connections between words in a text. We illustrate the advantages of such a representation by juxtaposing results of a detailed hand-made ana…
Lexical Cohesion Analysis of Political Speech
This article presents a novel automatic method of text analysis aimed at discovering patterns of lexical cohesion in political speech. The unit of analysis are groups of words with related meanings; the software is based on the results of a multiperson annotation experiment that captures reliably identified connections between words in a text. We illustrate the advantages of such a representation by juxtaposing results of a detailed hand-made ana…
Automatic Annotation of Semantic Fields for Political Science Research
This article discusses methods for automatic annotation of political texts for semantic fields—groups of words with related meanings. This type of annotation is useful when studying political communication, such as legislative debate or political speeches. We present three types of automatic annotation: unsupervised clustering, dictionary-based approaches, and a method based on relevant experimental data. All methods are applied to analyzing Marg…
From Annotator Agreement to Noise Models
This article discusses the transition from annotated data to a gold standard, that is, a subset that is sufficiently noise-free with high confidence. Unless appropriately reinterpreted, agreement coefficients do not indicate the quality of the data set as a benchmarking resource: High overall agreement is neither sufficient nor necessary to distill some amount of highly reliable data from the annotated material. A mathematical framework is develo…
The “image bite,” political language, and the public/private divide
Voice-overs with muted images, often known as the “image bite,” have become an increasingly used but understudied format of political language by the television news media. Because the media can use images to fit many contexts and purposes of commentary, the media images are susceptible to continuous de-contextualization and re-contextualization. Drawing from theories of feminist critical discourse analysis and gender performance as well as schol…
Automatic Annotation of Semantic Fields for Political Science Research
This article discusses methods for automatic annotation of political texts for semantic fields—groups of words with related meanings. This type of annotation is useful when studying political communication, such as legislative debate or political speeches. We present three types of automatic annotation: unsupervised clustering, dictionary-based approaches, and a method based on relevant experimental data. All methods are applied to analyzing Marg…
Lexical Cohesion Analysis of Political Speech
This article presents a novel automatic method of text analysis aimed at discovering patterns of lexical cohesion in political speech. The unit of analysis are groups of words with related meanings; the software is based on the results of a multiperson annotation experiment that captures reliably identified connections between words in a text. We illustrate the advantages of such a representation by juxtaposing results of a detailed hand-made ana…
From Annotator Agreement to Noise Models
This article discusses the transition from annotated data to a gold standard, that is, a subset that is sufficiently noise-free with high confidence. Unless appropriately reinterpreted, agreement coefficients do not indicate the quality of the data set as a benchmarking resource: High overall agreement is neither sufficient nor necessary to distill some amount of highly reliable data from the annotated material. A mathematical framework is develo…
The “image bite,” political language, and the public/private divide
Voice-overs with muted images, often known as the “image bite,” have become an increasingly used but understudied format of political language by the television news media. Because the media can use images to fit many contexts and purposes of commentary, the media images are susceptible to continuous de-contextualization and re-contextualization. Drawing from theories of feminist critical discourse analysis and gender performance as well as schol…
Associative lexical cohesion as a factor in text complexity
In this paper we present an application of associative lexical cohesion to the analysis of text complexity as determined by expert-assigned US school grade levels. Lexical cohesion in a text is represented as a distribution of pairwise positive normalized mutual information values. Our quantitative measure of lexical cohesion is Lexical Tightness (LT), computed as average of such values per text. It represents the degree to which a text tends to …
Advancing the validity argument for standardized writing tests using quantitative rhetorical analysis
Essay writing is a common type of constructed-response task used frequently in standardized writing assessments. However, the impromptu timed nature of the essay writing tests has drawn increasing criticism for the lack of authenticity for real-world writing in classroom and workplace settings. The goal of this paper is to contribute evidence to a validity argument for standardized writing tests. Using measurements of distances between rhetorical…
Beyond text complexity
Unveiling Patterns of Interaction With Automated Feedback in Writing Mentor and Their Relationships With Use Goals and Writing Outcomes
How Much Should I Read? An Analysis of Word Learning Opportunities in Children's Novels
With only about a third of students in US public schools achieving the NAEP Proficient level, many educators believe students are not getting enough reading practice. However, how much reading practice is enough? This study quantifies the relationship between the amount of book reading and the expected number of words learned. We collected 45 children's novels, M(Lexile) = 994 L, or Grade 6, and assembled a corpus of 3.2 million words. When readi…
Toward stealth assessment of reading comprehension
Reading comprehension is a critical skill that enables us to use text for learning, work, and pleasure. It is typically assessed through multiple choice or open-ended questions based on the text. In this article, we explore a novel machine-learning approach to assessing comprehension based on the properties of the text and of its oral reading that are known to be connected to comprehension. This method of assessing comprehension can potentially f…
Stealth assessment of oral reading fluency during interactive book reading
Oral reading fluency (ORF) assessments are widely used to predict students’ reading proficiency and signal the need for additional instruction. Standardized ORF assessments require substantial resources to develop and take time from instruction to administer; they may also increase test anxiety. To address these concerns, we explored stealth assessment of ORF during book reading. Eighty students (grades 4–5) engaged in interactive book reading th…
Linguistics (8 works) · Computer Science (7 works) · Psychology (5 works) · Artificial Intelligence (4 works) · Mathematics education (4 works) · Natural Language Processing Techniques (4 works) · Natural language processing (3 works) · Political science (3 works) · Politics (3 works) · Reading and Literacy Development (3 works)