Automatic measurement of propositional idea density from part-of-speech tagging

Brown, Cati; Snodgrass, Tony; Kemper, Susan; Herman, Ruth E.; Covington, Michael A.

doi:10.3758/brm.40.2.540

Cited by 161 publications

(136 citation statements)

References 17 publications

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“…Suppose the testing items of a programming language course are Multiple Choice [8], Completion, Short Answer Questions and Programming and the accuracy rate of a student in answering Question i is ( 1,2,3,4) i xi  , according to the Logistic Model, one can predict that the probability of the student in answering four questions is:…”

Section: Introductionmentioning

confidence: 99%

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Test Response Modeling Demonstrations for College Programming Language

Pu¹,

Chen²

2015

Advances in Social Science, Education and Humanities Research

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Abstract. This article applies Item Response Models into College Computer ProgrammingLanguage Test. According to the different characteristics of Programming Language Test, the author first get the Validity, the Discrimination Parameter and the Difficulty Factor of the test by using classical testing methods. Then, based on students accuracy of answering different examination questions, the author make use of Two-parameter Logistic Model to get students ability coefficient of answering different examination questions. The above mentioned model has been demonstrated and testified in a basic course test of the first-year students in a college. The results will be beneficial to improve both the teaching activities and raising teaching quality. IntroductionItem Response Model is a significant model to test students' capabilities[1] in modern educational s ystem . In teaching tests are an important factor[2] which can not only be used to facilitate feedbacks and evaluation of students'study, but also be used to evaluate students'information source entropy in study [3]. It can be applied both to the evaluation of students'learning and to the improvement of students'learning processes. Testing theories are scientific methods [4] used by researchers of learning in making effective and scientific judgments on the learning information collected and making decisions based on this information. Testing theories mainly consist of Classic Response Theory and Item Response Theory which offsets the deficiency of Classic Response Theory and makes a breakthrough in testing methods [5].

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Section: Introductionmentioning

confidence: 99%

“…In teaching tests are an important factor [2] which can not only be used to facilitate feedbacks and evaluation of students'study, but also be used to evaluate students'information source entropy in study [3]. It can be applied both to the evaluation of students'learning and to the improvement of students'learning processes.…”

Section: Introductionmentioning

confidence: 99%

Test Response Modeling Demonstrations for College Programming Language

Pu¹,

Chen²

2015

Advances in Social Science, Education and Humanities Research

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“…Idea density uses elements of language, verbs, adjectives, adverbs, prepositions, and conjunctions divided by the number of words to create a measure of cognitive ability (Brown et al, 2008). Garrard et al (2005) were also instrumental in highlighting Alzheimer's disease through changes in writing and used a different approach which included some other elements of language (nouns, verbs, adverbs and adjectives and function words, e.g., conjunctions, and pronouns) to create word lists.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Depression and Apathy on Sensory Language

Kernot¹,

Bossomaier²,

Bradbury³

2017

OJML

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The debate that language strongly influences thought is equally met by those who suggest language does not influence thought. While historically, the ability to communicate with words was believed to be intimately tied to an ability to form thoughts, we would argue that thought and language are linked together through our sensory and motor systems and severely impacted by depression and apathy. We test this by conducting parts of speech analysis from the comparative longitudinal studies of two highly creative and prolific writers, where one is diagnosed with Alzheimer's disease (AD), and the other lives a long and healthy life. We calculate function and contents word ratios, measure lexical repetition, and the use of sensory-based words in textual language to test for depression and apathy in AD which is supported by MannWhitney U-Testing and Principal Component Analysis. Our results support the hypothesis that thought and language are impacted by depression and apathy and revealed in a person's writing style 12 years before a formal diagnosis of Alzheimer's disease presents. We find higher lexical repetition in language 12 years prior to one author being diagnosed with AD while not apparent in the other. We identify low olfactory word use and also find that an increased use of sensory-based adjectives might be a sign of the early onset of Alzheimer's disease.

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“…In Brown et al (2008). The predicative proposition (HAS, MARE, NOSE) is represented by two dependency arcs.…”

Section: Introductionmentioning

confidence: 99%

“…The existing tool for automatic PID computation, 322 CPIDR (Brown et al, 2008), is based on counting POS tags. However, we noticed that the propositional structure of a sentence is very similar to its dependency structure, see the first column in Table 1.…”

Section: Introductionmentioning

confidence: 99%

Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017)

Lévy

Specia

2017

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Automatic measurement of propositional idea density from part-of-speech tagging

Cited by 161 publications

References 17 publications

Test Response Modeling Demonstrations for College Programming Language

Test Response Modeling Demonstrations for College Programming Language

The Impact of Depression and Apathy on Sensory Language

Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017)

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