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Botarleanu, Robert-Mihai; Dascalu, Mihai; Allen, Laura K.; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2021
Text summarization is an effective reading comprehension strategy. However, summary evaluation is complex and must account for various factors including the summary and the reference text. This study examines a corpus of approximately 3,000 summaries based on 87 reference texts, with each summary being manually scored on a 4-point Likert scale.…
Descriptors: Computer Assisted Testing, Scoring, Natural Language Processing, Computer Software
Lu, Chang; Cutumisu, Maria – International Educational Data Mining Society, 2021
Digitalization and automation of test administration, score reporting, and feedback provision have the potential to benefit large-scale and formative assessments. Many studies on automated essay scoring (AES) and feedback generation systems were published in the last decade, but few connected AES and feedback generation within a unified framework.…
Descriptors: Learning Processes, Automation, Computer Assisted Testing, Scoring
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Open-ended comprehension questions are a common type of assessment used to evaluate how well students understand one of multiple documents. Our aim is to use natural language processing (NLP) to infer the level and type of inferencing within readers' answers to comprehension questions using linguistic and semantic features within their responses.…
Descriptors: Natural Language Processing, Taxonomy, Responses, Semantics
Klein, Ariel; Badia, Toni – Journal of Creative Behavior, 2015
In this study we show how complex creative relations can arise from fairly frequent semantic relations observed in everyday language. By doing this, we reflect on some key cognitive aspects of linguistic and general creativity. In our experimentation, we automated the process of solving a battery of Remote Associates Test tasks. By applying…
Descriptors: Language Usage, Semantics, Natural Language Processing, Test Items
Liu, Ming; Rus, Vasile; Liu, Li – IEEE Transactions on Learning Technologies, 2017
Question generation is an emerging research area of artificial intelligence in education. Question authoring tools are important in educational technologies, e.g., intelligent tutoring systems, as well as in dialogue systems. Approaches to generate factual questions, i.e., questions that have concrete answers, mainly make use of the syntactical…
Descriptors: Chinese, Questioning Techniques, Automation, Natural Language Processing
Crossley, Scott A.; Kyle, Kristopher; McNamara, Danielle S. – Grantee Submission, 2015
This study investigates the relative efficacy of using linguistic micro-features, the aggregation of such features, and a combination of micro-features and aggregated features in developing automatic essay scoring (AES) models. Although the use of aggregated features is widespread in AES systems (e.g., e-rater; Intellimetric), very little…
Descriptors: Essays, Scoring, Feedback (Response), Writing Evaluation
Kerr, Deirdre; Mousavi, Hamid; Iseli, Markus R. – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2013
The Common Core assessments emphasize short essay constructed-response items over multiple-choice items because they are more precise measures of understanding. However, such items are too costly and time consuming to be used in national assessments unless a way to score them automatically can be found. Current automatic essay-scoring techniques…
Descriptors: Scoring, Automation, Essay Tests, Natural Language Processing
Kerr, Deirdre; Mousavi, Hamid; Iseli, Markus R. – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2013
The Common Core assessments emphasize short essay constructed response items over multiple choice items because they are more precise measures of understanding. However, such items are too costly and time consuming to be used in national assessments unless a way is found to score them automatically. Current automatic essay scoring techniques are…
Descriptors: Automation, Scoring, Essay Tests, Natural Language Processing
Zhang, Lishan; VanLehn, Kurt – Interactive Learning Environments, 2017
The paper describes a biology tutoring system with adaptive question selection. Questions were selected for presentation to the student based on their utilities, which were estimated from the chance that the student's competence would increase if the questions were asked. Competence was represented by the probability of mastery of a set of biology…
Descriptors: Biology, Science Instruction, Intelligent Tutoring Systems, Probability
Tu, Yuancheng – ProQuest LLC, 2012
The fundamental problem faced by automatic text understanding in Natural Language Processing (NLP) is to identify semantically related pieces of text and integrate them together to compute the meaning of the whole text. However, the principle of compositionality runs into trouble very quickly when real language is examined with its frequent…
Descriptors: English, Verbs, Computational Linguistics, Natural Language Processing
Kerins, John; Ramsay, Allan – ReCALL, 2012
This paper reports on the development of a prototype tool which shows how learners can be helped to reflect upon the accuracy of their writing. Analysis of samples of freely written texts by intermediate and advanced learners of English as a foreign language (EFL) showed evidence of weakness in the use of tense and aspect. Computational discourse…
Descriptors: English (Second Language), Second Language Learning, Writing Instruction, Semantics