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L. Hannah; E. E. Jang; M. Shah; V. Gupta – Language Assessment Quarterly, 2023
Machines have a long-demonstrated ability to find statistical relationships between qualities of texts and surface-level linguistic indicators of writing. More recently, unlocked by artificial intelligence, the potential of using machines to identify content-related writing trait criteria has been uncovered. This development is significant,…
Descriptors: Validity, Automation, Scoring, Writing Assignments
Huang, Eddie; Valdiviejas, Hannah; Bosch, Nigel – Grantee Submission, 2019
Metacognition is a valuable tool for learning, since it is closely related to self-regulation and awareness of one's own affect. However, methods for automatically detecting and studying metacognition are scarce. Thus, in this paper we describe an algorithm for automatic detection of metacognitive language in writing. We analyzed text from the…
Descriptors: Metacognition, Mathematics, Language Usage, Writing (Composition)
Sari, Elif; Han, Turgay – Reading Matrix: An International Online Journal, 2021
Providing both effective feedback applications and reliable assessment practices are two central issues in ESL/EFL writing instruction contexts. Giving individual feedback is very difficult in crowded classes as it requires a great amount of time and effort for instructors. Moreover, instructors likely employ inconsistent assessment procedures,…
Descriptors: Automation, Writing Evaluation, Artificial Intelligence, Natural Language Processing
Cai, Zhiqiang; Li, Hiyiang; Hu, Xiangen; Graesser, Art – Grantee Submission, 2016
This paper provides an alternative way of document representation by treating topic probabilities as a vector representation for words and representing a document as a combination of the word vectors. A comparison on summary data shows that this representation is more effective in document classification. [This paper was published in:…
Descriptors: Probability, Natural Language Processing, Models, Automation
Bermudez-Gonzalez, Daniel; Miranda-Jiménez, Sabino; García-Moreno, Raúl-Ulises; Calderón-Nepamuceno, Dora – Research-publishing.net, 2016
Nowadays, machine learning techniques are being used in several Natural Language Processing (NLP) tasks such as Opinion Mining (OM). OM is used to analyse and determine the affective orientation of texts. Usually, OM approaches use affective dictionaries in order to conduct sentiment analysis. These lexicons are labeled manually with affective…
Descriptors: Dictionaries, Spanish, Natural Language Processing, Psychological Patterns
Danielle S. McNamara; Laura K. Allen; Scott A. Crossley; Mihai Dascalu; Cecile A. Perret – Grantee Submission, 2017
Language is of central importance to the field of education because it is a conduit for communicating and understanding information. Therefore, researchers in the field of learning analytics can benefit from methods developed to analyze language both accurately and efficiently. Natural language processing (NLP) techniques can provide such an…
Descriptors: Natural Language Processing, Learning Analytics, Educational Technology, Automation
Papasalouros, Andreas; Chatzigiannakou, Maria – International Association for Development of the Information Society, 2018
Automating the production of questions for assessment and self-assessment has become recently an active field of study. The use of Semantic Web technologies has certain advantages over other methods for question generation and thus is one of the most important lines of research for this problem. The aim of this paper is to provide an overview of…
Descriptors: Computer Assisted Testing, Web 2.0 Technologies, Test Format, Multiple Choice Tests
Wilson, Joshua; Roscoe, Rod D. – Journal of Educational Computing Research, 2020
The present study extended research on the effectiveness of automated writing evaluation (AWE) systems. Sixth graders were randomly assigned by classroom to an AWE condition that used "Project Essay Grade Writing" (n = 56) or a word-processing condition that used Google Docs (n = 58). Effectiveness was evaluated using multiple metrics:…
Descriptors: Automation, Writing Evaluation, Feedback (Response), Instructional Effectiveness
Chen, Lei; Zechner, Klaus; Yoon, Su-Youn; Evanini, Keelan; Wang, Xinhao; Loukina, Anatassia; Tap, Jidong; Davis, Lawrence; Lee, Chong Min; Ma, Min; Mundowsky, Robert; Lu, Chi; Leong, Chee Wee; Gyawali, Binod – ETS Research Report Series, 2018
This research report provides an overview of the R&D efforts at Educational Testing Service related to its capability for automated scoring of nonnative spontaneous speech with the "SpeechRater"? automated scoring service since its initial version was deployed in 2006. While most aspects of this R&D work have been published in…
Descriptors: Computer Assisted Testing, Scoring, Test Scoring Machines, Speech Tests
Burrows, Steven; Gurevych, Iryna; Stein, Benno – International Journal of Artificial Intelligence in Education, 2015
Automatic short answer grading (ASAG) is the task of assessing short natural language responses to objective questions using computational methods. The active research in this field has increased enormously of late with over 80 papers fitting a definition of ASAG. However, the past efforts have generally been ad-hoc and non-comparable until…
Descriptors: Grading, Automation, Natural Language Processing, Computation
Sano, Makoto; Baker, Doris Luft; Collazo, Marlen; Le, Nancy; Kamata, Akihito – Grantee Submission, 2020
Purpose: Explore how different automated scoring (AS) models score reliably the expressive language and vocabulary knowledge in depth of young second grade Latino English learners. Design/methodology/approach: Analyze a total of 13,471 English utterances from 217 Latino English learners with random forest, end-to-end memory networks, long…
Descriptors: English Language Learners, Hispanic American Students, Elementary School Students, Grade 2
Ramachandran, Lakshmi; Gehringer, Edward F.; Yadav, Ravi K. – International Journal of Artificial Intelligence in Education, 2017
A "review" is textual feedback provided by a reviewer to the author of a submitted version. Peer reviews are used in academic publishing and in education to assess student work. While reviews are important to e-commerce sites like Amazon and e-bay, which use them to assess the quality of products and services, our work focuses on…
Descriptors: Natural Language Processing, Peer Evaluation, Educational Quality, Meta Analysis
Hu, Xiao – Learning: Research and Practice, 2017
Despite the rapid development in the area of learning analytics (LA), there is comparatively little focused towards the secondary level of education. This ongoing work presents the latest developed function of Wikiglass, an LA tool designed for automatically recognising, aggregating, and visualising levels of thinking orders in student…
Descriptors: Secondary School Students, Data Analysis, Learning, Automation
Bruno, James V.; Cahill, Aoife; Gyawali, Binod – ETS Research Report Series, 2016
We present an annotation scheme for classifying differences in the outputs of syntactic constituency parsers when a gold standard is unavailable or undesired, as in the case of texts written by nonnative speakers of English. We discuss its automated implementation and the results of a case study that uses the scheme to choose a parser best suited…
Descriptors: Documentation, Classification, Differences, Syntax
Pareja-Lora, Antonio – Research-publishing.net, 2016
For the new approaches to language e-learning (e.g. language blended learning, language autonomous learning or mobile-assisted language learning) to succeed, some automatic functions for error correction (for instance, in exercises) will have to be included in the long run in the corresponding environments and/or applications. A possible way to…
Descriptors: Electronic Learning, Automation, Error Correction, Natural Language Processing

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