Publication Date
In 2025 | 3 |
Since 2024 | 35 |
Since 2021 (last 5 years) | 134 |
Since 2016 (last 10 years) | 257 |
Since 2006 (last 20 years) | 402 |
Descriptor
Prediction | 408 |
Language Processing | 352 |
Task Analysis | 116 |
Second Language Learning | 93 |
Foreign Countries | 90 |
Sentences | 79 |
Semantics | 78 |
Correlation | 76 |
Models | 75 |
Syntax | 72 |
Language Acquisition | 67 |
More ▼ |
Source
Author
Publication Type
Journal Articles | 408 |
Reports - Research | 357 |
Reports - Evaluative | 35 |
Information Analyses | 9 |
Reports - Descriptive | 9 |
Opinion Papers | 6 |
Tests/Questionnaires | 6 |
Numerical/Quantitative Data | 1 |
Education Level
Higher Education | 77 |
Postsecondary Education | 58 |
Elementary Education | 26 |
Secondary Education | 8 |
Early Childhood Education | 7 |
Grade 4 | 4 |
Kindergarten | 4 |
Primary Education | 4 |
Grade 2 | 3 |
Grade 3 | 3 |
High Schools | 3 |
More ▼ |
Audience
Location
Germany | 12 |
Netherlands | 8 |
China | 7 |
Canada | 6 |
United Kingdom | 6 |
Australia | 5 |
France | 4 |
Hong Kong | 4 |
South Korea | 4 |
United States | 4 |
Florida | 3 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Frank Lee; Alex Algarra – Information Systems Education Journal, 2025
This case study examines employee attrition, its detrimental effects on businesses, and the potential of data analytics to address this challenge. By employing Latent Dirichlet Allocation (LDA), a sophisticated NLP technique, we delve into the underlying reasons for employee departures. Additionally, we explore using RapidMiner to develop…
Descriptors: Labor Turnover, Data Analysis, Natural Language Processing, Employees
Teo Susnjak – International Journal of Artificial Intelligence in Education, 2024
A significant body of recent research in the field of Learning Analytics has focused on leveraging machine learning approaches for predicting at-risk students in order to initiate timely interventions and thereby elevate retention and completion rates. The overarching feature of the majority of these research studies has been on the science of…
Descriptors: Prediction, Learning Analytics, Artificial Intelligence, At Risk Students
Seamus Donnelly; Caroline Rowland; Franklin Chang; Evan Kidd – Cognitive Science, 2024
Prediction-based accounts of language acquisition have the potential to explain several different effects in child language acquisition and adult language processing. However, evidence regarding the developmental predictions of such accounts is mixed. Here, we consider several predictions of these accounts in two large-scale developmental studies…
Descriptors: Prediction, Error Patterns, Syntax, Priming
John Hollander; Andrew Olney – Cognitive Science, 2024
Recent investigations on how people derive meaning from language have focused on task-dependent shifts between two cognitive systems. The symbolic (amodal) system represents meaning as the statistical relationships between words. The embodied (modal) system represents meaning through neurocognitive simulation of perceptual or sensorimotor systems…
Descriptors: Verbs, Symbolic Language, Language Processing, Semantics
Samah AlKhuzaey; Floriana Grasso; Terry R. Payne; Valentina Tamma – International Journal of Artificial Intelligence in Education, 2024
Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…
Descriptors: Test Items, Test Construction, Difficulty Level, Prediction
Jutta Kray; Linda Sommerfeld; Arielle Borovsky; Katja Häuser – Child Development Perspectives, 2024
Prediction error plays a pivotal role in theories of learning, including theories of language acquisition and use. Researchers have investigated whether and under which conditions children, like adults, use prediction to facilitate language comprehension at different levels of linguistic representation. However, many aspects of the reciprocal…
Descriptors: Prediction, Child Development, Language Acquisition, Error Analysis (Language)
Abu-Zhaya, Rana; Arnon, Inbal; Borovsky, Arielle – Cognitive Science, 2022
Meaning in language emerges from multiple words, and children are sensitive to multi-word frequency from infancy. While children successfully use cues from single words to generate linguistic predictions, it is less clear whether and how they use multi-word sequences to guide real-time language processing and whether they form predictions on the…
Descriptors: Sentences, Language Processing, Semantics, Prediction
Vela-Candelas, Juan; Català, Natàlia; Demestre, Josep – Journal of Psycholinguistic Research, 2022
Some theories of sentence processing make a distinction between two kinds of meaning: a linguistic meaning encoded at the lexicon (i.e., selectional restrictions), and an extralinguistic knowledge derived from our everyday experiences (i.e., world knowledge). According to such theories, the former meaning is privileged over the latter in terms of…
Descriptors: Knowledge Level, Prediction, Language Processing, Sentences
Bovolenta, Giulia; Marsden, Emma – Studies in Second Language Acquisition, 2022
There is currently much interest in the role of prediction in language processing, both in L1 and L2. For language acquisition researchers, this has prompted debate on the role that predictive processing may play in both L1 and L2 language learning, if any. In this conceptual review, we explore the role of prediction and prediction error as a…
Descriptors: Prediction, Error Analysis (Language), Teaching Methods, Second Language Learning
Marian Marchal; Merel C. J. Scholman; Vera Demberg – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
Linguistic phenomena (e.g., words and syntactic structure) co-occur with a wide variety of meanings. These systematic correlations can help readers to interpret a text and create predictions about upcoming material. However, to what extent these correlations influence discourse processing is still unknown. We address this question by examining…
Descriptors: Statistical Analysis, Correlation, Discourse Analysis, Cues
Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – International Journal of Artificial Intelligence in Education, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
Spyridoula Cheimariou; Laura M. Morett – Communication Disorders Quarterly, 2024
One of the basic tenets of predictive theories of language processing is that of misprediction cost. Post-N400 positive event-related potential (ERP) components are suitable for studying misprediction cost but are not adequately described, especially in older adults, who show attenuated N400 ERP effects. We report a secondary analysis of a…
Descriptors: Prediction, Costs, Older Adults, Aging (Individuals)
Qiao, Chen; Hu, Xiao – IEEE Transactions on Learning Technologies, 2023
Free text answers to short questions can reflect students' mastery of concepts and their relationships relevant to learning objectives. However, automating the assessment of free text answers has been challenging due to the complexity of natural language. Existing studies often predict the scores of free text answers in a "black box"…
Descriptors: Computer Assisted Testing, Automation, Test Items, Semantics
Duygu F. Safak; Holger Hopp – Studies in Second Language Acquisition, 2023
This study investigates whether cross-linguistic differences affect how adult second language (L2) learners use different types of verb subcategorization information for prediction in real-time sentence comprehension. Using visual world eye-tracking, we tested if first language (L1) German and L1 Turkish intermediate-to-advanced learners of L2…
Descriptors: Linguistics, Adults, Second Language Learning, Verbs
Lixiang Yan; Lele Sha; Linxuan Zhao; Yuheng Li; Roberto Martinez-Maldonado; Guanliang Chen; Xinyu Li; Yueqiao Jin; Dragan Gaševic – British Journal of Educational Technology, 2024
Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are…
Descriptors: Educational Technology, Artificial Intelligence, Natural Language Processing, Educational Innovation