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Akemoglu, Yusuf; Hinton, Vanessa; Laroue, Dayna; Jefferson, Vanessa – Journal of Early Intervention, 2022
We describe a study of the internet-based Parent-Implemented Communication Strategies--Storybook (i-PiCSS), an intervention designed to train and coach parents to use evidenced-based naturalistic communication teaching (NCT) strategies (i.e., modeling, mand-model, and time delay) and RTs while reading storybooks with their young children with…
Descriptors: Internet, Natural Language Processing, Parent Education, Communication Skills
Stemper, Samuel – ProQuest LLC, 2023
This dissertation includes three essays in the field of economics of education. The first essay estimates the effect of top school management on student achievement in America. I use newly-collected data on the tenures of school district superintendents--the highest-ranking executive in U.S. school districts--to estimate the impact of individual…
Descriptors: Economics, Superintendents, Scores, Administrator Effectiveness
Editorial Projects in Education, 2023
Artificial Intelligence (AI) is transforming traditional learning landscapes. This Spotlight will empower you with steps educators can take to be prepared for teaching in an AI-powered world; tips for using AI to plan lessons, email parents, and help struggling students; insights on principles to consider when crafting AI guidance; a guide to the…
Descriptors: Artificial Intelligence, Natural Language Processing, Computer Software, Educational Change
Mahowald, Kyle; Kachergis, George; Frank, Michael C. – First Language, 2020
Ambridge calls for exemplar-based accounts of language acquisition. Do modern neural networks such as transformers or word2vec -- which have been extremely successful in modern natural language processing (NLP) applications -- count? Although these models often have ample parametric complexity to store exemplars from their training data, they also…
Descriptors: Models, Language Processing, Computational Linguistics, Language Acquisition
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
Magliano, Joseph P.; Lampi, Jodi P.; Ray, Melissa; Chan, Greta – Grantee Submission, 2020
Coherent mental models for successful comprehension require inferences that establish semantic "bridges" between discourse constituents and "elaborations" that incorporate relevant background knowledge. While it is established that individual differences in the extent to which postsecondary students engage in these processes…
Descriptors: Reading Comprehension, Reading Strategies, Inferences, Reading Tests
Sennott, Samuel C.; Akagi, Linda; Lee, Mary; Rhodes, Anthony – Topics in Language Disorders, 2019
Artificially intelligent tools have given us the capability to use technology to address ever more complex challenges. What are the capabilities, challenges, and hazards of incorporating and developing this technology for augmentative and alternative communication (AAC)? "Artificial intelligence" (AI) can be defined as the capability of…
Descriptors: Augmentative and Alternative Communication, Artificial Intelligence, Knowledge Representation, Thinking Skills
Burstein, Jill; McCaffrey, Daniel; Beigman Klebanov, Beata; Ling, Guangming; Holtzman, Steven – Grantee Submission, 2019
Writing is a challenge and a potential obstacle for students in U.S. 4-year postsecondary institutions lacking prerequisite writing skills. This study aims to address the research question: Is there a relationship between specific features (analytics) in coursework writing and broader success predictors? Knowledge about this relationship could…
Descriptors: Undergraduate Students, Writing (Composition), Writing Evaluation, Learning Analytics
Vittorini, Pierpaolo; Menini, Stefano; Tonelli, Sara – International Journal of Artificial Intelligence in Education, 2021
Massive open online courses (MOOCs) provide hundreds of students with teaching materials, assessment tools, and collaborative instruments. The assessment activity, in particular, is demanding in terms of both time and effort; thus, the use of artificial intelligence can be useful to address and reduce the time and effort required. This paper…
Descriptors: Artificial Intelligence, Formative Evaluation, Summative Evaluation, Data
Sinclair, Arabella J.; Schneider, Bertrand – International Educational Data Mining Society, 2021
Collaborative dialogue is rich in conscious and subconscious coordination behaviours between participants. This work explores collaborative learner dialogue through theories of alignment, analysing inter-partner movement and language use with respect to our hypotheses: that they interrelate, and that they form predictors of collaboration quality…
Descriptors: Dialogs (Language), Cooperative Learning, Correlation, Predictor Variables
Sumie Tsz Sum Chan; Noble Po Kan Lo; Alan Man Him Wong – Contemporary Educational Technology, 2024
This paper investigates the effects of large language model (LLM) based feedback on the essay writing proficiency of university students in Hong Kong. It focuses on exploring the potential improvements that generative artificial intelligence (AI) can bring to student essay revisions, its effect on student engagement with writing tasks, and the…
Descriptors: English (Second Language), Second Language Learning, Language Proficiency, Foreign Countries
Bilal Hamamra; Asala Mayaleh; Zuheir N. Khlaif – Cogent Education, 2024
This article, drawing on essays written by students with the assistance of ChatGPT and interviews with some students who used this learning machine, highlights a shift in the educational landscape brought about by this technology. In broader terms, Palestinian universities follow the traditional methods of teaching based on memorization and rote…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, College Students
Sumie Chan; Noble Lo; Alan Wong – rEFLections, 2024
This study investigates the impact of feedback generated by large language models (LLMs) on improving the essay-writing skills of first-year university students in Hong Kong. Specifically, it examines how generative AI supports students in revising their essays, enhances engagement with writing tasks, and influences their emotional responses…
Descriptors: Artificial Intelligence, Natural Language Processing, Essays, Automation
Ranalli, Jim; Yamashita, Taichi – Language Learning & Technology, 2022
To the extent automated written corrective feedback (AWCF) tools such as Grammarly are based on sophisticated error-correction technologies, such as machine-learning techniques, they have the potential to find and correct more common L2 error types than simpler spelling and grammar checkers such as the one included in Microsoft Word (technically…
Descriptors: Error Correction, Feedback (Response), Computer Software, Second Language Learning
Lang, David; Wang, Alex; Dalal, Nathan; Paepcke, Andreas; Stevens, Mitchell L. – AERA Open, 2022
Committing to a major is a fateful step in an undergraduate education, yet the relationship between courses taken early in an academic career and ultimate major issuance remains little studied at scale. Using transcript data capturing the academic careers of 26,892 undergraduates enrolled at a private university between 2000 and 2020, we describe…
Descriptors: Undergraduate Students, Majors (Students), College Planning, Natural Language Processing