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Ahmed Magooda; Diane Litman; Ahmed Ashraf; Muhsin Menekse – Grantee Submission, 2022
Having students write reflections has been shown to help teachers improve their instruction and students improve their learning outcomes. With the aid of Natural Language Processing (NLP), real-time educational applications that can assess and provide feedback on reflection quality can be deployed. In this work, we first evaluate various NLP…
Descriptors: Undergraduate Students, Writing Assignments, Reflection, Natural Language Processing
Phung, Tung; Cambronero, José; Gulwani, Sumit; Kohn, Tobias; Majumdarm, Rupak; Singla, Adish; Soares, Gustavo – International Educational Data Mining Society, 2023
Large language models (LLMs), such as Codex, hold great promise in enhancing programming education by automatically generating feedback for students. We investigate using LLMs to generate feedback for fixing syntax errors in Python programs, a key scenario in introductory programming. More concretely, given a student's buggy program, our goal is…
Descriptors: Computational Linguistics, Feedback (Response), Programming, Computer Science Education
Ní Chiaráin, Neasa; Ní Chasaide, Ailbhe – Research-publishing.net, 2018
This paper details the motivation for and the main characteristics of "An Scéalaí" ('The Storyteller'), an intelligent Computer Assisted Language Learning (iCALL) platform for autonomous learning that integrates the four skills; writing, listening, speaking, and reading. A key feature is the incorporation of speech technology. Speech…
Descriptors: Computer Assisted Instruction, Language Acquisition, Independent Study, Assistive Technology
Garnier, Marie – Research-publishing.net, 2012
According to recent studies, there is a persistence of adverb placement errors in the written productions of francophone learners and users of English at an intermediate to advanced level. In this paper, we present strategies for the automatic detection and correction of errors in the placement of manner adverbs, using linguistic-based natural…
Descriptors: Form Classes (Languages), Error Correction, Natural Language Processing, Feedback (Response)
Harbusch, Karin; Cameran, Christel-Joy; Härtel, Johannes – Research-publishing.net, 2014
We present a new feedback strategy implemented in a natural language generation-based e-learning system for German as a second language (L2). Although the system recognizes a large proportion of the grammar errors in learner-produced written sentences, its automatically generated feedback only addresses errors against rules that are relevant at…
Descriptors: German, Second Language Learning, Second Language Instruction, Feedback (Response)