Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

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Reformulation is a form of written corrective feedback to help second language (L2) learners improve their writing. This study examined whether ChatGPT could produce reformulations that (1) retain the meanings of the original essays and (2) are linguistically more developed than learners’ original essays. In addition, three types of ChatGPT prompts were compared to see which type yielded better reformulations. One thousand two hundred argumentative essays written for the TOEFL iBT® independent writing task were submitted to ChatGPT. ROUGE-L scores, used as a proxy for meaning retention, showed that ChatGPT reformulations largely retained the meaning of the original essays. A qualitative...

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

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Assessment feedback is important to student learning. Learning analytics (LA) powered by artificial intelligence exhibits profound potential in helping instructors with the laborious provision of feedback. Inspired by the recent advancements made by Generative Pre-trained Transformer (GPT) models, we conducted a study to examine the extent to which GPT models hold the potential to advance the existing knowledge of LA-supported feedback systems towards improving the efficiency of feedback provision. Therefore, our study explored the ability of two versions of GPT models – i.e., GPT-3.5 (ChatGPT) and GPT-4 – to generate assessment feedback on students' writing assessment tasks, common in...

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Metodología: estudio empírico

Temas: inteligencia artificial

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Many engineering disciplines require problem-solving skills, which cannot be learned by memorization alone. Open-ended textual exercises allow students to acquire these skills. Students can learn from their mistakes when instructors provide individual feedback. However, grading these exercises is often a manual, repetitive, and time-consuming activity. The number of computer science students graduating per year has steadily increased over the last decade. This rise has led to large courses that cause a heavy workload for instructors, especially if they provide individual feedback to students. This article presents CoFee, a framework to generate and suggest computer-aided feedback for...

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Metodología: estudio empírico

Temas: inteligencia artificial

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This paper introduces the design and development of a framework that integrates a large language model (LLM) with a retrieval-augmented generation (RAG) approach leveraging both a knowledge graph and user interaction history. The framework is incorporated into a previously developed adaptive learning support system to assess learners’ code, generate formative feedback, and recommend exercises. Moreover, this study examines learner preferences across three instructional modes: adaptive, Generative AI (GenAI), and hybrid GenAI–adaptive. An experimental study was conducted to compare the learning performance and perception of the learners, and the effectiveness of these three modes using four...

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Tipo: artículo

Metodología: trabajo teórico

Temas: análisis de errores

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Las estrategias de autocorrección y autoevaluación constituyen una parte importante en el desarrollo de las competencias. Si en las personas jóvenes y adultas no existe una actitud consciente en cuanto al aprendizaje se puede afirmar que éste no será eficaz o no todo lo eficaz que podría ser. Son tres los conceptos básicos que vamos a definir brevemente en este artículo: la contribución del análisis de errores, el concepto de corrección y el concepto de autonomía. Se trata de relacionar estos términos para aplicar con mayor eficacia algunas estrategias que redunden en un aprendizaje más efectivo.

Self-correction and self-evaluation strategies are an important part of the development...

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

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Large Language Models (LLMs) have emerged as powerful computational tools with significant potential across various fields, particularly education. Previous research demonstrated that LLMs can be effectively integrated into the Tutoring Model of Intelligent Tutoring Systems (ITS) to generate motivational feedback within learning environments. To further explore this area, the authors define an ITS architecture that integrates an LLM (referred to as the ITS-LLM architecture) and validates this architecture by implementing a prototype using Llama 3.2 model. Moreover, the prototype aims to evaluate the impact of LLM-generated motivational feedback on student motivation and their learning...

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

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Text-based open-ended questions in academic formative and summative assessments help students become deep learners and prepare them to understand concepts for a subsequent conceptual assessment. However, grading text-based questions, especially in large (>50 enrolled students) courses, is tedious and time-consuming for instructors. Text processing models continue progressing with the rapid development of Artificial Intelligence (AI) tools and Natural Language Processing (NLP) algorithms. Especially after breakthroughs in Large Language Models (LLM), there is immense potential to automate rapid assessment and feedback of text-based responses in education. This systematic review adopts a...

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

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Feedback is an essential component of scaffolding for learning. Feedback provides insights into the assistance of learners in terms of achieving learning goals and improving self-regulated skills. In online courses, feedback becomes even more critical since instructors and students are separated geographically and physically. In this context, feedback allows the instructor to customize learning content according to the students' needs. However, giving feedback is a challenging task for instructors, especially in contexts of large cohorts. As a result, several automatic feedback systems have been proposed to reduce the workload on the part of the instructor. Although these systems have...

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Metodología: estudio empírico

Temas: inteligencia artificial

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Adopting mixed methods, the study compared teacher feedback and ChatGPT feedback on 35 Chinese university EFL learners’ essay revision, their Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) and their perceived benefits and drawbacks of the feedback. Students wrote two English essays and received writing feedback from their English teacher and ChatGPT respectively. They revised one essay using teacher feedback and another using ChatGPT feedback. Upon revision, students responded to a 5-point Likert-scale questionnaire regarding PU and PEOU of the two types of feedback. The results showed that students obtained significantly higher scores on the revised essays using ChatGPT...

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

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This mixed-methods study investigates how an AI-powered writing tool providing automated feedback compares with peer-generated feedback in supporting secondary students' essay writing. Two research questions guided the study: (1) Did using an AI-powered tool with AI-generated feedback yield greater gains in writing quality from the first to the final draft compared with a standard editor with peer feedback? (2) How did students’ engagement in the writing process differ in the target (used AI-generated feedback) and comparison (used peer feedback) groups, as evidenced by teacher–student and peer–peer interactions and how were these patterns associated with their conceptual understanding of...

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