andamiaje/scaffolding

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

With the rise of Generative Artificial Intelligence (GenAI), tools such as ChatGPT have shown great potential in enhancing online learning. However, existing applications in video-based learning remain limited, as they typically require learners to pause or switch interfaces to access AI support, disrupting learning continuity. To address this challenge, this study proposes a framework that utilizes ChatGPT to generate comments for an individual learner (i-Comments), displayed as scrolling text over educational videos, providing both knowledge and emotional support based on scaffolding theory. The present study evaluates the framework's generation capabilities to gain empirical insight that...

Less stress, better scores, same learning: The dissociation of performance and learning in AI-supported programming education

Patrick Bassner, Ben Lenk-Ostendorf, Ramona Beinstingel (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Introduction: Generative AI is reshaping programming education, yet its effects on conceptual learning, intrinsic motivation, and cognitive load remain unclear. This study tests whether assistance deepens understanding or primarily boosts task completion, and how scaffolded versus answer-giving designs matter. Objectives: This study compares performance, learning, cognitive load, frustration, and motivation across three AI support types, and examines students’ perceptions. Methods: A three-arm randomized controlled trial was conducted in an introductory programming (CS1) course at TUM (N=275). Participants completed a 90-minute exercise on concurrency, implementing a parallel sum with...

Taming the black box: Design principles for rule-integrated LLM tutoring systems in primary school mathematical problem solving

Chee-Kit Looi, Zhaolong Liu, Daner Sun (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

The integration of large language models (LLMs) into intelligent tutoring systems promises personalized learning, yet procedural domains such as primary mathematics remain challenging due to inconsistency and pedagogical opacity. LLM tutors may give unsolicited answers or show unstable scaffolding when students vary arithmetic, units, or rounding. This design science research develops and evaluates a rule-guided tutoring system for mathematical word problems in primary schools. We formalize a distinction between rule-guided scaffolding, in which tutoring is governed by a three-layer architecture (diagnosis → intent selection → constrained response generation), and ad-hoc scaffolding, where...

Enhancing student reflections with natural language processing based scaffolding: A quasi-experimental study in a large lecture course

Muhsin Menekse, Alfa Satya Putra, Jiwon Kim (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Multiple studies have shown that scaffolding plays an important role in regulating and enhancing students' metacognitive monitoring and reflections. However, scaffolding students' reflections in large courses is a major challenge. In the current study, we explored how real-time, technology-enhanced scaffolding affects the quality of students' reflections and academic performance. Two major research questions are: RQ1) Do students in the scaffolding condition construct more specific reflections than those in the non-scaffolding condition? RQ2) How do the scaffolding feature, reflection specificity, and the number of reflections relate to students' academic performance? To address these...

A mixed-methods analysis of AI scaffolding patterns and student inquiry profiles in a middle-school agriculture-STEM classroom

Selcuk Kilinc, Tugce Aldemir, Kamila Misiejuk (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

This study examines how generative AI can support middle school scientific inquiry in a rural agriculture-STEM classroom. Using a mixed-methods design with concurrent data collection and sequential analytic integration, we analyzed 42 eighth-grade students, organized into 12 groups, as they used Aspen, a custom AI chatbot, to revise scientific research questions and hypotheses around a sustainable agriculture problem. Data sources included group project journals, AI interaction logs, and peer discussion transcripts. First, a two-dimensional profiling method categorized the 12 groups into four analytic profiles: Struggling, Most Improved, Perfectionists, and High Achievers, based on initial...

Large language models for education: An open-source paradigm for automated Q&A in the graduate classroom

Ryann M. Perez, Marie Shimogawa, Yanan Chang (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Large Language Models (LLMs) offer scalable educational support, but face barriers regarding accuracy, cost, and learning depth. To interrogate these limitations, we developed the Teaching Assistant for Specialized Knowledge (TAsk), a retrieval-augmented generation enabled and educator curated pipeline. In this nine-week pilot study (N = 33 participants), we deployed TAsk in a graduate-level biological chemistry course. We compared TAsk against human expert teaching assistants (TAs) using blinded review process and analyzed inquiry depth. We observed three major findings related to potential pedagogical decisions and educational theory. First, TAsk delivered effective feedback that was...

From literature to research-based learning: An AI-powered information extraction system to enhance undergraduate thesis completion

Rong An, Weian Zhu, Qian Zhao (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Undergraduate thesis completion in STEM education is often constrained by limited timeframes, insufficient training, and the difficulty of navigating unstructured scientific literature. This study describes the design and evaluation of an AI-powered information extraction system that converts research publications into structured, traceable, and comparable datasets to support literature-driven comparison. The system is positioned as an epistemic scaffold that enables the inspection of evidence claim relationships through source traceability and structured comparisons while reducing low-level data-handling demands. A mixed-methods pilot study was conducted with 20 undergraduates from four...

Analytics of self-regulated learning strategies and scaffolding: Associations with learning performance

Tongguang Li, Lixiang Yan, Sehrish Iqbal (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Self-regulated learning (SRL) encapsulates learners' abilities to control, monitor, and regulate cognitive and metacognitive processes such as motivation, emotion, and learning strategies. A crucial element of SRL proficiency lies in learners' capacity to plan and implement effective learning strategies. As such, extensive academic research has been devoted to understanding the impact of learning strategies on learning performance, and the role of instructional methods (including real-time scaffolding) in amplifying students' ability to adopt effective learning strategies. However, while numerous studies have focused on learning strategies and SRL scaffolding, few have investigated their...

Scaffolding critical thinking with generative AI: Design principles for integrating large language models in higher education

Mireia Vendrell, Samantha-Kaye Johnston (2026)

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Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial

Resumen:

The rapid adoption of Large Language Models (LLMs) such as GPT-4 and DeepSeek R1 is transforming learning in higher education, yet unstructured use can weaken critical thinking by encouraging cognitive offloading, metacognitive disengagement, and reduced epistemic agency. This paper presents a conceptual and normative analysis that synthesises research from cognitive psychology, educational theory, and AI ethics to develop a design-oriented pedagogical framework for integrating LLMs in ways that strengthen, rather than displace, higher-order thinking. Grounded in design-based research principles, the framework identifies six essential processes that underpin critical engagement: conceptual...

The effect of collaborative writing in an EFL secondary setting

Izaskun Villarreal, Nora Gil-Sarratea (2020)

Language Teaching Research

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Tipo: artículo

Metodología: estudio empírico

Temas: aprendizaje colaborativo

Resumen:

Collaborative writing (CW) has been proven advantageous to enhance the second and foreign language skills of university students. However, little research to date has explored whether CW practices are fruitful for secondary school learners in foreign language (FL) contexts, a population characterized by low language proficiency levels, and few opportunities to engage with the FL. The present classroom-based study examines CW in this setting and aims to determine whether CW fosters language opportunities, operationalized as language-related episodes (LREs), which will allow learners in low-input scenarios to compose better texts. Two parallel intact classes were studied: a control group (n = 16) which produced an argumentative essay individually, and an experimental group (n = 16) which did so in pairs while recording their...