inteligencia artificial

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

The present study investigates the effectiveness of a GenAI-based chatbot, “Reading Bot,” in reducing foreign language reading anxiety (FLRA) and improving foreign language reading performance (FLRP) among Chinese secondary school students learning English as a foreign language (EFL). To do so, a mixed-methods quasi-experimental pre-test/post-test design with qualitative interviews was employed. After ensuring homogeneity between the two groups, one class was designated as the experimental group (n = 42), utilizing a chatbot as a treatment, while the other class served as the comparison group (n = 42), receiving traditional teacher support. Both groups participated in five 45-min reading...

Fostering machine learning literacy in senior primary education: Evaluating a structured pedagogical course design

Siu-Cheung Kong, Qiaoyi Wang (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Current K–12 artificial intelligence (AI) literacy education emphasizes tool usage over fundamental concepts, yet AI literacy requires grasping how and why AI works – critical for an AI-driven society. This highlights the need for machine learning (ML) education for young learners. We designed and evaluated a six-to 8-h ML course for 752 senior primary students (average age 11.36) across seven Hong Kong primary schools. Pre- and post-test results showed significant improvement in ML understanding, with a Wilcoxon effect size of 0.55. Students comprehended supervised learning and reinforcement learning, including algorithms such as k-nearest neighbours and artificial neural networks, via...

Artificial intelligence literacy in primary education: An arts-based approach to overcoming age and gender barriers

Iris Heung Yue Yim (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Artificial Intelligence (AI) literacy education was previously taught primarily at the university and secondary school levels but has recently started to be expanded to primary school settings. When available at the primary school level, AI literacy is often taught within computer science courses, which may potentially reinforce gender stereotypes and discourage female students' engagement. In AI literacy education, the predominant teaching methods are constructivist approaches, which, while effective in fostering active learning, heavily emphasize technical skills and are therefore limited in their pedagogical scope, as they underplay other important questions, such as disinformation, data...

Towards an understanding of the engagement and emotional behaviour of MOOC students using sentiment and semantic features

Xiaohui Tao, Aaron Shannon-Honson, Patrick Delaney (2023)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

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Online learning and teaching increased in 2020, driven by the COVID-19 pandemic. As many researchers attempted to understand the impact stress had on the emotional behaviours and academic performance of students, most studies explored these pre- and during-COVID behaviours in the context of brick and mortar institutions transitioning to online delivery. There is an opportunity to compare the experiences of students in the MOOC environment in this period, particularly in terms of the difference of engagement, semantics and sentiment/stress behaviours in 2019 and 2020. In this study, we use a dataset from AdelaideX between this time period to identify the most significant features...

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...

Toward understanding the role of generative AI in entrepreneurship education: A systematic review

Genping Yu, T. Ramayah, Zhongyan Lin (2025)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

Resumen:

This study presents a systematic literature review to explore the emerging role of Generative Artificial Intelligence (GAI) in entrepreneurship education (EE). While recent years have witnessed an increasing interest in applying GAI tools, such as ChatGPT, to support personalized learning, business model simulation, and decision-making, the field remains at an early exploratory stage. Drawing on 50 peer-reviewed journal articles published between 2019 and early 2025, the study aims to map the conceptual landscape, identify key themes, and assess the current state of theoretical and empirical development. The findings reveal four major domains in GAI-enabled EE: personalized and adaptive...

An AI-enhanced pattern recognition approach to temporal and spatial analysis of children's embodied interactions

Ceren Ocak, Theodore J. Kopcha, Raunak Dey (2023)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Multimodal video analysis is a complex and time-consuming process for a researcher; it entails capturing, watching, and re-watching video data to identify which segments best inform or address the questions that drive the research. Modern AI applications can alleviate the challenges that arise during the fine-grained analysis of learners' multimodal interactions captured through video. In this study, we present a supervised approach to training a deep neural network to analyze children's computational thinking (CT) captured through multimodal video data. The approach first uses a set of images extracted from video data to train the AI to map them to labels generated using a priori theory....

Towards responsible AI for education: Hybrid human-AI to confront the elephant in the room

Danial Hooshyar, Gustav Šír, Yeongwook Yang (2025)

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Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial

Resumen:

Despite significant advancements in AI-driven educational systems and ongoing calls for responsible AI for education, several critical issues remain unresolved—acting as elephant in the room within AI in education, learning analytics, educational data mining, learning sciences, and educational psychology communities. This critical analysis identifies and examines nine persistent challenges across the conceptual, methodological, and ethical dimensions that continue to undermine the fairness, transparency, and effectiveness of current AI methods and applications in education. These include: 1) the lack of clarity around what AI for education truly means—often ignoring the distinct purposes,...

Teachers’ motivation and engagement to harness generative AI for teaching and learning: The role of contextual, occupational, and background factors

Rebecca J. Collie, Andrew J. Martin (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Since their release in late 2022, generative AI (genAI) tools have led to widespread use, including among teachers. The aim of our study is to examine several factors that may be implicated in teachers' motivation and engagement to harness genAI in teaching and learning. We examined contextual (i.e., autonomy-supportive leadership, autonomy-thwarting leadership), occupational experience (i.e., professional growth striving, change-related stress), and background factors (i.e., gender, age, teaching experience, contract length, class size, school level) as predictors of motivation (i.e., genAI valuing) and, in turn, engagement (i.e., integration in teaching-related work and student learning...

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...