inteligencia artificial

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Artificial intelligence is becoming increasingly integrated into students’ academic lives in Ghana, making it crucial to examine their perspectives on ethical dimensions. Against this backdrop, this study assesses the artificial intelligence ethical awareness (AIEA) among 509 Ghanaian university students across the dimensions of human autonomy, beneficence, and fairness, based on AIEA scale originally developed and validated in Hong Kong. The confirmatory factor analysis supported the scale’s three-factor structure within this setting. The network analysis also demonstrated meaningful interconnection among the dimensions, with select items serving as conceptual links, most prominently tying...

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

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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...

Creating an AI-powered platform for generating modelling problems: A case study on direct variation in secondary school mathematics

Chung Kwan Lo, Xiaowei Huang, Ho Wai Cheung (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Integrating mathematical modelling into school curricula is essential for connecting school mathematics with real-world applications. However, teachers often lack the time and resources to design high-quality modelling tasks. While generative artificial intelligence (GenAI) can rapidly produce educational content, existing tools typically generate conventional word problems or routine mathematics exercises rather than resources that foster modelling competencies. This study reports on the design and evaluation of an AI-powered platform that generates mathematical modelling problems and associated pedagogical recommendations grounded in established design principles and retrieval-augmented...

From proficiency to pedagogy: A mixed-methods study of in-service teachers’ TPACK-GenAI and the mediating role of pedagogical knowledge

Laila Mohebi, Areej ElSayary (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

This study investigated in-service teachers' Technological Pedagogical Content Knowledge for Generative Artificial Intelligence (TPACK-GenAI) and examined the factors influencing their integration of generative AI in classroom practice. Using an explanatory sequential mixed-methods design, data were collected from 325 in-service teachers across 26 countries, followed by in-depth interviews with seven teachers. Quantitative results revealed that Technological Knowledge (TK), Pedagogical Knowledge (PK), and Pedagogical Content Knowledge (PCK) were significantly associated with teachers' overall TPACK-GenAI. Crucially, mediation analysis confirmed that Technological Pedagogical Knowledge (TPK...

Beyond binary outcomes: Evaluating and mitigating bias in national standardized test score prediction

Lin Li, Namrata Srivatava, Jia Rong (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Predictive analytics in education holds promise for supporting student learning but poses risks of bias potentially disadvantaging certain groups based on demographic attributes such as gender. Prior work on fairness in educational prediction has largely focused on binary outcomes in higher education, leaving continuous predictions, such as standardized test scores, comparatively understudied, especially in early schooling where consequences can be long-lasting. Despite a few fairness metrics available for continuous outcomes, they often rely on mean differences, obscuring distributional disparities that may disadvantage specific students. Even fewer studies have attempted to address bias...

Preferred scaffolding does not lead to better learning performance: Empirical evidence from AI-supported mathematical modelling

Wangda Zhu, Yin Yang, Yuqin Yang (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Mathematical modelling (MM) is widely recognized as a key competency for addressing complex real-world problems, which requires learners to engage in higher-order processes such as abstraction, representation, and iterative reasoning. However, students often experience difficulties in coordinating these processes within mathematics modelling tasks. While recent advances in artificial intelligence (AI) offer new possibilities for supporting mathematical modelling, limited research has examined how different forms of AI-mediated interaction shape students' learning processes in MM. To address this gap, the present study investigates five AI interaction roles, Tutor, Teaching Assistant, Peer,...

Generative AI (GenAI) as a mindtool that supports generative learning (GL)

Nada Dabbagh, Helen Fake (2026)

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Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial

Resumen:

Grounded in the learning sciences, Generative Learning (GL), is a learning method or process that encourages students to actively generate information and make connections between new and existing knowledge. This active participation in the learning process promotes a deeper understanding of the instructional material, fosters long-term retention of knowledge, and cultivates critical thinking skills and problem-solving abilities. The magic lies in the “generation” process, where learners actively make sense of the material rather than passively receiving information. In this paper, we argue that Generative Artificial Intelligence (GenAI) can be used as a Mindtool (knowledge representation...

Exploring the design of LLM-powered question generation for deaf and hard of hearing learners

Si Chen, Shuxu Huffman, Qingxiaoyang Zhu (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Deaf and Hard of Hearing (DHH) learners face unique learning challenges, often due to a lack of customized educational materials that address their specific needs. This study explores the potential of Large Language Models (LLMs) to generate personalized quiz questions to enhance the video-based learning experiences of DHH students. We iteratively designed, developed, and evaluated a prototype that combines LLMs to generate questions with the characteristics of the DHH learners in focus. The two unique question generation strategies include Visual Questions, which identify video segments where visual information might be misinterpreted, and Emotion Questions, which highlight moments where...

When the algorithm enters the classroom: A critical integrative review of large language models, nursing education structural gaps, and the reconstitution of professional identity

Yanjie Sun, Hongzhou Li, Xiaohui Tao (2026)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

Resumen:

Large language models (LLMs) are being integrated into nursing education at a pace that outstrips the field's capacity to evaluate their consequences. Existing syntheses have mapped what LLMs can do in nursing contexts. Among those identified in this review, none has examined how their integration affects the professional development processes through which nursing expertise is formed. This critical integrative review addresses that gap.Following Whittemore and Knafl’s (2005) five-stage framework, we systematically searched four databases (PubMed/MEDLINE, Web of Science, Scopus, CINAHL) for studies published between January 2017 and December 2025, yielding 489 included studies from 47...

Opportunities of artificial intelligence for supporting complex problem-solving: Findings from a scoping review

Srecko Joksimovic, Dirk Ifenthaler, Rebecca Marrone (2023)

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Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

Resumen:

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The research objective of this paper is to advance knowledge about the role of artificial intelligence (AI) in complex problem-solving. A problem is complex due to the large number of highly inter-connected variables affecting the problem state. Complex problem-solving situations often change decremental or worsen, forcing a problem solver to act immediately, under considerable time pressure. While research findings support the assumption that (1) affective, (2) (meta-)cognitive, and (3) social processes support complex problem-solving, opportunities of AI for supporting complex problem-solving need to be further investigated. This article presents a scoping review of relevant...