inteligencia artificial

Detalles Cerrar ✕

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...

Ethical principles for artificial intelligence in K-12 education

Catherine Adams, Patti Pente, Gillian Lemermeyer (2023)

Detalles Cerrar ✕

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

Resumen:

Texto completo en HTML

Advances in Artificial Intelligence in Education (AIED) are providing teachers with a wealth of new tools and smart services to facilitate student learning. Meanwhile, growing public concern over the potentially harmful societal effects of AI has prompted the publication of a flurry of AI ethics guidelines and policy documents authored by national and international government agencies, academic consortia and industrial stakeholders. AI ethics policy guidance specific to children and K-12 education has lagged behind; this scene is swiftly changing. In this paper, we examine the ethical principles currently informing AI ethics policy development for children and K-12 education. To...

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)

Detalles Cerrar ✕

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...

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)

Detalles Cerrar ✕

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo en HTML

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)

Detalles Cerrar ✕

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...

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

Nada Dabbagh, Helen Fake (2026)

Detalles Cerrar ✕

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...

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

Lin Li, Namrata Srivatava, Jia Rong (2026)

Detalles Cerrar ✕

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)

Detalles Cerrar ✕

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,...

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

Srecko Joksimovic, Dirk Ifenthaler, Rebecca Marrone (2023)

Detalles Cerrar ✕

Tipo: artículo

Metodología: revisión bibliográfica

Temas: inteligencia artificial

Resumen:

Texto completo en HTML

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...

The IDEA framework for metacognitively regulated GenAI use in higher education: Development and exploratory pilot evidence

Xiangpeng Wang, Ziwei Zheng, Jincheng Zhang (2026)

Detalles Cerrar ✕

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial

Resumen:

Generative artificial intelligence (GenAI) can enhance students’ efficiency and the apparent quality of academic work, yet its fluent outputs may encourage learners to outsource cognitive activities central to learning. This creates the risk of “performance without learning”, whereby successful task completion does not necessarily reflect meaningful understanding or learner regulation. To address this concern, this article develops the Intent, Deconstruction, Expression, and Adaptation (IDEA) framework, a theory-informed metacognitive scaffold for GenAI-supported academic work. IDEA guides learners to articulate goals and constraints, decompose tasks into essential processes, communicate...