2026 | Bibliografía fecha

El español ha experimentado una creciente implantación en las escuelas secundarias de China, un entorno altamente competitivo donde conciliar el rendimiento académico con el desarrollo socioemocional puede ser un gran desafío. Este estudio, con enfoque mixto, analiza la inclusión de elementos orientados a desarrollar las competencias socioemocionales en la primera serie oficial publicado en el marco del nuevo plan curricular del país. Los resultados muestran avances respecto a manuales anteriores, en particular en la integración de tareas contextualizadas orientadas al desarrollo de habilidades interpersonales, pero también carencias como insuficiente atención prestada a la gestión de sí...

From simulation to flight: Simulation-assisted drone learning with teacher-AI co-designed scaffolds for secondary students’ STEM knowledge and competencies

Richard Chung Yiu Yeung, Chi Ho Yeung, Daner Sun (2026)

Detalles Cerrar ✕

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

A persistent challenge in drone-based STEM education is the scarcity of teacher-verified, interactive simulations that support both conceptual learning and competency development. Generative AI can accelerate content creation, but its outputs frequently lack pedagogical validity and contextual alignment. This study examines whether simulation-assisted drone instruction, anchored by teacher-AI co-designed simulations, yields superior learning outcomes compared to the same hands-on curriculum delivered without simulations. Using a quasi-experimental pretest–posttest design with 30 secondary students (aged 13 to 17), both groups completed identical drone tasks with the same instructor; however...

Exploring the relationship between empowerment in using artificial intelligence for problem-solving and artificial intelligence ethical awareness: Multi-group structural equation modelling

Siu-Cheung Kong, Jinyu Zhu (2026)

Detalles Cerrar ✕

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

While increasing attention has been given to cultivating students' artificial intelligence (AI) ethical awareness, the factors that contribute to its development remain underexplored. Psychological empowerment is a crucial motivational factor influencing students' intentions to incorporate ethical norms in developing AI-based solutions. Hence, this study filled this up by exploring the relationship between empowerment in using AI for problem-solving and AI ethical awareness. Empowerment in using AI for problem-solving in this study comprised three components: impact, self-efficacy and meaningfulness. Data was collected from 681 students from secondary schools and a university in Hong Kong....

Coauthorship integrity: Reconceptualising assessment validity for the age of generative artificial intelligence

Mohsen Ebrahimzadeh, Antonette Shibani, Simon Buckingham Shum (2026)

Detalles Cerrar ✕

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial

Resumen:

We consider how a future of pervasive human/AI coauthorship challenges current notions of validity and academic integrity. Specifically, we address widespread concerns that in non-proctored contexts, students are using generative artificial intelligence (GenAI) to submit texts they do not understand. Adopting an assessment validity lens, we show how GenAI undermines the integrity of multiple forms of validity evidence, leading us to propose Coauthorship Integrity as a new conceptual source of validity evidence for addressing these threats. Coauthorship Integrity is violated when students submit AI-generated content that they do not understand. To hold students accountable in this regard, a...

LLM sentiment quantification reveals selective alignment with human course-evaluation raters

Joyce W. Lacy, Chi Nnoka, Zachary Jock (2026)

Detalles Cerrar ✕

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Student course evaluations contain rich qualitative feedback in the form of comments written in response to open-ended questions. However, this qualitative data, which may be more nuanced and detailed than quantitative ratings, is often unexamined in both administrative and research settings due to the labor-intensive nature of manual analysis. We investigate whether large language models (LLMs), including BERT, RoBERTa, and OpenAI model variants, can accurately replicate human judgments of sentiment in these comments. We compare masked and generative language models, using both naïve and fine-tuned approaches, to analyze a curated dataset of 1000 de-identified course evaluation responses....

Presenting your AI in education research with rigor: The TEP-AIED model

Gwo-Jen Hwang, Haoran Xie, Benjamin W. Wah (2026)

Detalles Cerrar ✕

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial

Resumen:

The rapid expansion of Artificial Intelligence in Education (AIED), particularly with the emergence of generative AI, has intensified the need for rigorous, transparent, and pedagogically grounded research reporting. Although existing frameworks offer valuable guidance on ethical responsibility or technical disclosure, they may be complex, fragmented, or difficult to operationalize in empirical and experimental contexts. This paper proposes the TEP (Transparency-Ethics-Pedagogy)-AIED model, a streamlined three-dimensional framework integrating transparency, ethics, and pedagogy to guide the design and reporting of AIED studies. The model highlights clear disclosure of AI system...

Building AI companions that prioritise learning over performance

Hassan Khosravi, Dragan Gašević, Shazia Sadiq (2026)

Detalles Cerrar ✕

Tipo: artículo

Metodología: trabajo teórico

Temas: inteligencia artificial

Resumen:

Generative AI, currently most visible in education through large language models (LLMs), is increasingly embedded in students’ everyday learning practices, supporting tasks such as writing, coding, reasoning, and analysis. Yet its educational value remains uncertain because systems designed to improve immediate task performance may also weaken the cognitive and metacognitive processes that support durable learning. This paper addresses this learning–performance paradox by asking how AI systems can be designed to support learning rather than merely produce better outputs. To address this, in this paper, we make three contributions. First, we synthesise current LLM-based study support with...

Language teachers’ AI literacy: A psychometric study based on the ED-AI framework

Salim Nabhan, Anita Habók (2026)

Detalles Cerrar ✕

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Artificial Intelligence (AI) is reshaping language education, making AI literacy crucial for teachers to engage critically and effectively with this technology. Nonetheless, most existing assessments target students or general users, leaving a gap in measuring AI literacy within language teacher education. This study sought to develop and validate the Teachers’ AI Literacy Scale (TAILS), grounded in the ED-AI literacy framework, which comprises six dimensions: knowledge, evaluation, collaboration, contextualization, autonomy, and ethics. The scale was tested with preservice English language teachers through two phases: exploratory factor analysis (EFA) with 165 participants and confirmatory...

GenAI as a runaway object in higher education: A socio-cultural view on AI-influenced academic practice in mathematics

Dionysia Bakogianni, Yvonne Liljekvist, Phuong Bui (2026)

Detalles Cerrar ✕

Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

This study explores how generative AI (GenAI) technologies are reshaping research and teaching practices at the university level. Drawing on Cultural-Historical Activity Theory (CHAT) (Engeström, 1987), we examine the interrelated activity systems of teaching and research through the lens of GenAI as a “runaway object”, a concept describing technologies that evolve unpredictably, disrupt boundaries, and reconfigure roles, tools, and epistemic norms. Based on qualitative data from ten academics in a mathematics department at a Swedish university, the analysis identifies five dominant themes that characterize emerging changes across both activity systems: boundary fluidity, shifting objects,...

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

Mireia Vendrell, Samantha-Kaye Johnston (2026)

Detalles Cerrar ✕

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...