estudio empírico

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA educación superior

Temas IA: IA y educación estudio empírico

Resumen:

The study evaluates the effectiveness of a 12-week AI module delivered to non-STEM university students in England, aimed at building students' AI Capital, encompassing AI-related knowledge, skills, and capabilities. An integral part of the process involved the development and validation of the AI Capital of Students scale, used to measure AI Capital before and after the educational intervention. The module was delivered on four occasions to final-year students between 2023 and 2024, with follow-up data collected on students' employment status. The findings indicate that AI learning enhances students' AI Capital across all three dimensions. Moreover, AI Capital is positively associated 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 grandes modelos de lenguaje andamiaje/scaffolding

Temas IA: modelos de lenguaje (LLM) prompts IA y aprendizaje

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...

Towards automated content analysis of educational feedback: A multi-language study

Ikenna Osakwe, Guanliang Chen, Alex Whitelock-Wainwright (2022)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial feedback/retroalimentación procesamiento del lenguaje natural

Temas IA: IA y evaluación estudio empírico

Resumen:

Feedback is a crucial element of a student's learning process. It enables students to identify weaknesses and improve self-regulation. However, studies show this to be an area of great dissatisfaction in higher education. With ever-growing course participation numbers, delivering effective feedback is becoming an increasingly challenging task. The efficacy of feedback will depend on four levels of feedback; namely, feedback about the self, task, process or self-regulation. Hence, this paper explores the use of automated content analysis to examine feedback provided by instructors for feedback practices measured on self, task, process, and self-regulation levels. For this purpose, four...

Developing an artificial intelligence literacy framework: Evaluation of a literacy course for senior secondary students using a project-based learning approach

Siu-Cheung Kong, Man-Yin William Cheung, Olson Tsang (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA educación primaria y secundaria

Temas IA: IA y educación estudio empírico

Resumen:

The advent of artificial intelligence (AI) in the workplace is pressuring employees to learn how to harness this technology. The goal of promoting AI literacy is to equip educated citizens with the readiness to apply AI. The aim of this study is to provide evidence to guide the development of an AI Literacy Framework to prepare educated citizens to participate in future society. We report on a 14-h AI literacy course for senior secondary students, emphasising problem-solving competence development and adopting the project-based learning approach. One hundred and twenty-eight students completed the course, and a mixed-methods analysis was conducted to evaluate the results. A post-course test...

Exploring ChatGPT adoption among business and management students through the lens of diffusion of Innovation Theory

Alaa Amin Abdalla, Mohd Abass Bhat, Chandan Kumar Tiwari (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ChatGPT educación superior

Temas IA: chatGPT estudio empírico

Resumen:

Purpose: this study aims to present an innovative approach (Diffusion of Innovation Theory) to investigate the adoption of ChatGPT by business and management students. The theory emphasizes integrating the variables Viz. relative advantage, compatibility, complexity, trialability, observability, attitude, and intention to adopt ChatGPT in the context of management education. Method: ology: a non-probability purposive sample of 383 students enrolled in management of Indian public and private institutions was taken to conduct survey to administer questionnaires. Partial Least Square-Structural Equation Modelling was employed to analyze the data using Smart PLS software. Findings: the findings...

Pre-service teachers preparedness for AI-integrated education: An investigation from perceptions, capabilities, and teachers’ identity changes

Lihang Guan, Yue Zhang, Mingyue Michelle Gu (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial formación de profesores creencias y actitudes de los profesores

Temas IA: IA y educación estudio empírico

Resumen:

Artificial intelligence (AI) has provided numerous learning benefits due to and beyond its personalization capabilities. AI significantly alters the interaction dynamics among students, teachers, and technology, necessitating the collaborative integration of AI in education instead of mere mechanical use. This study investigates pre-service teachers' perceptions and capabilities within the framework of social cognitive theory, focusing on their attitudes, intentions, self-efficacy, and AI literacy for effective AI integration. We discuss how these perceptions and capabilities help pre-service teachers prepare for the changing identities of being a teacher in AI-integrated education....

Is GPT-4 fair? An empirical analysis in automatic short answer grading

Luiz Rodrigues, Cleon Xavier, Newarney Costa (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial evaluación grandes modelos de lenguaje

Temas IA: IA y evaluación modelos de lenguaje (LLM) ética de la IA

Resumen:

Short open-ended questions represent a central resource in formative and summative assessments both face-to-face and online settings, ranging from elementary to higher education. However, grading these questions remains challenging for instructors, raising attention to the field of Automatic Short Answer Grading (ASAG). While ASAG has yielded valuable contributions to learning analytics, it often faces generalizability issues. Accordingly, the rapid advancement in Large Language Models (LLMs) has motivated their adoption to empower ASAG systems. Despite that, previous research has not investigated whether LLMs are fair graders in the context of ASAG. Therefore, this paper presents an...

Evaluating adaptive and generative AI-based feedback and recommendations in a knowledge-graph-integrated programming learning system

Lalita Na Nongkhai, Jingyun Wang, Adam Wynn (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial pensamiento computacional feedback/retroalimentación

Temas IA: modelos de lenguaje (LLM) IA y aprendizaje estudio empírico

Resumen:

This paper introduces the design and development of a framework that integrates a large language model (LLM) with a retrieval-augmented generation (RAG) approach leveraging both a knowledge graph and user interaction history. The framework is incorporated into a previously developed adaptive learning support system to assess learners’ code, generate formative feedback, and recommend exercises. Moreover, this study examines learner preferences across three instructional modes: adaptive, Generative AI (GenAI), and hybrid GenAI–adaptive. An experimental study was conducted to compare the learning performance and perception of the learners, and the effectiveness of these three modes using four...

Students’ multimodal prompting practices as epistemic work in AI literacy development

Sylvana Sofkova Hashemi (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial alfabetización en IA multimodalidad

Temas IA: prompts IA y educación estudio empírico

Resumen:

: As generative artificial intelligence (GenAI) rapidly transforms higher education, critical questions arise about how students engage with these open-ended tools and the implications for learning. This study provides empirical insight into this research gap investigating (1) the prompting strategies students develop when interacting with a university-provided GenAI tool and (2) how engagement in prompt engineering activities shapes their understanding of GenAI and AI literacy. Data were collected in an exploratory workshop with 28 postgraduate students engaged in collaborative multimodal prompting tasks, including the creation of short stories or poems and corresponding images. Students’...

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 enseñanza en línea e híbrida analítica del aprendizaje

Temas IA: IA y aprendizaje estudio empírico

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...