estudio empírico

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ChatGPT educación superior

Temas IA: chatGPT estudio empírico

Resumen:

Students and researchers are increasingly relying on ChatGPT as a tool to search for information, generate content, make translations and offer research support. This study employs nine variables derived from the Technology Acceptance Model to evaluate whether the variables can predict ChatGPT use among university students in the Philippines. To achieve this, a survey was carried out. Data was collected from 340 students across various faculties of a university. The data were analyzed with structural equation modeling (SEM). The model predicts that the nine variables that reflect students' perceptions towards ChatGPT, are indirectly or directly related to the students' use of ChatGPT. The...

An exploration of the role of generative AI in fostering creativity in architectural learning environments

Carlos Medel-Vera, Sandy Britton, William Francis Gates (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial educación superior creencias y actitudes de los estudiantes

Temas IA: prompts IA y educación estudio empírico

Resumen:

This paper explores the role of generative AI (GenAI) in supporting creativity within architectural education through the lens of a student-led AI drawing competition. The research addresses two questions: (1) how creative are students' text prompts and the resulting AI-generated images, and is there a relationship between them? and (2) to what extent do students perceive GenAI as a supportive tool in their creative process? Drawing on a mixed-methods approach, the study combines semantic analysis of text prompts, aesthetic evaluation of AI-generated images, and a Creativity Support Index (CSI) survey, complemented by sentiment analysis of student feedback. The semantic analysis reveals...

Predictive learning analytics in online education: A deeper understanding through explaining algorithmic errors

Martin Hlosta, Christothea Herodotou, Tina Papathoma (2022)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial analítica del aprendizaje enseñanza en línea e híbrida

Temas IA: IA y educación estudio empírico

Resumen:

Existing Predictive Learning Analytics (PLA) systems utilising machine learning models show they can improve teacher practice and, at the same time, student outcomes. The accuracy, and related errors, of these systems can negatively influence their adoption. However, little effort has been made to investigate the errors made by the underlying models. This study focused on errors of models predicting students at risk of not submitting their assignments. We analysed two groups of error when the model was confident about the prediction: (a) students predicted to submit their assignment, yet they did not (False Negative; FN), and (b) students predicted not to submit their assignment yet they...

Face value: How avatar identity shapes epistemic trust in AI-mediated learning

Zach Anthis, Avgousta Kyriakidou-Zacharoudiou (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial inclusión y equidad creencias y actitudes de los estudiantes

Temas IA: ética de la IA IA y aprendizaje estudio empírico

Resumen:

AI tutors are becoming the new faces of digital classrooms, but these faces may determine who is trusted and who is ignored. Anthropomorphic avatars designed to increase engagement, may also activate social heuristics that reproduce offline patterns of bias. Yet little empirical research has examined how these identity cues shape epistemic trust and enacted reliance in AI-mediated learning. This study addresses this gap by systematically isolating their effects on learners' evaluative judgments and behavioral uptake in diverse learning contexts. Two experiments examined how avatar race, gender, and age shape trust in AI-mediated education. Study 1 (N = 102) used a within-subjects laboratory...

Understanding self-directed learning in AI-Assisted writing: A mixed methods study of postsecondary learners

Chaoran Wang, Zixi Li, Curtis Bonk (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial expresión escrita aprendizaje autónomo

Temas IA: IA y enseñanza-aprendizaje de lenguas chatGPT IA y aprendizaje

Resumen:

This study investigates how postsecondary learners employ generative AI, specifically ChatGPT, to support their self-directed learning (SDL) for writing purposes. Following a sequential mixed methods design, we analyzed 384 survey responses and 10 semi-structured interviews with postsecondary writers. Findings suggest that the major learning task that the learners used ChatGPT for writing is brainstorming and seeking inspiration for ideas. While the entering motivation for using ChatGPT varies from curiosity about innovative technologies to fulfilling academic requirements, such entering motivation transformed into task motivation when the learners perceived the potential benefits of...

Diverging perceptions of artificial intelligence in higher education: A comparison of student and public assessments on risks and damages of academic performance prediction in Germany

Marco Lünich, Birte Keller, Frank Marcinkowski (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial analítica del aprendizaje ética

Temas IA: ética de la IA estudio empírico

Resumen:

The integration of Artificial Intelligence (AI) into higher education, particularly through Academic Performance Prediction (APP), promises enhanced educational outcomes. However, it simultaneously raises concerns regarding data privacy, potential biases, and broader socio-technical implications. Our study, focusing on Germany–a pivotal player in shaping the European Union's AI policies–seeks to understand prevailing perceptions of APP among students and the general public. Initial findings of a large standardized online survey suggest a divergence in perceptions: While students, in comparison to the general population, do not attribute a higher risk to APP in a general risk assessment,...

Beyond accuracy: Multimodal modeling of structured speaking skill indices in young adolescents

Candy Olivia Mawalim, Chee Wee Leong, Guy Sivan (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial expresión oral evaluación

Temas IA: IA y enseñanza-aprendizaje de lenguas IA y evaluación estudio empírico

Resumen:

This study introduces a novel method for explainable speaking skill assessment that utilizes a unique dataset featuring video recordings of conversational interviews for high-stakes outcomes (i.e., admission to high schools and universities). Unlike traditional automated speaking assessments that prioritize accuracy at the expense of interpretability, our approach employs a new multimodal dataset that integrates acoustic and linguistic features, visual cues, turn-taking patterns, and expert-derived scores quantifying various speaking skill aspects observed during interviews with young adolescents. This dataset is distinguished by its open-ended question format, which allows for varied...

Evaluating large language models as raters in large-scale writing assessments: A psychometric framework for reliability and validity

Yuehan Wang, Jinyan Huang, Lun Du (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial expresión escrita evaluación

Temas IA: IA y enseñanza-aprendizaje de lenguas IA y evaluación modelos de lenguaje (LLM)

Resumen:

In large-scale international writing assessments, human raters often exhibit inconsistency, undermining reliability and validity. Large language models (LLMs) offer a potential solution, but their assessment reliability remains underexplored. This study employed generalizability theory and many-facet Rasch modeling to compare human and LLM raters across three essay genres (4315 samples).Findings reveal that human-LLM discrepancies stem from fundamental evaluation differences, with minimal divergence in key-point scoring. Humans excel in holistic scoring scenarios but struggle with complex analytical rubrics where LLMs demonstrate advantages. While LLMs perform adequately for relative...

Are pre-service teachers ready to teach the Alpha generation? The impact of pre-service teachers' ChatGPT literacy levels on behavioral intentions toward ChatGPT-4.0

Eylem Kılıç, Firas Almasri, H. Eray Çelik (2025)

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Tipo: artículo

Metodología: estudio empírico

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

Temas IA: chatGPT estudio empírico

Resumen:

This study seeks to enhance our understanding of how pre-service teachers working with the Alpha Generation (PSTAG) interact with the Technology Acceptance Model (TAM) in the context of ChatGPT. It specifically examines their perceptions of ease of use (PEOU), perceived usefulness (PU), and behavioral intention (BI) toward ChatGPT-4o, utilizing an extended version of the TAM. The survey method was used, and 450 PSTAG participated in the current study. Data were collected through a survey including the ChatGPT literacy scale (ChatGPT-LS) and TAM to determine PSTAG's ChatGPT-4o literacy level and its relationship with PEOU, PU, and BI. Thirteen hypotheses are developed to test the proposed...

Temporal pathways to learning: How learning emerges in an open-ended collaborative activity.

Jauwairia Nasir, Mortadha Abderrahim, Aditi Kothiyal (2022)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial aprendizaje colaborativo analítica del aprendizaje

Temas IA: IA y aprendizaje estudio empírico

Resumen:

The learning process depends on the nature of the learning environment, particularly in the case of open-ended learning environments, where the learning process is considered to be non-linear. In this paper, we report on the findings of employing a multimodal Hidden Markov Model (HMM) based methodology to investigate the temporal learning processes of two types of learners that have learning gains and a type that does not have learning gains in an open-ended collaborative learning activity. Considering log data, speech behavior, affective states and gaze patterns, we find that all learners start from a similar state of non-productivity, but once out of it they are unlikely to fall back into...