IA y aprendizaje

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial autoevaluación enseñanza en línea e híbrida

Temas IA: IA y evaluación IA y aprendizaje estudio empírico

Resumen:

Previous studies have found that the frequency and the regularity of taking the self-assessment are positively correlated with learning performance. However, as artificial intelligence is widely used for self-assessment in various educational contexts, numerous behaviors have been identified, including nonstandard behaviors that can negatively impact learning. Therefore, more analysis regarding students' self-assessment behaviors in different contexts and their influence on learning is required. In this study, we examined students’ behaviors in online self-assessment task and how it affects their learning performance. A 6-week experiment was conducted in an accounting course. Students were...

Directive, metacognitive, or a blend of both? A comparison of AI-generated feedback types on student engagement, confidence, and outcomes

Omar Alsaiari, Nilufar Baghaei, Jason M. Lodge (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial feedback/retroalimentación metacognición

Temas IA: IA y evaluación IA y aprendizaje estudio empírico

Resumen:

Effective feedback is a central component of successful student learning, with extensive research examining how best to implement it in educational settings. Increasingly, feedback is being generated by artificial intelligence (AI), offering scalable and adaptive responses. Two widely studied approaches are directive feedback, which gives explicit explanations and reduces cognitive load to speed up learning, and metacognitive feedback which prompts learners to reflect, track their progress, and develop self-regulated learning (SRL) skills. While both approaches have clear theoretical advantages, their comparative effects on engagement, confidence, and quality of work remain underexplored....

An interactive test dashboard with diagnosis and feedback mechanisms to facilitate learning performance

Chih-Ming Chen, Jung-Ying Wang, Li-Chieh Hsu (2021)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial tecnología educativa evaluación

Temas IA: IA y evaluación IA y aprendizaje estudio empírico

Resumen:

This study developed an interactive test dashboard with diagnosis and feedback mechanisms (ITD-DFM) that can generate visualized, rich, and high-quality test feedback for each learner’s learning reflection and review based on simultaneously considering test response time and correctness to assist students’ learning. A quasi-experimental research was conducted with 50 Grade 8 students from two classes in a public junior high school in Taiwan to assess the learning performance of ITD-DFM. One class with 26 students was assigned to the experimental group using the ITD-DFM to support learning, whereas the other class with 24 students was assigned to the control group using the traditional test...

The effectiveness of an AI-integrated VR oral training application in reducing public speaking anxiety and interview anxiety

Peiwen Huang, Yanling Hwang, Jui Ling Hsu (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial expresión oral factores afectivos

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

Resumen:

Despite the growing importance of English oral communication skills, traditional language learning approaches show limited effectiveness in simultaneously addressing psychological barriers and speaking proficiency among college students. While previous studies have explored anxiety reduction or speaking enhancement separately, a significant gap exists in research examining integrated approaches that tackle Public Speaking Anxiety (PSA), Interview Anxiety, and English-speaking proficiency improvement simultaneously. This study investigated whether an AI-integrated VR oral training application could effectively address these interconnected challenges. A quasi-experimental design was employed...

Personality traits for self-regulated learning with generative artificial intelligence: The case of ChatGPT

Xiaojing Weng, Qi Xia, Zubair Ahmad (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ChatGPT aprendizaje autónomo

Temas IA: chatGPT IA y aprendizaje estudio empírico

Resumen:

Personality traits and educational technology may affect how well students utilise their abilities and strategies to achieve their learning objectives and potential. As generative artificial intelligence (GenAI) is creating new learning experiences, understanding the impact of five representative personality traits on students' self-regulated learning (SRL) while learning with GenAI tools can help to predict which personality traits indicate better self-regulation when learning with this innovative educational technology. Such a prediction can help educators to design effective learning activities by providing educational experiences that cater to students' different personality traits for...

Chat as learning: Student–AI conversations as discipline-associated cognitive engagement patterns

Chia-Kai Chang, Kuei-Hao Li (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial analítica del aprendizaje cognición y procesamiento

Temas IA: IA y aprendizaje estudio empírico

Resumen:

Generative AI teaching assistants are increasingly adopted in higher education, yet debates persist over whether student–AI conversations engage students in genuine cognitive processes or function primarily as information retrieval. We propose “Chat as Learning,” a measurement paradigm that treats student prompts as observable externalisations of in-progress learning cognition, complementing outcome-based assessment with a process-level signal aggregable at population, course, and student scales. We adopt the term learning to denote the paradigm’s theoretical positioning; the present study measures cognitive demand reflected in students’ prompts, classified via Bloom’s Taxonomy, rather than...

ChatGPT effects on cognitive skills of undergraduate students: Receiving instant responses from AI-based conversational large language models (LLMs)

Harry Barton Essel, Dimitrios Vlachopoulos, Albert Benjamin Essuman (2024)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial ChatGPT grandes modelos de lenguaje

Temas IA: chatGPT IA y aprendizaje estudio empírico

Resumen:

This study investigated the impact of using ChatGPT, a state-of-the-art generative AI-based model, on the critical, creative, and reflective thinking skills of university students in Ghana. The study utilized a mixed-methods research approach, incorporating quantitative and qualitative data collection instruments, and an experimental procedure with a pretest-posttest control group. The study ultimately enlisted a sample of 125 students randomly allocated to either the experiment group (60 students) or the control group (65 students). The research was conducted in the context of a Research Methodology course, which had adopted the flipped classroom approach. The students in the experiment...

Generative AI interactive textbook in electrotechnics: A four-year comparative study on student performance and inclusion

Branislav Fecko, Jozef Dziak, Tibor Vince (2026)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial materiales didácticos grandes modelos de lenguaje

Temas IA: IA y creación de materiales IA y aprendizaje estudio empírico

Resumen:

This study presents the results of the implementation of Generative-AI Interactive Textbook, an intelligent textbook built on a large language model based on GPT-4, which is directly integrated into the subject of Electrical Engineering course and provides interactive, adaptive teaching functions. The textbook was deployed in the 2024/2025 academic year, and the data was compared with the summary results from 2021 to 2024. The sample consisted of 736 students. The results suggest that the effects associated with the introduction of GenAI-T vary depending on the type of assessment and the analytical context. In multi-year analyses, a statistically significant improvement in mid-term...

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...

Investigating the impact of generative AI integration on the sustenance of higher-order thinking skills and understanding of programming logic

Jemimah Nathaniel, Solomon Sunday Oyelere, Jarkko Suhonen (2025)

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial pensamiento computacional pensamiento crítico

Temas IA: IA y aprendizaje prompts estudio empírico

Resumen:

This study investigates how integrating generative AI (GenAI) with instructional scaffolding and prompt engineering supports higher-order thinking skills (HOTS) and programming logic. A mixed-methods design was used, combining quantitative and qualitative data. The intervention followed a one-group pretest-post-test structure over seven weeks with 25 computer science students with no prior C++ experience. The GenAI-Ped framework guided the design. It combines Bloom's taxonomy, Seelf-Regulated Learning, Universal Design for Learning, and Vygotsky's Zone of Proximal Development. Students received scaffolded support across six instructional phases, including prompt training and guided GenAI...