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  • Jionghao Lin

Bibliografía: Jionghao Lin

Nº de publicaciones: 4
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Are deeper reflectors better goal-setters? AI-empowered analytics of reflective writing in pharmaceutical education
Yuheng Li, Mladen Rakoviฤ‡, Wei Dai (2023)
Computers & Education: Artificial Intelligence
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

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Reflection and goal-setting are interrelated processes in well-established educational theories to promote in-depth self-reflection and self-regulated learning. Prior studies have considered reflection to be an important antecedent for meaningful goal-setting. Yet, there lacks empirical evidence to shed light on how students' abilities to reflect inform their abilities to set goals. Hence, in the present study, we aimed to quantify the connection between students' retrospective reflection and their subsequent goal-setting, and derive more in-depth insights to benefit educators in their teaching to promote deeper reflection, more specific goal-setting and better self-regulation. To this end...

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Assessing the proficiency of large language models in automatic feedback generation: An evaluation study
Wei Dai, Yi-Shan Tsai, Jionghao Lin (2024)
Computers & Education: Artificial Intelligence
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

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Assessment feedback is important to student learning. Learning analytics (LA) powered by artificial intelligence exhibits profound potential in helping instructors with the laborious provision of feedback. Inspired by the recent advancements made by Generative Pre-trained Transformer (GPT) models, we conducted a study to examine the extent to which GPT models hold the potential to advance the existing knowledge of LA-supported feedback systems towards improving the efficiency of feedback provision. Therefore, our study explored the ability of two versions of GPT models – i.e., GPT-3.5 (ChatGPT) and GPT-4 – to generate assessment feedback on students' writing assessment tasks, common in...

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Why don't teachers teach AI ethics? Understanding teachers' beliefs and intentions in Chinese AI curriculum implementation through the theory of planned behaviour
Ming Ma, Davy Tsz Kit Ng, Zhichun Liu (2025)
Computers & Education: Artificial Intelligence
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo

While artificial intelligence (AI) education is expanding globally, the implementation of AI ethics education in K-12 AI curricula remains a critical challenge, particularly in top-down curriculum reform contexts like China. This study investigates the factors influencing secondary information technology (IT) teachers' intention to teach AI ethics, grounding in Theory of Planned Behaviour (TPB). Through semi-structured interviews with 14 in-service teachers in China's Greater Bay Area (GBA), we identified key behavioural beliefs (e.g., fostering critical thinking, navigating rapid technological change, and adapting western-centric ethics), normative beliefs (e.g., new curriculum policy,...

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Can large language models write reflectively
Yuheng Li, Lele Sha, Lixiang Yan (2023)
Computers & Education: Artificial Intelligence
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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Texto completo en HTML

Generative Large Language Models (LLMs) demonstrate impressive results in different writing tasks and have already attracted much attention from researchers and practitioners. However, there is limited research to investigate the capability of generative LLMs for reflective writing. To this end, in the present study, we have extensively reviewed the existing literature and selected 9 representative prompting strategies for ChatGPT – the chatbot based on state-of-art generative LLMs to generate a diverse set of reflective responses, which are combined with student-written reflections. Next, those responses were evaluated by experienced teaching staff following a theory-aligned...

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