Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

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Automating the process of qualitatively coding text data from learners has been a long-standing ambition of learning analytics researchers since it represents an essential step toward delivering timely and scalable feedback. Automating this process is especially challenging in the case of ordered coding schemes —necessary for temporal analytical methods— where one text utterance can be assigned more than one qualitative code and the assignment order matters. This problem goes beyond multi-class and multi-label classification and, therefore, cannot be easily tackled using classic language models such as BERT. Recent advances in generative artificial intelligence, especially with the advent...

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

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This study examines how generative AI can support middle school scientific inquiry in a rural agriculture-STEM classroom. Using a mixed-methods design with concurrent data collection and sequential analytic integration, we analyzed 42 eighth-grade students, organized into 12 groups, as they used Aspen, a custom AI chatbot, to revise scientific research questions and hypotheses around a sustainable agriculture problem. Data sources included group project journals, AI interaction logs, and peer discussion transcripts. First, a two-dimensional profiling method categorized the 12 groups into four analytic profiles: Struggling, Most Improved, Perfectionists, and High Achievers, based on initial...

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

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Currently, many generative Artificial Intelligence (AI) tools are being integrated into the educational technology landscape for instructors. Our paper examines the potential and challenges of using Large Language Models (LLMs) to code student-generated content in online discussions based on intended learning outcomes and how instructors could use this to assess the intended and enacted learning design. If instructors were to rely on LLMs as a means of assessment, the reliability of these models to code the data accurately is crucial. Employing a diverse set of LLMs from the GPT family and prompting techniques on an asynchronous online discussion dataset from a blended-learning bachelor-...

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