In this essay, we explored the feasibility of utilizing artificial intelligence (AI) for qualitative data analysis in equity-focused research. Specifically, we compare thematic analyses of interview transcripts conducted by human coders with those performed by GPT-3 using a zero-shot chain-of-thought prompting strategy. Our results suggest that…

Background: Existing conceptions of teaching quality assume that classroom interactions serve as the foundation for effective teaching. The resulting data necessitates analytical approaches capable of extracting the semantics of these interactions. Aim: This study investigates whether and to what extent lesson semantics provide insights into…

Coding think-aloud transcripts is time-consuming and labor-intensive. In this study, we examined the feasibility of predicting students' reasoning activities based on their think-aloud transcripts by leveraging the affordances of text mining and machine learning techniques. We collected the think-aloud data of 34 medical students as they diagnosed…

Generative Pre-trained Transformers (GPT) have shown promise as More Knowledgeable Others(MKO) for English Language Learners (ELLs) by providing on-demand, contextualized feedback within the Zone of Proximal Development (ZPD). In this study, a web app collected spoken responses from 680 adult ELLs, automatically transcribed them and sent them to…

Automated speaking assessment (ASA) of second language proficiency benefits both learners and educators. However, developing these systems for less commonly taught languages like Finnish and Finland Swedish is hindered by the need for large datasets with equal representation of all proficiency levels. Traditional machine learning algorithms used…