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Contenuto fornito da Owen Henkel & Libby Hills, Owen Henkel, and Libby Hills. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Owen Henkel & Libby Hills, Owen Henkel, and Libby Hills o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
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Season 2 : Three decades of AI in education: assessment to classroom collaboration

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Manage episode 419221987 series 3513246
Contenuto fornito da Owen Henkel & Libby Hills, Owen Henkel, and Libby Hills. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Owen Henkel & Libby Hills, Owen Henkel, and Libby Hills o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

This season Libby Hills from the Jacobs Foundation and AI researcher Owen Henkel continue to speak with leading researchers, practitioners and educators on the Ed-Technical podcast series about the cutting edge of AI in education. They will break down complex AI concepts into non-technical insights to better understand what the research says and help educators sift the useful insights from the AI hype.

In the first episode of Season 2, Libby and Owen speak with Peter Foltz about his work at the intersection of cognitive science, AI, and education over the past few decades. Peter discusses his experience building an automated essay scoring system in the late 1990s, which provided students with immediate, formative feedback on their writing. Peter reflects on the potential of large language models to enhance these systems by offering more substantive feedback to help students become better thinkers, not just better writers.

They then discuss the challenges and opportunities of using speech-to-text AI in educational settings. Peter’s team uses AI to analyze student conversations during group work, providing insights into collaboration, respect, and equity within teams that is fed back to the students to reward positive contributions. Despite the technical difficulties of accurately capturing audio in noisy classrooms, Peter highlights the potential of these tools to support teachers in assessing and fostering effective teamwork among students. They also touch on the importance of co-designing these technologies with teachers, students, and parents to ensure their appropriate and acceptable use in the classroom.

Guest and resources

Join us on social media:

Credits: Sarah Myles for production support; Josie Hills for graphic design

  continue reading

14 episodi

Artwork
iconCondividi
 
Manage episode 419221987 series 3513246
Contenuto fornito da Owen Henkel & Libby Hills, Owen Henkel, and Libby Hills. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Owen Henkel & Libby Hills, Owen Henkel, and Libby Hills o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

This season Libby Hills from the Jacobs Foundation and AI researcher Owen Henkel continue to speak with leading researchers, practitioners and educators on the Ed-Technical podcast series about the cutting edge of AI in education. They will break down complex AI concepts into non-technical insights to better understand what the research says and help educators sift the useful insights from the AI hype.

In the first episode of Season 2, Libby and Owen speak with Peter Foltz about his work at the intersection of cognitive science, AI, and education over the past few decades. Peter discusses his experience building an automated essay scoring system in the late 1990s, which provided students with immediate, formative feedback on their writing. Peter reflects on the potential of large language models to enhance these systems by offering more substantive feedback to help students become better thinkers, not just better writers.

They then discuss the challenges and opportunities of using speech-to-text AI in educational settings. Peter’s team uses AI to analyze student conversations during group work, providing insights into collaboration, respect, and equity within teams that is fed back to the students to reward positive contributions. Despite the technical difficulties of accurately capturing audio in noisy classrooms, Peter highlights the potential of these tools to support teachers in assessing and fostering effective teamwork among students. They also touch on the importance of co-designing these technologies with teachers, students, and parents to ensure their appropriate and acceptable use in the classroom.

Guest and resources

Join us on social media:

Credits: Sarah Myles for production support; Josie Hills for graphic design

  continue reading

14 episodi

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