Big data and algorithmic bias in education: what is it and why does it matter?

Ed-Technical

27:52

We made it— 300 episodes of This Is Woman’s Work ! And we’re marking this milestone by giving you something that could seriously change the game in your business or career: the skill of pitching yourself effectively. Whether you’re dreaming of being a podcast guest, landing a speaking gig, signing a client, or just asking for what you want with confidence—you’re already pitching yourself, every day. But are you doing it well? In this milestone episode, Nicole breaks down exactly how to pitch yourself to be a podcast guest … and actually hear “yes.” With hundreds of pitches landing in her inbox each month, she shares what makes a guest stand out (or get deleted), the biggest mistakes people make, and why podcast guesting is still one of the most powerful ways to grow your reach, authority, and influence. In This Episode, We Cover: ✅ Why we all need to pitch ourselves—and how to do it without feeling gross ✅ The step-by-step process for landing guest spots on podcasts (and more) ✅ A breakdown of the 3 podcast levels: Practice, Peer, and A-List—and how to approach each ✅ The must-haves of a successful podcast pitch (including real examples) ✅ How to craft a pitch that gets read, gets remembered, and gets results Whether you’re new to pitching or want to level up your game, this episode gives you the exact strategy Nicole and her team use to land guest spots on dozens of podcasts every year. Because your voice deserves to be heard. And the world needs what only you can bring. 🎁 Get the FREE Podcast Pitch Checklist + Additional Information on your Practice Group, Peer Group, and A-List Group Strategies: https://nicolekalil.com/podcast 📥 Download The Podcast Pitch Checklist Here Related Podcast Episodes: Shameless and Strategic: How to Brag About Yourself with Tiffany Houser | 298 How To Write & Publish A Book with Michelle Savage | 279 How To Land Your TED Talk and Skyrocket Your Personal Brand with Ashley Stahl | 250 Share the Love: If you found this episode insightful, please share it with a friend, tag us on social media, and leave a review on your favorite podcast platform! 🔗 Subscribe & Review: Apple Podcasts | Spotify | Amazon Music…

大约1年之前 25:22

MP3•单集首页

Ryan provides an overview of educational data mining (otherwise known as EDM) and explains how insights from EDM can help improve learner engagement and outcomes. Libby and Owen also explore the technical aspects of algorithmic bias with Ryan, discussing why it matters, how it is defined, and how it can be addressed from a technical perspective.

Links:

Ryan Baker biography
One of Ryan Baker’s research papers about algorithmic bias
Big Data and Education - Ryan Baker’s free massive online open textbook

Join us on social media:

BOLD (@BOLD_insights), Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel)
Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical
Subscribe to BOLD’s newsletter: https://bold.expert/newsletter
Stay up to date with all the latest research on child development and learning: https://bold.expert

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

33集单集

#Arts #Owen

Big data and algorithmic bias in education: what is it and why does it matter?

Ed-Technical

published 大约1年之前

MP3•单集首页

Links:

Ryan Baker biography
One of Ryan Baker’s research papers about algorithmic bias
Big Data and Education - Ryan Baker’s free massive online open textbook

Join us on social media:

BOLD (@BOLD_insights), Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel)
Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical
Subscribe to BOLD’s newsletter: https://bold.expert/newsletter
Stay up to date with all the latest research on child development and learning: https://bold.expert

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

33集单集

#Arts #Owen

所有剧集

1
Mimicry versus meaning: why context is important for AI tools 22:06

25天之前22:06

22:06

Another live Ed-Technical episode! In this short, Owen does a deep dive on AI and discourse analysis (the study of how meaning is constructed through language) with three experts. The conversation explores the intersection between AI, particularly Large Language Models (LLMs), and the study of discourse. This is a topical conversation as LLM capabilities continue to evolve. LLMs have mastered sentence level communication. However we know less about their ability to be useful over the course of a full conversation and complex and interactive processes (like learning) that require deeper appreciation of context. Featuring: Pani Kendeu: Professor at the University of Minnesota, researching learning, cognition, and technology, and a former elementary school teacher. Alyssa Wise: Professor of Technology and Education at Vanderbilt University, directing the Live Learning Innovation Incubator which bridges technology with real-world classroom challenges. Art Graesser: Professor at the University of Memphis, co-founder of the Institute for Intelligent Systems and the Society for Text and Discourse. Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
Live from SXSW EDU: Evidence Eats AI for Breakfast 31:21

5 weeks之前31:21

31:21

Everyone is talking about AI’s power to provide answers, but what about your lingering questions? What does the latest research actually tell us? Join Libby and Owen for this live session from SXSW EDU as they delve into the latest research to uncover where AI is truly adding value in the educational landscape — and where it falls short. They’re joined by two expert guests: Kristen DiCerbo from Khan Academy and Assistant Professor Peter Bergman from University of Texas at Austin and Learning Collider. The group discusses the most pressing open questions and key findings from the latest research. Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
181 Papers Later: What We Know (and Don't) About GenAI in Schools 15:42

8 weeks之前15:42

15:42

In this episode, Owen and Libby chat with Chris Agnew about Stanford's new generative AI hub for education. Chris leads this initiative within Stanford's SCALE program, which aims to be a trusted source for education system leaders on what works in AI and learning. Chris walks us through their research repository of 181 papers examining AI's impact in K-12 education. He outlines their GenAI tools typology which breaks down AI applications into three categories: efficiency gains, improving student outcomes, and reimagining schooling. The conversation explores key research gaps, including how schools can productively engage with teachers' unions on AI adoption and understanding how students use AI tools for homework - the "elephant in the room" that keeps education leaders up at night. Before joining Stanford, Chris worked in non-traditional learning environments from wilderness education to apprenticeship programs. He shares both aspirational and practical visions for AI in education over the next five years - though sadly, none involve Owen's hoped-for cyborg centaur tutors (yet). Links: Stanford Accelerator for Learning SCALE Initiative Generative AI Research Repository Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
Is two years of learning possible in six weeks with AI? 8:43

10 weeks之前8:43

8:43

In this short, Owen and Libby discuss a recent World Bank blog post about a study in Nigeria that evaluated the impact of Microsoft Copilot (powered by ChatGPT) on student learning outcomes. In a six-week after school programme, students were supported to use Copilot. The full study hasn’t been published yet but the blog post reports “overwhelmingly positive effects on learning outcomes”. It reports that the learning improvement over the six-week programme was equivalent to nearly two years of typical learning. Owen has a few questions about this… Link World Bank blog post ‘From chalkboards to chatbots: Transforming learning in Nigeria, one prompt at a time’ Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
Babies & AI: what can AI tell us about how babies learn language? 35:00

12 weeks之前35:00

35:00

In this episode, Libby and Owen interview Mike Frank, Professor at Stanford University and leading expert in child development. This episode has a different angle to the others, as it is more about AI as a scientific instrument rather than as a tool for learning. Libby and Owen have a fascinating discussion with Mike about language acquisition and what we can learn about language learning from large language models. Mike explains some of the differences between how large language models develop an understanding of human language versus how babies do this. There are some big questions touched on here, including how much of the full human experience it’s possible to capture in data. Libby and Owen also make excellent use of Mike’s valuable time by asking for his expert view on why infants find unboxing videos - videos of other children opening gifts - so addictive. Links Mike Frank’s biography New York Times piece about Mike’s work An interview with Mike about his research Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
Teachers & ChatGPT: 25.3 extra minutes a week 10:55

14 weeks之前10:55

10:55

In this short, Libby and Owen discuss a hot-off-the-press study that is one of the first to test how ChatGPT impacts the time science teachers spend on lesson preparation . The TLDR is that teachers who used ChatGPT, with a guide, spent 31% less time preparing lessons - that’s 25.3 minutes per week on average. This very promising result points to the potential for ChatGPT and similar generative AI tools to help teachers with their workload . However we encourage you to dig into the summary and report to go beyond the headline result (after listening to this episode) - this is a rich and rigorous study with lots of other interesting findings! Links EEF summary Full study Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
How & why did Google build an education specific LLM? (part 2/3) 38:22

18 weeks之前38:22

38:22

This episode is the second in our three-part mini-series with Google, where we find out how one of the world’s largest tech companies developed a family of large language models specifically for education, called LearnLM. This instalment focuses on the technical and conceptual groundwork behind LearnLM. Libby and Owen speak to three expert guests from across Google, including DeepMind, who are heavily involved in developing LearnLM. One of the problems with out-of-the-box large language models is that they’re designed to be helpful assistants, not teachers. Google was interested in developing a large language model better suited to educational tasks, that others might use as a starting point for education products. In this episode, members of the Google team talk about how they approached this, and why some of the subtleties of good teaching makes this an especially tricky undertaking! They describe the under-the-hood processes that turn a generic large language model into something more attuned to educational needs. Libby and Owen explore how Google’s teams approached fine-tuning to equip LearnLM with pedagogical behaviours that can’t be achieved by prompt engineering alone. This episode offers a rare look at the rigorous, iterative, and multidisciplinary effort it takes to reshape a general-purpose AI into a tool that has the potential to support learning. Stay tuned for our next episode in this mini-series, where Libby and Owen take a step back and look at how to define tutoring and assess the extent to which an AI tool is delivering. Team biographies Muktha Ananda is Engineering leader, Learning and Education @Google. Muktha has applied AI to a variety of domains such as gaming, search, social/professional networks and online advertisement and most recently education and learning. At Google Muktha’s team builds horizontal AI technologies for learning which can be used across surfaces like Search, Gemini, Classroom, and YouTube. Muktha also works on Gemini Learning. Markus Kunesch is a Staff Research Engineer at Google DeepMind and tech lead of the AI for Education research programme. His work is focused on generative AI, AI for Education, and AI ethics, with a particular interest in translating social science research into new evaluations and modeling approaches. Before embarking on AI research, Markus completed a PhD in black hole physics. Irina Jurenka is a Research Lead at Google DeepMind, where she works with a multidisciplinary team of research scientists and engineers to advance Generative AI capabilities towards the goal of making quality education more universally accessible. Before joining DeepMind, Irina was a British Psychological Society Undergraduate Award winner for her achievements as an Experimental Psychology student at Westminster University. This was followed by a DPhil at the Oxford Center for Computational Neuroscience and Artificial Intelligence. Link The LearnLM API Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
AI tutoring part 2: How good can it get? 21:26

20 weeks之前21:26

21:26

In this episode, Owen and Libby chat about AI tutoring with guests, Ben Kornell, Managing Partner at Common Sense Growth Fund, and Alex Sarlin, a veteran in the edtech industry. Both co-founded Edtech Insiders, a leading newsletter and podcast covering the growing Edtech industry. Ben and Alex differentiate between AI-powered search and true AI tutoring, and discuss trends like AI-enhanced human tutors, hybrid models, and fully autonomous AI bots. The conversation highlights the need for AI to integrate- and learn from traditional education in developing key elements, such as targeting the right zone of proximal development. Human tutors have the ability to sense motivation and frustration, helping students through the more challenging parts of learning. Emerging technologies are now using facial and physical cues to gauge engagement, proving valuable as nudges for AI tutors or human instructors to boost motivation or adjust level of content. They also address ethical and political risks, such as biased responses and dependency issues. With exciting developments on the horizon, the episode explores the at times seemingly sci-fi-like future of AI tutoring! Guest bios: Ben Kornell - Ben is currently serving as the Managing Partner of Common Sense Growth Fund at Common Sense Media. Prior to that, they have worked as a School Board Member for the San Carlos School District and was the Co-Founder and Podcast Host of Edtech Insiders. Alex Sarlin - Alex is a 15 year veteran of the Edtech industry, as a Product Manager and Learning Engineer at both large Edtech companies (2U, Scholastic, Chan Zuckerberg Initiative) and startups (Coursera, Skillshare, Credly, Knewton). He is currently a consultant and adviser to a number of Edtech companies in higher education and the future of work. He holds a Master's of Instructional Design from Columbia University, and is the founder of Edtech Insiders, a leading newsletter and podcast covering the growing Edtech industry. Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
Inside the black box: How Google is thinking about AI & education (part 1 of 3) 36:19

22 weeks之前36:19

36:19

This episode is the first of a three part mini-series with Google. There is a lot of interest in how big tech companies are engaging in AI and education and what their future plans are - in this mini-series, hear the latest directly from Google. The genesis of this mini-series was a short Ed-Technical episode from earlier this year. Libby and Owen discussed a paper Google released about the work they had done to fine-tune a LLM called LearnLM to make it more useful for education. This work was motivated by a realisation that some of the core behaviours of LLMs (helpfulness, sycophancy) aren’t aligned with what’s valuable from a learning perspective, and prompting can only go so far. This first episode focuses on how Google is integrating LearnLM’s capabilities into existing Google products like YouTube and new products like LearnAbout. The next episode in the mini-series will focus on LLMs and tutoring, and the final episode will be a more technical episode on the development of LearnLM. We had a chance to talk to a number of folks across a range of teams, including LearnX, Google Research and DeepMind. There was too much great content to squeeze into three episodes but all full interviews will be up on our YouTube channel. In this episode we include excerpts from interviews with four members of the team. Rob Wong is the Product Lead for LearnX, a team within Google that builds learning features on Search, YouTube, and Gemini chat, and also works on LearnLM in partnership with Google Research and Google DeepMind. Julia Wilkowski leads a pedagogy team at Google. Her team collaborates with Google product teams to apply learning science principles and teaching best practices. Markus Kunesch is a Staff Research Engineer at Google DeepMind and tech lead of the AI for Education research programme. His work is focused on generative AI, AI for education, and AI ethics, with a particular interest in translating social science research into new evaluations and modeling approaches. Angie Mac McAllister, PhD is a Group Product Manager at Google with a vision: to make a personal AI tutor available to everyone. Focused on developing learning features for Gemini, Mac combines 35 years of experience in education with cutting-edge AI to help students become better learners. Links: Google’s technical report on LearnLM Ed-Technical short episode on Google’s LearnLM paper Article about Learn About, Google’s experimental new AI tool Article by Angie Mac McAllister about new Gemini learning features Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
Big data and algorithmic bias in education: what is it and why does it matter? 25:22

26 weeks之前25:22

25:22

This episode, Owen and Libby speak to Ryan Baker, a leading expert in using big data to study learners and learning interactions with educational software. Ryan is a Professor in the Graduate School of Education at the University of Pennsylvania, and is Director of the Penn Center for Learning Analytics. Ryan provides an overview of educational data mining (otherwise known as EDM) and explains how insights from EDM can help improve learner engagement and outcomes. Libby and Owen also explore the technical aspects of algorithmic bias with Ryan, discussing why it matters, how it is defined, and how it can be addressed from a technical perspective. Links: Ryan Baker biography One of Ryan Baker’s research papers about algorithmic bias Big Data and Education - Ryan Baker’s free massive online open textbook Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
Think aloud or think before you speak?: OpenAI’s new model for advanced reasoning 10:59

28 weeks之前10:59

10:59

In this short episode, Libby and Owen discuss OpenAI’s new model for advanced reasoning, o1. They talk about its new capabilities and strengths, and what they think about its significance for education after an initial play around. They talk through the benefits of ‘think aloud’ versus ‘think before you speak’ approaches in education, and how this relates to o1. Links: OpenAI’s announcement about o1 Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
Misconceptions about misconceptions: How AI can help teachers understand & tackle student misconceptions 34:16

30 weeks之前34:16

34:16

In this episode, Libby and Owen are joined by Craig Barton, Head of Education at Eedi and host of the Mr Barton Maths and Tips for Teachers podcasts, along with Simon Woodhead, Director of Research at Eedi. Together, they explore the world of educational misconceptions—what they are, why they matter and how AI and data science can help tackle them. Links: Craig Barton biography Simon Woodhead biography Eedi’s research Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
Why Language Models are suck ups and how this can be bad for learning 11:56

32 weeks之前11:56

11:56

In this short, Libby and Owen discuss recent research from Anthropic looking at sycophancy – the tendency to agree with users – in large language models (LLMs), and key research from educational psychology about how important feedback is for learning. Libby and Owen connect the two papers and explore why sycophancy is especially a problem when it comes to using LLMs for educational purposes. Links: Anthropic paper on sycophancy in language models John Hattie and Helen Timberley’s paper, The Power of Feedback Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
Passionate about planning (and Tim Walz): automated lesson planning tools 13:36

34 weeks之前13:36

13:36

In this short, Libby and Owen discuss automated lesson planning tools (after Owen stops talking about his Tim Walz crush). There’s now a growing number of lesson planning tools out there for teachers who are using AI: Khanmigo, Magic School, Diffit and Oak National Academy (who will soon release a lesson planning tool) to name a few. Libby and Owen cover what some of the automated tools do and what some of their features are. They share their thoughts about the value and benefits of the tools. They also do a quick primer on lesson plans and how they differ from other education materials for all the non-teachers who listen. Links: Khanmigo blog about their approach to building a lesson planning tool Join us on social media: BOLD (@BOLD_insights) , Libby Hills (@Libbylhhills) and Owen Henkel (@owen_henkel) Listen to all episodes of Ed-Technical here: https://bold.expert/ed-technical Subscribe to BOLD’s newsletter: https://bold.expert/newsletter Stay up to date with all the latest research on child development and learning: https://bold.expert Credits: Sarah Myles for production support; Josie Hills for graphic design…

1
Short: Generative AI Can Harm Learning - our quick takes 10:13

36 weeks之前10:13