Black-Liberation.Tech

Black-Liberation.Tech

por Renée Jordan, Ph.D.
Temporada 8
Reading Is Thinking
AI Can Help You Read—But It Can't Do the Thinking for You What happens after AI explains a difficult reading? In this episode of AI for Academic Success, Dr. Renée Jordan completes the Module 1 walkthrough by exploring Janiyah GPT's response to Ashley's Excellence Exploration, featuring Latinas, Afro-Latinas, and Black women whose reading, research, curiosity, scholarship, and lifelong learning contributed to discovery, leadership, and community change. Then, the focus shifts away from prompting AI and back to the learner. Through the Scholar Reflection, Learning Connection, and “Try It Like Dr. Shirley Ann Jackson” activity, we explore active reading, noticing confusion, creating a Reading Reflection Log, asking AI for targeted support, checking understanding, and reflecting on growth. The central lesson: AI can support the reading process, but reading is still thinking—and that thinking belongs to you.
Exploring Excellence Through Reading, Research & Curiosity
What can the lives and work of accomplished women teach us about becoming stronger learners? In Part 5 of the AI for Academic Success Module 1 walkthrough, Dr. Renée Jordan continues the conversation with Jasmine and Janiyah GPT through an Excellence Exploration. This time, AI is prompted to identify Latinas, Afro-Latinas, and Black women whose reading, research, scholarship, scientific inquiry, writing, and lifelong learning contributed to discovery, innovation, leadership, education, and community change. The exploration introduces Dr. Shirley Ann Jackson, Ellen Ochoa, Dr. María Elena Bottazzi, Dr. Marta Moreno Vega, Dr. Alexa Canady, and Dr. Mae Jemison and considers the learning habits that may have supported their work. But the purpose isn't simply to generate a list of accomplished women. It's to ask a more meaningful question: What can learners take from their approaches to curiosity, careful reading, research, questioning, critical thinking, and lifelong learning—and practice in their own lives today? This episode explores how AI can support culturally responsive learning by helping students make connections between the academic skills they are developing now and people who have used those skills to expand knowledge, challenge barriers, serve communities, and create new possibilities.
Can AI Help You Think Through Information Overload?
AI for Academic Success What happens when the challenge isn't finding information—but figuring out what matters? In this episode of AI for Academic Success, Dr. Renée Jordan continues testing the Module 1 tutoring prompt through Jasmine, a composite learner navigating a digital literacy course and the very real challenge of information overload. Using a passage about digital literacy, online information, privacy, and responsible technology use, we examine whether AI can do more than summarize. Can it explain ideas clearly, build useful connections, introduce vocabulary, and ask questions that strengthen a learner's own understanding? Along the way, we explore an important tension: AI can help organize information, but it can also become one more source of information to manage. The goal isn't to have AI do the learning. It's to see whether thoughtful prompting can help a learner move from more information to better understanding—while keeping the learner responsible for questioning, evaluating, and deciding. How to use AI for academic success; using ChatGPT as a tutor not an answer machine; AI and information overload for students; how students can evaluate online information; digital literacy and artificial intelligence; responsible AI use for students; using AI to understand difficult concepts; how to use ChatGPT without replacing learning; AI tutoring and critical thinking; managing too much information online
AI as a Reading Coach: Putting the Homework Help Lab to the Test
AI as a Reading Coach: Putting the Homework Help Lab to the Test | AI for Academic Success What happens when we move from talking about responsible AI use to actually putting it into practice? In this episode of the Black-Liberation.Tech Podcast, Dr. Renée Jordan begins a test run of the AI for Academic Success: Homework Help Lab by stepping into representative learner perspectives from the Black-Liberation.Tech ecosystem. Using Ashley's composite learning scenario, we explore an AP Environmental Science prompt focused on environmental justice, community health, climate change, and fairness. Rather than asking AI to summarize a reading or provide an answer, the prompt positions AI as a reading coach—helping the learner unpack vocabulary, make connections, consider why a concept matters, and check her own understanding. Along the way, we explore a larger question at the heart of AI literacy: Can AI help us understand something more deeply without doing the thinking for us? This episode demonstrates what it can look like to use AI as a tutor and thinking partner—not a replacement for reading, reasoning, curiosity, or learner judgment. Ashley and Jasmine represent composite learning scenarios created for educational demonstration. They are not real student records or graded assignments. How to use AI to understand difficult readings; using AI as a tutor instead of an answer machine; AI reading comprehension prompts for students; responsible AI use for homework; environmental justice AP Environmental Science; using ChatGPT for studying without cheating; culturally responsive AI literacy
AI as Your Reading Coach
Read with Curiosity, Learn Through Questions What if asking questions while you read isn't a sign that you don't understand—but evidence that you're actively learning? In this episode of the Black-Liberation.Tech AI for Academic Success series, Dr. Renée Jordan enters the Homework Help Lab and begins putting the workbook's learning strategies into practice. First, meet the Homework Help Lab Scholars and Nevaeh, a learner beginning to discover how artificial intelligence can serve as a thinking partner. Then meet Rosario, whose story introduces the first learning strategy: reading with questions. Through the Help Me Understand What I Read activity, Dr. Jordan explores how learners can prompt AI to help them identify important vocabulary, define key terms, make connections to what they already know, understand why ideas matter, and generate questions that check their understanding. The episode also examines an important boundary: AI should support the reading process, not replace it. Learners remain responsible for reading the source material, evaluating AI's explanations, protecting private or restricted information, and doing the thinking necessary to build their own understanding. Because strong readers don't need to have all the answers. They remain curious enough to keep asking better questions.
Using AI as a Thinking Partner, Not a Replacement
What happens when the workshop ends—but you stay for the credits? In this introductory episode of the Black-Liberation.Tech podcast’s AI for Academic Success series, Dr. Renée Jordan introduces the AI for Academic Success: Homework Help Lab workbook—an “Easter egg” originally created for learners who reached the end of the AG-STEM Career Exploration workshop. Learn how the workbook was developed through instructional design, research, contributor insights, and collaboration with generative AI tools. Dr. Jordan also discusses its Creative Commons Attribution-NonCommercial license, introduces Janiyah GPT as an AI learning companion, and explains how to use the workbook. Most importantly, this episode establishes a principle that will guide the entire series: AI is a thinking partner, not a replacement. AI can help learners understand difficult concepts, ask questions, organize information, practice skills, and receive feedback—but curiosity, judgment, creativity, lived experience, and voice remain with the learner. The goal isn't simply to finish faster. The goal is to learn.
What's your next move?
The Future Is Built One Step at a Time What if the most important part of career exploration isn't choosing a career—but choosing your next step? In this episode of the Black-Liberation.Tech Podcast, we conclude our Ag-STEM Career Discovery Lab Walkthrough with Step 9: Choose Your Next Step. Career exploration is not about having all the answers. It is about taking meaningful steps toward learning, growth, and discovery. Throughout this series, we explored careers, educational pathways, role models, workplace environments, AI literacy, community impact, and the future of work. Now it is time to put that learning into action. In this episode, we explore practical next steps that students can take over the next two weeks, including: • Researching a college major • Comparing universities and programs • Interviewing professionals • Joining a STEM or Agriculture organization • Creating a portfolio project • Learning a new skill Listeners will learn how small actions can create momentum and help transform interests into opportunities. Most importantly, this episode reminds us that career pathways are rarely linear. Many of today's emerging opportunities exist at the intersection of agriculture, technology, community needs, sustainability, artificial intelligence, and innovation. Reflection Questions: • Which next step feels most exciting? • Which next step feels challenging? • What strengths can you bring to that experience? • What would success look like two weeks from now? • How might this action help shape your future pathway? Because exploration becomes meaningful when it leads to action. And every journey begins with a single step. Explore the Black-Liberation.Tech Ecosystem: Access the Free Open Educational Resource (OER): Black-Liberation.Tech Join the Patreon Community for Exclusive Coaching: patreon.com/BlackLiberationTech Partner with Jordan Nuance LLC for Your Organization: jordan-nuance.com
Turning Interests Into Impact
What if choosing a career isn't just about what you want to do—but about the problems you want to help solve? In this episode of the Black-Liberation.Tech Podcast, we continue our Ag-STEM Career Discovery Lab Walkthrough with Step 8: Community Impact Challenge. Career exploration is about more than finding a job. It is about discovering how your interests, talents, and future career can contribute to your community and help solve real-world challenges. In this episode, we explore how Ag-STEM careers can address issues such as food insecurity, environmental justice, climate resilience, community health, and economic opportunity in underserved communities. Using examples such as Community Food Systems Planner, Public Health and Agricultural Data Scientist, and Community Resilience Planner, we examine how professionals combine science, technology, agriculture, data, policy, and community engagement to create positive change. Listeners will learn how to: • Connect personal interests to community needs • Explore careers that create social impact • Understand how Ag-STEM careers improve quality of life • Examine the role of AI, technology, and data in community problem-solving • Reflect on how their own skills and passions can contribute to a better future Most importantly, this episode encourages learners to see themselves not only as future professionals, but also as future problem-solvers, innovators, advocates, and community leaders. Reflection Questions: • Which community challenge interests you most? • How might your talents help address that challenge? • What role could you imagine yourself playing? • How could technology support your efforts? • What impact would you like your future career to have on your community? Because career exploration is not only about what you do. It is also about who you help and the difference you make. Explore the Black-Liberation.Tech Ecosystem: Access the Free Open Educational Resource (OER): Black-Liberation.Tech Join the Patreon Community for Exclusive Coaching: patreon.com/BlackLiberationTech Partner with Jordan Nuance LLC for Your Organization: jordan-nuance.com
AI Literacy for Scholars
Becoming a Critical Consumer of AI Information What if the most important AI skill isn't learning how to get an answer—but learning how to determine whether the answer should be trusted? In this episode of the Black-Liberation.Tech Podcast, we continue our Ag-STEM Career Discovery Lab Walkthrough with Step 7: Verify Then Trust. Artificial Intelligence can be a powerful thinking partner, but it is not perfect. Strong AI users understand that every response should be evaluated, questioned, and verified before being accepted as accurate. In this episode, we explore how learners can critically evaluate information generated by AI while researching careers, educational pathways, emerging technologies, and social issues. Using the example of Community Resilience Planning, we examine how AI responses may contain limitations, omissions, biases, simplified explanations, or incomplete perspectives. We discuss why it is important to compare AI-generated information with trusted sources, including government agencies, universities, research institutions, and professional organizations. Listeners will learn how to: • Identify potential limitations in AI responses • Recognize bias, omissions, and incomplete perspectives • Verify information using .gov and .edu sources • Compare multiple viewpoints and sources of evidence • Ask stronger follow-up questions • Develop habits used by researchers, scholars, scientists, and informed citizens Most importantly, this episode emphasizes that AI literacy is not about blindly trusting technology. It is about learning how to think critically, evaluate evidence, and make informed decisions. Reflection Questions: • Did the AI response include multiple perspectives or only one? • What information should be verified independently? • What details were missing or underrepresented? • How did comparing sources change your understanding? • What questions would you ask next? Because responsible AI use begins with curiosity, critical thinking, and verification. Remember: Trust is not automatic. Trust is earned through evidence. Explore the Black-Liberation.Tech Ecosystem: Access the Free Open Educational Resource (OER): Black-Liberation.Tech Join the Patreon Community for Exclusive Coaching: patreon.com/BlackLiberationTech Partner with Jordan Nuance LLC for Your Organization: jordan-nuance.com
Using AI to Bring Careers to Life
What if the difference between curiosity and confidence is being able to see yourself in the role? In this episode of the Black-Liberation.Tech Podcast, we continue our Ag-STEAm Career Discovery Lab Walkthrough with Step 6: Visualize the Role. Career titles often sound interesting, but they can also feel distant and difficult to imagine. What does an Agricultural Drone Operations Specialist actually do every day? What tools does an Urban Agriculture Manager use? What does the workspace of a Product Designer or Residential Architect look like? In this episode, we explore how AI image generation can help transform abstract career titles into visual experiences that support deeper learning, reflection, and career exploration. Using examples from agriculture, technology, design, engineering, sustainability, and interdisciplinary careers, we discuss how learners can use AI to create visual representations of professionals at work, examine the tools and technologies they use, and better understand the environments where these careers take place. More importantly, we explore the questions that come after the image is generated: • What surprised you? • Did the image match your expectations? • Who was represented? • Who was missing? • How might your own experiences, talents, and interests connect to this role? This episode encourages listeners to use AI not simply as a content generator, but as a thinking partner for career discovery, self-reflection, and expanding what is possible. Whether you are exploring Ag-STEAm careers, STEM pathways, creative technology fields, public service careers, or interdisciplinary professions, visualization can help turn curiosity into clarity. Reflection Questions: • What surprised you most about the career visualization? • How did the image challenge or reinforce your assumptions? • What tools, technologies, and skills were represented? • Who was visible in the image, and who was absent? • How might you redesign the image to better reflect your own community and experiences? Because sometimes seeing a possibility is the first step toward becoming it. Explore the Black-Liberation.Tech Ecosystem: Access the Free Open Educational Resource (OER): Black-Liberation.Tech Join the Patreon Community for Exclusive Coaching: patreon.com/BlackLiberationTech Partner with Jordan Nuance LLC for Your Organization: jordan-nuance.com
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