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Ana Cristina Pratas's insight:
Nabila bruno's curator insight,
April 26, 2023 1:20 AM
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From
fltmag
By Roberta Montella and Dan Nickolai, Saint Louis University DOI: https://www.doi.org/10.69732/RVZW4726 One of the most time-consuming tasks of lesson planning is the preparation of pedagogical resources for our language courses. This is especially true when it comes to modifying or
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As students and educators adapt to digital platforms, student engagement has emerged as a key concern in online learning. Two such approaches—microlearning and andragogy—offer promising solutions to enhance student engagement and knowledge retention.
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"One major complaint about the use of AI to generate articles and answers to real-world questions is that it “hallucinates” — that is, it makes up facts that aren’t true and creates references to articles that don’t exist.
Although AI models like ChatGPT have improved in performing basic mathematics, they can still make errors, especially with more complex calculations. And they sometimes provide information that is imprecise or outdated when answering questions about the world. (...)
The problem today isn’t that we can’t depend on computers. In fact, we can’t depend on any media without a system of fact-checking, critical thinking and trust. The problem is that, up to now, we have been able to depend on computers. And now this trust has been broken. The real question is, how will we get that trust back again?"
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"We agree that AI should not be mystified. We agree that students should be taught to question it, prod it, and refuse to treat it like gospel. But here is where I push: it is not just about getting students to “understand” AI. It is about recognizing that AI already understands them — because it has been trained to. And it is already being embedded in schools in ways that make understanding secondary to compliance.
This is not theoretical. This is happening."
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PROJECTS > DIMENSIONS OF AI LITERACIES AI Literacies Applied Empirical findings on the appearance of AI literacies shows that they are multidimensional, interconnected, and socioculturally informed. As such, how they show up is dependent upon multiple factors including our roles, environment, and...
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Discover how Generative AI can enhance student competency through the assessment flywheel model, providing personalized feedforward comments and automating low-stakes formative assessments for deeper learning.
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The promise of ‘labour-saving’ technology is rarely straightforward. While new technologies will often lead to different working conditions, whether or not these equate with better working conditions tends to contestable (especially if we ask the pointed question of ‘better for whom?’). In the education sphere, the past few years have seen growing promises that generative AI…
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From
fltmag
By Ilka Kostka, Rachel Toncelli, and Catherine Fairfield, Northeastern University DOI: https://www.doi.org/10.69732/WNWY9538 From “Gotcha” to Guidelines “I’ve been ChatGPT’d!” Any educator who has been teaching during the rise of generative artificial intelligence (GenAI) knows what this phrase means. When we
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This article isn’t about the problems AI produces or the issues we face when it goes wrong. Numerous accounts of the weaknesses and risks of today’s AI systems can be found elsewhere. This article focuses on what will be developed when AI works, and how these developments will influence learning and development. While leaving room for the AI sceptics — sure, it might all fail
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Many of you reading this article are online teachers and I would like to start by asking two questions: Are you a good online teacher?
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Dimensions of AI Literacies AI literacies are becoming increasingly essential as AI continues to evolve and integrate into a multitude of educational contexts. Rather than viewing literacy as a singular skill, the Dimensions of AI Literacies embrace a pluralistic perspective, recognizing that... |
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Discover adaptable active learning strategies to boost student engagement in both traditional classrooms and asynchronous online courses.
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From
teachonline
"(...) I think challenges around the relevance and value of higher education are going to be compounded by AI. Many tasks performed by people in many jobs are going to be satisfactorily accomplished by AI agents (as we can already see). For example, if you've got a team of salespeople who are doing cold calling, outbound lead generation, you're going to replace most, if not all, of those people with AI agents, as companies are already doing. The whole ecosystem of higher education as we understand it now has to change.
Other parts of the ecosystem are changing dramatically, and ecosystems have to stay in balance or bad things happen. Imagine if higher education hadn’t changed in response to the Internet? Imagine if we still stood in lines with cards to register for classes, etc. I think many people don’t appreciate how much about higher education changed because of the Internet. It will change more because of AI. "
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Hey, y’all, I think I have this whole ‘AI in education’ thing figured out. Am I doing this right?
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Due to the sheer volume of AI options, pairing high-impact AI tools with highly desirable outcomes aids in the promotion and implementation of such usage in the online classroom.
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This article explores AI's historical evolution, critically assesses its benefits and challenges for teaching, and provides evidence-based strategies for faculty to integrate AI effectively.
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This free comprehensive guide explores AI’s transformative role across industries, emphasizing the need for AI literacy to remain competitive.
Key sectors include healthcare, engineering, cybersecurity, marketing, and education, with insights into AI-driven automation, predictive analytics, and personalized experiences.
The author highlights essential skills for adapting to AI advancements while addressing ethical concerns and workforce implications.
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One common theme throughout our initial conversations about AI with teachers are issues of time. Here, the primary narrative being pushed by school leaders and AI vendors is the idea of AI as a time-saver – taking on the burden of time-consuming but inessential tasks, and thereby ‘freeing up’ teachers “so you've got time to do other things…
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Hamilton & Middlebrook: Educators can use artificial intelligence to make tests more learner-centered and personalized, with a whole-child emphasis.
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These strategies can make classroom time more engaging and meaningful for students and teachers alike.
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When Students Use AI to Design Their Own Learning: Two Recent Classroom Stories
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From
tophat
Check out our Ebooks and Guides to get the latest teaching tips and tricks.
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ChatGPT is a revolutionary AI-enabled chatbot that provides long-form answers to complex questions. Trained to learn what humans mean when they ask a question, ChatGPT may be the most impactful tool since the modern search engine. 1. ChatGPT can create content in seconds ChatGPT is the latest addition to a suite of AI-enabled natural language processors and writing assistants.
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Curated links to deepen your AI knowledge and understanding. |
Table of Contents
Foreword
by Diana G. Oblinger
PDF
PART 1: Principles and Practices
Chapter 1. Space as a Change Agent
by Diana G. Oblinger
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Chapter 2. Challenging Traditional Assumptions and Rethinking Learning Spaces
by Nancy Van Note Chism
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Chapter 3. Seriously Cool Places: The Future of Learning-Centered Built Environments
by William Dittoe
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Chapter 4. Community: The Hidden Context for Learning
by Deborah J. Bickford and David J. Wright
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Chapter 5. Student Practices and Their Impact on Learning Spaces
by Cyprien Lomas and Diana G. Oblinger
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Chapter 6. The Psychology of Learning Environments
by Ken A. Graetz
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Chapter 7. Linking the Information Commons to Learning
by Joan K. Lippincott
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Chapter 8. Navigating Toward the Next-Generation Computer Lab
by Alan R. Cattier
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Additional Resource: Cox Hall Panorma
Chapter 9. Trends in Learning Space Design
by Malcolm Brown and Phillip D. Long
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Chapter 10. Human-Centered Design Guidelines
by Lori Gee
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Chapter 11. Designing Blended Learning Space to the Student Experience
by Andrew J. Milne
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Chapter 12. Sustaining and Supporting Learning Spaces
by Christopher Johnson
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Chapter 13. Assessing Learning Spaces
by Sawyer Hunley and Molly Schaller
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PART 2: Case Studies
Chapter 14. Learning How to See
Diana G. Oblinger
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Chapter 15. City of London: Sir John Cass Business School
Clive Holtham
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Chapter 16. Denison University: MIX Lab
Scott Siddall
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Chapter 17. Duke University: Perkins Library
Marilyn M. Lombardi and Thomas B. Wall
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Chapter 18. Eckerd College: Peter H. Armacost Library
J. Michael Barber
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Chapter 19. Estrella Mountain Community College: The Learning Studios Project
Homero Lopez and Lori Gee
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Chapter 20. Hamilton College: Science Center
Nikki Reynolds and Douglas A. Weldon
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Chapter 21. Indiana University-Purdue University Indianapolis: The ES Corridor Project
Nancy Van Note Chism
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Chapter 22. Iowa State University: LeBaron Hall Auditorium
Jim Twetten
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Additional Resource: VR tour of LeBaron Hall Auditorium
Chapter 23. London School of Economics: BOX
Andrew Harrison
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Chapter 24. Messiah College: Boyer Hall
Dennis Lynch
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Chapter 25. Michigan Technological University: Center for Integrated Learning and Information Technology
Paul Urbanek
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Chapter 26. MIT: The Brain and Cognitive Sciences Complex
Phillip D. Long
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Chapter 27. MIT: Steam Café
Scott Francisco
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Chapter 28. North Carolina State University: Flyspace
Hal Meeks
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Chapter 29. North Carolina State University: SCALE-UP
Robert Beichner
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Chapter 30. Northwestern University: Information Commons
Bob Davis and Denise Shorey
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Chapter 31. Ohio State University: Digital Union
Victoria Getis, Catherine Gynn, and Susan E. Metros
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Chapter 32. Olin College of Engineering: Academic and Olin Centers
Joanne Kossuth
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Chapter 33. Pennsylvania State University: Smeal College of Business
Peter Nourjian
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Chapter 34. St. Lawrence University: Center for Teaching and Learning
Sondra Smith and Kim Mooney
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Additional Resource: Web sidebar, Table 1, Table 2, Table 3
Chapter 35. Stanford University: GroupSpaces
Richard Holeton
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Chapter 36. Stanford University: Wallenberg Hall
Dan Gilbert
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Chapter 37. University of Arizona: Manuel Pacheco Integrated Learning Center
Christopher Johnson
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Chapter 38. University of British Columbia: Irving K. Barber Learning Centre
Simon Neame and Cyprien Lomas
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Chapter 39. University of Central Florida: Collaboration and Multimedia Classrooms
Ruth Marshall
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Chapter 40. University of Chicago: USITE/Crerar Computing Cluster and Cybercafé
Shirley Dugdale and Chad Kainz
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Additional Resource: Web sidebar
Chapter 41. University of Georgia: Student Learning Center
William Gray Potter and Florence E. King
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Chapter 42. Virginia Tech: Math Emporium
Barbara L. Robinson and Anne H. Moore
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Chapter 43. Virginia Tech: Torgersen Hall
J. Thomas Head and Anne H. Moore
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Additional Resource: Video interviews with Virginia Tech professors Carol Burch-Brown[12MB WMV] and Kerry J. Redican [4MB WMV] about teaching in Torgersen Hall
Index
View: PDF