“Knowing is not enough; we must apply. Willing is not enough; we must do.”
Johann Wolfgang von Goethe
Learning Transfer’s ultimate outcome is behaviour change, so we must understand the conditions that trigger a behaviour to start.
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According to Fogg, three specific elements must converge at the same moment for a specific behaviour to occur. Given that learning transfer is only successful when the learner starts behaving in the desired new ways, Fogg’s work is critical to understanding how to generate these new behaviours. The Fogg Behavioural Model [*1] states that B=MAP. That is, a specific behaviour will occur if at the same moment there is sufficient motivation, sufficient ability and sufficient prompt. If the behaviour does not occur, at least one of these three elements is missing or below the threshold required.
The prompt is, in effect, a call to action to do a specific behaviour. The prompt must be ‘loud’ enough for the target person to perceive it and be consciously aware of it. Once aware of a prompt, the target immediately, and largely unconsciously, assesses their ability to carry out the requested behaviour: how difficult would this be, how long will it take, who can help me, and so on. They base this on their perception of the difficulty of the requested behaviour, and their ability, as they see it, to achieve that behaviour.
These librarians, entrepreneurs, lawyers and technologists built the world where artificial intelligence threatens to upend life and law as we know it – and are now at the forefront of the battles raging within.
… To create this first-of-its-kind guide, we cast a wide net with dozens of leaders in this area, took submissions, consulted with some of the most esteemed gurus in legal tech. We also researched the cases most likely to have the biggest impact on AI, unearthing the dozen or so top trial lawyers tapped to lead the battles. Many of them bring copyright or IP backgrounds and more than a few are Bay Area based. Those denoted with an asterisk are members of our Hall of Fame. .
descrybe.ai, a year-old legal research startup focused on using artificial intelligence to provide free and easy access to court opinions, has completed its goal of creating AI-generated summaries of all available state supreme and appellate court opinions from throughout the United States.
descrybe.ai describes its mission as democratizing access to legal information and leveling the playing field in legal research, particularly for smaller-firm lawyers, journalists, and members of the public.
How Learning Happens — from edutopia.org In this series, we explore how educators can guide all students, regardless of their developmental starting points, to become productive and engaged learners.
These techniques have resonated with educators everywhere: They are focused on taking advantage of the incredible opportunity to help children reach their full potential by creating positive relationships, experiences, and environments in which every student can thrive. In fact, the science is beginning to hint at even more dramatic outcomes. Practices explicitly designed to integrate social, emotional, and cognitive skills in the classroom, the research suggests, can reverse the damages wrought by childhood trauma and stress—while serving the needs of all students and moving them onto a positive developmental and academic path.
Also from edutopia.org recently, see:
How to Introduce Journaling to Young Children— from edutopia.org by Connie Morris Students in preschool through second grade can benefit from drawing or writing to explore their thoughts and feelings.
The symbiotic relationship between reading and writing can help our youngest students grow their emergent literacy skills. The idea of teaching writing at an early age can seem daunting. However, meeting children where they are developmentally can make a journaling activity become a magical experience—and they don’t have to write words but can convey thoughts in pictures.
7 Digital Tools That Help Bring History to Life— from edutopia.org by Daniel Leonard Challenging games, fun projects, and a healthy dose of AI tools round out our top picks for breathing new life into history lessons.
We’ve compiled a list of seven teacher-tested tools, and we lay out how educators are using them both to enhance their lessons and to bring history closer to the present than ever.
What we teachers desperately need, though, is an ocean of examples and training. We need to see and share examples of generative AI—any type of artificial intelligence that can be used to create new text, images, video, audio, code, or data—being used across the curriculum. We need catalogs of new lesson plans and new curriculum.
And we need training on theoretical and practical levels: training to understand what artificial intelligence actually is and where it stands in the development timeline and training about how to integrate it into our classes.
So, my advice to teachers is to use any and all the generative AI you can get your hands on. Then experience—for yourself—verification of the information. Track it back to the source because in doing so, you’ll land on the adjustments you need to make in your classes next year.
From DSC: Interesting.
Learners can now seamlessly transition between AI-powered assistance (AI Tutor) and Live Expert support to get access to instant support, whether through AI-guided learning or real-time interactions with a human expert.
ASSIGNMENT MAKEOVERS IN THE AI AGE WITH DEREK BRUFF — from teachinginhighered.com by Bonni Stachowiak Derek Bruff shares about assignment makeovers in the AI age on episode 481 of the Teaching in Higher Ed podcast
Comment on this per Derek Bruff:
Why not ask ChatGPT to write what King or X would say about a current debate and then have the students critique the ChatGPT output? That would meet the same learning goals while also teaching AI literacy.
(Be sure to read Asim’s contribution for a useful take.)
Here’s a closer look at the concurrent AI landscape in schools — and a prediction of what the future holds.
So far, high-profile ventures in the instruction realm, such asKyron Learning, have fused teacher-produced, recorded content with LLM-powered conversational UX. The micro-learning tool Nolej references internet material when generating tasks and tests, but always holds the language model closely to the ground truth provided by teachers. Both are intriguing takes on re-imagining how to deliver core instruction and avoid hallucinations (generated content that is nonsensical).
As a result, real-time 3D jobs are among the most in demand within the tech industry. According to Unity’s vice president of Education and Social Impact, Jessica Lindl, demand is 50% higher than traditional IT jobs—adding that salaries for real-time 3D jobs are 60% greater.
“We want to provide really simple on ramps and pathways that will lead you into entry level jobs so that at any point in your career, you can decide to transfer into the industry,” Lindl says.
University World News continues its exploration of generative AI in our new special report on ‘AI and Higher Education’. In commentaries and features, academics and our journalists around the world investigate issues and developments around AI that are impacting on universities. Generative AI tools are challenging and changing higher education systems and institutions — how they are run as well as ways of teaching and learning and conducting research.
My advice for you today is this: fill your LinkedIn-feed and/or inbox with ideas, inspirational writing and commentary on AI.
This will get you up to speed quickly and is a great way to stay informed on the newest movements you need to be aware of.
My personal recommendation for you is to check out these bright people who are all very active on LinkedIn and/or have a newsletter worth paying attention to.
I have kept the list fairly short – only 15 people – in order to make it as easy as possible for you to begin exploring.
It is crucial to recognize that the intrinsic value of higher education isn’t purely in its ability to adapt to market fluctuations or technological innovations. Its core strength lies in promoting critical thinking, nurturing creativity, and instilling a sense of purpose and belonging. As AI progresses, these traits will likely become even more crucial. The question then becomes if higher education institutions as we know them today are the ony ones, or indeed the best ones, equipped to convey those core strengths to students.
Higher education clearly finds itself caught in a whirlwind of transformation, both in its essence and execution. The juxtaposition of legacy structures and the evolving technological landscape paints a complex picture.
For institutional leaders, the dual challenge lies in proactively seeking and initiating change (not merely adapting to it) without losing sight of their foundational principles. Simultaneously, they must equip students with skills and perspectives that AI cannot replicate.
“They begged, bargained with, and berated their instructor in pursuit of better grades — not “because they like points,” but rather, “because the education system has told them that these points are the currency with which they can buy a successful future.””
Habit #2: Engage students in a brain dump or two things as an entry ticket or exit ticket. Spend one minute or less having students write down everything (or just two things) they remember from class. The key: Don’t grade it! Keep retrieval practice no-stakes to emphasize it’s a learning strategy, not an assessment strategy.
Teaching from the heart in 13 steps — from timeshighereducation.com by Beiting He Engaging your students through empathy requires teachers to share their own stories and vulnerabilities and foster a safe space for learning. Here, Beiting He offers 13 ways to create a caring classroom
In summary, “I wish” is about proposing positive changes and improvements, while “I wonder” is about asking thoughtful questions to gain insight and foster meaningful conversations within the team.
If we want students to remember – to lock new information or ideas into long-term memory – getting meaningful repetitions still is key. And the science of learning still backs that up.
So … if we want students to get repetitions to make new learning permanent, how can they do it? Here are 10 ways to help students get repetitions for practice – and how classroom technology can help.
In this episode, I share ten engaging activities that combine education, technology, and plenty of fun to make the first week of class super memorable. From digital scavenger hunts to virtual field trips, hear about a few of my favorite ways to create an interactive start to your school year.
Tips for First Week of School Activity Ideas
Establish routines in a fun way.
Provide opportunities for collaboration.
Introduce tech tools that will be used all year.
From DSC: Dr. Burns has a great list of tools/tips/resources in this posting.
Four directions for assessment redesign in the age of generative AI— from timeshighereducation.com by Julia Chen The rise of generative AI has led universities to rethink how learning is quantified. Julia Chen offers four options for assessment redesign that can be applied across disciplines
Direction 1: From written description to multimodal explanation and application
Direction 2: From literature review alone to referencing lectures
Direction 3: From presentation of ideas to defence of views
Direction 4: From working alone to student-staff partnership
With the latest national test results showing a dispiriting lack of progress in catching students up academically in the wake of the pandemic, one potential explanation stands out: stubbornly high rates of student absenteeism. Vast numbers of students haven’t returned to class regularly since schools reopened.
The most significant problem I’ve seen for aspiring instructional designers is that they don’t have a solid plan in place with how to make acquiring a new job a reality. What does this involve? A monumental portion of instructional design is knowing about how learning works. Yes, there are other components about instructional design like technology, project management, relationship management, research, but at the end of the day, you need to know how people learn to design meaningful learning experiences. So, think of your instructional design journey as a learning experience. How would you reverse engineer this process to help you obtain your goal? Let’s start by asking a few questions:
Cognitive Load Theory is an influential theory from educational psychology that describes how various factors affect our ability to use our working memory resources. We’ve done a digest about cognitive load theory here and talked about it here and here, but haven’t provided an overview of the theory so I want to give an overview here.
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Cognitive load theory provides useful and dynamic model for how many different factors affect working memory and learning. Hopefully this post provides a useful overview of some of the main components of cognitive load!
Simplify the explanations of what you’re presenting as much as possible and break down complex tasks into smaller parts
Don’t place a large amount of text on a slide and then talk about it at the same time — doing so requires much more processing than most people can deal with.
Consider creating two versions of your PowerPoint files:
A text-light version that can be used for presenting that content to students
A text-heavy version — which can be posted to your LMS for the learners to go through at their own pace — and without trying to process so much information (voice and text, for example) at one time.
Design-wise:
Don’t use decorative graphics — everything on a slide should be there for a reason
Don’t use too many fonts or colors — this can be distracting
Don’t use background music when you are trying to explain something
Their most recognisable role is to partner with faculty and provide them with inspiration, expertise and support in their teaching. But a broader role is emerging at institutional level- helping create a culture where people value talking about teaching and more generally, fostering a culture of continuous learning. In this respect, CTLs act as agents of change, aiming to influence the organizational (learning) environment.
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CTLs are part of an ecosystem, internally and externally, and they have the potential to play a very important role, that of a network node. Internally, this can mean connecting various silos within the university, a much needed task, while externally it implies establishing collaboration flows with other CTLs that can in turn lead to broader inter-university collaboration. Making use of the full potential of this role can make a big difference for the success of a CTL.
Speaking of Teaching & Learning Centers, also see:
7 Questions on Engaging Faculty in Digital Accessibility — from campustechnology.com by Rhea Kelly We asked the Technical College System of Georgia’s accessibility champions how they help instructors create a more inclusive learning experience for all students.
In particular, TutorND’s emphasis on applying principles of cognitive science – the science of our how minds work – in tutoring practice has not only bolstered the interest and confidence of some of its tutors to pursue teaching, but also strengthened their instructional skills and meaningfully contributed to PK-12 student growth.
Today, TutorND trains and supports 175 tutors in schools across the greater South Bend community and across the country. Given that these tutors are students, faculty, and staff interested in cognitive science research and its application to student learning, they’re able to bridge theory and practice, assess the effectiveness of instructional moves, and foster learning experiences for students that are rigorous, affirming, and equitable.
Last week, as I was interviewing Shaun Vecera about a new initiative he directs at the University of Iowa, he made a comment that stopped me in my tracks. The initiative, Learning at Iowa, is meant to create a common vocabulary, based on cognitive science, to support learning across the university. It focuses on “the three M’s for effective learning”: mind-set, metacognition, and memory.
“Not because those are the wrong ways of talking about that. But when you talk about learning, I think you can easily see how these skills transfer across not just courses, but also transfer from the university into a career.”
From DSC: This reminds me of what I was trying to get at here — i.e., let’s provide folks with more information on learning how to learn.
When the researchers asked their interview subjects how they first learned about peer instruction, many more cited informal discussions with colleagues than cited more formal channels like workshops. Even fewer pointed to a book or an article.
So even when there’s a really well-developed recipe, professors aren’t necessarily reading it.
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In higher ed, teaching is often seen as something anyone who knows the content can automatically do. But the evidence suggests instead that teaching is an intellectual exercise that adds to subject-matter expertise.
This teaching-specific math knowledge, the researchers note, could be acquired in teacher preparation or professional development, however, it’s usually created on the job.
“Now, I’m much more apt to help them develop a deeper understanding of how people learn from a neuroscientific and cognitive-psychology perspective, and have them develop a model for how students learn.”
Erika Offerdahl, associate vp and director of the Transformational Change Initiative at WSU
From DSC: I love this part too:
There’s a role here, too, for education researchers. Not every evidence-based teaching practice has been broken into its critical components in the literature,