Serendipity35 - DESIGN

Frank Lloyd Wright’s Taliesin West

ronkowitz@gmail.com (Kenneth Ronkowitz) — Mon, 23 Jun 2025 19:07:00 +0000

I was able to visit Frank Lloyd Wright’s Taliesin West home-studio complex a few years ago. It was started back in the early 1940s, but evolved over many decades.

The version you see in the Architectural Digest video below probably won't change very much now. It is quite different from the original design Wright and his apprentices initially built over their first six years of life and work in the Arizona desert. It went through a good number of changes after Wright himself stopped visiting in his final year, 1959.

Tour guides point out that Wright may not have "approved" of all the expansions, modifications, and renovations made by Wright's "disciples," though they say they were made in keeping with his vision.

Taliesin West may be "purer Wright" than some other more famous Wright buildings because it was not created for a client. No one was telling Wright what they wanted or creating deadlines. It was built with apprentice labor.

It's not the first Taliesin. The original was in Spring Green, Wisconsin. Taliesin West was a home, a studio, and most importantly, an educational institution. Wright and his students spent the winters there every year from 1935 on, though it was a completely undeveloped site at first.

The Wrights stayed at an inn, but the apprentices camped out on-site. They were building straight from plans that their teacher could have drawn up the day before. Eventually, it had plumbing and electricity, but it was still a communal architecture school.

There is also a 360 Virtual Visit online that lets you walk through and hear what you might hear on an official tour. Schools sometimes use this as a virtual field trip. There is even a bit more in this virtual visit than the tour I took in person. For example, visitors aren't allowed in the Blue Loggia because foot traffic would damage the irreplaceable Chinese rug, so they never see the balcony above or the rug up close.

AI Agents

ronkowitz@gmail.com (Kenneth Ronkowitz) — Fri, 28 Feb 2025 09:50:00 +0000

AI agents are something of concern for OpenAI, Google, and any other players. "AI agents" are software programs designed to perform specific tasks or solve problems by using artificial intelligence techniques. These agents can work autonomously or with minimal human intervention, and they're capable of learning from data, making decisions, and adapting to new situations.

Gartner suggests that agentic AI is the most important strategic technology for 2025 and beyond. The tech analyst predicts that, by 2028, at least 15% of day-to-day work decisions will be taken autonomously through agentic AI, up from 0% in 2024. Does that excite or frighten you?

They can automate processes, analyze data, and interact with users or other systems to achieve specific goals. You probably already interact with them in applications (Siri or Alexa), customer service chatbots, and recommendation systems (Netflix or Amazon). They may be less obvious to you when using an autonomous vehicle or a financial trading system.

There are many categories into which we might place these agents because there are different types of AI agents, each with unique capabilities and purposes:

Here are some possible categorizations:

Reactive agents respond to specific stimuli and do not have a memory of past events. They work well in environments with clear, predictable rules.

Model-based agents have a memory and can learn from past experiences. They use this knowledge to predict future events and make decisions.

Goal-based agents are designed to achieve specific goals. They use planning and reasoning techniques to determine the best actions to take to reach their objectives.

Utility-based agents consider multiple factors and choose actions that maximize their overall utility or benefit. They can balance competing goals and make trade-offs.

Learning agents can improve their performance over time by learning from their experiences. They use techniques like machine learning to adapt to new situations and improve their decision-making abilities.You could also categorize agents in other ways, for example, in an educational contex.

For personalized learning, agents can adapt educational content to meet individual students' needs, learning styles, and pace. By analyzing data on students' performance and preferences, AI can recommend personalized learning paths and resources. In a related way, intelligent tutoring systems can provide one-on-one tutoring by offering explanations, feedback, and hints the way that a human tutor might. They might even be able to create more inclusive learning environments by providing tools like speech-to-text, text-to-speech, and translation services, ensuring that all students have access to educational content. By analyzing students' performance data, they could identify at-risk students and provide early interventions to help them succeed.

AI agents can automate administrative tasks for faculty, such as grading, attendance tracking, and scheduling, freeing up educators' time to focus more on teaching and interacting with students.

Agents can "assist" in creating educational materials. I would hope faculty would be closely monitoring AI creation of tests, quizzes, lesson plans, and interactive simulations.

Though I see predictions of fully AI-powered virtual classrooms that can facilitate remote learning, I believe this is the most distant application - and probably the one that most makes faculty apprehensive.

Blended Learning and Hybrid Courses

ronkowitz@gmail.com (Kenneth Ronkowitz) — Wed, 20 Nov 2024 14:00:00 +0000

If blending learning was only this simple.

I saw a mention of "blended learning" in an article that reminded me of that approach that I once taught and endorsed to faculty. I have not heard the term used much in the past few years, but I am no longer involved full-time in pedagogy.

Blended learning is a pedagogical model integrating traditional face-to-face classroom instruction with online learning experiences. In some ways it was a transitional model going back to the shift from 20th century to 21st century learning. As traditional faculty were being asked to use more online tools or even convert their courses to being fully online, this approach was a softer way to launch.

The idea was to combine the best aspects of in-person and digital education to create a more flexible and personalized learning environment. A Personalized Learning Environment (PLE) was another term that emerged at the time. Probably everyone in and out of academia now has a personalized learning environment of a kind, though it may not be formalized. A PLE was supposed to allow students to benefit from direct interaction with teachers and peers while also taking advantage of the accessibility and resources available through digital platforms.

Key components of blended learning include:

    In-person instruction: Traditional classroom teaching where students engage with teachers and classmates in real-time.
Online learning: Use of digital tools and resources, such as videos, interactive activities, and online assessments, that students can access at their own pace.
    Integrated learning activities: Assignments and projects that blend both in-person and online elements to enhance understanding and engagement.
    Flexible pacing: Students can often progress through material at their own speed, allowing for personalized learning experiences.

Some of the advantages associated with blended learning were to provide a more dynamic and adaptive educational experience and addressing diverse learning styles and needs.

An effective blended learning module has a good range of learning activities: on-campus activities, such as lectures, workshops and seminars; off-campus activities, such as field trips, exhibitions, and visits to companies; online synchronous activities; and independent learning activities, such as completing tasks after reading case studies or watching videos.

The article I read was from the UK timeshighereducation.com and had suggested goals for blended learning. In brief, they are:
Find a suitable space when attending online classes
Use digital tools
Create a sense of belonging (a difficult goal because online interactions often feel impersonal and might not be well suited to every student - or faculty member)

One suggestion that interested me the most was to use different types of assessment. This was an area that I worked with faculty on frequently as an instructional designer. Blended learning modules should use a good range of assessment types. It was difficult for many teachers to accept that their main form of assessment was testing, especially objective, knowledge-based tests and quizzes. Written assessments, such as reports and essays, appeared in some courses (especially in the humanities) but were often absent in STEM courses. Faculty would tell me, "They are too subjective." "They take too long to grade" "My course requires them to retain lots of facts that I have to assess." The latter was especially true in foundation courses.

Using online tests and quizzes became more popular because once created they could be automatically scored. Easy for the teacher and immediate feedback for the student.

In-person or recorded presentations were more in the blended model but were time-consuming and more popular in upper-level or graduate courses. Interacting face-to-face with their peers as a team or audience during the presentation is also an important skill. I saw video presentations, e-portfolios, digital projects, posters, podcasts and simulation games all used in blended courses.

One concept that often met with faculty indifference or opposition was the student-as-co-creator of assignments and assessments, though this can serve as a valuable source to gather student voices and improve their learning experience.

The term "hybrid course" became used more than "blended" but was often the same thing or just used interchangeably. While both models integrate online and offline learning, blended learning is a broader pedagogical approach that can be applied at various levels of education and in different ways. A hybrid course is a specific type of course design commonly used in colleges and universities.

A hybrid course refers to a course that "officially" combines face-to-face (F2F) classroom instruction with online components. The term is commonly used in higher education to describe courses where a significant portion of the learning activities are conducted online, with the remaining portion happening in a physical classroom setting. This becomes an issue concerning the registrar and scheduling areas. A course that met F2F on Tuesday and Thursday from 10:30 - noon may now only be assigned a classroom on one of those days. The goal is still to balance the in-person interaction with the flexibility of online learning, usually reducing the amount of time spent in a physical classroom compared to a traditional course.

Of course, hybrid learning models should not be used simply to free up classroom space or reduce parking issues on campus, but unfortunately, I knew of cases where that was a motivation for using it.

The development of online and blended learning modules got a boost during and after the pandemic. To a degree, that was from necessity and convenience, but it introduced these approaches to more students and more faculty and some of it has remained in use.

Developing the right balance between these different teaching modes varies according to discipline, but a mix of synchronous (real-time) and asynchronous (self-paced) online activities, along with in-person classroom sessions.is still the pedagogical approach.

The AI-augmented Educational Support Professional

ronkowitz@gmail.com (Kenneth Ronkowitz) — Tue, 18 Jun 2024 12:50:00 +0000

Working with AI on instructional design isn't at this point. Yet.

You can find numerous articles online about how artificial intelligence (AI) tools and activities can create the "AI-augmented professor." I have seen fewer opinions on how non-teaching staff members who support the learning process at most universities will be affected.

Certainly, AI augmentation will also affect those who support faculty and students, such as instructional designers, researchers, administrators, and other nonteaching professionals.

I read a piece on insidehighered.com about this group and keyed in on instructional designers since that was my area. The article uses an awkward term - BYOAI Bring Your Own AI - for his group because of the hybrid nature of home and office work for this group. Of course, many faculty are also hybrid now, teaching in a campus classroom as well as from their home or office online.

Instructional designers are already using generative AI tools to create graphics, images and audio segments for classes. New tools, such as OpenAI’s Sora can generate full-motion videos from prompts. Chatbots can write or revise content. It can produce a rough draft syllabus for a new course.

This is also something that should concern those people coming into higher ed (and secondary education too, though perhaps to a lesser degree currently). Citing a survey by Microsoft and LinkedIn, ZDNet reported that “AI skills are so much of a priority that the report suggests 66 percent of business leaders wouldn’t hire someone without AI skills, and 71 percent of leaders would prefer to hire a less experienced candidate with AI skills than a more experienced candidate without them.”

Simple AI-Generated Imagery Programs

ronkowitz@gmail.com (Kenneth Ronkowitz) — Wed, 07 Feb 2024 11:48:00 +0000

Cross-posted from my blog at https://ronkowitzllc.com

Artificial intelligence scares some people. When AI takes over human roles and takes the form of a human, that is quite scary. AI writing essays scares teachers and pleases students. It also scares people whose income comes from writing. None of us want to be replaced by a machine.

I have found that AI used to create images seems to be less scary. Oh sure, if I were a graphic designer, artist, or photographer, I would be frightened that my career could be replaced by AI. And you have heard the horror stories about "deep fakes" of photos and videos. But I have been playing with a few simple programs for generating images using AI. These are all free - for now. I do some drawing, painting, and photography myself with my hands, but I would not rate them as professional and this AI method is just so easy.

One of the first things I tried was Microsoft Bing bing.com/images/create/ These programs are very easy to use. You input text - a prompt - describing what you want to see created. The more detailed the prompt, the more likely it is that you will get a result that matches the one in your imagination. Beyond that, you don't have a lot of control. You can't choose colors for small parts of the image but you can describe a style (like a Renaissance painting, or anime, etc.) and add details.

For example, you could ask for an illustration of a woman. That is very broad. Let's try again - an Asian woman on a computer monitor. How about a man creating an image of an Asian woman using his phone and Bing and projecting it on a monitor. Okay, just as a test of its capabilities, let's add a small teddy bear.

Here is the result:

Search and you'll find lots of these programs. www.craiyon.com is another one. I also liked experimenting with deepai.org/machine-learning-model/text2img. I went down a similar path asking variations on a woman standing by a wall, sitting by a lake, etc.

I'll keep posting things I create on this site and I will be using them for a lot of my posts online.

I would like to see more control over these simple tools - such as being able to start with a photo of my own - and they are not perfect in following prompts. Did you notice that in the image at the top, Bing misspelled Bing?

4 variations on a monochrome man walking in the woods prompt

Can Bloom's Taxonomy Teach Us Anything About AI?

ronkowitz@gmail.com (Kenneth Ronkowitz) — Thu, 01 Feb 2024 09:34:00 +0000

Image gettingsmart.com

When I was studying to be a secondary school teacher, Bloom’s Taxonomy often came up in my classes as a way to do lesson planning and a way to assess learners. Recently, there have been several revisions to its pyramid stack. An article on www.gettingsmart.com suggests a spiral might be better, particularly if you want to use it as a lens to view AI.

The author, Vriti Saraf, opines that the most important potential of AI isn’t to enhance human productivity, it’s to enhance and support human thinking, and that looking at AI’s capabilities through the lens of Bloom’s Taxonomy showcases the possible interplay of humans and machines.

It is an interesting idea. Take a look.

Rethinking Accessible Courses

ronkowitz@gmail.com (Kenneth Ronkowitz) — Mon, 20 Nov 2023 09:44:00 +0000

When I was working full-time as an instructional designer, I became very concerned with making courses (especially online courses) accessible. In the early days of this century, very often the college I worked at was quite focused on making accommodations for students with special needs. That was a quick fix but not a sustainable approach.

Retrofitting online courses became part of my department's purview. Our instructional design thinking believed that access(ible) are more than making accommodations. We knew that courses that were accessible for students who had particular needs were also courses that ate probably more accessible for all the other students too. There were so many small examples of things we did. It turned out to be useful to all the students in the course.

One semester now 20 years ago, I decided to provide audio files of my short online lectures and of explanatory talk about some of the more complicated assignments. Some students told me that they would listen to them while driving in the car, or commuting on the train, or on their walks with their dogs. Most of these audio files were taken from videos that I had made often with accompanying PowerPoint slides. So the visual was lost but we all know that a good number of PowerPoint slides used for lecture or text, so not all of the visual content was needed.

The fact that students use them this way, not only convinced me to continue the practice but made me rethink what I was putting in those slides. Perhaps the truly visual presentations needed to be truly visual and not offered as audio files so that students would have to sit down and view the video version. I was rethinking my use of visuals overall.

Micromobility

ronkowitz@gmail.com (Kenneth Ronkowitz) — Tue, 10 Oct 2023 09:43:00 +0000

Micromobility refers to a range of small, lightweight vehicles operating at speeds typically below 25 km/h (15 mph) and driven by users personally. Micromobility devices include bicycles, e-bikes, electric scooters, electric skateboards, shared bicycle fleets, and electric pedal-assisted (pedelec) bicycles, and even hoverboards. The term "micromobility" was originally coined by Horace Dediu in 2017.

There are benefits and challenges for individuals using this type of transportation, including lower initial cost, maintenance, fuel, and parking costs in many instances. The cost for some of those options can even be zero, as with fuel for a traditional bicycle or scooter.

There are also benefits and concerns for communities. Particularly in the ever-evolving landscape of urban transportation, micromobility solutions are revolutionizing the way people commute, reducing congestion, improving air quality and redefining urban mobility.

Some of these modes are electric, some are traditional, such as bicycles, scooters, and skateboards, and some are hybrid. The range of micromobility vehicles offers compact, eco-friendly and convenient options for short-distance travel. By reducing congestion, decreasing carbon emissions and promoting active lifestyles, micromobility has the potential to positively impact urban environments.

One safety concern, particularly in urban areas, is how these vehicles will interact with pedestrains and traditional larger vehicles on roadways.

For more on this topic, see transportation.gov/rural/electric-vehicles/ev-toolkit/electric-micromobility