Digital Transformation and Education

Teaching tomorrow

From the Provost

Shirley Lefever:  In my last Teaching Today contribution, my first sentence was,

Provost Shirley Lefever

“Supporting students is perhaps the single most important thing we do as an institution of higher education.”  With this edition’s focus on digital transformation, that introductory sentence continues to describe our driving force in how we are approaching the role of digital transformation on teaching and learning at WSU. Certainly, embracing educational technologies and how they are shaping teaching and learning is aligned with Wichita State University’s 3 priorities of accessibility and affordability, talent development and economic prosperity. At its core, digital learning describes any practice that utilizes technology for the purpose of enhancing learning. Further, we know that digital learning platforms are transforming not only classrooms, but how industry is approaching employee training. 

Thus, the time is now to grow in our understanding and use of a full range of tools and experiences, limited only by our own imagination.  This month’s Teaching Today is setting us up to do just that.  Imagine.  What is the future of teaching and learning?  How do we continue to push the boundaries in creating learning environments that are engaging and stretch our students’ thinking while at the same time ensure all our students have access to those experiences?  WSU is in a good position to explore those questions because they are core to our mission.  I appreciate each of you contributing to this work and I look forward to seeing what will emerge as we continue to grow and learn as educators and researchers!   

With Shocker Pride,

Shirley Lefever

Executive Vice President and Provost

Digital transformation

Digital Transformation is...?

John Jones: Digital Transformation is the adoption of digital technologies at a scale that creates transformational change within a business, industry, or sector -- like higher ed.  And we have seen those changes already happening -- Covid pushed us quickly into operating more digitally, and as much as it's a relief to be able to spend time with colleagues and students in person again, many of the tools and tactics we learned aren't going away -- they're going to continue to be a part of how we work.

In an Educause article on Digital Transformation, Betsy Reinitz  broke things out this way:

  • We digitize information
  • We digitalize processes
  • We digitally transform institutions

Wichita state is at the start of that transformation -- more changes are coming, and our engagement with them will be more and more critical all the time.

Digital Transformation on the WSU Campus

Instruction at Wichita State has been undergoing transformation for decades. The Pandemic pushed new tools for instructors and students who would not have used them. But the tools were already on campus in the hands of early adopters and instructional design staff. The pandemic would have been much more challenging if that hadn't been the case.
Those tools aren't going back behind "break in case of emergency" glass, and neither are the expectations of students and faculty who found value in them.
Meanwhile, Wichita State is building the National Institute for Research and Digital Transformation. NIRDT is bringing opportunities for campus and the community, and that will include opportunities for instructional transformation, like the exploratory AWS Campus Invent day in September.

What is High Performance Computing?

Terrance Figy:  High-performance computing (HPC) refers to the multiple compute nodes doing parallel data processing connected through the network, and computing tasks are managed by a job scheduler. An HPC cluster usually consists of hundreds of compute nodes, and each compute node is an individual computer that may have 16 to 32 cores. Compared to the HPC cluster, a standard laptop usually has 8 cores. HPC is used to help scientists in many research areas, such as large-scale statistical analyses, particle physics simulations, and molecular dynamic simulations.

BeoShock is the HPC cluster at Wichita State University supported by the Academic Affairs, Office of Research, College of Engineering, and Fairmount College of Liberal Arts and Sciences. BeoShock is available to students, staff, and faculties at Wichita State University. You can make new requests using this online formBeocat is the HPC cluster at Kansas State University operated by the Institute for Computational Research in Engineering and Science. Beocat is available to any educational researcher in Kansas without cost. Learn more about Beocat here.

HPC is vital to the work of many researchers at WSU including:

  • Mathew Muether: Works with physics masters students to develop deep learning-based particle reconstrution tools for the international Neutrino Experiment based at Fermilab.
  • Katie Mitchell-Koch: Has used HPC to bring existing grant projects to completion. Data from Beoshock projects has resulted in eight publications since 2019, and more are in the works.
  • Elizabeth Behrman and James Steck: HPC allows the team to run quantum simulations of systems which themselves act as neural networks that "learn" to do a desired task.
  • Nick Solomey: Manages graduate students who eplore potential new science that can be done with a NASA Spacecraft development idea for a neutrino or dark matter detector in space.
  • James Beck: Uses HPC to enhance both research and teaching, especially as it impacts his plant diversity and evolution lab looking at thousands to tens of thousands of places in the genome.
  • Sergio Salinas Monroy: Working with educators from the University of Kansas, Kansas State University, and Wichita State to create a new course for spring called Community Data Labs.

Not in the sciences but wondering if HPC could help you?  It could! HPC has applications for media and entertainment, oil and gas, financial services, and more. Your human imagination is the one thing computers can never provide. Learn more about HPC.

DT and Microsoft Office 365

Microsoft Office has some fun and interesting features that will help you leverage and visualize data. There so much cool stuff going on with these new tools, that our go-to expert on the topic of all things Microsoft, Ali Levine, provided us a video!

ArcGIS, Big Data and You!

Ethan Lindsay:  Would you like to visualize the “digital divide” in Sedgwick County, so that you can use grant money to provide internet service to the communities most in need? Would you like to understand the effects of climate change on a rain forest over the past forty years? Would you like to see on a map patterns of social inequality that make some Kansas communities more vulnerable to tornadoes? Would you like to use demographic data, such as household income, to determine the most suitable location for your business?

For all these problems, GIS technology will help one organize the pertinent information for the problem in question and to map this data in a way that enables one to see, understand, and solve the problem. As the name implies, Geographic Information Systems, or GIS, is fundamentally about geography and making maps.  Using maps and 3-D models, GIS makes it possible to visualize geospatial data and to study various patterns of information about particular places, such as states, counties, and census tracts. The “geographic approach” that GIS facilitates opens up new ways of addressing complex problems such as climate change, social inequality, and political redistricting. As a result of these capabilities, GIS technology is now used in most academic disciplines and many industries.

Read the rest of Ethan's article here

ArcGIS is a family of software from Esri, the world’s largest and most influential GIS company. This software is map-centric and includes ArcGIS Online and ArcGIS Pro, powerful desktop software. The university’s license includes both desktop and web-based software, including ArcGIS StoryMaps, which enables one to make compelling visual stories integrating text, maps, and multimedia content.

A number of resources related to GIS are now available at WSU. For example, the undergraduate certificate program in GIS is multi-disciplinary in nature but is based in the Anthropology department. Dr. Peer Moore-Jansen is the coordinator. In addition, faculty in diverse fields such as Geology, Business, and Political Science are incorporating GIS technology in their teaching and research.

In addition, the University Libraries has now enhanced its ability to support those studying and teaching GIS. Library faculty and staff are building knowledge of GIS in order to provide consultations about teaching and researching with it.  ArcGIS workshops also introduce faculty, staff, and students to GIS software and help them start their geospatial journeys. Collaborations with GIS educators at Esri have been especially fruitful, and librarians can now connect GIS users to online tutorials and videos by Esri GIS educators.

Creative AI

AI and John Hammer: A Collaborative Dance

John Hammer:  I’d been working with DALL-E 2 and Midjourney for about a month when a good friend asked what it was like to create images using artificial intelligence. He wondered if it’s as simple as seen in recent news stories and YouTube videos. My hesitant answer was, “Yes. And… … no.” The best way I could describe the process was that it’s like a dance. A dance where both parties are expected to lead but to also follow. It has structure, but being nimble and flexible while remaining mindful of the direction, led to much better results.

And as I explained this, I was reminded of learning how to sail a small Sunfish years ago in college. I found that sailing was a balance, an agreement of sorts, between all the moving parts out of my control and with that of my intent, or rather, the direction I wanted to go.

Read the rest of John's article here

So, is creating art with AI as easy as the internet implies? Yes. it is as simple as typing in a prompt and waiting to see the magical results. Nevertheless, what you don’t see much of in those YouTube videos and news stories is the sheer number of unusable images you may get as you find your footing. Outtakes aren't as exciting, I suppose. But the truth is that it does require some effort on the part of the user, especially, if you have something specific in your mind that you wish to see. Sometimes it really is as easy as asking for an “astronaut on a horse” and getting just that. But if you’re wanting to visualize something that does not yet exist, something the AI will visualize right alongside you for the first time, then it will take some strategic prompt crafting. And some patience, perhaps.

While working with AI can greatly help in the design process, I don’t believe it a passive transaction. At least for a sustained level of intentional output. The role of the user as a creative participant is still boundless. But that’s today. Who knows, in three months AI might be to the point where it predicts what you’re thinking and just creates an image for you. No need to ask.

David MacDonald on AI and Music

David MacDonald:  “I forsee a marked deterioration in American music and musical taste, an interruption in the musical development of the country, and a host of other injuries to music in its artistic manifestations, by virtue—or rather by vice—of the various music-reproducing machines.”

This quote comes from an essay by one of the most influential composers in U.S. history, John Philip Sousa, best known for his marches like The Stars and Stripes Forever (1896). The 1906 essay “The Menace of Mechanical Music" is a forceful polemic against the then-increasingly popular phonograph and pianola (player piano). Sousa was not only concerned about music jobs lost to these machines, but about the cultural consequences of generation after generation of U.S. Americans who would not feel as compelled to learn to play an instrument, attend live concerts, and make music in their families and communities. Today, over a century later, musical cultures continue to flourish while a similar set of concerns are being expressed about artistic works created by “artificially intelligent” computer software, and some of this musical creativity is because of—rather than in spite of—the modern descendants of the machines that felt so threatening to Sousa in 1906.
I have taught this Sousa article in music courses and business courses, and students are often amazed at how stridently negative it is. They see intuitively the benefits recordings have had for musicians. Not only has it created new categories of music professionals—recording artists, session musicians, audio engineers, producers, and technicians—it has allowed these students to hear music from across time and around the world. Recording technology has absolutely changed musical culture, but it hasn't diminished it as Sousa predicted. These students can include performances from across the world (to say nothing of time) among their influences, to say nothing of music created with the technology itself.
Read the rest of David's article here
Today, many in higher education are concerned about the use of generative AI software—like GPT-3 for text and DALL-E 2 for images—in student assignments and what it may mean for academic integrity and student learning. At the moment, I’m not concerned about what this means for music, for two reasons: (1) The generative technologies are relatively limited in the music and audio domains, at least in the shorter term, and (2) in the longer term, I see these technologies as just another tool for creative people—including composers—to use.
The limits of machine-learning models for music are mostly the limits of the available training data. Unlike images and text, there simply isn’t anywhere near as much music available that is coded in a way that could train a machine learning model like DALL-E (as much as I would love to hear the AI generate a song from the prompt “atonal power ballad about an orca whale overcoming adversity in the style of Cyndi Lauper”). The programs that have been created for generating music and audio do so within fairly narrow constraints, such as an machine learning model that can only create chorales in the style of J.S. Bach, or country ballads in the style of Alan Jackson. None of these is sophisticated enough to produce a reasonable response to even the sorts of prompts that I give to my first semester undergraduate students.
And even as these machine learning models get smarter with new techniques and better training data, I don’t see them as a challenge to what I ask my students to do. Just as the phonographs and pianolas didn’t eliminate all gigs for all musicians, AI-composed music won’t supplant all composers. An early innovator in computer-generated compositions, David Cope, began writing about his experiments with “musical intelligence” in the 1980s. With his work—which used Markov chains and classical algorithms—he was simply trying to speed up his own frustratingly slow composition process. The output from his programs was simply a fast way to generate rough ideas that he then could shape into final, completed compositions. He created the program, fed it examples of his previous compositions, and then shaped the output. In his book The Algorithmic Composer in 2000, he points out that even when composers aren't working with computers, they are still thinking in deliberate processes, combining inputs from music they've heard or written in the past, and generating a rough output that they then refine into the final work. Compared to this "paper algorithm" process, the computer programs he wrote were not that different, only more efficient. And as he still controlled all the inputs and the outputs, he was really just composing the composer, in a way. Modern machine learning-based tools are even more efficient and can accommodate an even wider array of inputs and outputs, but I see them still as related techniques.
For composers and other musicians, I imagine this being just another tool they can use, either for efficiency or to achieve new kinds of creativity. For my students, that means I want them to be aware of these tools, their strengths, and their limitations. And even for faculty who are concerned about academic integrity issues raised by AI-generated music, if OpenAI’s Jukebox is anything to go by, I don't think it will be worth fretting about for a little while.

John Jones on Collaborating with AI

John Jones: I set out to explore what a free, online AI would produce in a couple of different writing scenarios.  This was my first time actually trying out a writing AI – I’ve been aware of the technology for years, but they were not always so easy to try out as they are now. 

  • Creative Sample – I tried out getting the AI to do some fairly silly creative writing.
    TLDR: Creative example
    The AI did some very interesting things – it didn’t just riff with my existing ideas, it added new ideas and did an interesting job making the ideas work together.  It was nothing like what I would want as a finished product, and the creative additions were not all that different from what I might have produced with a variety of other random element generators, but the results were definitely interesting and could be useful to generate ideas and shake things up in my writing process.
  • Non-Fiction Sample – I decided to give the AI a non-fiction prompt – and what better prompt than one that asks the AI to consider the impact of AI on academic honesty?
    TLDR: Non-fiction example
    The results were probably stronger than the results in the creative sample.  The writing wasn’t terrific, but it was serviceable, and in the process of regenerating the piece with the same prompt I got widely divergent results – each of my five samples takes a very different position and angle on the problem.

In the end, I think these writing AI tools are something that we would be wise to spend more time working with, so we can understand their strengths and weaknesses.  I believe that the availability of tools and the results that they can produce makes them a reality we need to work with.

New Challenges

Learning Theory in the 21st Century

Learning theory is keeping up as the world transforms. Connectivism, an outgrowth of the early twenty-first century works of George Siemens (2004) and Stephen Downes (2005), seeks to incorporate learning and memory that happens outside the individual into a unified theory of learning. While this theory is still under development, its foundational idea is that learning happens in networks and transcends individuals. Each learner is only part of the overall picture. This concept is a shift from the way traditional learning theories have defined "learning." If you are interested in learning more, the Office of Instructional Resources outlines Connectivism here.

AI Can Write Essays

Carolyn Speer: Artificial intelligence has advanced to the point that it can now write articles just like this one. In fact, Sudowrite, a free artificial intelligence online interface, collaborated with me to write this article, and even provided some "opinion" you may notice.

Sudowrite is an artificial intelligence that reads and analyzes text. It takes over where you leave off and creates articles like many you read on news sites like Google News. In fact, artificial intelligence probably writes many of the current event articles you read each day!

Using artificial intelligence in writing is part of a larger trend of using technology to replace human labor for some tasks. The content of this article is not completely human-generated, but it's not fully AI content either. Instead, Sudowrite and I worked together to create it. Is that cheating? If a student created an essay for your class this way, would it be a violation of our academic integrity policies?

Sudowrite doesn't think so, but it’s an important question to ask. Sudowrite uses a technology called natural language generation (NLG) to create articles. Natural language generation is a type of artificial intelligence that is quite different from human language. But it can't work well on its own. Instead, it partners with a human to create writing intended for real humans who understand the world the way humans think.

Addendum: On the day this newsletter was to be distributed, Inside HigherEd printed an opinion article arguing that AI is not a threat to the integrity of the college essay. If you are interested in developing your own views on this topic, OIR recommends Sudowrite because it's free and easy to use.

New Challenges, New Class Assignments

The rise of misinformation, especially through social media coupled with the development of "deepfakes," hyper-realistic manufactured images, represents a potential threat to elections in the United States and around the world.  One American Politics instructor at Wichita State is working to incorporate deepfake assignments into their class this semester. Using Tweetgen and DALL-E2 plus what they learned from the Spot the Troll quiz, students are asked to create their own (silly) deepfakes so they can learn how easy it is to disrupt the public conversation with fake information. The idea is to arm students with that knowledge so they can become better consumers of digital information. Interested in what kinds of deepfake images students create? Check out Esmeralda Monreal's "silly deepfake" of a cat hunting a parrot at the foot of a roller coaster: Cat stalking a parrot by a roller coaster

Data data data

Daily Habits, AI, and Higher Ed 

A defining quality of digital transformation has been the rapid development of artificial intellingence (AI). AI is improving rapidly, and sometimes it almost seems to read minds. But in a world awash with data, AI doesn't need to be a mentalist to know what we are thinking. Our lives are open books to any entity that can read our data.

We rely on AI's ability to learn about the world as we go about our modern lives. For example, car enhancements like navigation systems, dynamic cruise control, and even ride-sharing apps like Uber use AI. We also benefit from AI in when we go to the doctor. Have you had an x-ray lately? It was likely read by AI before it was handed off to a human. And of course, online retailers use algorithms too. Have you ordered something from Amazon today? Amazon's algorithms may have already anticipated your need. 

What's more, increasingly we are feeding our data into this system without even knowing it. New appliances, home security systems, and even the ubiquitous fitness trackers are all part of the "Internet of Things" (IoT), which provides so much data into the system that it's giving way to a new concept: the "Artificial Intelligence of Things" (AIoT). 

What does all this have to do with modern higher education? According to Stanford's 2021 Study Panel Report, "Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100)," higher education has work to do in the areas of research, ethics, and the education of students for the workforce. Keep learning and thinking about these topics at the January, 2023 Academic Resources Conference, where we will be focusing on data and all its influence on modern life.


learn more

WSU Offers Regular Events and Training

Wichita State offices offer regular training and events on topics related to digital transformation and artificial intelligence.  If you are interested in learning more, keep an eye out for the following opportunities:

Teaching Yesterday

Lest We Forget

It can be challenging to decide what new technologies are important to bring into the classroom. At the same time, it can be hard to give up on longtime habits that might need to be updated. Over the last several decades, classroom expectations have changed quite a bit. Consider:

  • Classes in the 1980s that didn't allow students to use computers or printers, arguing those tools were cheating.
  • In the mid 1990s, both professors and students had to be required to get and use email
  • Classes in the 1990s and early 2000's that didn't allow the use of digitized resources, favoring articles from microfiche over CD-ROMs and later, the internet.
  • Pre-COVID classes that never used online resources like Blackboard, video, or digitized textbooks. 

Education's distrust of technological changes predates the Information Age and digital transformation. Even Socrates distrusted the technology of his time, writing, which he believed would lead to forgetfulness:

The parable of Thamus: But when they came to writing, Theuth said: “O King, here is something that, once learned, will make the Egyptians wiser and will improve their memory; I have discovered a potion for memory and for wisdom.” Thamus, however, replied: “O most expert Theuth, one man can give birth to the elements of an art, but only another can judge how they can benefit or harm those who will use them. And now, since you are the father of writing, your affection for it has made you describe its effects as the opposite of what they really are.

In fact, writing will introduce forgetfulness into the soul of those who learn it: they will not practice using their memory because they will put their trust in writing, which is external and depends on signs that belong to others, instead of trying to remember from the inside, completely on their own. You have not discovered a potion for remembering, but for reminding; you provide your students with the appearance of wisdom, not with its reality.

Your invention will enable them to hear many things without being properly taught, and they will imagine that they have come to know much while for the most part they will know nothing. And they will be difficult to get along with, since they will merely appear to be wise instead of really being so.”