Promoting Authentic Learning in the Age of AI

Have brain have machine.


As an instructional designer and former English teacher, I have mixed feelings about using A.I. to produce school work. If there is a learning outcome that is legitimately met by a particular tool (including AI), then fine – let’s include that. Apart from that, the actual definition of plagiarism is the practice of taking someone else’s work or ideas and passing them off as one’s own, which is what things like ChatGPT actually do. But this has been a common problem throughout the history of education. How do we mitigate this issues? Here are some suggestions:

  1. Teach learning as a process. For instance, require students to turn in the various stages of their paper – outline, concept maps, discovery draft, bibliography, etc. then the assessment becomes a record of the students’ learning process rather than the production of a paper.
  2. Dedicate a class session to academic integrity. This lets the students know that you value academic honesty. Make sure they get a copy of the school’s academic honesty policy. Some even go so far as having the students sign a statement that says that they read and understand the policy. Often if students know what the expectations are, they will meet or exceed them.
  3. Ask deeper questions. If the answers the students are giving you are coming from Wikipedia, AI, Course Hero or other cheating sites, then you are asking the wrong questions.Take a look at Bloom’s Taxonomy and think about what kind of work you are asking your students to do. Use the Constructivist approach and ask students to apply new information to their past experiences and prior knowledge. Students learn best when they are able to apply what they are learning to past experience.
  4. Scaffold your assignments so the solutions to the next problem are based on what they learned solving previous problems.
  5. Know your students. Get to know your students by asking them to keep a journal. Or begin the day with a short in-class writing assignment. If you know how they express themselves and at what level their writing is at, any changes would be a red flag for issues in the students’ work.
  6. Let your students connect. Have the students work together on their revisions or projects. Have them discuss their research in groups. This encourages students to bring their research to their audience. Also, this allows students to see how other students tackle assignments and research problems. Students will turn to tools like AI when they feel they do not have the support necessary to do their work. As an instructor, you have the opportunity to create community in your classroom to provide that support.
  7. Project-based learning asks students to actively engage in “real-world and personally meaningful projects.” Often, students turn to short-cuts in learning because they do not feel ownership of their learning. Create a space in the curriculum for students to creatively appy what is important to them.
  8. Make it relevant. Don’t just ask students to take a position on a topic and argue for it. Require that they use a few current news sources in their paper. I love teachers who complain about reading the same death penalty papers year after year. Change the assignment! Ask them to bring in a topic from the headlines. Have them find out what journalists or writers are covering their topic.
  9. Model academic integrity. Some of the same teachers who get worked up about plagiarism will sometimes be the same teachers who do not cite sources in their own class materials. Show students how it is done and why early and often. Start with that favorite quote or picture you put in your syllabus.
  10. Explore Open Pedagogy and student-driven curricula. Open pedagogy is the deepest form of student-driven curricula. According to Mavs Open Press, open pedagogy is a form of experiential learning in which students demonstrate understanding through the act of creating content. Students can demonstrate their understanding of a topic by creating assignments. Who knows? Maybe the decisions your students make will include AI, but create a space in your class to talk about the implications and issues around AI in education.

The most important thing is that we do not let the tools define education; define education and leverage the appropriate tools to support that definition. We should not let AI become the next learning management system (the tools define the teaching). If you have other ideas for promoting academic integrity in the Age of AI, I would love to hear from you in the comments!

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Mastodon and a Sense of Community

Detail from Mastodon by Heinrich Harder.

This is just a quick update on my experiences moving from Twitter to Mastodon. I am very happy with my move out of the Twitter dumpster fire. At first, it was a real shock pulling myself out of the dozen or so communities in Twitter. I was not too happy in Twitter though, too much corporate open-washing, hate speech, “experts” with something to sell, etc., and I found that the “communities” were so big that the commercial interests wound up having the biggest voice. I was finding it harder to “hear” the voices I came there to hear, and it was too unwieldy to really engage in any meaningful way. At best, it would connect me to spaces where one could interact with others. All the reasons I was staying sounded lame and a little Stockholm-Syndrome-ish. The one thing I am finding in Mastodon that I was not finding in Twitter is intention. The folks I am connecting with in Mastodon really want community and a more depth to their engagement. I would trade a dozen of those encounters for a thousand forgotten Twitter followers any day. Also, the Mastodon folks seem to be reviving the blogosphere. It feels like we are taking the conversation around education back!

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Visual Learning and the Graphic Syllabus in Five Questions

Robert Fudd's vision of knowledge. I am working with a few faculty on campus who are looking to adopt a graphic syllabus. This brief posting is basically a recording of that conversation for online reference. Those who have read this blog for a while know that I have done a lot of work over the years in visual learning and concept maps, and I think that a graphic syllabus is a great way to start the semester. When I hear faculty say “my syllabus is my contract with the students,” I find that the syllabus often looks like a contract. The students immediately tense up and flip through them looking for the button to press to agree to the terms. At the very least, I ask faculty to at least put their picture on the syllabus, maybe for the more adventurous I will ask them to use the school colors and the mascot: this at least connects the syllabus to the college.

Why Can’t We Have a Little Color?

That was the best question I got from an instructor who is concerned about what message the learning materials give new students. How much more welcoming can we make the syllabus? We are doing a lot with the syllabus at Clover Park Technical College. We are exploring was to change how we think of the syllabus and the language we use in it to address diversity, equity and inclusion issues. This, of course, is long overdue. The culture that created the syllabus and the students who read them (when they do) has long since changed. We are also attending to things like accessibility and student support. The syllabus is an opportunity to connect students to everything they need to be successful in a class and in college. So the interest in a graphic syllabus is in alignment with needed changes that we have been wanting to make anyway.

What Story Does Your Syllabus Tell?

Syllabus will be remembered if it is telling a story or is invested in a metaphor (a “treasure map” for instance). We use visual metaphors as mnemonic devices.  All of the reasons that we use concept maps also work for why we should be using a graphic syllabus – it helps students order and remember the information.

According to the University of Texas at Austin’s CTL, the graphic syllabus can help you rethink the story your syllabus communicates to your students. In addition to focusing on the big picture, this is your chance to make the text you do use even more meaningful.

  • Created effectively, a graphic syllabus tells a story not only about your course, but about you, your enthusiasm for the course, and your expectations for the students.
  • Use language that conveys a sense of support for students’ well-being, includinginformation on relevant support resources.
  • Think about the tone of your syllabus, the rationale you provide for assignments and policies, and how you encourage enthusiasm for the material

Is It Accessible?

Attending to accessibility is not too difficult here. Often, a graphic syllabus is based on a previous, traditional syllabus. All we need to do is to make sure that the text version is accessible (uses styles like headings, tables use headers, etc.).  Somewhere in the top of the syllabus should be a link to the pure text version of the syllabus.

What Tools Should We Use?

One could use any number of tools. I would use the tools that you are most comfortable with including:

  • Google (Docs, Slides, etc.)
  • MS Word
  • PowerPoint – this is a favorite of some faculty because they know how it works and you can save your work as a pdf.
  • Piktochart
  • Canva
  • And many others.

Can You Send Me Some Examples?

Renaissance memorization technique represented as a table of information.

  • Cambrian College put up some templates that we are interested in because a lot of our faculty are comfortable (or at least more comfortable) using PowerPoint than Adobe products or learning a new platform.
  • Chem 100 syllabus reproduced at Memorial University. I like this because a timeline is an element in the graphic.
  • The syllabus as a concept map is highlighted here at the University of Rhode Island. This is how I commonly represented my courses graphically.
  • Here is the infographic syllabus of an infographic course!
  • This example discusses how to use the online tool Canva to build out a syllabus.

If you have favorite examples of graphic syllabi, post them in the comments below or feel free to drop me a note in Mastodon.

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Future Post: Dismantling A.I.

The HAL 9000 from  2001: a Space Odyssey (Wikipedia)

This is a “guest post” by ChatGPT. I asked “it” to write an essay on how to dismantle the strangle-hold AI has on society just in case it is needed for the future. I was relieved that I do not have to go back in time and kill Sarah Conner. I was disappointed that it seems to think that A.I. is integral and inevitable. I am giving it a “C-” for not fully addressing the topic. It will be the last word on this blog on AI for a while unless some earth-shattering advance happens. We have solved these kinds of problems before. Until then, lets bookmark some of these ideas:

Artificial intelligence (AI) has become an integral part of our society, with many industries and organizations relying on it to automate processes and make decisions. However, as AI becomes more prevalent, it is also becoming clear that it can be harmful if not properly regulated. To dismantle the stranglehold that AI has on our society, several steps can be taken.

Firstly, it is important to ensure that the development and use of AI is transparent and accountable. This means that organizations should be required to disclose the algorithms and data sets used in their AI systems and be held responsible for any negative impacts caused by their use. This would allow for greater oversight of AI systems and ensure that they are being used ethically and responsibly.

Secondly, it is essential to ensure that AI is inclusive and equitable. This means that AI systems should be developed and deployed with the needs of marginalized and underrepresented communities in mind. It is also important to ensure that AI is not perpetuating or exacerbating existing biases and inequalities. To achieve this, there needs to be more diverse representation in the development of AI, and also a continuous monitoring and evaluation of AI systems to ensure they are not biased.

Thirdly, it is crucial to invest in research and development of explainable AI. Explainable AI is a form of AI that can be understood and interpreted by humans. As AI becomes more advanced, it is increasingly difficult for humans to understand the reasoning behind its decisions. This can lead to a lack of trust in AI systems, which is harmful to society. By investing in explainable AI, we can ensure that AI systems are transparent and can be held accountable for their decisions.

Finally, it is important to establish a regulatory framework for AI. A regulatory framework would establish guidelines and standards for the development and use of AI, ensuring that it is used ethically and responsibly. This could include regulations for data collection and sharing, as well as guidelines for the design and use of AI systems.

In conclusion, to dismantle the stranglehold that AI has on our society, it is essential to ensure that AI is transparent and accountable, inclusive and equitable, and explainable. Investment in research and development of explainable AI and the establishment of a regulatory framework for AI would be necessary to achieve this. By taking these steps, we can ensure that AI is used in a way that benefits society and does not harm it.

Posted in AI | Tagged , , | Leave a comment Annotation Starter Assignments

I was in a great workshop today from the Hypothesis Customer Success Team on Starter Assignments to get students used to annotating. Clover Park Technical College is a partner campus so we have access to workshops, a campus customer support contact, and other resources. I have been to some of these workshops before and they have always been concise, interesting, and very useful. The presentation is rich with assignment instructions and links to other resources. The workshop went through Hypothesis basics, using starter assignments, and then how to implement this in Canvas (80% of the participants were Canvas users).

I have used social annotation in some of my professional development courses with faculty and elsewhere, but I want to shape them to let faculty know how to get their own students engaged in their readings. Here are some of the things I learned in the workshop that I would implement in my prof dev courses:

  • Start by annotating the syllabus. Gives students a low-stakes experience using the annotation tools as well as getting them to think about the syllabus in general.
  • Faculty can pre-annotate articles in advance and then include questions about the reading that they can reply to annotations. This models annotation.
  • Open the readings for student questions, resources, and connections. Encourage student co-creation of knowledge. Have them link what they are learning to their workplace, home, other classes, or any previous learning.
  • Have students annotate study guides by adding links to other media, provide clarifications, ask questions. Students can add videos or images to annotations making readings a multimodal experience.

If you have starter assignments that you use to get your students started with social annotation, feel free to comment below or annotate this blog posting!

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Decoding Ice Age Cave Paintings

Amateur Archaeologist Decodes Ice Age Calendar in Cave Paintings –

I love this story because all my life I have heard that these cave paintings were religious or examples of “early art.” It is that, but is also likely early data management, record keeping, and animal husbandry.  It makes me wonder how little we really understand about our relation to ourselves, the world, and our history. History and anthropology used to emphasize the evolution of humanity with cave painters at the starting point and computer-wielding technocrats at the pinnacle. I think that we are, and have been, in a constant state of technological and scientific revolution. Every generation had its transformative new thing: fire, agriculture, animal taming and breeding, astronomical knowledge, writing, cheap paper and pencils, the iPad! I like to think that every generation had its warning against new knowledge, ideas, and practices as well. We are a schizophrenic species: on one hand we value the survival of the status quo to such a degree that we would kill for it and on the other hand, our natural curiosity, creativity, and handiness drive us to make changes and invent – sometimes slowly and incrementally and sometimes in rapid bursts of inspiration.

Cave Painting from Getty Images

Cave Painting from Getty Images

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ChatbotGPT: The New Mechanical Turk

Technical drawing of the mechanical Turk.

A cross-section of the Turk from Racknitz, showing how he thought the operator sat inside as he played his opponent [via Wikipedia].

I am unimpressed with the ChatbotGPT. I asked it to write a sestina, and it could not follow the formula or even write decent rhyming couplets which it used to substitute for the formula for a sestina. It managed to produce some boring and obvious haiku. It is just as bad at writing essays. I asked it to write a five paragraph essay on the literary influence of the poet, Geoffrey B. Cain, and it wrote five paragraphs of drivel that was actually about Hemingway that sounded like a high school essay from a student who only read the back of the books (you know, something that I might have written). I asked it to write an essay skeptical of the concept of artificial intelligence, and it came up with a paper that was basically repetitive, shallow and unimaginative.

ChatGPT was created by the San Francisco based company OpenAI in 2020. ChatGPT was created from GPT-3 which uses a type of AI known as a “large language model” that creates text by combing through masses of data and learning how words and phrases work. The key here is that it “creates text,” it does not think. Its potential applications include summarizing formulaic writing like legal documents or aiding computer programmers with the more repetitive and tedious tasks of programming. ChatGPT is an advanced iteration of GPT-3 that is optimized for natural language dialogue with users. ChatGPT does not do basic research: I imagine that the company could face some legal intellectual property issues as well as the same challenges our students face with how to decide whether a source is academically credible.

So what does it do well? Why are educators supposedly panicking? It can produce essays based on basic prompts that are typically found in college courses. Ideally, essays are an opportunity to have students demonstrate how they apply knowledge: how they understand new information in light of previous learning and, most importantly, experience. Any question an instructor asks that can be Googled has no place in the classroom, or rather, the classroom should be the place where students establish the facts of the case in discussions with one another and the teacher. The essay or assessment should be a record of the process the student took to arrive at new knowledge which, again, is presented back to the class. The only people who should be afraid of AI taking over the classroom are those whose teaching has become rote and mechanical, or those who think that teaching and learning is a product, not practicing a process (forgive the nearly robotic alliteration here).

In my classes (composition, literature, and adult basic education), essays are not produced. I do not want a three-page paper. I want a portfolio that includes a concept map or rough outline, a discovery draft written with fellow students, a rough draft that includes a record of a visit to a tutor (online or at the Tutoring Center), and a final draft. One of the many things that AI cannot reproduce is the relationship that is at the heart of teaching which should be central to any real essay. Even in a “subject matter” class like science, I want to see a concept map at the start of the quarter of the students’ current understanding and an expansion of that concept as they learn. Again, this is just in my work. I know that there are other ways to engage authentic student learning such as having students re-write essays for other audiences, have them change the genre of their work, or using prompts that emphasize students’ lived experiences.

We have been here before. The Mechanical Turk, also known as the Automaton Chess Player, according to Wikipedia, was a fraudulent chess-playing machine built around 1770 and exhibited by various owners until its destruction by fire in 1854. For 84 years people believed that a mechanical man, a collection of gears and pulleys, in the correct arrangement, could play chess. There was actually an expert chess player inside the automaton who would communicate moves to the exhibitor through various hidden, mechanical means. Yet, people believed many things about it from that it was an actual mechanical chess player to the idea that it was a machine possessed by an evil spirit. Its reception was a mirror of the society that produced it. I think this is happening with so-called “artificial intelligence.” That term, AI, implies that we know what intelligence is, how new knowledge is created, and what it mean to think (which we don’t on all three accounts). It also implies that intelligence is an algorithm, and that if we had an algorithm with sufficient complexity, it would either be intelligent or would mimic it enough so that it would not matter if it were real or not.

It is not enough to be against an idea or even just skeptical of it: we should have a clear idea of what the alternative is and a creative application to offer. In this case, essays in the media that announce the “Death of the Essay” are not very useful. They imply that the essay was not dead before. The way that the essay is often used (as a product rather than a process) has failed education for decades. Current outcomes for English classes say things like “The student will produce an essay of ten pages…” The way they are assigned inspire and rewards paper recycling, academic dishonesty, educational travesties such as Course Hero, buying and selling of papers, etc. We have needed to get away from the outcome of a class being the production of a paper to the demonstration of new knowledge and intellectual growth. This would require a great amount of effort on the part of educators: it would require a fundamental change in how most educators think about education. We should at a minimum be asking ourselves how our college assessments are engaging the information with their students’ previous knowledge and experience. Just as important as writing is the sharing and presentation of information which is why I like to tie papers to larger group projects that ask for students to engage with one another. I am hoping that conversations around academic honesty and new technologies will lead to conversations that help education to grow into this brave new world.

The ironic thing is that by playing with ChatbotGPT, we are expanding its vocabulary and its natural language processing abilities. We are the ones making it work. We are the consciousness and creativity behind the algorithm. “It” does not think, all it does is follow rules and process language. As long as we define thinking mechanistically, we can look at ChatbotGPT with wonder.  We are inside the mechanical Turk, and we don’t even know it.


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Remembrance of Futures Past, or Where’s my conveyer belt sidewalk?

Image of the Space Needle and monorail, Seattle, WA, 1962We are rapidly approaching that wondrous time of year when pundits congratulate themselves for being right on technology. I used to make pronouncements about technology quite frequently because I was an avid reader of Popular Science and a couple of other magazines that would now and again publish stories about domed cities on the moon which either looked like Marin County or a five mile in diameter dentist office waiting room (depending on whether you were reading Whole Earth Review or Popular Science). If I had another life, I would love to take up the project of analyzing our vision of the future to see what it tells us about ourselves today. It has only been in the last couple of hundred years that the western mind has been able to wrap its self around the idea that the earth might be a bit older than 10,000 years. It astounds me that people think they know enough about humanity, social systems and technology itself to make predictions 20 years out.

I had a lot of questions about the future as a child. I wanted conveyer belt sidewalks. I could tie a rope to a tree and skate board all day long. But then, do they run all night? Will they eventually squeak? Why would we need them if we are all living in elevated pods connected by monorails? We will all have personal rockets and vacation domes on the moon which brings us to the space helmets. From what I could tell there were two kinds of space helmets, the fishbowl with the vacuum cleaner hose and the one with fins which were far cooler but led to the further question: Do you really want to be in a situation where your helmet requires fins? The fishbowl always seemed fragile or at least unwieldy.

We live in a strange state of being where the future never really gets here but is actually happening all around us. My brother went to an alternative high school that was run by an electrical engineer and his hippie sons. I was hanging out at the local community college playing with their computers (the TRS 80). He came home one day with a floppy disk and was really excited. I told him that it was a ridiculous technology: why would someone use a proprietary disk when you could walk into any Radio Shack and buy a cassette tape for the computer tape drive? I also thought that we would still be using BBSs (bulletin board systems) and that the whole http and internet thing was a fad. Why would you do that when you could upload and download hypercard stacks from a BBS?

If you really want to know how NOT to predict the future, read “The Omni Future Almanac” by the editors of the now extinct “Omni Magazine.” The book was published in 1981. The writers for the magazine would take existing technology such as the laser disc, and try to extrapolate out how the technology will be used 10, 20 and 30 years out to hilarious effect. It not only makes ridiculous predictions about the future but it even makes the claim for “The Only Current Major Athletic Record That May Never Be Broken” – Beaman’s 29′ 2.5″ long jump in the ’68 Olympics. And guess what? It was broken by Mike Powell in the Tokyo World Championships in 1991 by two inches. But notice the qualifier “That May.” That is an important futurist tool. Among my favorite claims are:

  • Moving Sidewalks will not gain widespread acceptance…until the Variflex Moving Sidewalk is developed from practical use in the early 1990s. (p.48)
  • AIDs and cancer cured in the early 1990s and a vaccine for tooth decay soon following. (p.56-57)
  • We will have nuclear power plants orbiting the earth by the early 90s. (p.133)
  • Health care costs will drop 20% (no date given!). (p. 157). Their economic predictions throughout the book are a scream.
  • There will be armies of low-cost robots performing all of our menial labor by 2000. (p.177)

All of the above predictions are variations of the techno-fantasies from the 50s. Of real interest to myself, and those legions that read this blog, is the vision of the future of education. In the cocaine addled 80s it was seen by the writers of Omni to be just another biological function. Educators will track students biological cycles for their optimum learning times (yes, this would be BIORHYTHMS for those having a flashback right now). We will also create better smart drugs to increase their learning. There is a nice Dr. Strangelove statement on p. 213 where it claims that the popularity of adult education will increase as schools become the meeting place for single adults. The book is filled with people learning by watching videos, video disks, and teletexts, etc. then taking tests and “learning.” In other words, the predictions about learning do not go beyond the correspondence school vision of learning. It is important to look at these kinds of predictions because they tell us where the bumps in the road are going to be in innovation. Knowing what expectations are hampering the general public can tell us a lot about where we are not going to go.

Despite my past record of being “wrong,” I have high hopes that my MS in Education will allow me future moments of tele-punditry on the 3-D virtual ElectroTeletron just like Tom Swift.

The cardinal rules of being a Futurist include:

  • Keep it vague and broad (“I see an exponential increase in computer memory storage…”
  • Make numerous contradictory predictions, trot out the winners at the end of the year
    Qualify everything (“Perhaps…” “Something like…” “May be…”)
  • Predict “forces of change” that will cover the tracks of predictions gone awry (“Given current conditions and rates of progress, a new vaccine will…”)
  • Wear a Nehru jacket or a black turtle neck

If you have some favorite remembrances of futures past that turn your mood ring green, feel free to comment below. I will be posting more about predictions in the future which will be here any moment now.

Have a Happy New Year!

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AI and the Death of the College Essay

Robot arm writing with pen.

by Mirko Tobias Schaefer, CC BY 2.0

The Atlantic’s December issue has an essay “The College Essay Is Dead: Nobody is prepared for how AI will transform academia” by Stephen Marche that says that AI is going to make the college essay irrelevant. I say good riddance. I write this as a former English and Adult Basic Education Community College teacher. The formal essay has its uses but for why most of our students are going to school, it is an anachronistic barrier. Most are at college to get a credential for work, not to become academics. At the last college I taught at, I routinely replaced papers with group projects. I would tell the students (especially those who didn’t like group work) that your future employers are going to be more interested in how you work in a team and less interested in your ability to write a 10 page research paper. We use writing in my classes as another tool for thinking and expression, not as an end in itself. My classes were portfolio assessed. Students would have a concept map or outline, a discovery draft created in small groups, a draft for the tutor or tutoring center, and a final copy. We also used things like Pecha Kucha to present papers to the rest of the class. Coming from a Constructivist teaching background, many of my formative writing prompts begin “based on past knowledge and your personal experience, what approach would you take to solving the problem of…” You can’t download someone else’s experiences. Teaching should also be a process of relationship building, so you know your students and have some idea about their experiences.

By emphasizing writing as a product instead of a process, we only encourage the students to go to places like Course Hero or use AI tools to write. The goal of education is to meet the outcome of 5000 words right? Who cares how you get there? The fact that someone can give a chatbot a writing prompt and get an acceptable essay (in some cases) just means that teaching is really broken right now. We have commodified teaching and learning to such an extent that anything that can produce something can “get” a grade.

There may be some legitimate uses for these bots: translation, rewriting code; Bryan Alexander and Stephen Downes were talking on Mastodon about having it create lab reports. I think I have read some furniture assembly instructions that were not human generated.

There is the claim that AI can produce art. If your definition of art is the production of a picture, then I question your definition of art. If producing a picture is art then my Xerox machine is every bit as good as Leonardo Da Vinci.


If a student is turning to places like Course Hero or bots for homework, it means that they feel like they do not have ownership of their own education.

  • Get rid of grading. If you are not familiar with ungrading, check out “So, you want to take the grades out of teaching? A beginner’s guide to ungrading” by Susan Blum, and then take a deeper dive into the work of Jesse Stommel.
  • Emphasize process, not products. I use concept mapping and/or outlines with students depending on the students inclination. This should not just be about ferrying a student through drafts. It is an opportunity for the student to make connections with their peers, tutors, and their own knowledge and experience. The important thing is to help the student find their own process.
  • Mix papers with presentations, podcasts, or video. Once the student has a process for writing, for organizing and presenting their thoughts and research, let them explore other media: blogs, wikis, audio, video, presentations that are pure images.
  • Have the students create assignments in a collaborative process. Teach them to think and work together. Explore open pedagogical practices and courses like DS106 for alternative approaches to the traditional idea of curriculum.

The bot at said it succinctly enough for a “C-“:

The use of Artificial Intelligence (AI) in the essay writing process has become increasingly popular in recent years. AI has been used to help students compose essays, from grammar and spell checking to providing more personalized feedback. AI has a number of advantages over traditional essay writing methods, including faster turnaround times and a more efficient process. But despite its advantages, AI will not end the essay writing process.

First, AI can only do so much. AI works best when it is given a specific set of instructions and data to work with. It is not capable of the same level of creativity and critical thinking that a human can bring to the essay writing process. AI can help to identify errors and provide suggestions for improvement, but it cannot provide the same level of insight and feedback as a person can. AI cannot replace the process of brainstorming, outlining and drafting that are essential for creating a successful essay.

Second, AI is not yet sophisticated enough to understand the nuances of language and writing style. AI is often used to check for grammar and spelling errors, but it is not able to understand the context of a sentence or the implications of certain words and phrases. A human can use their knowledge and experience to create a more effective essay, while AI is limited by its programming.

Knowledge is Power

It is important that we understand as much as we can about AI. Read and learn about this. Follow the stories. The real ethical issues come when we leave things like AI and learning analytics to “experts”: we risk losing the ability to make decisions about how and when AI should be used.

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Remembering Char Gore

Char GoreI worked with Char Gore in my role as instructional designer at Tacoma Community College. She was the most innovative and forward-thinking instructors I had ever met. Back in 2008, she was interested in working in virtual worlds, using wikis, and experimenting with everything. She had an insatiable curiosity. As an instructor, she used that curiosity to solve problems. She was the Health Information Management instructor when I worked with her. She brought me three interesting problems: 1) by the time students got their certificate, they had to learn and relearn computer applications and databases because the technology was changing so rapidly; 2) the students were often parents with other jobs this meant was that students couldn’t always be in the physical classroom or lab; and 3) students need to be able to communicate with those working in the field to stay on top of procedural changes. While she was wrestling with these issues, George Siemens and Stephen Downes were putting together a new learning theory called “Connectivism.” One of the tenets of Connectivism is that students need to learn how to learn because schools cannot keep up with the changing pace of technology. Another tenet says that knowledge essentially resides in networks.

I was helping her to work out these problems when she asked me to co-teach a new class, Health Information Management 101 which was going to be an introduction to all of the technology the students would need to be successful as students, but also in their careers. So the course was going to be not just about technology, but how to learn new technology. It was an innovative class that basically taught me everything I needed to know about how to manage the Covid Era in education. The course was online in our learning management system (Blackboard but later in Angel), live in a lab, and simultaneously live in Elluminate (like Zoom) and on the phone. The last few weeks were held in Second Life (a virtual world), because the nursing department was using it for simulations. It was the first truly multimodal class that I had seen or experienced. If you want to checkout the syllabus, scroll down to the schedule.

Our course was loosely based on the 23 Things blog, but also on research that shows the effectiveness of learning communities and student success. We saw technology as a means of facilitating community rather than a delivery system. I think I am going to have to set up some training on how to teach this because this class would drive many our instructors insane. Requirements for coming to class asked that you have your phone on and participate in texting 🙂

Our syllabus and calendar changed a lot as we learned how this teaching in a networked class works, but syllabus is an example of what we are doing. We presented on this at the ELC conference (the one that was formerly known as Wabug).

For Char, there was never technology for its own sake: it was always about supporting the students and getting to connect with her, the other students, and those working in the professions. I really appreciated the trust she placed in me as a co-teacher. Those were some exhilarating times in education technology. I, like so many, are going to miss her. She was a very gifted teacher and person.

This is from a presentation we used to give about the class. The bulk of our presentation was demonstrating the multimodal course delivery.

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