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Sunday, April 21, 2019

Data-Mongering (2): Algorithms and Agency, GIGO, and more

This is my second of these round-ups; you can see them all here: Data-Mongering Round-Ups. I'm also annotating as I go in Diigo, so you can the Diigo files here: Data-Mongering articles. The editorial comments there are just copied-and-pasted from the blog posts.

It's depressing to keep on reading and learning about this, but especially now that I'm reading Shoshana Zuboff's The Age of Surveillance Capitalism, I can see that the shift is happening at Instructure just as it has in one company after another: under their new CEO, Instructure has realized that its "collateral" data can actually be commodified, turning user behavior into the product that is being sold (Soylent Canvas). Who would have thought that the main outcome of the digital revolution in education would be the triumphant return of behaviorism...? Eegad. Skinner would be so happy. And I am not.

Anyway, here are some of the things I read this week that made me stop and think:


Postdigital: 10 years later, Algorithms and Agency by Lawrie Phipps. This piece gets at so many of my deep concerns right now, and it's "looking back" perspective to 10 years ago shows what a dramatic shift there has been in the normalizing of expansive digital networks, both good and bad. For example, re: TurnItIn and their ilk: "Would the sector have been so fast to sign up to a plagiarism service 10 years ago, if they had known all the student IP would one day be the property of a publishing company?" I too was wildly naive 10 years ago, and guilty of some techno-evangelism I guess. I still love teaching online, but more and more I see the technological space in which I am supposed to do my work (Canvas) as being a threat, not a resource. quote "The naive utopia we described in our 2009 postdigital paper probably only exists in the minds of idealists and tech evangelists. People have designed digital tools, platforms, and other environments with political and financial motives. In our current postdigital world, digital does not serve the social, but through the manipulation of people, it is driving a particular kind of society, one that exploits the weaknesses and and fears of people; enables the rise of racism and xenophobia, and intensifying inequality."

Why ‘learning analytics’? Why ‘Learning Record Stores’? by Donald Clark. I don't always agree with Donald Clark, but I think he is spot on in his criticism of learning analytics hype here: "Perhaps the best use of data is dynamically, to create courses, provide feedback, adapt learning, text to speech for podcasts and so on. This is using AI in a precise fashion to solve specific learning problems. The least efficient use of data is storing it in huge pots, boiling it up and hoping that something, as yet undefined, emerges" (that last bit sounds just like the pie-in-the-sky claims by Instructure's CEO that just because they have lots of data they can get lots of use out of it). Specifically on AI and learning behavior: "Recording what people just ‘do’ is not that revealing if they are clickthrough courses, without much cognitive effort. Just showing them video, animation, text and graphics, no matter how dazzling is almost irrelevant if they have learnt little. This is a classic GIGO problem (Garbage In, Garbage Out)."

One Way to Reduce Gender Bias in Performance Reviews by Lauren Rivera and András Tilcsik. This is a fascinating piece at Harvard Business Review that warns us to be suspicious of any measurement because the measuring stick itself shapes the data in ways that we never realized or intended, like the way that women are more discriminated against if you use a 10-point rating scale as opposed to a 6-point scale. So, before we start measuring everything, we need to stand back and think about the prejudices that are going to inform/deform every supposedly objective measurement we make.


Institutions’ Use of Data and Analytics for Student Success by Amelia Parnell, Darlena Jones, Alexis Wesaw, and D. Christopher Brooks. This is part of an Educause research project, and it's a good reference point for the ways that schools are trying to use data to improve student success. It is such a slippery slope, and insofar as these systems rely on numbers, and grades in particular, I am dubious. My main concern, though, is the fact that in their eagerness to run their own data experiments, schools have given companies like Instructure way too much freedom to commodify and monetize that student data for purposes that go far beyond any local initiative. From this report, I learned that my school is not alone in a strong focus on first-year retention, and the report also shows that efforts are instead going to advising, tutoring, and counseling, which is again the case at my school. IMO we need to focus on the direct educational mission, in my opinion, not just on ancillary supports. Sadly, the report does not recommend strengthening faculty role or involvement, instead the recommendation is to "identify and expand institutionally appropriate roles for IR, IT, and student affairs." But there was also this bizarre quote plunked down in the middle of the discussion of admin and support services: "As algorithms become more sophisticated, there will increasingly be opportunities for faculty to become more engaged in the delivery of interventions." The one bright spot was this recommendation: Recommendation 4: Increase the use of qualitative data, especially from students. Yes, I say, yes! Student voices please!

Developing Minds in the Digital Age: Towards a Science of Learning for 21st Century Education. Big book (250 pages) from Patricia Kuhl et al. at OECD, which I learned about from Ben Williamson at Twitter. I haven't read the book yet; I was really struck, though, by the capitalization of Big Data and Artificial Intelligence as if they were gods or something; what's up with that??? This image is from Ben Williamson's tweet:


Anyway, the book looks useful, and I will give it a read this summer. 


Insurers Want to Know How Many Steps You Took Today by Mark Raymond. I already knew a lot of the content covered here in the NYTimes article from reading Cathy O'Neil's Weapons of Math Destruction, and the whole "health management" business shows just what dangers await us in the "learning management" business: "As machine learning works its way into more and more decisions about who gets coverage and what it costs, discrimination becomes harder to spot." College pricing is already a nightmare (sticker price, as it were, versus what individual students end up actually paying). That's just one nightmare scenario I can see playing out in future, as colleges become increasingly convinced, rightly or wrongly, that they can predict accurately just how students are going to perform (and creating self-fulfilling prophecies as a result of the biases that they institutionalize in this way...).

And from @YujieXuett, a screenshot (which of course I cannot read) of data-mongering in Chinese schools:



Sunday, April 14, 2019

#TotalCoLearner: a great semester of Hanuman learning

I wrote my first data-mongering round-up yesterday and did a lot of reading on predictive analytics in education... and ugh, it's all worse than I expected. But learning is good, and the better informed I become, the more I useful I can be in voicing opposition to this dehumanized education.

Meanwhile, before the weekend runs away, I wanted to write up something about the #TotalCoLearner experiment this semester in Indian Epics, because it has gone GREAT. I've got a series of #TotalCoLearner posts over at my Canvas blog, plus tweets, but this is my first post here about #TotalCoLearner, and it's perfect timing since I just wrote my last story of the semester yesterday, and I'll be wrapping up the class soon, finishing up early as some of my students do too.

So, what is #TotalColearner? The idea is that I do the whole course just like a regular student! That means you can see my course blog, just as the students each have their own blog, and I also have a course project website, just as the students do. One of the best things about all of this is that students comment on my blog and on my website at random just like they comment on the work of other students at random. And yes, they are surprised to find out that I am a student in the class, and it's kind of a weird surprise, but a good one; you can see their comments on my Introduction post this semester here. You can also see their comments on my project at the Comment Wall.

I keep track of my progress as the students do, although I use a spreadsheet instead of the Canvas Gradebook... and, honestly, I feel badly about how clunky and primitive the Canvas Gradebook is; the spreadsheet I use is way more easy to configure based on the different ways I want to check my progress (by date, by type of assignment, by my plan for finding up, etc.). For example, you can see here that as one of the few assignments I have left to do, there's one I should do today, which is writing up a famous last words post. I'll do that after I finish this post.


The nature of the course design means I really can do everything exactly as the students do; I don't have to "pretend" anything... I can just be myself. Admittedly, I'm not a typical student, but the whole point of my course design is that there is no "typical" student. Instead, every student shows up here with their own background and interests, their own skills and gaps, their own goals and priorities. Based on all that, each person is choosing what they want to read and write and other work that they do for the class, week by week, sharing their work via their blog and their website. It's because I can choose that I am able to adapt the class to suit my learning needs and goals, and the students are also doing the same thing for their own needs and goals.

The only difference between my work for the class and what the students are doing is that I can't do the weekly "project feedback" assignments because I do feedback already on all the projects every week as part of my job as a teacher. So, no worries: I just replace that assignment with other optional assignments, mixing-and-matching from the available assignments just like the students also do based on what assignments they choose to do (or not). This semester I did extra credit reading posts because I was reading a ton of stuff.

And as a result, oh my gosh, I LEARNED SO MUCH. And that's because I set myself a really cool and new challenge: I immersed myself in the version of the Ramayana from Thailand known as the Ramakien, and I also gave myself a crash course in the arts of Thailand that are inspired by Rama's story (Khon theater masks, temple sculptures, so much beautiful stuff). I've always known about the Ramakien's existence before, and I knew about Suvannamaccha, Hanuman's mermaid lover... but that's all. I had never read the whole thing. So, this semester, I read the whole thing! (In a terrible translation, but alas, there is no good English translation of the Ramakien.)

So, just like the students, I posted my reading notes week by week on the Ramakien (and I also re-read Chitra Divakaruni's Mahabharata novel, Palace of Illusions, plus I read Samhita Arni's new novel based on the Silappadikaram, a south Indian epic; more about that here). For Tech Tip extra credit, I built some randomizing image widgets with Hanuman art from India and from South Asia, and I even learned how to embed image randomizers into a Google Sites page! On the writing side, I also pushed myself in new ways so that the project I ended up writing was actually not an anthology (my usual writing approach), but a true extended narrative that ended up wrapping around at the end back to where I started, with a Ramakien-inspired story about Hanuman's mother to which I added my own big reveal at the end; that's the story I wrote yesterday: Hanuman and Pirakuan. Figuring out how that story would work may be the biggest writing thrill I've ever had... I'm so proud of figuring out how to bring Hanuman's mother back around into the story there at the end. (And, yes, that means my project ending up being centered on women's stories, which is a theme that comes up again and again in student projects in the class too, finding ways to decenter the men's stories so that we can bring more women's voices into the epic world.) I also wrote some stories here at the blog separate from the project that I was really proud of, especially my story about Mandodari, plus one about Arjuna and Hanuman.

So, for finishing up the class, I need to add that final Hanuman-and-Pirakuan story to my Storybook website, as well as adding another image gallery page to the site, along with some wrap-up posts at the blog, which I'll probably do next weekend. And while I will be sad to end this particular learning adventure (there is so much more I still want to learn about the south Asian Ramayana!), I am also so excited about what I will do for the Myth-Folklore class next semester. I've got a huge (HUGE) Brer Rabbit project that I began over winter break, and that is what I am going to use to ignite my participation in the Myth-Folklore class in the Fall.



And yay Brer Rabbit too! :-)



Saturday, April 13, 2019

Data-Mongering: Platform U and Other News of the Week

It's Saturday and part of me wants to write a happy blog post about open-ended pedagogy and colearning... and maybe I'll do that later (see #TotalCoLearner at Twitter), but I think I need to review the data-mongering articles I read this week. In fact, I might try to make this a weekly round-up of sorts, scrolling back through my Twitter feed and sharing links here. These are articles that I read this week; some are new, but some are old which I only now got around to reading.

And what is "Platform U" you might ask? Read on:


The platform university: a new data-driven business model for profiting from HE by Ben Williamson. This article discusses exactly what I see happening at Instructure, and why I am so unhappy about it: 
Despite studies repeatedly showing Turnitin’s high error rate, and considerable concern over the mistrust it creates while monetising students’ intellectual property, its acquisition clearly demonstrates huge market demand for data-driven HE platforms. It changes how students are valued—not for their independent intellectual development but as raw material to be mined for market advantage.

How Ed Tech Is Exploiting Students [premium at Chronicle of Higher Ed] by Chris Gilliard. This is an article from last year warning about the dangers discussed in Williamson's article, focusing specifically on the students' lack of consent in the exploitation of their data:
When we draft students into education technologies and enlist their labor without their consent or even their ability to choose, we enact a pedagogy of extraction and exploitation. It’s time to stop.

Colleges Are Banding Together Digitally to Help Students Succeed. Here’s How [premium at Chronicle of Higher Ed] by Alexander C. Kafka. A truly horrifying piece about Canvas data mining, this time in the context of the Unizin consortium (my school does not belong). This is exactly what Goldsmith at Instructure promised (Soylent Canvas), and now with endorsement from the educational administrators themselves: they really believe in this data nightmare. Sad to see Jared Stein quoted here; I guess the whole Instructure crew really is on board with the new predictive-analytics push where students are reduced to their clickstreams and pageviews (my thoughts on AI Overreach: students are more than the data they leave behind in an LMS!).
Take students’ clickstreams and pageviews on the learning-management system, their writing habits, their participatory clicks during classroom discussions, their grades. Then combine that with information on their educational and socioeconomic backgrounds, their status as transfer students, and so on. You end up with "a unique asset," says Wheeler, in learning what teaching methods work.

Counting the Countless: Why data science is a profound threat for queer people by Os Keyes. The observations here about the state apply to educational institutions also, and it is surely the most vulnerable students who are going to be hurt most by tracking based on predictive analytics driven by LMS data-mining:
So: trans existences are built around fluidity, contextuality, and autonomy, and administrative systems are fundamentally opposed to that. Attempts to negotiate and compromise with those systems (and the state that oversees them) tend to just legitimize the state, while leaving the most vulnerable among us out in the cold. This is important to keep in mind as we veer toward data science, because in many respects data science can be seen as an extension of those administrative logics: It’s gussied-up statistics, after all — the “science of the state.”

Margin of error in data-driven decisions by Robin De Rosa. This is a great piece on the gap between quantitative and qualitative data, especially in education... data has to be more than number-crunching!
When we ask whether there is evidence for something related to learning, we are presuming that we all agree 1) what learning is and 2) what constitutes evidence. I contend that “learning” is broader and messier than what we generally assess, and also that “evidence” has been reductively equated with quantification and with the assumption that environments in education are controlled. At the core, I think the biggest problem is that we forget that humans aren’t just giant brains walking around: we are also a jumble of social contexts, emotions, and circumstances.

10 technologies that will impact higher education the most this year by By Macy Bayern. Yep, predictive analytics, AI, nudges, it's all there. instead of a pull-quote, I will share Robin's tweet. What she said.



And this cartoon that Bob Calder shared with me is a great way to express how all this top-down data-mongering looks very different from the point of view of teachers and students who are being surveilled. The cartoon circulates in lots of languages, but I think it may have started with the Polish version (?):


He likes it!
Have fun playing, little one.





Sunday, April 7, 2019

Curating a Public Domain of Folklore and Mythology

I've been blogging about Canvas here over the past few weeks, but there are other/better/happier things to blog about, especially now that SUMMER is coming (the semester is over on May 4 for me!)... and summer means PROJECTS. More specifically it means PUBLIC DOMAIN projects, so I am going to write up a post here with some thoughts about what the public domain means for me in general, and more specifically what I hope to be doing this summer.

The Freebookapalooza

The public domain of printed books is, for me, the most important resource for teaching my classes, and it is also where I want to focus my efforts when I finally retire from my job (or get laid off... whichever comes first, ha ha). Thanks to the amazing resources at Hathi Trust, Internet Archive, Project Gutenberg, and Sacred Texts Archive, along with other online book projects, there is a wealth of material in the world of folklore and mythology that is available in the form of full-text books online. Mythology and folklore is a field that really lends itself to these public domain resources, and the main way in which I have been curating those public domain resources for folklore and mythology is at my Freebookapalooza.

The Freebookapalooza is just a simple blog where each post at the blog is about a book online, most of which (but not all) are public domain books. For each post, I include basic information about the book along with link(s) to the book online. I also include a table of contents so that, in addition to the book title, there are also the titles of chapters/stories in the book. Most of the books I am collecting are story collections, and having those titles can be really helpful in deciding just how useful the book might be for a specific purpose. I also include an image of some kind: the book cover, an illustration from the book, or some other image that is relevant to the book's contents. I use those images in the randomizers, like in the sidebar of this blog for example.

Right now, I have 1222 books posted at the blog. My goal, in honor of the year 2019, is to get to 2019 books by the end of the year, and I've got a little reminder script to keep me on track towards that goal. Right now I'm just a little bit ahead of schedule, but not by much, as you can see in this screenshot:



The Public Domain of 2019

The reason I wanted to expand the blog this year was because 2019 was a turning point for the public domain: this year books that were published with a 1923 copyright entered the public domain! Back in 1998 Congress extended the 75 year copyright term by another 20 years, which meant that there has been a long freeze on books entering the public domain. But now we are back on track, so that books from 1923 entered the public domain this year, and next year it will be books from 1924, and so on. Of course, there are books published in 1924 and later which are not restricted by copyright, some of which are even in the public domain, such as books published with a Creative-Commons-0 license, "no rights reserved." There are also other Creative Commons licenses, plus books which publishers put online as a public service while retaining the copyright; it's a whole big beautiful world of digital books out there! So, I include a whole range of full-text books online at the Freebookapalooza, but I focus my efforts on the public domain books which can be shared and reused freely, without any limitations.

Curation Strategies

There are lots of ways to think of the curation process, and I see my work in terms of these general tasks:

Description/Annotation. A book title provides a tiny bit of description, but readers need more. In addition to just knowing about the contents of the book, readers also need a heads up about the limitations of the book, especially when it comes to pre-1924 books in the public domain where there is pervasive racism, sexism, colonialism, etc. That is a big aspect of my Brer Rabbit project this summer, so I'll have more to say about that in future posts. As an example of great description and annotation, the late, great John Bruno Hare's prefatory notes for the books at Sacred Texts are a wonderful model. In so many ways, the Sacred Texts Archive has been an ideal and inspiration for me ever since I first got online back in 1998.

Navigation. There is also a certain clunkiness in working with things that come in book form, so just helping people navigate the books is part of the process, especially since these are not necessarily books that you read from cover to cover; instead, you might just be interested in reading a few selected stories from a given book. So, what I need are not just links to the books, but links that go directly to specific stories in those books (and once again Sacred Texts Archive took this path, with books broken up into separate webpages, one page per story, each directly addressable). Ultimately, a remix system would be great; I manually created the thousands of pages in my UnTextbook a few years ago, and it was a fun experiment, but for the next iteration, I want something more flexible. I've proved the UnTextbook can be a fantastic way to approach the reading for the class, with students choosing their own reading pathways: I would like to open that up even more and make it even more configurable by the readers.

Discoverability. I see discovery as taking place through browsing, randomness, and search. I really enjoy making randomizers for the books (I'm presenting on randomizers at Domains19, whoo-hoo!), and I would like to create environments that are good for browsing. Search is also a priority, and it is a real problem too. It helps to be able to search the story titles, but not all story titles are equally revealing. Full-text search works on the book level, but not so well across books, and it also depends the accuracy of the OCR (which ranges from excellent to abysmal; again, Sacred Texts Archive, along with Project Gutenberg, are invaluable as sources of truly digitized text). Ideally, I would be writing up short synopses for the stories that would facilitate searching, with some use of keywords and other forms of tagging.

Time, Time, Time

What's hard about projects like this is that there is never enough time to do all the things you want to do. Should I spend my time finding more books to catalog? Creating active links in the tables of contents? Writing annotations and synopses?

Luckily I enjoy all of these tasks tremendously, and I've been able to take a very casual, unplanned approach to all this work over the past years since it's really just been a side hobby, with most of my efforts focused on course design, not content.

Now, though, I need to start making some real choices. I feel like I've reached my goals with course design, so henceforth I will be focusing my hobby-time on this kind of work, and I want to end up with some products of real value to me and to others. In particular, I want to create a really good Brer Rabbit Resource Book that could be repurposed and even redesigned by the user for different audiences/contexts (Brer Rabbit in an American history class would look different than Brer Rabbit in an English literature class, etc.).

I also have an idea for a "1001 Public Domain Nights" or something like that where I will pick 1001 public domain story collections, choose just one story from each collection, and weave them together into a book where each story will somehow lead to the next story and so on through shared motifs and themes. Even better: a make-your-own 1001 Nights, where each story would have keys that link to other stories and you choose what you want next: another story with a lion? about vengeance? with a happy ending? etc.

And I still want to do Star Trek Aesop where I will retell Aesop's fables using characters (and animal species) from the Star Trek universe.

Yes, these are the kinds of nerdy fantasies that I have for my retirement, ha ha.

Anyway, for the next few weeks I will just keep on messing around... but when summer comes, I really want to start getting serious and thinking about priorities and possibilities so that I can make good use of my time and find the right technology tools to be using too. I've gone a long way with spreadsheets and blogs, but the time has come for a real database and some real cms.

And I'll close with this curation graphic from the ever-inspired Silvia Tolisano at Langwitches: Blogging as Curation. I am excited about my coming summer of curation! :-)



Sunday, March 31, 2019

Samhita Arni's The Prince and Juggernaut Books

Today is a day of two blogs posts; this one is a HAPPY post where I get to talk about a marvelous new book by Samhita Arni and a fascinating publishing platform in India, JuggernautBooks (the other post is an unhappy reflection on student data-mining: AI Overreach). I did the posts in order this way so that I could end on a happy note!

I'll start with some notes about Samhita's wonderful book, and it's one I can recommend to any and all readers (no knowledge of Indian literature required!). Then I'll say a few words about Juggernaut, which is both an ebook platform and  a writing platform for budding authors.


Samhita Arni's The Prince

I first learned about Samhita Arni's books when I was collecting resources for my course in the Epics of Ancient India; here's the author's page about her at my class blog: Featured Author — Samhita Arni. In my school's library, we have her illustrated Mahabharata (Samhita is a wonderful artist as well as being a wonderful writer), and we also have a graphic novel based on the Ramayana for which Samhita wrote the story, with art by Moyna Chitrakar: Sita's Ramayana. Both of those books are excellent ways to start exploring the world of the Indian epics. My favorite of Samhita's books (well, my favorite ... until now) is her novel The Missing Queen which is an ingenious retelling of the Ramayana that upturns everything you thought you knew about that epic, and about the hero Rama in particular. But I don't want to give anything away here. The Missing Queen is available as a Kindle book, which makes it easy for my students to purchase and read; having books available as Kindles has been really important for me because it means students can choose their own reading, rather than me having to order a textbook for the whole class. (More on that below.)

I think I first connected with Samhita at Twitter (@samarni) when Missing Queen came out, and that means I've been following her progress on this new novel, The Prince, over the past few years. I knew she was working on a Tamil epic, something about an anklet. And, to my shame, I really didn't get why she would be doing that; I'd never heard of the Silappadikaram, much less read it... but I figured that if Samhita was working on it, then it would certainly be worthwhile.

And, oh my gosh: IT IS SO WORTHWHILE. I had ordered a copy of the book from a reseller via Amazon since it does not have a U.S. publisher yet (hey, publishers! look at this book!), not knowing that I could simply grab it at Juggernaut (more about that below). So, the book arrived this past Monday:

I began reading it immediately, and finished on Thursday in the waiting room at my dentist. It was one of those oh-my-gosh moments, and since I was reading an actual hard copy I was able to wave it around in the waiting room and tell people how good it was. I mean, it was just SO GOOD: I had to tell people. Right away!

I'm going to write up a proper review to share at Amazon and at the Juggernaut site, and for here I'm just going to indulge in two very personal reactions.

First of all, it was so exciting to read something totally new, where I had no idea at all what was going to happen next. And the plot of the story is so unpredictable — and so un-Hollywood, so un-fairy-tale: be warned that there are grim things that happen, bad things that happen to good people, bad things that good people do, not even realizing what they are doing. Most of the novels from India that I read are remixes of and riffs on traditional epics and mythology. They are full of surprises, to be sure, like Samhita's own Missing Queen, but they do not have that walking-on-the-edge-of-a-cliff sense of the unknown that this novel had for me. Samhita does a fantastic job of bringing each character into focus and fully to life very quickly, and it was never overwhelming to keep track of who was who and what they were doing (don't let the list of character at the front of the book intimidate you). So, that feeling of newness was very exciting. And now I am also excited to read the novel a second time, knowing what is about to happen and being able to frame the characters in that new way.

Second, it was so affirming to read a novel that is not afraid of the world's pain, and which even provides an attempt at a response to that pain, an authentic response to real pain. I'll just include one quote here, out of context to avoid any spoilers; just some wise words to ponder:
We believe we live in a cruel, wretched world, and that moves us to cruel, wretched acts. The world is beautiful. The truth is that the darkness lies within us. You cannot force out darkness, you cannot cut it out or carve it out. How can you cut your own shadow from under your feet? It is impossible. Each one of us must learn to accept the darkness within us, those things we consider too horrible to reveal. And yet, once we learn this, we discover that this same darkness abides in every other soul, hidden away and in secret — and this moves us to an even greater realization — we find our own selves reflected in everyone we meet, we find out own soul in them.
So, don't you want to read the book now? Of course you do! It is BEAUTIFUL.

And............ you can easily snag a copy at Juggernaut Books, either in your browser or using the Juggernaut phone app.

More about Juggernaut

Juggernaut Books (Juggernaut.in) is the publisher of The Prince, and it is available from them as a hardback book; I ordered a copy from a book reseller at Amazon, thinking that I could not use the Juggernaut app in the U.S. The printed book itself is labeled "for sale in the Indian subcontinent only," and I had assumed (wrongly!) that Juggernaut ebooks were not available internationally.

But... I am so glad to have found out I was wrong about that: readers in the U.S. can indeed use Juggernaut ebooks! After reading The Prince I really wanted to tell my students how they could get a copy of this book and read it, so I decided to explore the Juggernaut Books app just to see what would happen. I installed the app on my phone, and, lo and behold, I was indeed able to purchase an ebook copy of The Prince. I used a credit card, and my credit card company pinged me for an extra security code that I had to use (presumably because it was an international purchase?), but it went through just fine, and I had The Prince on my phone. Even better: I then logged on to Juggernaut Books in my browser, and was able to access my account and read the book in my browser, not having to use my phone (with my eyesight, I do better with big fonts on a big screen).

And now... a whole world of delights awaits me at Juggernaut. I am especially excited to find a series of book-shorts by Arshia Sattar that I did not even know about, retellings of episodes from the epics and Indian mythology that would be wonderful reading for my students. Some of her books are available as Kindle books, but there is a whole series of shorts at Juggernaut that I had not seen before:


It's just a few weeks until summer begins for me and, as always, summer means READING... and I am excited about exploring this new treasure trove of books to read at Juggernaut. And honestly, I could not resist, so I bought just one of Arshia Sattar's shorts just now (my credit card required a security code again, so that is one extra step when purchasing at Juggernaut, but it's easy).


For the summer, I think I will need to subscribe to their Readers Club so that I can just read and read. Yay for summer!

Juggernaut... for Writers!

I've been following Juggernaut Books at Twitter for a while now (@JuggernautBooks) because I was interested in the way they are encouraging and recruiting writers, as you can see here at their About Juggernaut page. Their goals are to get more Indians to read books, to encourage more Indians to write, and to make books less intimidating.


Isn't that exciting? So, I am really glad that Samhita's book was my gateway to landing here at Juggernaut where I will explore and learn more. I'm actually thinking I might try to publish something there. For years, I've thought about doing an anthology of Indian and European fairy tales in order to explore the famous "Indian origins" hypothesis about the diffusion of Indian fairy tale motifs throughout Europe. Regardless of where you come down on that debate, reading Indian fairy tales side by side with European fairy tales is a mind-bending adventure, and maybe I could create an anthology like that to publish on the Juggernaut writer platform.


And if you're wondering about the name, yes, Juggernaut is a word that comes to English from India! More about that here: Sanskrit Word in English: Juggernaut.

So, Happy Sunday, everybody! I'm going to go read some more! :-)




AI Overreach in Education: Teachers and Students Must Speak Out

Two weeks ago I wrote here about the comments by Instructure's CEO Dan Goldsmith in which we learned that Instructure is now going to be mining student data and using machine learning to create intrusive algorithms, telling students what and when and how to learn: My Soylent-Green Moment: Instructure and the Future of Canvas. Even if Instructure could make good on that promise, I still think it is wrong for them to take and use our data for that project. Just as importantly, I also think that project is doomed to fail, and that it will be squandering valuable resources in the process.

So, in this blog post, I want to say something about both of those topics: first, I will explain why I have zero expectation that Instructure will be able to build useful algorithms; then, I will share an article I read this week about student data-gathering in China that shows what could happen if teachers and students do not speak out now to protest these moves by Instructure and other ed-tech harvesters of student data.

Canvas and the Assumption of Sameness

Anyone who's used Canvas knows that it is committed to an assumption of sameness. You cannot even modify your course menus without installing an external tool that then "redirects" menu items, even when the "redirect" is going to a page in your own course. Moreover, you have to install a new instance of the redirect tool app from the app store for every change you make. 


I have seven separate instances of the redirect tool installed in my Canvas courses (you can see here: Myth.MythFolklore.net), and no matter how much I want to rename the "Grades" menu item there is nothing I can do in order to change its name. When we used D2L I was able to change the name to "Declarations" (which suits my class better), but Canvas adamantly refuses to let me change the menu labels.

Why must everything be the same, named the same, look the same, etc.? Apparently students will be "confused" if things are not exactly the same, or so I've been told again and again by Canvas enthusiasts. That paternalistic, condescending assumption is something that has always bothered me about Canvas; I think it should be up to students and teachers to make choices about what works and what doesn't. Based on my 20 years of teaching experience, I don't think students are so easily confused as Canvas assumes that they are. Learning how to navigate difference is something students need to do in school, and minimizing difference is not necessarily doing anybody a favor. In any case, both students and teachers need freedom to customize their own learning spaces in the ways they think are best. 

But Canvas is all about minimizing difference. Sure, you can use the redirect tool if you want, and you can use other plug-ins and tools to bring external content into Canvas (that is the method I rely on most), but there is an abiding assumption of sameness in Canvas, and there always has been. It's not a bug; it's a feature.

Now, of course, as Instructure launches its data mining and machine learning efforts, it is going to be all the more important to keep things the same. Not so that the students will not be confused, but so that the computer will not be confused. Because if you are going to try to bring together all the data, across schools and across curriculums as Dan Goldsmith claims, then you really need to make sure things are the same across those schools and curriculums. That's what will allow Instructure to combine the data to create "the most comprehensive database on the educational experience in the globe" (again quoting Goldsmith).

But here's the thing: not all courses have the same design. Not all teachers have the same approach. Not all students learn the same way; they are not white lab rats genetically engineered to respond in the exact same way to the exact same stimuli in the exact same conditions, as a computer does. Nothing in human learning is ever exactly the same.

Canvas, however, wants to make everything the same. Sometimes the results of that sameness are just annoying, like having to add the redirect tool app again and again to a course. At other times, though, the results are dangerous, like when Canvas decided to start labeling my students' work, incorrectly, with big red labels in the Gradebook. LATE said Canvas, and MISSING said Canvas, even though my students' assignments are not late and not missing. Here's a real screenshot from a real student's Gradebook display... and none, not one, of these labels is appropriate:


Canvas started adding these labels as part of the new Gradebook. I documented the problem extensively at the Canvas Community back in Fall 2017, at which point they rolled the feature back, but then, like a good zombie, it returned from the dead again this semester when my school made everyone switch to the new Gradebook. Nightmare. I'm not going to repeat all the details here, but you can see my posts with the #red ink tag documenting the story at the Canvas Community (that last post about the future of Canvas is the one that prompted the Community Managers to prohibit my future blogging at the Community).

Suffice to say, Canvas has no idea how my courses are designed, and they have no right to be labeling my students' work that way in the Gradebook. There is no place for punitive, deficit-driven grading in my classes (more about that here), and that means there is no place for Canvas's red labels. Those labels are just wrong, completely and absolutely wrong. And my students were, understandably, upset when the red ink missing and late labels showed up out of nowhere. I don't mind apologizing to students for mistakes that I make, but I sure don't like apologizing to students for mistakes that the computer software is making. Especially when it's computer software that I am required to use by my school for grading purposes because of FERPA.

This is just one example from one teacher, but I know that we could document thousands upon thousands of examples of ways in which individual teachers and students are doing work that Instructure's "machine" simply cannot understand. And because the machine cannot grasp all the different ways we do things, that means it cannot actually learn from what we are doing. Even worse, it will learn wrongly and do the wrong things, like putting all the wrong labels on my students.

In short, it seems to me that anyone who believes in Goldsmith's claims about "the most comprehensive database on the educational experience in the globe" does not really understand what educational experiences (PLURAL) are all about.

From Bad to Worse: Really Big Data in China

If you have not read this horrifying/fascinating report about student surveillance and data-gathering in China, then you need to do that now; yes, it's long, and it's worth reading from start to finish: Camera Above the Classroom. You can find the author at Twitter: @YujieXuett.


Power of hashtags: I love the way the investigation begins with a hashtag: #ThankGodIGraduatedAlready. A hashtag, and also a government plan:
In July 2017, China’s highest governmental body, the State Council, released an ambitious policy initiative called the Next Generation Artificial Intelligence Development Plan (NGAIDP). The 20,000-word blueprint outlines China’s strategy to become the leading AI power in both research and deployment by 2030 by building a domestic AI industry worth nearly $150 billion. It advocates incorporating AI in virtually all aspects of life, including medicine, law, transportation, environmental protection, and what it calls “intelligent education.”
So, in the great data-arms race to have "the most comprehensive database on the educational experience in the globe," Instructure is really going to have to up their game. Just clicks and eyeballs are not going to be enough. Now they are going to need our faces too.

Much like the MOOC-boosters of yesteryear, this data collection is presented as something that is really for the students, for their benefit, for their own good:
“Do you know the two types of students teachers pay the most attention to?” Zhang asks. “The smartest and the naughtiest.” Hanwang’s CCS technology was born from the desire to care for every kid in the classroom, even the “often-ignored, average students,” he adds.
The desire to care. Uh-huh. "Class Care" is the name of the system, CCS. But is this how students want to be cared for? As the article documents, the students are not happy about this surveillance:
Back in the classroom, my questions about the cameras evoke curiosity among the boys. Jason tells them everything he knows. There is a gasp, followed by silence. “I want to smash it,” one boy says. “Shhh!” Another boy shakes a warning glance at Hanwang’s camera behind us. “What if the camera just captured everything?”
Some students are indeed disabling the cameras in their classrooms, despite their justified fears. Brave students: bravo!

Privacy? The Chinese ed-tech vendor Hanwang is using the same excuse that no doubt Instructure will use: privacy is being respected because data is only being used "in-house" and not shared with a third party:
CCS doesn’t violate the students’ privacy. We don’t share the reports with third parties, and you see that on the in-class pictures we send to the parents, all the faces other than their child’s are blurred out.
It begins innocently enough, as you can see in this exchange with a principal at a school that has installed the system:
Niulanshan’s principal, Wang Peidong, who has over 40 years of teaching experience, is also dismissive of CCS. “It’s not very useful,” he says. “You think a teacher standing on a podium needs AI to tell her if a student is sleeping in class?”
“Then why is it still used in your classrooms?” I ask.
“Zhang Haopeng is an alumnus of our school. He wants to do experiments here, so we let him. We don’t need to pay for it anyway,” he says, already walking away to get to his next meeting.
Don't think it can happen here? Think again: check out this eerily similar graphic for a rah-rah-data article in the Chronicle of Higher Education:


Labels in the Gradebook. Labels in the classroom. 

Wrong labels. Punitive labels. 

My sense of despair here is enormous, and I am glad that I will be retired from teaching before we have handed everything of importance over to our new data-driven robo-overlords.

Don't get me wrong. I believe in using data: small data, data that fits the educational experience: The Value of SMALL Data and Microassignments. We need to let the educational experience drive the data first. Otherwise, it's just wrong data. And big wrong data is dangerous data. You cannot let that data drive our education.


And speak out. Money talks, and money is ultimately what is driving all of these conversations. So, we cannot just talk: we have to shout! I'm going to keep on shouting. I admire the students in China who are disconnecting the surveillance cameras in their classrooms in protest, and I am going to keep on protesting the overreach of AI in Canvas and their (mis)use of my students' data (even if that conversation cannot happen in the Canvas Community itself).

More to come.



Wednesday, March 27, 2019

The Value of SMALL Data and Microassignments

I'm taking a few minutes this morning to write a post inspired by a Twitter convo yesterday with Yang Fan.


What I want to do here is report on my use of small data to help me in my teaching. I don't have any big data, and I don't want any big data.


Instead, I design my classes so that I get the good, small data I need to help my students make sure they are making progress so that they can pass the course.


It's not rocket science; in fact, it's very simple. That's the point! Here's how it works:

Microassignments. My system depends on using microassignments in my classes so that I can see how things are going from week to week and help students who are not making good progress. Everything in the Canvas LMS works against using microassignments (that's a topic for a separate post), but I am committed to microassignments; this approach is good for the students, and it's good for me too. I've written about this in my Canvas Community blog, and I've copied over two of those blog posts here:
Microassignments and Completion-Based Grading
Microassignments and Data Analytics

Weekly Data. So here's what my data analysis looks like right now, based on manually transferring my students' points week by week into a spreadsheet (because god forbid that the Canvas Gradebook, a faux spreadsheet, actually let me conduct my own analysis of my own data); this is at the end of Week 9, sorting from high to low for the number of weeks a student has been failing the class:


That little snapshot of data tells me a lot! It tells me that right now, out of 90 students in the class, there are 9 students who are not passing, and that has been steady most of the semester, with around 7, 8, or 9 students in trouble in any given week. For me, that's important; I know there are always going to be students who are struggling in a class. If I were seeing a lot more students struggling, I would need to think about some major class redesign, but at this level, I am more focused on working with the individual students rather than some larger course redesign effort.

Something else you can see there is that the cohort of struggling students has changed over the semester. There is one group of students who have been struggling from the very start, another set of students who have just recently fallen behind, along with a set of students who found a good routine for the class and are no longer in trouble. That's what I learn from sorting on the number of weeks students have been in the danger zone.

Data for communication. But the way I usually look at the chart is what you see below, focusing on the students who are currently having trouble by sorting on the current week's column:


Each week I communicate with the students who are currently in danger of not passing the class, but how I do that varies from student to student. I can eyeball the chart to see if they made good progress from the previous week, and if so I can send them an email of encouragement to keep on doing more of the same. By this point in the semester, I also know each student's story, so I can also take that into account when I write to them (e.g., overwhelmed by school, by work, by health problems, by life problems; every student has their own story). I have other columns in the spreadsheet that make it easy to get a fuller understanding of what is going on with each student because I have links to their class blog, their course project, along with their email addresses (I cannot stand the Canvas Messaging system and never use it unless I have to; that is also a subject for a separate post).

Data. Real Data. For me, this system works great. Every piece of work the students do for class is reflected here: their reading, their writing, their class project, their participation at other students' blogs and websites, all of their work for the course leaves a digital trail that is reflected here in those numbers. The numbers are not the work itself, but they are a good enough proxy, and I can then use the links right here in the spreadsheet to access the students' blogs and websites, seeing the work itself with a single click. For example, here is a link to my blog for the class as a student; the different types of assignments have their own labels so it's easy to browse the blog by type of assignments and/or by week of the semester. (I need to write up a post here sometime about my #TotalCoLearner experiment where I take one of my classes each semester as a student, doing all the work just like a regular student; it's so helpful!)

By contrast, the Canvas Gradebook is useless to me, so in another post I will chronicle in more detail the failure of Canvas to help me track the data I need, along with the uselessness of the data that Canvas provides me with instead. Sure, Canvas has data about my students (all those clicks! all those eyeballs!), but the data that Canvas collects is meaningless because it understands absolutely nothing about my course design. Not to mention that it knows nothing about my students and their stories.

But more on that later. For now, I just wanted to sing the praises of small data and how it makes it possible for me to keep up with my 90 students and their progress at a cost of just 10 minutes or so of my time each week.


Microassignments and Data Analytics


I've copied and pasted this old post from my Canvas Community blog in order to reference it here.

Microassignments. Each week of my class students have a set of 6 core assignments plus up to 8 different kinds of extra credit assignments they can complete (here's what a week looks like). Each assignment is worth 2 or 4 points depending on whether it is something quick (maybe 10-15 minutes) or something that takes more time (maybe 30-60 minutes). I ask students to spend appx. 5-6 hours per week on the class, which is the equivalent of 3 classroom hours plus 2-3 hours outside the classroom; the difference is that we have no classroom time since I teach fully online, so all the time that the students spend doing work for the class is active work: read, writing, interacting with each other. There are 30 points every week over a semester of 15 weeks. Students can decide whether they want to complete points for an A, B, or a C (here's how I explain that to them), but I don't get into any of that; I have literally no idea how many students in my class right now are headed for an A or B or C; the students record their points in the Gradebook themselves (here's how that works). My only goal is that everybody should pass the class with at least a grade of C, so that is the only thing I track, and in this blog post I want to show how easy it is for me to do that using a simple spreadsheet.

Analytics. So, on Monday afternoon, after each week is over, I go into the Canvas Gradebook and sort the total points from low to high. I manually transcribe the names and points of any student who has less than a passing grade (70%) for each of the three classes that I teach based on the total points so far. So, for example, last Monday was the end of Week 13. There were 390 points possible thus far, so I recorded the name and points of any student with fewer than 273 points. It takes literally just a couple of minutes to copy out the names and points, and then I paste that into my spreadsheet. You can see the result here; this shows all the students who were failing the class at any point during the semester, with their points in the weeks column, plus one column that tracks automatically how many weeks they were failing. That's literally all the data I need in a single screenshot to show how I measure course progress. The completely steady schedule plus the fine-grained microassignments make this a reliable set of measures. As you can see, some very stable patterns emerge here:


Here's what I see in that data:

Number of students failing. This is the total number of students who, in that given week (column) did not have a passing grade. As you can see, there is a large group of students there at the end of Week 2; a total of 16 students. These are the students who didn't understand at first that they really have to do work for the class every week. They slacked off in Week 2, and they could see immediately the results: not good! Of those students who were failing at the end of Week 2, 6 of them got on track and basically did not have any more serious trouble. Then the total number of students who were failing was pretty steady (between 8 and 11 students) every week up until Week 12. At that point, when they could see the end of the semester approaching, a few students really got their act together, and now I am down to just 5 students who are in real danger of not passing. That's out of a total of 90 students.

Failing weeks per student. This is another way to look at that same data in terms of the number of weeks in which students were failing the class. There is a group of 9 students that just spent 1 or 2 weeks in the danger zone, and of that group only 1 of them is in real danger now (they only recently started having trouble with the class). There are 2 students who spent 5 or 6 weeks in the danger zone, but they both pulled themselves out of trouble by Week 8 and did not have any trouble for the rest of the semester. Then there is the group of 8 students who have been in trouble for more than 10 weeks, and 4 of those students find themselves still in danger of failing now in the last few days of the semester.

These are the only students that I communicate with about their class progress. I send various kinds of assignment-based reminders to the class, especially at the start of the semester when people are developing their class routines, but the only students I communicate with about their overall course progress are the students who show up here on this spreadsheet, the students who are not currently passing. Every Monday after I transcribe the points to the spreadsheet, I send an email to the students who is failing. Sometimes it's a generic email that I send to the students BCC, but sometimes it's an email to the individual student. As I get to know more about them and the problems they are facing (lack of time, procrastination, personal troubles, etc. etc. -- each student's story is different), I can try to use what I know to write useful and encouraging emails that are forward-focused on what they can do to get on track for the class.

Note that this is just a small percentage of my students overall in the class. There are 90 students total, so that is fewer than 20% of the students who even appear here on the spreadsheet at any time, and fewer than 10% who have been seriously struggling. I'm still optimistic that all of them will pass, which is my goal for the semester. Last semester everybody passed, so that was a good semester for me. I'll post an update here on Friday when I see how this semester turns out.

UPDATE: WHOO-HOO! EVERYBODY PASSED! That makes me very happy. I also wrote up a post about end-of-semester evaluation comments from the students, including comments re: grading, here:
End-of-Semester Evals: Grading and Creativity


Microassignments and Completion-Based Grading


I've copied and pasted this old post from my Canvas Community blog in order to reference it here.

In my first posts in this series I gave an overview of my rejection of punitive "bad" grades and also my rejection of so-called "good" grades. In this post, I will provide an overview of my solution to these problems, where I give my students feedback about their work, but they do the grading.

I sometimes call this approach "all-feedback-no-grading" because, from my perspective, that is how it works: I give lots of feedback, but I never put a grade on anything. Students decide what grade they will get, not assignment by assignment but through their overall work in the class.

Again, this is just an overview, and I'll get more specific in later posts. Meanwhile, please feel free to ask questions, and that will help me know what to address in those future posts! I've been using this system for so long now (over 15 years) that it is totally familiar to me, and it's sometimes hard to gauge just what is self-explanatory and what actually needs explaining.

Microassignments

I use microassignments in my classes. I made up the term microassignment to convey the idea that there are no big, high-stakes assignments of any kind. Some of these little assignments take just 10 or 15 minutes to complete; others might take as much as an hour, but not more than an hour — unless, of course, the student gets excited and wants to spend more time; sometimes they do, especially when they are working on their class project.

I advise students to budget a total of 5-6 hours to spend on my class each week; how they schedule that time is totally up to them. Because the assignments are small, students can work on them in short snatches of time, or they can sit down and complete several assignments in a longer study session; it's all up to them. I love teaching online for just that reason: I am glad to take advantage of any time the students can find for this class.

Success is the sum of small efforts,
repeated day in and day out.

Gradebook Declarations

As students complete each microassignment, they record the completed assignment in the Gradebook using a "Gradebook Declaration," which is actually just a true-false quiz. The quiz contains a checklist of all the requirements for the assignment to be complete, which is more or less detailed depending on how complex the assignment is.

I include the checklist text in the assignment instructions, as you can see here: Week 1: Storybook Favorites

The Declaration checklists are also a good reminder to them about exactly what they need to have done for the assignment to be complete. Students answer "true" to indicate the assignment is complete and, presto, the points go into the Gradebook.

There is no partial credit; students get credit for completed assignments only. If they start an assignment, but do not have time to finish it, they can finish it the next week; everything rolls forward that way, so no work is lost.

The students do all this grade-work themselves. As they complete each and every assignment, they do a Gradebook Declaration. They find it a little strange at first, but they quickly get used to it. Admittedly, getting the students to slow down and read the Declaration sometimes takes a little work on my part at first; a few students start out treating the checklists as a kind of terms-of-service which they agree to without reading, but when I follow up with them about that, there are no further problems. Because every assignment leaves a digital trail at their blog or at their website, there is clear accountability. They know that; I know that. During the Orientation week, I watch all the blog posts carefully to make sure students understand how the system works.

Student Choice

There are many assignments students can choose to complete each week. Take a look here for a typical week:
Week 3: Myth-Folklore and Indian Epics.
(I have the same assignments in both classes; it's just the content that is different.)

As you can see there, each week has six "core" assignments which provide a week-long workflow: two reading assignments, a storytelling assignment based on the reading, blog commenting on other students' stories, a semester-long project, plus feedback on other students' projects. Most students complete most of the core assignments. Those assignments add up to a total of 30 points each week.

In addition there are eight "extra" assignments, and those add up to 20 points each week. Students can use those to make up any of the core assignments they missed. They can do extra assignments if they want to do more of something (more reading, more commenting, more technology, etc.). Students can also use the extra assignments as a way to accumulate points if they want/need to finish the class early. It's all good.

So, there are 50 possible points each week, but there is no expectation that students would do all that work. The idea is that they CHOOSE what assignments to do. They can focus on the core assignments and only on the core if they want, or they can mix in extra assignments. They can also work ahead if they want. It's all up to them.

Class Progress

As the points accumulate week by week, students can see if they are on target to reach their desired grade. Some of my students want/need to get an A. Some of them just need to pass the class with a C to graduate. Some of them can even take a D and have the class count for graduation; I always tell them to check with their advisor about that, though, because Ds do not always work for Gen. Ed. credit or for financial aid. Here's the chart they can use to track their progress: Progress Chart

My own goal is just that every student should pass the class. As far as I am concerned, this is a P/NP class. Whether a student wants to get an A or B or C makes literally no difference to me, and I do not know until I check the Gradebook at the end of the semester who is getting what grade; I only monitor the Gradebook for students who are in danger of not passing the class. More about my DIY data analytics here:
Microassignments and Data Analytics

Yes, It Works!

Yes, this is all kind of weird... but the students really like it. Here is every comment students have made about grading in my end-of-semester evaluations since we went digital back in 2010: Grading: What Students Say

I've been using this system, largely unchanged, since I started teaching online in 2002. The reason I haven't changed it much is exactly because of that student feedback: it works. Students like it. Students REALLY like it. And they like it for the reasons that are important to me: they feel in control of their grade, they are not stressed, it encourages them to be creative and learn a lot.

When I introduce this admittedly strange grading system to the students in their very first assignment for the semester, I include a link to those student comments. I can go on (and on and on) about the advantages of this system, but the most powerful words come from the students themselves! Here's how I introduce all this on the first day of class:
Designing Your Course

Thoughts from a Brand-New Student...

And since some of my students have started already for Spring 2019 (flexible schedule also means starting early if they want), I will share this screenshot of a blog post that popped up literally just a few minutes ago. I think this says it all; one of the Orientation Week assignments is for the students to let me know if this all makes sense and what they think. Here's what one of the students is thinking right now, at this moment. And it sounds good to me! This student understands not just how the course works but why it is set up this way, and I am excited to see what she will do with the reading and writing as she moves on to Week 2, and I'll see how that goes right there in her blog.


And maybe that should be the subject for my next post: how blogging and other visible student work is an important part of the shift from grading to feedback! More on that tomorrow. :-)

Sunday, March 24, 2019

The Paradox of Canvas's "Big Data" and Lack of Search

If you haven't read Phil Hill's piece about Instructure's new pursuit of machine learning, start there:
Instructure: Plans to expand beyond Canvas LMS into machine learning and AI

In particular, note Goldsmith's claim about the Instructure database: he says it is "the most comprehensive SaaS database on the educational experience." I'll set aside for now the very depressing view of "educational experience" which Goldsmith is promoting here (but more on that later), and I'll also set aside the claim about "most comprehensive" except to note that it sounds scarily similar to the boasting of Jose Ferreira, Knewton’s founder and former CEO: “We literally know everything about what you know and how you learn best, everything” (more at Marketplace).

What I want to emphasize here is the stark contrast between what Instructure is doing with data for its own purposes and the data it denies to teachers and students who are trying to use Canvas LMS: specifically, the fact that you cannot search the content of a Canvas course.

That's weird, right? 

It's very weird. Read on to find out more.

Seek and Ye Shall Not Find: No Search in Canvas

One of the biggest advantages of digital content is that it is searchable. So, you would think that if teachers go to the trouble of using Canvas tools to create content, then they would be able to search the content they create, and the students would also be able to search the content.

But... you cannot search your content in Canvas. You can create Pages, sure, and you can use the "rich content editor" in order to do that. But you cannot search that content, and your students cannot search the content either. 

Here's what the Pages look like to a student. No search box. No searching.


Here's what the Pages look like to the teacher: again, no search box. Add a new Page? Yes. Edit? Yes. Delete? Yes. Duplicate? Yes. But... Search? Nope. Thou shalt not search.


You have to remember everything yourself. Memorize. With your own brain. Because the Canvas database, big though it may be, is not going to help you here.

Given all the other problems with Canvas Pages (no folders, broken links if you try to rename a page, etc. etc.), I cannot imagine why anyone would actually choose to use Pages to develop content, and I feel really badly for all the teachers who, because of school policies, are required to use Pages for their content.

Back when Canvas was just a scrappy LMS built on a shoestring budget, sure, I guess it sort of maybe kind of made sense that they skipped the search feature of the Pages area. Although even that is still very strange IMO. 

But Instructure's CEO is now making claims about how big their database is and all the data mining they are going to do... while teachers and students still cannot even search their own course content.

Project Khaki Did Not Deliver

This problem was supposed to be fixed after the Project Khaki back in 2017 when search was one of the features voted up and supposedly a priority for engineering resources. (Disclosure: I participated in Project Khaki that year.)

But that Project Khaki commitment led nowhere. The engineers scoped the project as "global search," and then they decided that they did not have the resources available to implement global search. Did they rescope the project? Like maybe the ability to search course content in Canvas Pages? Nope. They did not rescope the search project. It's just... deferred. And is there any timeline about the availability of search coming soon? So far as I know, there is no such timeline. Which means it is now the year 2019, and neither teachers nor students can search their own Canvas Pages to find something they are looking for.

Of course, if you can pay...

Given that search is a real need, perhaps it is not surprising that, yes, there is a third-party vendor, Atomic Jolt, that is willing to provide a Canvas search feature for you. Just look at all the happy Atomic searchers: laughing and smiling. Atomic Search users can search for content, they can save time... except they have to pay more money to do that. 


The existence of this paid service does prove one thing: schools really want to have a search option. So much so that they are willing to pony up additional money to pay another company simply in order to be able to search their course content and allow their students to do the same. (My school does not pay for this service.)

The Google Work-Around

The irony is that you can use a Google work-around: just open up your Canvas course — and, yes, this is my favorite thing about Canvas: you really can open up your course with real URLs, linkable and searchable. Once you do that, Google will be glad to index your content and return results via Google search. So, because I keep all my Canvas spaces fully open, I can use Google as my search engine even if Canvas will not let me search. 

Each course has its own distinctive subdirectory, so I just need to add site:canvas.ou.edu/courses/54178/ to search my Widget Warehouse course site for any term. For example, if I am looking for cats, I can search like this:



You can also do this across a school. So, for example, adding the search delimiter site:canvas.ou.edu/courses to a Google search will search all the open course content at my school. The problem is that very few instructors (how many? I don't know) choose to open up their courses. All the cat results you get this way are still my cats, except that now these are results for all the cats in my Canvas Pages across all my OU Canvas course spaces:



Yes, Google is also extracting its own value from this search to build its advertising empire, but at least it is also returning some value back to me in the ability to perform my own searches.

Instructure, meanwhile, is extracting value from our course content as part of its machine-learning pipe dream, but they are not even letting us perform our own searches of that data.

Plus, Instructure is also missing out on one of the best possible data sources as a result: if they did let us search, they could learn a lot and share what they learn back with us.  Assuming that Instructure is willing to let us make use of our own data, in this case our own search history. Which is a very big assumption. And one I am feeling completely pessimistic about at this time.

LMS: Undermining Digital Literacy

One last point: I've argued before that the LMS is bad for digital literacy, and this lack of search is a perfect example. For students to become skilled users of digital tools, they need to use real tools, and the lack of search in Canvas shows how it fails as a real web tool. Search is one of the key components of digital literacy, but Canvas doesn't allow students to search, which further means that Canvas does not help students to learn how to search well.

So, while Instructure is busy mining our data supposedly in order to further our education, it is at the same time depriving us of one of the key educational tools that we need.

The year 2018 went by without a search feature in Canvas Pages.
I wonder where we will find ourselves at the end of 2019...?
I promise to update this post if/when news is available.

Meanwhile, you can learn lots more about web literacy, and about search in particular, at this nifty resource from the Mozilla Foundation: Web Literacy: Search


Plus there's a Latin LOLCat who knows all about the power of search... and, yes, I found this cat at my Latin LOLCats blog by using the search feature there. :-) 

Quaerendo invenietis.
By seeking you will find.