E-Learning, Digital Learning, Digitally Transformed Learning---Do They All Mean the Same?

Nowadays we often hear that the term "e-learning" is a bit outdated, we should rather speak about "digital learning" or even "digitally transformed learning" when we talk about things like using learning management systems (LMS), students collaborating online, etc. Are these terms interchangeable, then? Does it even mean that in learning we are ahead of other areas which are yet to be digitally transformed---right now or in the near future---as we have been doing e-learning for 15 or 20 years now, or perhaps even since the 1960s (have look at PLATO)?

As for other fields, you could talk about the aspects of digitization, digitalization, and digital transformation of learning, and what they imply when it comes to skills and competences you should have and you could acquire. We will do this in a separate article.

In an attempt to look at similarities with other areas, we could try to define various waves or eras of learning, or even try to define "learning revolutions" in analogy to "industrial revolutions." And then we would arrive at terms like "Learning 4.0" (to have the same version number as in "Industry 4.0," or rather "Learning 3.0," or maybe "Learning 3.11 for Workgroups---OK, just kidding). And then we would need cover terms to name the eras of learning.

When we take the industrial revolutions as tertium comparationis, we have the first revolution with the advent of looms---mechanical work done by hand had been automated on a small scale---and the steam engines---the automation of mechanical work at a larger scale. The second revolution was the advent of electricity. This also involved the introduction of the production of electricity as a utility, as a service. It became possible to produce energy at some place and transfer it over fairly long distances to run machines. It wasn't necessary any longer to produce energy directly in or very close to factories. Ford introduced assembly lines and mechanical work done by hand changed again, workers specialized in specific areas. The third revolution came with the introduction of computers, we got CAD/CAM, industrial robots, etc. In all those processes, the human was the main factor: humans control and regulate, they make decisions with the help of machines.

Now in the fourth revolution we face the merging of real and virtual worlds, we not only interact with machines, we let machines decide and call this digital transformation. Computer programs decide whether or not you are creditworthy---some years ago, the banker would inspect the gathered and aggregated data and then make a decision; now the computer decides on its own based on models it created from relevant and irrelevant data using machine learning. We are close to let machines decide whether or not you are prone to return to your bad habits after rehab or prison (see, e.g., AI Judges and Juries in the December issue of CACM).

Let's look at education, where can we position "e-learning"? With the advent of tele-learning in the 1950s and 1960s, we find some aspects of automating parts of teaching. But even earlier, in the 1920s, we have actual machines: mechanical devices as first introduced by Sidney Pressey to let people answer multiple choice questions. Later Skinner developed them further to provide automatic, immediate, and regular reinforcement, and thus trigger learning. And it could be shown that students actually learned while using those machines. Already then we find the discussion whether or not machines would replace human teachers in the near future.

When we look at developments in the 1970s, with the PLATO systems, we find the same ideas: to provide automatic, immediate, and consistent feedback. That's part of "teaching," though, it doesn't redefine "learning"!

Then, at the start of the 21st century, we integrated computers into teaching and learning. We often talk about "e-learning," but we only rarely talk about "e-teaching." However, even with LMS and all of their still improving (or let's rather say: accumulating) functionalities, we still focus on automatic, immediate, and consistent feedback. That's what all the e-assessment, peer activities, forums, etc. are about. And we all agree that just using your fully-fledged LMS to distribute your PowerPoint slides doesn't qualify to be named "e-learning." But still, we have no actual interaction of human and machine, you just get feedback and then decide what to do next. So "e-learning" in this sense is just a contemporary (as in "use mobile electronic devices") teaching machine.

But wait, we also had intelligent (adaptive) tutoring systems in these first years of e-learning! Actually, those teaching machines by Skinner as well as the PLATO V were also intelligent tutoring systems (ITS)---and they were advertised as such. So also this isn't a brand new idea! For various reasons, these systems weren't successful at the time. But most contemporary e-learning research doesn't refer to those old publications when talking about adaptive systems. But maybe now, given the available computing power, it would be time to revisit those old ideas. If technology (including bandwidth) for distribution and interaction was the bottleneck back then, we may be able to solve those issues now.

There have been various attempts around the start of this century, though, tackling another potential bottleneck: the learner model. Using computers, it was more comfortable to implement and maintain various learner models accounting for different learning paths through the material towards the final goal of acquiring some specific competencies or skills. Attempts like <ML>³, (Multidimensional Learning Objects and Modular Lectures Markup Language) or elml (eLesson Markup Language) aimed at foreseeing learning paths and provide students with the appropriate next steps depending on previous actions and (formative) testing outcomes. It turned out that creating such material was rather challenging and demanding. The same was true for testing formats like SET (Satzergänzungstests), which allow you to answer a question by adding parts of sentence(s), an instantiation of "Reihenerweiterungswahl" (Closed Sequence Selected Extension Items) according to the typology of Rütter (Rütter, T., 1973. Formen der Testaufgabe. Eine Einführung für didaktische Zwecke. C. H. Beck, München.) as we showed in a paper. Even with a rather sophisticated editor, it was a nightmare to produce those tests.

Writing learner models using rules, manually, is probably not working. One simply cannot foresee all possible activities and interests. A truly adaptive intelligent system would need a model covering all those possibilities. For now this seems achievable only by using machine learning. In the way we construct language models we could create learner models to feed into tutoring systems and let the machine decide what experience the learner makes next, what problems the learner should solve next, etc. And there we would have it: the digitally transformed teaching/learning as a blending of real and virtual worlds with the machine not only providing information to support human decision-making but with the machine deciding and interacting with the human. Of course this also raises ethical questions: is it OK to have the computer model you as a learner? But that's along the same lines as in "is it OK to have the computer model you to decide whether or not you will get this credit or whether or not you can get that life insurance?"

As long as we identify "e-learning" with "using the full potential of LMS and (apps on) mobile devices" (does anybody remember "clickers"? You can have them as apps now, yeah!), we don't talk about the digital transformation, but about the electronic re-engineering of teaching machines. But as long as we're just deploying "electronic teaching machines," we should stick with the term e-learning. Oh, and we still have vast communities who use LMS as PDF or PowerPoint distribution vehicles only, there isn't even digitalization involved, only digitization.

Clearly, with all those MOOCs around where you interact with the video and the instructors/tutors, a lot of logging is could be going on. This data will be used to model learners. And as for language models in Natural Language Processing, those models created by machine learning might be not exact but appropriate or good enough for specific tasks. The big issues there revolve around the questions of "which features matter, which features do you use?" The same will be true for learner models or learning models. What we have in e-learning are various models of teaching, and those could be described by manually crafted rules. They are based on hundreds of years of research and developments in didactics and pedagogy (and schools thereof). For determining and weighting features for learning, we shouldn't leave the fields to the usual suspects of Big Data processing. This research and development and thus the digital transformation of learning should be driven by the field of teaching and learning, by the experts involved with didactics and pedagogy.

Back where I started

So, we have 2018 and I'm an e-learning specialist at a university of applied sciences in Switzerland.

Last week I found my old business cards when I was looking for something else in my desk drawers. And I realized that exactly 10 years ago, I also had business cards as e-learning consultant of a university of applied sciences in Switzerland — in 2008, I was at the School of Social Work at the University of Applied Sciences Northwestern Switzerland (HSA FHNW), today I'm with the Bern University of Applied Sciences (BFH), at the Competence Center for Higher Ed Didactics and E-Learning. And the fun thing is: exactly 10 years after, I now have a 50% permanent position as I had then, I do similar things — although I'm not on my own as I was 10 years ago but a member of a wonderful team — , and even my salary is the same (yes, I also found old pay slips when looking for documents needed for the 2017 tax declarations).

So, what did I do in between — and was it worth it when I end up almost where I started? Let's look at the business card circle (the current card is at the top, the starting card is the one right to it and the circle goes clockwise).

The e-learning job at HSA FHNW wasn't my first one, but the first outside the University of Zurich (and I even had an e-learning job there from 2004 to 2008). After that I held various positions and did various things as senior researcher at the University of Basel, as acting professor at the University of Konstanz (I blogged about that experience and most of the posts are still quite relevant, I guess), as postdoc and scientific coordinator at the University of Stuttgart, as scientific coordinator and later as senior researcher at the Institut für Deutsche Sprache in Mannheim, as guest professor again at the University of Stuttgart, and as researcher at the University of Bern. All of those activities where related to my other live as computational linguist and writing researcher — I used e-learning activities and tools for my teaching, but I wasn't active in that area during that time.

I had left the e-learning business in 2010 for a chance to pursue my scientific career and to become a professor one day. Turns out, I didn't succeed.

Yes, I published a lot, yes I finished and defended my thesis (so at least I have a different academic title on my current business card), yes I grew an international network, yes I founded two workshop series (both of them have fallen asleep because of decreasing interest), yes I edited various proceedings (oh, and yes I know a lot about publishing and “added values” by publishers now and I do have an expletive explicit opinion about those and their work flows), yes I was what's called “an active member of the scientific community” (I founded and still run a doctoral consortium, I'm co-leader of a SIG, I was a newsletter editor), yes I was active in various scientific areas (computational morphology, writing research, document engineering, corpus linguistics), yes I taught a lot (as acting and as guest professor I did the usual German 9 hours per week (so 3 to 4 courses per term) teaching load and I taught one course per term at the other places), yes I have been acting professor, yes I reviewed for various prestigious conferences and journals — all those activities you find listed as recommended or even necessary on your way towards professorship. But I'm still not a professor.

However, I grew older.

And last year when I got the chance to “go back to e-learning” I decided to no longer actively pursue the scientific career road — my chances will not increase. I will not apply for grants any longer, I will reduce reviewing activities, I might continue publishing but will carefully chose where and how (considering issues of access and submission formats). I hopefully will continue teaching and I hopefully will get chances to do small scale research at the intersection of document engineering, linguistics, and writing research. I will not apply to scientific jobs — my list of rejected or even unanswered applications is long enough now. I'm not sure whether all of this equals “I'm leaving academia”, but time will tell.

So the question remains: was it worth it? I guess so. I got chances to do research, I taught a lot (and I didn't know that I actually enjoy teaching before!), I could present my research at various places I wouldn't have visited otherwise, and last but not least I got to know a lot of people with similar interests, some of whom I call friends today.

Professor for one year (week 48): Who does profit from MOOCs?

Actually, this blog post was scheduled for the first week of March. However, the topic is still relevant even a few weeks later. Just pretend it's early March 2014 (i.e., cold and rainy) while reading.

During our visit of US higher ed institutions last year, we met James P. Honan from Harvard's Grad School of Education. We discussed various things and also touched e-learning and MOOCs. Honan told us about his experiences as a teacher and consumer of e-learning courses and contents and then some musing started about the underlying principles of MOOCs. I will briefly follow up here.

From a didactically point of view, massive open online courses (MOOCs) are old wine in new skins. I wrote about this part in an earlier post. E-Learning courses hosted on servers of universities started around 2000, and courses supported by current technology are as old as TV. The only new aspect is the "massiveness". At a university, e-learning courses are offered to the students of a particular subject at a certain point of their studies enrolled at that specific university. So there might be several hundreds of students using the materials of a course.

Going "massive" and "open", those courses skip restrictions -- everybody can take part -- but no change in didactics might be involved. Allowing more than only a few hundred users to access the material may involve changes in server architecture, maybe clustering, but not necessarily in the general technology used for user interaction and the like.

However, someone has to run those servers and someone should be paid for maintenance. The first MOOCs were developed from scratch, not just scaled e-learning courses (there will be another post on this aspect, stay tuned) -- maybe the content providers would need some payment, too. But declaring those courses as "open" doesn't only mean everybody may join, but also means nobody should pay anything for taking part. So where should the money come from to pay development and maintenance?

Honan gave a hint when he told about the fear of teaching staff at universities: Attending a course may have two main reasons. People just are curious about a certain topic (a), or people have to acquire certain knowledge (due to job demands or the like) and that involves getting a certificate (b). For a certificate, attendees would have to do some sort of exam. And this exam would have to be assessed and graded by someone. And guess who is qualified for assessing and grading student work? Right, teaching staff.

So while in the early years of e-learning instructors feared to be replaced by machines, the advent of MOOCs makes instructors fear to be used for grading only. And in the end, to be replaced by cheap grading staff -- why should you need highly qualified academics when you can have people trained to grade certain exams only. MOOCs would not result in replacing humans, but in downgrading educators.

At the one hand, this nightmare might not become true to the extend instructors might expect -- similar to the fear of teachers being replaced be educational TV shows or e-learning courses --, but on the other hand, that's probably part of the business model of companies like Coursera, edX, or Udacity. Participation in MOOCs might be free, but to get a certificate you would have to pay -- part of this money might get down to the graders, but most of it will go to the company owners. Those certificates don't have to cost a fortune. Look at prices for apps -- as long as the audience is big enough, small fees are fine.

Of course, with "certificate" a mean any piece of paper stating that you passed the exam of this course. As soon as participants actively demand official certificates of the hosting institutions, e.g., from Stanford or the MIT, another question arises: How much is such a certificate worth? As an on-campus student, you would have to pay a lot of money -- if you would ever get accepted in the first place. However, nobody would pay several thousand dollars for an on-line course offered or developed by Stanford or MIT staff.

So maybe several hundred dollars? But wouldn't that be a hard competition for those Ivy League Universities? If I could get a prestigious certificate without moving to Stanford and without enormous debts, why should I even send an application to Stanford? But here we're already touching another topic.

Professor for one year (week 21): The WWW

The University of Konstanz uses ILIAS for E-Learning.  So far, I also worked with OLAT/OpenOLAT and Moodle, I will compare all three in a later post.  Today, I will only comment on the WWW I found in ILIAS.  No, not the World Wide Web, but the World's Worst Wiki.


That's how the editor looks like, you can modify text and make it bold, italic, etc. And you can itemize and enumerate things or have three levels of headings.  That's what I did in this short text: three headings (level 2) followed by a bit of text each.

Then you hit "Save" and face this:

The text is broken into small pieces and you are no longer able to edit the text as a whole!  You could edit or delete one of the headings or one of the paragraphs independently.  Awkward!

Sure, for the visitor of the page, it looks like it was intended:

With an interface like this, it's no fun to edit wiki pages.  Therefore I can forget about this activity in my courses -- I always have students organize group work, discuss ideas to present, collect material, and decide who is responsible for which part.  All of this involves structuring text, moving parts of written text around, editing and restructuring.  Which is impossible with this GUI.

Professor for one year (week 6): Maybe the "e" in e-learning in fact stands for "evil"?

These days, Massive Open Online Courses (MOOCs) are discussed widely.  They are a success story and they are criticized.  The aspect of "massive" leads to audiences of several thousand students, the aspect of "open" suggests that no tuition has to be paid for attending these courses.  The rest, i.e., "online courses", is a rather old concept.

The development of online courses was one of the key factors of "E-Learning".  Roughly ten years ago, a lot of tax payers' money went into such projects.  Online courses were developed to suit the needs of growing student numbers and to make use of the Internet for teaching ("learn anything, anywhere, anytime").  Students could attend these courses as a replacement for traditional face-to-face lectures.  For example MiLCA was supposed to facilitate learning computational linguistics.  It was developed at the University of Tübingen and some students from the University of Zurich successfully completed the course as part of their studies in Zurich.  However, this was pre-Bologna, i.e., for most of the courses during your studies, there were no formal exams.

Some of these courses are still in use and some universities extend these courses into MOOCs, like the University of Marburg.  They aim to make these courses count towards a BA or MA degree, which means you can earn credit points.

And here the problems start:  To earn credits towards your degree, the attended course has to fit the concept of your study program.  As I wrote last week, the concept of what a module is, differs from university to university.  There might be certain requirements for successfully completing a module like compulsory attendance or an oral exam.  How does that fit into the concept of an online course?  Can a certificate stating completing the online course on phonetics from University of Marburg be used as a replacement for the phonetics course at the University of Konstanz?  Which of the two universities is responsible for quality management?  Who can define how many credit a student can earn?

A colleague even told me that some universities already face a rather odd situation: Students collect online course certificates fitting the overall curriculum of a specific study program and thus avoid attending these courses at their home institution -- i.e., they avoid rather challenging exams, but they want to be awarded the more prestigious degree of that institution.

So if a university starts to accept certificates from online courses offered by other institutions, they open Pandora's box.