Friday, February 12, 2016

Personal Learning MOOC



Instructor: Stephen Downes

This course explores the topic of learning in three ways: first, through an examination of research and development issues related to the topic; second, through interaction with a personal learning environment (specifically: LPSS) to take the course; and third, through activities supporting the development of a personal learning environment at a conceptual level.

Course objectives: participants will develop an appreciation of different models of online course delivery, ranging from the traditional LMS through connectivist MOOCs to potential future models of personal learning and performance support.

Course environment: NRC01 Personal Learning will be delivered using OpenEdX and will include text-based content, videos, discussion, and exercises. Participants will be also invited to explore additional learning environments, including the gRSShopper, LPSS.me and Arke prototypes developed by NRC. In addition, participants will be encouraged to explore and work in online environments related to the topics covered in the course and report their findings in the discussion area or their own website. Participants may also be subscribed to a daily newsletter for the duration of the course.

Course Tag: #NRC01PL

Course Registration: https://openedx.lpss.me

Registration is now open!

February 22 – April 8 (7 weeks)

Week 1 – Feb 22  -  Learning Through Practice
The first week will introduce participants to the online learning environment, exploring the EdX learning environment, and exploring similar MOOC environments that have been developed in the last few years. Main environment: OpenEdX 

Week 2 – Feb 29 – Content Knowledge v Practice
In this week we will challenge some of the presumptions about learning embodied in traditional learning management systems. What are the alternatives? We will look for practical examples of online learning outside traditional college and university environments. Main environment: OpenEdX

Week 3 – March 7 – The Case of the cMOOC
The concepts and ideas behind the connectivist MOOCs are explored this week, and participants will have the opportunity to explore the gRSShopper content management and distribution system developed to support the first MOOCs. We will examine how connectivist MOOCs employ social networks to facilitate and encourage multiple perspectives to emerge around a single subject or area of enquiry. Main environments: OpenEdX, gRSShopper

Week 4 – March 14 – Personal Learning Environments – a History
We look at the concept of the personal learning environment as it developed in the 2000s, examine some relevant PLE projects (PLEx, ROLE), Participants are introduced to the LPSS.me prototype and we examine some core concepts of personal learning: content aggregation and personal cloud. Main environments: OpenEdX, LPSS.me

Week 5 – March 21 – Learning and Performance Support Systems - an Overview
Core concepts of the LPSS.me environment are examined, including personal learning records, personal learning analytics. We consider what it means to learn in a personal learning environment, exploring the concepts of competencies and learning objectives. Main environments: OpenEdX, LPSS.me

Week 6 – March 28 – The Personal Learning Assistant
In this week we explore the practical application of a personal learning environment. We explore how people connect with each other to share and support learning, how activity records are recorded in third party environments such as NRC’s NeuroTouch, and examine how personal learning leads to performance support. Main environments: OpenEdX, LPSS.me or Arke

Week 7 – April 4 – Applications and Extensions
What does the future look like for personal learning. In this final week we consider the types of applications and services that could grow around a personal learning environment and think about how personal learning environments could play a wider role in all parts of participants’ lives. Main environments: OpenEdX, LPSS.me or Arke

Participants should familiarize themselves by viewing the following presentations:
·         The MOOC Ecosystem
COURSE STAFF



Stephen Downes
Stephen Downes is a specialist in online learning technology and new media. He is a leading voice in online and networked learning. He speaks from practical experience both as a college and university teacher and the author of learning management and content syndication software. Through a 25-year career in the field, Downes has developed and deployed a series of progressively more innovative technologies, beginning with multi-user domains (MUDs) in the 1990s, open online communities in the 2000s, and personal learning environments in the 2010s. Downes is perhaps best known for his daily newsletter, OLDaily, which is distributed by web, email, and RSS to thousands of subscribers around the world. As a teacher and designer, he is also known as the originator of the Massive Open Online Course (MOOC).

Monday, February 08, 2016

The Green Solution

Canada's PostMedia, concerned as always about meeting Canada's climate change targets, has published an article in the Toronto Sun arguing that Trudeau's emissions reduction targets are (and I quote) "impossible". In support of this conclusion the cite "math".

Here's Lorrie Goldstein:
Reducing our emissions by 127 Mt would mean the equivalent of shutting down all of Canada’s electricity sector (85 Mt) plus half of the building sector (43 Mt), in less than five years.

Achieving the mid-level reduction of a 146 Mt reduction would mean shutting down the equivalent of Canada’s agriculture sector (75 Mt) and most of our emission-intensive and trade-exposed industries (76 Mt), in less than five years.
 You get the idea.

Of course, with "math" you have to have numbers. Goldstein doesn't tell us where the numbers came from, but they're pretty easy to find. Here they are:

Our total emissions are 716 megatonnes (Mt). And yes, the electricity sector is responsible for 85 Mt, or 12% of Canada's total. And the rest of Goldstein's numbers can be found in the chart as well.
But math? Well, maybe the math of a ten-year old. People who actually do math can read for themselves how these numbers are created. Here's the formula:
Emissions = activity data × emission factor 
So, yes, if you reduce the activity to zero, you reduce the emissions to zero. But who, other than a toddler, would do it that way?



Let's take Canada's electricity sector, for example. We could shut the entire sector down to eliminate 76 Mt in five years. But that would be a ridiculous way to do it.

Let's look at how we generate electricity in Canada:




About a quarter of Canada's energy production requires fossil fuel. The majority is created from hydroelectric and nuclear, with wind accounting for about 4 percent. Why would we shut down all of that just to mitigate the damage caused by fossil fuels? Nobody would do that.

Here's some more math. Fossil fuels produce about 130 megawatts in Canada. The cost of installing wind power is roughly $2 million per megawatt. So for an investment nation-wide of $260 million, we could eliminate fossil fuel from Canada's electricity generation. That's two thirds of Trudeau's target right there!

So we would need 42 Mt savings on 630 Mt of emissions. If we made everything else 10% more efficient, we could exceed that target by a lot. Remember, emissions = activity data × emission factor. Is it reasonable to think that, instead of, say, eliminating the transportation sector, we could make it use 10% fewer fossil fuels?

We could look at buildings (86 Mt) for example.Instead of eliminating the entire sector, as Goldstein would have us do, we could search for a 10 percent reduction in heating costs, perhaps emulating Germany, which despite being one of the cloudiest nations on the planet, still manages to produce a surplus of home-generated solar power.

One of the major carbon-producers in the energy-intensive industries (76 Mt) is concrete production. Even passive techniques as on-demand mixing and concrete recycling could create significant energy savings.

Yes, there is a cost associated with this, and with the other ways to reduce the emissions factor.It costs money to electrify trains, to invest in public transit, and to convert from diesel to LPG or even fuel cells (transportation, 170 Mt). But with selective applications of public money to provide incentives, as well as increasing the cost of dirty technologies, all of this is manageable.

What we don't need are columns like this one published in PostMedia exhibiting what amounts to baby-logic. These are changes we need to make, and having a tantrum won't alter that fact.

Accomplishing our climate change goals will ultimately mean not only saving the planet, it will create more efficient industries. And if we can be among the first to accomplish this, we will be able to export these technologies. It is actually an era of opportunity, not crisis.





Friday, January 22, 2016

What I Learned Using Paypal

Doug Belshaw wrote an item this week called 3 things I’ve learned from 200 weeks of sending out an email newsletter which made me smile and think "newbie" to myself. That's not even four years!

But it's actually a major commitment  and I respect anyone who can carry out something on a regular basis for 200 weeks. I have a good sense of what it takes, not only in terms of effort, but also in terms of computing power and servers.

He draws three lessons:

- "You are the most important audience". By "you" he doesn't mean "you, the reader," he means "you, the author." If the newsletter didn't mean something to me personally, I would not keep it up. Belshaw has learned the same lesson.

- "People like commentary". I can attest to this. I've run surveys a couple times over the years, and I always ask whether people like the commentary or whether I should shut up and just deliver the news. The responses are unanimous. Readers want the opinion. Informed opinion.

- "A little bit of personality goes a long way." Like Doug, I don't just stick to a narrow diet of education technology tools and applications, or some similar specialization. My items reflect an interest in a range of disciplines, and the articles orbit around a set of core ideas, not some market managers conception of a vertical.

But also, like Doug, I have asked for donations. As I explained in my Donations page, my website costs me $200 a month to run, or $30,000 over the years. The traffic demands it; I have tried to run OLDaily and the rest of the website on a cheaper server, and simply crashed the server. It has created some financial stress, so I asked for help.

But I was also curious. Some people say that you simply have to ask, and you will receive, but I don't really fit the demographic. I'm not private-school pretty, I'm prickly and annoying, I'm not exactly a supporter of the corporate and entrepreneurship agenda, and I don't really have an interest in self-promotion (that doesn't mean I don't do it, it just means I feel guilty whenever I do).

But, you know, I always wonder, if I ever wanted a backup gig, could this be it? I look at some of the other people who started out as ed tech pundits and became self-employed as writers or consultants. There are some who make a living doing it, but I don't see people retiring early on the money. It looks like a tough life, with a lot of work in the trenches.

So how did I do?

From 30 donors I received about $1478. Most of the donations were the minimum $25 but I receive a large number of $75 contributions and a couple of people gave $250. Nobody selected the $1000 option (I thought maybe a company or two might want their name and link on the logo, but it didn't happen). It really is a tremendous response, and it comes close to covering my server costs for the year, and I'm grateful.

Here's what I did: when I redesigned the site to make it mobile-friendly over the holiday break, I added a donation page. I put a donate button on the home page, and ran one link in the January 4 issue of OLDaily. That was it for advertising. I thought anything more would be crass. But given that the link had (as of this writing) 67 views, maybe it wouldn't have been so crass.

I thought I would get a flurry of donations right away, and then nothing, but that's not what really happened. I've had a steady flow of donations spaced out over the last three weeks. Sure, I got 12 donations in the first two days, but it's averaged a steady one-a-day since then, in varying amounts.

I got my thank-you emails sent out today. At first I didn't think I could even send them - while PayPal faithfully reports the incoming donations, it downplays the sender's email. It has a co-branded service whereby it will print shipping lables and handle delivery for you - for a fee. Smart. But that was more than I wanted to pay just to send an email.

Sending out 30 individual emails took some time, and I was always afraid I would get the person's name wrong (happened once) or misrepresent the amount they donated (happened once). Cut-and-paste seems so impersonal, but retyping the same message would have been too much, but I was able to add some personal touches. Were the frequency of donations to increase, I would create a 'thank you' script.

I received a few comments on the list of options. Feeling very clever, I created the following range of choices: $25, $75, $250, $1000. And as we see on donation pages everywhere, I offered incremental rewards for each level (I resisted calling them 'gold', 'platinum', 'sustaining', etc.). Within a day I had to add two additional notes on the donations page: one telling people they could choose whatever amount they wanted, and another telling them they did not have to have their name listed on the page. A few people chose their own amounts, and two people took the extra effort to mail me a cheque instead of using PayPal.


Would I do it again? Definitely. I feel people appreciated the opportunity to say thanks. The money was significant. And server costs aren't going away. And hey, maybe a few companies will start using that $1000 option. :)



Saturday, January 16, 2016

Organizing

Quoted at length from Self-organization of complex, intelligent systems: an action ontology for transdisciplinary integration, Francis Heylighen, Integral Review:

A mobilization system would combat this confused and unproductive way of acting by
redirecting effort in the most efficient way at the most important issues. This requires the
following steps:

  • helping people to reach consensus about the specific goals that they consider most important. This can be done in part by seeking inspiration about fundamental values in the evolutionary worldview [e.g. Heylighen & Bernheim, 2000], in part by creating effective discussion systems that help a group to come to a well-reasoned consensus. Examples of such systems are being developed on the web [Klein, 2007; Malone & Klein, 2007].
  • motivating and stimulating people to work towards the goals that have thus been agreed upon. Here, a very useful paradigm is the concept of “flow” [Csikszentmihalyi, 1990], which specifies the conditions under which people work in the most focused and motivated manner. These conditions are:
    • clear goals: there should be minimal ambiguity about what to do next;
    • immediate feedback: any action should be followed by an easily interpretable result, so that you either get a confirmation that you are on the right track, or a warning that you need to correct your course;
    • challenges in balance with skills: tasks should be neither too difficult nor too easy for the people entrusted to perform them, in order to avoid either stress or boredom.
    • Additionally, there exists a wide range of techniques from psychology, behavioral economics and memetics that help us to formulate goals and tasks in a way that is maximally motivating, persuasive and easy to follow [Heath & Heath, 2007; Thaler & Sunstein, 2009; Heylighen, 2009]
  • coordinating and aggregating the individual contributions so as to ensure maximum collective results. This can be built on the mechanisms of stigmergy and selforganization mentioned before [Heylighen, 2007a; Parunak, 2006].
By minimizing uncertainty, confusion, friction and procrastination, work that is mobilized by
such a system would not only become much more productive and effective, it would also
make the participants more satisfied with what they are doing.

Wednesday, January 13, 2016

The Banality of Death

Late last fall my cat Bart died, then Jay Cross died, and finally 130 people in Paris died, all within a few weeks of each other.

Bart's death was not felt widely beyond my own immediate family, Jay Cross's death was more widely felt, and of course the impact of the Paris attacks was worldwide.

They all felt about the same to me.

It seems shameful to admit this. The sheer number of people killed in Paris should give the event more significance, shouldn't it? And surely the loss of Jay Cross is of more significance than that of a cat.

But it set off in me a chain of thought that I cannot escape, and which runs around and around in my head even to this day.

After the Paris attacks, I felt like I was the only remaining opponent to war, the only person who did not at once rise to the challenge and call for the degradation and destruction of those responsible.

I felt that way after 9-11 as well. I felt the United States would feel it had to attack someone (in this case Afghanistan, and then for good measure, an innocent bystander in Iraq) but I didn't have any sense of what good it would produce. And as the intervening fifteen years have shown, no good at all.

We heard a lot in those years about the fight to bring democracy to Afghanistan, to improve the lives of women, to increase self-sufficiency and end poverty. All of those are noble goals, but none of them were really the reason for the war in the first place. They were fictions we told ourselves as the occupation wore on and on.

I have a similar feeling about the bombing campaigns in Syria. The flow of refugees has made it plain that all anyone has accomplished was to make life miserable for the general population.

How many Syrian dead does it take for their deaths to become as meaningful as those in France, or here in Casselman? What is the calculus of death?

It seems to me that the fighters for ISIS have, like so many idealistic youth before them, been the victims of the great con, that theirs could be and would be a 'meaningful' death. In this regard, it doesn't matter what they are fighting for - it could be for religious purity, it could be for the advancement of society, it could be 'for peace'.

What I realized on that fall day is this: there are no meaningful deaths.

Bart's passing was as peaceful and timely as could be hoped. He slipped away without a murmur the morning after his failing kidneys took away his sight. His last night was peaceful; he slept beside me, twitching and dreaming of play-games, listening to classical music. He always loved music.

But it was still wrong, it still hurt like a deep knife, and it was still pointless.

Why is there death at all? It is part of the package deal that makes us human (and him feline). It's part of the same mechanism that underlies thought and sentiment, perception and cognition.

It's how humans (and cats) evolve. It's how they have come to be at all. Death is what enables the dynamic interaction and reproduction of the species to create new versions of themselves. It is the ultimate feedback mechanism informing a mechanism driven by the interplay between small things.

It was a great mechanism for getting us to the point where we are conscious, self-aware, adaptable, and even caring beings. But it's no longer needed, and there's no 'off switch', and it's clear to us now that the same objective can be achieved without doing away with the participants.

Assuming we even wanted more evolution, we can imagine means much more subtle than the cudgel that is death. We can tweak the DNA with gene splicing, we can induce change with tailored phage, we can decide. And similarly, socially, we can create a new government, or a new society, without the need to exterminate any proportion of its members.

A nation is not better because it arose out of the ashes of revolution. A cultural identity is not forged on the battlefield. These are not the engines of birth, they are the engines of destruction, elimination, of utterly needless death.

We do not need to destroy in order to be able to see.

All I ever feel when I think of death is a feeling of loss. It was never "someone's time". It is never made up for by the fact that he led "a beautiful life". It matters naught that he died for "something greater than himself." It's means nothing that "he died with dignity." That's all the big con.

In truth, it is death itself that is the enemy. It is death itself that is the blackness that erases the light. It is death itself that is ultimately the most pointless, banal, distressing part of a person's existence.

Nothing can convince me that some social, political, economic or religious ideal is "worth" a life. Nothing is left behind by death, even the death of a vanquished foe, but loss and emptiness. Where once there was life, now there is only silence.

Today we talk about the morality of accepting refugees, as though there were actually a moral question regarding the desirability of allowing people to be bombed, starved, beaten or drowned into submission.

The existence of borders blocking the flight of people to safety is an affront. The waste of human lives in the name of a nation, a religion, or an idea is offensive to the sight and mind.

No matter how pointless or meaningful we are told that it is, each death is to someone the ultimate tragedy. All deaths are the same. Once we come to realize this, together, we can begin thinking about how we can live together, work together, and begin to cherish this most beautiful thing in the world: life.

Friday, January 08, 2016

Ought and Is

Experts are typically expert in two types of things:
  • what is the case
  • what ought to be the case

And for that matter, we all have attitudes and beliefs regarding both types of statement. For example:

  • it's 20 degrees in here
  • it ought to be warmer
That's fair enough.

Science and research are sometimes depicted as consisting necessarily only of the first sort of statement: that is, researchers should confine themselves to discussing what is, and not what ought to be the case.

I don't agree with this. I think that unless research is guided by some sense of ought there is no motive nor even mechanism for determining what is. For example, if it didn't matter what the temperature is, why would anyone bother measuring it, and indeed, what sort of scale would we even use?

Indeed, it's pretty hard to make sense of any human endeavour without invoking both an is and an ought. Any action plan, indeed, contains these two elements: the action plan is a description of the route from the is to the ought. And all research is based on this formulation.

Having said all of this, there are two hard and fast rules that apply regarding inferences involving is and ought:

1. You cannot derive an ought from an is

Suppose it's 20 degrees in here. Does it follow that it should be warmer or colder? No. It depends on your point of view. If you're a duck, you're probably OK with 20 degrees. But if you're me, you want it warmer. And if you're a rock, it doesn't matter at all.

It's sometimes hard to see this. "Look at that starving child," someone will say. Well, yes, the child is starving. But that by itself doesn't allow us to infer that the child should be fed. The inference follows only if we have an expression of need or value, for example, "allowing children to starve is wrong."

This is sometimes called the 'naturalistic fallacy'. People say, for example, "It's human nature to do such-and-such, so such-and-such is OK." Or, conversely, they say something is wrong because "it's not natural."


2. You cannot derive an is from an ought


"If wishes were horses," goes the old saying, "then beggars could ride." There's wisdom in that. Certainly we may believe things ought to be one way or another. But this belief doesn't mean that anything actually is one way or another. This would be nothing more than wishful thinking.

These lead to a third rule:

3. An ought is derived only from an ought, and an is is derived only from an is.


It follows from these two rules that the veracity of is and ought statements is determined very differently for each.

There are two very different forms of logic. The first - the logic of wants and desires - is called deontic logic. Other forms of logic (propositional logic, for example) describe the other sort of inference.

So why is all this important?

Well, as I said, or pretty much any enquiry, including scientific research, you need both an is and an ought. So, on the one hand, you need data, to tell you what is the case, and on the other hand, you need some sort of problem or domain of enquiry, which tells you why you need the data and what you hope to do with it.

This means that the citations for any research should include some from column A and some from column B. Good research requires a clear context, problem, or domain of application, and it requires facts, data and evidence. And - even more importantly - the references supporting each of these need to be of the right type.

4. Define context, problem or domain of application from expressions of need or obligation, including social, political and economic perspectives, and not from data.

This should be obvious, but isn't. Even your unit of measurement is going to incorporate these perspectives, and will in some sense define the desired state. The units of measurement are not inherent in the facts of the matter.

We often hear sentences like "the data dictates that...". No. The data does not dictate anything. The only thing a set of data can produce for you is more data.

For example, the data may say "5 percent of the people finish the course." Nothing about the quality of course design follows from this. You only get this sort of statement if you've already agreed that "not finishing reflects a design flaw" or some similar ought statement (which in turn needs to be substantiated).

I see in the academic community a lot of expressions of value or obligation criticized on the basis that it's not derived from data. The idea these critics express is that all reference in an academic paper ought to be peer reviewed, and the statements of value and obligation therefore grounded in some sort of fact. But that's an error. There is not some sort of fact-based mechanism for determining value or obligation. 

5. Define data in terms of empirical measurement, and not in terms of expression of need or obligation.

This is probably the most consistent flaw of research provided by the education policy 'think tanks'. The 'data' they provide owes as much to the center's political orientation as it does to 'facts'.

Take a statement like this: "The professional expectations for today’s teachers are undoubtedly high." This looks like data; it looks like a statement of fact (as indicated by the word 'undoubtedly'). But it's a statement of what ought to be, in two senses: first, it describes 'expectations', and second, it uses a relative value-laded term of measurement, specifically, 'high'.

Of course, it's OK to make statements like that. But they need to understood as expressions of what ought to be the case, and subject to assessment in terms of value and obligation, rather than represented as data and misused as the starting point for an action plan.

There's a lot more that could be said on the subject of ought and is, but I'll leave it here for now, happy if I've managed to alert the reader to be sensitive to these two types of statement.

More reading:

Is ought - University of Texas
The Is-Ought Problem - Wikipedia
The Is-Ought Gap - YouTube
Hume on Is and Ought - Philosophy Now
Is/Ought Fallacy - Fallacies Files






Thursday, November 05, 2015

What Else can Work at Scale? and Techniques from Social Media

My contribution to the Networked Learning Conference 'Hot Seat' discussion. You can read the whole discussion here.

# # #

Anything that can be automated works at scale. Anything that cannot be automated must be distributed, and if so, works at scale. Only centralized non-automated things do not work at scale.

# # #

This is a good question:

"Humans scale, and have scaled before any automation existed, so what made us scale? Localized transmission of knowledge (oral tradition), the automated cell/gene replication in combination with adaptations? "

And I think that the answer is inherent in the nature of life: that we are autonomous, and interactive, so we create a distributed network of diverse activities, adapting to local conditions, and scaling naturally.

Life seeks conditions of success. Humans, crickets, birds, plants - we migrate to the places where we flourish and avoid the places we don't, each making our decisions one by one.

Too dense a network and society fails. Too sparse a network and society fails. Autonomy is productive; eliminate it and society fails. But where autonomy is extended to point where it disrupts the network, society fails. (These aren't truisms; they are empirical observations, and subject to verification.)

# # #

Also, comments from the thread titled 'Educational Designers and Techniques from Social Media'.

I have argued that the design for MOOCs should take more from games than from social media (though there are some pretty strong overlaps), including in a talk just last week3. My point was that instead of trying to design learning, which is focused on content, we should create environments in which people can practice.

Social media is a bit like an environment. It is a space (mostly) not bounded by structured presentation of material or decision trees (Facebook's stream is an oft-criticized exception). People are able to try out new ideas and new personals. The problem with social media is that the interaction is (mostly) limited to conversation. I would much rather see people interact by solving problems, figuring out puzzles, playing games, and creating things.

# # #

Again, I have not clearly stated my point.

I use games as a metaphor to talk about MOOCs:

There are two types of games:
- those that depend on programmed design and memorization, and
- that create an environment.where players and objects interact

In the same way, there are two types of MOOC:
- those that depend on programmed design and memorization - xMOOC
- that create an environment.where participants and objects interact - cMOOC

The first type of game was a failure. They could be defeated by mere memorization and were not interesting. They disappeared from the market.

The second type of game was a success, and should be used as a model for MOOCs (and indeed, were a part of the model George and I used when we developed cMOOCs).

So this second type of games is the type of games I am talking about.

When comparing this second type of games and social networks, I agree with you that there are many elements in common. They are both environments, they are based on the interaction between participants, and they can be used to solve problems, negotiate and communicate.

But there are also some important differences:
  • games are inherently about solving problems or responding to challenges, while social networks can be much more passive.
  • games typically involve a wide range of different types of objects (even objects in the physical world) while social networks involve conversational elements only.
This not to say that we must choose between either games or social networks. Both inform the theory of environmentally-based learning, where participants interact in a common space with objects and with each other.

But it is to say that a model based on social networks alone will be insufficient to inform the design of successful MOOCs. The elements of a successful networking environment need to be taken into account.

Because, yes, the connections are of the utmost importance. We cannot learn from each other without connections.

But the manner, organization and structure of those connections must be designed with the intent of creating the most interesting and accessible environment. People will learn from each other, not from the MOOC.

# # #

I don't agree with this: "It's important what the discussion is about, what the goal of the discussion is..." I think there is too much desire on the part of educators to shape the learning of individuals. We should see our function as more supportive than directive.

# # #

You say: "The content - or the concrete problem - should be the center in dialogue for learning." And yet: "not that this should be determined by the instructor/teacher/facilitator."

Two things:
  • First, I don't think both things can be true. If you are going to say something should be the case in learning, then you cannot say that it should not be determined by the instructor/teacher/facilitator.
  • Second, there are many cases wher this need not be the case. Where someone is learning merely for pleasure, for example (which explains how I acquired a knowledge of the Roman Empire). Or where different people are working on different problems, not a common problem.