- Doug / @dajbelshaw / http://piratepad.net/QRjhF77J8M
- Dan / @moodledan / http://piratepad.net/bLPtUG9yoG
- Roz/ @rozhussin / http://piratepad.net/nZrUFH6UbW
I suddenly realized this morning that many of my early “blog posts”, from way back when I first started engaging in online Connectivist Learning, are potentially “wasted resources” if I do not now go back, revisit them, harvest them, and curate them into some semblance of documentation. The concept of Metacognitive Learning (Flavell, 1976) is well established, but the Learning Protocols, -ie- the how-to-do-it-STePs for Metacognitive Learning, are NOT commonly known. In other words, there aren’t many DIY textbooks out there entitled – “How to embark in self Metacognitive Learning”.
So, I have decided to start a personal effort to revisit the first Massive Open Online Course (MOOC) that I took last year, where I first embarked in Connectivist Learning. I want to “harvest” the MOOC platform by copy-pasting some of the key aha-moment blogs that I had posted in that platform, and re-post them here, in my public blog. I will then document my Metacognitive reflections of what I now (today) have learned since those original blogs. These documentations will form a data repository for qualitative research analysis, and will (hopefully) spark potential article publications by myself and/or other collaborators/readers. I welcome anyone who reads this blog to utilize the data that I am posting here, for the purposes of learning and publishing about learning.
FYI, my virgin MOOC was a course by Stanford University titled “Designing a New Learning Environment” (DNLE). The platform on which that MOOC was hosted, is NovoED, previously known as VentureLab.
The following is the first blog that I am “harvesting” from DNLE.
Copy-pasted from my DNLE Personal Journal from 8 months ago
https://novoed.com/education/blog_posts/user/59471
https://novoed.com/education/blog_posts/6897?data_type=post
Potential research stemming from this MOOC (DNLE)
This post was originally posted as a response to a discussion in another thread. I am copy-pasting it here, as it highlights the potential for (additional) research to be carried out, based on this DNLE MOOC “experiment”.
The topic of online terminology, connotations, culture, context, and syntax…. this is an area of study of personal interest to me. I had been researching the impact of these variables on human task performance for awhile now. In my studies, I also looked at the differences between what impacts a native monolingual English speaker, versus what impacts a native bilingual speaker (someone who truly was raised with two languages from birth), versus what impacts a person who speaks English as a second language.
Context has a different impact when it is listed as part of a task instruction, or issued by the instructor, or by persons of official authority in a context, or when posted by a peer.
The use of vocabulary, its impact on readers, and its application in purposeful subliminal messaging, has been studied and published extensively in the field of advertising. But it has not yet been researched or published much in the field of instructional design. Also, what little that has been studied, has always been in the context of the western world. Now, with global online MOOCS, I personally think this area of study needs to be addressed in the context of various international cultures.
Why, just look at THIS MOOC alone… if you sift through the many journals, forums and projects (and I don’t mean just the popular active threads… take a look at the many projects by bilingual and non-English speaking students), you can see an array of language sentence structures, and the evident impact (positive or negative) that certain posts convey.
Just through accidental discovery, I have encountered at least a dozen or so posts that had been “misread” or “differently-interpreted” due to differences in language syntax. Imagine if someone actually purposefully looked at that phenomenon as a bonafide research question…
I think someone should use this MOOC to do a study on that.
BACKGROUND NOTE: This blog is (1) a continuation of an earlier blog I wrote on Ripples, (2) a follow up from being triggered by an article I read on a G+ post by Mike Allton, and (3) an aha-moment I had as I revisited two G+ posts — (3a) the first post that I had originally posted a few weeks ago, and (3b) a second post that David Amerland had posted as a follow up.
The article by Mike Allton talked about the benefits we gain from the Google’s Ripples tool from the perspective of social networking in the business world. I can see the benefit for business, but I am in the business of education, so while I’m thrilled at the existence of the Ripples tool, I am frustrated that it’s design is not (yet) developed to benefit the objective of learning…
Ripples measures re-shares. From the lens of learning this type of quantitative data is not very useful, even though it does qualitatively present a “sociogram“, -ie. a visual representation of the people-networking, emanating from a particular G+ post. The problem is that the existing Ripples-sociogram (merely) represents a very shallow level of “thinking”. Ripples (in its present form), is a value system based on statistical dichotomy — re-share or not re-share.
In order to be useful for learning, what Ripples should do instead, is to measure comments. By tracking and quantifying the reactions and follow-up contributions from people in relation to an original post, then, the sociogram that is generated would represent a deeper level of cognitive response to the original post.
Let’s look at a few hypothetical examples…
Let’s say original post #X has 3 comments, original post #Y has 30 comments, and original post #Z has 300 comments. This would imply that original post #Y triggered a discussion that is more successful in engaging dialog than original post #X, and that original post #Z is a catalyst for hyper-engagement.
If both original posts #C and #D have 20 comments each, but if the comments from original post #C are contributed by 20 people, while comments from original post #D are contributed by only 2 people, this would suggest that the comments to original post #C are reaction-comments (as the discussion has only reached a single-layer of responses), while the comments to original post #D are probably reflection-comments (as the discussion contains multi-iterations of dialog). In other words, the depth of dialog and/or level of engagement in the latter is deeper than the former.
If both original posts #E and #F have 50 comments each, but if the comments from original post #E occur within a span of 1 hour, while comments from original post #F are spread out over a period of 5 months, this would suggest that original post #F triggered a longer duration discussion, -ie. a more sustainable life-span. This would suggest that the author of original post #F and/or the responders to original post #F, were successful dialog facilitators who managed to sustain ongoing engagement.
Now, let’s look at two real examples:
by Roz Hussin (me) originally shared publicly – Jul 14, 2013
1 re-share, 12 +’s, 84 comments, 33 pages, 9614 words
by David Amerland originally shared publicly – Jul 14, 2013
10 re-share, 49 +’s, 72 comments, 22 pages, 5056 words
Measurement / Engagement Criteria |
Post #A:by Roz Hussin |
Observation / Analysis |
Hypothesis / Research Questions |
|
G+ posts |
1,151 |
19,000 |
Author of Post #B is ≈ 20 times more influential online than Author of Post #A |
Does the quantum of re-shares (valuing a post to be important / useful for others) and endorsements (valuing a post to be interesting / containing useful content) depend on the author’s online influence status? |
re-share |
1 |
10 |
Post #B had 10 times more re-shares than Post #A |
|
+’s |
12 |
49 |
Post #B had 4 times more re-shares than Post #A |
|
comments |
84 |
72 |
Number of comments in both posts are comparable |
What criteria influence the quantum of discussion engagement? Duration? Intensity? Sustainability? Depth? Detail of discussion? Number of reference URL links quoted in the discussion? Number of people “pulled” into the discussion? |
pages |
33 |
22 |
Total length / duration of discussion engagement of Post #A is 30% longer than Post #B |
|
words |
9614 |
5056 |
Total depth / volume of content of Post #A is double that of Post #B |
If the author’s “influence” is a factor in determining discussion engagement, then WHY does Post#B only have HALF of the depth/volume of discussion than Post#A? (despite the fact that Author of Post#B is 20 times more influential that Author of Post#A)
If the number of re-shares and number of +’s are statistical numbers that are indicative of the post’s “value”, then WHY does Post#B have a THIRD less content than Post#A? (despite the fact that Author of Post#B is 10 times more re-shares and 4 times more endorsements than that Author of Post#A)
Judging from the simple analysis above, it looks like there are many more unanswered questions than clarifications regarding the issue of discussion engagement and the criteria that determines the levels of such engagement.
This reminds me of my elementary and middle school days… where the “popular kids” are popular because of publicity reasons, and not because of their actual contributions in school… Isn’t this sad? That the adult online world is no different than our childhood popularity nightmares? (David Amerland… No offense OK? I love your blog posts, and I sincerely appreciate the accolades you gave me in your post… but in the name of research, I hope you forgive me for using your post as an example).
IF online discussion is to be seen as the key vehicle for engaging online learners in online courses, wouldn’t the protocols of engagement in online discussions be an important literacy? How would online learners gain these competencies? Where do instructors and learners learn about these issues? Who is researching and discovering these findings? Who is teaching people how to maximize this knowledge? Anyone?
As technology continues to develop, I hope that the keepers de jure of the online domain -ie. coders, programmers, policy makers, business investors – pay a little more attention to the needs of online learners, and not just of online consumers and suppliers. After all, isn’t online learning a business too?