Self- Assessment and Self-Remediation – 1st Post

In this first week of this #rhizo14 experience, I’ve had a few modest goals. I thought it was interesting how many people defined their role in the MOOC as “cheating” because they were lurking and would be picking and choosing how they participate. I think with a connectivist online experience, that’s really the only way to operate, unless one happens to have the luxury of a lot of spare time. I do not. I entered the experience knowing that I would have significant time constraints. Nonetheless, one of my goals was to blog regularly, aiming for a couple of times a week.

That commitment has made connecting with other participants in the MOOC much richer. I like the concision of twitter, but it’s hard to connect over deep ideas in that space. In the first week, I’ve appreciated the comments on my blog, the people who’ve given a quick nod by favoriting my posts, and the connections on twitter building on the ideas.

Maha Bali(@Bali_maha), Simon Ensor (@sensor63), Jaap Bosman (@jaapsoft), Terry Elliott (@telliowkuwp), Aaron Johannes (@imagineacircle), Jenny Mackness (@jennymackness) and Kevin Hodgson (@dogtrax) are some of the people I connected with last week, and I hope to continue the conversations throughout this learning experience. In my past MOOC experiences, I have not felt particularly connected to people, even with a lot of dialogue. I have considered the facebook and google plus group.

One of my ongoing goals is to continue to refine my social media and productivity workflows. I use the following tools to manage information flows:

  • Hootsuite for twitter. I set up a view of #rhizo14 to easily scan on my commute.
  • I favorite tweets that I want to come back to. Favorited tweets automatically create a draft wordpress post via IFTTT rule
  • WordPress app on phone installed to quickly approve comments

What other strategies for pulling together and managing all the information in this MOOC are others using?

And a question I’d like to explore in the coming week:

  • What role should the affective and conative domains have in teaching and assessment? OR
  • Can empathy and curiosity be taught?
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Degree Hack

Earlier in the week, I re-read the initial post by ralfe poisson and his verbiage around gaining “advantage by using unfair methods.”  ralfe mentioned hacks and here I will share an example of a Degree Hack (borrowing slashdot’s label) . These articles highlight the case of Richard Linder, who constructed an associate’s degree for under 3000 through some very creative strategies.

I want to  juxtapose the characteristics and questions around learning in the classroom and the question of “what is cheating” with Linder’s degree hack. The comments on the Chronicle of Higher Ed article assert that he couldn’t possibly have gotten a quality education through this method. Linder’s circumventing of widely accepted, mainstream approaches to credit feels like he’s getting about with something. But how do we know that his learning experience is not of adequate quality? While there is a lot of discussion of outcomes in education, but at the end of the day, most credentials are granted based on evidence of “time on task”– approximately 135 hours of effort = 3 credits. Why are we so sure that people sitting in a classroom sharing an experience together is a quality learning experience? Why are we so sure that if someone circumvents this that they’re “cheating” and it couldn’t have been a quality experience?

I don’t think his approach is for everyone, but I do think that if I were looking for someone with some creative solutions to problem-solving, I’d be interested in someone willing to take risks and think outside the box like this.

 

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Questions about Cheating as Learning

This theme of cheating as learning or cheating in learning is really rich for Week 1.  I’ll start with some quick observations and assumptions around cheating in the learning process. These observations assume that learning in whatever manner, should be applicable in the “real world” (whatever that is, if your learning is already taking place in the real world).

1) If I can cheat easily, ie, look up the answer to a question to find an answer accepted as “fact”– well, where is it, exactly, that I will be in the real world that I won’t be able to use the same method to find this information. Why are are you asking me this question anyway?

2) If a class is organized to encourage group work, or study groups and we share methods and answers on practice tests or exercises, is that cheating? Or is that group work? Where is the line?

3) What kind of cheating will have real consequences in one’s professional world? Plagiarism comes to mind. But there are boundaries and nuance around “borrowing” work as long as it’s properly synthesized and cited–ie, there are requisite ethics around remixing, but certainly being aware of and referencing the work of others is a requirement of being part of a world of knowledge.

Dave’s challenge this week was: Use cheating as a weapon. How can you use the idea of cheating as a tool to take apart the structures that you work in? What does it say about learning? About power? About how you see teaching?

What if we replace the word “cheating” with “challenging the status quo?” Does that fit? It doesn’t feel like the same question. Cheating is just a little too pejorative a term for me to get comfortable with. The idea of cheating implies that there are right and wrong ways to demonstrate knowledge. At the same time, those might translate into professional ethics in particular circumstances. The problem with the term is that someone, somewhere is setting the rules about what cheating entails. Some of the source of acceptable practices might be from those in charge, some from traditional practice, some from professional best practice and standards. How can we be certain, when we are part of those defining what it means to “cheat,” that we focus on creating learning situations that by their very nature are asking the learner to engage in experiences where it is challenging to cheat.

An example might be having the learner apply key concepts to their own experience. There is a way that someone could cheat even with this… One could really just not try. I think there is a need to parse out the idea of cheating to separate clever solutions to problems that others perceive as a shortcut versus someone taking a short cut because they are afraid to try or don’t want to try. What do others think?

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Rhizomatic Learning – Motivation for Participating

Rhizomatic Learning on P2PU, initiated by Dave Cormier is an opportunity to explore a topic that is paradoxically near and dear to my heart, and at the same time feels uncomfortable against the backdrop of formal education. I came to the field of education first through applied linguistics, finding myself drawn to social linguistics and then moving towards instructional design. I’m not sure these areas could be philosophically more different, but the juxtaposition through my career has been essential. I think the most important lesson in life, no matter what your profession is that context matters and that adapting one’s approach based on the situation at hand is critical for expertise. I’m being very surface level right now, because I know that one could conceptualize learning in some other organic metaphor besides a rhizome, but I think it works, particularly for trying to capture the nature of social learning, of the randomness but interconnectedness of experience, and the shape of nonformal learning. As Deleuze and Guattari note: “A rhizome has no beginning or end; it is always in the middle, between things, interbeing, intermezzo.” A learner is always in progress, always in the learning process– there is no end.

That’s where the tension comes in. In formal learning, if one were to tell a student that there is no end, no mark of accomplishment, no grade, no graduation, no degree, this would not be particularly motivating (to most people). When planning out a learning experience, for learners who are learning for the sake and enjoyment of the learning process, of discovering something new, and of being inspired by these new findings, it doesn’t really matter what the desired learning outcomes are– the learner will define those themselves. But even the same individual might find this to be a fine approach for something that they are really motivated to learn about, but for other subject areas might want a more structured approach.

At any rate, these are my assumptions at the outset of this experience. I look forward to delving a bit more into the rhizome and seeing my ideas evolve. Thanks to Dave Cormier for assembling this experience!

Next post will be about Week 1’s topic– Cheating as learning.

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Commenting, annotating, and collaboration (in advance of #FutureEd)

The collaboratively-taught MOOC on Shaping the Future of Higher Education begins on Jan 27th. I’m excited about the content, and though the last MOOC I participated in — well, sometimes I didn’t have the time and attention that I wanted to devote– I committed to being ok with what I could get out of it. In advance of the MOOC, I have some observations about some of the design and communication decisions with some thoughts about how this might be applicable for any instructor.

As I was taking a look at some of the MOOC materials, some observations about the organization and design of the materials popped out at me, particularly as juxtaposed with technological capabilities in a typical LMS.

Prioritizing Learner Voice: The syllabus has been developed and posted for several months, with a version for public comment, which is a nice way to hear feedback in advance of the course. As I see that, I wonder why LMS’s like Blackboard couldn’t be designed with an option to create content that interacts in the same manner as Google Docs. With the recent functionality built into the grade center for in-text commenting, one would think it wouldn’t be too much of a stretch. And while that wouldn’t always be ideal, having any page have the ability to have comments might even be an interesting approach to provide options for making learner voice more a part of the course.

Facilitating Interaction: Just as it would be neat to be able to annotate directly on the text– whether it is instructor or student created, it would be handy to be able to annotate any text and to be able to do so in real time. Yes, of course this is possible to do using Google Docs, but why is this still after half a decade the only option available? The #FutureEd Mooc will include an assignment on Rap Genius (which should be interesting to try out!) Davidson described using Rap Genius for having students do peer review earlier this fall. I think the biggest challenge with the use of the site is that there are offensive lyrics within the site, which makes it a harder sell for a lot of educational contexts.

Yes, I know that there are a ton of free tools out there to get at all this functionality– but if we’re thinking about the future of education, I can’t help but wonder when the technology tools for learning, ie, the LMS will place the learner at the center of the action, to look like the virtual version of this:

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(Image Source Tappe Libraries)

instead of this:

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(Image Source Sholeh)

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Blended Learning and Waves of Response in Post-Earthquake Christchurch

Of the many angles to take around why blended and online learning can be a beneficial asset and component of the learning process, one that I often have in the back of my mind during a inclement weather is that it can help mitigate against circumstances that might significantly impede the educational process.  Of course, doing away with the concept of snow days is not appealing to a lot of students out there, but there can be other weather events that render it challenging to travel to an educational experience, from hurricane-related, to earthquake, to general public safety.

Now, as I learned in Baltimore in the winter of 2010, even online can be a serious challenge when there are infrastructure threats.  Having tried to solve the challenge of a class canceled due to a snow storm with a synchronous online session, this turned out to be more complicated than it was worth when a number of students had power and internet failures. Even converting to asynchronous activities was challenging for some students as the region was pummeled with 4 feet of snow in two separate storms just a few days apart. Even with those hassles and necessary flexibility for some students  we were able to stay on track in the course. However, what about those events that prove to be more impactful than a couple of class sessions?

In looking at applications of blended learning at a large scale and strategy level, academic writing from post-earthquake New Zealand yields some insight into some methods used to keep learners on track during that chaotic time.

Mackey et al describe the  response of the University of Canterbury’s School of Education to the post-earthquake scenario and identifies a “waves of response” model to the event itself and the phases needed to respond to the unfolding situation.

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From Mackey et al

It also demonstrates the difference between using blended/online learning as a short-term solution for a very minor disruption, to the overall shift needed to connect, regroup, and build capacity for the larger, systemic change that must occur in reaction to the large scale event. This model is helpful for conceptualizing the long-term nature of the investment of time and resources into being able to successfully implement blended or elearning in response, and the need for resources for capacity-building in waves 2 and 3, so everyone can get up to speed on what is needed.

Accordingly, in comes research such as Alice Cruikshank’s thesis on elearning in the public library environment was directly related to the aftermath of the earthquakes, where even when some services had been restored, physical buildings remained closed to the public for years. This would tie into those latter waves of response, where there is a recognition of the need for change and programs put into place from this need, particularly as it becomes clearer that while there are resources (people) available, rebuilding physical spaces will take a long time.

Another interesting approach is the idea of responsive curriculum and service-learning as an integral part of the educational experience as proposed by O’Steen and Perry, also at the University of Canterbury. They quote Charles Fritz who describes that “essential effect of
shock is to arrest habitual repetitive patterns of behavior and to cause a redefinition and restructuring of the situation in accordance with present realities” (p. 55).” This resonates with that wave of response model above as an impetus to drive change in behavior. O’Steen and Perry then write,  “With regard to curriculum, this “arrest [of] habitual patterns of behavior” could be metaphorically viewed as a call to adjust the curriculum in order to lean toward the disaster, not shy away from it. This jolt can lead to new ideas, different perspectives and a fundamental
restructure of action and reaction according to immediate concerns.” (p.3). The paper also references online discussions as one of the tools used in the service-learning course that was developed– and why not?
Online learning should be equipped to accompany transformative experience nicely.

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Efficacy and the Big Picture

Last night, as I was falling asleep, I thought about a presentation from Ted Frick that I saw in about 2006 about what basically amounts to educational AI.  All at once, I was overwhelmed with both the magnitude of what his work has been attempting and doubt that it’s even possible to begin to break down all the variables that will support a predictive system of learning.  And yet, my thought last night was that we’re going to get there, more or less, as a society in my lifetime. Metrics and analytics will be used to create predictive and adaptive learning in a meaningful way. It’s going to be a long haul, and the education industry will be resistant (sometimes for good reason), and there will need to be checks and balances and a human touch built into the system for both the analytics that measure efficacy and the metrics that are studies to make predictions both about what will help people learn and about their overall potential.

This thought process started with Carrie Saarinen’s really elegant comparison of current teaching and learning vis-a-vis learning outcomes to a spirograph. There’s a lot in the post to unpack, particularly around the current implementation of feedback and assessment in courses where a grade might be delivered on a student’s first attempt at demonstrating mastery. As she notes:

One of the problems I see with course level learning outcomes is an expectation that students will achieve mastery on the first attempt and that there are often minimal attempts at an outcome. Evaluating hundreds of courses each year, I look at thousands of different course activities, assignments, projects and quizzes it is striking to see how frequently activities map back to multiple outcomes and few outcomes map out to multiple activities. In other words, I see courses with dozens of outcomes but only a handful of linked activities.

This is such a key issue– that students would be expected to master an outcome and would receive a summative grade based on one chance at demonstrating their newly acquired knowledge. And as she rightly points out, changing this expectation would not only have to happen at the program level, there would have to be impact on how programs are designed and for how instructors see their role vis-a-vis students for this to change.

What is the connection between educational AI and individual course outcomes? Carrie’s piece was inspired by Michael Feldstein’s analysis of Pearson’s new focus on efficacy in learning. And the example of what Pearson is trying to do– well, it feels impressive. Can a rubric change a business? It can, but it has be immersed into the culture and the people who need to use the rubric/checklist need to feel like it’s solving a problem or that the mission is so critical that they’ll match their actions against the rubric routinely. However, the difference between efficacy in medicine and efficacy in education is that in medicine, the end result is pretty transparent. There are well defined metrics for assessing whether a body is healthy– there are standards of temperature, blood pressure, BMI, very minute breakdowns of what one’s blood should be comprised of, T cell count, thyroid level ranges, etc etc etc. What are our measures of success in education that will be widely adopted as universal standards? What’s the educational equivalent of normal blood pressure?

Education will get there, but it will be and my best guess is that a focus on efficacy and AI will be most helpful in content areas that will map to areas where there are clear right/wrong answers.

 

 

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