Surfing the Wave: Keeping Abreast of the Digital Ed Field in ISTE 5

Riding the Wave

This week’s question for EDTC 6103 was pretty straightforward. Given ISTE standard 5, I wanted to focus in on indicator C, which called for teachers to “evaluate and reflect on current research and professional practice on a regular basis to make effective use of existing and emerging digital tools and resources in support of student learning” (ISTE).  My question was about how to best do this in an ever-changing field.  Are  there any best-practices for teachers who wish to stay abreast of developments in such a rapidly evolving field?  It may be helpful to remind ourselves that the “digital” part of digital education is fairly recent.

In 1965 Gordon Moore predicted that the sheer processing power of computers would double every two years, and while there is some debate about the reality of the prediction today, the fact remains that in the last 50 years, computers have increased tremendously in power and decreased drastically in size and in cost.  In 1991, the year I got my first computer, an Apple laptop (Macintosh Powerbook) cost around $2300, or just over $4000 in today’s money, had a 16 MHz processor, and weighed about 6 pounds (Comen, et. al. 2016).  Today, I see I can get a 4.4 pound Apple MacBook Air  with 1.4 GHz Intel Core i5 processor on Amazon for just under $800. Combine the evolution of processing power, weight, and cost with other digital developments in the last thirty years like the creation of the World Wide Web (1989), the creation of modern-day internet behemoths like Amazon (1994), Google (1998), and YouTube (2005), and technology that made computers truly personal, like the iPhone (2007) and iPad (2010) and you have an inkling of the kind of hectic evolution we’re dealing with.  Factor in the educational components of this equation – like the tech-savvy teachers necessary to bridge the new digital divide (see previous post here), and you have desperate, persistent struggle to keep up with what’s current.  Keeping up with what’s new is crucial and it needs to be part of professional development as well. According to Patterson, “91 percent of teachers believe their success in the classroom depends heavily on having access to technology training. Unfortunately, 60 percent of teachers don’t feel adequately prepared to integrate technology into their lessons” (Patterson).  Keeping of top of all this technology and pedagogy can be difficult for digital education leaders, and it can be devastating for teachers who are not technologically inclined.  And it’s not just about the technology we have now.  The standard itself even requires us to not only stay current on that which exists (“existing…digital tools and resources”), but also that which does not truly exist in full form yet (“emerging…digital tools and resources”).  The standard requires us to “ride the wave” of educational technology and demands we stay current.

Looking to the Librarians

 the librarians
Photo from TV Guide (and apologies to TNT)

So I found some help from the librarians.  Ok, maybe not the librarians from the TNT show, The Librarians, but I did find help on this topic from the Association of College and Research Libraries, which is a division of the American Library Association.  In an article by Steven J. Bell called “Keeping up with the EdTech Surge” I found some useful advice for all of us trying to surf the EdTech wave…or “surge.”  After a brief overview of the “EdTech explosion,” Bell goes on to explain how we should “engage” with EdTech and here he provides 5 key thoughts/recommendations (Bell):

  1. Explore three to five new educational technologies a week. This could be as simple as visiting a website or viewing a video.
  2. EdTech usually falls into one of three categories. Is it “free, freemium or fee.”
  3. Asking permission versus forgiveness. Researching tech on the job IS part of your job (ask forgiveness if it’s a problem) vs. a librarian-specific situation where you ask permission before exposing someone else’s students to an EdTech solution (ask permission)
  4. What’s the EdTech community saying? Check reviews online.
  5. Exploration is good but ask why.  No matter how cool it is and how much you make like it, the EdTech product must serve a purpose.

http://www.ala.org/acrl/publications/keeping_up_with/edtech

Admittedly, these suggestions are for librarians, but I find these guidelines to be helpful for any EdTech leaders.  The surge (“wave”) can be intimidating at times, but this measured response feels manageable. It even seems encouraging as it’s a persistent process of exploration – not a never-ending hunt for the latest-and-greatest ed tech.  It’s purposeful (tip 5) but not deterministic.  It has guidelines, but ultimately it must fit the mission.

Bell goes on to identify a dozen links to help “navigate the surge.” These are a combination of k-12 and college-level sites that deal with blogs, twitter, and other forms of digital communication that can be useful for anyone involved in surfing the EdTech wave.

The Mystery Box

Bell also includes a section on the “Mystery Box.”  I’ll admit that I was a bit skeptical of what he was talking about here, but in the end, I think it makes sense.  Bell shares a link to a TED talk featuring director JJ Abrams.  In it, Abrams discusses a “Mystery Box” that he received as a child but never opened.  It was supposed to be full of incredible magic tricks, but for Abrams, this unopened mystery box served as metaphor for the power of the unknown – a hallmark of much of his subsequent work as director. Bell applies it to EdTech, “When it comes to EdTech and blending our librarianship and instructional technology skills, Abrams words speak volumes because it is the drive to unravel the mystery of how to best leverage technology to enhance learning that should drive us, as academic librarians, to explore, experiment and discover all that the EdTech world has to offer” (Bell).  Again, Bell is speaking for librarians, but I see no reason why “librarianship” cannot be replaced with “teaching sklls” – especially if we are to be EdTech leaders.

Whether or not we view it as a “mystery box,” exploring EdTech is something we must always be doing as digital education leaders; it just comes with the territory.  After all, we don’t want to be using last-decade’s digital tools any more than we want to be using last-century’s pedagogy (though we often see both).  I believe Bell’s suggestions can go a long ways towards helping us avoid these hazzards and help us get on our boards and more effectively surf that Ed-Tech wave!

Addressing the Prompts:

Connecting with ALL of the ISTE Teaching Standards, write a narrative of your learning throughout this quarter: 1 What level of understanding and competence of the ISTE Teaching Standards did you start with this quarter? 2 What were one or two of the more significant areas of growth throughout this quarter? 3 Where would you like to continue to grow? 4 How can you empower others- colleagues, etc., as outlined in ISTE Coaching Standard 2?

  1. While I started with no formal understanding of the competence of the ISTE Teaching Standards, I was familiar with them through their connection with the ISTE Student Standards from last quarter.  Dr. Wicks had indicated that we would be addressing these in the following class, so while they were not completely unknown to me, this is the first time had studied them in-depth.
  2. While there is quite a bit of overlap between the student and teachers standards, there are others that were more unique in their application to teachers and thus afforded me the most opportunities for personal growth throughout the quarter.  These would be standards 2 and 5.  Standard 2’s requirement to develop digital age learning experiences and assessments – particularly as it applies to technology-rich learning environments, was very interesting to me; and standard 5’s requirement for professional growth is another area where not only myself, but all teachers could afford to grow (“growth”is in the title, after all, and it therefore connotes a continuous process).
  3. I think I would like to continue growing in the two aforementioned areas, particularly in #2 – as it relates to the digital teaching environment. I believe that if teachers are impeded from truly transforming their classrooms into digital learning environments, then we will not see the 21st century classroom, just the 19th century classroom with computers in it.  That would be a shame.  The Patterson article comes to mind again, “This misstep [lack of tech training] can increase teacher resistance and negate the power of technology implementations.” (Patterson). The true promise of digital education lies in its effective implementation, not merely its presence, and therefore the more we can do to make that evolution a reality, the better.
  4. When looking at coaching standard 2, the piece that jumps out to me the most are the verbs used in the standard.  “Coach and model” appear in all of the indicators for standard 2 and the verb “assist” is the primary action given in the standard itself. It seems to me that the standard is requiring we empower others by modeling the effective use of technology and assisting them in doing so also.  To that end, I believe that I can best empower my colleagues by demonstrating meaningful, effective use of digital technology and encourage and facilitate others in doing the same. This involves not only using the technology, but also maintaining a positive mindset about the use of technology (which can be difficult when things go wrong) and demonstrating flexibility in the face of adversity (like when things go wrong).

 

Bell, Steven J. “Keeping Up With… The EdTech Surge.” Association of College & Research Libraries.  Retrieved from: http://www.ala.org/acrl/publications/keeping_up_with/edtech

Comen, Evan, and Michael B. Sauter and Samuel Stebbins (April 15, 2016). “The Cost of a Computer the Year You Were Born.” 247wallst.com.  Retrieved from: http://247wallst.com/special-report/2016/04/15/how-much-a-computer-cost-the-year-you-were-born/6/

ISTE (2008). “ISTE Standards for Teachers.” International Society for Technology in Education. Retrieved from https://www.iste.org/standards/standards/standards-for-teachers

Patterson, Mike (2016, April 26).  “Tips for Transforming Educational Technology through Professional Development and Training.”  EdTech K-12 Magazine. Retrieved from http://www.edtechmagazine.com/k12/article/2016/04/tips-transforming-educational-technology-through-professional-development-and

 

 

I, Robot – or at least thinking like one: ISTE Standard #5 “Computational Thinking”

Image result for asimov foundation

“Students formulate problem definitions suited for technology-assisted methods such as data analysis, abstract models and algorithmic thinking in exploring and finding solutions.” ISTE Standard 5, indicator 5a (2016)

“This kind of thinking [computational thinking] will part of the skill set of not only other scientists, but of everyone else…computational thinking is tomorrow’s reality.” Jeanette M. Wing, “Computational Thinking” (2006)

“1. A robot may not injure a human being, or, through inaction allow a human being to come to harm.  2. A robot must obey the orders given it by human beings except where such orders would conflict with the First Law.  3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.” The Three Laws of Robotics. Isaac Asimov, I Robot (1950)

Image result for i robot asimov

I would like to bookend my thoughts on ISTE standard 5 this week by using one of my all-time favorite science fiction authors, Isaac Asimov.  In 1950, when robots were still the stuff of science fictions and computers took up an entire room and had an internal memory of 1000 words, Asimov imagined walking, talking, almost-sentient robots who served mankind.  The genius of his story-telling was not in making talking, thinking robots – there have been countless, forgettable sci-fi stories about robots, but in the algorithm he had integrated into all of his fictitious automatons: the Three Laws of Robotics.  These were the fail-safe mechanism in the universe he created, and they were also the basis for all of the stories in I, Robot.  In a way, I, Robot is a book about computational thinking.

Computational thinking (CT) is useful for solving real-world problems and it trains the mind to think in a very specific way – a practical, logical, and beneficial way.  In fact, I think the world would be better off if more of us used CT on a regular basis to solve problems in our lives.  And the ISTE is with me on this. Their fifth standard for students is “Computational Thinking” and it advocates for “Students [to] develop and employ strategies for understanding and solving problems in ways that leverage the power of technological methods to develop and test solutions” (ISTE).  Brilliant.  Upon further reading, I came across indicator 5a, which states its intention to help, “Students formulate problem definitions suited for technology-assisted methods such as data analysis, abstract models and algorithmic thinking in exploring and finding solutions.”  This intrigued me, especially the first part.  What is this saying about the questions we should be encouraging our students to ask?  The expanded explanation in the ISTE site states that “formulate problem definitions,” means students should “Create and articulate a precise and thorough description of a problem designed to facilitate its solution, including conditions and constraints that must be taken into account.” The heart of my question for this standard revolves around this process.  Are we to encourage our students to frame their questions around a particular way of thinking?  One that is “precise” and leads to a “solution”?  In some ways, these goals sound contradictory to the “authentic” problems laden with “ambiguity” and “open-endedness” valued in ISTE standard 4.  Framing the question is important.  How the question is framed – how it’s conceived – can often determine the outcome.  If we are going to buy-in to a specific way of thinking and a specific way of framing the questions we ask, we should be aware of exactly what we are doing.  My question seeks to reconcile the two approaches mentioned in the standards and to find out more on how to apply CT specifically to my field of history.

A partial answer was located in one of the readings for the week, Barr, Harrison, and Conery’s piece on “Computational Thinking: A Digital Age Skill for Everyone” (2011). In this article, which advocates for teaching CT in K-12, they identify a number of “dispositions or attitudes that are essential dimensions of CT.”  Among these are “tolerance for ambiguity” and “the ability to deal with open-ended problems.”  How these manifest themselves in the in process of computational thinking is not clear.  In fact, they really say nothing about it, other than it’s an attitude.  In searching the article further, I came across the name of a woman who is at the center of the CT movement, Dr. Jeannette M. Wing.  The Barr article mentions one of her works on CT as “seminal” and so I decided to go straight to the source to find out more.

https://www.cs.cmu.edu/~15110-s13/Wing06-ct.pdf

Dr. Wing’s article argues for the importance and inevitability of CT. She also explains what it is and what it isn’t. She writes, “it is conceptualizing, not computer programming…It is fundamental, not rote skill…It is a way humans, not computers, think…It complements and combines mathematical and engineering thinking…It is ideas, not artifacts,” and, “it is for everyone, everywhere” (Wing, 2006).  The third statement struck me as relevant for my point and I examined further.  Dr. Wing states that CT is a way humans solve problems, but not trying to get humans to think like computers.  She writes, “Computers are dull and boring; humans are clever and imaginative. Equipped with computing devices, we use our cleverness to tackle problems we would not dare take on before the age of computing.”  I understand her point that we need to be creative and use computers as tools to further our creative endeavors, but it’s difficult to discern how that fits with CT.  Her first point about CT being conceptualizing, not programming is helpful in this regard since she points out that “Thinking like a computer scientist means more than being able to program a computer. It requires thinking at multiple levels of abstraction.”  I can only surmise that that’s where the answer lies: in our ability to think abstractly.  It would allow for ambiguity and it would allow for open-ended questions and answers.  I’m still not sure how it fits with the formulaic part of CT or what it means for devising questions along the lines of CT.  In fact, on this latter issue, Dr. Wing wants us so invested in CT so heavily that we don’t even realize we do it. She writes with regard to her last point that, “Computational thinking will be a reality when it is so integral to human endeavors it disappears as an explicit philosophy.”  So essentially we should do it and not even think about it.  That seems like an awfully big ask.

With regard to CT and history, the answer is even less clear.  The Barr article gives an example that uses it to some degree, but it’s much more of a compare and contrast exercise (which uses some degree of CT) than it is a specific example of the use of CT.  Dr. Wing has another article from 2010 where she mentions “computational social science” but does not elaborate on what that course looks like (Wing, 2010).  She also references an as-yet unpublished manuscript she’s writing called, “Demystifying Computational Thinking for Non-Computer Scientists” and issues a call to other computer scientists, “Our immediate task ahead is to better explain to non-computer scientists what we mean by computational thinking and the benefits of being able to think computationally.”  Yes, this is what I need.  I think there is work to be done here. While I think I understand the process, in some ways it’s still fairly mystical to me – in its approach to asking questions, in its totality, and in its application to the social sciences.

Humans are difficult, by nature, to think about computationally.  When studying history, we study behaviors and actions and stories over hundreds or thousands of years.  Humans do not function like computers.  We do not always act logically. Love, hate, fear, confidence, selfishness, and altruism (just to name a few) are all contradictory parts of our nature and have played various roles in the history of human-kind.  How can CT account for that?  One of my favorite topics to teach my students is “prisoner’s dilemma.”  It essentially where a person acting selfishly gets the least-beneficial outcome for themselves AND the person they are competing against (see video below).  Why would a person choose a sub-optimal outcome for both themselves AND another person when a more optimal outcome is available to them?  Oddly, it IS logical.  And yet, if we are only concerned with the best outcome – solving the problem with the intent to get the optimal result, we would be choosing the “wrong” path.  History is full of sub-optimal outcomes that defy rationality.  People act for their own reasons at a given time, but they don’t know the results in advance.  As historians, we look back with 20-20 vision. We know what’s coming (for the group being studied) and we try to understand why things happened as they did.  It’s the ultimate exercise in open-ended questions. I don’t know, as of yet, how CT helps with that.  I don’t know how it helps my students with that.  I guess I’ll wait for the demystification article.

 

I started this post by saying I’d bookend it with Isaac Asimov and so I shall.  I said that I, Robot is, in a way, about computational thinking, and it is.  But in some ways, it’s a book about the problems with such an approach. Each chapter involves some sort of conflict with or alteration of the Three Laws of Robotics. The robots in these stories are bound (“hard wired,” if you will) to that basic algorithm and Asimov has a great deal of fun pointing out the potential problems when something must operate strictly using a set pattern of behavior.  It is the humans who must come up with the creative solutions to the problems created by their own inventions.  I still remember reading as child the second chapter of the book about the Speedy the robot.  Speedy was casually ordered to get some selenium from a pool on Mercury but failed to return. When they found Speedy, he was running in circles and acting as if drunk.  The problem was that Speedy was an expensive, experimental robot, so the 3d Law about self-preservation was strengthened. He couldn’t complete his task because of some dangerous gas near the pool which would probably destroy him (3rd law strengthened), but he also could not ignore the order he was given (2nd law, weekly ordered).  The ensuing conflict had him stuck in a loop which was only broken when one of the scientists on Mercury deliberately put himself in harm’s way and Speedy’s application of the First Law kicked in and he saved the human.  I think CT too may have it’s limits.  Of course, admittedly, I don’t entirely grasp all aspects of it, but I will keep asking questions – even when it’s supposed to be so internalized we don’t even think about it.  I’m sure there’s a creative solution.

Incidentally, the year after Asimov published I, Robot, he published another book called, Foundation.  It was the story of a mathematician who used advanced mathematics (CT?) and history to formulate a completely accurate predictive model of the future.  Combining math and history gave him the key to knowing the future.  It was called “psychohistory.”  Maybe that’s next.

Image result for asimov foundation

 

Asimov, Isaac (1950).  I, Robot.  London: Folio Society

Barr, D., Harrison, J., & Conery, L. (2011). “Computational thinking: A digital age skill for everyone.” Learning & Leading with Technology, 38(6), 20-23.

ISTE (2016). “ISTE Standards for Students 2016.” International Society for Technology in Education. Retrieved from http://www.iste.org/standards/standards/for-students-2016

Wing, Jeannette M. (2006). “Computational Thinking.” Viewpoint, Carnegie Mellon School of Computer Science.  Retrieved from https://www.cs.cmu.edu/~15110-s13/Wing06-ct.pdf

Wing, Jeannette M. (2010). “Computational Thinking: What and Why?”  Carnegie Mellon School of Computer Science.  Retrieved from http://www.cs.cmu.edu/~CompThink/resources/TheLinkWing.pdf