Category Archives: algorithm

Lifestream Blog Final Summary


In EDC, we practiced a ‘pedagogy of networked learning’ in which knowledge was “located in the connections and interactions between learners, teachers and resources” (J. Knox). This was my first blogging experience. I approached the blogging requirement with much hesitation and trepidation, as my personal preferred learning style is much more introspective. Now that I am more ‘educated’ about digital cultures, I expect to be more circumspect henceforth about my digital presence and interactions.

Block One was an exploration of the ‘uncanny’ themes and ‘blurring boundaries’ of the human-technology binary. We pondered the quintessential question: “What does it mean to be human” in the digital age? This ‘unorthodox’ initiation – juxtaposing robots, cyborgs, androids and theoretical discourse on post- and trans-humanism immediately imbued me with sense of ‘belonging’ to an eclectic online academic community. The ‘comfort level’ was enhanced by the course design that had a seminar-like ambiance with less than a dozen students. The interaction with new EDC peers and instructors struck an appropriate balance between friendly, supportive online exchanges and serious academic inquiry.

The creation of our Block One digital artefact was a major accomplishment for me, as it was my first publicly posted YouTube video. I was initially overwhelmed by learning new digital tools, ‘wasted time’ and made many production mistakes. However, a confluence of serendipitous events coalesced to enable me to pull together the digital artefact. Learning should be a trial and error, constructive and creative process. Also, I learned that technology is symbiotic with being human, and that technology can indeed enhance or even transform learning. We just need a more nuanced understanding. (S. Bayne; TEL)

The MOOC micro-ethnography project during Block Two was another confidence-building assignment. Kozinets affirmed that technology and culture are co-determinant and co-constructive. A “thorough understanding of these contexts requires ethnography.” Assuming the role of a digital ethnographer afforded insights into the MOOC learning environment that I would not have achieved otherwise, purely as a MOOC student. I experienced the ‘tension’ of being both an insider and outsider simultaneously; the empathy and the distance.

Block Three was punctuated by our intensive Tweetorial which I approached in an atypically extroverted mode. My ‘performance’ revealed a latent obsessive-compulsive learning tendency that demands deeper self-reflection. My online reputation (‘klout’), based 100% on Twitter activity, doubled during this course from an initial measure of about 18% in January to 36% at the end of the course. From an ‘analytics’ perspective, this metric indicated some level of transitory increased engagement activity on my part as a digital learner.

With each Week’s blog posts, I tried to include at least one substantive blog summary of the academic readings to demonstrate my understanding of key concepts. Later in the course, I also tried to synthesize and share some of key concepts from readings within the constraints of the 140-character Tweet limit. Martin Hand enjoined us to consider the “parameters of access, interactivity and authenticity of an emerging digital culture.” Ben Williamson warned us that “algorithms are out of control,” while Jeremy Knox appealed to us to interrogate how learning analytics can “make the invisible visible.” In light of the paradigmatic shift from teacher-directed classrooms towards learner empowered, technology-enhanced education, perhaps the role of educators is to teach the critical thinking skills required to regain control of our humanity, as technology becomes more powerful and pervasive.

Making mistakes is a critical aspect of learning. I only hope that my EDC online interactions caused ‘no harm.’

“The presence of others who see what we see and hear what we hear assures us of the reality of the world and ourselves.”(Hannah Arendt)

Thank you for the ‘assurances,’ distant yet close EDC friends. See you again, soon, online.

EDC Final Summary Cloud
(Word cloud of my Weekly EDC Summaries)

Week Ten Summary: Continuing the Journey into the Unknown


Although Week Ten was labeled as “Pulling it All Together”, I find myself bewildered and grasping at week’s end for a coherent focus for the final assignment. I felt that we had collectively thoroughly and critically interrogated algorithms during Week Nine and the Tweetorial. I personally felt however, that I had not put enough time and thought into learning analytics and educational data mining (EDM). Although I had read Dr. Jeremy Knox’s essay and spent some time reviewing commenting on the Ben Williamson video, there were other areas that peers highlighted in their blogs that I have not explored enough. Perhaps I can try to tease out these areas a bit more cogently in the remaining weeks.

The Google Hangout was engaging and instructive, but I wish that I had refreshed my memory immediately beforehand by re-reviewing peers’ recent blog posts. There were many creative artefacts and salient points that I had read on their blogs, but after work on Friday evening (in my timezone) when I was logged onto the Hangout, I could not readily recall and distinguish between everyone’s blogs to comment lucidly, in an obviously informed and constructive manner. Fortunately, our mentors artfully sorted it out and provided clear context and synthesis.

As mentioned during the Hangout, I am exploring some readings on the theme of ‘invisibility’ which has illuminated some interesting manifestations for online learning. For example, Michael F. Beaudoin has done research on tracking the “invisible” online learner (e.g., are they lurking or learning). Other aspects that might considered are the time is spent in On- and Off-line activities, different learning styles, different uses of various platforms, etc… Also, related to our Hangouts, is the nature of ‘online silence,’ issues of non-participation and unresponsiveness, and response latencies in asynchronous computer mediated communications. It seems that, in EDC as with other MScDSE coursework, there is invariably one or two ‘pregnant’ pauses during these group online sessions. I find this phenomenon quite fascinating. Is that a collective ‘learning moment’? or perhaps there is another clever pedagogical phrase for it?

My outing on Sunday to two museum exhibitions, which I blogged about below, was an attempt to get some fresh air and fresh insights. I am still ‘marinating’ on those excursions hoping that they will foment some profound revelations that will enable me to assemble the recent EDC course themes, and magically and materially “pull it all together.”

Week Nine Summary: Algorithmic and Learning Analytics Sense-making

Lifestreaming this week has revolved around a deeper interrogation of ‘algorithmic culture’ and an introduction to learning analytics. The goal of ‘sense-making’ in these areas of exploration has proven elusive, but the week’s activities have been instructive and illuminating, and opened up a variety of paths for future research.

Ben Williamson’s video presentation offered many valuable insights as to what he envisions as ‘imagining’ of the digital university and all the attendant issues related to the influence of algorithms and learning analytics. The vision is of a higher educational institution that is ‘sentient,’ ‘data-driven,’ and mediated by digital technologies. He advocated for the need to develop a sense for the emergence of socio-technically-oriented “fabricated spaces.” His explanations of algorithms, though somewhat pedantic in the way he read directly from slides, provided new perspectives on ‘socio-algorithmic relationality’ (slides 4-6; citing David Beer, 2013) and the influence of “algorithmists.” I thought his investigations of the ‘epistomology’ of big data (slides 10-15) was most penetrating in describing how algorithms are increasingly becoming entwined with academic knowledge; what he refers to as the “algorithming of the academy.” Honestly, I am now more profoundly sympathetic towards the increasing demands on university professors, with their evolution from their traditional role as ‘performers’ in the lecture hall to the requirement to maintain a presence online, on social media, as well as in the lecture hall/classroom environments.


I believe that the ‘digital university’ is becoming a reality. For example, in the form of the Minerva School experiment in San Francisco, the Singularity University, and probably several other initiatives at higher educational institutions world-wide. The challenge will be adjudicating the potential of the learning analytics and algorithmically-driven technologies with the concerns for privacy, data access and transferrability, and monetarization of data in these exciting new learning environments.

Ben Williamson tweeted recommendation of a recent article by Frank Pasquale, “The Algorithmic Self,” which I strongly recommend. It convincingly articulates and place into context all the current themes surrounding algorithms. A poignant observation is that: “We need some common, clear awareness of whom the algorithms behind the screen truly serve before we accept their pervasive presence in our lives.”

PJ Klout My Klout influence rating, based 100% on my Twitter activity, has risen from a low of 18.91 to 34.90 in the past 90 days. So what? How do I ‘modulate’ my online selfhood? Is this my “data self”?

“…there is a delicate balance between appropriating new technologies and being appropriated by them.” (Harmut Rosa, cited by Frank Pasquale)

Dr. Jeremy Knox asked me to reflect on last week’s investigations of algorithms and my own personal Quill Connect report. My Tweeter activity swelled this week as we engaged in an intensive Tweet tutorial. I assumed a very, uncharacteristic, aggressive posture towards this activity. My intent was not to boost my ‘influence,’ but to experiment liberally with this media to determine the ‘reach’ of this modality. I repeated the Quill Connect Report this week, which revealed that I posted 50 tweets this past week, 31 tweets more than usual, but somehow my average tweets per week remain at the Twitter user average of 2 per week. So now I am more suspicious, cynical, skeptical of what is actually going on with the underlying algorithm of Quill Connect; as I am generally now of all algorithms.

Dr. Konx prodded me to consider: “What does that (‘average twitter user’) really mean for a service like Twitter? I think it means more ‘committed’ subscribers; that is, a consumption-driven imperative, not necessarily a thoughtful, or educative one). Dr. Knox noted that I focused last week on ‘statistical measures,’ and I confess that I probably feel into the Big Data ‘big fallacy’ trap elucidated by Ben Williamson (with credit to Rob Kitchin) that ‘de-contextualized statistical data analysis can be reductive, functionalist & unhelpful as it lacks embedding in wider debates, social theory & contextual knowledge.” Apparently, the “average Twitter” user is a middle-aged, American female with an IPod.

Frank Pasquale suggests: “the first step of protecting the self in age of algorithmic manipulation is to recognize such manipulation as a problem.” One needs “source of value,” “sources of the self,” and “anchors of integrity,” pertinent to each individual, to protect oneself from potential domination by powerful technologies. I think this is the role that education and educators can play, in transmitting such knowledge and values.

Surrendipitously, I happened to view a couple U.S. news broadcast that I felt were relevant to recent EDC themes; which I tweeted below. One broadcast featured the introduction of digital technologies into the classrooms of the very traditional, conservative, religious sub-culture of the Amish community in the Mid-west of the U.S.A. Surprisingly, despite maintaining a simplistic, technology-free lifestyle, the Amish have embraced digital, educational technologies. This was yet another example of how socio-technological relationalties are changing rapidly.

Another broadcast examined a rising interest incoding. There was some debate in our Twitter Tutorial this past week about whether everyone needed to learn to code, with some EDC peers citing Evgeny Morozov, who considered it a “most bizarre and repressive idea.” However, even Morozov conceded that he is “all for making us aware of the various technological infrastructures at work.” Morozov is also no fan of the notion of “program or be programmed,” disdaining the use of metaphors. But, the question arises what the average online user needs to know about algorithms, coding, programming? What do we (as educators) need to teach to the next generation, so that they can make sense of themselves and rapidly emerging technologies?

I look forward to “pulling it all together” over the remaining few weeks.

Pasquale, F. (2015). “The Algorithmic Self” in The Hedgehog Review: Vol 17, No. 1.

Siemens, G. (2013) Learning Analytics: the emergence of a discipline. American Behavioral Scientist, 57(10): 1380-1400.

Williamson, B. (2014) Calculating Academics: Theorising the algorithmic organization of the digital university.

A New Look for College? by Unknown Author

By Unknown Author

Readers discuss the pluses and minuses of the online learning model.

Published: March 15, 2015 at 09:00AM

from NYT Opinion

IFTTT algorithm at work! I had to ask myself, where did this come from? Then realized that I have an IFTTT recipe to forward NY Times articles on MOOCs.

Week Eight Summary – Algorithmic Me?

Time Magazine Cover 2006

filter bubble1filter bubble 2011

In 2006, the cover of Time magazine, proclaimed “You” (I read that to mean, me), “Yes, you, are in control of the Information Age.” This past week’s Lifestream caused me to question whether I am really in control, or actually being progressively controlled by ‘invisible’ “active algorithms,” (Knox, J. 2014) “filter bubbles” (Pariser, E. 2011) and embedded codes. Transitioning to this week’s focus on algorithms from previous block on MOOCs, Dr. Knox’s assertion that “rapid rise of the MOOC demonstrates that education is not exempt from the wider infiltration of code into all aspects of social life” (p. 43) was a poignant segue.

“Control” is a word that I expected to encounter more often this past week, and I’m not sure why it didn’t appear as often expected. Perhaps academic research is still scrambling to catch up with all the research dimensions of the exponential spurge of digital technologies and their pervasive influence of our lives. Perhaps we need new paradigms and models to explain the phenomenon. Perhaps the tools are not adequate to cope with the sheer volume of data. Maybe individual “control” is becoming an obsolete concept in the digital age, where large multinational for-profit companies are insidiously implanting themselves in our socio-materiality.

Surprisingly, “movement” is a word that seemed to be mentioned more frequently that expected; rather than “control.” This notion of movement reverberates in Knox’s examination of the ‘socio-materiality’ of the EDCMOOC where “there is no inside and outside, but rather a relations set of practices and mobilities” (p. 46), and “ideas about transition and movement between different spaces is a challenge to the the practices of data mining assumed to be one of the drivers..” (behind the major MOOCs) (p.53).
Active Algorithms.pdf

Readings, experiments with algorithmic plays, and daily virtual (mostly Twitter) exchanges with EDC peers this past week led to a increasing sense of vulnerability and hopeless abandon to a Hobson’s choice of either acquiescing to the algorithmic reach into personal freedom, or attempting to go incognito or anonymous. [See New Yorker “The Solace of Oblivion” post below]. Knox further points out that “we may need to recognize that the growing proliferation of algorithms and code act in ways that cannot be predicted.” (p. 52) The only personal defensive posture is to become more educated to be able to detect the algorithms – that Gillespie labels “codes with consequences” – all around me. Yet, Gillespie notes the seductive allure where “we simply enjoy when the algorithm confirms our sense of our self” and the deterministic logics “of these algorithms that not only shape user practices, but lead users to internalize their norms and priorities.”

Preparing myself for “more and more encounters with the unexpected” this week.

Knox, J. K. (2014). Active algorithms: sociomaterial spaces in the E-learning and Digital Cultures MOOC. Campus Virtuales, 3(1): 42-55.

Gillespie, T. (2012). The Relevance of Algorithms. forthcoming, in Media Technologies, ed. Tarleton Gillespie, Pablo Boczkowski, and Kirsten Foot. Cambridge, MA: MIT Press.

Pariser, E. (2011). The Filter Bubble: What the Internet is Hiding from You. New York, NY: The Penguin Press.

Comments on PJ’s Quill Connect

Quill connect4

I found the algorithmically-generated Quill Connect summary report of my history in the “Twitterverse” to be informative and insightful about the sheer power of algorithms, their relevance and some of the cautions. In terms of the power of algorithms and ‘big data,’ I would never have been able to examine the 6,104 tweets from myself and my recent followers that Quill Connect claims to have examined. In his forthcoming paper “The Relevance of Algorithms,” Tarleton Gillespie suggests that the key logic governing the flows of information generated by algorithms produce the “power to enable and assign meaningfulness” (Langlois 2012). This Quill Connect summary certainly provided me with some ‘food for thought’ to consider about my influence or lack thereof, and how I might interface more effectively with Twitter in the future. The capability of the algorithm to synthesize my personal data also validated Gillespie’s characterization of them to be “manna from heaven” for researchers.

quill 9

I was very reticent to join the “Twitterverse” until three years ago in 2012 when I finally realized that something profound was happening with social media, and that I had better
get ‘on-board.’ I ‘lurked’ the Coursera E-Learning MOOC and was so intrigued that I applied to the Edinburgh MScDE Programme. My engagement as a ‘digital learner’ and confidence level with social media continues to grow, but I still remain relatively cautious and conservative about my online presence and exposure because I have genuine concerns about security and privacy.

Gillespie discusses the emergence of the algorithm as “a trusted information tool” and the inherent “fundamental vulnerability” and lack of transparency that are engendered by “a new knowledge logic.” So, while my own Quill Connect report gives me some comfort that I now have a viable online history, presence and that people are interested in what I tweet, there remains a lingering skepticism of putting faith in unseen algorithmic machines that may be susceptible to human error, bias or manipulation.

I tweet ‘right at average’ for my collection of followers at 2 per week. Quill Connect indicates that I have 42 followers, which is fewer than average, landing me in the 42nd percentile of Twitter users measured by followers. This modest following does not bother me at this stage of development because I am not particularly concerned about my ‘influence’ beyond the ‘safe’ environment of my online learning community. I am concerned, however, that I have attracted other followers outside that community that I do not know.

quill 6

I have been inspired by this EDC course to be more active online, and as a result, my recent Twitter activity has picked up. This week, I sent out 19 tweets this week, eight more than last week and above my weekly average. It is curious that my most popular tweet was about the issue of time management and MOOCs shared with EDC peer Ben. For me, this tweet was just a routine
information-sharing exchange, but it seems that this theme resonated with some of my followers.

quill 10

The most popular tweet from recent followers was very curious indicating my affiliation with Vedic Sage. I believe that I attracted Vedic Sage as a follower because of previous online digital learning coursework that I had done on meditation; for example, online postings of ethnographic observation activities at the Buddhist Centre in Second Life.

It is accurate that my Tweets are most focused on Education, Business, Technology, and Politics. I always try to be positive in tone. While this report indicates that the sentiment of my Tweets “don’t skew positive or negative,” ….it also points out: “your followers skew more positive than you overall.” This commentary may cause me to reflect more in the future about how I craft Tweets, and to be more circumspect about the subtleties of tone and sentiment.

I am not overly concerned with increasing my “Twitter reach.” So I am unlikely, at this juncture anyway, to deliberately try to increase my reach is to repeating myself. However, I may heed the advice to follow people in my areas of interest, and/or people who follow the people that I follow.

Living in an Age of Algorithmic Culture

This is an hour long video recommended by EDC peer Nick. The introduction is somewhat tiresome about a colleague who didn’t show, but there is value in the two talks contrasting online and natural world impacts of algorithms on our lives. It is worth a watch in bite-size doses. I found it to be a good anchor for exploring some of the algorithmic themes that I will explore this week:
– “algorithms are invisible”
– “algorithm reveals itself in ‘rupture'”
– social reality is being determined by algorithms
– our online social influence; we are being judged, measured, “made valuable” through algorithms
– “intelligent curation”
– humans as “trusted filters”

more to follow…