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Category: Teaching

The education revolution at our doorstep

Published by demetriodor on November 14, 2012

University education is at the brink of radical transformation. The revolution is already happening and the Khan Academy, Udacity, Coursera and the Marginal Revolution University are just the harbingers of a change that will soon sweep over universities throughout the world. Alex Tabarrok has a must-read piece on the coming revolution in education here. The entire piece is highly recommended, so I am not gonna even try to summarize it here, but this part stands out: Teaching today is like a stage play. A play can be seen by at most a few hundred people at a single sitting and it takes as much labor to produce the 100th viewing as it does to produce the first. As a result, plays are expensive. Online education makes teaching more like a movie. Movies can be seen by millions and the cost per viewer declines with more viewers. Now consider quality. The average movie actor is a better actor than the average stage actor. As a result, Tabarrok predicts that the market for teachers will became a winner-take-all market with very big payments at the top: the best teachers would be followed by millions and paid accordingly. My prediction is that the revolution in education will also lead to greater specialization – maybe you can’t be the best  Development Economics teacher, but you can be the best teacher on XIXth Century Agricultural Development in South-East Denmark: economies of scale brought by online education can make such uber-specialization of teaching portfolios profitable (or, indeed necessary). Surprisingly or…

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How (not) to give an academic talk?

Published by demetriodor on April 4, 2012

Some great advice by Cosma Shalizi. These are just the footnotes: * Some branches of the humanities and the social sciences have the horrible custom of reading an academic paper out loud, apparently on the theory that this way none of the details get glossed over. The only useful advice which can be given about this is “Don’t!”…  ** … big tables of numbers (e.g., regression coefficients) are pointless; and here “big” means “larger than 2×2”. The entire post is highly recommended.

Unit of analysis vs. Unit of observation

Published by demetriodor on January 27, 2012

Having graded another batch of 40 student research proposals, the distinction between ‘unit of analysis’ and ‘unit of observation’ proves to be, yet again, one of the trickiest for the students to master. After several years of experience, I think I have a good grasp of the difference between the two, but it obviously remains a challenge to explain it to students. King, Keohane and Verba (1994) [KKV] introduce the difference in the context of descriptive inference where it serves the argument that what often goes under the heading of a ‘case study’ often actually has many observations (p.52, see also 116-117). But, admittedly the book is somewhat unclear about the distinction and unambiguous definitions are not provided. In my understanding, the unit of analysis (a case) is at the level at which you pitch the conclusions. The unit of observation is at the level at which you collect the data. So, the unit of observation and the unit of analysis can be the same but they need not be. In the context of quantitative research, units of observation could be students and units of analysis classes, if classes are compared. Or students can be both the units of observation and analysis if students are compared. Or students can be the units of analyses and grades the unit of observations if several observations (grades) are available per student. So it all depends on the design. Simply put, the unit of observation is the row in the data table but the unit of analysis can…

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Overview of the process and design of public administration research in Prezi

Published by demetriodor on December 19, 2011

Here is the result of my attempt to use Prezi during the last presentation for the class on Research Design in Public Administration. I tried to use Prezi’s functionality to provide in a novel form the same main lessons I have been emphasizing during the six weeks (yes, it is a short course). Some of the staff is obviously an over-simplification but the purpose is to focus on the big picture and draw the various threads of the course together. Prezi seems fun but I have two small complaints: (1) the handheld device I use to change powerpoint slides from a distance doesn’t work with Prezi, and (2) I can’t find a way to make staff (dis)appear ala PowerPoint without zooming in and out .

What makes a video go viral?

Published by demetriodor on November 28, 2011

Internet Marketing expert Dr Brent Coker claims to have developed an algorithm that can predict which ad movies will go viral on YouTube. I don’t plan a career move to advertising but was nevertheless intrigued by the claim from a research methods & design perspective. Unfortunately, there is very little information available (yet?) and what information is available makes me a bit skeptical about the reliability of the conclusion. Still, Dr Coker’s approach might make for a nice discussion in the context of a Research Design course since it touches upon a question students can relate to, and raises various issues from operationalization to theory specification to theory testing. In short, according to Dr Coker, “there are four elements that need to be in place for a branded movie to become viral: (1) congruency, (2) emotive strength, (3) network-involvement ratio, and (4) paired meme synergy”. Congruency is the consistency of the video’s theme with brand knowledge. Disgust and fear, for example, imply powerful emotive strength. The network-involvement ratio refers to how relevant the message is to the seeded network. The last element ‘paired meme synergy’ means that certain memes are effective when paired with certain other memes. “For example, impromptu entertainment acts appeared to work when paired with ‘Eyes Surprise’. When paired with ‘bubblegum nostalgia’, the … pair doesn’t work. Anticipation works with Voyeur, but not on its own. And so forth.” As I said, there is not much information available on the research design, but from what I can gather, the predictive algorithm is based on an inductive approach: analyze movies that did go…

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