Archive for the ‘Academics’ Category

A summary of ‘Improved Learning in a Large-Enrollment Physics Class’ by Deslauriers, Schelew & Wieman

February 17, 2017

Deslauriers et al. (2011) measured learning outcomes from research-based instruction in a university introductory level physics class. The outcomes were compared to outcomes from tutoring the same material in traditional lectures by an experienced and highly rated instructor. That is, the latter was used as control in a purportedly controlled experiment.

science332Deslauriers et al. (2011) found that students subject to research-based instruction scored more than twice as well as students subject to traditional lecture tutoring (74% vs. 41%). Both attendance and engagement reportedly went up. The authors were seemingly puzzled by the increased attendance (‘reason not known’), while it seems obviously a case of rubbernecking or something similar but more sophisticated. (Google awaits!)

The research-based instruction in question (it could be almost anything) was designed to have students engage in deliberate practice at thinking scientifically. Thinking scientifically was taken as making and testing predictions and arguments about relevant topics, solving problems, and questioning their own reasoning and that of others, presumably after the appropriate reasoning was revealed. Multiple (unspecified) ‘best instructional practices’ were incorporated, but the educational benefit was believed to derive from the overall, integrated deliberate practice framework rather than any particular practice. Class schedules were mostly an alternating sequence of discussions in small student groups, clicker questions, and instructor feedback. That the measured engagement in such classes surpasses the measured engagement in traditional lectures comes as no surprise.

While I am personally convinced that active learning and deliberate practice better provide learning than traditional lectures, I have doubts regarding size of the reported effect and both internal and external validity of the experiment.

Could other factors influence the measured learning outcomes and reduce the real effect of research-based instrution? Two obvious factors are that the research-based instruction was more resource intensive (the instructor had an assistant in class throughout the experiment; materials were pilot-tested before used in class) and contrbution of the Hawthorne effect (‘where any change in conditions is said to result in improved performance’). Regarding the latter, one may add temporarily. The Hawthorne effect is, interestingly enough, dismissed by Deslauriers et al. (2011) because the effect could not be detected in the original Hawthorne data. But that the effect was not present in some data does not mean that the effect does not exist.

How well was the experiment controlled? The experiment group (subjected to research-based instruction) was instructed by two of the authors of the study, and not the usual instructor. This is presented as something that should reduce the measured effect because the authors had less teaching experience and background knowledge in physics. Clearly, the experiment would be better controlled if the usual instructor was trained and assisted (outside of class) in research-based instruction. The experiment would also be better controlled if the experiment and control group had had the same instructor prior to the experiment. Alas, they did not. Both of these improvements would have been readily achievable.

Can the findings be generalized outside the experiment, like tutoring in other subjects, and at all university level tutoring? The experiment lasted for one week, so the foremost concern is whether the research-based instrution would provide a similar effect on the full-scale course level. I am sure it would, but research-based instruction, as argued above, does require more resources than the traditional lectures. A ‘twice as well’ effect is probably unlikely, however (Hawthorne again, and temporality).

In a subsequent survey of the students subjected to the research-based instruction, students express satisfaction with the alternative form of instruction. This finding is taken as evidence against concerns of student opposition towards changes in the instruction. But not all students answered the survey, and measures were taken within the experiment group to avoid resistance against the instructional approach. The survey evidence is thus questionable if not useless.

It amazes me that a study with so many obvious weaknesses is published in one of the most prestiguous scientific journals.

Deslauriers, L, E. Schelew, C. Wieman (2011), Improved Learning in a Large-Enrollment Physics Class. Science 332, 862 – 864.

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ARC-Change web page

October 26, 2016

Earlier this year, I posted on a new research project, ARC-Change, on climate change in the Arctic and its consequences for governance and resource industries. The project is now underway, and recently the project web page went online (click logo below to go to the site).

arcchangelogoboxfish

Harvest control rules in modern fisheries management

August 5, 2016

My latest paper is joint work with a rather large group of people. We met at a workshop two years ago, and after interesting and fruitful discussions, we decided to write a paper based on our work there. After a long and winding process, the paper is now published in the open-access journal ElementaThe abstract reads as follows:

Harvest control rules have become an important tool in modern fisheries management, and are increasingly adopted to provide continuity in management practices, to deal with uncertainty and ecosystem considerations, and to relieve management decisions from short-term political pressure. We provide the conceptual and institutional background for harvest control rules, a discussion of the structure of fisheries management, and brief introductions to harvest control rules in a selection of present day cases. The cases demonstrate that harvest control rules take different forms in different settings, yet cover only a subset of the full policy space. We conclude with views on harvest control rules in future fisheries management, both in terms of ideal and realistic developments. One major challenge for future fisheries management is closing the gap between ideas and practice.

The paper is part of the special feature Climate change impacts: Fish, fisheries, and fisheries management:

The atmosphere and oceans are warming, seasonal sea ice is retreating and salinity and ocean circulation patterns are changing, all of which can impact fish populations. Largely using comparative analyses, this Special Feature examines some of the effects of climate changes on fish stocks in the northern hemisphere, particular in the Northeast Atlantic and around the continental United States. It considers what marine ecosystems may look like under anthropogenic climate change and how existing fisheries management strategies, such as Harvest Control Rules, may fare in the future. It also notes some potential economic and societal consequences of climate change.

Elementa

New Research Project on Climate Change and the Arctic

April 5, 2016

I will take part in a new research project on climate change in the Arctic. The project carries the long name “ARCtic Marine Resources under Climate Change: Environmental, Socio-Economic Perspectives and Governance,” or ARC-Change for short. From the project description:

As we enter the Anthropocene, climate change moves the parameters we live within. First and foremost, these changes will take place in Arctic regions, regions that already are subject to substantial, large scale natural variability and where higher temperatures and retreating sea ice will redefine boundaries of biological life, ecological structure, and commercial and social opportunities. Complex interactions and causal mechanisms exist from the physical impact, in terms of temperature, ocean currents, via biological and ecological adaptations, in terms of habitat expansion, growth conditions, species interactions, via social and business enterprise, in terms of new fishing areas, trade routes, mineral wealth, to governance implications, in terms of pressure on existing agreements on fishing, surveillance, and commercial activity. A cross-sectorial and cross-disciplinary perspective is needed to investigate and understand climate change impacts. ARC-Change will study some of these interlinkages, from the physical and biological to the economical and governmental, while brining together expertise from an array of disciplines and institutions.

More in the press release.

Optimal maintenance scheduling for local public purpose buildings

April 1, 2016

New paper forthcoming, something other than fish this time. The abstract:

Design/methodology/approach
We formulate the maintenance scheduling decision as a dynamic optimization problem, subject to an accelerating decay. This approach offers a formal, yet intuitive, weighting of an important trade-off when deciding a maintenance schedule.

Findings
The optimal maintenance schedule reflects a trade-off between the interest rate and the rate at which the decay accelerates. The prior reflects the alternative cost, since the money spent on maintenance could be saved and earn interests, while the latter reflects the cost of postponing maintenance. Importantly, it turns out that it is sub-optimal to have a cyclical maintenance schedule where the building is allowed to decay and then be intensively maintained before decaying again. Rather, local governments should focus the maintenance either early in the building’s life span and eventually let it decay towards replacement/abandonment or first let it decay to a target level and then keep it there until replacement/abandonment. Which of the two is optimal depends on the trade-off between the alternative cost and the cost of postponing maintenance.

Originality/value
The paper provides a first formal inquiry into important trade-offs that are important for maintenance scheduling of local public purpose buildings.

The Ensemble Kalman Filter for Multidimensional Bioeconomic Models

September 22, 2015

Natural Resource ModelingIn the recent issue of Natural Resource Modeling, I have an article together with my old boss. The idea is to apply the ensemble Kalman filter to fit multidimensional foodweb models to data for use in bioeconomic analysis. The abstract:

To integrate economic considerations into management decisions in ecosystem frameworks, we need to build models that capture observed system dynamics and incorporate existing knowledge of ecosystems, while at the same time accommodating economic analysis. The main constraint for models to serve in economic analysis is dimensionality. In addition, to apply in long-term management analysis, models should be stable in terms of adjustments to new observations. We use the ensemble Kalman filter to fit relatively simple models to ecosystem or foodweb data and estimate parameters that are stable over the observed variability in the data. The filter also provides a lower bound on the noise terms that a stochastic analysis requires. In this paper, we apply the filter to model the main interactions in the Barents Sea ecosystem. In a comparison, our method outperforms a regression-based approach.

Harvesting in a Fishery with Stochastic Growth and a Mean-Reverting Price

February 14, 2015

EREAt the end of last year, my research team got a study accepted in Environmental & Resource Economics. Our long and unsexy title — Harvesting in a Fishery with Stochastic Growth and a Mean-Reverting Price — tells only part of the story (but as much as we could fit!): We study a fish harvest model in two stochastic state variables (stock and price), where the price further is mean-reverting. Perhaps the most important finding is our demonstration of the complexity that arises in relatively simple models. The complex behavior of the optimal solution that we observe is difficult to understand intuitively, something which gave us a hard time in the peer-review process. As it should be, I guess. Anyway, our abstract reads as follows:

We analyze a continuous, nonlinear bioeconomic model to demonstrate how stochasticity in the growth of fish stocks affects the optimal exploitation policy when prices are stochastic, mean-reverting and possibly harvest dependent. Optimal exploitation has nonlinear responses to the price signal and should be conservative at low levels of biological stochasticity and aggressive at high levels. Price stochasticity induces conservative exploitation with little or no biological uncertainty, but has no strong effect when the biological uncertainty is larger. We further observe that resource exploitation should be conservative when the price reverts slowly to the mean. Simulations show that, in the long run, both the stock level and the exploitation rate are lower than in the deterministic solution. With a harvest-dependent price, the long-run price is higher in the stochastic system. The price mean reversion rate has no influence on the long-run solutions.

Letters to a Young Scientist by Edward O. Wilson

August 21, 2013

Letters to a Young Scientist entices you with its nice cover, small format, and promising title. ‘Pulitzer Price Winner’ is emblazoned on the front, below Wilson’s name. If you don’t think twice, you may think that he got the Pulitzer for Letters. He didn’t.

letters to a young scientist mech.inddIn Letters, Wilson aims to share wisdom accumulated during a long career as a biologist. Admittedly, I am not among his intended readers, as the book is specifically aimed at scientists in the hard sciences. But, science is science, social or not, so I decided there quite likely was some good advice there for a young social scientist as well (young seems to mean younger than Wilson, and that is just about everybody; I think he is in his nineties eighties).

One of the first of Wilson’s advices is, well, essentially, follow your passion. In Wilson’s words, ‘put passion ahead of training’ (p. 25*). I find this advice interesting because over the last couple of years, I have followed Cal Newport’s blog. Cal Newport is a young professor in computer science or something thereabouts. He is also a prolific writer, and he writes about how to succeed at whatever you do. He wrote a book on it called So Good They Can’t Ignore You. I read it. His ideas are particularly suited to young people with high education or much training behind them (like musicians). Cal Newport think passion is the last thing you should worry about if you want to succeed and proceed to live a remarkable life (which, presumably, is the normal course of events; I am sure Newport has a more nuanced view of this, in particular, I think he thinks finding pleasure in being on the way to success is a key element, but this is an aside). Newport has developed something reminiscent of a theory of how to go about to have success. An important part of the theory is that skills developed through meticulous training is necessary to have success. And, to get back to Wilson, Newport’s mantra that following your passion is bad advice clashes with Wilson’s advice, head on. So, who to believe? The experienced, senior, and highly successful Wilson, or the young Newport (on his way to success, I am sure)? I think Newport is right. I do not doubt that Wilson’s advice is ‘an important principle [he’s] seen unfold in the careers of many successful scientists’ (p. 25), but I bet most of them took their training very seriously. If Wilson didn’t, he is probably the lucky guy. Wilson sees a lot of trees, I’m afraid, but there is no forest (his dust jacket notwithstanding). And that most successful scientist has a lot of passion for what they do is not strange at all. It gave them success, after all, and research is supposed to be important and good and I am sure most successful scientist receives a lot of such feedback, and that probably helps if the passion is not always so strong.

Wilson devotes most of his letters to recount success stories from his long life in science. Wilson has studied ants more than anything (and anyone, one gets the impression). Ants are interesting, but do not always feel very relevant to the overarching idea (advising young scientists to succeed). It is not always straight forward to understand what Wilson tries to say. He has a letter with the heading What is Science?, for example, where his answer to his own question leaves something to be desired. In the same letter, he poses What, then, in broadest terms is the scientific method? and again fails to provide a satisfactory answer. In Wilson’s view, a scientific problem leads, after much investigation and in the best of cases, to a scientific fact. He does not find it necessary to make the young scientist aware that there exist an entire literature on philosophy of science that any budding, young scientist should become at least somewhat familiar with and that discusses whether the idea of a scientific fact is indeed well-defined. And, most investigations into scientific problems lead to few answers and more, but perhaps deeper, problems.

A source of the ground strength of science are the connections made not only variously within physics, chemistry, and biology, but also among these primary disciplines. A very large question remains in science and philosophy. It is as follows: Can this consilience-connections made between widely separated bodies of knowledge-be extended to the social sciences and humanities, including even the creative arts? I think it can, and further I believe that the attempt to make such linkages will be a key part of intellectual life in the remainder of the twenty-first century [pp. 62-63].

That is a good advice from Wilson, I think, but already largely taken up in the existing or emerging structure of science, where interdisciplinary work is everywhere pursued and encouraged.

The ideal scientist thinks like a poet and only later works like a bookkeeper [p. 74].

Another meaningful advice, but I think the ideal scientist finds the ideal balance. The creativity necessary to move science (forward, presumably), and the bookkeeping need both to be kept up throughout and cannot be separated into disconnected modes.

Wilson’s narrow world view, which I think makes much of his advice of little value, manifests itself in the following passage, under the title Science as Universal Knowledge:

There is only one way to understand the universe and all within it, however imperfectly, and that is through science. You are likely to respond, Not true, there are also the social sciences and humanities. I know that, of course, I’ve heard it a hundred times, and I’ve always listened carefully. But how different at their foundations are the natural sciences, social sciences, and humanities? The social sciences are converging generation by generation of scholars with biology, by sharing methods and ideas, and thereby conceding more and more to the realities of the ultimately biological nature of our species. […] Yet however much the humanities enrich our lives, however definitively they defend what it means to be human, they also limit thought to that which is human, and in this one important sense they are trapped within a box [pp. 169 – 170].

And with that, he rambles into speculations about extraterrestrial intelligence. But what to take away? If your passion lies with a social science, you should become a biologist as that is where everything ends up in the end, anyway? I don’t think so (I don’t even think passion should matter). Wilson only stretches the meaning of biology, and that is of little use. He may be right that one day, human knowledge may be much more integrated as an entire body of knowledge rather than a number of separate disciplines with a few links in between. But that is really not all that relevant. What we should be thinking, is that all scientific activity sorts under science. To think of different scientific activities in a hierarchical manner is of little value.

Wilson has already proposed a biologically based theory of human behavior; human sociobiology. It caused a lot of upheaval at the time, and understandably so given statements like the following, by Wilson:

In hunter-gatherer societies, men hunt and women stay at home. This strong bias persist in most agricultural and industrial societies and, on that ground alone, appears to have a genetic origin. […] My own guess is that the genetic bias is intense enough to cause a substantial division of labor even in the most free and most egalitarian of future societies. […] Even with identical education and equal access to all professions, men are likely to continue to play a disproportionate role in political life, business and science [quoted from S. J. Gould’s An Urchin in the Storm, p. 29, Wilson originally appeared in The New York Times Magazine, October 12, 1975].

Stephen Jay Gould has written extensively on human sociobiology. Much of it appears in his An Urchin in the Storm. Among his conclusions are that human sociobiology is founded on a flawed mathematical and theoretical basis, that its empirical content is failing. For anyone interested, I can recommend Gould’s review (pp. 107-ff in Urchin) of Wilson’s popular work Promethean Fire, where Gould attacks, among other things, Wilson’s belief in reductionism.

I am not sure how to round up my review of Wilson’s Letters. As a young (social) scientist myself, I cannot say I learned a lot from it; nothing I had not heard from before. As someone not overly interested in ants (although I do find social behavior among animals and insects interesting), I found Wilson’s accounts of his many worldly and scientific adventures way over the top. And Wilson’s constant glorification of his own career and his own choices are nothing but annoying. My conclusions is Don’t read Wilson’s Letters.

* Page numbers refer to the first edition, 2013.

Notes on an Academic Writing Class

July 10, 2013

While I visited UC Berkeley, I took the opportunity to follow a writing class aimed at visiting researchers. Natalie Reid, who has written Getting Published in International Journals: Writing Strategies for European Social Scientists, gave four lectures on the basics of punctuation, editing (your own text) and revising, organization and how to structure arguments, and a curious topic she called journal analysis. In her lectures, Reid drew on her experience as a professional editor and writer and supplied illustrative examples and instructive stories of writing gone good and bad.  And she made no mistake reminding us of her book throughout the course.

Ever since I entered academics, I have entertained an interest in good writing. I found Reid’s lectures a useful reminder of all those small things important but that is easily forgotten in the heat of the writing. Below, I have transcribed some of my notes from the lectures (in the order they appear in my notebook). Some are important, some are good, some I disagree with, and some are just great quotes.

  • English is not a language, but a language group, for example with differences between US English and British English. Reid repeated this message endlessly. Some of the repetition could with advantage have been traded for some important details on these differences, of which Reid said very little.
  • ‘Writing is thought made visible.’ (Famous quote, but I failed to take note of who said or wrote it.) Implication: Clear writing cannot arise from unclear thinking. McCloskey discusses the point at some length somewhere (in her Rhetorics, I think), and goes on to maintain that writing is thinking and thinking is writing. McCloskey’s point is that they are not unconnected processes and that they must and should happen in parallel.
  • A definition of Rhetoric: Organisation and strategies speakers and writers use to affect their audience. (And it is a two-way street: the audience affects the rhetoric.)
  • The reader should not have to think (by themselves), only absorb and consider.
  • Good academic writing (in the Anglo-Saxon tradition or whatever) follows Aristotelian logic.
  • Reid advanced the following advice for how to structure an article (or argument): Tell the reader what you are going to tell him; tell him; tell him what you told him. McCloskey (one of my rhetorical heroes, as my hypothetical readers may know) argues against such unnecessary repetition and I agree with McCloskey (see her Economical Writing if you think you disagree).
  • Rewrite.
  • Murphy’s Law will strike: If there is any chance the reader can misunderstand, he will.
  • A good sentence is clear on first reading.
  • We suffer from tunnel vision when we write. (We only see our meaning, not what we are actually writing; we should try and revise with a cool eye.)
  • Less is More: Make every word tell (see Strunk & White’s Elements of Style). Shorten structure words (like due to the fact that; in view of the above; in the course of).
  • Avoid too long sentences: You should be able to read a sentence out loud in one breath.
  • Avoid the common ‘previous literature’ (of course it is previous, what else?).
  • ‘It is’ and ‘there is’ is bad writing. (I find this advice hard to follow, by the way. What am I supposed to write instead when I want to make the reader aware of the existence of whatever?)
  • One of my favorites: Sound like an expert (reduce hedging).
  • Editing for clarity: avoid ambiguity; use the active voice, check modifiers, use parallel structure; check punctuation.
  • The solution to vagueness is (often?) repetition.
  • Use not ‘this’ and ‘these’ by themselves; attach the appropriate noun.
  • Only use ‘it’ when there is only one word it can refer to.
  • ‘Which’ and ‘that’ can only refer to the word immediately before them. Further, ‘that’ (with no comma) for essential information; ‘which’ (with comma) for nonessential information.
  • ‘Good writing is speech written down and then cleaned up’ (a Reid-quote, I presume).
  • Avoid the passive voice. It requires more words, it obfuscates the order of things and adds mental strain, and it is boring.
  • Watch modifiers. (This advice is also hard to follow as modifiers pop up all the time and seldom with a red flag.)
  • My notes on Reid’s lecturing on organisation and arguing in Aristotelian logic are unfortunately insufficient to be valuable.
  • Conclusions (the final part of an article) should derive solely and logically from the body of the article; no new arguments are to be introduced. If the journal in question has discussion and conclusions in the same section, conclusions are to come first and discussion second.
  • The abstract is the last thing to be written.
  • Outline, outline, outline. Reid laid out a strategy for outlining: 1. Write down the purpose statement in one sentence. 2. Write a (vertical) list of all things that goes into the article. No second-guessing: brain storm. 3. Do the entries on the list serve the purpose in step 1? Be critical, make everything fit the purpose. 4. Sort the list into  different sections. 5. Sort each section into a logical order. 6. Sort sections. (I actually tried this, but realized I did not know everything that was going into my paper. Not from the top of my head, at least. Step 2 has to be a deep exercise if Reid’s strategy is to be useful, I think.)
  • Revision: Is the language correct? Is stuff in the appropriate section? Do the argument support the conclusion? Boring or confusing? Counter all possible objections. Use an editor (a self-serving advice on Reid’s part, of course, but still not a bad advice). Follow journal guidelines.
  • Some advice on writing resubmission letters: Do not assume the editor remembers anything. ‘Echo’ comments before replies such that the editor do not have to check back to his original letter (in general, make the editor’s job as easy as possible). Use respectful language (can be trickier than one might think when one ain’t a native speaker).
  • On paragraph length: Language influences paragraph length. The British has a peculiar habit of writing long and short paragraphs in imperfect alternation. The Americans want their paragraphs to be no more than ten to twelve lines of type. But a journal may have its own ideas about paragraph length. McCloskey’s advice is that the paragraph is the unit of thought (or something); one idea (or perhaps argument) per paragraph. Some of my arguments certainly require more than twelve lines of type, but I am of course a rather poor writer.
  • Reid spent quite a lot of time on what she called journal analysis and implicated that serious scholars habitually spend considerable time on journal analysis every time they are about to submit something. Journal analysis helps you decide on where to submit work, and how to decrease the chance of rejection. Journal analysis covers several pages in my notebook, but I am not convinced of its usefulness. The process suggested by Reid would take too much time, in particular as much of the process is far removed from the actual writing.
  • Suggested literature (popped up at different times throughout the course): Dictionary of Concise Writing (Rob. Hartwell Fiske; vocabula.com). Ayn Rand’s book on writing. On Writing Well by Zinsser. Stephen King’s book on writing.