Calculus. Years of macro theory. Micro theory. Econometrics. Study the lecture notes, practice old exams, give the prof what he or she wants. It works.
Until the day the prof says "Come up with an original research topic."
Panic. "But no one's ever taught me how to be original."
Finding an original research topic is a bit like finding a friend or a lover or a soulmate. There's no magic formula that guarantees you will meet the one person who is right for you. But you can do things that will stack the odds in your favour.
To begin with, take a page from the dating advice manuals: be open, receptive to new experiences. Go some place you haven't been before - in the real world, or in some virtual reality. Everywhere you go, look around you.
Perhaps you might spot a phenomenon that's odd, interesting, or puzzling. For example, why are so many nail salons run by people from Vietnam? Why has the number of walk-in health clinics been growing in Ontario? Why are the majority of Canadian undergraduate students female? Why do married men earn more than single men?
Perhaps you might notice a change underway, a "natural experiment". Civil war. The introduction of cable television. A change in NHL point rules. Chip and pin credit card machines that automatically calculate restaurant tips. And you wonder: what will happen? What will the consequences be?
If you go out into the world, you can observe differences between places, and over time. Many British people dry their laundry outside on clothes lines; most Canadians use driers. In some places most people are thin, elsewhere most people are overweight. Rich and powerful men don't wear ties as often as they used to.
Once you've got your observation - your puzzling phenomenon, your change in the world - then you have to ask yourself "Is it right for me?"
Again, dating guides give sound advice. Sure, hotness will grab your attention, and keep you interested for a while. But in the long run, you have to ask yourself: what do I want? What are my interests, goals, ambitions? Will this topic help me reach those goals?
And, realistically, your goal is to graduate with a degree in economics.
To achieve that goal, pick a research topic that passes two tests.
1. It can be explained in economic terms. For micro, that means an explanation based on people's choices or people's constraints - underlying material realities. Consider, for example, the question "Why are a disproportionate number of nail salons run by people from Vietnam". "Culture" is a lousy explanation because culture can explain just about anything. "Why do birds fly south?" "Because it's their culture." Where does that culture come from? What forces created these norms and values?
A good explanation will involve choices: people work in nail salons because it's the best option available. But why is it the best option available for Vietnamese immigrants, as opposed to immigrants from Germany or Rwanda or Sri Lanka? Perhaps it's a question of language skills, education, credential recognition - new immigrants work in nail salons because it's best option available for someone with limited language skills. That could be tested with data on occupational choice, language, and so on: once language skills, education and so on are controlled for, are Vietnamese people any more likely to work in nail salons than non-Vietnamese people?
If the answer is yes, then perhaps Vietnamese immigrants have some special skills in operating nail salons. It could be, for example, that information about how to work in, or operate, a nail salon is transferred through social networks, communities of friends and relations. Not culture, but "cultural capital" or ethnic capital that builds skills, knowledge, and human capital. That's a better explanation, and I suspect it's probably right.
But I don't know. And this leads us to the second test a research topic must pass:
2. Can your hypothesis be tested? For example, I have a hypothesis that the political donations tax credit goes primarily to high income Canadians. But I can't test this hypothesis, because there is no data set that contains information on both the political donations tax credit and income [correction: the Longitudinal Administrative Databank, or LAD, has this information - see comments below]. I have a hypothesis that height differences explain some of the earnings differences across ethnic groups found by Pendakur and Pendakur. But, again, I don't have the data [correction: the Canadian Community Health Survey has data on height, income and ethnicity].
Lack of data is what would probably kill Vietnamese nail salons as a research topic. My guess is that the big publicly available Canadian data sets - the Census, Labour Force Survey, General Social Survey, etc - do not separate out nail salon workers from other beauty technicians, or nail salons from other similar businesses. But you could be creative - go out and interview salon owners, with approval from the Research Ethics Board. Or search for nail salons on google maps, plot the location of the salons, and match it with information on neighbourhood ethnic composition collected from the census (though I'm not sure what you'd learn from that exercise).
Data limitations mean that, sometimes, you can't be with the one you love. So love the one you're with. Perhaps it's not possible to do research specifically on nail salons. But it might be possible to do something on cultural or ethnic capital and entrepreneurship or self-employment. Or the labour market experiences of immigrant women.
Endogeneity is another killer of beautiful and creative research ideas. When two things happen at the same time, how do you know: does A cause B, or does B cause A. "Look, I've found that professors rated as hot on my ratemyprofessors.com earn more!!!" "That's just because profs with lots of money dress better, that's why they are rated as hot." (Seriously? Have you actually looked at how the average economics professor dresses?) I try not to worry about endogeneity for the same reason that I try not to worry about cancer: it's pervasive, and there's only so much you can do about it. Sure, deal with it if you can, but accept that you might not be able to beat it.
Let's assume that you have it all: a great idea, an economic theory that generates testable hypotheses, data, a brilliant instrumental variables strategy that allows you to deal with any potential endogeneity concerns. Then the dating scene reality hits you once again: all the good ones are taken. There are tens of thousands of economists all trying to come up with brilliant research ideas. The odds that someone, sometime, has explored a research problem similar to yours are high.
But so what? Taking a US study and re-running it using Canadian or other data, updating a study that someone else has done before with more recent data or better econometrics techniques, focussing in on particular population subgroups - all of these are valuable contributions. Each person is unique, so if you can bring your own perspective to a problem, you might see it in a new way, come up with a slightly different angle. You will have the satisfaction of building an idea, creating something new.
As the great philosopher Calvin once said:
It's a magical world, Hobbes, ol' buddy... Let's go exploring...
Addendum: I now realize that many of the topics I write about are things that make me mad, or things that I think are stupid. Gary Becker's observations about women who want to specialize in the market market being "deviant" enraged me as an undergrad, and spurred my work on economics of the household. Getting angry about Canada's lack of support for families with children prompted my work on the tax treatment of the family. Enthusiasm fades. Interest fades. But anger will keep a fire in your belly through many a long day at the keyboard.
So writing down a list of things that make you angry, things that you think are stupid, or things that you are worried about is a good way to come up with research topics.
This advice would have been helpful 20 years ago.........
Posted by: Rob | July 26, 2011 at 09:53 AM
Fran, I will probably distribute this widely to our students - and I suspect many others will as well. Another good piece; thanks.
Posted by: Linda | July 26, 2011 at 11:03 AM
I can't supply better advice than what Frances has given, so I'm just going to list some topics from my favorite area, that I would like to see covered by budding economists. I believe they all meet the two criteria. I'm guessing that your students can frame the problems in a more nuanced way.
1. Value-based payment (or purchasing, VBP) in health care. Option 1: Does it drive improvement in medical care? Option 2: Is it cost-effective to implement, even if it works? (My opinion: no, and no.)
2. Labor substitution in health care: Option 1: Nurse practitioners can supply many of the functions currently carried out by family docs, and thus earn more money than even a senior RN. Why do so few nurses go into it? Option 2: In jurisdictions where they exist, nurse practitioners and physician assistants (or physician associates) have virtually identical scopes of practice. How should an employer decide which type of job to fund? What are the total costs involved?
3. Direct-to-consumer advertising of pharmaceuticals. There is a knee-jerk fear that this will cause (or has caused) more unnecessary drug consumption. Is this concern justified?
4. Delisting in public health insurance. There are many examples in Canada since the 90s of provinces removing certain procedures from the list of insured items. Evaluate the impact of the change. To what extent did delisting change the price?
5. Anything on antibiotics: Why is the incentive to discover a new molecular entity so low? If the market is so huge, why is there so little private sector research on it? Given the risk to inpatients and the potential future savings, should health systems (hospitals) co-fund research into an MRSA antibiotic?
Clearly, I could go on, but I think these are pretty compelling subjects and hope someone will take an interest in them.
Posted by: Shangwen | July 26, 2011 at 11:27 AM
There actually is a data set that contains information on both the political donations tax credit and income.
It is Statscan's Longitudinal Administrative Data (LAD) database. It is a longitudinal database that traces back to 1982 and contains most variables from your federal tax declaration.
There is no external access, but universities and governments have had tables/regressions done on a cost recovery basis.
Here's the dictionnary:
http://www.statcan.gc.ca/pub/12-585-x/12-585-x2006000-eng.pdf
Posted by: SimonC | July 26, 2011 at 11:51 AM
and yes, I believe this database could be used a lot more.. :)
Posted by: SimonC | July 26, 2011 at 11:58 AM
Linda - I hope it helps them. If you type how to find a topic for an economics research essay into google the top hit is a custom essay-writing service ($10 a page! No plagiarism guarantee!).
Posted by: Frances Woolley | July 26, 2011 at 12:09 PM
SimonC - Do you know for sure that the LAD actually breaks out political contributions from other donations? The CRA Taxation Statistics don't, and I thought the variable definitions were similar in the two. I clicked on the link you included, but it goes to a page that says archived, and the other LAD documentation just bounces back to that archived link.
Unfortunately, useful as the LAD is, the costs (time, money, etc) of using it are just too high for most researchers outside of Statscan. I had a conversation the other day with someone who had a great research topic that could only be answered using the LAD - but the person has family commitments, lives a fair ways from Ottawa, and couldn't afford to pay for the dozens of runs that a serious piece of applied economics would take. : "I just can't get up to Ottawa to use the LAD - do you have any other suggestions?" "How about talking to Ross Finnie - he might be willing to work with you on it" "Yes, other people have suggested that..." But Ross's time is constrained too.
Perhaps "liberate the LAD" would be a good topic for a blog post.
Shangwen - do you know of datasets that would help people evaluate the impact of delisting - e.g. are there datasets that describe the frequency with which a procedure is carried out in different places?
There are lots of fascinating research topics that can be done on specific occupations - nursing is a nice one because it's clearly delineated, and there are lots of different data sets that could be used to identify nurses.
Posted by: Frances Woolley | July 26, 2011 at 12:32 PM
Frances: I agree that the LAD is not used nearly enough for it's potential and it's "liberation" would stimulate a lot of work. In a similar fashion, a truly public and free "public use microdata file" for the census would be great. I wonder how many persons use american data on ipums.org just because they dont have access to Canadian census data.
I'm not sure what doesnt work with the link, when I copy paste it in my internet explorer it works fine. I cannot guarantee that it actually *is* in the LAD as I no longer work there. It does appear to be:
Political contributions, gross federal (1982 to present)
Definition: Gross federal political contributions refer to the total amount of a taxfiler's
political contributions made to a registered federal political party, or to an officially
nominated candidate for election to the House of Commons (whether or not they
belong to a registered political party). A portion of this contribution is deductible from
total Taxable income.
Derived from: Line 409 (1984 to present), Line 64 (1982 to 1983)
LAD: FPLCG I, F, P
Political contributions, provincial (1982 to1997)
Definition: The Provincial political contributions field contains the amount of the
taxfiler's contributions to a recognized provincial/territorial political party, constituency
association, or candidate. Only Newfoundland and Saskatchewan do not offer this
credit for political contributions in their provinces. This field was discontinued in 1997.
Derived from: Provincial tax credit forms
LAD: PPLC_ I, F, P
Political contribution tax credit, provincial (1999 to present)
Definition: The provincial political contribution tax credit may be claimed if the taxfiler
made a contribution to a provincial political organization during the tax year. All
provinces except Saskatchewan offer political contribution tax credits. This credit is
non-refundable and is deducted from a taxfiler's income taxes payable.
The amounts and the types of contributions that are allowed to be claimed vary by
province (these amounts stayed the same from 1988 to 1996):
[...]
Derived from: Provincial tax credit forms T1C (1999 to present).
LAD: PPLCC I, F, P
Posted by: SimonC | July 26, 2011 at 01:09 PM
SimonC - perhaps it was a browser issue, then, I'm using Safari. I've corrected the post, perhaps someone will be inspired to look at this with LAD, or pay StatsCan do to the runs. Thanks for pointing this out, Frances
Posted by: Frances Woolley | July 26, 2011 at 01:18 PM
I forgot the most important in my rush to promote the LAD: Once again, great post and thanks for it. I'm on the lookout for ideas and it was most interesting the read this.
Cheers!
Posted by: SimonC | July 26, 2011 at 02:20 PM
This piece is timely! I'm struggling to find a topic for my PhD applications.
I do worry about limiting topics to those which have a testable hypotheses. Cannot a student simply explore a topic of interest, without necessarily testing a limited set of variables?
It seems that economics is still plagued by the dangers of "small thinking," which Galbraith did such a good job of critiquing. Take, for example, University of California economists who examined citrus and prune prices. “These were not great men but they did useful work and were highly respected by the prune growers and citrus cooperatives,” wrote Galbraith. “They would have been less useful if exposed to more cosmic questions or even diversified to artichokes.”
I think, particularly as young students, they should be invited to explore these cosmic questions without the confines of testable hypotheses. Otherwise, I simply worry that they may not diversify, even to the study of artichoke prices.
Posted by: Matthew Brett | July 26, 2011 at 02:53 PM
Matthew, allow me to offer exactly the opposite opinion: Economists should seek to answer questions we can answer, we should think small in that sense. A corollary is that we should largely limit attention to hypotheses for which we can provide at least some evidence. Galbraith added precisely nothing to economic thought. Keynes did, and his advice differs sharply from Galbraith's: "If economists could manage to get themselves thought of as humble, competent people on a level with dentists, that would be splendid."
Due to problems such as those Frances discusses, the problems we face as economists are often formidable. The world refuses to divulge to us how it works, instead coyly offering the occasional hint. We should capitalize on those hints, but not pretend to offer answers when we really cannot. In an econometric context Guido Imbens recently offered a formalized notion of this position in [url=http://www.nber.org/papers/w14896.pdf]this paper[/url].
On the topic of finding topics for research essays, here's my advice to students: read papers, read papers, and then read some more papers. Choose a topic in which you have a genuine intellectual curiosity rather than a topic you think might look good to employers, or is easy, or any other motivation. And don't choose a topic which requires you to access an RDC, unless we're talking about a doctoral thesis.
Posted by: Chris Auld | July 26, 2011 at 05:52 PM
Also, we should strive to learn how to correctly embed links when posting on Typepad.
Posted by: Chris Auld | July 26, 2011 at 05:57 PM
Matthew: "I do worry about limiting topics to those which have a testable hypotheses. Cannot a student simply explore a topic of interest, without necessarily testing a limited set of variables?"
Yes, definitely, begin with a topic of interest. And, yes, there is room in economics (or at least a little room) for methodological diversity - take a look, for example, at Daniel (?) Hausman's article on economic methodology in Journal of Economic Perspectives. ("Economic methodology in a nutshell" is the title).
But avoid self-indulgence: you're writing for others, not for yourself. Always bear the reader in mind - why should he or she care?
Chris: "here's my advice to students: read papers"
I disagree. By the time students have got to fourth year, or doctoral studies, they've read lots of papers. There's a real danger that reading too many papers will just give a student the impression that all the good ideas are taken. The challenge is creating something new, something of one's own -and at some point you just have to dive in and start writing.
Writing is thinking: the sooner you start, the better.
Posted by: Frances Woolley | July 26, 2011 at 08:24 PM
Simply in the spirit of discussion, and because I am enjoying this thread, I would echo back to Bertrand Russell, the great logician, mathematician, philosopher, etc. etc.
He has an excellent short essay titled "'Useless' Knowledge," in which he suggests that we need more of it! First published in 1935, he wrote that "knowledge, everywhere, is coming to be regarded not as a good in itself, or as a means of creating a broad and humane outlook on life in general, but merely an ingredient in technical skill. This is part of the greater integration of society which has been brought about by scientific technique and military necessity" (1986: 29-30). I believe that much of the social sciences are of this later variety. Concerns have become too instrumental, and there is near-constant talk of "policy-focused theory." I worry about this kind of technocratic thinking, and perhaps what is needed is less of an emphasis on scientific technique and more of a philosophical disposition.
Posted by: Matthew Brett | July 26, 2011 at 11:02 PM
I always feel I cheated a bit to get my economics degree because my senior seminar paper involved almost no mathematics. Matthew, you might approve: The topic was comparing critical perspectives on participatory economics. Fortunately this weekend I talked to an economist who was more math-minded and feels he cheated in the opposite direction. We cancel each other out.
Posted by: Donald Hughes | July 27, 2011 at 01:47 AM
Matthew: "He has an excellent short essay titled "'Useless' Knowledge," " I found part of the essay on google books - he does write so beautifully, and it sounds so convincing.
I share his concerns with technocratic education - what could be more useless than teaching grade 7 students how to use the latest word processing software - it will be obsolete by the time they graduate from high school. Learning Latin, on the other hand, could possibly give a lasting understanding of the English language.
But bear in mind - what with being a younger brother, and death duties, and multiple marriages - Russell was supporting himself in part by his pen.
Russell was always writing for a purpose - to convince someone of something, to entertain, to educate, to persuade, to prove a point.
Anyone is free to contemplate cosmic questions: "Why is the sky blue?" Actually, approached with appropriate knowledge of physics etc., "why is the sky blue" is a fascinating question. But unless you know enough physics to come up an informative answer to "why is the sky blue" there's not much point in writing an essay on the topic.
Better stick to "why is toilet bowl cleaner blue?" instead. Anything, as long as you have the power to say something about the topic, either through rigorous inductive logical reasoning, or by bringing some kind of empirical evidence (quantitative, qualitative, administrative, whatever) to bear on the subject.
Posted by: Frances Woolley | July 27, 2011 at 08:24 AM
A few comments:
You said Frances: ''I try not to worry about endogeneity for the same reason that I try not to worry about cancer: it's pervasive, and there's only so much you can do about it. Sure, deal with it if you can, but accept that you might not be able to beat it.''
As a labour economist, I dont like this sentense at all for obvious reason. :)
In labour, it is very hard to publish well without taking care of endogeneity....
Reading or Reading abstract of 5 years of top field papers and 5 years of paper in your field in top 5 is probably the best advise I got when in grad school. In Labor, I read/browse JoLE, JHR and QJE and AER plus some labour econ and CJE and nber working papers. Now I would also suggest reading AEJS... I learn what was a good paper and what is a good question. I actually found this way my 3 topics very fast and made more than 3 papers while in grad school... I ended up doing them and now they got published in similar ranked journal....
Spend time learning: who is good in your field? what are the good journals? Where the field is going....
I think reading what is important in your field is crucial... Another way is when you find an author you like: read/browse everything he did...
Find what is hot in your field: Labour: RD right now...
DD and IV dont publish as well for obvisous reasons now...
If your empirical strategy is not good, it won't publish well. Trust me, I know unfortunately... :)
Another way to find a question is to find something you can measure well. So you can start from looking at available data set or discontinuity or natural experiment....
I did my best paper so far this way...
you don't have data? Can you create it from field experiment or lab??? This is a new popular empirical tool...
Your ideas as been done? Good, it means you are on the right track... Can you build on this idea? Find an interesting (and ambitious enough) twist? If you can you have for sure a good paper...
my 2 cents...
Posted by: John | July 27, 2011 at 08:39 AM
John - "Find what is hot in your field: Labour: RD right now...
DD and IV dont publish as well for obvisous reasons now..."
I'm guessing that RD=regression discontinuity, DD=difference in difference, IV=instrumental variables.
What you say is good advice for someone aiming to publish in a top journal.
Unfortunately there aren't that many "natural experiments" that offer opportunities to identify causality. Economists are academic vultures circling around hoping to feed off calamity and disaster: "university tuition is going from 3,000 pounds to 9,000 pounds? Excellent! What a wonderful opportunity for a natural experiment!!!".
There is no way I can find enough problems that can be approached using RD or DD or *sensible* IV strategies for 40 or 50 or 70 undergrad honours essays this year. And next year. And the year after. So sometimes you just have to hold your nose and say "I've found this relationship, it's interesting, but it may or may not be causal."
I have to say spending some time in Exeter at this year's economic psychology/behavioural economics conference was a eye-opening experience. (You're expecting me to believe that the behaviour of Harvard undergrads is generalizable to the population as a whole? Really?) There is a massive variation in the quality of lab/field experiments out there.
Posted by: Frances Woolley | July 27, 2011 at 09:00 AM
Great fun. Thanks for this conversation! Will stay tuned for future posts.
Posted by: Matthew Brett | July 27, 2011 at 09:48 AM
Frances you said: There is no way I can find enough problems that can be approached using RD or DD or *sensible* IV strategies for 40 or 50 or 70 undergrad honours essays this year. And next year. And the year after. So sometimes you just have to hold your nose and say "I've found this relationship, it's interesting, but it may or may not be causal."
I thought it was a small honor class, my bad... I agree but I think your best student should try to aim at using the best econometrics out there... especially if the ones who aim at going to grad school... They could have a great advantage...
I agree, lab experiments are controversial... Some are good though. I prefer field experiments but most are expensive... Peter Kuhn and a coauthor has an new interesting paper about lab experiment in labor econ....
Posted by: John | July 27, 2011 at 10:05 AM
John, it's not so big, but I'm teaching it twice, so 40=2*20, 50=2*25 etc.
I've given them: Joshua D. Angrist, Alan B. Krueger, Chapter 23 Empirical strategies in labor economics, In: Orley C. Ashenfelter and David Card, Editor(s), Handbook of Labor Economics, Elsevier, 1999, Volume 3, Part 1.
So far that's the best intro I've found to the general problem of making inferences from data - it sets out the problem, and then goes through the various approaches to establishing causality, RD, DD, IV etc. Do you have a more recent reference?
Posted by: Frances Woolley | July 27, 2011 at 11:43 AM
I think those two can be usefull:
Mostly harmless econometrics from angrist & Pischke, but it might be a little advanced for undergrads. Still it seems to be used at some universities for senior level undergrads...
I think a better one might be Thomas Lemieux's master degree notes. I think it is appropriate to advanced undergrad and Thomas has put the stata codes in his notes for every section... http://faculty.arts.ubc.ca/tlemieux/econ594/594course.htm
Posted by: John | July 27, 2011 at 12:18 PM
Tony Lawson on non-mathematical economics:
http://ineteconomics.org/video/conference-kings/really-reorienting-modern-economics-tony-lawson
I think highly relevant to this post!
m
Posted by: Matthew Brett | July 27, 2011 at 05:17 PM
Matthew - I didn't have the patience to watch a video, but this sets out Tony Lawson's position, http://www.paecon.net/PAEReview/issue50/Lawson50.pdf.
Lawson is critical of the emphasis on deductive reasoning in much mainstream economics. In some ways, he has a point - solving problems by assuming you have a can-opener only gets you so far. But I don't really understand what he sees as being the alternative to 'normal science' economics, that is, the orthodox mainstream variety of econ that's taught in most North American schools. Last time I heard him speak there was a long discussion, IIRC, on the nature of windows. I didn't really get it - that doesn't mean it wasn't brilliant, just that I didn't get the point.
In fact economics is changing, and become in many ways much more open to different approaches. Economic psychology takes a more inductive approach, as opposed to a deductive one, and isn't nearly as wedded to the assumptions of rationality/efficiency/etc.
If I was looking to challenge economics-as-usual, I'd go and sit in on some social psychology or sociology or psychology or evolution or biology or physics classes. The margins, the boundaries where things meet - river banks, tidal zones, the forest's edge - are some of the richest and diverse systems.
Posted by: Frances Woolley | July 27, 2011 at 09:01 PM
"He who refuses to do arithmetic is doomed to speak nonsense." --- J. McCarthy.
Tony Lawson's attack on math is ridiculous, his hand-waving dismissal of all of econometrics is so willfully ignorant that it amounts to nothing more than naked anti-intellectualism. It baffles me that anyone, even the self-proclaimed "heterodox," are willing to countenance this crap. I can do no better than quote Herb Gintis, who is a competent critic of the mainstream:
Another persistent theme in these pages [Real World Economics: The Post-Autistic Economics Reader---CA]is that the core micro courses in graduate schools should use less math, since all the high-tech math of microeconomic theory is worthless. Why is it worthless? Because, say the post-autistics, the super high-tech economics journals produce a lot of fancy models with no real-world relevance. The fact is that most economists are not economic theorists, and could not understand an Econometrica article if they wanted to (which they do not). However, the level of mathematics used in the everyday life is orders of magnitude higher than that of other behavioral disciplines, and one cannot write a cogent analysis of an economic issue without being able to write and analyze simple mathematical models. Economists learn how to do this in the first three years of graduate school, where almost all course are applied micro of one kind or another. This is as it should be. I think the American Economic Review and the Journal of Economic Perspective are examples of journals that thrive on high-level microeconomic model building and testing of a sort that every economists should be capable of generating and understanding. If there is some systematic alternative to microeconomic theory, I would love to see it, but I doubt that it would be less math-intensive that the standard fare of the AER.
Posted by: Chris Auld | July 28, 2011 at 12:20 AM
Frances:
"I share his concerns with technocratic education - what could be more useless than teaching grade 7 students how to use the latest word processing software - it will be obsolete by the time they graduate from high school. Learning Latin, on the other hand, could possibly give a lasting understanding of the English language."
Grade 7 students ( at least my nephews) use word-processing software. We are supposed to use cly tablets till there is adefintive version? Whatever the subject, teach what is current and try to be a little prospective. The future will come soon enough and when they will be stuck with learning Word 55.89, they'll get the valuable lesson that they can't sit on their laurels.
I learned Latin (and classical Greek) during my Cours classique in the late 60's. Wonderful intellectual exercise which helped not a bit in understanding neither French nor English ( not even later with Spanish and even Italian.That's why they are called different languages)
The point, apart from keeping young boys busy and out of juvie) was to get an intellectual exercise, far more from history than the language itself. Kurdish folk dancing might have been more useful by opening a subject even more distant than our own ancestors civilisation.
In fact, most of us never use 90% of our undergraduate courses, ( History of economic thought: Cantillon's view of agricultural exports as bad because it is exporting soil...I refer to that every day while discussing the causes of the Little Depression...)
Posted by: Jacques René Giguère | July 28, 2011 at 01:20 AM