[Humanist] 28.204 toward a better curriculum

Humanist Discussion Group willard.mccarty at mccarty.org.uk
Wed Jul 16 19:11:43 CEST 2014


                 Humanist Discussion Group, Vol. 28, No. 204.
            Department of Digital Humanities, King's College London
                       www.digitalhumanities.org/humanist
                Submit to: humanist at lists.digitalhumanities.org

  [1]   From:    "Murphy, Orla" <o.murphy at ucc.ie>                          (10)
        Subject: RE:  28.200 toward a better curriculum?

  [2]   From:    "Turnator, Ece G" <e.turnator at austin.utexas.edu>          (11)
        Subject: RE:  28.200 toward a better curriculum?

  [3]   From:    Mark LeBlanc <leblanc_mark at wheatoncollege.edu>            (93)
        Subject: Re:  28.200 toward a better curriculum?

  [4]   From:    Willard McCarty <willard.mccarty at mccarty.org.uk>          (36)
        Subject: essential topics


--[1]------------------------------------------------------------------------
        Date: Tue, 15 Jul 2014 15:12:53 +0000
        From: "Murphy, Orla" <o.murphy at ucc.ie>
        Subject: RE:  28.200 toward a better curriculum?
        In-Reply-To: <20140715140911.32BDD643A at digitalhumanities.org>


Dear List,

After years of testing the waters at undergraduate and postgraduate levels teaching DH - there's a  first iteration distillation in our new BA program at University College Cork http://www.ucc.ie/en/ck118/ working with colleagues in Computer Science.

This first iteration will see students on September 8th this year.  We are since in conversation with colleagues in Geography, and History and perhaps in the future the Law faculty too, as ideally a Law strand on IP not just in terms of texts but in terms of students' innovation may be necessary if colleagues were agreed. 

We are hopeful that this work will be formative and generative across the college, and the university.  

Assessment - usually an open portfolio of work equivalent to 4,000 words (in a traditional essay form).  Online engagement and contribution is encouraged - innovation in terms of the type of digital artefacts produced is welcome, so network analysis, interactive documentary, database, website or animation are all welcome.  (No Java yet ...)

Best of luck with the endeavour!

Orla 

On Tue, Jul 15, 2014 at 10:09 AM, Humanist Discussion Group <willard.mccarty at mccarty.org.uk> wrote:

>                  Humanist Discussion Group, Vol. 28, No. 200.
>             Department of Digital Humanities, King's College London
>                        www.digitalhumanities.org/humanist
>                 Submit to: humanist at lists.digitalhumanities.org
>
>
>
>         Date: Tue, 15 Jul 2014 12:21:51 +0200
>         From: Tara Andrews <chrysaphi at gmail.com>
>         Subject: Questions toward a better DH curriculum
>
>
> Dear Humanist,
>
> I write to pick your collective brains a little on the subject of digital
> humanities curriculum. I am in the process of setting up a teaching program
> in DH at the university of Bern, catering to a mix of undergraduates,
> masters' students, and Ph.D. candidates. At the moment they all come from
> various departments in the humanities, but I hope to attract some computer
> scientists in the near future as well. As yet there is no degree program,
> and my mission is to serve students throughout the humanities more or less
> equally - classes should hold relevance for musicologists and art
> historians just as they do for philologists and linguists.
>
> After a year of trying things out with mixed results, I have two questions
> for those who have taught, or those who have thought about teaching,
> general courses on digital humanities:
>
> 1) What do you expect the students to have learned, and how do you assess
> it? I'm equally interested in answers for theory-based and practice-based
> courses, though the latter strike me as more of a practical problem - how
> good can I expect a student to get, over the course of a term, in a skill
> like XML or Javascript? And if I shy away from teaching actual programming,
> what should I expect them to be good at after 12 weeks of experimentation
> with tools like Neatline, Oxygen, Gephi, or what have you?
>
> 2) Formalisation and modelling in the humanities is turning into something
> of a hobby horse of mine - I think this is possibly the most important
> thing that DH could teach, and ideally I would like to devote an entire
> class to it. I have a couple of nebulous ideas of my own, but I ask here
> for good old brainstorming help - if you have taught, or would teach, such
> a class, what would you teach and what toolkits (if any) would you use?
> And, just because I sometimes like stirring up a hornet's nest, I'll impose
> an additional constraint - what would you teach *apart from XML/TEI*?
>
> Many thanks in advance for answers, advice, experience, etc.!
>
> Best wishes,
> -tara
>
> --
> Prof. Dr. Tara L Andrews
> Digital Humanities, Universität Bern
> http://www.dh.unibe.ch/


--[2]------------------------------------------------------------------------
        Date: Tue, 15 Jul 2014 16:38:37 +0000
        From: "Turnator, Ece G" <e.turnator at austin.utexas.edu>
        Subject: RE:  28.200 toward a better curriculum?
        In-Reply-To: <20140715140911.32BDD643A at digitalhumanities.org>


Hi Tara,

I am interested in finding out answers to exactly the same questions you pose. What else *must* you teach in a humanities concentration/minor/major other than TEI (and do we take TEI as a given)? I got silence in return so far... I had looked at different programs-how they are set up. Have a google doc to share if you are interested. 

Ideally it would be great to set up an uber-mooc like system where experts who happen to be good teachers teach a specific topic for those who want to specialize in certain tools, because no single institution can accommodate it all. Then we circle back and ask the same question, " yes but what are the essentials you would want a student new to DH get out of it?".

I would be interested in teaming up with you if you have any ideas about how to get a few good answers to that question.

All the best,
Ece (pronounced A.J.)
CLIR-Mellon Post-Doc Fellow at UT Austin,
Dept of English and UT Libraries


--[3]------------------------------------------------------------------------
        Date: Tue, 15 Jul 2014 13:24:43 -0400
        From: Mark LeBlanc <leblanc_mark at wheatoncollege.edu>
        Subject: Re:  28.200 toward a better curriculum?
        In-Reply-To: <20140715140911.32BDD643A at digitalhumanities.org>


tara:

>  what would you teach *apart from XML/TEI*?

two suggestions (where i feel i am making a small contribution to what is
now a growing DH community here):

(0) i teach programming using language-based examples (Python); i assign
codeAcademy HTML/CSS and Python modules to insist on practice (and i don't
apologize for sending my ("in class") students to such sites and MOOCs);
students work on problems that include: "Does Tolkein use words like 'tall'
near elf names?" and how to build a tool for "Reading Poetry Backwards"; ...
with a healthy mix of regular expressions sprinkled in;

http://cs.wheatoncollege.edu/~mleblanc/131/syllabusSpring2014.pdf
http://wheatoncollege.edu/lexomics/computing-poets/  [assignments and source
available]

(i'm not screaming for teaching programming; it is just what i do well and
students value from the experiences; some go on to do more; the experience
with computational thinking of this sort makes for a stronger DH team member
later, whether she continues to program or not);

and/or

(1) students use our Lexos (http://lexos.wheatoncollege.edu) and/or other
tools to design and run small explorations of texts and corpora of interest
to them; independent of (and even without) any programming, students value
from an exposure to some of the decisions required for computational text
analysis including: encoding, scrubbing and cutting texts, stopwords,
lemmatization, character- and word- Ngram counting, tf-idf weighting, and
introductory visualizations (e.g., word and topic clouds and rolling window
analyses), cluster analyses and other unsupervised methods of comparison. 
Setting up and running experiments is the focus in all of this, no matter
the result (negative experiments are ok, welcomed, and expected ... until
the next one).


-----------------------------------------------------------------------------
Mark D. LeBlanc, Ph.D.
Meneely Professor of Computer Science
Wheaton College, Norton, MA 02766
508.286.3970

http://cs.wheatoncollege.edu/mleblanc



--[4]------------------------------------------------------------------------
        Date: Tue, 15 Jul 2014 11:17:32 -0700
        From: Willard McCarty <willard.mccarty at mccarty.org.uk>
        Subject: essential topics
        In-Reply-To: <20140715140911.32BDD643A at digitalhumanities.org>


In answer to Tara's question about a curriculum, I'd suggest looking beyond
available technologies to the cognitive struggle between actual or
conceivable tools and techniques on the one hand and on the other our
objects of study in whatever media we find them. 

In regards to text-analytics, for example, I would place TEI way down the
line, to be considered as a special case after the fundamental problems of
marking up a text to any standard were encountered and discussed. That
encounter having shown that for interpretative questions markup fails in
significant ways, I'd move to other approaches, such as basic concordancing,
and from that to statistical analytics of a simple kind. All the while I'd
be orbiting the massive question of interpretation: what happens when a
scholar interprets a text and so on. In my view we dwell far too much on the
kit at hand, on training people in the skills of using this or that
invention. No wonder many think our scholarly relation to the humanities
dubious. We never get around to problems recognizable as belonging to the
interpretative disciplines because we are always working to provide the
means to interpret as it has been presented to us. We train others to use
the tools made to fit scholarly practice as closely as possible. These tools
then having delivered the raw material for scholarship, it then happens
elsewhere by other means.

Alternatively one could begin with experiments in programming with Python,
Perl, R etc, as others have suggested, building some very simple, basic
tools to approximate models of scholarly interpretation. Trying them out
would immediately run into the hermeneutical question: is this how we as
scholars understand a text, a painting, a musical performance, a dance and
so on? Ultimately I think it would be a matter of indifference whether you
approached the subject by the former path, using off-the-shelf tools, or by
the latter one -- as long as you kept the focus on the cognitive struggle.
But I would in any case be setting digital analytics alongside unassisted
reading/viewing/listening/moving and looking for the differences.

Yours,
WM

--
Willard McCarty (www.mccarty.org.uk/), Professor, Department of Digital
Humanities, King's College London, and Research Group in Digital
Humanities, University of Western Sydney




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