Monthly Archives: junio, 2011

The times, they are a-changin’ (2/3)

junio 26th, 2011 Posted by aside to camera, blog, community, internet No Comment yet

In the first post on this topic, I wrote that scholarly e-journals are definitely better than their printed counterparts in many respects. They are, however, just an improvement on an existing research resource. The same is often said about digital libraries such as ACM, ISI Web of Knowledge and Google Scholar, although they should not be seen as catalogues or 

bibliographical databases, such as BITRA, but as sources for documents. These new libraries are actually turning good old packed and dusty shelves into computer directories cluttered with large numbers of pdf documents scholars need to manage.
 
Enter Mendeley, a user-friendly proprietary reference-and-pdf manager that will make your work much easier. This all-in-one program has too many features to explain them here, just have a look! Now this feels like something really new. On the one hand, boring, mechanical tasks such as maintaining your own library records and tracking and typing your references on a paper have now become nearly automated. On the other one, new needs such as pdf tagging and grouping are finally easier to perform, and features such as one-click document download and full-text searches might in time even change the way you gather, use, and present information. Now we are getting closer to scholarship 2.0. but there is even more to Mendeley than that, through social networking features.

Social networking

Social networking is not new to scholars, thanks to websites such as Connotea, Academia.edu and MyExperiment. And there is also Zotero, which has many of Mendeley’s features. in fact, Zotero and CiteULike may be better suited for the humanitites and the social sciences than Mendeley is (which is probably why Mendeley can be synchronized with both Zotero and CiteULike accounts). You may just silently follow the work of your colleagues simply by adding them to your contact list, very much like Google Alerts do (Mac users should also check MyPeers). One more step: Collaborative filtering helps you reduce the information overload while it expands your sources of knowledge (e.g. Logvynovskiy & Dastbaz 2010). In brief, rather than a sort of Facebook for scholars, it is more like a last.fm for researchers (Henning & Reichert 2008).
 
Mendeley also lets users establish public, open research groups, such as Translation Studies and Cognitive Translatology, and also closed, smaller ones, such as PETRA’s. Public groups let users share reading lists and closed groups let them share the documents and also collaboratively tag and annotate them. Thus, Mendeley is an invaluable tool to help us build an online scientific community for cognitive translatology (and other areas of Translation Studies, of course). However, there are some differences worth taking into account between Mendeley and Academia.edu. In Academia.edu, linking to colleagues is just a one-way step, whereby users may silently follow somebody else's work. In Mendeley, linking attempts must be accepted by adressees. This subtle difference provides for some embarrasing situations in Mendeley which in Academia.edu are simply out of question. My recommendation is to use both networks. Mendeley is better suited for smaller, topic-centered networks and Academia.edu is great for larger, interdisciplinary networks.
A community of practice
Beyond the hype of crowdsourcing, collective intelligence (but see Williams et al. 2010) and similar concepts, the web 2.0 (the read and write web) really supports easier and more varied ways to communicate and cooperate with colleagues. Sure, the new possibilities also have a dark side, such as the danger of trading scientific thoroughness for the wisdom of the crowds (check my next posts on cognitive biases). But before we dismiss scholarly social networking as a bummer, we might want to try some possibilities.Perhaps online scientific community is a little pompous; I prefer to think of it as a community of practice instead (see also Gannon-Leary & Fontainha 2007). Whatever the name, I sure hope that looking at a screen will never substitute face-to-face interaction. But there are often situations in which you simply cannot join your peers (didn’t get it? Look here). A community of practice for cognitive translatology (or TPR) is already slowly but steadily growing. We may arbitrarily date its start in the now extinct European network EXPERTISE (expert probing through empirical research on translation processes). Hubs or poles for this community are at least the Translog and CRITT nets, the TransPro database, TransComp seminars on translation process research, PACTE’s network, and even this blog, which should soon welcome many researchers to a neighborhood with street names such as cognitive translatology, translation process research, psycholinguistic approaches to translation and interpreting, bilingualism, etc.
 
Cloud computing and really smart smartphones are going to foster the development of scholarly communities of practice a little bit further. We should not drag our feet and we should not rush into it. Not because most of us are digital immigrants, but simply because we are witnessing the dawn of a new era and it is not clear which changes are just transitory, which ones are here to stay, and which ones are just one more step from a longer way. We just need to keep our research standards as high as we can, while we interiorize change and welcome innovation ‘cause the times, they are a-changin'.
 
 
References
 
Gannon-leary, Pat & Elsa Fontainha. 2007. Communities of practice and virtual learning communities: Benefits, barriers and success factors. @ Elearning Papers 5. ISSN 1887-1542.
 
Henning, Victor & Jan Reichelt. 2008. Mendeley - A last.fm for research? @ Proceedings of IEEE 4th International Conference on Escience, pp. 327–328. DOI 10.1109/escience.2008.128.
 
Logvynovskiy, Alex & Mohammad Dastbaz. 2010. Bibliography mapping with semantic social bookmarks. @ Proceedings of IEEE 5th Conf. of Intelligent Systems, pp. 7–12.
 

Williams Woolley, Anita, Christopher F. Chabris, Alex Pentland, Nada Hashmi & Thomas W. Malone. 2010. Evidence for a collective intelligence factor in the performance of human groups. @ Science 330/6004: 686-688. DOI 10.1126/science.1193147

 

When you think you got it

junio 24th, 2011 Posted by blog, data analysis, empirical research, empirical-inductive approach, The sorcerer's apprentice, theoretical-deductive approach No Comment yet

So you have been preparing the pilot study for your translation process research project with passion: You have been weighing the pros and cons of every single method and tool of data collection—you just want the best one, of course. You have been choosing the source texts meticulously, screening them from many different angles. You have been defining your experimental subjects and recruiting people, some of whom you finally managed to convince to participate in the test.

Then came the D-day: You carried out the experiment, or, properly speaking, you let your subjects carry it out—the subjects patiently translated with Translog (http://www.translog.dk); they also filled out some questionnaires. And, afterwards, evaluators had a look at their translations.

This is the moment when you start feeling that you made it, that the first big step is done, your first tentative data collected; and it’s true, but it’s also true that there is a much steeper step awaiting you now:

The analysis of data

(“Night on Bald Mountain” might do as a soundtrack effect here).

You may feel some kind of dizziness or trepidation in the face of the amount of data you have collected. So, now what? What’s next?

First of all: Stay calm and don’t despair!

There are two ways out of this trial:

 

  1. You could have a look at the materials you collected, those based on a theory you have been working out before. The theory offers you one or various perspectives onto your data (theoretical-deductive approach).

Or else

  1. You could let your data speak first and let the facts emerge and grow, and adapt your interpretation and your theory to the outcome (empirical-inductive approach).

If you were looking for something well defined, if it was an experimental setting, if you just wanted to (dis)prove some theory or theoretical point, if you —or your dissertation director— are not willing (!!) to modify the theory, then option 1 seems to better fit your needs. If you are doing descriptive research, if everything is foggy and you don’t trust the rosy & complex notions you have been using, then option 2 might get you further down the way.

The problem is, your research project may fall somehow in between, and anyway data collected are simply overwhelmingly rich. So, before choosing one way or the other, you may want to ask yourself the following questions (if you haven’t done so already):

What was I looking for?

Which elements in the data are useful for my purpose? Which are not?

How could I check what I wanted to see/know/measure?

When you have found the answers, start selecting your material. Focus on the data you really need for your study aim(s) and leave those aside you don’t need for this project; maybe later you can use them in another project, so don’t think they are worthless. Do NOT dispose of anything. Umberto Eco said that one of the main problems in writing a dissertation is chopping off side branches, I mean, mmm, reducing the scope of your goals to a size that can be managed in a few years. The times are over when a PhD research project was the crown of a whole career, welcome are now dissertations that let you prove you can do high quality research.

In any case, in translation process research you nearly must resort to triangulation, to cross-referencing qualitative and quantitative data, both to improve intersubjective agreement within your scientific community and to avoid the distortion effects of each single method.

So just take a deep breath now and keep going. Just do not go into the light. Research weather is always foggy.

 

Further reading

Shuttleworth, M. (2009). What is the scientific method? URL: http://www.experiment-resources.com/what-is-the-scientific-method.html
Wang, J. & Khosravi Sereshki, H. (2010). How to implement ITIL successfully? Jönköping. Chapter 2.2. URL: http://www.scribd.com/doc/52864057/13/Approaches-of-Deductive-Inductive-and-Abductive

petraTAG: new release

junio 17th, 2011 Posted by blog No Comment yet

petraTAG has evolved from a simple demo application and now includes some basic concordancing functionality. With the new release, it is possible to select a set of text files, tag them and perform several kinds of searches. One of the most advanced features is the ability to automatically obtain the distribution of words according to the criteria specified by the user. For instance, you can search all the instances of the group noun-adjective and see instantly which adjectives 

are most frequently used with which nouns, as the following picture shows:

petraTAG is being developed in Java on Ubuntu Linux, and it runs in every platform with a suitable Java Machine, such as Android, Windows or Mac. petraTAG is provided with an extensive dictionary of Spanish words which covers +200,000 different words. While dictionaries for other languages are not available currently, the system of stem+suffixes enables a fast creation of dictionary for other languages. Moreover, as it is a totally free and open-source tool, it is specially suited for using it in education or as a starting point for developing advanced tools.

More information is available on the online help site for this tool or in the sourceforge web site. As always, we are happy to receive feedback or suggestions about this project.

 

by J. Perea

Crossing Manuel

junio 11th, 2011 Posted by blog No Comment yet

petranoncomment02

Training on Research

junio 6th, 2011 Posted by blog, empirical research, methods, training, TransWorld Airy Lines No Comment yet

Ph.D Course in Translation Processes Research15 – 19 August 2011

Theoretical aspects of process research; experimental research design and methodology; data visualization and human translation process modeling; qualitative and quantitative data analysis; user interaction with language technological tools.

CBS Center for Research & Innovation in Translation & Translation Technology

Registration fee for PhD students: 190 €
Registration fee for university researchers: 250 €
Reduced registration fee for the immediately ensuing NLPCS workshop: 110 €.
Registration deadline: 15 July 2011 at noon.
Support requests deadline: 15 June 2011.
Writing Process Research 2011: Keystroke Logging and Eye Tracking

7-9 September 2011

Possibilities and limitations of keystroke logging and eye tracking; good practices for ethnographical and experimental writing process research; complementary nature of observation methods; writing process data exploration; data preparation for further analysis; statistical analysis of writing process data; networking.

University of Antwerp Training school
20 trainees max.
Registration fee 125€
Registration deadline:7 July 2011
Confirmation of participation & grants: 1 August 2011

Three good reasons for carrying out a pilot study

junio 3rd, 2011 Posted by blog, empirical research, functionality check, pilot study, preliminary results, reliability, The sorcerer's apprentice No Comment yet

Both in experimental and in descriptive research, a pilot study is a small-scale version or trial run of the main study. A pilot study has to be carried out under the same conditions of the main study. Otherwise carrying out a pilot study would not make much sense, since the main goal is to trace possible sources of error to avoid those in your main study. There are at least three good reasons for carrying out a pilot study before you carry out the full-scale experiment:

 

    1. Functionality check of the study design by testing

 

a) research tools and methods regarding adequacy

When choosing tools and methods for data collection, you should always consider your study aim(s): What do you really want to measure in your study? By which means can you achieve these aims? With a pilot study, you can check whether your methods and tools are optimal for your purposes.

b) study feasibility

A pilot study will show you if your study design works the way you planned. Maybe you will have to introduce some modifications, for example, regarding the experimental setting.

    1. Collecting preliminary results

A pilot study will give you some first tentative results which may show at least the potential trends in the future outcome of the main study. This will let you read more about the possible ways to interpret these results.

  1. Increasing research reliability

By doing a pilot study, the reliability of your research project will increase. Other researchers and (maybe even funding) institutions maybecome more interested in your project.

Take your time for a pilot study. It is one of the best investments of time and effort in order to make an excellent main study trial.

Further reading

Altman, D., Burton, N., Cuthill, I., Festing, M., Hutton, J. & L. Playle (2006). Why do a pilot study. National Centre for the Replacement, Refinement and Reduction of Animals in Research. URL: http://www.nc3rs.org.uk/downloaddoc.asp?id=400

Gilbert, N. (2001). The importance of pilot studies. Social Research Update, 35, URL: http://sru.soc.surrey.ac.uk/SRU35.html

Neunzig, W. (2002). Estudios empíricos en traducción: apuntes metodológicos. In F. Alves (Hrsg.): O proceso de traducão. Cadernos de Traducão, 10, 75-96.

 

by P. Klimant

Recent Comments