This week LibParlor is proud to publish the second post in a three-part series, written by Alison Hicks. A week after being promoted to Associate Professor in the United States, Alison (@alisonhicks0) accepted a faculty position in the Department of Information Studies at University College, London. Having last lived in the UK 13 years ago, she is slowly readjusting to the soggy isle…
I freely admit that I snoozed my way through most of my Research Methods class in library school. Unused to North American registration systems, it was one of the only options that was left for me to take in my first semester by the time that I had worked out how to access the internet and piece together all the new terminology. Because this class came so early on in my library career, however, I was unable to see the value of learning anything to do with research. After all, I had already ruled the tenure-track career option out… When I further discovered that the class would be uniquely focused on quantitative methods, I became even more disillusioned and spent the rest of the semester working out how I could do the bare minimum and still pass the class. Until, of course, the day that I realised that I would have to actually, err, use some of these so-called pointless research methods in my new tenure-track position. If, like me, you find yourself feeling very underprepared for carrying out research, here are some things that I figured out after the fact.
“Qualitative data do, however, produce complex and meaningful understandings about what is going on within individuals’ lives as they interact and engage with information, libraries and librarians and it is for these reasons that I have found them so valuable within LIS.”
Most importantly, and my research methods class notwithstanding, research does not need statistics, graphs, tables, or any other numerical device to make it valid. When I first started out in the field, I somehow assumed that I needed numbers in order to be a proper researcher. A little pre- and post-test here, a minor flirtation with Chi square here, and boom, I would have generalisable and graphically exciting statistics that would see me through to promotion and tenure. Gradually, however, as I worked with more experienced colleagues and read more about research methods, I realised that qualitative methods made far more sense for what I wanted to study. Obviously, if bibliometrics or data visualisation are your thing, then yes, an understanding of statistics is fairly essential. Nowadays, however, I would argue that quantitative methods do not always add value to many areas of LIS research and especially to topics such as information literacy. That is not to say that qualitative studies are easier – while a more thorough grounding in research methods in my doctoral programme means that I can t-test with the best of them, I’ve found that the focus on interpretation within qualitative studies as well as the need to reconceptualise ideas of data quality and to acknowledge one’s own positionality in relation to data complicates matters considerably. Qualitative data do, however, produce complex and meaningful understandings about what is going on within individuals’ lives as they interact and engage with information, libraries and librarians and it is for these reasons that I have found them so valuable within LIS. If, like me, you had never really come across qualitative methods before, or are not really even sure of the difference between qual and quant, try Alison Pickard’s excellent Research Methods in Information, which helpfully compares and contrasts various different approaches to research and makes the whole process a lot clearer.
Similarly, you don’t have to use surveys in your research project. Alongside my automatic assumption that research = statistics, I initially supposed that good research was carried out through questionnaires, possibly because of all the terrible survey-based game shows (Family Fortunes, FTW) that constituted British TV in the 1990s. However, while surveys still form one of the most popular research methods in LIS (e.g. Turcios, Agarwal & Watkins, 2014), there are many, many, many, many other ways of generating data, and you don’t need to rely on the latest trends in skip logic and likert scale design to explore how individuals engage and interact with information. Focus groups or individual interviews, for example, provide the opportunity to hold a proper conversation with your participants, or to go off topic, and to allow them to express their own views rather than remaining limited to what you think is important. Similarly, visual methods involving maps, photos, or drawings are becoming more well known in library usability studies but can also be used within information literacy research to explore how an individual understands the concept of information or engages with information activities across time and space (Hicks & Lloyd, 2018). If you have little sense of what research methods are available to you, see if you can audit a qualitative methods class at your institution. Similarly, I found a Scholarship of Teaching and Learning group that brought in guest speakers to cover the basics of qualitative research and analysis as part of our research project training. Don’t forget to explore data analysis methods too, which will help you make sense of all the lovely data that is produced from your interview transcripts or focus group notes.
Ethics matter. I feel horrible admitting this, but it wasn’t until a couple of years into being on the tenure-track that I really understood what it meant to consider the ethical implications of my work. I had undergone all the training and was brought up short at the Tuskegee syphilis experiments, but my understanding of ethical consideration was still mostly limited to how I could get through the Institutional Review Board (IRB) procedures. You ticked all the right boxes, you rolled your eyes at the vast majority of questions because no, of course, you weren’t testing some top-secret super drug on the pet hamsters of seven-year-old children, and then waited with bated breath for the official nod that controlled whether you could start your research this semester or the next. Under pressure to get going on research, it was easy to almost see participants as barriers to data collection (hurry up and give me the data, my tenure clock is ticking!) instead of individuals with fears, hopes, and lives that could be affected by my investigations. However, after attending a couple of very moving sessions at the I3 conference, where researchers such as Jess Elmore and Frances Hultgren explored some of the ethical considerations that went into their work with refugees and immigrants, something clicked, and I finally saw the connections and the potential implications of my work. While, thankfully, I didn’t need to change anything in my research projects, these realisations did help me to think more carefully about the design of future studies, particularly with college students who are often juggling jobs, caring duties, and numerous other stresses and strains in a tightening job market and amidst rising costs.
In effect, when I first started out as a researcher, I paid a lot of attention to what I thought I should do, or how I could meet my (erroneous) preconceptions of what research or a researcher was rather than following my research questions. Obviously, the field of Library and Information Science has a rich research heritage, but there is also space to question and move beyond traditional means of investigation to explore new research problems as well as ways of addressing these issues.
Check out Alison’s first post, Reluctant Writers, Unite, and stay tuned for the third post in this series, coming March 2018 on the reviewer’s perspective.
Featured image [CC0], via Pexels
This work is licensed under a Creative Commons Attribution 4.0 International License.
The expressions of writer do not reflect anyone’s views but their own