“Our failure to account for how researchers leave the field–how they can responsibly extricate themselves from an ethnographic situation that binds researcher and researched through ongoing processes of ‘colonialism, imperialism, missionization, multinational capital, global cultural flows, and travel’–is a troubling area of silence” (Figueroa, 2014, p.129).

This week I choose to reflect on the above quote from Paris and Winn’s (2014) Humanizing Research because of the applicability to my own area of research.  In education abroad, reentry, or reverse culture shock, “is the process of readjusting, reacculturating, and reassimilating into one’s own home culture after living in a different culture for a significant period of time” (Gaw, 2000, p.83).   In Figueroa’s poignant essay, she implores social researchers to pay more attention to the ‘exit’ phase of the research process, whereby the researchers depart their communities that they have been studying to return to their regular communities of practice. This part of the research process can be overlooked and instead, Figueroa suggests that researchers should ask, “have we acknowledged and fulfilled our responsibility to the communities who have welcomed us?  Have we–in both our own opinion and the opinion of participants–fulfilled the commitments we made at the beginning of the study?” (p.129).  

Just as researchers must leave a community that at once may have seemed foreign and personal to them, so to do our students leave their host cultures only to return to a home that is perhaps less familiar where they must then make sense of all that they encountered and learned while abroad.  Consider this #ReEntryProblem tweet from Twitter user @DanielleSleeper:

The sad fact is, that as Figueroa asserts is the case in research, often times, not much attention is paid to the critical exit and reentry period.  Aside from a myriad of psychological issues that might affect returning students, such as depression, loneliness, and general anxiety (Gaw, 2000), having an intervention during the reentry process can be important for meaning-making as part of the students overall transformational experience. Rowan-Kenyon and Niehaus  (2011) echo this sentiment, stating, “as institutions provide these short-term experiences, it is also important for follow-up to occur after the experience is over. This follow-up presents opportunities for students to build on their experiences rather than letting them fade” (p. 225).

Therefore, as I consider the goals international educators often have for their study abroad participants it is intriguing to apply this education abroad lens to support Figueroa’s plea for researchers to “move beyond outdated notions of researcher neutrality,” (p.130).  Rather than merely being passive bystanders observing the host culture from a bubble, we tend to want to see our students engaging in thoughtful, reciprocal interaction with their hosts.  That is where intercultural learning and understanding can occur.  Why, then, do we expect that this would be any different for social researchers?

While I still struggle with the concept of forgoing objectivity in research, when I think about this dilemma from my education abroad lens, I begin to see logic in what Figueroa and others are advocating for in terms of humanizing research.  In order to maximize the learning opportunity, shouldn’t researchers seek to understand their subjects by injecting themselves in the middle of their daily lives?  The problem is, if this is done, then care must be taken when it comes time to leave the community.  It is a question of humans interacting with humans–a science wholly different from that of a researcher breaking down enzymes in a lab or an engineer working with software on a computer.  When we relegate our human research participants to data in a spreadsheet, what do we lose in the knowledge-making process?  What about ethics?  These questions are similar to those questions I have about our American students studying abroad.  When we fail to assist our students in reflecting in order to derive meaning and to be able to articulate their abroad experiences, when we turn a group of American college students loose in a foreign town without teaching them about humility and cultural relativism, do we not do more harm than good?



Gaw, K. (2000). Reverse culture shock in students returning from overseas. International Journal of Intercultural Relations, 24, 83-104.

Paris, D., & Winn, M. (Eds.). (2014). Humanizing research. Thousand Oaks, California: SAGE Publications, Inc.

Rowan-Kenyon, H. T., & Niehaus, E. K. (2011). One year later: The influence of short-term study abroad experiences on students. The Journal of Student Affairs Research and Practice, 48(2), 213-228.



Tracking v. Mixing; Seeking Humanization

Classroom dynamics are shaped by many things, including attributes, dispositions, knowledge, and skills of the teacher, students’ personalities and backgrounds, and, among other things, students’ academic abilities. Margarita Pivovarova (2014) seeks to isolate and measure the effect of students’ academic abilities, as measured by a low-stakes standardized test, on the performance of other students on subsequent exams, in effect, attempting to address the title question of whether students should be homogenously tracked or heterogeneously mixed according to academic ability. As I read this article, there were several things that I took issue with, each of which I want to address in turn.

Relatively early in the article, Pivovarova (2014) begins to use certain words to describe students’ academic performance that I found to be rather unsettling and dehumanizing in nature; by simply reducing them students to statistics on a page and using descriptors such as, good, bad, average, and marginal, she fails to positively recognize that the data she are interpreting are individual humans who are much more complex than simple adjectives. In an attempt to distance herself from the inescapable connotations associated with such words, she includes the following in her notes section, nearly three fourths of the way through the article:

4In order to make the interpretation easier, instead of labeling students by the level of achievement as 1 to 4, I will call students at the lowest level of achievement “bad” students without attaching the actual meaning of the word “bad”; students at the highest level – “good” students, and students in the middle of the achievement distribution – “average”. Among “average” students, I will distinguish between “marginal” (those whose achievement is below provincial standards, or level 2) and just “average” (level 3). (Pivovarova, 2014, p. 29)

While I recognize that it can often be easier to simplify data for ease of writing and communication with the reader, I found the inclusion and repeated use of these words to be over-simplified and indelible choice. The visceral reaction I had when reading these words, to me, underscores the importance and value of being very conscious and intentional in my word choices when making qualitative judgments and assessments about data points, and to always remember what the data I describe actually represent, which, in this case are students.

                When I began to reflect on the situative context behind Pivovarova’s (2014) work to better her dispositions and analyses, it became clear that her approach was quite distanced from any actual interaction with the students themselves. With such a large sample size (n=228,947 students), it seems likely that this information was reported to her by, or obtained through an institution involved with Ontario’s standardized testing, as opposed to being collected by she herself. While there were likely human-to-human interactions in the collection and analysis of these data, it seems as though one could reproduce such a study without ever seeing an actual person represented by the data. I see this as a major weakness of her methods; by never interacting with the ‘subjects’ of a study, it seems as though it would be quite easy to make such qualitative assessments that fail to acknowledge the humanity of the data points. As I read more about the author and her background, I found that her focus is in field of economics, which can have a cold, sterile distance to it, which was the feeling conveyed through this article.

Despite my above sentiments, when I began to reflect on the motivation behind Pivovarova’s work, I see the most noble of intentions behind it. The article intends to dispel current thinking on the linear relationship between the effects peers have on an individual achiever’s learning. This is done in the name of improving school effectiveness and efficiency, with the ultimate goal of improving student achievement.  If current practice dictates that students be grouped into classrooms in a certain way, homogeneously by achievement, for example, and new information suggests that more students would benefit to a greater extent if they were grouped using a different method, then the paper serves to fill an invaluable need that will improve outcomes for a significant number of students, something that has limitless value. An example of this, representing another particular strength of Pivovarova’s (2014) article is the manner through which she debunked an oft-used excuse of educators: the idea that a “bad apple” student can ruin the learning environment for all other students. Her data suggest that an increased number of low-performing students do not, on the whole, negatively impact the outcomes of high achieving students (Pivovarova, 2014). To use data to soundly reject such a dehumanizing (of students) notion is one of my most valuable take-aways from this research.

Through reading this article, I have gained a valuable insight about how I will implement my innovation into my own practice. I hope that collecting data through participative action research and utilizing methods that always actively seek to humanize my participants, my innovations will not reduce the lives and abilities of those involved to mathematical formulas, algorithms, and simple numbers on paper. But rather, that my methods will always refer to the data in ways that respectfully acknowledge the various backgrounds and stories of those involved in the study.


Works Cited:

Pivovarova, M. (2014). Should We Track or Should We Mix Them? Mary Lou Fulton
Teachers College. Tempe: Arizona State University.