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How I Learned To Write In English
Seven years ago, I could neither read nor write in English; my native language is Arabic. When I arrived in the United States in May 2016 to pursue higher education, I needed a translator at the airport because I could not answer basic immigration questions.
After I graduated with my bachelor's degree in psychology from the University of Miami, I was fortunate to attend what I consider the best graduate school in the world: The University of Pennsylvania. In this Ivy League space, my non-native English proved to be insufficient.
In a meeting that came to define my time at Penn, one of my professors aggressively scolded my non-native prose. He essentially told me that I had to visit the campus disability office to fix my inferior writing.
I was furious. In an effort to channel my anger, I decided that I would become one of the best non-native English writers in the world. To this end, I decided to read as many books as I could on the topic of good prose. At this point, I feel I have surveyed the literature almost in its entirety; I have reached a saturation point, where ideas sound repetitive. Yet in all the "classic" books on writing, I did not find what I was looking for.
When I fortuitously stumbled across the work of Professor George Gopen, I felt that I had finally found a way to crack the "code" of the English language. I first read his magnum opus, Expectations: Teaching Writing from the Reader's Perspective, and then its sequel, The Sense of Structure: Writing from the Reader's Perspective. Reading Gopen's prose was a transformative revelation for me.
After reading most or perhaps even all of what Gopen has published, I emailed and asked him to be my writing mentor. To my surprise and delight, he agreed, and has personally invested in my learning: He has taught me how to "swing" in writing and make the swinging worthwhile.
We met via Zoom for almost a year, discussing nothing but English prose. I pride myself on being a serious mentee, and Gopen was a brilliant mentor. Since he took me under his wing, I feel that I've blossomed as a non-native English writer. Thus far, I have published almost 100 articles and essays, in both commercial publications and professional and academic journals—a proven track record.
I will share Gopen's key lessons below: The Elements of Reader Expectations. The title is inspired, of course, by The Elements of Style by Strunk and White, in which they shared their articles of faith in how English prose operates. Following in their footsteps, I hereby share the articles of faith of the Gopen method. (I would encourage interested readers to peruse his books and papers for themselves—or even better, attend one of his transformative lectures.)
1. Do not demonstrate; instead, communicate. Gopen makes a distinction between the mere demonstration of information and the skillful communication of knowledge. In demonstration, the writer is concerned with avoiding mistakes; in communication, the writer is concerned with the rhetorical task of persuasion.
Most writing assignments in school follow the demonstration model, which may explain why so many students struggle to produce persuasive prose. The Gopen method teaches writers to communicate rather than to demonstrate. Gopen teaches writers how readers experience prose on the page so that they can communicate their knowledge in ways that readers are going to interpret them.
2. Use the "litmus test of good writing."According to Gopen, the "litmus test" of good writing is one straightforward question: Did the reader receive what the writer was trying to send? If the answer was yes, then the writing was good. If the answer was no, then the writing was bad.
The quality of the writing, therefore, is not determined by its elegance alone. Instead, it is determined by whether or not it accomplishes its rhetorical purpose. Did the writer affect readers in the way they intended? Did the writer come across in the way they planned?
3. No rules, but tools. Gopen has one rule: No rules. That is, he believes that there are no rules in good writing. There are only tools that can be deployed to achieve certain rhetorical effects.
Rules are stultifying. Tools are liberating. Rules often stifle the creativity of writers; tools give writers the agency to experiment until they find their writerly voice. Good writers know what tools to use to achieve the intended rhetorical effects on their readers.
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4. Be aware of "reader energy."Readers summon a type of mental, called "reader energy," to experience prose. Good writers are careful not to waste this.
In the Gopen method, good writers express sophisticated ideas in simple prose, which means they write sentences that are easy to read—even when the concepts are complicated. Readers should not waste their energy figuring out what the writer is trying to say; instead, they should spend that energy to assess the strength of the writer's ideas.
5. Good writing has two hallmarks.According to Gopen, good prose has two hallmarks: First, every single word has a clear function; second, every single word is located in the appropriate position within the sentence and paragraph. By ensuring that the prose has these two hallmark qualities, writers produce clear, powerful, and elegant prose.
6. Avoid "splat prose."Gopen describes disconnected prose as "splat prose," wherein writers simply demonstrate information but do not communicate any insightful connections. The opposite of splat prose is prose that connects backward, moves forward, and places keywords in their most useful position. That is writing transformed.
Bad writers deliver readers splat prose, in which the connections between the sentences are ambiguous. Good writers make the connections between sentences and paragraphs explicitly clear.
7. Write musical sentences. Gopen shares that everything he learned about writing comes from his long-time obsession with classical music. He discovered "colometrics," a method by which to analyze prose rhythm. Just like musical notes have a structural rhythm to them, Gopen claims, so too do written sentences have a structural rhythm and cadence.
Good sentences, then, have a pleasant rhythm to them, with a particular sound and cadence. Bad sentences violate the explicit and implicit conventions of rhythm. Prose rhythm is implicitly experienced by readers, but Gopen makes its production explicit for writers.
8. Readers should know where to look for what.Good writers meet readers' expectations most of the time—but violate them occasionally for effect. Readers understand the meaning of prose not from the meaning of words but rather from the order of words. That is the most revolutionary insight in the entire Gopen tradition. Good writers put the appropriate substance in the right structure.
Disability Research: Nothing About Us Without Us
In psychology, there is a stigma against conducting me-search, or self-relevant research about one's own identity or experiences. This bias overshadows the fact that self-relevant research is common and can be a strength, especially by increasing the inclusion of underrepresented minorities like people with disabilities.
Comprising 26% of the adult U.S. Population, people with disability represent the largest minority group and perhaps the only minority group you can join at any time. However, disabled researchers and—consequently, I would argue—disability research, is severely underrepresented in our field. In a report examining the years 2006 to 2012, only 2% of faculty and 3% of students in APA-accredited programs reported a disability. More recently, the National Science Foundation reported that only 3% of STEM workers had a disability in 2021.
Self-relevant research is widespread in the field of psychology, yet we neglect to recognize the most prevalent kind as such. Our field has long been criticized for sampling primarily Western, educated, industrialized, rich, and democratic (WEIRD) participants. Interestingly, there is so little attention paid to disability in psychology that its absence has not even been noted in that acronym. I might propose adding a new letter, for "abled," leading to WEIRDA. Unsurprisingly, WEIRDA samples match the demographics of the academics doing the research and the editorial teams of top journals. Thus, one might argue that WEIRDA samples are also self-relevant research.
When people in the majority group study the majority group, their research is perceived as universal and objective; when minority group members study experiences of their own group, it may be perceived as subjective and biased. This is because dominant identities—e.G. Whiteness, abledness, etc.—are often perceived as the default or neutral. In contrast, research on identities and experiences that are outside the dominant group is perceived as less important or relevant; it is seen as niche and relegated to "specialty" journals. Thus, self-relevant research on minorities is more likely to be classified as such compared to self-relevant research on majority samples.
Another reason self-relevant research is more common than it appears is that not all minority identities are visible. The distinction between visible and invisible identity affects the salience of self-relevant research, or whether it is identified as self-relevant at all. When a person has an invisible minoritized identity (e.G. A mental health condition or a chronic pain disorder), people may assume the default—as discussed above: that the person is a majority group member. As a visibly disabled researcher, anyone who views my headshot or listens to me speak at a conference can make the connection between my identity and my disability research. This experience is shared by many members of racial and ethnic minorities and some sexual and gender minorities whose identities are visible.
In a study of clinical, counseling, and school psychologists and students, more than half of participants reported engaging in self-relevant research. Compared to majority group members, minorities were more likely to report conducting self-relevant work. This study also found that self-relevant researchers were rated as more biased and having poorer judgment compared to researchers who did not conduct research relevant to themselves. Participants who reported not engaging in self-relevant research made more stigmatizing judgments of self-relevant research than participants who reported having conducted self-relevant research.
Kathleen Bogart
Source: Beau Bogart / used with permission
A Personal ExampleAs a case study of the benefits and challenges associated with self-relevant research, I'll describe some of my own experiences as a self-relevant disability researcher. I was born with a rare neurological disorder, Moebius syndrome, which results in facial paralysis. Communicating in an unusual way made me fascinated with social interaction, drawing me to psychology. As an undergraduate, I wanted to do a term paper on Moebius syndrome. However, I was frustrated to discover that there were only a handful of studies on the topic in psychology. The existing research examined Moebius syndrome for the purpose of better understanding "normal" processes. Critics have noted that majority group members researching minorities often take a deficit approach, with a goal of understanding dominant groups rather than understanding or improving the daily lives of minorities.
Recognizing the need to fill the gap in research on quality of life among people with Moebius syndrome and other conditions involving facial paralysis, I realized I had the unique motivation and insight to build this field. While pursuing graduate work, I found it challenging to find mentors. Psychology graduate programs follow an apprenticeship model, which hinges on finding a mentor who is an expert in your chosen field of study. The lack of psychologists studying facial paralysis combined with the paucity of role models with disabilities were barriers to finding a suitable graduate program.
Eventually, I found excellent mentor-allies with expertise in broader areas that could be related to facial paralysis. At the start of my graduate work, I also connected with Moebius syndrome and facial paralysis communities for the first time. These connections were invaluable, providing me with an understanding beyond my own experiences of the issues facing this diverse group of people. I have since conducted some of the largest and most comprehensive psychosocial studies of people with facial paralysis.
Challenges of self-relevant disability researchThe most common argument against self-relevant research is that it interferes with objectivity. Critics may argue that a self-relevant researcher may overweight their own perspective at the expense of others when conducting research. Of practical concern is that a self-relevant researcher may have preexisting relationships with participants and community organizations. If a participant knows a researcher, the participant may feel social pressure to participate or to respond in ways that the researcher might approve of.
Benefits of self-relevant disability researchAs exemplified in my experience, self-relevant researchers may be motivated to fill research gaps and make discoveries that otherwise would not be explored. Shared identity between researchers and participants builds trust and engagement, especially in marginalized populations that may mistrust science due to previous harms. Insider knowledge may promote more valid and representative research questions, study designs, sampling, interpretation, and implementation of findings. Thus, research is more likely to directly benefit the community.
Maximizing the cost-benefit ratio of self-relevant researchConsidering positionality. Positionality statements have been an important tradition in qualitative research, but are less common in quantitative work. Positionality statements are a transparent acknowledgement of the ways in which one's own perspective as a researcher has influenced one's work. There is a growing movement to include positionality statements in quantitative psychology research as well. When majority group members engage in positionality statements, it may prompt reflection and encourage them to conduct more inclusive team science.
Those with invisible identities can choose not to disclose the self-relevance of their research, while those with visible or apparent identities do not have this privilege. Thus, it should be noted that positionality statements put people with invisible identities in a position where they may feel expected to disclose a self-relevant identity but do not feel safe doing so. Fear of disclosing due to stigma speaks to a larger problem in our field as a whole that must change, but in the meantime, it is important to consider this paradox.
Participatory research. Organizations and funders are now calling for community-based participatory research. This approach asserts that community stakeholders with lived experience should co-produce science with researchers. Best-practice guides for this type of research focus on decentering power structures, building knowledge, skills, and trust, and co-creation at every level, with the goal of developing research that solves the self-identified problems of communities.
ConclusionAs our field moves closer to fully open science, we need transparency around diversity. Psychology's WEIRDA self-relevant research will continue until we diversify our education, faculty, peer reviewers, and editorial boards. Destigmatizing self-relevant research will increase the recruitment and retention of diverse researchers, further enhancing the science that is produced in our field.
A longer version of this article appears in Communications Psychology under a Creative Commons Attribution 4.0 International License.
Clicks And Tricks: How Online Tests Are Changing Motor Learning
A recent study utilized big data to enhance understanding of motor learning, revealing key insights into how age, gender, and other factors impact motor control. This approach offers a novel perspective, complementing traditional lab-based research. Credit: SciTechDaily.Com
Data generated by citizen scientists offer researchers new insight into how people adapt and move differently to correct for movement errors.
A new research study examined the results from data generated by citizen scientists using a simple web-based motor test. The big data approach provides researchers with a unique way to explore how people correct for motor control errors. The resulting insights may one day pave the way for personalized physical therapy or tailor an athlete's training routine. The results are available in the January 30th issue of the journal Nature Human Behaviour.
Complementing Traditional Lab Studies"This exploratory approach does not replace lab based studies, but complements them, asking whether motor behavior can generalize to the greater population," said Jonathan Tsay, assistant professor in the Department of Psychology at Carnegie Mellon University and first author on the paper. "I see this large-scale approach as a way to democratize motor learning research."
Jonathan Tsay, assistant professor in the Department of Psychology at Carnegie Mellon University. Credit: CMU
Traditionally, motor learning scientists have studied how people learn motor skills in a lab setting using expensive equipment to capture the subtle changes in a person's movement in response to movement errors. These studies often involve a small number of participants. Whether these results generalize to the larger population remains unknown.
Harnessing the Power of Big DataTsay wanted to explore motor skills from a new perspective, using big data. To gather the data, he developed a simple motor-learning assessment that people could take online in the comfort of their homes. The result is a dataset of more than 2,000 sessions from a diverse participant population.
The study can also evaluate different underlying processes in motor learning, that is, the relative contribution of subconscious, implicit motor learning, and conscious, explicit motor learning. With the data in hand, Tsay was able to examine how demographic variables affect the relative contribution of these two learning styles.
The short, at-home test took about eight minutes compared to a normal 80-minute experiment in the lab. Many participants logged back in and contributed multiple sessions to the database, allowing the research team to track changes in motor learning efficiently.
Uncovering New InsightsThe potential of the big data lies in a better understanding of variables, like gender, age, visual impairment, and even video game experience, that can impact motor adaptation.
Tsay points to age as an example. It may seem obvious that age would be an important factor affecting motor adaptation, but the effect of age has been mixed in laboratory studies. The confusion may be in part due to the small sample size and the focus on extreme age groups (very young and very old).
Using big data, Tsay and his colleagues were able to examine age as a continuous variable. The results showed how participants modified their strategies to correct for a motor error across the lifespan, with adaptation peaking between 35 and 45 years of age. These adaptations have been missed by previous studies involving only a limited sample size.
"Using machine learning and other techniques, [this approach allowed us] to predict who would be successful at motor learning and what properties — speed of movement and reaction time — are good predictors of success in motor learning during a session," said Tsay. "The results we found in this exploratory big data manner can be brought back to the lab to do more hypothesis-driven [studies] to find the mechanism behind the finding we see online."
Challenges and Future DirectionsThe simple motor learning task was only able to predict about 15% of the variance in the study, which limits the insights that can be drawn from these results. In addition, the motor task was not conducted under an experimenter's supervision or specifically controlling for parameters, like type of technology and internet speed, that increased noise in the data. Despite these limitations, Tsay still believes this large-scale approach is able to examine this variability in a detailed manner, drawing insights that can be valuable to the motor research community.
"Many, many questions in psychology are amenable to on-line testing, but there are few motor studies," said Richard Ivry, distinguished professor in psychology at the University of California, Berkeley and co-author on the study. "The NatHumBehav study further adds to our confidence that on-line studies can be very meaningful for studying motor control, and I know that many labs around the world have taken advantage of these tools."
Reference: "Large-scale citizen science reveals predictors of sensorimotor adaptation" by Jonathan S. Tsay, Hrach Asmerian, Laura T. Germine, Jeremy Wilmer, Richard B. Ivry and Ken Nakayama, 30 January 2024, Nature Human Behaviour.DOI: 10.1038/s41562-023-01798-0
Tsay and Ivry were joined by Hrach Asmerian and Ken Nakayama at University of California, Berkeley, Laura Germine at Harvard Medical School, and Jeremy Wilmer at Wellesley College on the study.
The study received funding from the National Institute of Health National Institute of Neurological Disorders and Stroke.
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