Impactful Reading for New Behavior Analysts

As an undergraduate psychology major, I knew that I liked psychology and generally wanted to help people. But similar to most psychology majors, I didn’t know how I wanted to help people or in which area of psychology I wanted to continue my studies. Thankfully, my research methods teaching assistant introduced me to behavior analysis through Chiesa’s (1994) Radical Behaviorism and encouraged me to join the operant laboratory. Another graduate student encouraged me to read Sidman and Tailby (1982) given my interest in classics and language.

I was fortunate to learn about behavior analysis from people who were passionate about research and took the time to mentor those of us who knew nothing about it. What I now consider early influences on my understanding of the field and approach to research (as well as teaching) are Sidman’s enthusiasm for research and the laboratory lore articles in The Behavior Analyst (TBA).

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Enthusiasm for Research

I’ve always thought that science was fun, and this was likely due in large part to my high school chemistry/physics teacher. James Sparks let us listen to classic rock music while we conducted our chemistry experiments, and he gave us interesting, practical problems to solve with specific materials in physics. We used to say that he should have been working for NASA instead of wasting his talents on us, but all my teachers were creative and great at motivating us to care about their respective subjects. 

While my undergraduate psychology courses were interesting, I didn’t get the sense that research was fun. As I teach scientific writing now in the research methods course, my students say the same thing that I thought then: The language that most authors use in writing scientific articles is inaccessible, and reading the peer-reviewed literature is boring. B. F. Skinner was trained as a writer and is very careful in his word choice; he had to be while creating the foundations of behavior analysis. I don’t think that I noticed Skinner’s jokes because they were so similar in tone to the rest of his writing. In authoring books, there is more freedom to present information infused with some personality, but this is not the case with the peer-reviewed articles that undergraduate students typically encounter for a class. Having a sense of humor about your research or reminding the audience that there is a person behind the research is mostly punished by the academic community because of the perception that it detracts from the objectivity of science. However, there are some people such as Steven Pinker who don’t laud academese as the highest form of writing (see for example, Pinker (2014)). It’s still a work in progress to learn how to write for broader audiences in textbooks and short-form communications. Sidman (2007, p. 309) felt similarly: 

In our scientific writing, we fail to transmit the excitement of doing research. We rarely describe the thrill of finding out things no one knew before. Although the prevalent public conception is that scientists are cold, logical creatures, it is easy to demonstrate that scientists are also lovers of worldly pleasures…What scientists seem reluctant to acknowledge, however, is the poetry in what they themselves do, the poetry that is intrinsic to the process of discovery.

I enjoyed how Sidman (1994) communicated his enthusiasm for research in his “big book.” I felt the same way that Sidman (1994, p. 3) did about language: “But to me, one of the most fascinating observations is that we often react to words and other symbols as if they are the things or events they refer to.” Research started to seem like something that people did, and Sidman was teaching me how to be a researcher by describing what he already knew, what he wanted to do, and what he thought would happen. Yes, of course this was also what the other authors of peer-reviewed publications also did, but Sidman was telling a research story in a way that no one else I was reading had. I particularly liked the section where Sidman (1994, p. 34) described the results of the first experiment when they taught a boy with intellectual disorder to read: 

We had not yet been able to teach him to read with comprehension. In the experiment, it took us more than 15 hours of instruction over a four week period to teach him to match 20 spoken to printed three-letter words. And then, at the end of that month, we watched him suddenly matching the 20 printed words to pictures and vice versa without having been directly taught to do so. During the final test session, the excitement in the laboratory was palpable. We were all outside the experimental cubicle, jumping up and down with glee as we watched correct choice after correct choice registering on the recorder. My son, who was helping in the lab that summer, said to me, “Dad, I never saw you lose your cool like that before.” Looking inside the cubicle through a one-way window, we could se Os Cresson, good lab technician that he was, sitting quietly behind the subject, hands folded in his lap, not moving–hardly breathing, saying nothing, only his eyes, wide open and unblinking, betraying his tension. But when the boy had completed the tests, Os could contain himself no longer. He grabbed the…boy in a bear hug and cried out, “Goddammit, Kent, you can read!”

I couldn’t wait to start designing my own experiments and seeing such a drastic change in skill. Matching-to-sample procedures and stimulus equivalence seemed like such a powerful way to teach, and this could be a way that I could help people. I haven’t actually helped anyone, but I have taught many pigeons arbitrary matching to sample with shapes and hues. As it turns out, I like basic stimulus control research and leave the difficult part of helping people in the very capable hands of practitioners.

When I started shaping lever pressing with rats in the operant laboratory, it seemed unlikely that I could create new behavior for a rat with an operant chamber, a handswitch, and sweetened condensed milk (see also Swisher (2023, May 31) for analogous alternatives to shaping with nonhuman animals). Sidman (2007, p. 310) had also been there before and knew what I would experience:

There, in the very first lab session, I found myself creating behavior. Without any words being exchanged between me and my experimental subject, that little white furry animal was doing exactly what I told it to do–things it had never done before, things that gave it no evolutionary advantage, and even more incredibly, exactly what the lab manual said the animal was going to do when I set up specified contingencies.

It’s one thing to learn about the contingencies of reinforcement from a textbook and quite another to witness them working in real time. It took me about 2 weeks to get my first rat to press a lever – which is longer than the process should take, but I was still trying to find the proper combination of the maximum number of reinforcers per shaping session without overfeeding, how long to allow access to the milk for each successive approximation, and when to move from reinforcing one topography to the next in the behavior chain.

[3] Image provided courtesy of Tima Miroshnichenko under Pexels license
TBA: Lab Lore 

The graduate students in the lab encouraged the undergraduate students to attend conferences and read The Behavior Analyst from cover to cover. I dutifully carried around my current copy of The Behavior Analyst whenever I traveled and read as many of the articles as I could. In earlier versions of The Behavior Analyst, there were special sections on lab lore and operational definitions for frequently-used terms.

The Lab Lore articles appeared in the first issue of the Spring 1988 Volume 11 publication. Buskist and Johnston (1988) introduced the section on laboratory lore, which focused on questions that every researcher has but that no one seems to discuss. Until that time, most research in the experimental analysis of behavior was conducted with nonhuman animals. While similar procedures and protocols can be used with human participants, important differences exist. 

Morris et al. (1988) cautioned about how subject selection effects such as history, developmental age, demand characteristics/participant bias, gender, and other subject variables can affect the outcome of an experiment (i.e., internal validity), which in turn affect the generality of the findings (i.e., external validity). It is therefore important to report all these participant characteristics as well as how participants were recruited so other researchers can determine how representative the current sample is to their target population and thus how likely they are to reproduce an effect when they replicate the procedures. In addition to how to sample from the target population, researchers must consider what participants get in exchange for their time when participating in experiments. Typically, convenience samples of introductory psychology students are used in psychological experiments, and they participate in exchange for a more immersive educational experience and course credit. Galizio and Buskist (1988) also indicated that children are sometimes used as participants, and more directly consumable reinforcers delivered during the experiment would be preferable in those situations. Alternatively, adult participants could receive extra credit, money, immediately consumable reinforcers, and/or experimental procedures that are similar to games.

Bernstein (1988) described the session logistics and recommended that sessions should last long enough to provide a large sample of steady-state behavior depending upon the topography of that response (e.g., >1 hour) in every condition, and sessions should be conducted as frequently as possible with as little time in between sessions as can be reasonably scheduled.

Pilgrim and Johnston (1988) described the advantages and disadvantages of using more minimal instructions versus extensive instructions as well as manipulating instructions as an independent variable to determine how they control participant behavior. Given the differences between contingency-shaped and rule-governed behavior, the experimenter must decide which type of control they want in an experiment and design the procedures accordingly. Even when participants are asked about what they were doing in an experiment and why they did it, their self-reports are sometimes unhelpful when attempting to determine the functional relations in experiments (cf. Perone, 1988). However, Perone (1988) explained that participants’ verbal reports provide valuable data when treated as an operant response that can be conditioned during the course of an experiment rather than as an explanation for their nonverbal behavior.

Reading these in-depth discussions of experimental decisions and the reasoning behind them was an accessible introduction to the literature that I might not have found otherwise. It also helped me to start thinking about what types of research questions I would want to ask and how I would want to design the procedures.

These experiences might not be applicable to everyone, but they were invaluable for me along with having peers and mentors with which to discuss these readings. For more impactful experiences and voices that shaped her approach to behavior analysis, please refer to Elcoro’s (2023, December 13; 2024, February 28) blog posts.

Image credits

[1] Image provided courtesy of nappy under Pexels license

[2] Image provided courtesy of fauxels under Pexels license

[3] Image provided courtesy of Tima Miroshnichenko under Pexels license


Bernstein, D. J. (1988). Laboratory lore and research practices in the experimental analysis of human behavior: Designing session logistics–how long, how often, how many? The Behavior Analyst, 11, 51-58. 

Buskist, W., & Johnston, J. M. (1988). Laboratory lore and research practices in the experimental analysis of human behavior. The Behavior Analyst, 11, 41-42. 

Chiesa, M. (1994). Radical behaviorism: The philosophy and the science. Authors Cooperative. 

Elcoro, M. (2024, February 28). Introducing bell hooks to teachers of behavior analysis. Behavioral Education, ABAI. 

Elcoro, M. (2023, December 13). Your teachers and mentors in behavior analysis. Behavioral Education, ABAI. 

Galizio, M., & Buskist, W. (1988). Laboratory lore and research practices in the experimental analysis of human behavior: Selecting reinforcers and arranging contingencies. The Behavior Analyst, 11, 65-69. 

Morris, E. K., Johnson, L. M., Todd, J. T., & Higgins, S. T. (1988). Laboratory lore and research practices in the experimental analysis of human behavior: Subject selection. The Behavior Analyst, 11, 43-50.  

Perone, M. (1988). Laboratory lore and research practices in the experimental analysis of human behavior: Use and abuse of subjects’ verbal reports. The Behavior Analyst, 11, 71-75. 

Pilgrim, C., & Johnston, J. M. (1988). Laboratory lore and research practices in the experimental analysis of human behavior: Issues in instructing subjects. The Behavior Analyst, 11, 59-64. 

Pinker, S. (2014). The sense of style: The thinking person’s guide to writing in the 21st Century. Penguin. 

Sidman, M. (1994). Equivalence relations and behavior: A research story. Authors Cooperative.

Sidman, M. (2007). The analysis of behavior: What’s in it for us? Journal of the Experimental Analysis of Behavior, 87, 309-316. 

Sidman, M., & Tailby, W. (1982). Conditional discrimination vs. matching to sample: An expansion of the testing paradigm. Journal of the Experimental Analysis of Behavior, 37, 5-22.

Swisher, M. (2023, May 31). Teaching operant conditioning principles via virtual reality and in-class demonstrations. Behavioral Education, ABAI. 

Blog post contributed by Melissa Swisher