Posted by: Michael Atkisson | October 18, 2010

The Newtonian Misstep: Notes on Rychlak’s The Psychology of Rigorous Humanism

Generation of scientific knowledge in three ways (Rychlak, 1988, p. 46)

  1. Theory
  2. Procedural evidence (via cognitive method)
  3. Validating evidence (via research method)


“A theory is the uniting of meaningful relations between designated terms (constructs, abstractions), often framed as propositions or hypotheses (Rychlak, 1968, p. 42)” (Rychlak, 1988, p. 45).

POINT 1: Procedural Evidence: also known as cognitive methods or formal cause—The rational tests of mathematics and philosophy (Rychlak, 1988, p. 45).
  • Mathematical Proofs
    • “mathematical proofs are no more dependent upon time than are logical proofs” (Rychlak, 1988, p. 47).
    • “the sense of conviction of a mathematical or logical proof does not wait on the prescribed succession of events to generate data” in support of one’s contention, as in the case in validation” (Rychlak, 1988, p. 47).
    • “They cannot be efficiently caused because they are like internally consistent patterns, which are only to be recognized and not brought about or made to happen. Mathematical proofs are therefore always coherence theories (procedural evidence), relying on the internal consistency of a tautology to bring conviction rather than on their correspondence with externally (efficiently) caused events” (Rychlak, 1988, p. 47).
  • Logical proofs
    • “circles are drawn within circles, …[the] necessary conclusion is visualized immediately, within time…There is no antecedent force bringing about this evidence as a consequent over time” (Rychlak, 1988, p. 44).
  • Procedural evidence or formal cause (time and observation not involved)
    • “The evidence suggested in such cognitive tests we have called procedural (ibid. p. 74), for it allows thinking to go forward by steps of plausibility and common sense” (Rychlak, 1988, p. 45).
    • “We test our ideas against the internal consistency of other ideas, and then, because of the plausibility afforded by the common sense of the totality, we proceed in thought with confidence if not conviction” (Rychlak, 1988, p. 45).

Validating Evidence:

  • Control and prediction (Rychlak, 1988, p. 46)
  • Efficient Cause (as opposed to formal cause), like a machine- observable consequences of antecedents over time
    • “As an observational frame we have noted that Gilbert[i] employed a machine analogue. Machines are the quintessence of efficient causality, in which some antecedent factor moves or brings about a consequent factor over time. The basic meaning of an efficient cause involves this cause-effect occurrence over time. One cannot have an efficient cause explanation outside of a timeframe” (Rychlak, 1988, p. 44).
POINT 2: Distinguishing between efficient and logical proof causality: are we looking for a temperature change or a logical line of evidential development, or both?

“if we overlook the fundamental contribution of nonefficient-causality in our methodological verifications, possibly we may misinterpret that very evidence on which we claim the rigor of our science depends”(Rychlak, 1988, p. 45).

POINT 3: The Wrong Turn in the Path

“Having distinguished these terms, we can now analyze an historical development that blurred the distinction between what was a theoretical- and procedural-evidence-based proof and what was a validation in the control-and-prediction sense across a time span” (Rychlak, 1988, p. 47).

POINT 4: Newtonian formal causes (procedural evidence) get mistaken for natural-science efficient causes.

“Even so, thanks to Newton, the machinelike methodology of Gilbert, the laws of motion proposed by Galileo, and the efficient-caused emphasis of Francis Bacon were all brought together into a formidable coalition that was to make Newtonian formal causes into natural-science efficient causes” (Rychlak, 1988, p. 47).

POINT 5: Newton’s mathematical proofs could predict the movement of the planets and stars, and predicted the existence of stars not visible through the calculation of gravitational fields. It was a mathematical interpretation (procedural evidence out of time) of a moving reality (efficient cause). Rychlak is saying that, even though Newton’s conclusions were considered to be efficient cause proofs, that in reality they were at the same level of evidence as procedural evidence, a logical proof, outside of the bounds of real-time observation.

“Newton looked to Gilbert’s experimental methods as the ultimate source of truth. So long as a scientist could empirically demonstrate natural lawfulness—helping the effort along the way through mathematics—he was doing his job properly. He was in the empirical realm of how things really happened even though admittedly (and properly!) he could not always say in his formal theory why these predictions held up in the world of palpable events. Though admirably empirical, this Newtonian brand of “natural” science actually survived on the blurring of a necessary distinction in the generation of knowledge” (Rychlak, 1988, p. 49).

POINT 6: —How observational evidence became the only evidence, and the flaws in science that result from such a premise—Because Newton’s conclusions were mistaken for efficient-cause explanations and because they were so persuasive, in order to be persuasive from that point forward as a scientist you needed to only use efficient-cause explanations. The result of this is that the procedural evidence is not seen as having significant explanatory power.

POINT 7: However, because you can observe and predict without understanding why, efficient-cause explanations are not enough. When procedural evidence that underlies efficient-cause explanations is not examined systematically, false assumptions prevail with evidence to back them up. The why depends on the premise of the question. The explanatory power that enables one to interpret the efficient-cause evidence rests in the procedural evidence that underlies the experiment.

POINT 8: This is important for learning analytics because many just assume that it is a practical methodology that will help to know when and how to intervene in online learning situations. Without consideration to what the logical proofs and assumptions (procedural evidence) are, analysts will not be able to interpret the results of their calculations properly. They could be making the same things happen the same way without knowing why or thinking that it is because of something else other than its cause. It is not just methods without theory. If not it isn’t science.

“Newton’s concept of gravity was purely formal, a mathematical prediction of moving points in timeless mathematical space. But, thanks to the efficient-cause machine paradigm of Gilbert’s scientific method and the call for efficient (and material) cause description in natural science by Bacon, a confounding took place between what was method (Gilbert) and what was theory (Bacon, Newton). There were two general results of this confusion: (1) Only efficient causes were assumed to be involved in the Newtonian explanation of gravity (motion, moment, then force); and (2) Observations of natural phenomena made through experiments were given an exclusively efficient- (and material)- cause explanation. Although presumptions of natural lawfulness an mathematical regularity had nothing to do with eh efficient-cause meaning, a “natural scientist” looking (extra-spectively) out to the “facts” could take these unnamed presumptions in his approach and report back nothing but the flow of efficient cause across time. His method confirmed his presumptions again and again, for it could not do otherwise. For Him to see other than efficient causes in events that took place over time was impossible in principle. As Burtt so marvelously expressed it, the Newtonian physicist thereby succeeded in making “a metaphysics out of his method” (ibid., p. 229)” (Rychlak, 1988, p. 49).

The Newtonian misstep in the explanation of why behaviorist got it wrong.
POINT 9: Operationalizing does not mean that we understand the terms or phenomena we have defined. The abstraction may lead away from its meaningfulness or true nature.

“As operational definitions do not always clarify a meaning as originally expressed (recall Tolman’s redefinition of purpose), so to validation in an experimental context does not always answer what we want to know. That is, sometimes we can observe a controlled sequence of events (experimental design) and even predict its eventual outcome without understanding what is taking place, how it achieves its predictable outcome, or why it would work under certain circumstances and not others” (Rychlak, 1988, pp. 168-169).

POINT 10: Science is more than methodology, observations, and verified predictions; it is also the formulation, adjustment, confirmation, and rejection of theory and metaphor. Assuming it is just the latter leads to unquestioned assumptions in the interpretation of data.

“As the eminent philosopher of science Philipp Frank (1957) has shown, scientific findings (validated predictions or observations) outstrip the common sense understanding of them, taking us back to that condition earlier in history where we could control and predict without knowing why, what, or how such regularities in events were really brought about. Man predicted his course of travel under the stars, controlled the crops through practical know-how, and cured himself of certain diseases centuries before there was anything like a scientific account of these beneficial outcomes. With the birth of science, and especially with the advent of modern physics, the kinds of predictions that were possible from the thinking of an Einstein or a Bohr did not make “common sense,” although they were found observationally to be valid. In truth the earlier folk theories of stars as baubles, hung in the sky above a flat terrain by a God so that man could find his way about were more plausible thank, for example, the notions of gravity as inertia, or electros making quantum leaps” (Rychlak, 1988, p. 169).

“The obvious lesson is that science is not only a methodological endeavor. Constant attention must be given to theoretical considerations—or, as they might be called, metaphorical or philosophical considerations…Later, in Newtonian science, the uncritical acceptance of empirical data without sophisticated study of assumptions lead to a “theorization” of scientific method—that is, the assumptions of the method were projected onto the world as a necessary characteristic and then “proved so” by the results of these very same method (Burtt, 1954, p. 229). Though functionalists like to point to the former circumstance as an inevitable outcome of the teleology in science, they constantly fall into the errors of the latter variety by confusing what is their methodological commentary with their theory of explanation” (Rychlak, 1988, pp. 169-170).

POINT 11: Because behaviorists deemed philosophical analysis as something less than empirical, they never noticed that they were mistaking IV-DV, a mathematical formal cause, for S-R (what they thought was efficient-cause evidence), a metaphor and philosophical abstraction. Instead of controlling for IVs, Watson was controlling stimulus as if it could be done directly, as if the abstraction were the object of measure.

“This confounding was easy to make because both stimulus-response (S-R) theory and the independent variable-dependent variable (IV-DV) sequence of experimentation can be construed in exclusively efficient-cause terms—even though the IV_DV sequence was introduced as a mathematical formal cause (see Chapter 1, p. 50). Because the functionalists eschewed philosophical analysis as not sufficiently empirical for science to worry about, the almost shocking confounding of terms that was to result went unnoticed in the arbitrariness and practicality of their research efforts.In his opening call for behaviorism John Watson (1913) set as his goal the “working out [of] a systematic scheme for the prediction and control of response in general” (pp. 162-163). As we have just reviewed it, the phrase control and prediction defines validating evidence. But Watson was not saying that the experimentalist performs this activity to support or refute his theoretical hypotheses, which in turn might account for the observed data. He was controlling not an independent variable, but as “stimulus” (ibid., p. 163) so that he might efficiently cause the organism’s movements to go the way he wanted them to go. Rather than validated knowledge, behaviorism sought lawful ties of stimuli to responses: “In a system of psychology completely worked out, given the response the stimuli can be predicted; given the stimuli the response can be predicted” (ibid., p. 167).” (Rychlak, 1988, p. 170).

POINT 12: The consequence of this view is anything but practical. It results in something to the effect of, “Either you accept my unchecked assumptions as law or you are not a scientist.”

“To speak of response variables is blatantly to preempt the possible theoretical account of why experimental variables might be said to bear an observed relationship. This paradigmatic preemption effectively dictates terms to the experimenter, who must now either see his dependent variable as a response or risk being considered nonscientific by his peers” (Rychlak, 1988, p. 171).

POINT 13: Skinner sounds a lot like an interventionist using Learning Analytics“Though he does not consider himself an S-R psychologist (and for good reason), Skinner can say of himself: “As an analyst of behavior, I want to relate the probability of response to a large number of independent variables, even when these variables are separated in time and space” (Evans, 1968, p. 12). A scientist who believes he is observing “variables at play,” which are efficient causes only in the experimental context, sill have put himself in the position of being unable to see a role for teleology in behavior in principle, so long as he follows this experimental procedure! He will have defined himself into a mechanistic corner which even empirical evidence cannot bring him out of” (Rychlak, 1988, p. 172).

POINT 14: Rychlak’s response to an article that uses skinner’s and Watson’s assumptions about behavior.

“There seems to be a behavioral (S-R) regularity in there, but until we delineate all of the antecedent variables controlling these measured responses the author seems to think are self-initiated intentions, we are unable to say what is taking place. One thing for certain: this business about mental intentions and personal directions is unwarranted by the observations. We must find the antecedents determinants (S-R laws) of these mediating intentions. We need a more scientific account!”(Rychlak, 1988, p. 172).


Burtt, E. A. (1954). The metaphysical foundations of modern physical science: the scientific thinking of Copernicus, Galileo, Newton and their contemporaries. Doubleday.

Evans, R. I. (1968). B. F. Skinner; the Man and His Ideas: The Man and His Ideas. Dutton.

Frank, P. (1957). Philosophy of science: the link between science and philosophy. Prentice-Hall.

Rychlak, J. F. (1988). The Psychology of Rigorous Humanism (2nd ed.). New York University Press.

Watson, J. B. (1913). Psychology as the behaviorist views it. Psychological Review Company.

[i] The English astronomer and physicist (24 May 1544 – 30 November 1603) who was the first to attribute the magnetism that controlled the compass to the core of the earth containing iron.



  1. […] But it does not seem like this enough to differentiation keep other related fields from taking over learning analytics ideas. If learning analytics is going to put more than the “tool” stake in the ground, it needs to define and make contributions in the fundamentals of how we interpret and interact with teaching and learning, (i.e. philosophy, epistemology, and metaphor) in addition to its technological innovations. Otherwise, we will be selecting, capturing, aggregating, reporting, predicting, using, refining, and sharing all while not understanding why or how. […]

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