Model of hierarchical complexity

The Model of Hierarchical Complexity is a framework for scoring how complex a behavior is. It quantifies the order of hierarchical complexity of a task based on mathematical principles of how the information is organized and of information science. This model has been developed by Michael Commons and others since the 1980s.

Overview
The Model of Hierarchical Complexity (MHC), which has been presented as a formal theory, is a framework for scoring how complex a behavior is. Developed by Michael Lamport Commons, it quantifies the order of hierarchical complexity of a task based on mathematical principles of how the information is organized, and of information science. Its forerunner was the General Stage Model. It is a model in mathematical psychology.

Behaviors that may be scored include those of individual humans or their social groupings (e.g., organizations, governments, societies), animals, or machines. It enables scoring the hierarchical complexity of task accomplishment in any domain. It is based on the very simple notions that higher order task actions are a) defined in terms the next lower ones (creating hierarchy), b) they organize those actions c) in a non-arbitrary way (differentiating them from simple chains of behavior insuring a match between the model-designated orders and the real world orders). It is cross-culturally and cross-species valid. The reason it applies cross-culturally is that the scoring is based on the mathematical complexity of the hierarchical organization of information. Scoring does not depend upon the content of the information (e.g., what is done, said, written, or analyzed) but upon how the information is organized.

The MHC is a non-mentalistic model of developmental stages. It specifies 15 orders of hierarchical complexity and their corresponding stages. It is different from previous proposals about developmental stage applied to humans. Instead of attributing behavioral changes across a person's age to the development of mental structures or schema, this model posits that task sequences of task behaviors form hierarchies that become increasingly complex. Because less complex tasks must be completed and practiced before more complex tasks can be acquired, this accounts for the developmental changes seen, for example, in individual persons' performance of complex tasks. (For example, a person cannot perform arithmetic until the numeral representations of numbers are learned. A person cannot operationally multiply the sums of numbers until addition is learned). Furthermore, previous theories of stage have confounded the stimulus and response in assessing stage by simply scoring responses and ignoring the task or stimulus.

The Model of Hierarchical Complexity separates the task or stimulus from the performance. The participant's performance on a task of a given complexity represents the stage of developmental complexity.

Vertical complexity of tasks performed
One major basis for this developmental theory is task analysis. The study of ideal tasks, including their instantiation in the real world, has been the basis of the branch of stimulus control called psychophysics. Tasks are defined as sequences of contingencies, each presenting stimuli and each requiring a behavior or a sequence of behaviors that must occur in some non-arbitrary fashion. The complexity of behaviors necessary to complete a task can be specified using the horizontal complexity and vertical complexity definitions described below. Behavior is examined with respect to the analytically-known complexity of the task.

Tasks are quantal in nature. They are either completed correctly or not completed at all. There is no intermediate state (tertium non datur). For this reason, the Model characterizes all stages as P-hard and functionally distinct. The orders of hierarchical complexity are quantized like the electron atomic orbitals around the nucleus. Each task difficulty has an order of hierarchical complexity required to complete it correctly, corresponding to the atomic Slater eigenstate. Since tasks of a given quantified order of hierarchical complexity require actions of a given order of hierarchical complexity to perform them, the stage of the participant's task performance is equivalent to the order of complexity of the successfully completed task. The quantal feature of tasks is thus particularly instrumental in stage assessment because the scores obtained for stages are likewise discrete.

Every task contains a multitude of subtasks (Overton, 1990). When the subtasks are carried out by the participant in a required order, the task in question is successfully completed. Therefore, the model asserts that all tasks fit in some configured sequence of tasks, making it possible to precisely determine the hierarchical order of task complexity. Tasks vary in complexity in two ways: either as horizontal (involving classical information); or as vertical (involving hierarchical information).

Horizontal complexity
Classical information describes the number of "yes–no" questions it takes to do a task. For example, if one asked a person across the room whether a penny came up heads when they flipped it, their saying "heads" would transmit 1 bit of "horizontal" information. If there were 2 pennies, one would have to ask at least two questions, one about each penny. Hence, each additional 1-bit question would add another bit. Let us say they had a four-faced top with the faces numbered 1, 2, 3, and 4. Instead of spinning it, they tossed it against a backboard as one does with dice in a game of craps. Again, there would be 2 bits. One could ask them whether the face had an even number. If it did, one would then ask if it were a 2. Horizontal complexity, then, is the sum of bits required by just such tasks as these.

Vertical complexity
Hierarchical complexity refers to the number of recursions that the coordinating actions must perform on a set of primary elements. Actions at a higher order of hierarchical complexity: (a) are defined in terms of actions at the next lower order of hierarchical complexity; (b) organize and transform the lower-order actions (see Figure 2); (c) produce organizations of lower-order actions that are qualitatively new and not arbitrary, and cannot be accomplished by those lower-order actions alone. Once these conditions have been met, we say the higher-order action coordinates the actions of the next lower order.

To illustrate how lower actions get organized into more hierarchically complex actions, let us turn to a simple example. Completing the entire operation 3 × (4 + 1) constitutes a task requiring the distributive act. That act non-arbitrarily orders adding and multiplying to coordinate them. The distributive act is therefore one order more hierarchically complex than the acts of adding and multiplying alone; it indicates the singular proper sequence of the simpler actions. Although simply adding results in the same answer, people who can do both display a greater freedom of mental functioning. Additional layers of abstraction can be applied. Thus, the order of complexity of the task is determined through analyzing the demands of each task by breaking it down into its constituent parts.

The hierarchical complexity of a task refers to the number of concatenation operations it contains, that is, the number of recursions that the coordinating actions must perform. An order-three task has three concatenation operations. A task of order three operates on one or more tasks of vertical order two and a task of order two operates on one or more tasks of vertical order one (the simplest tasks).

Stages of development
The notion of stages or stagecraft is fundamental in the description of human, organismic, and machine evolution. Previously it has been defined in some ad hoc ways. Here, it is described formally in terms of the Model of Hierarchical Complexity (MHC).

Formal definition of stage
Since actions are defined inductively, so is the function h, known as the order of the hierarchical complexity. To each action A, we wish to associate a notion of that action's hierarchical complexity, h(A). Given a collection of actions A and a participant S performing A, the stage of performance of S on A is the highest order of the actions in A completed successfully at least once, i.e., it is: stage (S, A) = max{h(A) | A ∈ A and A completed successfully by S}. Thus, the notion of stage is discontinuous, having the same transitional gaps as the orders of hierarchical complexity. This is in accordance with previous definitions.

Because MHC stages are conceptualized in terms of the hierarchical complexity of tasks rather than in terms of mental representations (as in Piaget's stages), the highest stage represents successful performances on the most hierarchically complex tasks rather than intellectual maturity. Table 1 gives descriptions of each stage.

Stages of hierarchical complexity

 * {| class="wikitable"

! Order or Stage ! What they do ! How they do it ! End result
 * +Table 1. Stages described in the Model of Hierarchical Complexity
 * 0 – calculatory
 * Exact computation only, no generalization
 * Human-made programs manipulate 0, 1, not 2 or 3.
 * Minimal human result. Literal, unreasoning computer programs (at Turing's alpha layer) act in a way analogous to this stage.
 * 1 – sensory or motor
 * Discriminate in a rote fashion, stimuli generalization, move
 * Move limbs, lips, toes, eyes, elbows, head; view objects or move
 * Discriminative establishing and conditioned reinforcing stimuli
 * 2 – circular sensory-motor
 * Form open-ended proper classes
 * Reach, touch, grab, shake objects, circular babble
 * Open ended proper classes, phonemes, archiphonemes
 * 3 – sensory-motor
 * Form concepts
 * Respond to stimuli in a class successfully and non-stochastically
 * Morphemes, concepts
 * 4 – nominal
 * Find relations among concepts; use names
 * Find relations among concepts; use names
 * Single words: ejaculatives & exclamations, verbs, nouns, number names, letter names
 * 5 – sentential
 * Imitate and acquire sequences; follows short sequential acts
 * Generalize match-dependent task actions; chain words
 * Various forms of pronouns: subject (I), object (me), possessive adjective (my), possessive pronoun (mine), and reflexive (myself) for various persons (I, you, he, she, it, we, y'all, they)
 * 6 – preoperational
 * Make simple deductions; follow lists of sequential acts; tell stories
 * Count event events and objects; connect the dots; combine numbers and simple propositions
 * Connectives: as, when, then, why, before; products of simple operations
 * 7 – primary
 * Simple logical deduction and empirical rules involving time sequence; simple arithmetic
 * Adds, subtracts, multiplies, divides, counts, proves, does series of tasks on own
 * Times, places, counts acts, actors, arithmetic outcome, sequence from calculation
 * 8 – concrete
 * Carry out full arithmetic, form cliques, plan deals
 * Does long division, short division, follows complex social rules, ignores simple social rules, takes and coordinates perspective of other and self
 * Interrelations, social events, what happened among others, reasonable deals, history, geography
 * 9 – abstract
 * Discriminate variables such as stereotypes; logical quantification; (none, some, all)
 * Form variables out of finite classes; make and quantify propositions
 * Variable time, place, act, actor, state, type; quantifiers (all, none, some); categorical assertions (e.g., "We all die")
 * 10 – formal
 * Argue using empirical or logical evidence; Logic is linear, 1 dimensional
 * Solve problems with one unknown using algebra, logic and empiricism
 * Relationships (for example: causality) are formed out of variables; words: linear, logical, one-dimensional, if then, thus, therefore, because; correct scientific solutions
 * 11 – systematic
 * Construct multivariate systems and matrices
 * Coordinates more than one variable as input; consider relationships in contexts.
 * Events and concepts situated in a multivariate context; systems are formed out of relations; systems: legal, societal, corporate, economic, national
 * 12 – metasystematic
 * Construct multi-systems and metasystems out of disparate systems
 * Create metasystems out of systems; compare systems and perspectives; name properties of systems: e.g. homomorphic, isomorphic, complete, consistent (such as tested by consistency proofs), commensurable
 * Metasystems and supersystems are formed out of systems of relationships
 * 13 – paradigmatic
 * Fit metasystems together to form new paradigms
 * Synthesize metasystems
 * Paradigms are formed out of multiple metasystems
 * 14 – cross-paradigmatic
 * Fit paradigms together to form new fields
 * Form new fields by crossing paradigms
 * New fields are formed out of multiple paradigms
 * }
 * 12 – metasystematic
 * Construct multi-systems and metasystems out of disparate systems
 * Create metasystems out of systems; compare systems and perspectives; name properties of systems: e.g. homomorphic, isomorphic, complete, consistent (such as tested by consistency proofs), commensurable
 * Metasystems and supersystems are formed out of systems of relationships
 * 13 – paradigmatic
 * Fit metasystems together to form new paradigms
 * Synthesize metasystems
 * Paradigms are formed out of multiple metasystems
 * 14 – cross-paradigmatic
 * Fit paradigms together to form new fields
 * Form new fields by crossing paradigms
 * New fields are formed out of multiple paradigms
 * }
 * New fields are formed out of multiple paradigms
 * }

Relationship with Piaget's theory
There are some commonalities between the Piagetian and Commons' notions of stage and many more things that are different. In both, one finds: Higher-order actions defined in terms of lower-order actions. This forces the hierarchical nature of the relations and makes the higher-order tasks include the lower ones and requires that lower-order actions are hierarchically contained within the relative definitions of the higher-order tasks. Higher-order of complexity actions organize those lower-order actions. This makes them more powerful. Lower-order actions are organized by the actions with a higher order of complexity, i.e., the more complex tasks.

What Commons et al. (1998) have added includes: Higher order of complexity actions organize those lower-order actions in a non-arbitrary way.

This makes it possible for the Model's application to meet real world requirements, including the empirical and analytic. Arbitrary organization of lower order of complexity actions, possible in the Piagetian theory, despite the hierarchical definition structure, leaves the functional correlates of the interrelationships of tasks of differential complexity formulations ill-defined.

Moreover, the model is consistent with the neo-Piagetian theories of cognitive development. According to these theories, progression to higher stages or levels of cognitive development is caused by increases in processing efficiency and working memory capacity. That is, higher-order stages place increasingly higher demands on these functions of information processing, so that their order of appearance reflects the information processing possibilities at successive ages (Demetriou, 1998).

The following dimensions are inherent in the application:
 * 1) Task and performance are separated.
 * 2) All tasks have an order of hierarchical complexity.
 * 3) There is only one sequence of orders of hierarchical complexity.
 * 4) Hence, there is structure of the whole for ideal tasks and actions.
 * 5) There are transitional gaps between the orders of hierarchical complexity.
 * 6) Stage is defined as the most hierarchically complex task solved.
 * 7) There are discrete gaps in Rasch Scaled Stage of Performance.
 * 8) Performance stage is different task area to task area.
 * 9) There is no structure of the whole—horizontal decaláge—for performance. It is not inconsistency in thinking within a developmental stage. Decaláge is the normal modal state of affairs.

Orders and corresponding stages
The MHC specifies 15 orders of hierarchical complexity and their corresponding stages, showing that each of Piaget's substages, in fact, are robustly hard stages. Commons also adds four postformal stages: Systematic stage 11, Metasystematic stage 12, Paradigmatic stage 13, and Crossparadigmatic stage 14. It may be the Piaget's consolidate formal stage is the same as the systematic stage. There is one other difference in the orders and stages. At the suggestion of Biggs and Biggs, the sentential stage 5 was added. The sequence is as follows: (0) computory, (1) sensory & motor, (2) circular sensory-motor, (3) sensory-motor, (4) nominal, the new (5) sentential, (6) preoperational, (7) primary, (8) concrete, (9) abstract, (10) formal, and the four postformal: (11) systematic, (12) metasystematic, (13) paradigmatic, and (14) cross-paradigmatic. The first four stages (0–3) correspond to Piaget's sensorimotor stage at which infants and very young children perform. The sentential stage was added at Fischer's suggestion (1981, personal communication) citing Biggs & Collis (1982). Adolescents and adults can perform at any of the subsequent stages. MHC stages 4 through 5 correspond to Piaget's pre-operational stage; 6 through 8 correspond to his concrete operational stage; and 9 through 11 correspond to his formal operational stage.

The three highest stages in the MHC are not represented in Piaget's model. These stages from the Model of Hierarchical Complexity have extensively influenced the field of Positive Adult Development. Few individuals perform at stages above formal operations. More complex behaviors characterize multiple system models. Some adults are said to develop alternatives to, and perspectives on, formal operations. They use formal operations within a "higher" system of operations and transcend the limitations of formal operations. In any case, these are all ways in which these theories argue for and present converging evidence that some adults are using forms of reasoning that are more complex than formal operations with which Piaget's model ended.

Empirical research using the model
The MHC has a broad range of applicability. The mathematical foundation of the model makes it an excellent research tool to be used by anyone examining task performance that is organized into stages. It is designed to assess development based on the order of complexity which the individual utilizes to organize information. The MHC offers a singular mathematical method of measuring stages in any domain because the tasks presented can contain any kind of information. The model thus allows for a standard quantitative analysis of developmental complexity in any cultural setting. Other advantages of this model include its avoidance of mentalistic or contextual explanations, as well as its use of purely quantitative principles which are universally applicable in any context.

The following can use the Model of Hierarchical Complexity to quantitatively assess developmental stages:
 * Cross-cultural developmentalists;
 * Animal developmentalists;
 * Evolutionary psychologists;
 * Organizational psychologists;
 * Developmental political psychologists;
 * Learning theorists;
 * Perception researchers;
 * History of science historians;
 * Educators;
 * Therapists;
 * Anthropologists.

The following list shows the large range of domains to which the Model has been applied. In one representative study, Commons, Goodheart, and Dawson (1997) found, using Rasch (1980) analysis, that hierarchical complexity of a given task predicts stage of a performance, the correlation being r = 0.92. Correlations of similar magnitude have been found in a number of the studies.

List of examples
List of examples of tasks studied using the Model of Hierarchical Complexity or Fischer’s Skill Theory (1980):
 * Algebra (Commons, in preparation)
 * Animal stages (Commons & Miller, 2004)
 * Atheism (Commons-Miller, 2005)
 * Attachment and Loss (Commons, 1991; Miller & Lee, 2000)
 * Balance beam and pendulum (Commons, Goodheart, & Bresette, 1995; Commons, Pekker, et al., 2007)
 * Contingencies of reinforcement (Commons, in preparation)
 * Counselor stages (Lovell, 2004)
 * Empathy of Hominids (Commons & Wolfsont, 2002)
 * Epistemology (Kitchener & King, 1990; Kitchener & Fischer, 1990)
 * Evaluative reasoning (Dawson, 2000)
 * Four Story problem (Commons, Richards & Kuhn, 1982; Kallio & Helkama, 1991)
 * Good Education (Dawson-Tunik, 2004)
 * Good Interpersonal (Armon, 1989)
 * Good Work (Armon, 1993)
 * Honesty and Kindness (Lamborn, Fischer & Pipp, 1994)
 * Informed consent (Commons & Rodriguez, 1990, 1993; Commons, Goodheart, Rodriguez, & Gutheil, 2006; Commons, Rodriguez, Adams, Goodheart, Gutheil, & Cyr, 2007).
 * Language stages (Commons, et al., 2007)
 * Leadership before and after crises (Oliver, 2004)
 * Loevinger's Sentence Completion task (Cook-Greuter, 1990)
 * Moral Judgment (Armon & Dawson, 1997; Dawson, 2000)
 * Music (Beethoven) (Funk, 1989)
 * Orienteering (Commons, in preparation)
 * Physics tasks (Inhelder & Piaget, 1958)
 * Political development (Sonnert & Commons, 1994)
 * Relationships (Armon, 1984a, 1984b)
 * Report patient's prior crimes (Commons, Lee, Gutheil, et al., 1995)
 * Social perspective-taking (Commons & Rodriguez, 1990; 1993)
 * Spirituality (Miller & Cook-Greuter, 2000)
 * Tool Making of Hominids (Commons & Miller 2002)
 * Views of the Agood life@ (Armon, 1984c; Danaher, 1993; Dawson, 2000; Lam, 1995)
 * Workplace culture (Commons, Krause, Fayer, & Meaney, 1993)
 * Workplace organization (Bowman, 1996a, 1996b)
 * Writing (Commons & DeVos, 1985)

Literature

 * Armon, C. (1984a). Ideals of the good life and moral judgment: Ethical reasoning across the life span. In M.L. Commons, F.A. Richards, & C. Armon (Eds.), Beyond formal operations: Vol. 1. Late adolescent and adult cognitive development (pp. 357–380). New York: Praeger.
 * Armon, C. (1984c). Ideals of the good life and moral judgment: Evaluative reasoning in children and adults. Moral Education Forum, 9(2).
 * Armon, C. (1989). Individuality and autonomy in adult ethical reasoning. In M.L. Commons, J.D. Sinnott, F.A. Richards, & C. Armon (Eds.), Adult development, Vol. 1. Comparisons and applications of adolescent and adult developmental models, (pp. 179–196). New York: Praeger.
 * Armon, C. (1993). The nature of good work: A longitudinal study. In J. Demick & P.M. Miller (Eds.), Development in the workplace (pp. 21–38). Hillsdale, NJ: Erlbaum.
 * Armon, C. & Dawson, T.L. (1997). Developmental trajectories in moral reasoning across the life-span. Journal of Moral Education, 26, 433–453.
 * Biggs, J. & Collis, K. (1982). A system for evaluating learning outomes: The SOLO Taxonomy. New York: Academic Press.
 * Bowman, A.K. (1996b). Examples of task and relationship 4b, 5a, 5b statements for task performance, atmosphere, and preferred atmosphere. In M.L. Commons, E.A. Goodheart, T.L. Dawson, P.M. Miller, & D.L. Danaher, (Eds.) The general stage scoring system (GSSS). Presented at the Society for Research in Adult Development, Amherst, MA.
 * Commons, M.L. (1991). A comparison and synthesis of Kohlberg's cognitive-developmental and Gewirtz's learning-developmental attachment theories. In J.L. Gewirtz & W.M. Kurtines (Eds.), Intersections with attachment (pp. 257–291). Hillsdale, NJ: Erlbaum.
 * Commons, M.L., Goodheart, E.A., & Bresette, L.M. with Bauer, N.F., Farrell, E.W., McCarthy, K.G., Danaher, D.L., Richards, F.A., Ellis, J.B., O'Brien, A.M., Rodriguez, J.A., and Schraeder, D. (1995). Formal, systematic, and metasystematic operations with a balance-beam task series: A reply to Kallio's claim of no distinct systematic stage. Adult Development, 2 (3), 193–199.
 * Commons, M.L., Goodheart, E.A., & Dawson T.L. (1997). Psychophysics of Stage: Task Complexity and Statistical Models. Paper presented at the International Objective Measurement Workshop at the Annual Conference of the American Educational Research Association, Chicago, IL.
 * Commons, M.L., Goodheart, E.A., Pekker, A., Dawson, T.L., Draney, K., & Adams, K.M. (2007). Using Rasch scaled stage scores to validate orders of hierarchical complexity of balance beam task sequences. In E.V. Smith, Jr. & R.M. Smith (Eds.). Rasch measurement: Advanced and specialized applications (pp. 121–147). Maple Grove, MN: JAM Press.
 * Commons, M.L., Goodheart, E.A., Rodriguez, J.A., Gutheil, T.G. (2006). Informed Consent: Do you know it when you see it? Psychiatric Annals, June, 430–435.
 * Commons, M.L., Krause, S.R., Fayer, G.A., & Meaney, M. (1993). Atmosphere and stage development in the workplace. In J. Demick & P.M. Miller (Eds.). Development in the workplace (pp. 199–220). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
 * Commons, M.L., Lee, P., Gutheil, T.G., Goldman, M., Rubin, E. & Appelbaum, P.S. (1995). Moral stage of reasoning and the misperceived "duty" to report past crimes (misprision). International Journal of Law and Psychiatry, 18(4), 415–424.
 * Commons, M.L., & Miller, P.A. (2001). A quantitative behavioral model of developmental stage based upon hierarchical complexity theory. Behavior Analyst Today, 2(3), 222–240.
 * Commons, M.L., Miller, P.M. (2002). A complete theory of human evolution of intelligence must consider stage changes: A commentary on Thomas Wynn's Archeology and Cognitive Evolution. Behavioral and Brain Sciences. 25(3), 404–405.
 * Commons, M.L., & Miller, P.M. (2004). Development of behavioral stages in animals. In Marc Bekoff (Ed.). Encyclopedia of animal behavior. (pp. 484–487). Westport, CT: Greenwood Publishing Group.
 * Commons, M.L., & Pekker, A. (2007). Hierarchical Complexity: A Formal Theory. Manuscript submitted for publication.
 * Commons, M.L., & Richards, F.A. (1984a). A general model of stage theory. In M.L. Commons, F.A. Richards, & C. Armon (Eds.), Beyond formal operations: Vol. 1. Late adolescent and adult cognitive development (pp. 120–140). New York: Praeger.
 * Commons, M.L., & Richards, F.A. (1984b). Applying the general stage model. In M.L. Commons, F.A. Richards, & C. Armon (Eds.), Beyond formal operations: Vol. 1. Late adolescent and adult cognitive development (pp. 141–157). New York: Praeger.
 * Commons, M.L., Richards, F.A., & Kuhn, D. (1982). Systematic and metasystematic reasoning: A case for a level of reasoning beyond Piaget's formal operations. Child Development, 53, 1058–1069.
 * Commons, M.L., Rodriguez, J.A. (1990). AEqual access" without "establishing" religion: The necessity for assessing social perspective-taking skills and institutional atmosphere. Developmental Review, 10, 323–340.
 * Commons, M.L., Rodriguez, J.A. (1993). The development of hierarchically complex equivalence classes. Psychological Record, 43, 667–697.
 * Commons, M.L., Rodriguez, J.A. (1990). "Equal access" without "establishing" religion: The necessity for assessing social perspective-taking skills and institutional atmosphere. Developmental Review, 10, 323–340.
 * Commons, M.L., Trudeau, E.J., Stein, S.A., Richards, F.A., & Krause, S.R. (1998). Hierarchical Complexity of Tasks Shows the Existence of Developmental Stages. Developmental Review, 8(3), 237–278.
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 * Commons-Miller, N.H.K. (2005). The stages of atheism. Paper presented at the Society for Research in Adult Development, Atlanta, GA.
 * Cook-Greuter, S.R. (1990). Maps for living: Ego-development theory from symbiosis to conscious universal embeddedness. In M.L. Commons, J.D. Sinnott, F.A. Richards, & C. Armon (Eds.). Adult Development: Vol. 2, Comparisons and applications of adolescent and adult developmental models (pp. 79–104). New York: Praeger.
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 * Danaher, D. (1993). Sex role differences in ego and moral development: Mitigation with maturity. Unpublished dissertation, Harvard Graduate School of Education.
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 * Dawson Tunik, T.L. (2004). "A good education is" The development of evaluative thought across the life span. Genetic, Social, and General Psychology Monographs, 130, 4–112.
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 * Funk, J.D. (1989). Postformal cognitive theory and developmental stages of musical composition. In M.L. Commons, J.D. Sinnott, F.A. Richards & C. Armon (Eds.), Adult Development: (Vol. 1) Comparisons and applications of developmental models (pp. 3–30). Westport, CT: Praeger.
 * Inhelder, B., & Piaget, J. (1958). The growth of logical thinking from childhood to adolescence: An essay on the development of formal operational structures. (A. Parsons, & S. Seagrim, Trans.). New York: Basic Books (originally published 1955).
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 * Kitchener, K.S., & King, P.M. (1990). Reflective judgement: Ten years of research. In M.L. Commons, C. Armon, L. Kohlberg, F.A. Richards, T.A. Grotzer, & J.D. Sinnott (Eds.), Beyond formal operations: Vol. 2. Models and methods in the study of adolescent and adult thought (pp. 63–78). New York: Praeger.
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 * Rasch, G. (1980). Probabilistic model for some intelligence and attainment tests. Chicago: University of Chicago Press.
 * Sonnert, G., & Commons, M.L. (1994). Society and the highest stages of moral development. Politics and the Individual, 4(1), 31–55.