DSRP is a theory and method of thinking, developed by systems theorist and cognitive scientist Derek Cabrera. It is an acronym that stands for Distinctions, Systems, Relationships, and Perspectives. Cabrera posits that these four patterns underlie all cognition, that they are universal to the process of structuring information, and that people can improve their thinking skills by learning to use the four elements explicitly.^[1]

Cabrera distinguishes between the DSRP theory and the DSRP method. The theory is the mathematical formalism and philosophical underpinnings, while the method is the set of tools and techniques people use in real life settings (notably in education).

History

DSRP was first described by Derek Cabrera in the book Remedial Genius.^[2]: 13 In later writings, Cabrera describes D, S, R, and P as "patterns of thinking", and expands upon the implications of these thinking skills.^[3][4] The DSRP theory is a mathematical formalism of systems thinking and cognition, built on the philosophical underpinnings of constructivism and evolutionary epistemology. The DSRP method is used in education and has influenced educational reform as well as in management of learning organizations.^[5]

In 2008, a special section of the journal Evaluation and Program Planning was dedicated to examining the DSRP theory and method.^[6]

The 2015 self-published book Systems Thinking Made Simple is an updated treatment of DSRP.^[7][8]

DSRP theory

DSRP consists of four interrelated structures (or patterns), and each structure has two opposing elements. The structures and their elements are:^[9]

• Making Distinctions – which consist of an identity and an other
• Organizing Systems – which consist of part and whole
• Recognizing Relationships – which consist of action and reaction
• Taking Perspectives – which consist of point and view

There are several rules governing DSRP:^[10]

1. Each structure (D, S, R, or P) implies the existence of the other three structures.
2. Each structure implies the existence of its two elements and vice versa.
3. Each element implies its opposite (e.g. identity implies other).

These rules illustrate that DSRP is a modular, fractal, nonlinear, complex systems process. The four DSRP structures do not occur in a stepwise, linear process but in a highly interdependent, complex way.

DSRP theory states that these four structures are inherent in every piece of knowledge and are universal to all human thinking, and that any piece of information can be viewed using each of these structures to gain a deeper understanding of that information. The order in which the operations take place does not matter, as all four occur simultaneously.^[11]

Gerald Midgley pointed out that the structures of DSRP have analogues in other systems theories: distinctions are analogous to the boundaries of Werner Ulrich's boundary critique; Stafford Beer's viable system model explores nested systems (parts and wholes) in ways analogous to the "S" of DSRP; Jay Wright Forrester's system dynamics is an exploration of relationships; and soft systems methodology explores perspectives.^[12]: 318

Formula

The primary application of the DSRP theory is through its various methodological tools but the theory itself is a mathematical formalism that contributes to the fields of evolutionary epistemology and cognition. The formal theory states that DSRP are simple rules in a complex adaptive system that yields systems thinking:

${\displaystyle {ST}_{n}={\underset {info}{\oplus }}{\underset {j\leq n}{\otimes }}{\left\{:{D}_{o}^{i}\circ {S}_{w}^{p}\circ {R}_{r}^{a}\circ {P}_{v}^{\rho }:\right\}}_{j}}$

The equation explains that autonomous agents (information, ideas or things) following simple rules (D,S,R,P) with their elemental pairs (i-o, p-w, a-r, ρ-v) in nonlinear order (:) and with various co-implications of the rules (○), the collective dynamics of which over a time series j to n leads to the emergence of what we might refer to as systems thinking (ST).

The elements of each of the four patterns follow a simple underlying logic as do the interactions between patterns. This logic underlies the unique ability of DSRP to be characterized as multivalent, but contain within it bivalency.

${\displaystyle P:=\left({e}_{1}\leftrightarrow {e}_{2}\right)}$	A Pattern is defined as element1 co-implying an element2
An element1 exists	An element2 exists	element1 co-implies element2	A Pattern exists
${\displaystyle {e}_{1}}$	${\displaystyle {e}_{2}}$	${\displaystyle \left({e}_{1}\leftrightarrow {e}_{2}\right)}$	${\displaystyle$ :=P}

${\displaystyle D:=\left({i}\leftrightarrow {o}\right)}$	A Distinction is defined as identity co-implying an other
An identity exists	An other exists	identity co-implies other	A Distinction exists
${\displaystyle {i}}$	${\displaystyle {o}}$	${\displaystyle \left({i}\leftrightarrow {o}\right)}$	${\displaystyle$ :=D}

${\displaystyle S:=\left({p}\leftrightarrow {w}\right)}$	A System is defined a whole co-implying a part(s)
A whole exists	A part exists	whole co-implies part	A System exists
${\displaystyle {w}}$	${\displaystyle {p}}$	${\displaystyle \left({w}\leftrightarrow {p}\right)}$	${\displaystyle$ :=S}

${\displaystyle R:=\left({a}\leftrightarrow {r}\right)}$	A Relationship is defined as an action co-implying a reaction
An action exists	A reaction exists	action co-implies reaction	A Relationship exists
${\displaystyle {a}}$	${\displaystyle {r}}$	${\displaystyle \left({a}\leftrightarrow {r}\right)}$	${\displaystyle$ :=R}

${\displaystyle P:=\left(\rho \leftrightarrow {v}\right)}$	A Perspective is defined as a point co-implying a view
A point exists	A view exists	point co-implies view	A Perspective exists
${\displaystyle {\rho }}$	${\displaystyle {v}}$	${\displaystyle \left(\rho \leftrightarrow {v}\right)}$	${\displaystyle$ :=P}

${\displaystyle \intercal \left(D\vee S\vee R\vee P\right)\rightarrow \left(D\wedge S\wedge R\wedge P\right)}$	The existence of D or S or R or P implies the existence of D and S and R and P
If D or S or R or P exists	Then D and S and R and P exists	One Pattern implies all the Patterns
${\displaystyle \left(D\vee S\vee R\vee P\right)}$	${\displaystyle \left(D\wedge S\wedge R\wedge P\right)}$	${\displaystyle \intercal \left(D\vee S\vee R\vee P\right)\rightarrow \left(D\wedge S\wedge R\wedge P\right)}$

DSRP method

DSRP as a method is built upon two premises: first, that humans build knowledge, with knowledge and thinking being in a continuous feedback loop (e.g., constructivism), and second, that knowledge changes (e.g., evolutionary epistemology).^{[4]: 19–21} The DSRP method builds upon this constructivist view of knowledge by encouraging users to physically and graphically examine information. Users take concepts and model them with physical objects or diagrams. These objects are then moved around and associated in different ways to represent some piece of information, or content, and its context in terms of distinctions, systems, relationships, or perspectives. Once a concept has been modeled and explored using at least one of the four elements of DSRP, the user goes back to see if the existing model is sufficient for his or her needs, and if not, chooses another element and explores the concept using that. This process is repeated until the user is satisfied with the model.^[13]

The DSRP method has several parts, including mindset, root lists, guiding questions, tactile manipulatives, and DSRP diagrams.

Educational outcomes

With continued use, the method is supposed to improve six specific types of thinking skills:^[11]

• Critical thinking improves as people learn to examine the reasoning behind the distinctions they draw and the perspectives and relationships that influence how information is presented
• Creative thinking improves as people make connections (i.e. relationships) between new pieces of information.
• Systems thinking improves as one becomes increasingly fluent with all four elements of DSRP.
• Interdisciplinary thinking improves as people reconsider boundaries (i.e. distinctions) and make connections between new pieces of information.
• Scientific thinking improves as people learn to analyze information in a logical way.
• Emotional intelligence and prosocial behavior improves as people learn to take multiple perspectives—particularly to imagine the perspectives of other people.

In addition, the DSRP method is supposed to improve teacher effectiveness.

Applications

Cabrera claims that DSRP theory, as a mathematical and epistemological formalism, and the DSRP method, as a set of cognitive tools, is universally applicable to any field of knowledge.^[1]

Criticism

Not all experts agree that DSRP is definitive of systems thinking, as Cabrera claims. Gerald Midgley has argued that the "DSRP pattern that Cabrera et al. propose is an interpretation imposed on other perspectives, and they are prepared to dismiss concepts in those perspectives that do not fit."^[12]: 318 Midgley argued for pragmatic methodological pluralism against unification, and he advised: "Rather than seeking to rationalise the systems thinking field, arguably they [Cabrera et al.] would be better off acknowledging that theirs is one perspective amongst many. It is then up to them to argue its coherence and utility while still keeping the door open to insights from other perspectives."^{[12]: 319–320}

See also

References

Further reading

• Arnopoulos, Paris (2005) [1993]. Sociophysics: cosmos and chaos in nature and culture (2nd ed.). Hauppauge, NY: Nova Science Publishers. ISBN 978-1590339671. OCLC 54501389.
• Basseches, Michael (1980). "Dialectical schemata: a framework for the empirical study of the development of dialectical thinking". Human Development. 23 (6): 400–421. doi:10.1159/000272600.
• Basseches, Michael (1984). Dialectical thinking and adult development. Publications for the advancement of theory and history in psychology. Vol. 3. Norwood, NJ: Ablex Publishing. ISBN 978-0893910174. OCLC 10532903.
• Benack, Suzanne; Basseches, Michael; Swan, Thomas (1989). "Dialectical thinking and adult creativity". In Torrance, E. Paul; Glover, John A.; Ronning, Royce R; Reynolds, Cecil R. (eds.). Handbook of creativity. Perspectives on individual differences. New York: Plenum Press. pp. 199–208. doi:10.1007/978-1-4757-5356-1_12. ISBN 978-0306431609. OCLC 20012005.
• Böttcher, Florian; Meisert, Anke (February 2011). "Argumentation in science education: a model-based framework". Science & Education. 20 (2): 103–140. Bibcode:2011Sc&Ed..20..103B. doi:10.1007/s11191-010-9304-5. S2CID 119954511.
• Bunge, Mario Augusto (2012). Evaluating philosophies. Boston studies in the philosophy of science. Vol. 295. New York: Springer Verlag. doi:10.1007/978-94-007-4408-0. ISBN 9789400744073. OCLC 806947226.
• Chu, Dominique (February 2011). "Complexity: against systems" (PDF). Theory in Biosciences. 130 (3): 229–245. doi:10.1007/s12064-011-0121-4. PMID 21287293. S2CID 14903039.
• Dewey, John (1998) [1933]. How we think: a restatement of the relation of reflective thinking to the educative process (Revised ed.). Boston: Houghton Mifflin. ISBN 978-0395897546. OCLC 38878663.
• Dewey, John (1938). Logic: the theory of inquiry. New York: Henry Holt and Company. ISBN 9780030052507. OCLC 229987.
• Dewey, John; Bentley, Arthur Fisher (1949). Knowing and the known (PDF). Boston: Beacon Press. OCLC 1435965. Archived from the original (PDF) on 2016-04-08. Retrieved 2016-03-18.
• Ferreira, J. Soeiro (June 2013). "Multimethodology in metaheuristics" (PDF). Journal of the Operational Research Society. 64 (6): 873–883. doi:10.1057/jors.2012.88. S2CID 1170426.
• Hicks, Michael J. (2004) [1991]. Problem solving and decision making: hard, soft and creative approaches (2nd ed.). London; New York: Thomson. ISBN 9781861526175. OCLC 55852024.
• Hogan, Michael J.; Harney, Owen M.; Broome, Benjamin J. (2014). "Integrating argument mapping with systems thinking tools: advancing applied systems science". In Okada, Alexandra; Buckingham Shum, Simon J.; Sherborne, Tony (eds.). Knowledge cartography: software tools and mapping techniques. Advanced information and knowledge processing (2nd ed.). New York: Springer Verlag. pp. 401–421. doi:10.1007/978-1-4471-6470-8_18. ISBN 9781447164692. OCLC 890438015.
• Holman, Peggy; Devane, Tom; Cady, Steven, eds. (2007) [1999]. The change handbook: the definitive resource on today's best methods for engaging whole systems (2nd ed.). San Francisco: Berrett-Koehler. ISBN 9781576753798. OCLC 66527256.
• Hovmand, Peter S. (2014). Community based system dynamics. New York: Springer Verlag. doi:10.1007/978-1-4614-8763-0. ISBN 978-1461487623. OCLC 857646084.
• Huff, Anne Sigismund, ed. (1990). Mapping strategic thought. Chichester, UK; New York: Wiley. ISBN 978-0471926320. OCLC 20722225.
• Jordan, Thomas (2014). "Deliberative methods for complex issues: a typology of functions that may need scaffolding". Group Facilitation: A Research and Applications Journal (13): 50–71.
• Jordan, Thomas; Andersson, Pia; Ringnér, Helena (February 2013). "The spectrum of responses to complex societal issues: reflections on seven years of empirical inquiry". Integral Review. 9 (1): 34–70.
• Mathewson, James H. (April 2005). "The visual core of science: definition and applications to education". International Journal of Science Education. 27 (5): 529–548. Bibcode:2005IJSEd..27..529M. doi:10.1080/09500690500060417. S2CID 145376815.
• Mathewson, James H. (January 1999). "Visual-spatial thinking: an aspect of science overlooked by educators". Science Education. 83 (1): 33–54. Bibcode:1999SciEd..83...33M. doi:10.1002/(SICI)1098-237X(199901)83:1<33::AID-SCE2>3.0.CO;2-Z.
• Midgley, Gerald; Cavana, Robert Y.; Brocklesby, John; Foote, Jeff L.; Wood, David R. R.; Ahuriri-Driscoll, Annabel (August 2013). "Towards a new framework for evaluating systemic problem structuring methods". European Journal of Operational Research. 229 (1): 143–154. doi:10.1016/j.ejor.2013.01.047.
• Mingers, John; Rosenhead, Jonathan, eds. (2001) [1989]. Rational analysis for a problematic world revisited: problem structuring methods for complexity, uncertainty and conflict (2nd ed.). Chichester, UK; New York: John Wiley & Sons. ISBN 978-0471495239. OCLC 46601256.
• Mingers, John; Rosenhead, Jonathan (February 2004). "Problem structuring methods in action". European Journal of Operational Research. 152 (3): 530–554. doi:10.1016/S0377-2217(03)00056-0.
• Passmore, Cynthia; Gouvea, Julia Svoboda; Giere, Ronald N. (2014). "Models in science and in learning science: focusing scientific practice on sense-making". In Matthews, Michael R. (ed.). International handbook of research in history, philosophy and science teaching. New York: Springer Verlag. pp. 1171–1202. doi:10.1007/978-94-007-7654-8_36. ISBN 9789400776531. OCLC 889928527.
• Pepper, Stephen C. (1942). World hypotheses: a study in evidence. Berkeley: University of California Press. ISBN 978-0520009943. OCLC 4025805.
• Rajagopalan, Raghav; Midgley, Gerald (September 2015). "Knowing differently in systemic intervention". Systems Research and Behavioral Science. 32 (5): 546–561. doi:10.1002/sres.2352. S2CID 62832672.
• Reynolds, Martin; Holwell, Sue, eds. (2010). Systems approaches to managing change: a practical guide. London; New York: Springer Verlag. Bibcode:2010satm.book.....R. doi:10.1007/978-1-84882-809-4. ISBN 9781848828087. OCLC 428028266.
• Sterman, John D. (Winter 2002). "All models are wrong: reflections on becoming a systems scientist". System Dynamics Review. 18 (4): 501–531. doi:10.1002/sdr.261.
• Straus, David (2002). "The 64 heuristics". How to make collaboration work: powerful ways to build consensus, solve problems, and make decisions. San Francisco: Berrett-Koehler. pp. 219–221. ISBN 978-1576751282. OCLC 49350877.
• Stroh, David Peter (2015). Systems thinking for social change: a practical guide to solving complex problems, avoiding unintended consequences, and achieving lasting results. White River Junction, VT: Chelsea Green Pub. ISBN 9781603585804. OCLC 908375619.
• Teller, Paul (December 2001). "Twilight of the perfect-model model". Erkenntnis. 55 (3): 393–415. CiteSeerX 10.1.1.201.9410. doi:10.1023/A:1013349314515. S2CID 117071231.
• Treagust, David F.; Tsui, Chi-Yan, eds. (2013). Multiple representations in biological education. Models and modeling in science education. Vol. 7. New York: Springer Verlag. doi:10.1007/978-94-007-4192-8. ISBN 9789400741911. OCLC 818463586.
• Veldhuis, Guido Arjan; Scheepstal, Peter van; Rouwette, Etiënne; Logtens, Tom (June 2015). "Collaborative problem structuring using MARVEL". EURO Journal on Decision Processes. 3 (3–4): 249–273. doi:10.1007/s40070-015-0045-1. S2CID 108617231.
• Winther, Rasmus Grønfeldt (December 2012). "Interweaving categories: styles, paradigms, and models". Studies in History and Philosophy of Science Part A. 43 (4): 628–639. doi:10.1016/j.shpsa.2012.07.005.
• Winther, Rasmus Grønfeldt (February 2011). "Part–whole science". Synthese. 178 (3): 397–427. doi:10.1007/s11229-009-9647-0. S2CID 18372542.
• Yearworth, Mike; White, Leroy (September 2014). "The non-codified use of problem structuring methods and the need for a generic constitutive definition". European Journal of Operational Research. 237 (3): 932–945. doi:10.1016/j.ejor.2014.02.015. hdl:10871/26098. S2CID 30180206.

External links

• Cabrera Research Lab