STELLA (short for Systems Thinking, Experimental Learning Laboratory with Animation; also marketed as iThink) is a visual programming language for system dynamics modeling introduced by Barry Richmond in 1985. The program, distributed by isee systems (formerly High Performance Systems) allows users to run models created as graphical representations of a system using four fundamental building blocks. STELLA has been used in academia as a teaching tool and has been utilized in a variety of research and business applications. The program has received positive reviews, being praised in particular for its ease of use and low cost.[3][4][5]
Within that paper, Richmond mused on the study of system dynamics: "If this stuff really is so great, then why hasn't the field 'taken off'?"[11] Steve Peterson, a colleague of Richmond's, reflected after his death in 2002 that Richmond held the belief that modeling was a tool everyone should be using and that that notion was reflected in Richmond's work.[8] He quoted a 1994 paper in which Richmond described STELLA as "quite unique, quite powerful, and quite broadly useful as a way of thinking and or learning. It's also capable of being quite transparent–leveraging the way we learn biology, manage our businesses, or run our personal lives".[8]
Functionality and features
A simple STELLA model of a cat population; stocks are represented as rectangles, flows as pipes to/from the stock, converters as the circles, and connectors as the curved lines with arrows.[12]
STELLA's approach to modeling systems shares some similarities with a precursor, the DYNAMOsimulation language. DYNAMO explicitly defined "stocks" (reservoirs) and "flows" (inputs and outputs) as key variables in a system, a vocabulary that STELLA shares.[9] Within STELLA, users are presented with a graphical user interface in which they may create graphical models of a system using four fundamentals: stocks, flows, converters, and connectors.[13] Relationships between converters (which convey transforming variables) and other elements may be drawn with converters. Users are able to input values for stocks, flows, and converters (including a variety of built-in functions).[14] STELLA does not differentiate between external and intermediate variables within a system; all of them are represented with converters.[15]
The software produces finite difference equations that describe the graphical model and allows users to select a numerical analysis method to apply to the system, either the Euler method or various Runge–Kutta methods (either second or fourth order).[16] Before running a model, users may also specify a time step and runtime for the simulation.[17] STELLA can output data in graphical or tabular forms.[18]
STELLA runs one window at a time, meaning that only one model can be run at any given moment.[4] The program's native file formats are denoted either by an .stm, .stmx, .itm, or .itmxfilename extension. STELLA also uses the emerging XML-based standard for storing models, XMILE.[19] In 2012, two researchers released StellaR, software which can translate STELLA models into the R programming language.[20]
Applications
Education
A STELLA model from a paper on carbon impacts in forest biomass[21]
Because of its simplicity relative to more complex modeling languages, STELLA has been cited as a useful tool in educational settings.[6] Richmond derisively viewed most education as "assimilating content" and proposed systems thinking as a remedy to this.[22]
In 1987, High Performance Systems released a guide to STELLA encouraging its use in academic settings[23] and numerous textbooks have been published that teach modeling and systems thinking using the software.[24][25] Sample exercises with STELLA include recreating the Daisyworld model,[26] simulating the Easter Island population crash,[27] and modeling the protagonist's motivation throughout William Shakespeare's Hamlet.[28]
A 2010 study of the efficacy of project-based learning upon a watershed-modeling project undertaken by 72 middle schoolers found that the addition of a STELLA modeling component in the project improved overall comprehension of the material over traditional methods, especially among female students who outperformed their male counterparts with the addition of STELLA.[29]
Academia and commerce
The software is also used in research settings. Among other projects, researchers have used STELLA to apply Hubbert peak theory to the Chinese coal supply,[30] to model atrazine dynamics within agricultural lands,[31] and to simulate the interactions between marine macroinvertebrates.[32]
isee systems[a] markets an identical software targeted at business consumers under the name iThink (previously STELLA for Business).[5][33] iThink models have been applied to a variety of systems including manufacturing lines,[13] hospital waste in developing nations,[34] coordination between an emergency room and hospital beds,[35] and competition in the home video market.[5]
Reception
In a 1987 review of the program in BioScience, Robert Costanza wrote that "STELLA is a solid program–well planned and executed–that breaks new ground."[3] He praised its ease of use as beneficial both to beginners interested in learning how to build models and experts who could use it to test components of more complex models.[3] A 1998 review of the program in the Bulletin of the Ecological Society of America concurred that the program was easy to use, especially for beginning modelers, but noted its lack of model optimization tools and the ability to run only one window at a time as drawbacks.[4]
Writing for Complexity in 1997, Benedikt Hallgrímsson found the program's accompanying manual to be overzealous in its promotion of systems theory but cautioned that "the manual need not detract from what is otherwise a very well-thought-out and constructed program."[36]
A 1991 review of iThink in Planning Review noted that the software's strength was in its low cost (the program retailed at around $450 (US$967 in 2022 dollars [37]) and the vast number of possibilities allowed by its open-ended form.[5]
^ abcdCarter, J. (October 1998). "Two Visual Programming Languages for Simulation Modeling: Stella 5.0 and Modelmaker 3.0". Bulletin of the Ecological Society of America. 79 (4): 237–239. doi:10.2307/20168276. JSTOR20168276. S2CID62582639.
^ abcdSamzelius, J. E.; Miller, S. E. (1991). "ithink: Animated Strategic Models on Your Desktop Computer". Planning Review. 19 (1): 32–34. doi:10.1108/eb054316.
^ abDoerr, H. M. (1996). "Stella ten years later: A review of the literature". International Journal of Computers for Mathematical Learning. 1 (2): 201–224. doi:10.1007/BF00571080. S2CID19428296.
^ abde Souza, R.; Huynh, R.; Chandrashekar, M.; Thevenard, D. (October 1996). A comparison of modelling paradigms for manufacturing line. IEEE International Conference on Systems, Man, and Cybernetics, 1996. Beijing. pp. 1253–1258. doi:10.1109/ICSMC.1996.571288.
^Taffe, W. J. (March 1991). Simulation and modelling with Stella: a general education course. 22nd SIGCSE Technical Symposium on Computer Science Education. San Antonio, TX. pp. 87–91. doi:10.1145/107005.107021.
^Hopkins, P. L. (Winter 1992). "Simulating Hamlet in the classroom". System Dynamics Review. 8 (1): 91–98. doi:10.1002/sdr.4260080109.
^Eskrootchi, R.; Oskrochi, G. R. (January 2010). "A Study of the Efficacy of Project-based Learning Integrated with Computer-based Simulation – STELLA". Journal of Educational Technology & Society. 13 (1): 236–245. JSTORjeductechsoci.13.1.236.
^Tao, Z.; Li, M. (June 2007). "What is the limit of Chinese coal supplies—A STELLA model of Hubbert Peak". Energy Policy. 35 (6): 3145–3154. doi:10.1016/j.enpol.2006.11.011.
^Ouyang, Y.; Zhang, J. E.; Lin, D.; Liu, G. D. (March 2010). "A STELLA model for the estimation of atrazine runoff, leaching, adsorption, and degradation from an agricultural land". Journal of Soils and Sediments. 10 (2): 263–271. Bibcode:2010JSoSe..10..263O. doi:10.1007/s11368-009-0107-8. S2CID14407780.
^Gertseva, V. V.; Schindler, J. E.; Gertsev, V. I.; Ponomarev, N. Y.; English, W. R. (August 2004). "A simulation model of the dynamics of aquatic macroinvertebrate communities". Ecological Modelling. 176 (1–2): 173–186. doi:10.1016/j.ecolmodel.2003.10.029.
