Four-C’s of creativity.
\n\n
\n\nThe project work was funded by the European Commission (EC) 7th Framework Programme (FP7), under the 9th Call for projects on Information and Communication Technologies. The publishing of this book was funded by the EC FP7 Post-Grant Open Access Pilot programme. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"63425",title:"Analysis of Seismic Responses of Rock Massif to Explosive Impacts with Using Nonlinear Methods",doi:"10.5772/intechopen.80750",slug:"analysis-of-seismic-responses-of-rock-massif-to-explosive-impacts-with-using-nonlinear-methods",body:'Synergetics is an interdisciplinary science that allows one to imagine the phenomenon of self-organization in the tasks of physics, chemistry, biology, earth sciences, sociology, and other open systems. The term synergetics was proposed in the 1970s by the German physicist Haken [1]. His works had been devoted to the theory of self-organization in various natural systems. At present, important theoretical and experimental results have been obtained, confirming the relevance of synergetic approach for studying the universal properties of open nonequilibrium dynamical systems, cooperative effects in self-organization processes [2]. In recent decades, interest is aimed to study of nonlinear dissipative systems in which a decrease in the number of degrees of freedom that effectively describes them has been observed. Sometimes it is possible to distinguish several degrees of freedom, to which all the others are adjusted. They determine the dynamics of processes and are therefore called order parameters. When studying dissipative systems, their existence allows for a simplified description or construction of an entire hierarchy of simplified models. A decrease in the number of degrees of freedom means that self-organization occurs in the system, i.e., the system has properties that none of the subsystems possesses. To emphasize this circumstance, the theory of self-organization is also called synergetics. The term “dissipative structure” was introduced by I. Prigozin. He and his school helped to establish the connection between the origin of structures, phenomenological models, and representations of nonequilibrium thermodynamics, which played a big role in the theoretical and experimental study of ordering in open systems [3, 4, 5]. Removability from equilibrium and nonlinearity can serve ordering in the system. Between order, stability, and dissipation, a nontrivial relationship arises. Ordered configurations that appear outside the stability region of a thermodynamic branch will be called dissipative structures, which can exist only due to a sufficiently large energy or matter flow. The appearance of order in open nonlinear systems is a paradoxical fact.
In equilibrium systems, dissipative processes destroy any order, and thermodynamic equilibrium is established. In nonlinear open systems, together with other processes, dissipative processes affect the type, form, and size of the dissipative structures. It is known that the geological environment is an open dynamic system that undergoes natural and artificial influences at various scale levels, changing its state, resulting in a complex multi-face hierarchical evolution, which is also one of the subjects of the study of geosynergetics [6, 7, 8, 9, 10]. The large number of geological systems is open and nonequilibrium, which can exist for a long time only in the mode of pumping energy through them. The termination of the energy flow leads the system to transition to the conservation stage, when the duration of existence is determined by its energy potential due to the accumulated energy at the previous stage. A distinctive feature of open geological systems is their irreversibility and multifunctionality. Using the synergetic approach, it is necessary to clearly distinguish the scale of natural phenomena. Thus, the growth of individual crystals obeys the laws of thermodynamics, and already the morphology of crystals clusters’ changes of their forms is determined by the state of the growth medium linked with external influences [11].
Geological environments can be divided into concentrated and dispersed states. Concentrated systems are characterized by their continuity; they represent as a whole on the considered time interval and state by parameters, determining at the first approximation their stationary state. It can be a magmatic chamber, a single fluid system, a block of rocks of a similar composition, a water basin, an oil deposit, or a massive ore body. In concentrated stationary systems, nonequilibrium processes occur aimed for equalizing the thermodynamic parameters characterizing their state. The distributed systems represent a set of autonomous subsystems that are interconnected by heat and mass transfer channels within the framework of irreversible processes, which can be broken down into several stationary states characterized by a constancy of the main control parameters of the process in the chosen time interval. For heterogeneous and complex in composition real geological systems, it is advisable to talk about the equality of not all parameters but only those that determine the macroscopic state of a particular system—its control parameters. In a predominant number of cases, geological systems are non-stationary, since their parameters do not remain unchanged during their existence. The entire development path of such systems is divided into a number of stationary subsystems, characterized by small changes in their parameters at the chosen time interval. Accordingly for each stationary subsystem, a set of stationary processes are fixed in certain structurally real complexes.
At a certain stage of development, an open dynamic system, exchanging matter and energy with the environment, breaks up into a number of subsystems, which in turn can further split into even smaller systems. How to draw boundaries between them if the processes in these systems could take place tens and hundreds of millions of years ago and sometimes billions? The criterion for determining the boundaries of such systems is one of the tasks of synergetics: macroscopic processes in systems where self-organization processes occur in the nonlinear area are carried out cooperatively, in concert and coherently. In the case of geological systems, the boundary will pass along the line of replacement of some structural-material complexes by others, usually mineral aggregates. The basis of the processes of self-organization in open nonequilibrium geological systems is the energy source. If the energy potential does not reach the threshold value, then the processes of self-organization do not occur, but if it is sufficient to compensate for its loss to the external environment, then self-organization processes will appear and spatial–temporal or temporal structures will be formed. The transition of the chaos structure is carried out abruptly. If the energy input into the system is too much, the structuring of the medium stops, and we have a transition to chaos. In any open, dissipative, and nonlinear systems, self-oscillating processes arise, supported by external sources of energy, as a result of which self-organization proceeds [12].
The paradigm of physical mesomechanics introduced by academician Panin V. Y. and his school [13], which includes a synergetic approach, is a constructive tool for studying and changing the state of heterogeneous materials. This result was obtained by this school on samples of various materials. In our studies of the non-stationary geological environment, in the framework of full-scale experiments in real mountain massifs under strong technogenic influence, it was shown that the dynamics of the state can be detected using synergetics in hierarchical environments [14, 15]. An important role in the study of dynamic geological systems is played by a combination of active and passive geophysical monitoring, which can be carried out using electromagnetic and seismic fields. The change in the state of the system on the investigated spatial bases and times is manifested in parameters related to the structural features of the medium of the second and higher rank. Thus, the study of the dynamics of the state and its structure and the phenomenon of self-organization of the array should be led by geophysical methods tuned to the multi-rank hierarchical non-stationary model of the environment [16]. The results obtained from laboratory experiments allowed physicists to propose a model of periodic structural transformations based on a system of nonlinear differential equations that determine the joint evolution of the densities of decaying boundaries, chaotic dislocations, and the boundaries of the emerging structures and also to show that the synergetic scheme allows to describe in a unified way the structurally caused plastic deformation in condensed media [17]. For the fields of plastic deformation and stresses, a system of nonlinear equations is proposed that makes it possible to represent such a regime in agreement with the experimental data. The available results of terrestrial and especially borehole and underground geophysical observations indicate nonlinear manifestations in rock massive during their development.
One of the fundamental problems of mining, which is traditionally attributed to the problems of geomechanics, is the development of theoretical and experimental methods for studying the structure and state of rock massive with a view to predicting and preventing catastrophic phenomena in the mining of deposits. This problem is complicated by the fact that the rock massif is influenced by direct or indirect technogenic impact, which leads to a significant non-stationary of both the structure and the state of it. The ideological inspirer of the search for integrated geophysical and geomechanical approaches to the solution of this problem in the Ural was N. P. Vlokh [18]. An analysis of the manifestations of mountain impacts in the mine workings of the Oktyabrsky deposit of the Norilsk ore site showed that more than 60% of them are confined to tectonic disturbances. Peeling and intensive incineration occur mainly in excavations located outside the zone of influence of clearing works at a distance of 10–12 m from the surface of the tectonic disturbance. In the ores and rocks of medium disturbance, the dynamic phenomena dominate in the areas of interface of the excavations and are accompanied by collapse of the massif. When intersections with excavations of areas of the massif with irregularities have two or more planes of displacement, with a zone of crumpled and fragmented rocks, collapse from the roof and collapses from the sides are observed, accompanied by a dynamic effect and reaching considerable volumes [19]. When conducting mining operations in high-stress rock massive, technogenic seismicity is manifested, with forecasting and prevention issues being given much attention in all countries with a developed mining industry. An important role here belongs to the short-term forecast; the methodology for identifying criteria for it is still a problem, both in mining and in seismology [20]. From the point of view of the paradigm of physical mesomechanics, which includes a synergetic approach to changing the state of rock massive of different material composition, this problem can be solved with the help of monitoring methods tuned to the study of hierarchical structural media [13, 21]. Changes in the environment, leading to short-term precursors of dynamic phenomena, are explained within the framework of the concept of self-organized criticality [17, 20], for which mainly significant moments are heterogeneity and nonlinearity [13].
Within the framework of the IGD SB RAS School, important results have been achieved in studying the state of the rock mass within the framework of nonlinear geomechanics [22] using geophysical methods that have the resolving power to detect the nucleation and decay of self-organizing structures [23].
For the first time, using the electromagnetic method developed in the IGF UB RAS, it was possible to realize the idea of identifying zones of disintegration in an array of rocks within the framework of field studies [24, 25] and to monitor their morphology [26]. The technique used relates to geophysical methods of nondestructive testing. It differs from the previously known methods of semitransparency or tomography by observation systems and the subsequent interpretation method based on the concept of three-stage interpretation [27]. In [28] the first full-scale results on the detection of the self-organization phenomenon in a rock massif with anthropogenic impact and the method of developing stability criteria based on the proposed classification methodology had been represented. These results were obtained on the basis of analysis of several cycles of electromagnetic monitoring of the massif of the shock-dangerous Tashtagol underground mine, conducted in 2000, 2001, 2002, 2003, 2004, and 2005 in a number of excavations located on four horizons at depths from 540 to 750 m in order to reveal the morphology of the zones of disintegration in the near-working space in a rock massif that is under intense man-caused impact and the influence of the natural stress field. In the work [23], studies were conducted aimed at developing criteria for spatial–temporal complex active and passive seismic and electromagnetic monitoring to prevent destructive dynamic phenomena based on 6-year seismic monitoring data conducted by the service of rock shocks in Tashtagol underground mine and the experience gained using the IGF UB RAS systems of induction electromagnetic space–time monitoring on arrays of various material composition before and after mass explosions.
We analyzed the morphology of the structural features of the disintegration zones before a strong dynamic phenomenon during the next cycle of electromagnetic observations at the Tashtagolsky mine during August 2007. On August 9, there was a rock explosion with the energy: lg E = 6.9 in the range of the ort 3 at a level of 16 m below the horizon −280 (Figure 1), N = 108 (Figure 2(a) and (b)). The analysis of the second curve (Figure 1) demonstrates the irregularity of the number of weak dynamic phenomena in the array of the entire mine field with energy lgE < 6 in time. So, after a mass explosion on the same day, 42 phenomena were registered, for the next day, already 17, and then this number in the next day is even more reduced. Before the rock impact, there is a significant rarefaction of the number of dynamic phenomena—a zone of calm. During the day, when there was a rock shock after it, 12 weak dynamic phenomena were observed, similar to how it happened on the third day after the mass explosion.
The distribution of the dynamic phenomena in the Tashtagolsky mine after the mass explosion (N = 1). (Data from the seismological catalog of the Tashtagolsky mine (authors Klimko V. K., Shipeev O. V.)).
Geoelectric sections along the profile ort 4, horizon −210, northwestern section. (a) August 6 and (b) August 8, 2007, frequency: 10.15 kHz. Legend: M˜0i = M0 × L0 × 103, where M0 is the coefficient by which the moment of the electric current line is multiplied by the influence of the zone by the parameter of geoelectrical heterogeneity equivalent over the field and which is proportional to the ratio of the conductivity difference of the disintegration zone to the conductivity of the surrounded medium, L0 is the length of the current line, and the resistance of the section is given in ohms. Vertical values are given in m (absolute marks), horizontal axes and output length in pickets (pc) and meters.
Three days before the rock shock in the ort 4 (Figure 2(a) and (b)) in the geoelectrical sections of the massif, subvertical discrete structures are found, into which disintegration zones have merged. These structures manifested themselves in a resonant mode at different frequencies and only at one frequency for each of the units. We discovered the same phenomenon earlier during one day at the mine Estyuninsky and SUBR (mine15) [21] (Figure 3).
(a–c) Geoelectrical section along profile ort 3, horizon −210, northwestern section. (a) July 9, (b) July 23, and (c) July 26, 2010, frequency: 10.15 kHz. The legend is the same as in the Figure 2(a) and (b).
Regarding Figure 4 we see the comparative data from 2000 to 2007 the distribution of the parameter of the interval intensity Spint (in 2007 the results were given according to the electromagnetic measurements before and after the rock shock) in the bottom of the Ort 2 of the massif, horizon −210 at two frequencies: 5.08 and 20 kHz. According to the classification [29], the state of the array of the Ort 2 was defined as quasi-stable. The obtained results show that, despite the very close location to the site where the rock shock occurred, the massif remains practically in a state described by the gradation quasi-stable. For the period from August 2 to August 13, 2007, the maximum of the parameter Spint moved from the fourth interval (3–4 m) to the first (0–1 m) without increasing its amplitude. The emergence of these structures of subvertical morphology is a forecast of a strong dynamic phenomenon; however, in order to determine the place and magnitude of an event, it is necessary to have information on the state of the arrays and their belonging to the appropriate ranks of stability of the array, as was done in [29].
The distribution of the parameter of the interval intensity Spint for eight observation cycles in the array of Ort 2, horizon −210, Tashtagolsky mine according to active electromagnetic induction monitoring. (a) Observations in 2000–2007 years, frequency 5 kHz. (b) Observations in 2000–2007 years, frequency 20 kHz; 2007 (1) in the legend corresponds to data before rock shock; 2007 (2) in the legend corresponds to data after rock shock. Axes Y-SpintNT=∑iNM˜0iT -parameter of the interval intensity of geoelectrical heterogeneities of the second rank, detected by electromagnetic induction monitoring, where N is the number of the interval into which the soil of near-working space is divided and where M˜0i is the intensity of the disintegration zone and T is the year of observation [14].
Thus, the introduction of the proposed integrated passive and active geophysical monitoring, aimed at studying the transient processes of redistribution of the stress–strain and phase states, can contribute to the prevention of catastrophic dynamic manifestations during the development of deep-located deposits. Methods of active geophysical monitoring should be tuned to a model of a hierarchical heterogeneous medium.
The technology of working out ore deep-lying deposits provides carrying out of preventive and safety control measures. For this purpose, a number of the largest Russian mining enterprises have installed multichannel-automated seismic monitoring systems within the mine fields influenced by underground mining [30]. Analysis of a large database of seismic records of shocks and rock shocks recorded by the Norilsk seismic station at the Norilsk deposit mines using the previously proposed analysis method [31] detects the pulsating seismic energy release from stressed areas of ore and rock massive from the motion of fronts of induced seismicity by the type of oscillating pendulum [32]. In the development of this result, studies were carried out to study the transient process of redistribution of the stressed and phase states of the massif between strong man-made impacts at the Tashtagol underground mine [33]. We studied the parameters of seismological monitoring as the values of the total energy lg (Ev), extracted by the array of a specific development block in the form of dynamic phenomena after each mass explosion, the values of the absorbed array of the same energy block we define as lg (Ep), and the maximum volume of the mine field where the dynamic phenomena occur from the given mass explosion lg (Vmax).
The transient process of energy release by an array in the form of a response to anthropogenic impact is analyzed—a mass or technological explosion for the realization of a particular technological procedure (cutoff, segmenting, compensation, collapse) in the development block. The analysis of the seismic detailed mine catalog data allows us to draw the following conclusions: when working out a specific block of the array, the entire array of the mine field undergoes a change in the stress–strain and phase states from explosion to explosion; the amount of energy absorbed and delivered by the array is not equal to each other, and therefore energy accumulation takes place in the array; the process of energy release occurs with a delay and depends strongly on the gradient of the energy absorbed from mass explosions; in the array there are zones of dynamic calm; these zones should be monitored using seismic monitoring data using the parameters proposed by us; after it is out of the minimum of the lull, it is necessary to conduct a spatial–temporal active electromagnetic or seismic monitoring within a week or 2 weeks before the technological collapse, in order to identify zones of potential instability of the second rank; these zones may be after a mass explosion, timed to collapse by sources of strong dynamic phenomena; and introduction of the proposed integrated passive and active geophysical monitoring aimed at studying the transient processes of the redistribution of the stress–strain and phase states in the system of testing can help prevent catastrophic dynamic manifestations during the development of deep-seated deposits. These conclusions are based on the analysis of seismological data spatially related to the array of a specific processing unit. However, analysis of seismological data shows that strong dynamic phenomena (rock shocks) can occur in a wider area than the actual block of mining and can be initiated with time lags. Within 9 years from 2000 to 2008, in the mine of the Tashtagolsky mine on four horizons in a number of excavations, active electromagnetic induction monitoring was carried out within the framework of the frequency-geometric technique. On the basis of these detailed data and their subsequent interpretation, a method was developed for estimating and classifying an array of near-working space within the limits of developing its stability in three respects relative to strong technogenic impacts during the development of large and super-large deposits. As a result, a positive verification of the site forecast and evaluation of the magnitude of the destructive dynamic phenomenon in the mine of the Tashtagolsky mine were carried out [34]. As the experience of our studies has shown, the change in the state of the system at the investigated spatial bases and times is manifested in parameters related to the structural features of the medium of the second rank. Thus, the study of the dynamics of the state and its structure and the phenomena of self-organization of the array can be conducted by geophysical methods tuned to the multi-rank hierarchical model of the environment. This conclusion satisfies the principles of the paradigm of physical mesomechanics introduced by academician Panin V. E. and his school [13], which are also a constructive tool for studying the state of the non-stationary geological environment, which is an open dynamic system [14, 27, 35]. The use of an in-plane multi-level induction electromagnetic method with a controlled source and an appropriate processing and interpretation technique made it possible to identify disintegration zones that are an indicator of the stability of the array [26]. The introduction of the integral parameter—the intermittent distribution of the intensity of the disintegration zones—allows us to proceed to a detailed classification of the array in terms of the degree of stability, introduces quantitative criteria for this, and characterizes the stability of the array from the viewpoint of reaching the stationary cyclic position of the maximum of the parameter Spint as a function of the distance from the output Zmax. Analysis of the variance from the frequency of Zmax allows us to introduce additional gradations on the stability of the array in its detailed classification. Comparison with the data of seismological monitoring made it possible to carry out the geodynamic classification of the array using the integral parameter Sp [15].
In [35], the possibility of using the mathematical results of the developed physical and mathematical theory of the study of the state of open dynamic conservative and dissipative systems [17, 36] is shown. These include also rock massive during the process of mining. A dynamical system is understood as an object or process for which the concept of a state as a collection of values of certain quantities at a given moment of time is defined and an operator defining the evolution of the initial state in time is specified [36]. If to describe the behavior of a system, it is sufficient to know its state at a finite number of moments of time, and then such a system is called a system with discrete time. As a rule, the control of the state of a rock massif in mines is not continuous but within the framework of observation cycles or at discrete moments of time. To describe its development, differential analogs of differential evolution equations are used. Dynamic systems are divided into conservative and dissipative systems. For the former, the total energy of the system is preserved; for the second, energy losses are possible. In the appendix to our problem, when studying the state of an array that is in the process of working out, the model of the heterogeneous and non-stationary dissipative system is closest. Nevertheless, in the array can be such local parts of it, which will be described by a conservative dynamic model, i.e., model of energy balance. The analysis of the phase portrait of the dynamic system allows us to conclude that the system is characterized during its observation period. So, in conservative systems there are no attracting sets. An attractor is a subset of the phase space ΡN, to which trajectories starting in some neighborhood of it incline with time. If a periodic motion exists in a conservative system, then such motions are infinitely large and are determined by the value of the energy under the initial conditions. Attractive sets can exist in dissipative systems. Stationary undamped oscillations for dissipative dynamical systems are not characteristic. However, in nonlinear systems it is possible to have a periodic asymptotically stable motion, in the mathematical image of which is the limit cycle, represented in phase space by a closed line, to which trajectories from some neighborhood of this line are contracted with time. In terms of the shape of the phase portrait, one can judge the characteristic behavior of the system, and the “smooth” deformations of the phase space do not lead to qualitative changes in the dynamics of the system. This property is called the topological equivalence of phase portraits. It allows you to analyze the behavior of various dynamic systems from a single point of view: on its basis, the set of dynamical systems under consideration can be divided into classes within which systems demonstrate qualitatively similar behavior. From the mathematical point of view, the “smooth deformation” of the phase portrait is a one-to-one and mutually continuous transformation of the phase coordinates, as a result of which new singular points cannot appear, and on the other hand, singular points cannot disappear. The earlier results of the study of the phase state of the rock mass [15] indicate that the classification of the massif with respect to its stability and its further control can be very effectively carried out using the parameter Spint-interval intensity of second-rank heterogeneities or, according to the terminology adopted in geomechanics, the disintegration zones.
In addition, when using the integrated intensity parameter Sp: (
To realize this research, the seismic catalog of the Tashtagol underground mine was used for 2 years from June 2006 to June 2008. As the data, the space–time coordinates of all the dynamic phenomenal responses of the array that occurred during this period inside the mine field, as well as the explosions produced for working out the array, and the value of the energy fixed by the seismic station were used. In our analysis, the entire mine field was divided into two halves: the development of the northwestern section, the areas of the trunks of the western and Novo-Kapital and the outputs from 0 to 14 are designated by us, as the northern section, from 15 to 31 and the southern ventilation and field drifts. The trunk of the southern mine is designated as the southern section. All event responses from horizons −140, −210, −280, and −350 m were taken into account. Explosions were carried out in the southeastern section of mine development at the horizons +70 m, 0 m, −70, on the remaining sections—on the above horizons. As the data, the space–time coordinates of all the dynamic phenomena occurring within the minefield and fixed by the seismic station, as well as their energy characteristics were used.
The phase portraits of the state of the arrays of the northern and southern sections are plotted in the coordinates Ev(t) and d(Ev(t))/dt, where t is the time expressed in fractions of the day and Ev is the seismic energy extracted in the array in joules. In this paper, we will first analyze the morphology of the phase trajectories of the seismic response at various successive intervals of time in the southern section of the mine for two reasons: (1) According to the data on the technological and mass explosions produced (Figure 5), most of the energy was pumped into the southern part of the mine. (2) At the end of 2007, the one of the strongest rock shocks occurred in the history of the mine happened in the southern sector. Figure 6(a)–(h) shows the evolution of the morphology of the phase trajectories of the array response to technogenic impacts from the middle of 2006 to the middle of 2008. Figure 6(c) shows the characteristic morphology of phase trajectories of the response of an array located locally in time in a stable state: there is a local region in the form of a tangle of intertwined trajectories and small outliers from this coil, which do not exceed 105 joules in energy. This same feature is manifested in all the figures presented in Figure 6(d), except that at some intervals this ejection exceeds 105 joules, reaching 106 joules (Figure 6(d) and (e)) and even 109 joules (Figure 6(g)). Since the volume of the array under study is the same and we are studying the process of its activation and decay, obviously, there are two mutually dependent processes: the accumulation of energy in the region attracting the phase trajectories and the resonance discharge of the stored energy (e.g., Figure 6(g)). It is interesting to note that after this reset, the system returns again to the same region attracting the phase trajectories.
Distribution in time of the absorbed seismic energy as a result of working out of an array by technological and mass explosions.Axis OY: D = Σlg (Ep (N)), where N is time intervals in days (OX axis) and Ep is absorbed energy from explosions. Explosions (1) provided in the southern part of the mine; explosions (2) provided in the northern part of the mine.
(a–h) Phase portraits of the array state response in consistent time intervals: (a) 5-24.09-29.09, 4-01.10-13.10, 3-14.10-12.11 2006; (b) 1-14.10-12.11, 2-12.11-18.11, 3-19.11-25.11 2006; (c) 24.12-29.12 2006; (d) 1-01.01-28.01 2007; (e) 1-29.01-31.03, 2-02.04-25.05 2007; (f) 1-02.04-25.05, 2-25.06-19.07, 3-22.07-27.09, 4-27.09-24.11 2007; (g) 1-30.09-24.11, 2-25.11-29.12 2007; (h) 1-29.12 2007-21.04 2008, 2-01.06-05.08 2008. The axis OX is the energy allocated by the array in joules at appropriate intervals. The axis OY: A = aLgf, f=∂E∂t, a = sign ∂E, where t is time in fractions of a day. It is of interest to analyze in more detail the phase trajectories of the seismic response of the array before and after the strongest impact (Figure 7(a)–(c)). The entire process is described by three attractive phase regions: a large number of phase-traversing low-energy region trajectories, which both precede strong energy resonance (Figure 7(b)) and follow after a strong energy resonance (Figure 7(c)).
Phase portrait of the response of the state of the array during one of the most powerful mountain impacts at the Tashtagolsky mine, (a) for a time interval of 25.11-29.12 2007, (b) for a period of time before a rock shock (1), and (c) for a period of time after a rock shock (2). The legend for the axes is the same as in Figure 6.
Comparison of the phase portraits of the response of the state of the array before and after the mountain impacts of different intensity and at different time intervals indicate that the volume selected by us in the form of the southern section reacts to the effect exerted on it, similarly, by reflecting a coherent or joint mechanism for releasing the accumulated energy Figure 8(a-b). The first results obtained from the analysis of a detailed seismological catalog from the point of view of the mathematical foundations of synergetics and open dynamical systems possessing the properties of nonlinearity and dissipativity [2, 17, 20, 38] lead us to the necessity of posing a new mathematical modeling problem different from the one previously performed. If in previous productions, the problem of the transition of a system from an ordered state to chaos was investigated; in our case, for our system, the chaos of a given level is, on the one hand, a stable state for the system. On the other hand, this parameter is the control for the transition of the system to a state with another parameter, which is catastrophic for it. After the realization of this catastrophe, the system again creates a chaos region with a parameter close in value to the first. This process differs from the bifurcation process, because in the space of the distributions of phase trajectories studied by us, there is an attractive point, in the plane, the extracted energy, and the time derivative of the logarithm of the extracted energy. Thus, further study of the detailed seismic catalog will allow us to formulate the criteria for predicting the behavior of the rock mass from the point of view of the mathematical theory of synergetics [36]. This approach can also be used to analyze seismological data at seismological landfills (Figure 8).
Comparison of the phase portraits of the response of the state of the array before and after the mountain impacts of different intensity and at different time intervals in 2007. (a) 1-25.11, 2-01.01-13.01, 3-27.09-11.10. (b) 1-25.11-29.12, 2-13.01-28.01, 3-11.10-24.11. The legend for the axes is the same as in Figures 6 and 7.
At present, theoretical results on the modeling of the electromagnetic and seismic fields in a layered medium with inclusions of a hierarchical structure are in demand. Algorithms for modeling in the electromagnetic case for 3D heterogeneity are constructed, in the seismic case for 2D heterogeneities [39, 40, 41]. It is shown that with increasing degree of hierarchy of the medium, the degree of spatial nonlinearity in the distribution of the components of the seismic and electromagnetic fields increases, which corresponds to the detailed monitoring experiments conducted in the shock-hazard mines of the Tashtagolsky mine and the SUBR. The constructed theory demonstrated how the process of integrating methods that use the electromagnetic and seismic field to study the response of a medium with a hierarchical structure becomes more complicated. This problem is inextricably linked with the formulation and solution of the inverse problem for the propagation of electromagnetic and seismic fields in such complex media. The problem of constructing an algorithm for solving the inverse problem using the equation of the theoretical inverse problem for the 2D Helmholtz equation is considered in [41], [42]. The explicit equations of the theoretical inverse problem for the cases of scattering of an electromagnetic field (E and H polarization) and scattering of a linearly polarized elastic wave in a layered conducting and elastic medium with a hierarchical conducting or elastic inclusion, which are the basis for determining contours of nonaligned inclusions of the first rank of the hierarchical structure, are written out. Obviously, when solving the inverse problem, monitoring systems that are set up to study the hierarchical structure of the environment should be used as initial monitoring data. On the other hand, the more complex the medium, each wave field introduces its information about its internal structure, so the interpretation of the seismic and electromagnetic field must be kept separately, without mixing these databases.
The belief that creativity is too difficult to measure is still a dominant myth [1] and can be considered as a byproduct of definitional issues. Researchers from various cultures and disciplines attempted to define creativity and offer a valid way to assess it. As creativity is a multifaceted phenomenon, it is a complicated task to define and operationalize it. For the sake of the discussion, one should start with defining “creativity”. The usefulness of higher order cognitive constructs is related to their definitions’ degree of clarity [2]. Unfortunately, most creativity research oversees the importance of this point. In a content analysis done for the articles published in two major creativity research journals, Creativity Research Journal and Journal of Creative Behavior respectively, researchers found that only 34% of the selected articles provided and explicit definition of creativity [3]. In order to examine a concept scientifically, we should rely on operationalized definitions and the relatively low rates of explicit definitions on creativity, constitutes a major problem for the field. As a result, I will use the following definition provided in Ref. [3] to clarify my perspective for this chapter. Creativity is “the interaction among aptitude, process, and environment by which an individual or group produces a perceptible product that is both novel and useful as defined within a social context”.
Starting with a definition would help but not provide the answer to our question at hand, why assess creativity? Although this question may have hundreds of answers the most basic and extensive answer would be: because creativity is the apex of human evolution and it is the most desirable skill in the information age. Creative thinking was the main ability that helped humans to move forward towards using a hand ax to complicated machines or produce complex language algorithms. Furthermore, creativity has become one of the most popular skills that schools and organizations search for. World Economic Forum, in its Future of Jobs report, ranked creativity in number three out of ten most important skills for the fourth industrial revolution [4], and also creativity is listed in the competencies part of 21st century skills. As of now, supporting creativity is the common goal of a kindergarten, a research institute or the biggest corporations in the world. The importance of creativity is anticipated to increase in the future due to various societal and economic trends as explained in Ref. [5].
Globalized markets require more competition.
Product development cycles shortened due to the information and communication technologies (For example, contemporarily any product that has been manufactured is redesigned within 5–10 years and this time period decreases to 6–12 months if the product is a technological device).
More and more jobs get automatized if it does not require creativity.
As job market demanded creativity more, the schools started to restructure their goals and curriculum to meet those need too. In the educational context, assessment of creativity is mostly about recognizing creativity and creating ideal conditions to nurture it, not about categorizing the students as “creative” or “not creative”. In Ref. [6] possible purposes of creativity assessment have been discussed; these can be summarized as follows:
Guide the individuals recognize their own strengths and support them in nourishing them.
Develop a better understanding about human abilities like intelligence and creativity. By maintaining that we will gain insight into the working structures of these complicated concepts.
Restructure the curriculum and learning experiences in accordance with the needs of the students. If educators understand their students’ strengths and weaknesses regarding creativity, they can tailor the educational opportunities for supporting creativity.
Imply creativity assessment as a program evaluation tool. Educators typically implement programs to enhance creativity, without pre and post assessments it would be impossible to know which approach worked best.
Utilization of standard measures will provide a common language for professionals to discuss various aspects of creativity.
Despite its importance, creativity did not become a major research area in psychology. Till the midst of 20th century creativity was seen as a marginal research topic and only 0,2% of the references in Psychological Abstracts indexes were about creativity [7]. Even the term “creativity” was not widely used before 50’s, however there were some influential works and essays written by philosophers and scientists (e.g. Bergson, Einstein, Kekulé, Poincaré) or early models proposed by researchers (see [8]). Modern creativity research began in 1950s and J. P. Guilford’s famous presidential address in American Psychological Association ignited the wick [9]. After Guilford’s call various researchers began to work on the field of creativity. Before that, assessment of creativity was not even a concern, especially for the young people or in the educational context. Because previous studies were solely focused on extraordinary creative achievements or eminent creative people. However, Binet’s pioneering intelligence test constituted an exception, it included some items to measure “creative imagination” [10]. Historically, some intelligence test developers considered creativity to be a part of intelligence or a totally independent construct [11]. In Ref. [12], authors categorized the approach towards the relations between creativity and intelligence under five groups. These are; creativity is a subset of intelligence, intelligence is a subset of creativity, creativity and intelligence are overlapping sets, creativity and intelligence are coincident sets and creativity and intelligence are disjoint sets. In the light of recent research, it can be claimed that the relation between intelligence and creativity depends on how each construct is defined and measured. Contemporary research widens these horizons. Creativity is now seen as a psychological trait distributed in the general population, that can be developed and measured [13].
The growing mindset which sees creativity as a flexible trait, increased the attention about the levels of creative magnitude. Creative accomplishments were categorized as everyday (little c) and historical (Big C) creativity. Imagine a 14-year-old math fan solving problems enthusiastically and compare it with the work of Fields Medal winner Andrew Wiles. She will not be as creative as Wiles and she does not need to be. Everyday creativity is certainly different from world changing efforts. The little-c, Big-C dichotomy was so sharp that one cannot distinguish the creative levels ranging in between. Kaufman and Beghetto [14, 15] proposed a “Four-C Model of Creativity” (mini-c, little-c, Pro-c and Big-C) to present a new perspective to this problem (see Table 1).
Mini-c | Learning is closely related to creativity, when we learn a new thing or try to solve a new problem some degree of creativity will be involved. At the mini-c level the creative act or product is new and original for the individual himself. For example, after several trials Sasha baked her first ceramic, although it was just in beginner’s level, it was new and meaningful to her. |
Little-c | The little-c level is one step further of the mini-c. The product or idea might be valuable to others. Sasha brought her ceramic to her house and her family loved it and put it on top of the dresser so that they use and enjoy seeing it. |
Pro-c | In the Pro-c level individual is at a professional level with years of experience and deliberate practice. Sasha majored in art in college and her artwork is now exhibited in galleries. Her work is followed by art experts and she is considered to be a creative artist. |
Big-C | People who achieve Big-C level are eminent ones and will be remembered in history books. One’s whole career and work is evaluated for this level. Sasha’s ceramics have been bought by art collectors and exhibited in art galleries regularly. |
Four-C’s of creativity.
Thus, it can easily be seen that every level of “c” requires a different approach and technique for assessing creativity. Over the years, researchers and theorists have proposed several different methods and theories for assessing creativity (e.g., Amabile, Csikszentmihalyi, Kaufman and Baer, Sternberg and Lubart, Torrance) (see [16, 17, 18, 19, 20]). These few examples constitute just the tip of the iceberg, there exist dozens of definitions, methods and theories in the field of creativity. As an illustration, in Ref. [21] Treffinger presented more than 100 different creativity definitions and as your definitions guide your assessment approaches, there are at least as many techniques to assess it. The reader can find information on more 70 different creativity assessments on Center for Creative Learning’s web page (see reference [22]). However, the variety of definitions and assessment techniques does not mean that creativity research has no consensus at all. Researchers tried to identify psychological factors that best predict creative outcomes and proposed several assessment techniques that imply these factors as a means of measurement [13]. Indeed, we can even argue that the field of creativity assessment has never been so prosperous before.
Today it is accepted that creativity is a combination of cognitive, conative and emotional factors which interact with the environment dynamically. As all of these factors are present in human beings and all these variables affects us to a certain degree, it can be argued that a specific combination of them results in creativity. In the historical research of creativity, several researchers tried to investigate the nature of creativity through the eyes of the aforementioned factors. The 4P framework (process, person, product, press) proposed by Rhodes [23] is a widely accepted categorization in psychometric study of creativity.
Process: Mental processes involved in creative thought or creative work.
Person: Personality traits or personality types associated with creativity.
Product: Products which are judged to be creative by a relevant social group.
Press (Environment): The external forces that effects creative person or process (e.g. sociocultural context, trauma)
In this section, historical and recent research in the field of creativity assessment will be presented. Although, every single creativity test, scale or rating will not be discussed, instead the focus will be on the historical milestones and contemporary methods of creativity assessment. This chapter embraced the integrative review approach with the aim of assessing, critiquing and synthesizing the literature on assessment of creativity.
Psychometric measures of creative process and potential has been extensively implied in the field. These processes involve cognitive factors that lead to creative production like finding and solving problems, selective encoding (i.e. selecting info that is relevant to problem and ignoring distractions), evaluation of ideas, associative thinking, flexibility and divergent thinking. Nevertheless, from this long list of cognitive factors the assessment of creative process mostly relied on divergent thinking in the creativity assessment tests. Even researchers in Ref. [24] underlined the irony in the study of creativity, although creativity itself requires novel and original solutions to a problem, researchers mostly focused on divergent thinking (DT) tasks. Not only major efforts were put on developing DT tests, even the earliest DT tests are still widely used in creativity research and educational areas. Divergent thinking can be explained as a thought process used to generate creative ideas via searching for many possible solutions. Whereas, convergent thinking is the ability to arrive the “correct” solution. Guilford [25] who came up with these concepts clearly underlined the difference between them.
In convergent thinking tests, the examinee must arrive at one right answer. The information given generally is sufficiently structured so that there is only one right answer… An example with verbal material would be: “What is the opposite of hard?” In divergent thinking, the thinker must do much searching around, and often a number of answers will do or are wanted. If you ask the examinee to name all the things, he can think of that are hard, also edible, also white, he has a whole class of things that might do. It is in the divergent thinking category that we find the abilities that are most significant in creative thinking and invention (p. 8)
In divergent thinking it is important to produce as many responses to verbal or figural stimuli as possible such that, more is better in DT. After the examinee come up with various answers, testers score them. The scoring is based on the concepts of originality (uniqueness of responses to a given stimuli), fluency (number of responses produced to a given stimuli), flexibility (number and/or uniqueness of categories of responses to a given stimuli) and elaboration (to add details to the ideas produced for a given stimuli) [25, 26]. As Guilford pioneered the research on creativity, initial efforts to assess it came from him and his colleagues too. Though, there were others who developed test batteries to measure creative thinking abilities and focused mostly on process components (e.g., Kogan and Wallach, Torrance, Mednick).
Structure of Intellect Divergent Thinking Test: Guilford’s famous Structure of Intellect Model (SOI) was mainly about defining and analyzing the factors constitute intelligence and he proposed 24 distinct types of DT [27]. His model covers 180 (6x5x5) intellectual abilities organized along three dimensions namely; operations (evaluation, convergent production, divergent production, memory, cognition), contents (visual, auditory, symbolic, semantic, behavioral) and products (units, classes, relations, systems, transformation, implications). Guilford’s SOI battery included several DT tasks like; in figural implications examinees were required to add lines to simple figures to create a new figure or in semantic units, listing commonly mentioned consequences of an impossible event, such as people not needing to sleep. Other examples include the Making Objects task (fluency with figural systems); in which participants make a new object from the provided four and by using alt least two of them or the Name Grouping task (flexibility with symbolic classes) which requires participants, given a set of names, forming subgroups based on different rules.
“Guilfordian” Tests: Guilford’s work was so influential that it was followed, replicated and reinterpreted by different researchers in 60s. Wallach and Kogan [28] argued that creativity tests should be administered in a game-like environment and should not apply time limitations. With this in mind, they focused on assessing creativity in children and developed the Instances Test (list as many things that move wheels, things that make noise) and the Uses Test (tell me the different ways you can use knife, tire or like in Ref. [29] toothpicks, chair or bricks). Wallach and Kogan proposed a different perspective than Guilford, not in the content of the test but for the target age group and way of administration (for a detailed discussion on the effects of different testing environments see reference [30]). Testing the divergent thinking ability of children would allow the educators and educational institutions to recognize their creatively able children and provide the necessary support and enrichment in their education.
Torrance Tests of Creative Thinking (TTCT): If we were to make a hits list for creativity assessment tests, TTCT most probably would be the number one. Torrance’s name was equated with assessment of creativity but it was not his major goal. TTCT was developed for research and to provide a tool that can be used to individualize the instruction [31, 32]. The TTCT, which are mainly based on SOI battery, are the most widely used and studied creativity tests [33, 34] and continue to attract attention in international level [35, 36]. Over the course of years, TTCT was refined in terms of scoring and administration and re-normed, which can account for its popularity. The TTCT consist of two different tests, the TTCT-Verbal and the TTCT- Figural, and each test has two parallel forms allowing it to be used as pre-posttests in experimental settings. The TTCT scores were expressed by four factors: fluency, originality, flexibility and elaboration. After the streamlined system introduced, Figural tests scored for resistance to premature closure and abstractness of titles in addition to originality, fluency and elaboration. Flexibility was removed because of the close correlation between fluency and flexibility scores [37]. The TTCT recommend an administration of game-like environment like Wallach and Kogan but apply time limitations.
The TTCT-Verbal is entitled as “Thinking Creatively with Words” and the Figural form entitled as “Thinking Creatively with Pictures”. Verbal form consists of six activities each whereas figural form consists of three (see Table 2).
TTCT-Figural | |
---|---|
Picture Construction | Participant uses a basic shape and expands on it to create a picture. |
Picture Completion | Participant is asked to finish and title incomplete drawings. |
Lines/Circles | Participant is asked to modify many different series of lines and circles. |
TTCT-Verbal | |
Asking | Participant asks as many questions as possible about the picture. |
Guessing Causes | Participant lists possible causes for the pictured action. |
Guessing Consequences | Participant lists possible consequences for the pictured action. |
Product Improvement | Participant is asked to make changes to improve a toy. |
Unusual Uses | Participant is asked to think of many different possible uses for an ordinary item. |
Unusual Questions | Participant asks as many questions as possible about an ordinary item (this item does not appear in later editions). |
Just Suppose | Participant is asked to “just suppose” that an improbable situation has happened then list possible ramifications |
TTCT- figural and TTCT-verbal subtests (adapted from reference [38]).
Remote Associates Test: Mednick [39], proposed a different perspective to creativity assessment and instead of solely focusing on divergent thinking he argued that convergent thinking should be taken into consideration too. Mednick believed that creative people are able to produce original ideas because they have the ability to form associations in their minds. Mednick analyzed the creative process through stimulus-response (S-R) perspective, he thought producing unusual or original responses to a stimulus required creativity and defined creativity based on this point of view.
….define the creative thinking process as the forming of associative elements into new combinations which either meet specified requirements or are in some way useful. The more mutually remote the elements of the new combination, the more creative the process or solution ([39], p. 221).
Mednick argued that people can achieve a creative solution through serendipity, similarity and mediation. His analysis showed that people’s associative hierarchies or set of responses to stimulus situations differ. Noncreative people have steep hierarchies, with a strong or dominant response to a given situation. As an example, if someone says pros, and if I cannot think anything else besides cons, that will be my dominant response to that stimulus and I will display a steep associative hierarchy. Whereas, the creative person has a flat associative hierarchy with multiple responses to a given stimulus. For example, for the stimulus word “table” a creative person might come up associations like chair, class, wood, leg, food whereas a non-creative person might come up with strongest associative links like chair, class and wood and stuck there.
For the operational definition of his theory, Mednick developed the Remote Associates Test (the RAT). RAT consisted of 30 items originally, each item included three stimulus words and the participant was required to find a fourth word that links them all. As an example; given stimulus set is; ‘book/shelf/telephone’ and the fourth word that link them all will be ‘book’. Some argued that, as test requires a single correct answer, it does not seem to require creative thinking [40]. However, one should note that the RAT itself is not aimed to measure creative thinking directly; it is measuring the capacity to think creatively and also in order to reach a single answer one should think divergently in RAT. Weisberg [41] joined this discussion by giving the example of a marathon runner, if one wants to identify a runner who has the potential to be a good marathon runner, he should measure lung capacity instead of running speed.
The Test for Creative Thinking – Drawing Production (TCT-DP): The discussion on TTC-DP should start with an annotation that it is not solely based on measuring creative processes (especially traditional divergent thinking tests) instead designed to mirror a more holistic concept of creativity. Though, as the theoretical basis of the test reflects mostly the cognitive processes involved in creative production, I preferred to discuss it under this heading. Urban [42] explained the approach in developing TCT-DP as a more holistic and gestalt-oriented one and aimed to consider not only divergent thinking but also aspects like content, gestalt, composition, elaboration, mental risk taking, breaking of boundaries, unconventionality and humor. The TCT-DP was developed by Jellen and Urban [43] and the test consist from a ‘big square frame’ with five fragments in the square and one fragment out of it. The participants are required to complete the drawing as they wish. TCT-DP has two parallel forms and although participants are not informed about the time limit during administration, it has a fifteen-minute duration for each form. TCT-DP is both an individual and group-oriented test and can be used with test-takers of most ages, from 4 to 95 years. The evaluation manual for TCT-DP includes a set of 14 key criteria ([42, 43], see Table 3).
Continuations (Cn) | Any use, continuation or extension of the six given figural fragments. |
Completion (Cm) | Any additions, completions, complements, supplements made to the used, continued or extended figural fragments. |
New elements (Ne) | Any new figure, symbol or element. |
Connections made with a line (Cl) | Between one figural fragment or figure or another. |
Connections made to produce a theme (Cth): | Any figure contributing to a compositional theme or “gestalt”. |
Boundary breaking that is fragment dependent (Bfd) | Any use, continuation or extension of the “small open square” located outside the square frame. |
Boundary breaking that is fragment independent (Bfi) | Any use or extension located outside the square frame independent of “small open square”. |
Perspective (Pe) | Any breaking away from two-dimensionality. |
Humor and affectivity (Hu) | Any drawing which elicits a humorous response, shows affection, emotion, or strong expressive power. |
Unconventionality, (Uc, a) | Any manipulation of the material. |
Unconventionality, b (Uc, b) | Any surrealistic, fictional and/or abstract elements or drawings. |
Unconventionality, c (Uc, c) | Any usage of symbols or signs. |
Unconventionality, d (Uc, d) | Unconventional use of given fragments. |
Speed (Sp) | A breakdown of points, beyond a certain score-limit, according to the time spent on the drawing production. |
Evaluation of Potential Creativity (EPoC): EPoC, similar to TCT-DP is not solely a process assessment, although it has strong cognitive factors it synthesized several traditions of measurement. The developers [44] embraced the multivariate approach proposed by researchers [45], which is, the combination of the cognitive, conative-affective and environmental factors influences creative capacity. EPoC was developed for children aged between 5 to 12 years old and aims to evaluate the creative potential of school-aged children. The test has two parallel forms and measurement relates to two fields of expression, graphic and verbal, and implies divergent-exploratory (find numerous original responses based on a given stimulus) and convergent-integrative (produce an original work integrating several elements in a creative synthesis) ways of thinking [13, 44]. EPoC’s forms are composed of eight subtests, administered individually and it is considered to be a modular domain-specific tool (see Table 4). EPoC is the most up to date creativity assessment instrument and the team is working on the extension of the test battery for new domains of creativity like music and science.
Field of expression | Exploratory-divergent thinking | Integrative-convergent thinking |
---|---|---|
Graphic | Abstract form | Abstract forms |
Concrete object | Concrete objects | |
Verbal | Story endings | Story with given title |
Story beginnings | Story with characters |
Distribution of the tests by field of expression and the mode of thinking evaluated for each parallel form (source [44]).
For convenience TCT-DP and EPoC has been presented under assessing the creative process and the discussion regarding their psychometric evidence is included in the next part along with other process assessment tools. As the reader may guess, there exist numerous tools for creativity assessment. Furthermore, there is a growing interest for domain-specific creativity assessment but domain-specific measures of creative potential are beyond the scope of this chapter, interested readers may check the suggested sources (i.e., For example, see [46, 47, 48]).
The most important question regarding any measurement instrument, whether it is a thermometer or test of creative thinking would be; is it reliable, does it produce consistent outcomes? To ensure reliability psychometric instruments must show consistent results in tests of reliability like test-retest reliability and split-half reliability. Research studies have showed that divergent thinking tests are reliable [30]. However, there are important points for further consideration, for example, some studies found that performance on DT tasks is affected by instructions (if you instruct people to be creative, they score higher). Weisberg [41], highlighted this situation by asking the question ‘If you instruct the examinee to be smart in the IQ test, will he be smarter?’. Weisberg himself gives the answer to this question; as children are used to answer questions exists in IQ tests, their score will not change with the instruction to be smart. However, questions in creativity tests are different in nature, most of them do not have a single correct answer and children are not familiar with this kind of questions. Thus, additional instruction might not be flaw for tests of creativity.
Once the reliability of a testing instrument is maintained, questions about validity arouse. Validity is a complex concept that can be ensured in a testing instrument via different analyses like discriminant, face, criterion and predictive validity. Tests of creative potential are reliable yet major discussions and suspicions exists about their predictive and discriminant validity.
To start with the Guilford SOI model, it is known that there exist enormous amount of assessment data and the archives are still available. SOI data was analyzed extensively within the years and the results generally supported the model [49, 50], or some researchers said that revisions needed [51] or concluded that the model has serious problems [52]. The results are pretty much same for Wallach and Kogan, although tests are reliable there are mixed results about its validity.
TTCT has been the most widely used and researched test of creativity, thus having extensive data to support its reliability and validity. Research about TTCT report good reliability scores for scoring and test-retest reliability [53, 54]. The majority of predictive validity studies for TTCT was run by Torrance himself, beginning in 1958 they included all grades 1 to 6 in two Minnesota elementary schools and in 1959 all students in grades 7–12 took TTCT. They followed up these students in four time periods (7-12-22-40 years) and collected data about their creative achievements. The longitudinal studies have shown that [20, 37, 55, 56] TTCT results correlate to adult creative achievement thus having predictive validity (for a detailed discussion see [57]). Though, Baer [58] raised some questions about the relevance of criterion variables (subscribing to a professional journal, learning a foreign language), do questions asked for the creative achievements in adult life are solely related to creativity? One can justifiably argue that, these criterion variables are strongly related to intelligence too. In addition, Torrance tests also correlate with intelligence then the predictability of creative achievements might be based on intelligence not on divergent thinking ability [41]. On the other hand, Plucker [59] presented more positive results concerning the predictive validity of the divergent thinking tests. He used multiple-regression analysis to reanalyze the Torrance data and examined its predictive power and provided support for the tests’ usefulness. Weisberg and Baer make other criticisms including the design of the study and interested readers should refer to these sources (see [41, 58]).
Mednick ‘s Remote Associates Test enjoy mixed support in terms reliability and validity too. Although RAT showed to be reliable [60], validity of the test is problematic [61]. It is important to note that the criterion/predictive validity of RAT, TCT-DP or EPoC have been subject to less investigation compared to divergent thinking tests like SOI or TTCT. TCT-DP has been normed in several countries like Germany, Korea, Poland and Australia for different age groups. The reliability studies showed fair to very good scores in terms of parallel test, scoring and differential reliability [42, 43]. Urban stated that the question of validity is hard to answer for TCT-DP as there are no instruments directly comparable to it [42]. So, they examined correlations with intelligence and verbally oriented divergent thinking tests and expected low or slightly positive correlations to ensure the instruments validity and attained supportive findings for the validity of the test [42]. As a modern creativity assessment instrument, EPoC was initially developed and validated in France with French sample. Internal validity was acceptable and for external validity researchers reached satisfactory results by proving that EPoC scores are independent from intelligence scores, moderately correlated with personality-relevant dimension like openness to experience and highly correlated with classic divergent tests [13, 44]. Although, EPoC shows promising validity results, extensive research is needed to support its criterion and predictive validity.
Extensive discussion regarding the reliability and validity of creativity assessment is mostly based on the divergent thinking tasks and tests. One major problem is about the scoring systems and several researches showed that fluency can act as a contaminating factor on originality scores [62]. To resolve fluency problem a new calculation named Creativity Quotient (CQ) was proposed by researchers [63]. CQ formula rewards response pools that are highly fluent and flexible at the same time. The discussion on fluency scoring is ongoing and some researchers advocate that fluency is a more complex construct than it is originally thought.
The debate on the predictive validity of divergent thinking tests is still ongoing, it seems like there exist two camps of researchers, one supporting the predictive power of DT [59, 64] and the other opposes [41, 58]. In an extensive review Kaufman and his colleagues [24] summarized the methodological issues in studies of DT tests’ predictive validity and pointed out that scores may be susceptible to intervention effects, administration procedures can affect the originality and fluency scores, statistical procedures may be inadequate, score distributions often violate the statistical assumption of normal distribution and creative achievement in adulthood may be domain specific and the DT tests used are almost always domain general. Runco [65] with all these criticism in mind, advocated for DT tests by saying;
Theorists who dismiss divergent thinking as entirely unimportant have ignored recent empirical research. . . . Additionally, some critics seem to expect too much from divergent thinking. Again, divergent thinking is not synonymous with creativity. Divergent thinking tests are, however, very useful estimates of the potential for creative thought. Although a high score on a divergent thinking test does not guarantee outstanding performance in the natural environment, these tests do lead to useful predictions about who is capable of such performances. . . . Divergent thinking is a predictor of original thought, not a criterion of creative ability. (p. 16)
In the early 60s and 70s creativity assessment was pretty much equal to DT tests however after several years and hundreds of research, the field should embrace a wider perspective. We now have more complex systems theories of creativity and it would be more prosperous for the field, if the upcoming research focus on developing and testing contemporary instruments more.
Autonomous, self-confident, open to new experiences, independent and original are some of the character traits that creative persons possess and the assessment of creative person deals with it. Measures that focus on the characteristics of creative person are self-reports or external ratings of past behavior or personality traits and they have been reviewed extensively in the literature [66]. Creative personality traits are diverse and can be perceived to be both positive and negative. Such as; perseverance, tolerance for ambiguity risk taking, psychoticism, dominance or non-conformity. One of the leading theories of personality is the five-factor theory. These five factors are neuroticism, extraversion, openness to experience, conscientiousness and agreeableness. Openness to experience is highly associated with creativity measures such as self-reports [67], verbal creativity [68], and psychometric tests [69].
Researchers study the common personality characteristics and past behaviors of people who are accepted as creative and develop instruments to measure personality correlates of creative behavior. There exist numerous instruments of personality scales and attitude checklist such as; The Khatena-Torrance Creative Perception Inventory, Group Inventory for Finding Talent, Creativity Achievement Questionnaire or Runco Ideational Behavior Scale.
The Khatena-Torrance Creative Perception Inventory: This inventory consists of two self-rating scales called What Kind of Person Are You? (WKOPAY) and Something About Myself (SAM). It is designed to identify creative people 10 years or older [70]. There are 50 forced-choice items in each inventory and asks test takers for example, if they have courage for what they believe or select true or false options for the sentences like; I have made a new dance or song. The inventory has satisfactory reliability data and validity data was moderate.
Group Inventory for Finding Creative Talent (GIFT): GIFT is a self-report for 1–6 grader to assess their creative potential [71]. Students give yes/no answers to a series of questions aiming to assess flexibility, curiosity, perseverance or hobbies such as; I like to take things apart to see how they work. Later in 1982, Davis and Rimm developed a new personality scale called Group Inventories for Finding Interests (I and II), known as GIFFI. These instruments were designed for junior and senior high school students and are very similar to GIFT [72]. Reliability and validity data for GIFT and GIFFI were moderate and researchers stressed that additional data is needed to support their psychometric structure.
The NEO Personality Inventory - NEO-Five Factor Inventory: Costa and McCrae’s [73, 74] inventories are one of the most popular five-factor measures of personality theory. For openness to experience part, they used down to earth-imaginative, uncreative-creative, conventional-original, prefer routine-prefer variety as adjective definers and fantasy, esthetics, feelings, actions, ideas and values as scale definers [73]. This type of items has been used in numerous studies and most of the studies did not find any personality differences among cultures except in some studies it has been shown that European-American cultures tended to be more open to experience than Asian-African cultures (for a detailed discussion see [24]).
Creativity Achievement Questionnaire (CAQ): Self-reports of activities and attainments can be used to measure creativity. CAQ developed by researchers in Ref. [75] and assesses achievement across 10 domains of creativity. It is a self-report checklist consisting 96 items that load on to an Arts (Drama, Writing, Humor, Music, Visual Arts and Dance) and a Science factor (Invention, Science and Culinary). The respondent indicates to which extent the phrases in the items represent him/her. For example, within Scientific Discovery scale items range from “I do not have training or recognized ability in this field” to “I have won a prize at a science fair or other local competition”, to “My work has been cited by other scientists in national publications.” The CAQ possess high levels of evidence of reliability and acceptable evidence of validity [75] and has been used in several studies (see [76, 77]).
Runco Ideational Behavior Scale (RIBS): In everyday life, generating creative ideas is a sign of creative performance and RIBS’s purpose is to measure this idea generation. Ideation involves idea generation and attribution of value to it; thus, it can be an adequate creativity criterion. Runco and his colleagues developed a set 100 items and reduced it to 23 to measure ideational behavior [78]. Sample items include, “I am able to think about things intensely for many hours” or, “I often find that one of my ideas has led me to other ideas that have led me to other ideas, and I end up with an idea and do not know where it came from”. Psychometric integrity of RIBS in terms of reliability and validity has been proven to be adequate [78] and RIBS has been used in several studies and adapted to other languages as well (see [79, 80]).
“Person” perspective or conative factors in creativity assessment mainly take into account that significant personal characteristics and existing creative behavior are best predictors of future creative behavior. Feist, an influential personality researcher, for example investigated the personality characteristics of scientists versus scientists, more creative versus less creative nonscientists and artists versus nonartists. In general, he showed that creative people are more open to new experiences, less conventional and less conscientious, more self-confident, self-accepting, ambitious, dominant, hostile and impulsive [81, 82]. In sum, self-reported creativity has attracted considerable attention in the field because it is fast and easy to score. Although, researchers willing to use these instruments should take into account the validity issues and the possibility that respondents may not be telling the truth. All kinds of self-assessments generally correlate to each other but the correlation data with performance assessments are contradictory [83, 84, 85]. Thus, citing from reference [24] “although self-assessments have a function and purpose, they are not useful in any type of high-stakes assessment”.
Think about the Nobel, Oscar or Grammy prizes, how the winners are designated? For example, do the Nobel committee requires the nominees to take TTCT or fill the creativity questionnaires or a taxi driver’s opinion will be count as an expert opinion in determining the nominees for chemistry? As explained in theories of Csikszentmihalyi and Amabile any idea or product to be seen as creative it should be valued by others or recognized experts in that field [86, 87]. Measuring the creativity of a product can be the most important aspect of creativity assessment yet it did not receive as much attention as process or personality variables. Some researchers even believe that product assessment is probably the most appropriate assessment of creativity and referred as the “gold standard” of it [88]. Researchers developed several instruments to evaluate creative products, such as Creative Product Semantic Scale or Student Product Assessment Form. These instruments ask educators to rate the specific features of students’ products. Though, above all Consensual Assessment Technique is the most popular way of assessing products. A brief explanation of each is provided below.
Creative Product Semantic Scale (CPSS): The CPSS is based on a theoretical model that conceptualizes three dimension of product attributes: novelty (the product is original, surprising and germinal), resolution (the product is valuable, logical, useful, understandable) and elaboration and synthesis (the product is organic, elegant, complex and well-crafted) [89]. The instrument relies on the idea that untrained judges can evaluate the creativity of a product by using a validated and reliable instrument [90]. The CPSS is scored on 7-point Likert-type scale, ranging from 1 to 7 between bipolar adjectives such as old-new. CPSS has shown to have adequate reliability values.
Student Product Assessment Form (SPAF): SPAF was developed by Renzulli and Reis [91], and aimed to assess the various types of products developed by students in enrichment programs. SPAF is designed for use with gifted learners and provides ratings of nine creative product traits (e.g. problem focusing, appropriateness of resources, originality, action orientation, audience) [92]. SPAF again, like CPSS have evidence of reliability although validity issues remained to be addressed.
Consensual Assessment Technique (CAT): Researchers need external criteria in creativity research to reach evidence of validity but an absolute criterion of creativity is not readily available (criterion problem) [24]. In CAT, the creativity of a product is judged by the experts in that field. These experts can be a group of mathematics professors to a group of kindergarten teachers depending on the product at hand. CAT was formulated by Amabile [87, 93] and since then has been applied in the creativity research extensively. When using CAT, the participants are asked to produce something (an actual product like haiku, collage, poem etc.) and experts rate the creativity of these products according to their perception of a creative product. CAT’s procedure is working similar to the real world and it does not provide standard scores, only comparative scoring is possible.
CAT has been proven to be reliable in several studies [58, 85, 88, 93, 94], inter-rater reliabilities ranged between .70 to .90. The average number of judges involved in the CAT studies run by Amabile [93] was just over ten. Using expert judges ranging between 5 to 10 is recommended, fewer than 5 experts may results in low inter-reliability levels and using more than 10 (although desirable) can be expensive and hard. Although, CAT steadily shows high reliability in various studies, using experts in creativity assessment is not without controversy. For example, Amabile states that determining the necessary level of expertise for judges is important and it is recommended that the experts should have formal training and experience in the target domain. Furthermore, researchers reported mixed results about the expert and novice ratings. For example, Kaufman and his colleagues showed low correlations among novice and expert raters [95], whereas in another study higher correlations reported [96], in more recent work researchers approached the expertise problem from a different perspective and argued that it should be understand as a continuum [88]. CAT also possess strong face validity yet, face validity (an instruments capability to measure what it looks like to measure) is not sufficient enough. For example, experts can agree a product is not creative and still be wrong (e.g. van Gogh was not valued as a creative artist by the experts in his time). Predictive validity discussion is even more complicating, it has been shown that CAT scores do predict later CAT scores, meaning they are stable across time in the same domain. However, does this mean CAT scores can predict later creative achievement? Historiometric research data supports this argument, for example analysis of Mozart’s music pieces in his early life predicted his later creative achievement [97].
Various environmental factors contribute to creative potential and have deep effects on it. Parental practices, trauma, birth order, culture, teaching practices and group interactions may affect creativity. Following the previous example of Mozart, we know that he was born in Salzburg and to a musical family (his father was a music teacher, composer, conductor and violinist). Imagine what would happen to the same Mozart if he would have born in small village in the Alps as son of a shepherd, would he be able to develop as a musical prodigy? Although creativity is highly related to cognitive factors, it is impossible to disregard the impact of environment.
As environmental factors are identified as important contributors to creative potential, studies aiming to determine the presence or absence of these factors in an individual’s environment become really important. There are instruments for assessing classroom and learning environment like Classroom Activities Questionnaire-CAQ (cited in [13]). However, the majority of the instruments for assessing environmental effects on creativity are mostly about the organizational structures, such as KEYS: Assessing the Climate for Creativity [98]. CAQ has not been widely applied in research studies therefore lacking the psychometric data, KEYS on the other hand, which was designed to “assess individuals perceptions and influence of those perceptions on the creativity of their work” ([98], p. 1157) possess evidence of reliability and validity and is widely applied in the organizational creativity field.
Creativity has various definitions, theories and also understood therefore assessed in many ways. Enhancing students’ creative thinking skills has become one of the major goals of education. Unfortunately, Kim’s comprehensive research on TTCT is disquieting. The normative data of TTCT 1974, 1984, 1990, 1998 and 2008 (272,599 participants) were re-analyzed and it was found that creative thinking scores either remained static or decreased, starting at the sixth grade [99]. There can be millions of reasons behind this failure. The inability to embed creativity in classroom practices can be one reason whereas the development and implication of up to date creativity assessment is the other. The field should move forward to using comprehensive theories as the basis of assessment, renew the norms of existing creativity tests such as TTCT and pay more attention to the validity studies of the creativity assessment instruments.
This chapter introduced a brief overview of existing tools of creativity assessment and to reach a “perfect” measure, researchers should take these approaches’ and instruments’ strengths and weaknesses into account (a brief overview is provided in Table 5).
Type of Assessment | Examples | Advantages | Disadvantages |
---|---|---|---|
Process based assessment (e.g. divergent thinking tests) | Torrance Tests of Creative Thinking | Well researched having years of research data available | May only tap limited aspects of creativity |
Person based assessment (e.g. Assessment by others) | Group Inventory for Finding Creative Talent or other instruments | Creativity is rated by a teacher, peer, or parent who knows the individual. | Questions about validity and reliability |
Person based assessment (e.g. Self-assessment) | Asking someone to rate his or her own creativity | Quick, cheap, and has high face validity | People can be subjective about their level of creativity |
Product based assessment (e.g. Consensual assessment technique) | Having experts rate a creative product | Allows for very domain-specific information about creativity, | Time consuming and expensive |
Brief overview of creativity assessment (adapted from [24]).
Furthermore, the argument that Sternberg [100] made by claiming that the evaluation of creativity is always local has to be kept in mind. Judging any thought or product is relative to some set of norms and this perspective raises questions for tests like TTCT or Unusual Uses, because these tests assume that some sort universal creativity exists and they measure it. Sternberg believes that creativity should be assessed locally because it has culture dependent elements just like intelligence and he suggests that “we should agree that our evaluations of what usually is viewed as constituting creativity – novel, surprising, and compelling ideas or products – represent local norms” ([100], p. 399).
The laypeople, the philosophers, the artists, and the creativity researchers all agree that creativity is a complex phenomenon and we know less about its scope and measurement than we wish to know. However, from a historical perspective in recent years more research has been conducted on creativity and the field of creativity can said to be at its prime. Hence, upcoming efforts of understanding and assessing creativity has the potential to produce more reliable, valid and comprehensive methods and theories. As discussed in this chapter, creativity assessment has its own limitations but it is recommended for future efforts to focus more on building a theoretical basis and providing multifaceted, multimodal assessment systems to measure creativity in order to overcome the aforementioned limitations.
The author declares no conflict of interest.
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