Prospection: Methodological Complexities of Imagining Academia

Abstract

Simulations can be considered a particular act of thinking that entails imagining oneself in a hypothetical scenario (as either the doer or the observer) to explore potential outcomes. Imagining the structure and functioning of institutions of higher education in the future is a complex task that may involve a blend of known and estimated facts along with desired outcomes. In the present paper, we discuss the merits of mental simulation along with a straightforward paradigm that may be useful in the study of prospection applied to this specific task. It is based on the assumption that prospection is a natural outcome of an intelligent cognitive system, which envisions the future to both anticipate and shape forthcoming events. We then discuss the benefits of prospection when the object to imagine is the university.

Keywords

prospection higher education cognition

The call for papers entitled “Imagining possible futures for the university” caught our attention as we were reminiscing on the misfortunes of a private academic institution in the USA that had recently closed its doors. For over two decades, the institution’s primary response to declining enrollment was to change presidents frequently. Each proposed a slightly different core mission (i.e., the intended basic purpose of the institution) through a governance structure that was utterly inadequate to create a sustainable niche for the institution. As structural and functional alterations never ensued from the shifting missions, workforce reduction was the chosen and recurring response to the relentless decline in enrollment, which rendered the institution even less viable. Not surprisingly, a last-ditch and frantic attempt to raise cash from alumni preceded the inevitable closure. Could mental simulations of its future have changed what appeared at the end as the inevitable outcome of an institution that did not understand how to serve its students? We begin our paper by introducing the concept of mental simulation.

Mental Simulation: Defining Properties

Future thinking is defined as the “projection of the self into the future to pre-experience an event” (Atance and O’Neill 2001, 633). Thus, it may involve imagining contents (i.e., objects, ideas, people, and actions) in context, known as “thinking about the future”, and projecting oneself into the context developed by one’s mind, thereby watching or actively participating in the created contents, known as “thinking in the future.” When the two are combined in real time, then a mental simulation can be said to have occurred.

Simulations can be considered a particular act of thinking that entails imagining oneself in a hypothetical scenario (as either the doer or the observer) to explore potential outcomes. They do not often consist of a unitary progression from a clear beginning to a well-defined outcome. Instead of a deterministic single forecast, simulations rely on divergent thinking to explore alternatives, including actions and outcomes. As such, they are goal-directed, flexible tools for imagining perceptions and actions. It is important to note though that simulation of a percept “is essentially the same as actually perceiving it, only the perceptual activity is generated by the brain itself rather than by external stimuli” (Hesslow 2002, 242). Similarly, simulation of action entails the activation of “motor structures of the brain in a way that resembles activity during normal action but does not cause any overt movement” (Hesslow 2002, 242). Unlike actual behavior or actual percepts, however, simulations rely on past experiences with the purpose of viewing, mentally experiencing, and testing different versions of what may happen. Through their generating materials for both prediction and anticipation, they can also guide perceptual processing of actual occurrences as well as behavior.

Simulations illustrate the human mind’s ability to engage in prospection, a more general orientation towards the future (including prediction and anticipation) through which information stored in memory is used to imagine, simulate and predict future occurrences (Schacter et al. 2007). In this context, prospection is the ability to “pre-experience the future by simulating it in our minds” (Gilbert and Wilson 2007, 1352). It includes prediction or expectation, which refers to a representation of an event, and anticipation, which describes the impact of a prediction on current cognition (e.g., decision-making) and behavior (Butz et al. 2003). Simulations are made possible by the prospective brain, a set of neural structures that include prefrontal and medial temporal regions, whose key function is to use information stored in memory with the specific purpose of imagining, planning for, and predicting future occurrence (Schacter et al. 2007). Of course, the contributions of both semantic memory (i.e., knowledge of the general properties of an event) and episodic memory (i.e., personal experiences) are likely to guide the process of envisioning the future in the future.

Challenges of Simulating Academia in the Future

The purpose of the present paper is to consider the emerging collection of empirical findings and ideas about the practicalities of future thinking (Atance and O’Neill 2001) when the aim is to reflect on the prospect of the institution we have come to know as university (Rudolph 1990; Scott 2006). Of course, the aim of the exercise of envisioning the future of universities may be of two sorts: (a) Simulating scenarios consistent with one’s ideological bent, thereby hoping that an optimistic framing will increase the chances that desired states will become reality (Pezzo et al. 2006); or (b) simulating pragmatic, albeit imperfect, scenarios of what a university might be, given the contextual factors in which it is embedded. Through either type of simulation, it may be possible to get valuable insights into not only people’s knowledge of the university at the individual, organizational/structural, and societal levels, but also their use of such knowledge for the purpose of prospection. The following are a few key methodological hurdles in the study of such thinking.

First, there are two overriding properties of future thinking. It involves “time travel,” whereby pre-experiencing a future event occurs through detaching the self from the present (Tulving 2005). It also entails a constructive process whereby scenes are assembled from the details of the information available in one’s memory. Such details are extracted and recombined to simulate future events (Suddendorf and Corballs 2007). Because future thinking is often based on a person’s memories, which do not tend to excel in accuracy, they are prone to errors. For instance, memories tend to shrink the amount of time taken to complete various tasks. Since the prospective brain relies on such memories and often fails to take into account potential complications, people underestimate the time needed to complete these tasks in the future (Buehler et al. 1994; Roy et al. 2005). People’s predictions of their future happiness also tend to be based on atypical, but highly memorable experiences. Since these experiences are unlikely to re-occur, predictions of future happiness are generally inaccurate (Morewedge et al. 2005).

Four kinds of properties of simulations make them sensitive to prospective inaccuracies (Gilbert and Wilson 2007). Mental simulations are (a) unrepresentative (i.e., they often rely on the most unusual or recent memories instead of the most likely past events); (b) essentialized (i.e., inessential details are often omitted with lapses increasing as temporal distance increases), (c) abbreviated (i.e., they represent only a few aspects or moments of an event and usually the earlier ones), and (d) decontextualized (i.e., they tend to ignore that contextual factors, which shape human behavior in the present, may be different in the future). Compared with genuine sensory perceptions and actions, simulations are imperfect. They may allow people to navigate time, preview the future, and pre-experience a multitude of events and their consequences, but each is a fabrication whose foundations rest on shaky grounds.

Second, because future thinking is a goal-directed process, whereby a story may have more than one way to begin and multiple ways to end, envisioning the future of institutions of higher learning requires a clear sense of the functions that such institutions are intended to perform in societies across the globe. The latter is an opinion, nevertheless an influential one as different functions lead to different ways of envisioning the existence of universities. Institutional models of the university exist which highlight different functional responsibilities. Each model defines the university by identifying its core mission (its basic purpose). The latter usually entails a unique conceptualization and prioritization of three key aims (teaching, research, and public service; Scott 2006). One model, for instance, which can be called the “entrepreneurial university” (Etzkowitz et al. 2003), aligns research and teaching with economic development. The entrepreneurial (vocational) university is a knowledge-producing and disseminating institution at the service of the economic engine of the society where it exists. As such, teaching is vocational, taking the form of training students to face real-world problems in a given domain, whereas science changes from basic to applied. Privatization and commercialization are its driving credos as applied research is prioritized with the goal of achieving marketable advances in knowledge and inventions. Because of its close ties with industry and government, and its responsiveness to their “needs,” it promotes a science-based economic development at the service of a capitalistic engine. Antithetical models see the pecuniary interests of the entrepreneurial university model as not only compromising the integrity of its educational and knowledge-producing mission, but also expressing an uncritical servitude to industry and government (Krimsky et al. 1991; Pelikan 1992). Under this umbrella, the purist, (lyceum-like) model puts a premium on academic pursuits (learning for learning’s own sake), which are treated as detached from materialistic interests, as well as from time, culture and utility concerns. In the lyceum, knowledge is universal wisdom to be imparted and pursued by those who have the means. Thus, in its practical instantiations, the purist model is elitist at its core (Barber 1992). The civic-mission model instead sees the university as an institution devoted to the public good. As such, the university is a civic-minded institution whose mission is the cultivation of knowledge and independent judgment in individuals who appreciate and pursue freedom of thought. Knowledge is seen as being socially constructed through a democratic process of idea-sharing within communities. No party or idea is privileged over others simply because of its origin. In the “pluri-versity” instantiation of the latter model, institutions of higher education are construed as agents of social transformation (Newson and Buchbinder 1988). Accordingly, they are expected to “contribute not only to the equalization of educational opportunities but also to collective projects that promote social and environmental justice and ultimately alter existing social, economic, and political relationships” (Schugurensky 2006, 303).

Third, once the mission of institutions of higher learning is clearly stated for either desirable or practical prospection, the next task is to define the context in which they are expected to operate. The latter entails complex social, economic, and political factors that render envisioning the university not merely in the distant future, but also in the near future a rather volatile and variable process. Variability stems from cultures, which differ in the extent to which particular values are regarded as significant, shaping the ideological apparatus of societies (or nation-states) around the world accordingly. Volatility results from random and quasi-random events embedded and interpreted by cultures, which interact with each other through contrastive and assimilative responses, thereby being in essence hybrid frameworks subject to constant change (Morris et al. 2015). Technological changes are one of the principal engines of volatility as they have promoted, and will continue to promote greater interdependence of the world’s economies, cultures, and populations (Shohat and Stam 2014). Widespread globalization, supported by technology, will continue to alter the way people work, process information, learn, and participate in leisure activities. Thus, the functions of higher education institutions and the context in which they will operate in the future may not only vary regionally, but also be different depending on the timeframe selected.

Most of the current evidence regarding cultural differences stems from culturalism (Morris et al. 2015), which holds that people are molded by the culture of origin. Within this framework, several cultural dimensions exist, such as orientation towards others (level of individualism or collectivism), power distance (degree of acceptance of an egalitarian or a hierarchical structure), uncertainty avoidance (level of comfort with ambiguities), and masculinity-femininity (interest in power relative to interest in nurture). Each dimension, treated as either a dichotomous variable or a continuum defined by two extreme points, defines boundaries that do not clearly exist between purported different cultures of geographically separate regions of the world (e.g., the West and the Far East). Yet, cultures are not defined by purity or equity (see the impact of colonialism). Even if an array of dimensions is assumed to define a society, members select (or are induced to select) values, beliefs, habits from a cultural menu, and are thus differentially shaped by particular cultural dimensions. According to poly-culturalism, people’s engagements with cultures are by definition dynamic and partial. As such, cultural patterns are difficult not only to capture in the present without making broad generalizations, but also to envision in the future.

Fourth, simulating scenarios of the future of the university, either consistent with one’s ideological bent or pragmatic, requires a sensible protocol that allows for the measurement of the quality of the mental simulation. Clearly, it is not possible with this kind of prospection to distinguish between biases (systematic errors) and simple errors representing random deviations or distortions (Armor and Sackett 2006). Thus, the guidelines set by Hassabis et al. (2007) in their protocol for imagining the future may be useful as measures of the quality of the scenarios that people develop when they are asked to “think of” and “think in” the future. Yet, an entity or event can be represented at different levels (Liberman and Trope 2008). Lower-level scenarios are concrete as well as contextualized representations that tend to include subordinate and incidental details. Higher-level scenarios, instead, are abstract, schematic, and decontextualized representations. They extract the gist of events or entities by emphasizing key details and omitting those that vary without significantly changing the structure of what is represented. Simulating academia in the future is primarily an exercise of the latter level. However, it may integrate lower-level scenarios, depending on the forecaster’s preferences or the instructions/guidelines of the task of imagining the future. The latter set the boundaries of his/her traveling into the time ahead, thereby biasing to a certain extent the contents of his/her imagination. For instance, the label university may be left vague (i.e., “a university”) if the goal is to gather information about the key aspects of a prototypical instance of higher education institutions in the future. Alternatively, it may explicitly refer to a university familiar to the forecaster, such as one he/she attends or where he/she works, if the goal is to gather information about key aspects of an actual instance of a higher education institution in the future. To promote a simulation that feels “real” to the forecaster, instructions may be given to start his/her simulation by imagining as vividly as possible taking a walk on the grounds where the envisioned university is purported to exist while narrating his/her experiences. While verbalizations are recoded, the forecaster may then be probed with questions on more abstract matters, such as the nature of the curriculum, instruction, learning outcomes, and institutional governance.

It is important to acknowledge that there may be different versions of the simulation depending on whether the forecaster relies on a viewpoint (individual, organizational, or societal) or favors transitions to different ones. If the latter is adopted, the individual viewpoint may vary with the forecaster’s assumed role, such as student, faculty, or administrator. If left undefined, simulations are likely to assume multiple viewpoints, increase in complexity, and be less integrated. Nevertheless, information about the expertise/profession of the forecaster is to be collected as it is likely to be correlated with the quality of his/her simulation. The timeframe of the required leap into the future is also to be decided, keeping in mind that as the date becomes more remote, precision will diminish. In fact, what seems to shape the precision of a simulation is psychological distance, which refers to the spatial, temporal, and social dimensions of the contents of envisioning the future. Evidence exists that people process events that are psychologically distant (compared with those that are psychologically near) more abstractly and in broader brushstrokes rather than in concrete details (Liberman and Trope 2008; Trope and Liberman 2003, 2010).

The protocol of Hassabis et al. (2007) may be followed to ensure that the evaluation of simulations of the future of the university involves standard measures of quality (Rendell et al. 2012). It may include:

(a) Self-ratings of the extent to which the forecaster feels he/she is truly in the imagined future (“How much of a sense of being there did you have when imagining?” scored on a 4-point scale from “I did not feel like I was there at all” to “I felt like I was really there”); self-ratings of the salience of the experience (“How vivid was the scene you imagined in your mind?” scored on a 4-point scale from “not vivid at all” to “extremely vivid”); and self-ratings of coherence (“I could see the whole scene in my mind” versus “the scene was a collection of separate images”). (b) Objective content analysis carried out by independent raters. The transcript of each forecaster is segmented into a set of statements, each to be categorized according to several criteria: (1) relationships of entities within a scene (e.g., mention of general education courses being intermixed with topical courses), (2) the number of items of any given type cited by the forecaster (e.g., particular courses), (3) description of the properties of an entity (e.g., type of assignments and activities to be performed by learners), and (4) thoughts, intentions, emotions, and actions, either introspective or assumed in other people (e.g., the forecaster’s view of university governance as including officials elected by all the constituents of the university in free elections).

(c) Independent raters’ evaluation of how well the forecaster’s descriptions evoke a detailed picture in the raters’ mind. Ratings may range from a construction entirely devoid of details and no sense of experiencing to a rich and highly evocative construction. In addition to the criteria defined by Hassabis et al. (2007), it may be helpful to record whether the forecaster’s narrative relies on a prevailing viewpoint (individual, organizational, or societal) or entails transitions to different levels.

Elevated ratings on quality dimensions suggest a forecaster who has wholeheartedly moved into the future. Comparisons of simulations of different forecasters, classified according to their domain of expertise, may offer useful advice and guidance for addressing the issue of what a university might or should be in the future (if it is to exist at all).

The Utility of Mental Simulations

When faced with decisions that involve the future, the human cortex previews the future and pre-feels its consequences through mental simulations. Simulation allows us to answer “what if” questions by making explicit and accessible information about a selected situation as if one were in that situation (Moulton and Kosslyn 2009). Gilbert and Wilson (2007, 354) call simulations “ingenious but imperfect.” They state that “compared to sensory perceptions, mental simulations are mere cardboard cut-outs of reality.” Yet, future thinking is an unavoidable human developmental step as much as is language acquisition. By the third year of age, children are able to talk about the future as well as display awareness that the future is somewhat uncertain. At preschool-age, they are able to consider the future consequences of their behavior, demonstrating increasingly skilled planning and anticipatory abilities (Atance and O’Neill 2001). Important to note is that in neither children nor adults, prospection involves giving imagination free reign. Pre-experiencing is constrained. For instance, pre-experiencing the activities connected with learning in a virtual classroom of the future may require that the forecaster take upon himself/herself the roles of both instructor and student, determine learning outcomes, consider timeframe, etc., all of which are constraints to the imagination. If prospection is an unavoidable quality of being human, which is not necessarily unique to the human race (see Clayton et al. 2003), it is reasonable to ask whether mentally simulating the future of the university yields specific benefits. For instance, could simulation have prevented the closure of the higher education institution mentioned in the introductory section of our paper?

Consider that mental simulations tend to enhance the links between thought and action. In fact, mental simulations make envisioned event-sequences and action-sequences seem plausible, thereby creating a state of readiness for action. More broadly, the act of imagining provides information about events and actions, such as their key features and relationships, thereby making valuable information accessible to planning (Miller et al. 1960). Thus, it is not unreasonable to think that mental simulations of the future could have stimulated the members of the governance body of that institution to translate images and thoughts into concrete plans of actions to address the inertia that ultimately decided its doom.

Important to note though is that mental simulations can be outcome-oriented or process-oriented, depending on whether the attention of the forecaster is focused on outcomes or on the steps to get there. Evidence suggests that the latter significantly facilitates planning and forthcoming performance (Pham and Taylor 1999). Thus, both imagining a desired future scenario for the university or imagining a pragmatic one can potentially benefit from a process-oriented attentional focus.

Of course, whether process-oriented mental simulations could have specifically saved the institution mentioned above is a matter of conjectures. Obviously, mission statements are not enough. As Maya Angelou (2009, 96) reminds us “words mean more than what is set down on paper. It takes the human voice to infuse them with deeper meaning.” Yet, there is no shortage of books and articles on the university as an institution in crisis (Husen 1991; Scott 2018). The higher education of large segments of the world population has needed improvement for a long time (Duderstadt 2012; Grosfoguel 2013; Orfield et al. 2004). Closure or consolidation has affected hundreds of colleges and campuses in the USA (Andrew and Friedman 1976; Stowe and Komasara 2016). Consolidation has translated into curricular changes (adding degree programs in emerging tech fields, as well as dropping low-enrollment programs), as well as in increased reliance on online education to reach bigger audiences. Substantial changes to the institutions’ original curriculum and pedagogy are merely reactive responses for which a clear sense of the future is often missing. Because present as well as future environments, where the university is to exist, are inherently uncertain, simulations may not be intended as foretelling the future. At the very least, they are tools to devise strategies that are sufficiently flexible to enable the governance body of the university to respond adequately and efficiently to shifting contingencies to avoid catastrophic outcomes (Healey and Hodgkinson 2008).

In a context characterized by turmoil and uncertainty, mental simulations may help make the university face its existential crisis by not only suggesting feasible solutions, but also moving from reaction to proaction. Undoubtedly, the factors that must be considered to envision higher education in the future are many, complex and interrelated: the diverse and overlapping needs of communities, technological changes and their impact on everyday life, economic and financial inequalities, etc. (Szadkowski 2017). Nevertheless, mental simulations may move the discussion from the usual focused attention on topical subjects (e.g., money, students, politics) to a different level of analysis, which may not only offer to governance officers a better perspective of the key challenges and opportunities of the higher education of the future, but also stimulate action. In addition, if the simulation entails imagined exchanges of ideas among different constituencies, it may promote cooperation among them, thereby further increasing the chances of plans translating into action (Meleady et al. 2013). As such, interested parties are not merely responsive to the demands of industry, government, and other entities, but become active proponents of change that has been pre-experienced (albeit imperfectly) via mental simulation.

Footnotes

Author’s Note

Khadija El Alaoui is now affiliated with American University of Iraq, Sulaimani (AUIS).

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Maura A. E. Pilotti

Author Biographies

Maura A. E. Pilotti is a cognitive psychologist whose research interests include learning and memory processes across the lifespan. Currently, her research focuses on the interrelations of memory, language, and emotion. She received her PhD in Cognitive Psychology at the City University of New York (USA).

Khadija El Alaoui is a scholar of American Culture whose specializations encompass History, and Peace and Justice Studies. Currently, her research focuses on the history of the Arab and Western worlds, human diversity, and cultural practices. She received her PhD in American Studies from the University of Dresden (Germany).

Muamar Hasan Salameh is the Chair of the Law Program, Dean of Faculty Affairs, and Director of the Center for Futuristic Studies at Prince Mohammed Bin Fahd University. Currently, his research interests include human rights, Palestinian–Israeli conflict, arbitration and mediation, public international law, and constitutional law. He received his PhD in Public International Law and Human Rights from the University of La Sapienza (Italy).

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