So, what is theory?
Let’s start with what theory is not! In a now-classic piece, Sutton and Staw (1995) argue that the lack of consensus on the nature of theory may explain why we find it hard to develop strong theory in our field. According to them, there are several things that we should not mistake for theory:
References: while these help to set the scene, on their own they don’t serve as theory. Theory should follow a stream of logic or argumentation which explains how the elements fit together and why they matter.
Data: empirical evidence plays an important role in formulating, revising, or contesting theory but is not theory in itself. The difference between the two is quite simple – while data show what phenomena we are observing, theory offers an explanation why the data take the form that they do and what else might be expected (or not expected).
Lists of variables, models, or diagrams: while variables can be combined in exploratory models and can support theory development, on their own they do not count as theory. The theoretical explanation that goes with such models should define these particular variables and explain why they are expected to be relevant, how they came about, and why they are related.
Hypotheses: these are crucial for linking our evidence to the theory and building a conceptually sound argument. Again, the explanation of why this is expected is where theory comes in, offering some generalisations, justifications, and showing the underlying pattern, logic or argument.
So, we could argue that theory is a “way of explaining, of saying how things relate to each other, why they are the way that they are, and how they relate to other things” (Thomson, 2018).
But why does it feel so hard to develop theory?
Developing theory is a process of meandering, holding on to uncertainties, and handling contradictions. Theory itself is not a one-stop-shop, it’s a continuum. It’s a craft that not only requires skill but also perseverance (Rivard, 2021). While we might sometimes hold idealistic views that theory can be a flawless product of deductive thinking (Rivard, 2021), it is often the case that theorising is messy, unfinished and mostly results in rather minimal achievements.
We also often hold normative positions that theory has to be complex, elaborate, or fit within certain “imaginary” disciplinary boundaries (Leeds-Hurwitz, 2012). Most of all, we seem to hope that our theory will swipe everyone off their feet and overshadow existing explanations – when we think theory, we think great theory or grand theory (Weick, 1995).
To add to the weight on our shoulders – the field of children’s digital lives is very multidisciplinary and rapidly evolving both in terms of children’s engagement with digital technologies that we study and the explanations we need to provide. The field grows much faster than we can monitor, eroding our confidence in being able to offer a competent synopsis of the discipline or confidently claim any novelty (Donsbach, 2006). Our knowledge tends to be practical and provisional, and that’s an uncomfortable position for any theorist. This poses the question – can we ever do it well?
How to develop a good (enough) theory?
There can’t be a one-size-fits-all solution but a good start is to try to be realistic and aim for a good enough theory that can be developed and improved over time. Facing blows and criticisms can be hard but throwing our theory “into the ring” can help hammer it into a better shape.
There can be many approaches to developing theory, here are some interesting examples:
A spiral of bite-size activities and outputs: Rivard (2021) proposes a model of theorising which includes three activities (read, reflect, write) – repeat iteratively. With each iteration, the activities are adjusted and additional elements may be added, improving cohesion, erudition, motivation, definition, imagination, explanation, presentation.
Observation – tentative theorising – justification: Swedberg (2012) proposes a general structure of theorising which relies on exploring empirical evidence, creativity and (again) iteration. The basic steps of this model include observation, conceptualising and developing an early-stage theory with tentative explanations, and justification that puts the tentative theory to the test.
Opening theory up: a frisky guide on theory development is offered by Manghani (2017) who focuses on the creative process and playfulness. The rules here include: theory should not feel like work, read and re-read the work of others, discuss your work with a selected/reading group, don’t get settled with contentment, situate your position, think of theory as a process of critical making, and keep an open mind.
You can look for further resources, guidance and inspiration on understanding and developing theory on children’s digital lives in the CO:RE theories toolkit.
Donsbach, W. (2006) The Identity of Communication Research. Journal of Communication, 56(3), pp. 437–48.
Leeds-Hurwitz, W. (2012). These Fictions We Call Disciplines. Electronic Journal of Communication/La Revue Electronique de Communication, 22(3–4).
Manghani, S. (2017). Open Theory. Media Theory, 1(1), pp. 162-167.
Rivard, S. (2021) Theory building is neither an art nor a science. It is a craft. Journal of Information Technology, 36(3): pp. 316-328.
Sutton, R. I., & Staw, B. M. (1995). What theory is not. Administrative Science Quarterly, pp. 371–384.
Swedberg, R. (2012). Theorizing in sociology and social science: turning to the context of discovery. Theory and Society, 41, pp. 1–40
Thomson, P. (2018) theory fright – part one. Available from: https://patthomson.net/2018/11/12/theory-fright-part-one/
Weick, K.E. (1995). What theory is not, theorizing is. Administrative Science Quarterly, 40(3), pp. 385–390.