To cite this article: Christine Greenhow & Cathy Lewin (2016) Social media and education:
reconceptualizing the boundaries of formal and informal learning, Learning, Media and
Technology, 41:1, 6-30, DOI: 10.1080/17439884.2015.1064954
Social media and education: Reconceptualizing the boundaries of formal and
informal learning
Christine Greenhow, Counseling, Educational Psychology and Special Education, College of
Education, Michigan State University, East Lansing, MI 48824, USA
Cathy Lewin, Education and Social Research Institute, Manchester Metropolitan University,
Cheshire Campus, Crewe, CW1 5DU, UK
It is argued that social media has the potential to bridge formal and informal learning through
participatory digital cultures. Exemplars of sophisticated use by young people support this
claim, although the majority of young people adopt the role of consumers rather than full
participants. Scholars have suggested the potential of social media for integrating formal and
informal learning, yet this work is commonly under-theorised. We propose a model
theorising social media as a space for learning with varying attributes of formality and
informality. Through two contrasting case studies we apply our model together with social
constructivism and connectivism as theoretical lenses through which to tease out the
complexities of learning in various settings. We conclude that our model could reveal new
understandings of social media in education, and outline future research directions.
Keywords: Social media, informal learning, formal learning, digital cultures, teaching
Introduction
Technological advancements and pedagogies that emphasize learners as co-producers of
knowledge (Selwyn 2011) have contributed to people’s adoption of the term social media to
indicate websites and online applications that enable users to create and participate in various
communities through functions such as communicating, sharing, collaborating, publishing,
managing, and interacting (Mao 2014; Social media, n.d. ). Typical social media features
promote individual users through profile pages (eg., displaying likes, comments,
recommendations). Social media features include interconnections with other users through
links and news feeds, and sharing of user-generated content (eg., photos, ratings, tags). Pages
can be dynamically updated and content embedded (eg., embedding a video). Examples of
social media include social network sites (eg., Facebook); wikis (eg., wikispaces); media-
sharing services (eg., YouTube); blogging tools (eg., Blogger); micro-blogging services (eg.,
Twitter); social bookmarking (eg., Delicious); bibliographic management tools (eg., Zotero);
and presentation-sharing tools (eg., Slideshare) (Gruzd, Staves and Wilk 2012).
It has been argued that educators would benefit from ‘a stronger focus on students’
everyday use of and learning with Web 2.0 technologies in and outside of classrooms’
(Greenhow, Robelia and Hughes 2009, 255). Others argue that only a small proportion of
young people are actually using social media in sophisticated ways that educators might
value (Eynon and Malmberg 2011; Ito et al. 2008). Complicating this tension, there is a lack
of current models that theorise social media as a space for informal learning. There is also
considerable debate about the benefits and challenges of appropriating technologies (e.g.,
social media) in everyday use for learning and little exploration of the connections between
formal, non-formal, and informal learning such technologies might facilitate.
In this paper, we draw on relevant theory, prior literature and our own research in Europe and
the United States to suggest a model that theorizes social media as a space for learning with
varying attributes of formality and informality. Using ideas derived from social
constructivism and connectivism as promising initial lenses through which to conceptualize
social media and learning, this paper problematises ‘learning’ and ‘teaching’ across multiple
contexts, illustrating the complex relationships between formal, non-formal, and informal
learning. It considers research projects from two regions focusing on young people’s uses of
social media tools to support these varied forms of learning. Because our studies involve
participants of varying ages including teenagers and college-age youth we refer to ‘education’
broadly as spanning school and higher education contexts. We revisit the debate about social
media, or ‘social software’ in education to suggest how this model illuminates current
tensions and suggests new opportunities for research and innovation.
Research on social media in education
The educational benefits of appropriating social media into learning contexts are contested.
Research on social media in education suggests that integrating social media in learning and
teaching environments may yield new forms of inquiry, communication, collaboration,
identity work, or have positive cognitive, social, and emotional impacts (Gao, Luo and Zhang
2012; Greenhow, Burton and Robelia 2011; Greenhow and Robelia 2009a, 2009b; Pimmer,
Linxen and Grohbiel 2012; Ranieri, Manca and Fini 2012). For instance, research on learning
and social network sites (eg., Facebook) in particular has suggested their affordances for
interaction, collaboration, information and resource sharing (Mazman and Usluel 2010);
encouraging participation and critical thinking (Mason and Rennie 2007; Ajjan and
Hartshorne 2008); increased peer support and communication about course content and
assessment (DiVall and Kirwin 2012); inter-cultural language learning (Mills 2011); and their
positive effects on the expression of identities and digital literacies, particularly for
marginalised groups (Manca and Ranieri 2013).
On the other hand, researchers have warned against exploiting social media for learning.
Kirschner and Karpinski (2010) found that time spent on Facebook negatively affected
college grades. Similarly, Junco and Cotton (2013) examined how students multitask with
Facebook and found that using Facebook while doing schoolwork was negatively associated
with their overall grade point average. Students’ use of social media in extracurricular
activities was found to be distractive to learning, especially among weaker students
(Andersson et al. 2014). Finally, students were less willing to appropriate social media as a
formal learning tool, preferring it for course-related communication (Prescott, Wilson and
Beckett 2013) or using it largely for socializing and non-academic purposes (Selwyn 2009).
Despite a growing body of work concerned with social media and ‘informal learning’, ‘there
has been little serious attention to the form or nature of that learning’ (Merchant 2012, p16)
or the interrelationship with formal learning (Cox, 2013). Many studies consider
appropriation of social media within ‘formal’ and/or ‘informal’ learning, but in most cases
these terms are under-theorized or treated as binary conditions, which oversimplify the
complexities of the actual learning contexts today’s youth inhabit. Some researchers suggest
that appropriating social media can facilitate ‘seamless’ integration across learning situations
integrating formal and informal learning (Dabbagh and Kitsantas 2012). Others highlight the
challenges of appropriation (Crook 2012). Adopting a more ‘principled approach’ to
understanding these tensions and interrelationships is especially important in light of recent
technological developments, policy initiatives, changing teacher and faculty demographics,
and the realities of young people’s access to social media. As described in more detail below,
these converging trends suggest it may be more useful and realistic to theorize social media
as a space for learning with varying attributes of formality and informality.
Theorising social media as a space for learning
Social constructivism and connectivism are promising initial lenses through which to
conceptualize social media and learning with varying attributes of formality and informality.
Social constructivism draws on the idea that learning is situated in the context of
circumstances, activity or culture. What is known resides not only in the individual, a
position advanced by cognitive constructivists, but also in the collaboration and interaction
among many (Vygotsky 1978; Windshitl 2002). Conceptually, social media practices seem
well aligned with social constructivist views of learning as participation in a social context
and values of knowledge as decentralized, accessible, and co-constructed among a broad base
of users (Dede 2008); ‘knowledge’ may become ‘collective agreement’ that ‘combines facts
with other dimensions of human experience’ (ie., opinions, values) (Dede 2008, 80). Validity
of knowledge in social media environments can be negotiated through peer review in an
engaged community, and expertise involves understanding disputes and offering syntheses
accepted by the community (Dede 2008).
Similarly, connectivist ideas (Siemens 2005), which view learning as the process of creating
connections and articulating a network with nodes and relationships, also seems well aligned
with social media practices. Connectivism can best be viewed as a developing perspective
(Kop and Hill 2008) that overlaps with other more established theory like social
constructivism; it is under-researched but provides ‘fertile testing ground for ideas, which, in
turn, may lead to empirical research’ that can then refine, validate or disprove the framework
over time (Kop and Hill 2008, n.p.). Connectivism draws strength in using Internet activity
as a powerful and intuitive analogy for conceiving of distributed learning through networks;
if learning transpires via connections to nodes on the network, then perhaps the maximization
of learning can be understood by studying the properties of effective networks (Kop and Hill
2008). From the connectivist perspective, being knowledgeable can be seen as the ability to
nurture, maintain, and traverse network connections; to access and use specialized
information sources just-in-time; and as the ‘capacity to know more’ rather than the
individual’s ability to construct meaning from prior knowledge, or ‘what is currently known’
(Siemens 2005, 4). Connectivism allows for non-linearity, unintentioned ‘chaos’ and
unanticipated network effects in the learning process as learning occurs within ‘nebulous
environments of shifting core elements – not entirely under the control of the individual’
(2005, 4).
Underlying these ideas are assumptions that boundaries between learning in and out of
‘formal’ education can be porous, slippery and perplexing (Barron 2004, 2006). Definitions
of formal and informal (and non-formal) learning are contested and the interrelationships are
complex (Colley, Hodkinson, and Malcolm 2003; Sefton-Green 2004; Selwyn 2007). Some
models attempt to draw clear boundaries between each term (EC 2001; Livingstone 2001;
Eshach 2007) whilst others suggest that informal and formal learning are on a continuum
(Lai, Khaddage, and Knezek 2013; Sefton-Green 2004). Sefton-Green (2004, 6), for instance,
suggests that distinctions can be ‘more clearly made around the intentions and structure of the
learning experience.’ From a different perspective, Colley and colleagues suggest that it is
impossible and unhelpful to separate informal, non-formal and formal learning (2003) at all.
Rather they argue that ‘It is more sensible to see attributes of formality and informality as
present in all learning situations’ (2003: Executive Summary, emphasis as in original).
Furthermore, they suggest that the balance between these attributes varies and can influence
the impact of learning. They describe an approach to considering the attribute balances which
focuses on purpose (intentional/unintentional), process (structure, pedagogy, support,
assessment, etc.), location (including norms and structures such as timetables in educational
institutions), and content (high stakes knowledge to leisure interests). Although this work
stems from the lifelong learning field, the authors relate the approach to school contexts, with
one of four cases exemplifying their ideas in different contexts concerning a formal education
institution for 16-18-year-olds (Colley, Hodkinson, and Malcolm 2003).
In recent debates, many authors have not attempted to problematize the terms formal and
informal in relation to learning with social media. Informal learning is described as that
which is not directed by school or externally mandated but is learner controlled (eg.,
Ferguson et al. 2014; Luckin et al. 2009; Tan 2013;), exploratory, self-directed and
spontaneous (Dabbagh and Kitsantas 2012; Mardis 2013; Yang, Crook, and O’Malley 2013).
Many use the terms to indicate context with formal representing the confines of the classroom
and informal covering everything else from after-school clubs to the home (Ranieri and Bruni
2013; Reynolds and Chiu 2013). In some cases boundaries are acknowledged as not being
clear-cut (Schuck and Aubusson 2010) and in others informal learning is conceived as closely
entwined with formal learning (Ebner et al. 2010; Mardis 2013). Some authors avoid any
explicit definition without any clear rationale for doing so (Chen and Bryer 2012).
Notions of informal learning are often compared with non-formal, not-school learning where
one has certain objectives in mind (self-directed learning) and actively seeks information
from sources that may include peers, mentors, or media (Sefton-Green 2004; 2013). Both
terms typically contrast with definitions of formal learning situations in which some agent - a
teacher, an educational software program, or a learning management system - is directing the
student’s learning. The agent guides the student through a formalized set of objectives
typically generated by an outside authority, such as curriculum standards developed by
professional organizations or mandated by the government.
In reality we draw on social constructivist and connectivist ideas and the work of Colley,
Hodkinson, and Malcolm (2003) to argue that students may practise learning with formal,
informal, and non-formal attributes across a wide range of contexts and exercise considerable
authority over how they learn, when they learn and with whom. In Table 1 we outline our
model for theorizing social media as a space for learning with varying attributes of formality
and informality.
Table 1. A model of learning attributes, adapted from the work of Colley, Hodkinson,
and Malcolm 2003
Category
Formal attributes
Informal attributes
Social media attributes
Purpose
Learning as primary
purpose (intentional)
Learning as unintended
outcome (or not recognised)
Casual learning
Communication
Creating
Sharing
Connecting
Playing
Consuming
Externally determined
(eg. curriculum standard)
Self-determined
Community of interest
Self-determined
Socially-determined
Audience for student
work is closed, known
(teachers, parents,
classmates)
Audience for student work
may be closed/known or
open/unknown or variation
Audience for user-
generated content may be
closed/known or
open/unknown or
variation
Process of
Learning
Teacher-initiated
Incidental, experiential,
spontaneous
Self-initiated
Peer- or other-influenced
Teacher-led (didactic)
Self-directed (negotiated)
Individual agency
Self-directed
Peer- or other-influenced
Unintended network
effects
Teacher support
Peer/friend support
Network support
Summative assessment
Formative assessment
Individual Accountability
Feedback
Community evaluation
(rating, commentary,
bookmarking)
Teachers as Authority
Students can provide
input
Democratization of expertise
Expertise via
participation
Predominantly text-
based, some multimedia
Varies
Multimodal (eg. Images,
videos, tags, ratings,
hyperlinks)
Location/
context
Educational institution
(e.g., school)
Home, community, museum,
after-school club (eg. out of
school)
Online, ubiquitous
(subject to internet
access)
Time-restricted
Open-ended
Open-ended
Learning objective
No learning objective
Varies
Certification
No certification
Individual recognition
(e.g., badge)
Social recognition
Curriculum
No curriculum
Varies
Content
Knowledge acquisition
Everyday practice
User-generated,
Re-mixed
High status knowledge
Status of knowledge
irrelevant/unacknowledged
Social construction and
distribution
Knowledge as collective
agreement
Specified outcomes rigid
Specified outcomes flexible
or serendipitous
Outcomes vary
Unintended network
effects
Our model summarises the attributes proposed by Colley, Hodkinson, and Malcolm (2003),
recognising the issues arising in reducing complex concepts to a series of labels. For
example, such attributes can be contested, interpreted differently and may not be of equal
importance in different learning contexts (Colley, Hodkinson, and Malcolm 2003). Moreover,
