Open Data as Educational Resources: The Case of Medical Education

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Open data as OERs offer new opportunities for innovation in medical education which merit further exploration and research.  Specific areas of potential include topics such as public health, global health, prescribing and patient safety, health inequalities.  There is also potential to integrate open patient data into simulation to support authentic learning.

There is no doubt that Medical Education, albeit slowly, is starting to conceptualise innovative ways to make use of open data. The literature documenting case studies is still scarce, therefore medical educationalists currently need to rely on their own creativity and pedagogic expertise to design educational interventions based on open data.

If this interests you, please read this Blog post.

This was written by Natalie and myself for the Open Education Working Group Blog, and it is a call for Medical Education practitioners that are experimenting in this largely unexplored area to share their experiences and good practice. We look forward to discussing and sharing ideas :)

 

Why Open Data is key to teach democracy and citizenship

After having just completed a short communication for the journal “Tecnologie Didattiche” on OER for teaching social cohesion, in particular which in the refugee emergency, I embrace these words completely. We, as educators, need, now more than ever, to reflect how our practice can make this whole situation take a turn for the better…

Thoughts on Open Education

It has taken mi few days to reflect about what has happened in the country I called home for the last few days, it has been sad, confusing and overwhelming.

Not long ago, with my colleague Leo Havemann (@leohavemann) started doing some research about the value of Open Data as Open Educational Resources, and with a little help from our friends, we published a book and a paper, but until this point this was just an idea in our heads, Open Data is key to teach citizenship skills and to understand democracy, and we did lots of research about it, and we saw its value at theoretical level, but when I woke up on Friday, in despair, I noticed that as Open Data and Open Education community we haven’t done enough to educate others, because the voters in the UK have been misleading with false claims and manipulated…

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Seven complex lessons in education for the future

Just a quick post to share something I’ve been thinking about lately. Some of my colleagues will know how much I like a book from French sociologist Edgar Morin: Seven complex lessons in education for the future (2002). As the years go by this is probably the one book I would suggest reading to all teachers, but also students and generally to those involved in education. 

In his book, Morin describes seven basic principles for future education, which are fundamental yet too often ignored. These seven principles highlight the importance to educate future generations to understanding the human condition, how knowledge is formed and what are the possible errors in this process, the importance of understanding each others and confronting and accepting uncertainty and complexity.

These subjects are not only very contemporary, but also particularly important in healthcare education, where students need to raise their eyes from the micro-cosmos of the  basic sciences to the macro-cosmos of social health issues, understanding how the two are interwoven and continuously inter-influenced.

As this week I was thinking about how “Human Sciences” subjects are being assessed in medicine, I had of course think of how they were taught. It would be nice to see if Open Data could be used to teach students about the “human condition” and general World Health issues. Something is starting to move in this direction. How could open data be used in Medical Sociology teaching, for example?

I would be particularly interested to see whether using open data as OERs, to facilitate students’ critical understanding of socio-cultural elements influencing , for example, health issues could nurture compassion.

However, all this to say that I really recommend reading this book, which will probably make you want read another gem: “On Complexity“, which is about… the complexity of human being. I won’t say more, for now :)

 

#Rhizo15 Week two – numbers, and a semi-organised flow of thoughts.

The quantified self

This weeks’ #rhizo15 theme has made me wander with my thoughs, at a point that I didn’t really know what to write, or where to start. But this is probably the most exciting challenge of the rhizome, that not only connects you with people and different views, but also takes you to reflective paths which make you question what you thought was a formed opinion. However, here is part of what I’ve been thinking about in relation to learning measures, facets of human experience we want to quantify and numbers, of course…

Pedagogy was born as “applied philosophy” in the Ancient Greece, so mostly a subjective, dialogic matter. However during the 8th century pedagogy acquired the status of “science” trough the tools of biology, psychology, sociology, using them to define its own aims and tools[1]. This until when, through various reinterpretations over the centuries, in the late 19th century pedagogy reached the point to define itself on strict experimental and empirical basis, often taking a reductive and anti-humanistic turn [2].

We have now passed that point though. However, while in the current academic contexts pedagogy sits between philosophic, scientific and critical paradigms, it seems that the scientific, measurable part still gets the upper hand. Especially with the use of emerging technologies in education, educators aim to “make learning visible” through these tools, which in part is absolutely great. I say in part, because have my own views on this matter, and these fall mostly in in favour of the dialectic, qualitative domain rather than the quantitative.

I’ve been reading a lot about “learning analytics” in the past few years. These have been defined as a

field associated with deciphering trends and patterns from educational big data, or huge sets of student-related data, to further the advancement of a personalized, supportive system of higher education. [3]

So what we are doing with these is essentially quantifying students’ learning and engagement looking at their grades and at how many times they viewed or posted on the VLE, to then personalise the system of higher education to increase these numbers(???). The problem is that we are “personalising” something (often a VLE, or a curriculum) for someone else, which per se is a strange concept. For example, see this presentation from Stephen Downes, where he makes the distinction between personal and personalised learning. This post nicely defines the concept:

Personalized learning, while customized for the student, is still controlled by the system. A district, teacher, company, and/or computer program serve up the learning based on a formula of what the child ‘needs’.

Shouldn’t we be allowing and supporting learners to develop personal learning landscapes, instead?

I think it is far too easy to equate meaningful participation, or learning, with numbers coming from analytics. @e_hothersall, @nlafferty and I have recently wrote a conference paper on a Twitter experience with medical students. We used SNA to look at students’ engagement, however it was quite clear that the number of tweets or mentions doesn’t account for the deeper processes of learning. They can offer an initial evaluation (and beautiful, colourful charts!), but without careful content (or discourse) analysis the portrait, in my opinion, is rather incomplete.

In medical education, but I’m sure not only here, metrics seem to prevale as objective ways to evaluate students, their participation, depth of learning, engagement. Sometimes we count whether and how many boxes they have ticked in their online portfolios, which should provide evidence of an achievement. This happens even with things such as empathy or emotions. Not only we aim to make them more explicit, but we want to do it in such a way that they can be measured. This is perhaps because doctors are increasingly held to account for qualities such as empathy and compassion. One consequence of this tendency has been, for example, the development of measurement scales; 38 different measurement scales for empathy, for instance, were described in a recent review [4]. The construct of Emotional Intelligence (EI), used within the medical academic environment to define a set of skills in which students are “trained” and then assessed for, serves exactly the same reason. Emotions are captured and measured from their instrumental use, which manifests itself in certain skills, behaviour and patterns of communication that can be learned, practiced, observed and evaluated.

This is what the psychometrics era brought in education. Measures to objectively evaluate and quantify students’ performance. But, where do the subjective and the collective fit?

This is an extract from a great paper by Brian Hodges:

The psychometric era brought not only the concept of reliability, but also other new concepts that gave credence to some practices and delegitimized others. The most important discursive shift was the negative connotation taken on by the word subjective. Framed in opposition to objective, the use of subjective in conjunction with assessment came to mean biased and biased came to mean unfair. [5]

I think we are slowly correcting this shift, and last week theme in #rhizo15 is the proof. Also, hybrid, critical pedagogies (see, for example @HybridPed) are surely highlighting the value of dialogic, unfixed, complex and dynamic elements, which cannot be quantified in education.

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P.s: As humans, though, we tend to quantify, even socially. Social Media tools have exasperated this tendency… Don’t we all get a sense of increased self-appreciation, when we get many retweets, many favourites, new followers, “likes” or comments on a blog post? Even more-or-less subconsciously, I think many look at these numbers, judging, at least initially, a person’s social media account from the amount of followers. These are numbers… but they get a (social) meaning.

References:
1 – Cambi, F. (2008). Introduzione alla filosofia dell’educazione. Editori Laterza.
2 – Striano, M. (2004). Introduzione alla pedagogia sociale. Editori Laterza.
3 – Horizon Report 2013
4 – Hemmerdinger, JM, Stoddart, SDR, Lilford, RJ. (2007). A systematic review of tests of empathy in medicine. BMC Medical Education, 7: 1-8.
5 – Hodges, B. (2013). Assessment in the post-psychometric era: Learning to love the subjective and the collective. Medical Teacher, 7: 564-568.

#rhizo15 week one – Subjectives and resuscitation

Beak to beak resuscitation?
Beak to beak resuscitation?
Chickenofeathers CC BY-NC-SA 2.0

I am finally resuscitating my blog for #rhizo15. This seems a rather good occasion to do something I was meant to do quite a while ago! Hopefully I will manage to finish this MOOC, as I’m used to sign-up and never finish them. Except #moocmooc, that was my first – and only – completed MOOC.

So, this is my post for week one, I have introduced myself to some tweeps, and I have commented on two posts (@kwhamon’s and @nlafferty’s post). Actually, I will use those comments to develop this, and try to answer David Cormier’s questions:

Build learning subjectives: How do we design our own or others learning when we don’t know where we are going? How does that free us up? What can we get done with subjectives that can’t be done with objectives?

@kwhamon’s post attracted me immediately. Keith encourages educators and learners to sustain equanimity, just like Sir William Osler did with his medical colleagues, despite the struggle of the medical profession. I agree, we, too, should maintain certain stability, even in that complex environment of any rhizomatic course. Edgar Morin talks about the need to embrace complexity as a natural part of uncertainty, which emerges from the limited human beings’ ability to comprehend phenomena. But, how can we practice this valuable lesson? Are we teaching our students to embrace the complexity and the uncertainty of the rhizome, when we provide them with a full, comprehensive list of learning objectives (and learning material to assimilate), which barely leave space for subjectives to emerge?

In my – relatively short – experience at University, I notice very little acceptance and flexibility towards complexity and the uncertainty it brings. Many students want to know exactly what information they need to master, and be sure, in that way, that they will pass the exams. This doesn’t leave space to exploration of different, but maybe more exciting, paths.

Students seem to look for the certainty provided by the pre-traced track of defined learning objectives, rather than the freedom of following “subjectives”. Is this maybe a reaction to the easier access to digital information? I do think this can be overwhelming, and rather than embarking in content research, selection and critical evaluation, it is definitely easier to be provided with the pre-packaged information to study. Building – or, more precisely, pursuing – learning subjectives requires independent, critical skills.

Designing others’ learning when we don’t know where we are going is complex. There is a delicate interlace of elements that (un)balance the freedom of personal preferences and the direction and support we need to provide students, in order to help them pursue meaningful and contextual learning. Why go through this path then? And, as Dave asks, what can we get done with subjectives that can’t be done with objectives?

I see the two things a bit like visiting a new city by following the touristic paths from a map and visiting the same city without a map, half wandering around, stopping to check the hidden, little shop, walking through a tiny passage just because there are lovely coloured doors in it, turning right because there is a signpost for the Colosseum, but then turning left again because there is an interesting, broken column I must check. What’s the difference?

In the first case I will surely view the most salient archeological monuments in less time, in the second case I will still see some of them, but I will have discovered things that are interesting to me, even if they are not defined “archeological monument”. I will probably have gotten lost and wasted time, stopped to ask information, met people, and learned my way through. This path will have maybe taken more time (or less!), but taken me to different streets and enriched me in different ways.

In real life I do both, really. It depends from the context, the people I’m with, the place I’m visiting. I still need to define my personal meaning of the word subjectives, but I think with them we can better develop our personal agency, and, to cite Vygotsky, move through and across different ZPLs to reach unexpected learning.

Thoughts on SNA and online learning

Following the previous post

The structural paradigm of  Social Network Analysis (SNA) with its constitutive theory and methods, began to emerge around the 1930s, applied and influenced by a broad range of disciplines such as sociology, psychology and statistics (Scott and Carrington, 2011).

In social network theory a social structure is represented by a group of “social actors” connected by a set of relationships. These actors – or “nodes” – can be individuals, groups, institutions, organisations or even Web pages. There can be many different kinds of relationships – or “ties” – between nodes, which constitute a “map” of connections between the actors in a network. When a social network is visualised the nodes are usually represented by points and the ties by lines linking one or more nodes.

A visualisation of the network involved in a Twitter chat for Public Health teachingwe ran at Dundee Medical School in 2012.

A visualisation of the network involved on a Twitter chat for Public Health teaching we ran at Dundee Medical School in 2012. Created with TAGSExplorer.

The focus of SNA is on the relationships between nodes and the structure of these connections. The object of study is the pattern, nature and dynamics of these interactions, as opposite to the individual characteristics of the actors. This representation allows analysis of the social processes determined by the relationships between the individuals (Martino and Spoto, 2006). SNA enables to visualise the position of a social agent within a particular network, however, because less importance is given to individuals, this theory has less consideration for the influence of personal characteristics and individual agency in determining the success of a relationship.

The connections within nodes in a network facilitate exchange of “resources”  which can be influenced by the quantity and quality of the linkages and interactions. Looking at online educational networks through a SNA lens is a way to establish wether the ways in which individuals connect with a particular environment may influence their access to information and knowledge. As Rita Kop states “the Web is portrayed as a democratic network on which peer to peer interaction might lead to a creative explosion and participative culture of activity” (Kop, 2012 p3) but how is this potential being exploited in education? What are the processes beyond this interaction and how can they be used to facilitate students access to information, knowledge and ideas?

The potential of social media in forming networks, extending students knowledge and translating this into academic achievement is impacted by a multitude of elements such as individuals’ attitudes (Morrison, 2002), University environment and socialisation processes (Yu et al., 2010). Other mechanisms influencing this process may be the particular educational practices and experiences, the success of connections, the dynamics in which participants negotiate the structure of the network and exchange practices and many others which can not be controlled.

This analysis can be enriched by Bordieau’s concept of “social capital”, which introduces a set of dynamics between the social dimension, the identity dimension (habitus) and the individual’s practice. In this system of reciprocal influences it is interesting to look at the transformation processes and effects of elements such as “weak ties”, “brokers”, “latent connections” and “structural holes” in the information flow within a network.

Acknowledging the potential of these processes and of the structure of a network is vital for educators who aim to harness the changing affordances of Web 2.0 technology applied to pedagogical interventions.  According to Morrison (2002) the configuration of the network structure has an important role on the learning processes occurring during socialisation (p 1157). This is confirmed by a recent study on student engagement via social network where Badge, Saunders and Cann (2012) suggest that “where online communication channels are adopted, teaching staff need to ensure they have adequate network connections with all students, but especially to cultivate connections with and the networks of lower-performers” (p11). Student learning is influenced by the quantity and quality of connections in a network and by the students’ position in the network, which is determined by both giving and getting information from other student (Hommes, 2012).

References:

Badge, J.L., Saunders, N.F.W., Cann, A.J. (2012). Beyond marks: new tools to visualise student engagement via social networks. Research in Learning Technology. 20:1-14.

Hommes et al. (2012). Visualising the invisible: a network approach to reveal the informal side of student learning. Advances in Health Sciences Education, 17(5), 743-757.

Kop, R. (2012). The Unexpected Connection: Serendipity and Human Mediation in Networked Learning. Educational Technology & Society, 15 (2), 2–11.

Martino, F. And Spoto, A. (2006). Social Network Analysis: A brief theoretical review and further perspectives in the study of Information Technology PsychNology Journal 4(1), 53 – 86.

Morrison, E. W. (2002). Newcomers’ relationships: the role of social network ties during socialization. Academy of Management Journal, 45(6), 1149–1160.

Scott J., Carrington P.C. (eds) (2011) Handbook of social network analysis. Sage, London

Yu, A.Y. et al. (2010). Can learning be virtually boosted? An investigation of online social networking impacts. Computers and Education, 55, pp. 1494–1503

Social Capital and online learning – a brief intro

I decided to post a brief section of my literature review after reading the article Natalie tweeted this morning, which portrays similar ideas.

I’m happy to see my reasoning is supported by others but I realise I should probably make an effort to at least try and publish some! Anyway, here it is and I’ll post more…

Access to knowledge, information and ideas is mediated by the fabric of social relationships within individuals in a social network. These can be seen as benefits gained from social interactions and can be conceptualised as “Social Capital”.

This concept, which is also a theory, is rooted in the work of several scholars, starting from Bourdieu (1986) and Coleman (1988) who provided the first definition of social capital. The theory was then extended by the work of Burt (1992), Putnam (1995) and more recently by Lin (2001).

Social capital was defined by Bourdieu as “the aggregate of the actual or potential resources which are linked to possession of a durable network of more or less institutionalized relationships of mutual acquaintance and recognition”  (Bourdieu, 1986 p 51). Social capital allows individuals to access resources – e.g. information – through relationships with members belonging to the same network (Ellison, Steinfield & Lampe, 2007). This  process is not linear or transparent, in fact a person’s actions or practices are influenced by a complexity of social forces acting in the immediate locus where the action is exploited (“field”) and a set of dispositions of thoughts and behaviours assimilated over time by the individual (“habitus”).

The dynamics of reciprocal influence between a social structure and an individual’s ways of thinking and acting are explained by Bourdieu with a formula which highlights their interdependence:

[ (habitus) (capital) ] + field = practice (Bourdieu, 1984 p101)

These factors, if applied and understood within an online educational activity, could help theorise why different students embark in different trajectories and degrees of learning and engagement. If the success of an online educational intervention depends upon the relationships, the dynamics between participants, the medium itself and the social interactions, it is vital that we understand these processes. Steinfield, Ellison and Lampe (2008) argue that “the ability to form and maintain relationships is a necessary precondition for the accumulation of social capital” (p435) and this mechanism could determine the access to certain benefits – information, knowledge – by network members.

Putnam (2000) outlined the concepts of bonding and bridging capital, which reside in the fabric of relationships within a network. Bonding capital refers to the emotional benefits that individuals who have a very close personal relationship with each other can profit from, while bridging capital encompasses informational benefits derived from weak connections. These two processes can explain the acquisition of knowledge in a community of learning.

The importance of the strength of weak ties in bridging capital was highlighted by Granovetter (1973). The power of these connections resides in the fact that they allow individuals in the social network to access pieces of information that would otherwise be inaccessible. Another concept that emphasises the importance of weak ties in the information flow is that of “structural hole” introduced by Burt (1992). A missing connection – a “hole” – between two nodes, or two networks, can be bridged by an individual, a “broker” who can span the hole, bringing together otherwise disconnected contacts (Burt, 2000).

Applying these concepts to a social network of students engaged in an online educational activity, could help understanding on how knowledge flows within the network and subsequently how to moderate and facilitate this exchange between users. Lin (2001) has emphasised the importance of social networks and interpersonal relationships in the development of social capital, which he describes as “resources embedded in a social structure which are accessed and/or mobilized in purposive actions”  (p35). The access and subsequent use of resources embedded in the network facilitates the flow of information and gives some form of profit. So we have three ingredients in the notion of social capital: resources, accessibility and use. (Lin, 2001 p35). While these elements have been conceived within studies concerning the structures of society and the use of social resources in relation to socioeconomic statuses (Lin, 1982 in Lin, 2001), it is apparent that the mechanisms of accessibility and use of resources in an online social network can influence the creation and use of social capital. It is important to highlight the fact that it is not an intrinsic characteristic of technology that allows growth of social capital: it is the specific ways that individuals use technology which determine the amount of this benefit (Valenzuela, Park & Kee, 2009).

Further reading: The Habitus of Digital Scholars by Cristina Costa – and her Blog Post

References:

Bourdieu, P. (1986) The Forms of Capital. In: John G Richardson (eds) Handbook of theory and research for the sociology of education. New York: Greenwood Press.

Burt, R.S. (1992) Structural holes: the social structure of competition. Cambridge, MA: Harvard University Press.

Coleman, J.S. (1988) Social capital in the creation of human capital. The american journal of sociology. 94(Supplement): S95-S120.

Ellison, N.B., Steinfield, C. And Lampe, C. (2011) Connection strategies: social capital implications of Facebook-enabled communication practices. New Media & Society. XX(X):1-20.

Granovetter, M. (1973) The strength of weak ties. American journal of sociology. 78: 1360-1380.

Lin N (2001) Building a network theory of social capital. In: Lin N, Cook KS and Burt RS (eds) Social Capital: Theory and Research. New York: Aldine de Gruyter. 3–29.

Putnam, R. (1995) Bowling alone: America’s declining social capital. Journal of Democracy. 6:65-78.

Putnam, R. (2000) Bowling alone: The collapse and revival of american community. New York: Simon and Schuster.

Valenzuela, S., Park, N., Kee, K.F. (2009) Is there social capital in a social network site?: Facebook use and college students’ life satisfaction, trust and participation. Journal of Computer-Mediated Communication. 14:875-901.