HuCETA: Human-Centered Embodied Teamwork Analytics

After about 7 years working on multimodal teamwork analytics (specifically in nursing simulations) with Roberto Martinez-Maldonado, and then PhDs with Vanessa Echeverria & Gloria Fernandez — and more recently in an ARC-funded project with Dragan Gasevic, Lixiang (Jimmie) Yan, Linxuan Zhao — we are moving towards theoretically grounded, open source infrastructure for analysing collocated teamwork. We’ve distilled the essence of all that we’ve learnt into a new conceptual framework called HuCETA:

Echeverria, V., Martinez-Maldonado, R., Yan, L., Zhao, L., Fernandez-Nieto, G., Gasevic, D., & Buckingham Shum, S. (2022). HuCETA: A Framework for Human-Centered Embodied Teamwork Analytics. IEEE Pervasive Computing, 1-11. https://doi.org/10.1109/MPRV.2022.3217454 [Open Access Eprint]

Abstract: Collocated teamwork remains a pervasive practice across all professional sectors. Even though live observations and video analysis have been utilized for understanding embodied interaction of team members, these approaches are impractical for scaling up the provision of feedback that can promote developing high-performance teamwork skills. Enriching spaces with sensors capable of automatically capturing team activity data can improve learning and reflection. Yet, connecting the enormous amounts of data such sensors can generate with constructs related to teamwork remains challenging. This article presents a framework to support the development of human-centered embodied teamwork analytics by 1) enabling hybrid human–machine multimodal sensing; 2) embedding educators’ and experts’ knowledge into computational team models; and 3) generating human-driven data storytelling interfaces for reflection and decision making. This is illustrated through an in-the-wild study in the context of healthcare simulation, where predictive modeling, epistemic network analysis, and data storytelling are used to support educators and nursing teams.

ICQE20 keynote: QE Visualizations as tools for thinking

We just wrapped up the 2nd International Conference on Quantitative Ethnography (open access proceedings from Springer), postponed from October due to the pandemic, in the hope that we might all yet meet up in February — alas it was not to be. However, the organisers did a really great job designing the program with a lot of informal interaction time, and the delegates threw themselves into it with a fantastic spirit, with everyone out to help everyone, as the crew figures out how to sail this recently launched ship!

If QE is new to you, it springs from the foundational work at the University of Wisconsin-Madison’s Epistemic Analytics Lab, led by the inspirational David Williamson Shaffer. The team’s publications are the source point, specifically, David’s QE book, which impressed me so much and drew me into this vision of how quant+qual could come together. In fact, I first met David in 2013 after I received a very hot tip that he was doing amazing work, relevant to a discourse analytics workshop I was chairing. His keynote was a revelation to me of his team’s long term research program, but it’s taken a while to figure out if and how to bring it into my own work.

Well, the first conference (ICQE 2019 / proceedings) was a great success, and so it was a real honour to be asked to give one of the keynote talks at this year’s conference. However, following the brilliant 2019 keynotes by Jim Gee, Dragan Gašević and Gol Arastoopour Irgens, I accepted with some trepidation to be honest, since I am far from a QE expert compared to those blazing this new trail. At the time of being invited, my team had not done any work with the main QE analysis approach, Epistemic Network Analysis, though we had drawn inspiration from its data modelling methodology in our multimodal learning analytics work.

So I thought long and hard about what I might bring to the party, with several false starts, which might have gone deeper into QE and Learning Analytics, or QE and Algorithmic Accountability. I decided in the end to go back to my roots — all the way back to my PhD in fact, focusing on the cognitive affordances of semiformal graphical representations, and what I’ve learnt since about what it takes to wield such tools in participatory design with fluency, developing open source visual hypermedia software for 20 years, and more recent work on data storytelling. What was particularly fun was bringing that into dialogue with what I was seeing in the QE webinars last year, specifically, how the community is telling its stories with visualizations. It was really enjoyable thinking what my journey might have to say to the QE community, the talk seemed to go down well, and I’m looking forward to seeing if/how these ideas take deeper root.

I am indebted to so many colleagues who have shaped those ideas, noting in particular, the Knowledge Art research and practice of my PhD student, colleague and friend, Al Selvin, tragically taken from us, far too early.

Quantitative Ethnography Visualizations as Tools for Thinking [pdf slides]

Abstract: All research must give form to data and insights. Visualizations serve as cognitive extensions that assist researchers not only in exploring their data, but in communicating findings to colleagues and broader audiences. Especially in data-intensive fields, widely used software tools define, and are defined by, research communities; you can’t fully participate in a community until you can wield its tools responsibly. In an emerging field like Quantitative Ethnography (QE), inventing its own tools, how we model and map the world are therefore defining characteristics, and merit critical reflection.

QE’s principles currently find fullest expression in Epistemic Network Analysis (ENA). It’s fair to say that the interest in ENA is attributable not only to the power of its data modelling and analysis, but also to the engaging, interactive visualizations it generates. Inspired by the ways I see ENA used, in this talk I bring my background in Human-Computer Interaction and the design of tools for working with conceptual structures, as a lens on ENA and other QEgenerated visuals. When we consider in detail how external representations serve as personal and shared cognitive tools, this illuminates current and future techniques for presenting QE analyses. A data-storytelling lens asks how the audience will engage with our insights, while participatory methods ask whether we cast them as passive recipients or active agents in validating those narratives. Moreover, as QE analyses begin to underpin new tools designed for people other than QE researchers, human-centred design should give voice to non-technical stakeholders. These lenses could point to a future in which visualization tools evolve to scaffold more participatory forms of sensemaking as an important hallmark of how QE models and narrates the world.

2 tools to help PhD students make their thinking visible

In this post, I share two ways to map your thinking, at different scales (rather like geographical maps)…

CQOCE Diagrams (or “Thesis Maps”)

One of the challenges that most/all PhD students have is to make their thinking visible — to themselves, to their supervisors, and to other researchers. There are so many potential ideas to weave into a narrative, and often different narrative pathways.

In our Learning Analytics PhD Program, we’ve been using the unpronounceable but very useful CQOCE diagram described by Luis Prieto in his Happy PhD blog. I encourage you to learn more about this:

“the diagram is commonly used in the introduction section of a dissertation, and it is meant to introduce, in graphical form, some of its main elements: the research Context, main research Question, Objectives, Contributions of your thesis and their Evaluation. However, many of us have also used it way before starting to write the dissertation book itself, as a “guiding star” when discussing with others and planning the thesis work.”

We have also been using it not just as a writing up device, but as a challenge right in the first year, to get doctoral researchers thinking about their thesis story. I tend to just call it the Thesis Map! As Luis comments, this goes through many revisions as the PhD takes its twists and turns. So in the end it serves two key purposes:

  1. As a mirror for the supervision team to reflect on how we’re doing — “Oh, the contributions I thought I was making don’t align with the Research Questions…” “What kind of evaluation will be needed next year to back up this claimed Contribution 2?…”
  2. As a navigational aid — a map — for the reader of the thesis, or indeed, for the audience if it’s used in a talk (“…in this talk I’ll be covering only this part of the map, but it shows you how this is a stage in a longer journey, in a  wider landscape…”)

Here are two recent Learning Analytics theses that use this, from Vanessa Echeverria and Carlos Prieto.

Echeverria, V. (2020). Designing Feedback for Collocated Teams using Multimodal Learning Analytics

Prieto-Alvarez, C.G. (2020), Engaging Stakeholders in the Learning Analytics Design Process

        

Note that sections of the map can then be introduced in each chapter, to remind the reader where we are on the journey.

Argument Maps

The Thesis Map provides a macro-structure for the thesis argument: once you’ve bashed your map into shape, then your high level claim to have evidenced contributions to advance knowledge that addresses important RQs just drops out naturally. But there will be many micro-level arguments in the thesis that are invisible at this scale.

Zooming in, we’re experimenting with Argument Maps, that make visible more detailed moves. Here’s my briefing during a PhD session which introduces some basics…

2 weeks later, a couple of researchers shared their maps for feedback, and both commented on how it helps clarify thinking. Thanks to Ben Hicks and Gloria Fernandez-Nieto for jumping in!

Ben used the freely accessible ArgDown website which uses a classic Argument Map notation, enriched with optional colour-coding from #tags:

Gloria used the free Compendium tool that my team developed at KMi Open University, using the IBIS notation (QuickStart Guide to install):

Note: Al Selvin inventor and power user of Compendium, used it to create multimedia maps of his thesis thinking and qualitative data analysis [screen demos], incorporating many kinds of documents (which can be dragged and dropped onto maps).

    

Far more info on Knowledge Cartography is available if this interests you.

I hope these help you make your own thinking more visible — to yourself, your supervisors, and the world  🙂

AI in Education 2020 – Best Paper :-)

I’m proud to say that a paper from a UTS team led by Roberto Martinez-Maldonado (now @Monash Uni) scooped the Best Paper award at AIED2020: The 21st International Conference Artificial Intelligence in Education, which is the premier research conference in the field. As ever, papers in this field are highly interdisciplinary, in this case seeing connections forged across educational data science, computer science, user experience and physics teaching pedagogy.

This paper is part of a series emerging from this research program into analytics for classroom proxemics, with contributions from Katerina Mangaroska, who worked in CIC on her Australian Endeavour Fellowship.

Always fun to attract some media coverage 🙂 • Technology Decisions • Architecture and Design • Education Matters • Education Today

Martinez-Maldonado, R., Echeverria, V., Schulte, J., Shibani, A., Mangaroska, K. and Buckingham Shum, S. (2020), Moodoo: Indoor Positioning Analytics for Characterising Classroom Teaching. In Proceedings of the 21st International Conference on Artificial Intelligence in Education (AIED2020), (Ifrane, Morocco, July 6–10, 2020). Springer, pp.360-373. [PDF]

Abstract. This paper presents Moodoo, a system that models how teachers make use of classroom spaces by automatically analysing indoor positioning traces. We illustrate the potential of the system through an authentic study aimed at enabling the characterisation of teachers’ instructional behaviours in the classroom. Data were analysed from seven teachers delivering three distinct types of classes to +190 students in the context of physics education. Results show exemplars of how teaching positioning traces reflect the characteristics of the learning designs and can enable the differentiation of teaching strategies related to the use of classroom space. The contribution of the paper is a set of conceptual mappings from x-y positional data to meaningful constructs, grounded in the theory of Spatial Pedagogy, and its implementation as a composable library of open source algorithms. These are to our knowledge the first automated spatial metrics to map from low-level teacher’s positioning data to higher-order spatial constructs.

CHI2020: Layered Storytelling for Multimodal Learning Analytics

As a PhD student from 1988 at the University of York HCI group and Rank Xerox Cambridge EuroPARC (as it was called then), I found my intellectual community and cut my teeth at the British HCI conference, and ACM CHI. I then spun off into various other orbits, seeing HCI as my bedrock but enjoying smaller, more focused conferences (e.g. Hypertext, CSCW, Semantic Web, OER and then ed-tech). However, my current desire to see Learning Analytics become more human-centred in its design processes, and working with Roberto Martinez-Maldonado, has looped me back into the HCI community again, and I’m thoroughly enjoying reconnecting with old and new faces!

So, here’s our latest work, building on our CHI19 paper, which is for me a very satisfying convergence of multimodal analytics, collocated teamwork, visual analytics, pedagogy and my longstanding interest in narrative. It incorporates the doctoral work of Vanessa Echeverria (who has just submitted her thesis and is now at CMU HCII) and Gloria Fernandez-Nieto (who just passed her first year with flying colours).

The teaching and learning challenge is to give instant feedback to nursing students on how well they performed as a team in treating a patient in a simulation. The research question is how to make streams of multimodal data intelligible. Enjoy!

Martinez-Maldonado, R., Echeverria, V., Fernandez-Nieto, G. & Buckingham Shum, S. (2020). From Data to Insights: A Layered Storytelling Approach for Multimodal Learning Analytics. Proc. ACM CHI 2020: Human Factors in Computing Systems (April 25–30, 2020, Honolulu, HI, USA), Paper 21, pp.1-15. https://doi.org/10.1145/3313831.3376148 [Open Access Eprint]

Abstract: Significant progress to integrate and analyse multimodal data has been carried out in the last years. Yet, little research has tackled the challenge of visualising and supporting the sensemaking of multimodal data to inform teaching and learning. It is naïve to expect that simply by rendering multiple data streams visually, a teacher or learner will be able to make sense of them. This paper introduces an approach to unravel the complexity of multimodal data by organising it into meaningful layers that explain critical insights to teachers and students. The approach is illustrated through the design of two data storytelling prototypes in the context of nursing simulation. Two authentic studies with educators and students identified the potential of the approach to create learning analytics interfaces that communicate insights on team performance, as well as concerns in terms of accountability and automated insights discovery.

Knowledge Art learning resources

Following the tragically premature death of Al Selvin in October 2015, I continued to think about how his inspirational research can live on in more than research writings. Friends and colleagues were discussing ways in which we could communicate the ideas behind Knowledge Art to reflective practitioners, in contrast to the more academic audiences we’d been engaging with.

One outcome of this came to fruition as learning resources for the University of Technology Sydney’s Master of Data Science & Innovation, specifically, for the subject I coordinated at the time, Data Visualisation & Narrative.

I prepared a reading based on the book (Publisher/Facebook) tuned to our data science students, with an assessment based on a role-play scenario that gave students the chance to practise their ‘knowledge artistry’. (This is linked to real data challenges that our students engage in with TransportNSW and the NSW Data Analytics Centre, here in Sydney.)

These are Creative Commons-licensed open access resources — do let me know if you find them useful for your own thinking, especially teaching/coaching.

PreviewScreenSnapz096 PreviewScreenSnapz095

Here’s a snapshot from that first session…

…and updated video and slides from the latest session this evening 31 March 2021 [PDF]

BCII Visualizing Complexity

Resources from today’s session with students on the UTS Bachelor of Creative Intelligence & Innovation, who are on a 2-week intensive Creativity & Complexity summer school.

Readings and multimedia to go deeper…

Human-Centred Informatics (HCI) & Complexity

Making Thinking Visible in Complex TimesThis is a video replay of how the 1960s pioneering work of Doug Engelbart foresaw our current need to “augment human intellect” to tackle the “urgent complex problems” facing society, and how this traces through to mapping dialogue and debate.

Collective Intelligence for OER Sustainability: This article considers the implications for Collective Intelligence tools, of some of complex systems concepts introduced in the summer school.

Knowledge Cartography Software Tools and Mapping Techniques [Lib][Pub]
Constructing Knowledge Art: An Experiential Perspective on Crafting Participatory Representations [Lib][Pub][Fbk].

How work and organisations are changing how knowledge flows

Hagel III, J., Seely Brown, J. & Davison, L. (2010). The Power of Pull: How Small Moves, Smartly Made, Can Set Big Things in Motion. Basic Books

New book: Chapter 1 v0.1

Al Selvin and I are working on a book to distill the key messages from his long term research programme, culminating in his PhD 18 mnths ago. So, we’re thinking aloud as we try out different ideas… reactions welcomed!

Possible titles…

Making Representations Matter: Catalyzing Collective Intelligence with Visualizations

Collective Intelligence Cartography: Emergence of a New Discipline


The word depict, from the Latin depingere, means to picture; a depiction means a representation in a picture, sculpture, or words. What this book is about is understanding how people help each other understand things by creating a picture of some kind together. By engaging people in making some kind of depiction, we can help each other explore an issue, or comprehend a situation or idea better. While much of this book will describe sophisticated kinds of depictions, like software-assisted knowledge maps, the act of engaging each other in depictions for the purpose of understanding is something that can happen at the most basic of levels.

Young Tom, six years old, had been given a small, round black compass by his parents. He was excited when he got it and ran off from the lunch table to experiment. Not long after he came back into the kitchen, on the verge of tears. “I don’t understand what it means,” he mourned. “The little needle moves all over the place. How does it help me find things?” His mother, Jackie, said, “It’s not that hard, Tom. I’ll show you.” She took some brass badges out of a drawer, and put them on the kitchen table. Tom sat him down in the chair next to her. “Now let’s pretend this one is Sally’s house,” she said, pointing at one of the badges, “and this one is the school. Where would the park be?” He moved one of the badges near one the “school”. “That’s right!” she said. “Now put the compass in the middle of them where our house would be.” Jackie took Tom’s hand, the one clutching the little compass, and moved it to the table between the objects. He put it down. Jackie pointed at the “school” and said, “Which letter on the compass is closest to the school?” “E”, Tom said. “That’s right, E is east, so that means that the school is east of our house. What about the park?” “S”, Tom said. “So which direction is the park from us?” “South,” Tom said, beginning to smile.

She moved one of the badges to the lower left, and asked “Now which direction is that?” “South… west,” said Tom, smiling. “Southwest.” “Southwest, that’s right,” his mum said. “What if it’s… west east?” he said.” “You can’t get west east,” she replied, pointing at the compass so he could see that the two directions were on opposite sides. He laughed.  “Where’s Luke’s house?” asked his father. “He’s on Peel Road,” Tom answered. “Can you point? Where do you think Luke’s house is, in relation to our house?”  asked his father. “Where’s L “It would be…” he started. She handed him a pen lid, saying “here you go, show us where Luke’s house is.” She pointed at one of the badges. “This is where our house is, show us where Luke’s house is.” ““Mummy can I just have a piece of paper?” Tom asked. “No, do it with the pen lid. Where’s Luke’s house?” He smiled and first pushed the lid farther away on the table. “No, it’s not over there”, she said, while Tom laughed. “Which way do we walk to get to Luke’s house?” He then put it more carefully to the left of the compass. “That’s right, so which way are we going to get to Luke’s house?” “North,” Tom said, smiling confidently. She pointed at her plate from lunch, farther to the left on the table. “Now Mummy’s plate is school, which way do we walk to school?” “North,” he said. “There you go!” she declared.

This story illustrates much of what this book will explore.

There was an important issue – Tom’s sadness and frustration at not understanding how the compass worked. There was someone who wanted to help Tom deal with the issue, learn something, and have fun doing it. There was the instant, unplanned inspiration – an improvisation – that Jackie came up with, to use the little shiny objects and make it into a game. She decided how the objects would play into the representation, making aesthetic choices with simple but clear tactile and visual rules, deciding (on the fly) on a compelling and engaging form that Tom could understand, enter into and be part of. She got him to point and him to move the objects around, or in the language we will use in this book, she got him to engage in the representation and in its evolution. She improvised a “script” for the game that contained a rising set of complexity and demands on Tom’s skills and evolving knowledge, or in the terms we will use in this book, she crafted a narrative with actions that had sequences and meanings. She made decisions – what we will call ethical choices – about what Tom should pay attention to, and what he could do and not do with the representation (for example, she decided that he should stick with the depiction they had created together when it came to saying where Luke’s house was, and not just draw it on paper as he asked. Jackie was sweet to Tom throughout, but also kept him firmly “on task” long enough for Tom to grasp the principles of the compass and understand how it could tell him directions between things he cared about. In doing this, Jackie helped Tom make sense of something that had been frustrating him, turning it into something he could enjoy and take forward into life.


This is what the book covers. We will discuss how we engage others in creating representations to help understand issues, but more to the point what that activity is actually composed of. As we’ll see in Chapter 2, most treatments of participatory visualizations talk about methods and outcomes, but few treat the practice  of engaging people in such visualizations as a subject worthy of attention in its own right. This book focuses on ways to look at and understand the practice of making participatory representations – the skills and considerations involved, the choices that practitioners make, and the ways in which participants can engage and make use of them.

We start with parents and kids precisely because of the everyday nature of those interactions. Helping our children understand things is not a matter of stuffing facts and ideas into their heads from outside. We know that for them to learn and grow, it has to mostly come from inside of them. Kids need to engage with situations, try them out, learn them from the inside out. They do this for themselves with their imaginative play, setting things up and manipulating them, creating whole worlds from whatever they have around them.

When our kids were small, their number one toy, in terms of getting actually used and played with over and over again, was just ordinary cardboard and wooden blocks. They could make them be anything they wanted – a house, a fort, a landscape. They were making representations and engaging in them with all of the energy and imagination they could muster.

When we as parents want our kids to learn something, especially something they are struggling with, we meet them where they are. As Jackie did with the compass, we give them tangible ways to understand their world and pick up new abilities. For example, parents best help kids with their writing assignments not by giving them general principles or the same kinds of drills they get in school. Instead they can help them look at specific sentences, words, and paragraphs in the context of what their assignment is about, and try to help them see what works or doesn’t work in that arena. The real help they provide is very close-grained, very close to the materials themselves. The tactile and visual contact with specific words and sentences — moving them around to see what works best, like Tom’s little metal items on the kitchen table — make the difference. It’s not giving kids the answers, instead it’s helping them to see how to come up with the answers themselves.

The parent’s role is to help that process along by the simultaneous close engagement with the materials and medium itself (what they are writing about and how they are doing it), with the interactions with the kids as people, with an attitude of love and hope and respect for their own intelligence — an attitude that tells the kids they will get it, they just haven’t gotten there yet. There is something about that close work with words and sentences and meanings, with styles and effects, with thinking through the consequences of different choices, providing examples but only to help them to see why it does or doesn’t work in the context, that helps kids move toward being able to do it on their own. It’s not much different from other things parents teach their kids, like how to ride bicycles. That skill, too, has to come from inside the child. A parent can’t ride the bikes for them or tell them in the abstract how to do it. Instead, the parent has to help kids to learn the little tricks of balance and navigation, and the confidence that they don’t need a puffing parent running alongside holding the bike up straight. Ultimately what matters is when could get around the block under their own power, wearing that look of pride and freedom on their faces when they had done it.

This fostering of capability in the ability to engage others in making helpful representations is a huge motivation to us. We want to be of help to people trying to achieve and express what they are trying to do with the new media for mapping the connections between ideas. If the considerations in this book can help people see for themselves why something does or doesn’t work, and come up with their own inspirations, it will have been worth it.

That is what the considerations in the remaining chapters speak to.


A second example bridges between the more commonplace examples above and the main content of this book, which mainly explores the kinds of considerations that obtain when engaging people in software-based representational tools. Though as the above discussion tried to state, really the core ideas are common to the most everyday attempts of people to help others by engaging them in making a depiction together.

A committee in a medium-sized public school district (approximately 20,000 students) in the Hudson River Valley region of New York State was tasked with analyzing the alternatives for school building capacity in the district, which has experienced declining enrollment. This highly contentious issue had come up many times before. The district’s superintendent of schools was concerned that the discussion would be unproductive, due to tensions and unsurfaced assumptions between the various interest groups (school administrators, teachers, parents, taxpayers, etc.). Every school building has an active, vocal contingent of parents and teachers who have strong interests in keeping their own local school open. Equally strong and vocal are the many local taxpayers who feel that school taxes are already too high. To address this, the superintendent asked two outside facilitators with expertise in conducting participatory knowledge mapping sessions to help run the meetings.

The two facilitators convened a series of meetings in a library of one of the schools. A committee of twenty parents, teachers, community activists, and administrators met once a week to work through the alternatives. For each meeting, the facilitators prepared an agenda with a hypermedia issue mapping tool, which was projected in front of the group on large screens. The agenda focused on various alternatives, policy matters, process considerations, and other issues.

CompendiumTemplate-SchoolDistrict

The facilitators employed a variety of approaches. First, they facilitated a general discussion of the issues involved, using a conventional Issue-Based Information System (IBIS) approach (representing discourse as issues, positions, pros, and cons) to capture and display the discussion as it proceeded. This involved rapid synthesis of what the meeting attendees were saying, thus creating nodes and links in the hypermedia tool that showed the relationship of statements to each other. They also validated the way they captured the statements by frequently asking the participants to look at the maps, asking “Does this capture what you said accurately?” Sometimes participants looked closely and provided detailed feedback (e.g, “Well, not really. What I was really trying to say was this…”). At other times, the heat of the discussion was such that it was difficult for the practitioners to intervene without running the risk of derailing the meeting’s momentum. The practitioners had to make moment-to-moment decisions on how much to intervene, and in what ways.

Between meetings, the practitioners analyzed the maps from the general discussion. They looked for recurring themes and questions and, from these, created a template covering the major considerations that would guide choices between the alternatives (see Figure 2). They then facilitated several sessions using the template to structure conversation about each of the alternatives in turn. By the fourth session, the facilitators were able to induce the participants to conduct an analysis according to the template, while still capturing as much of the side discussion and issues as possible. Also between sessions, the district office distributed via mail all of the map output in text form to all the participants.

At the end of the process, the practitioners held a plenary session for the broader community to understand the final decision. The maps of rationale and templated analysis made the pros and cons for each alternative, as well as many of the comments and points of view, clear and explicit. Even though there was little consensus that the chosen alternative was the best one, the community members completing a post-presentation questionnaire agreed that the process had been conducted in a fair manner, and that the discourse and competing points of view had been made more explicit and comprehensible than in previous years.

In this example, a very different set of considerations and techniques were employed. However, we aim to show that the framework and language we are developing — to describe how one adds value to a conversation with real time representational practice — is as applicable to this as it is to our opening kitchen scene:

PRP-ConceptualFramework


As we navigate the second decade of the 21st century, humanity confronts intensely complex challenges, at many scales from personal, to community, to national and global. Finance, health, energy, education, urbanization, terrorism: the dilemmas we face stretch to the very limit our cognitive and interpersonal capacities — to make sense of overwhelming amounts of data; to assess conflicting judgments about its trustworthiness; to resolve polarized interpretations about the implications; and to negotiate effective courses of action to which all parties can commit.

Better data and information/communication technologies (ICT) are not only drivers of these challenges, but have key roles to play in managing them. However:

more data + more processing technology ≠ more insight or wisdom

The nature of the problems we face means we will depend on nuanced human judgment over complex tradeoffs long into the foreseeable future, because despite their scientific and engineering foundations, these are not purely rational problems to be solved from first principles, using tried and tested algorithms or methods. The nature of policy formulation and implementation is fraught with the messiness of human life — social, organizational, political and cultural dimensions cannot be simply wished away. Technically sound engineering blueprints are not sufficient when designing solutions to wicked problems, whose very definition is contested. Somehow, humanity’s collective intelligence must chart courses through these white waters.

None of this is news of course, and many people are working on it. Under the broad heading of collective intelligence (including other strands of our own work) we see community activists, academics, businesses and governments seeking to improve the social fabric of the internet in order to better harness the collective intelligence of human networks, operating largely asynchronously across timezones, augmented by machine intelligence (e.g. www.ci2012.org). Another strand of work uses sensor networks and computational simulation of social systems (e.g. www.futurict.eu) to help us understand, increasingly in real time, the complex adaptive systems permeating society, but whose structure and dynamics we are only beginning to grasp — often with tragic consequences when we consider our lack of control over financial markets or medical epidemics.

Collective Intelligence Cartography (CIC) occupies a different niche. All of the above work will generate symbolic representations of many sorts, around which many meetings will be held to figure out what they mean, and it is here that CIC makes a contribution. Our focus is on a pervasive, critical, and hence surprisingly neglected piece of the collective intelligence jigsaw puzzle, namely, how do we improve our capacity to use such representations when we meet?

This focus on the dynamics of collective intelligence in small scale, synchronous contexts complements the social-semantic web/collective intelligence focus on large scale, asynchronous interaction.

CIC also complements the big data and simulation efforts, shifting attention from machine-mining patterns in relatively low-level data to the highest levels of meaning-making that humans are capable of:

  • wrestling with ethical dilemmas
  • resolving conflicts between diverse stakeholders
  • crafting metaphorical power through stories
  • empathizing by placing oneself in another’s shoes

This is the next step from machine-generated information visualizations to their manipulation and annotation as people discuss them, and to the manual crafting of representations (with or without computational aids) that reflect a team’s evolving understanding of a problem or the creative process as a design solution emerges.

This focus takes us back to humanity’s most established mode of information diffusion and collective sensemaking: talking face to face, and inscribing marks in dirt, leaves and clay. In an earlier book, we introduced the concept of maps as follows:

Maps are one of the oldest forms of human communication. Map-making, like painting, pre-dates both number systems and written language. Primitive peoples made maps to orientate themselves in both the living environment and the spiritual worlds. Mapping enabled them to transcend the limitations of private, individual representations of terrain in order to augment group planning, reasoning and memory. Shared, visual representations opened new possibilities for focusing collective attention, re-living the past, envisaging new scenarios, coordinating actions and making decisions.

Maps mediate the inner mental world and outer physical world. They help us make sense of the universe at different scales, from galaxies to DNA, and connect the abstract with the concrete by overlaying meanings onto that world, from astrological deities to signatures for diseases. They help us remember what is important, and explore possible configurations of the unknown. (Preface to Knowledge Cartography, 2008)

Thus, we are interested in how teams build new meaning using ‘representational artifacts’ which take into account all the ‘hard’ technical criteria as well as the ‘softer’ human criteria mentioned above. In millions of meetings today, people will be scribbling and sketching on paper and whiteboards; typing lists of bullet points and outlines on screen; displaying, annotating and sharing photos, diagrams, maps and websites. However, CIC is not about collaboration and visualization software per se (although much of our work has been with hypermedia visualization tools), but about the human skillset needed to wield these and non-digital artifacts effectively, in real time, to build new meaning in a group. We’ve all been in meetings where a shared display added little value — but we’ve all been in meetings when the right representation at the right moment helped to harness the collective energy and wisdom in the room, people connect with each other and the problem at a deeper level, and things move forward tangibly. What does someone do with a representation to catalyse such moments?

We need to attend to the people who know how to do this, and learn from them (and instructively, from those who are less fluent). We argue that what we call Participatory Representational Practice is a poorly understood but vital new civic skill for all types of collaborative knowledge work, where the complexity of the problem requires, or benefits from, the construction of a collectively owned representational artifact — whether scribbled on a napkin or detailed in a multiuser computational modeling tool. Hence, this includes meeting facilitators, but extends to many others, such as students, teachers, designers, academics and policy analysts.

To substantiate this claim, we have been documenting the vacuum in our current understanding, both in academic research and in practitioners’ state-of-the-art: nobody seems to have articulated the experience and skillset of this new breed of ‘cartographers’.

Schön (1983) insisted that there is an artistry to professional practice that, although difficult to describe, nonetheless informs and shapes what practitioners actually do:

Let us search … for an epistemology of practice implicit in the artistic, intuitive processes which some practitioners do bring to situations of uncertainty, instability, uniqueness, and value conflict. (1983: 49)

This book intends to contribute to that search. We describe the process by which we have developed a language to describe the distinctive experience and skillset that marks these people out (Chapter X). To give you a feel for what’s to come, in developing a language capable of expressing what we found when studying such practitioners, we found it necessary to draw from Aesthetics (how practitioners shape and craft the representation), Ethics (how a practitioner’s actions affect other people), Narrative (meaning and causality applied to the flow of events), Sensemaking (the ways in which practitioners deal with situations of doubt or instability) and Improvisation (the spontaneous, creative moves that practitioners can make).

This language has emerged in dialogue with designing ways of seeing this in action by analyzing and visualizing video data at different scales, both quantitatively and qualitatively (Chapter X). This lays the conceptual and empirical foundations for future practitioner training and software development (Chapter X).

To conclude, in an age of unprecedented complexity, we urgently need people who are fluent at “augmenting human intellect” with new kinds of “concept structures”, to borrow Doug Engelbart’s iconic 1963 language. Our schools, universities and workplaces train us to read and write as solo authors and speakers, paying little or no attention to the pervasive role of representations in our thinking with others. Understanding the experience and skillset that people fluent in such practice is a key first step. Perhaps this may come to be seen as a 21st century literacy — reading and writing symbolically in ways designed specifically to build real-time collective intelligence.

We hope this whets your appetite. If so, then let us take you on a journey…

Al Selvin and Simon Buckingham Shum

Making Representations Matter: Al Selvin PhD

In an earlier post on Knowledge Art, a term coined by friend and colleague Al Selvin, I opened with this question:

What does it mean to be literate in crafting representations that help a group make sense of the world?

Arguably, this is a literacy of first order importance as we confront novel challenges of overwhelming complexity, which will always (and increasingly) require external representations as extensions and augmentations of personal and collective cognition. However smart our  technologies are, people must then engage in sensemaking activity around them to decide how to act. If a group is building a model of the world in some medium (paper +/or digital) what is the skillset to orchestrate effective interaction around and via that representation?

Compendium has provided us with a long term vehicle to explore these questions specifically around fluency with participatory hypermedia and knowledge cartography for sensemaking, but our interest has stretched beyond any one software tool or practice.

I’m delighted to say that Al has now completed his doctoral research, which has been unpacking this question very elegantly (see his Knowledge Art blog), and his dissertation is online today as a KMi Technical Report:

Selvin, A.M. (2011). Making Representations Matter: Understanding Practitioner Experience in Participatory Sensemaking. Doctoral Dissertation, Knowledge Media Institute, The Open University, Milton Keynes, UK. Available as Eprint: http://oro.open.ac.uk/30834

Abstract: Appropriating new technologies in order to foster collaboration and participatory engagement is a focus for many fields, but there is relatively little research on the experience of practitioners who do so. The role of technology-use mediators is to help make such technologies amenable and of value to the people who interact with them and each other. When the nature of the technology is to provide textual and visual representations of ideas and discussions, issues of form and shaping arise, along with questions of professional ethics. This thesis examines such participatory representational practice, specifically how practitioners make participatory visual representations (pictures, diagrams, knowledge maps) coherent, engaging and useful for groups tackling complex societal and organizational challenges. This thesis develops and applies a method to analyze, characterize, and compare instances of participatory representational practice in such a way as to highlight experiential aspects such as aesthetics, narrative, improvisation, sensemaking, and ethics. It extends taxonomies of such practices found in related research, and contributes to a critique of functionalist or techno-rationalist approaches to studying professional practice. It studies how fourteen practitioners using a visual hypermedia tool engaged participants with the hypermedia representations, and the ways they made the representations matter to the participants. It focuses on the sensemaking challenges that the practitioners encountered in their sessions, and on the ways that the form they gave the visual representations (aesthetics) related to the service they were trying to provide to their participants. Qualitative research methods such as grounded theory are employed to analyze video recordings of the participatory representational sessions. Analytical tools were developed to provide a multi-perspective view on each session. Conceptual and normative frameworks for understanding the practitioner experience in participatory representational practice in context, especially in terms of aesthetics, ethics, narrative, sensemaking, and improvisation, are proposed. The thesis places these concerns in context of other kinds of facilitative and mediation practices as well as research on reflective practice, aesthetic experience, critical HCI, and participatory design.

Many congratulations to him on completing this step of the journey, and I can’t wait to see what the next step holds in store.

A recent journal paper provides a partial account of this work:

Selvin, A., Buckingham Shum,S.J. & Aakhus, M. (2010). The Practice Level in Participatory Design Rationale: Studying Practitioner Moves and Choices. Human Technology (Special Issue on Creativity and Rationale, Ed. John Carroll), 6, (1), pp. 71–105. [www.humantechnology.jyu.fi]. Preprint: http://oro.open.ac.uk/20948

The webcast and slides from a KMi seminar he gave are below:

Al Selvin, KMi Webinar [click to replay in new tab]
Al Selvin, KMi Seminar, 8 June, 2011 [click to replay in new tab]

Mapping PhD research in Compendium

Colleague and part-time KMi PhD student Al Selvin has posted a fantastic lightning tour of his PhD project database in Compendium. This illustrates very well the power of lightweight semantics in a flexible, visual hypermedia environment, for tracking over a long period issues, ideas, themes and documents with many levels of connection. Even better, he’s placed his analysis maps online as open research data.

(Background: in 2002 Al’s team at NYNEX licensed Compendium to KMi for co-development as an open source tool. Since then, with continuous funding primarily from the UK Research Councils, it has developed into a robust knowledge management tool, with >100,000 downloads and an active user community, plus significant contributions to the codebase coming from non-OU developers)

Watch the movie — but here are a few stills to give a feel for the range of interlinked representations that he uses.

(A series of podcasts from the e-Dance project describes in detail the use of Compendium as a tool for compiling, presenting, and teaching with multimedia research resources, in support of arts and humanities research, such as choreographic research, which sees the practice as research. See also the PARIP conference where we ran a workshop, introducing Compendium within Selvin’s Knowledge Art framework).

Analysis maps homepage:

Summary points from video analysis sessions, connected to maps containing all data for each session

Mapping the emerging taxonomy from the data

A map linking all the representational artifacts used to analyse video data

Using the tagging interface to filter and browse the literature review maps

Visualizing Discourse & Reasoning @VAST2010

The leading conference on designing and evaluating tools for visual analytics has just gone live with its website: Visual Analytics Science & Technology 2010, which forms part of the huge VisWeek set of co-located conferences (Oct. 24-29, Salt Lake City). VAST includes a challenge which enables different teams to compete, making more systematic comparison possible.

Of notable importance – from this corner of the planet – is their call for submissions on:

Discourse visualization and visual representations of the reasoning process

This is a new element of the conference that I’m delighted to see them taking onboard, recognising the significant growth in visualizing different forms of discourse, such as dialogue around wicked problems, deliberation over design options, and argumentation over truth/plausibility. Arguably, these are amongst the most complex, highest order forms of human reasoning, and require rather different computation and human interaction to rendering huge, structured datasets.

I encourage everyone working in this field to consider submitting. From the CfP, here’s how the conference frames the challenge:

Visual Analytics is the science of analytical reasoning supported by highly interactive visual interfaces. People use visual analytics tools and techniques in all aspects of science, engineering, business, and government to synthesize information into knowledge; derive insight from massive, dynamic, and often conflicting data; detect the expected and discover the unexpected; provide timely, defensible, and understandable assessments; and communicate assessments effectively for action. The issues stimulating this body of research provide a grand challenge in science: turning information overload into the opportunity of the decade. Visual analytics requires interdisciplinary science, going beyond traditional scientific and information visualization to include statistics, mathematics, knowledge representation, management and discovery technologies, cognitive and perceptual sciences, decision sciences, and more. Your submission should help develop and/or apply Visual Analytics, clearly showing an interdisciplinary approach.

Modelling Scholarly Debate: Neil Benn PhD

Another of the Hypermedia Discourse group’s students, Neil Benn, passed his thesis viva in July, with a strong defence of his dissertation Modelling Scholarly Debate: Conceptual Foundations for Knowledge Domain Analysis Technology. Co-supervised with John Domingue (KMi) and Clara Mancini (formerly KMi and now in Computing), Neil’s work picked up the challenge raised in previous work by the group (IJHCS article), namely to use a  constrained set of “Cognitive Coherence Relations” (CCR) to model in a uniform way the relationships between publications, people and arguments.

I’m really excited about the result of the work, as summarised in Neil’s abstract:

Knowledge Domain Analysis (KDA) research investigates computational support for users who desire to understand and/or participate in the scholarly inquiry of a given academic knowledge domain. KDA technology supports this task by allowing users to identify important features of the knowledge domain such as the predominant research topics, the experts in the domain, and the most influential researchers. This thesis develops the conceptual foundations to integrate two identifiable strands of KDA research: Library and Information Science (LIS), which commits to a citation-based Bibliometrics paradigm, and Knowledge Engineering (KE), which adopts an ontology-based Conceptual Modelling paradigm. A key limitation of work to date is its inability to provide machine-readable models of the debate in academic knowledge domains. This thesis argues that KDA tools should support users in understanding the features of scholarly debate as a prerequisite for engaging with their chosen domain.

To this end, the thesis proposes a Scholarly Debate Ontology which specifies the formal vocabulary for constructing representations of debate in academic knowledge domains. The thesis also proposes an analytical approach that is used to automatically detect clusters of viewpoints as particularly important features of scholarly debate. This approach combines aspects of both the Conceptual Modelling and Bibliometrics paradigms. That is, the method combines an ontological focus on semantics and a graph-theoretical focus on structure in order to identify and reveal new insights about viewpoint-clusters in a given knowledge domain. This combined ontological and graph-theoretical approach is demonstrated and evaluated by modelling and analysing debates in two domains. The thesis reflects on the strengths and limitations of this approach, and considers the directions which this work opens up for future research into KDA technology.

The thesis is published as a KMi Technical Report:

Benn, N.J.L. (2009). Modelling Scholarly Debate: Conceptual Foundations for Knowledge Domain Analysis Technology. Doctoral Dissertation, available as: Technical Report KMI-09-04, Knowledge Media Institute, The Open University, UK. http://kmi.open.ac.uk/publications/pdf/kmi-09-04.pdf

A distillation of work midway through the project was presented as:

Benn, N., Buckingham Shum, S. Domingue, J. and Mancini, C. (2008). Ontological Foundations for Scholarly Debate Mapping Technology2nd International Conference on Computational Models of Argument (COMMA ’08), 28-30 May, 2008, Toulouse, France. IOS Press