The document outlines the assignments for a course on knowledge media design, including an ontology task defining key concepts and their relationships, presentations analyzing frameworks and design challenges, and a final report proposing a solution to a design challenge. It provides examples of framework visualizations and discussions of concepts like design, knowledge, and media to guide the assignments. Students are asked to analyze relationships between pairs of concepts and propose innovative approaches to addressing knowledge media design problems.
Slides from my presentation at the ECIR 2012 workshop on "Information Retrieval Over Query Sessions" (SIR2012) held in Barcelona, Spain.
Title: Exploring Session Search
Abstract:
Exploratory search is typically characterized by recall-oriented information needs and by uncertainty and evolution of the information need. As searchers interact with the system, their understanding of the topic evolves in response to found information. These two characteristics – uncertainty of information need and the desire to find multiple documents – drive the need to run multiple queries. Furthermore, these queries are not independent of each other because they often retrieve overlapping sets of documents. Yet traditional information retrieval systems often treat searchers’ queries in isolation, ignoring the evolution of a person’s understanding of the information need and the historical coupling among queries.
I this talk, I will describe some interface ideas we're exploring to help people incorporate their search history into their ongoing retrieval and sense-making tasks, and will touch on some issues related to retrieval algorithms and evaluation.
Modeling Framework to Support Evidence-Based DecisionsAlbert Simard
Describes a framework for modelling in a regulatory environment founded on sound scientific and knowledge management concepts. It includes 1) demand (isue-driven) and supply (model driven) approaches to modelling, 2) balancing modeler, manager, and user perspectives, 3) documentation to demonstrate due diligence, and a 700-term glossary.
Design considerations for machine learning systemAkemi Tazaki
Critical commentary based on my professional experience in designing apps with artificial intelligence and on desktop research. Presentation slides for Botscampe 2016.
Slides from my presentation at the ECIR 2012 workshop on "Information Retrieval Over Query Sessions" (SIR2012) held in Barcelona, Spain.
Title: Exploring Session Search
Abstract:
Exploratory search is typically characterized by recall-oriented information needs and by uncertainty and evolution of the information need. As searchers interact with the system, their understanding of the topic evolves in response to found information. These two characteristics – uncertainty of information need and the desire to find multiple documents – drive the need to run multiple queries. Furthermore, these queries are not independent of each other because they often retrieve overlapping sets of documents. Yet traditional information retrieval systems often treat searchers’ queries in isolation, ignoring the evolution of a person’s understanding of the information need and the historical coupling among queries.
I this talk, I will describe some interface ideas we're exploring to help people incorporate their search history into their ongoing retrieval and sense-making tasks, and will touch on some issues related to retrieval algorithms and evaluation.
Modeling Framework to Support Evidence-Based DecisionsAlbert Simard
Describes a framework for modelling in a regulatory environment founded on sound scientific and knowledge management concepts. It includes 1) demand (isue-driven) and supply (model driven) approaches to modelling, 2) balancing modeler, manager, and user perspectives, 3) documentation to demonstrate due diligence, and a 700-term glossary.
Design considerations for machine learning systemAkemi Tazaki
Critical commentary based on my professional experience in designing apps with artificial intelligence and on desktop research. Presentation slides for Botscampe 2016.
A quick little upload that outlines why I'm doing a thesis in transmedia storytelling. I've just handed it in but I thought I would put this up for anyone who was interested.
Using visualization to show distributions of taxonomic data to give context and show trends in your data. Presented by Kevin W. Boyack of SciTech Strategies, Inc. at the 2012 Data Harmony User Group meeting on February 9, 2012 at the Access Innovations, Inc. offices.
Reading academic papers is one of the most important parts of scientific research. However, junior graduate students may spend a lot of time learning how to read papers efficiently and effectively. In this talk, I will discuss some basic issues and introduce useful websites/tools/tips for paper reading.
Content Analysis Overview for Persona DevelopmentPamela Rutledge
After developing an Ad Hoc persona as the core of your engagement strategy, it's important to test your assumptions against real people and real data. Content analysis is a methodology for evaluating text-based data that can be gathered from social media tools.
This is the presentation of the Juan Cruz-Benito’s PhD “On data-driven systems analyzing, supporting and enhancing users’ interaction and experience” that was defended on September 3rd, 2018 in the Faculty of Sciences at University of Salamanca Spain. This PhD was graded with the maximum qualification “Sobresaliente Cum Laude”.
SDD Symposium - Bringing Design to Dialogic Design Peter Jones
Design competencies address many gaps in current SDD practice:
- Lack of methods defined for Discovery
- Contested ways of enacting Action from planning
- Creative approaches to coalition formation
- Ability to better adapt & stage practices to differing cultures
SMART Infrastructure Facility was pleased to host Dr Ruth Deakin Crick, a Reader in Systems Learning and Leadership, at University of Bristol, UK as she presented ‘Learning Journeys: making learning visible in developing infrastructure futures’ as part of the SMART Seminar Series on October 16th, 2014.
Open Learning Analytics panel at Open Education Conference 2014Stian Håklev
The past five years have seen a dramatic growth in interest in the emerging field of Learning Analytics (LA), and particularly in the potential the field holds to address major challenges facing education. However, much of the work in the learning analytics landscape today is closed in nature, small in scale, tool- or software-centric, and relatively disconnected from other LA initiatives. This lack of collaboration, openness, and system integration often leads to fragmentation where learning data cannot be aggregated across different sources, institutions only have the option to implement "closed" systems, and cross disciplinary research opportunities are limited. Beyond the immediate concerns this fragmentation creates for educators and learners, a closed approach dramatically limits our ability to build upon successes, learn from failures and move beyond the "pockets of excellence (and failures)? approach that typifies much of the educational technology landscape.
The potential benefits of openness as a core value within the learning analytics community are numerous. Learning initiatives could be informed by large scale research projects. Open-source software, such as dashboards and analytics engines, could be available free of licensing costs and easily enhanced by others, and OERs could become more personalized to match learners' needs. Open data sets and reproducible papers could rapidly spread understanding of analytical approaches, enabling secondary analysis and comparison across research projects. To realize this future, leaders within the learning analytics, open technologies (software, standards, etc.), open research (open data, open predictive models, etc.) and open learning (OER, MOOCs, etc.) fields have established a "network of practice" aimed at connecting subject matter experts, projects, organizations and companies working in these domains. As an initial organizing event, these leaders organized an Open Learning Analytics (OLA) Summit directly following the 2014 Learning Analytics and Knowledge (LAK) conference this past March as means to further the goal of establishing "openness' as a core value of the larger learning analytics movement. Additional details on the Summit and those involved can be found at: http://www.prweb.com/releases/2014/04/prweb11754343.htm.
This panel session will bring together several thought leaders from the Open Learning Analytics community who participated in the Summit to facilitate an interactive dialog with attendees on the intersection of learning analytics and open learning, open technologies, open data, and open research. The presenters represent a broad range of experience with institutional analytics projects, an open source development consortium, the sharing of open learner data, and academic research on open learning environments.
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A quick little upload that outlines why I'm doing a thesis in transmedia storytelling. I've just handed it in but I thought I would put this up for anyone who was interested.
Using visualization to show distributions of taxonomic data to give context and show trends in your data. Presented by Kevin W. Boyack of SciTech Strategies, Inc. at the 2012 Data Harmony User Group meeting on February 9, 2012 at the Access Innovations, Inc. offices.
Reading academic papers is one of the most important parts of scientific research. However, junior graduate students may spend a lot of time learning how to read papers efficiently and effectively. In this talk, I will discuss some basic issues and introduce useful websites/tools/tips for paper reading.
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After developing an Ad Hoc persona as the core of your engagement strategy, it's important to test your assumptions against real people and real data. Content analysis is a methodology for evaluating text-based data that can be gathered from social media tools.
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SDD Symposium - Bringing Design to Dialogic Design Peter Jones
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The past five years have seen a dramatic growth in interest in the emerging field of Learning Analytics (LA), and particularly in the potential the field holds to address major challenges facing education. However, much of the work in the learning analytics landscape today is closed in nature, small in scale, tool- or software-centric, and relatively disconnected from other LA initiatives. This lack of collaboration, openness, and system integration often leads to fragmentation where learning data cannot be aggregated across different sources, institutions only have the option to implement "closed" systems, and cross disciplinary research opportunities are limited. Beyond the immediate concerns this fragmentation creates for educators and learners, a closed approach dramatically limits our ability to build upon successes, learn from failures and move beyond the "pockets of excellence (and failures)? approach that typifies much of the educational technology landscape.
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See screencast of Researchr in action here: http://vimeo.com/25295002
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4. Example of a Framework Visualization
S a n d e r s , L i z . " A n E v o l v i n g M a p o f D e s i g n P r a c t i c e a n d D e s i g n R e s e a r c h . "I n t e r a c t i o n s
15.6 (2008): 13-17 5 . 6
5. ONTOLOGY TASK: In computer and information science an ontology formally represents
knowledge as a set of concepts within a domain and the relationships among those concepts
In this course we are examining concepts related to how media can be designed and adapted to
promote building and sharing of knowledge. Within that context we are exploring the meaning of
design and waymaking, knowledge and interdisciplinarity and media and embodiment.
The ontology task asks you to discuss relationships between those pairs of concepts or any other
set of 3 pairs of concepts. The task has three stages
1) for each pair specify each concept with a short (about 100 +/- 50 words) definition; pick a
definition that you are comfortable with and that can be linked a reputable and citable source;
2) briefly discuss how the two concepts are related to each other and the overall goals of the
course as you understand them,
3) repeat the exercise for two more concept pairs of your choosing. You should end up with 5
pages of text.
The report should be about 5 pages (1.5 line spacing 2000 words).
9. Kant’s conceptualization of concept formation
Kant investigated the way that empirical a posteriori concepts are created. The logical acts
of the understanding by which concepts are generated as to their form are:
1.comparison, i.e., the likening of mental images to one another in relation to the unity of
consciousness;
2.reflection, i.e., the going back over different mental images, how they can be
comprehended in one consciousness; and finally
3.abstraction or the segregation of everything else by which the mental images differ ...
In order to make our mental images into concepts, one must thus be able to compare,
reflect, and abstract, for these three logical operations of the understanding are essential
and general conditions of generating any concept whatever. For example, I see a fir, a
willow, and a linden. In firstly comparing these objects, I notice that they are different from
one another in respect of trunk, branches, leaves, and the like; further, however, I reflect
only on what they have in common, the trunk, the branches, the leaves themselves, and
abstract from their size, shape, and so forth; thus I gain a concept of a tree. — Logic, §6
From Wikipedia entry on Concept (http://en.wikipedia.org/wiki/Concept)
10. DESIGN AS A PROCESS FOR
FORMATTING DATA INTO KNOWLEDGE
Data/Information Input Biased by a Concern or Need
Design Learning Problem Diagnostics Systems
Concept Solving Engineering
Explore Comprehension Discovery Initiation Identify Objectives
(comparison) Application Definition Sensing Specify Criteria
Prototype Analysis Design Analysis Map Relationships
(reflection) Synthesis Decision Making Diagnosis Identify Alternatives
Specify Evaluation Action Planning Reporting Evaluate Alternatives
(abstraction) Innovation Mobilization Indexing Choose One or Two
Knowledge Output Useful in Addressing Concern or Need
12. Before Dec 22, all students will have submitted a final design brief outlining their KMD concept or
process innovation and how their analysis suggests a re-design. The brief should have three sections:
1) Map/Indentify the Design Challenge Conceptualization and Desired Outcomes
identify the KMD domain that you will focus on and a particular challenge you will be exploring
provide a history of previous attempts to conceptualize the challenge and contrast them with yours
describe the design constraints, usability, and goals that are guiding your design conceptualization
provide a summary of uncertainties and gaps in knowledge related to the proposed approach
2) Prototype
Consider a few implications of the way that you have chosen to conceive of the challenge
develop a framework for evaluating the outcomes of the suggested solutions to the challenge,
think of situations and people who could find your approach useful
imagine possible impacts of different possible solutions consistent with your constraints and values
determine which of these you want to specify in greater detail and why
3) Detail/Specify
identify a specific use case and user community that could appreciate your solution
summarize why the solution is appropriate at the suggested time and place
analyze strategies for obtaining confirming your expectations
analyze potential sources of support for implementing further study and refinement of your concept
analyze potential resistance to or criticism of your design conceptualization
4) Synopsis
13. Integrative Knowledge Media Design Research Model
People Seeking & Sharing Information
(People)
Sense-making, Knowledge Building, Community-of-Practice
Colleges & Universities, Internet, Libraries, Media, Publishing, Consulting
Knowledge Media Design
a design process to explore ways of enabling
formatting of data and presentation of information
so as to allow groups to build, represent, and mobilize
contextualized knowledge within a system
Knowledge Systems Systems of Devices & Media
(Place) (Technology)
Academic Disciplines & Media Industrial Design & Engineering,
Higher & Professional Education ICT, Electronics, Informatics
14. Integrative Knowledge Media Design Research Model
People Seeking & Sharing Information
(People)
Sense-making, knowledge Buiding, Community-of-Practice
Colleges & Universities, Internet, Libraries, Media, Publishing, Consulting
Knowledge Media Design
a design process to explore ways of enabling
formatting of data and presentation of information
so as to allow groups to build, represent, and mobilize
contextualized knowledge within a system
Knowledge Media
Designer
(knowledge integrationist)
15. Matrix of themes and Challenges to be considered in the course
Sub-Theme: Having Knowledge & Visualizing of Actions Embodying Interactions
Challenge: Mapping Intentions & Consequences & Solutions
Design &
Wayfinding
Knowledge &
Interdisciplinarity
Media &
Embodiment
21. Attribute Match Standing Authority
Qualities Relevance/Pertinence Certification / Authenticity Credibility/Trust
Validity (guidance/true)
How it functions? Perceived Usability Persuasively True Evident Quality of
Interpretational, (Material) (Real) Source (Ranking)
Epistemological
Precedence (perspectives/
insight/ discrimination)
Perceived Usefulness Persuasive Warrant Evident Credentials
What is it about?
(Germane) (Acceptable) (Clarity)
Topical, Ontological
Maturity (feasibility)
Perceived Utility Persuasively Feasible Evident Impact
How can it be used?
(Actionable) (Reasonable) (Reliable)
Motivational, Methodological
22. Attribute Objective Representation Subjective Representation
(Extracted from data analysis) (Introspective interpretation)
Match Relevance – Statistical,. Pertinence – Judged.
Claims in source (meaning) matching query string useful to question
Standing Certification – Warranted by Authenticity – Authorial intent,
Warranted linking of claim to journal, editor, publisher, revealed & accessible in source
evidence (agency) repository, organization etc.
Authority Credibility – Source’s Trust – Subjective recognition
Evidence in source (power) credentials, citations, history of trustworthy source
23. Three Articulated Perspectives on Information Significance
Reflection
Judgement
Meaning
How the Information is used
(diffusion/application)
Pertinence
(subject)
User
(governance/consumption)
MATCH
Server
(instruments)
Relevance