2015
17.
Parsons, Paul; Sedig, Kamran; Mercer, Robert E.; Khordad, Maryam; Knoll, Joan; Rogan, Peter
Visual analytics for supporting evidence-based interpretation of molecular cytogenomic findings Conference
Proceedings of the 2015 Workshop on Visual Analytics in Healthcare (VAHC ’15) at IEEE VIS 2015, 2015.
Links | BibTeX | Tags: healthcare, visual analytics
@conference{Parsons215a,
title = {Visual analytics for supporting evidence-based interpretation of molecular cytogenomic findings},
author = {Paul Parsons and Kamran Sedig and Robert E. Mercer and Maryam Khordad and Joan Knoll and Peter Rogan},
doi = {10.1145/2836034.2836036},
year = {2015},
date = {2015-10-21},
booktitle = {Proceedings of the 2015 Workshop on Visual Analytics in Healthcare (VAHC '15) at IEEE VIS 2015},
keywords = {healthcare, visual analytics},
pubstate = {published},
tppubtype = {conference}
}
16.
Sedig, Kamran; Parsons, Paul; Naimi, Anthony; Willoughby, Keith
Reconsidering healthcare evidence as dynamic and distributed: the role of information and cognition Journal Article
In: International Journal of Evidence-Based Healthcare, vol. 13, no. 2, pp. 43–51, 2015, ISSN: 1744-1609, (ISBN: 0000000000000).
Abstract | Links | BibTeX | Tags: distributed cognition, healthcare
@article{Sedig2015,
title = {Reconsidering healthcare evidence as dynamic and distributed: the role of information and cognition},
author = {Kamran Sedig and Paul Parsons and Anthony Naimi and Keith Willoughby},
url = {https://www.dvclab.net/wp-content/uploads/2020/04/Sedig-et-al-2015-IJEBH.pdf},
doi = {10.1097/XEB.0000000000000030},
issn = {1744-1609},
year = {2015},
date = {2015-01-01},
journal = {International Journal of Evidence-Based Healthcare},
volume = {13},
number = {2},
pages = {43--51},
abstract = {AIM. The basic thrust of evidence-based healthcare is that current best evidence should be used explicitly and judiciously for diagnosis, management, and other activities in healthcare settings. For this to be possible, researchers, practitioners, and other stakeholders must have a clear and accurate conceptualization of what constitutes ‘evidence’ in healthcare environments, and the manner in which it is used in decision-making and other activities. Currently, the dominant conceptualization of evidence is that of a body of information that can be retrieved by stakeholders for use in healthcare practice. The aim of this article is to critically examine the concept of evidence, particularly in light of recent models of human cognition and information use in decision-making and other cognitive activities. METHODS. In this theoretical article, we employ both analytical and synthetic methods to critically examine the concepts under investigation. Key concepts, such as evidence and information, and the essential relationships between them are analyzed from the vantage point of cognitive science, information science, and other relevant disciplines to explicate a conceptualization of evidence that moves past static and objectivist accounts. RESULTS. We demonstrate that evidence is fundamentally information that takes various forms—i.e., artifacts, mental structures, or communication processes. Specific forms and manifestations of evidence can thus be described in the context of information use in dynamic information environments. Furthermore, evidence-based healthcare activities are shown to be fundamentally cognitive in nature. For any given evidence-based healthcare activity, its quality and outcome can be understood in the context of how different sources of evidence are coordinated within a distributed cognitive system. In this sense, evidence based health care activity becomes more a matter of understanding the movement of information and knowledge within a distributed and dynamic cognitive system than mere access to or translation of a ready-at-hand resource. CONCLUSIONS. The conceptualization of evidence presented in this article has a number of implications for evidence- based healthcare—in terms of where attention is focused, the direction of future research efforts, how evidence generation, use, and practice are conceptualized and discussed, and how healthcare technologies are designed and evaluated. Furthermore, the conceptualization presented in this article has implications for the manner in which evidence ‘hierarchies’ are developed. Such hierarchies do not provide a complete picture of evidence and the way it is used in healthcare activities. Understanding the dynamic nature of evidence and its role in distributed cognitive activities may lead to more robust and multi-faceted taxonomies, frameworks, and hierarchies related to evidence-based healthcare.},
note = {ISBN: 0000000000000},
keywords = {distributed cognition, healthcare},
pubstate = {published},
tppubtype = {article}
}
AIM. The basic thrust of evidence-based healthcare is that current best evidence should be used explicitly and judiciously for diagnosis, management, and other activities in healthcare settings. For this to be possible, researchers, practitioners, and other stakeholders must have a clear and accurate conceptualization of what constitutes ‘evidence’ in healthcare environments, and the manner in which it is used in decision-making and other activities. Currently, the dominant conceptualization of evidence is that of a body of information that can be retrieved by stakeholders for use in healthcare practice. The aim of this article is to critically examine the concept of evidence, particularly in light of recent models of human cognition and information use in decision-making and other cognitive activities. METHODS. In this theoretical article, we employ both analytical and synthetic methods to critically examine the concepts under investigation. Key concepts, such as evidence and information, and the essential relationships between them are analyzed from the vantage point of cognitive science, information science, and other relevant disciplines to explicate a conceptualization of evidence that moves past static and objectivist accounts. RESULTS. We demonstrate that evidence is fundamentally information that takes various forms—i.e., artifacts, mental structures, or communication processes. Specific forms and manifestations of evidence can thus be described in the context of information use in dynamic information environments. Furthermore, evidence-based healthcare activities are shown to be fundamentally cognitive in nature. For any given evidence-based healthcare activity, its quality and outcome can be understood in the context of how different sources of evidence are coordinated within a distributed cognitive system. In this sense, evidence based health care activity becomes more a matter of understanding the movement of information and knowledge within a distributed and dynamic cognitive system than mere access to or translation of a ready-at-hand resource. CONCLUSIONS. The conceptualization of evidence presented in this article has a number of implications for evidence- based healthcare—in terms of where attention is focused, the direction of future research efforts, how evidence generation, use, and practice are conceptualized and discussed, and how healthcare technologies are designed and evaluated. Furthermore, the conceptualization presented in this article has implications for the manner in which evidence ‘hierarchies’ are developed. Such hierarchies do not provide a complete picture of evidence and the way it is used in healthcare activities. Understanding the dynamic nature of evidence and its role in distributed cognitive activities may lead to more robust and multi-faceted taxonomies, frameworks, and hierarchies related to evidence-based healthcare.
15.
Parsons, Paul; Sedig, Kamran; Didandeh, Arman; Khosravi, Arash
Interactivity in Visual Analytics: Use of Conceptual Frameworks to Support Human-Centered Design of a Decision-Support Tool Proceedings Article
In: Hawaii International Conference on System Sciences, pp. 1138–1147, IEEE, 2015.
Abstract | Links | BibTeX | Tags: human-centered design, interactivity, visual analytics
@inproceedings{Parsons2015,
title = {Interactivity in Visual Analytics: Use of Conceptual Frameworks to Support Human-Centered Design of a Decision-Support Tool},
author = {Paul Parsons and Kamran Sedig and Arman Didandeh and Arash Khosravi},
url = {https://www.dvclab.net/wp-content/uploads/2020/02/07069945-1.pdf},
doi = {10.1109/HICSS.2015.138},
year = {2015},
date = {2015-01-01},
booktitle = {Hawaii International Conference on System Sciences},
pages = {1138--1147},
publisher = {IEEE},
abstract = {Visual analytics (VA) combines the strengths of humans and computers such that joint cognitive systems are formed. To be effective, a VA tool should be designed such that the component parts of the whole system are strongly coupled and function in a harmonious fashion. These components include cognitive and perceptual issues, tasks, algorithms, data models, and other aspects of the systems that contribute to its overall efficacy. The quality of interaction among all of these components can be referred to as interactivity. In the existing visualization literature, not enough focus has been placed on developing our understanding of human-centered aspects of interactivity. We have recently developed some conceptual frameworks to inform and guide the design of visual analytics tools in a systematic, human- centered fashion. In this paper, we describe the design of a tool that supports decision-making and other complex cognitive activities. We discuss how the conceptual frameworks supported systematic design and coherent thinking about the interactivity of the tool. We also discuss some extensions of interactivity into important areas of concern for visual analytics tools.},
keywords = {human-centered design, interactivity, visual analytics},
pubstate = {published},
tppubtype = {inproceedings}
}
Visual analytics (VA) combines the strengths of humans and computers such that joint cognitive systems are formed. To be effective, a VA tool should be designed such that the component parts of the whole system are strongly coupled and function in a harmonious fashion. These components include cognitive and perceptual issues, tasks, algorithms, data models, and other aspects of the systems that contribute to its overall efficacy. The quality of interaction among all of these components can be referred to as interactivity. In the existing visualization literature, not enough focus has been placed on developing our understanding of human-centered aspects of interactivity. We have recently developed some conceptual frameworks to inform and guide the design of visual analytics tools in a systematic, human- centered fashion. In this paper, we describe the design of a tool that supports decision-making and other complex cognitive activities. We discuss how the conceptual frameworks supported systematic design and coherent thinking about the interactivity of the tool. We also discuss some extensions of interactivity into important areas of concern for visual analytics tools.
2014
14.
Sedig, Kamran; Parsons, Paul; Dittmer, Mark; Haworth, Robert
Human-centered interactivity of visualization tools: Micro- and macro-level considerations Book Chapter
In: Huang, Weidong (Ed.): Handbook of Human-Centric Visualization, pp. 717–743, Springer, New York, 2014.
Abstract | Links | BibTeX | Tags: human-centered design, interactivity, visualization
@inbook{Sedig2012a,
title = {Human-centered interactivity of visualization tools: Micro- and macro-level considerations},
author = {Kamran Sedig and Paul Parsons and Mark Dittmer and Robert Haworth},
editor = {Weidong Huang},
doi = {10.1007/978-1-4614-7485-2 29},
year = {2014},
date = {2014-01-01},
booktitle = {Handbook of Human-Centric Visualization},
pages = {717--743},
publisher = {Springer},
address = {New York},
abstract = {Visualization tools can support and enhance the performance of complex cognitive activities such as sensemaking, problemsolving, and analytical reasoning. To do so effectively, however, a human-centered approach to their design and eval- uation is required. One way to make visualization tools human-centered is to make them interactive. Although interaction allows a user to adjust the features of the tool to suit his or her cognitive and contextual needs, it is the quality of interaction that largely determines how well complexcognitive activities are supported. In this chapter, interactivity is conceptualized as the quality of interaction. As interactivity is a broad and complex construct, we categorize it into two levels: micro and macro. Interactivity at the micro level emerges from the structural elements of individual interactions. Interactivity at the macro level emerges from the combi- nation, sequencing, and aggregate properties and relationships of interactions as a user performs an activity. Twelvemicro-level interactivity elements and five macro- level interactivity factors are identified andcharacterized. The framework presented in this chapter can provide some structure and facilitate a systematic approach to design and evaluation of interactivity in human-centered visualization tools.},
keywords = {human-centered design, interactivity, visualization},
pubstate = {published},
tppubtype = {inbook}
}
Visualization tools can support and enhance the performance of complex cognitive activities such as sensemaking, problemsolving, and analytical reasoning. To do so effectively, however, a human-centered approach to their design and eval- uation is required. One way to make visualization tools human-centered is to make them interactive. Although interaction allows a user to adjust the features of the tool to suit his or her cognitive and contextual needs, it is the quality of interaction that largely determines how well complexcognitive activities are supported. In this chapter, interactivity is conceptualized as the quality of interaction. As interactivity is a broad and complex construct, we categorize it into two levels: micro and macro. Interactivity at the micro level emerges from the structural elements of individual interactions. Interactivity at the macro level emerges from the combi- nation, sequencing, and aggregate properties and relationships of interactions as a user performs an activity. Twelvemicro-level interactivity elements and five macro- level interactivity factors are identified andcharacterized. The framework presented in this chapter can provide some structure and facilitate a systematic approach to design and evaluation of interactivity in human-centered visualization tools.
13.
Parsons, Paul; Sedig, Kamran
Distribution of Information Processing while Performing Complex Cognitive Activities with Visualization Tools Book Chapter
In: Huang, Weidong (Ed.): Handbook of Human-Centric Visualization, pp. 693–715, Springer, New York, 2014.
Abstract | Links | BibTeX | Tags: distributed cognition, interaction, visualization
@inbook{Parsons2013,
title = {Distribution of Information Processing while Performing Complex Cognitive Activities with Visualization Tools},
author = {Paul Parsons and Kamran Sedig},
editor = {Weidong Huang},
doi = {10.1007/978-1-4614-7485-2 28},
year = {2014},
date = {2014-01-01},
booktitle = {Handbook of Human-Centric Visualization},
pages = {693--715},
publisher = {Springer},
address = {New York},
abstract = {When using visualization tools to perform complex cognitive activities, such as sense-making, analytical reasoning, and learning, human users and visu- alization tools form a joint cognitive system. Through processing and transfer of informationwithin and among the components of this system, complex problems are solved, complex decisions are made, and complex cognitive processes emerge—all in a manner that would not be easily performable by the human or the visualization tool alone. Although researchers have recognized this, no systematic treatment of how to best distribute the information-processing load during the performance of complex cognitive activities is available in the existing literature. While previous research has identified some relevant principles that shed light on this issue, the pertinent research findings are not integrated into coherent models and frameworks, and are scattered acrossmany disciplines, such as cognitive psychology, educational psychology, information visualization, data analytics, and computer science. This chapter provides an initial examination of this issue by identifying and discussing some key concerns, integrating some fundamental concepts, and highlighting some current research gaps that require future study. The issues examined in this chapter are of importance to many domains, including visual analytics, data and information visualization, human-informationinteraction, educational and cognitive technologies, and human-computer interaction design. The approach taken in this chapter is human-centered, focusing on the distribution of information processing with the ultimate purpose of supporting the complex cognitive activities of human users of visualization tools.},
keywords = {distributed cognition, interaction, visualization},
pubstate = {published},
tppubtype = {inbook}
}
When using visualization tools to perform complex cognitive activities, such as sense-making, analytical reasoning, and learning, human users and visu- alization tools form a joint cognitive system. Through processing and transfer of informationwithin and among the components of this system, complex problems are solved, complex decisions are made, and complex cognitive processes emerge—all in a manner that would not be easily performable by the human or the visualization tool alone. Although researchers have recognized this, no systematic treatment of how to best distribute the information-processing load during the performance of complex cognitive activities is available in the existing literature. While previous research has identified some relevant principles that shed light on this issue, the pertinent research findings are not integrated into coherent models and frameworks, and are scattered acrossmany disciplines, such as cognitive psychology, educational psychology, information visualization, data analytics, and computer science. This chapter provides an initial examination of this issue by identifying and discussing some key concerns, integrating some fundamental concepts, and highlighting some current research gaps that require future study. The issues examined in this chapter are of importance to many domains, including visual analytics, data and information visualization, human-informationinteraction, educational and cognitive technologies, and human-computer interaction design. The approach taken in this chapter is human-centered, focusing on the distribution of information processing with the ultimate purpose of supporting the complex cognitive activities of human users of visualization tools.
12.
Parsons, Paul; Sedig, Kamran
Common visualizations: Their cognitive utility Book Chapter
In: Huang, Weidong (Ed.): Handbook of Human-Centric Visualization, pp. 671–691, Springer, New York, 2014.
Abstract | Links | BibTeX | Tags: cognition, visualization
@inbook{Parsons-Common,
title = {Common visualizations: Their cognitive utility},
author = {Paul Parsons and Kamran Sedig},
editor = {Weidong Huang},
doi = {10.1007/978-1-4614-7485-2 27},
year = {2014},
date = {2014-01-01},
booktitle = {Handbook of Human-Centric Visualization},
pages = {671--691},
publisher = {Springer},
address = {New York},
abstract = {Visualizations have numerous benefits for problem solving, sense mak- ing, decision making, learning, analytical reasoning, and other high-level cognitive activities. Research in cognitive science has demonstrated that visualizations fun- damentally influence cognitive processing and the overall performance of such aforementioned activities. However, although researchers often suggest that visu- alizations support, enhance, and/or amplify cognition, little research has examined the cognitive utility of different visualizations in a systematic and comprehensive manner. Rather, visualization research is often focused only on low-level cognitive and perceptual issues. To design visualizations that effectively support high-level cognitive activities, a strong understanding of the cognitive effects of different visual forms is required. To examine thisissue, this chapter draws on research from a number of relevant domains, including information and data visualization, visual analytics, cognitive and perceptual psychology, and diagrammatic reasoning. This chapter identifies and clarifies some important terms and discusses the current state of research and practice. In addition, a number of common visualizations are identified, their cognitive and perceptual influences are examined, and some implications for the performance of high-level cognitive activities are discussed. Readers from various fields in which a human-centered approach to visualization is necessary, such as health informatics, data and information visualization, visual analytics, journalism, education, and human-information interaction,will likely find this chapter a useful reference for research, design, and/or evaluation purposes. P.},
keywords = {cognition, visualization},
pubstate = {published},
tppubtype = {inbook}
}
Visualizations have numerous benefits for problem solving, sense mak- ing, decision making, learning, analytical reasoning, and other high-level cognitive activities. Research in cognitive science has demonstrated that visualizations fun- damentally influence cognitive processing and the overall performance of such aforementioned activities. However, although researchers often suggest that visu- alizations support, enhance, and/or amplify cognition, little research has examined the cognitive utility of different visualizations in a systematic and comprehensive manner. Rather, visualization research is often focused only on low-level cognitive and perceptual issues. To design visualizations that effectively support high-level cognitive activities, a strong understanding of the cognitive effects of different visual forms is required. To examine thisissue, this chapter draws on research from a number of relevant domains, including information and data visualization, visual analytics, cognitive and perceptual psychology, and diagrammatic reasoning. This chapter identifies and clarifies some important terms and discusses the current state of research and practice. In addition, a number of common visualizations are identified, their cognitive and perceptual influences are examined, and some implications for the performance of high-level cognitive activities are discussed. Readers from various fields in which a human-centered approach to visualization is necessary, such as health informatics, data and information visualization, visual analytics, journalism, education, and human-information interaction,will likely find this chapter a useful reference for research, design, and/or evaluation purposes. P.
11.
Sedig, Kamran; Parsons, Paul
Interacting with Digital Information Book Section
In: Information Science & Technology, pp. 3762–3769, IGI Global, 2014, ISBN: 978-1-4666-5888-2.
Abstract | Links | BibTeX | Tags: design, interaction
@incollection{Sedig2014,
title = {Interacting with Digital Information},
author = {Kamran Sedig and Paul Parsons},
doi = {10.4018/978-1-4666-5888-2.ch370},
isbn = {978-1-4666-5888-2},
year = {2014},
date = {2014-01-01},
booktitle = {Information Science & Technology},
pages = {3762--3769},
publisher = {IGI Global},
edition = {3},
abstract = {Every day, people from all kinds of professions and disciplines need to use information to make decisions, plan courses of action, discover patterns, solve problems, analyze situations, make sense of phenomena, learn new concepts, make forecasts about future trends, and so on. These are all activities that involve human cognition; in other words, they are cognitive activities. People whose professions involve the frequent or continual performance of cognitive activities include scientists, health-care specialists, medical researchers, librarians, journalists, learners, engineers, stock brokers, archeologists, educators, social scientists, and others—i.e., the so-called knowledge workers. As the amount and complexity of information is on the rise, computer tools are increasingly being used to support knowledge workers in their everyday cognitive activities...},
keywords = {design, interaction},
pubstate = {published},
tppubtype = {incollection}
}
Every day, people from all kinds of professions and disciplines need to use information to make decisions, plan courses of action, discover patterns, solve problems, analyze situations, make sense of phenomena, learn new concepts, make forecasts about future trends, and so on. These are all activities that involve human cognition; in other words, they are cognitive activities. People whose professions involve the frequent or continual performance of cognitive activities include scientists, health-care specialists, medical researchers, librarians, journalists, learners, engineers, stock brokers, archeologists, educators, social scientists, and others—i.e., the so-called knowledge workers. As the amount and complexity of information is on the rise, computer tools are increasingly being used to support knowledge workers in their everyday cognitive activities…
10.
Parsons, Paul; Sedig, Kamran
Adjustable properties of visual representations: Improving the quality of human-information interaction Journal Article
In: Journal of the Association for Information Science and Technology, vol. 65, no. 3, pp. 455–482, 2014, ISSN: 23301635, (arXiv: 0803.1716 ISBN: 978-0-88986-920-2).
Abstract | Links | BibTeX | Tags: design patterns, human-information interaction, interaction
@article{Parsons2012ab,
title = {Adjustable properties of visual representations: Improving the quality of human-information interaction},
author = {Paul Parsons and Kamran Sedig},
url = {http://doi.wiley.com/10.1002/asi.23002},
doi = {10.1002/asi.23002},
issn = {23301635},
year = {2014},
date = {2014-01-01},
urldate = {2014-01-16},
journal = {Journal of the Association for Information Science and Technology},
volume = {65},
number = {3},
pages = {455--482},
abstract = {Complex cognitive activities, such as analytical reasoning, problem solving, and sense making, are often performed through the mediation of interactive computational tools. Examples include visual analytics, decision support, and educational tools. Through interaction with visual representations of information at the visual interface of these tools, a joint, coordinated cognitive system is formed. This partnership results in a number of relational properties—those depending on both humans and tools—that researchers and designers must be aware of if such tools are to effectively support the performance of complex cognitive activities. This article presents 10 properties of interactive visual representations that are essential and relational and whose values can be adjusted through interaction. By adjusting the values of these properties, better coordination between humans and tools can be effected, leading to higher quality performance of complex cognitive activities. This article examines how the values of these properties affect cognitive processing and visual reasoning and demonstrates the necessity of making their values adjustable—all of which is situated within a broader theoretical framework concerned with human-information interaction in complex cognitive activities. This framework can facilitate systematic research, design, and evaluation in numerous fields including information visualization, health informatics, visual analytics, and educational technology.},
note = {arXiv: 0803.1716
ISBN: 978-0-88986-920-2},
keywords = {design patterns, human-information interaction, interaction},
pubstate = {published},
tppubtype = {article}
}
Complex cognitive activities, such as analytical reasoning, problem solving, and sense making, are often performed through the mediation of interactive computational tools. Examples include visual analytics, decision support, and educational tools. Through interaction with visual representations of information at the visual interface of these tools, a joint, coordinated cognitive system is formed. This partnership results in a number of relational properties—those depending on both humans and tools—that researchers and designers must be aware of if such tools are to effectively support the performance of complex cognitive activities. This article presents 10 properties of interactive visual representations that are essential and relational and whose values can be adjusted through interaction. By adjusting the values of these properties, better coordination between humans and tools can be effected, leading to higher quality performance of complex cognitive activities. This article examines how the values of these properties affect cognitive processing and visual reasoning and demonstrates the necessity of making their values adjustable—all of which is situated within a broader theoretical framework concerned with human-information interaction in complex cognitive activities. This framework can facilitate systematic research, design, and evaluation in numerous fields including information visualization, health informatics, visual analytics, and educational technology.
2013
9.
Sedig, Kamran; Parsons, Paul
Interaction Design for Complex Cognitive Activities with Visual Representations: A Pattern-Based Approach Journal Article
In: AIS Transactions on Human-Computer Interaction, vol. 5, no. 2, pp. 84–133, 2013.
Abstract | Links | BibTeX | Tags: design, human-information interaction, information visualization
@article{Sedig2013,
title = {Interaction Design for Complex Cognitive Activities with Visual Representations: A Pattern-Based Approach},
author = {Kamran Sedig and Paul Parsons},
url = {http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1057&context=thci},
year = {2013},
date = {2013-01-01},
journal = {AIS Transactions on Human-Computer Interaction},
volume = {5},
number = {2},
pages = {84--133},
abstract = {This paper is concerned with interaction design for visualization-based computational tools that support the performance of complex cognitive activities, such as analytical reasoning, sense making, decision making, problem solving, learning, planning, and knowledge discovery. In this paper, a number of foundational concepts related to interaction and complex cognitive activities are syncretized into a coherent theoretical framework. This framework is general, in the sense that it is applicable to all technologies, platforms, tools, users, activities, and visual representations. Included in the framework is a catalog of 32 fundamental epistemic action patterns, with each action pattern being characterized and examined in terms of its utility in supporting different complex cognitive activities. This catalog of action patterns is comprehensive, covering a broad range of interactions that are performed by a diverse group of users for all kinds of tasks and activities. The presented framework is also generative, in that it can stimulate creativity and innovation in research and design for a number of domains and disciplines, including data and information visualization, visual analytics, digital libraries, health informatics, learning sciences and technologies, personal information management, decision support, information systems, and knowledge management.},
keywords = {design, human-information interaction, information visualization},
pubstate = {published},
tppubtype = {article}
}
This paper is concerned with interaction design for visualization-based computational tools that support the performance of complex cognitive activities, such as analytical reasoning, sense making, decision making, problem solving, learning, planning, and knowledge discovery. In this paper, a number of foundational concepts related to interaction and complex cognitive activities are syncretized into a coherent theoretical framework. This framework is general, in the sense that it is applicable to all technologies, platforms, tools, users, activities, and visual representations. Included in the framework is a catalog of 32 fundamental epistemic action patterns, with each action pattern being characterized and examined in terms of its utility in supporting different complex cognitive activities. This catalog of action patterns is comprehensive, covering a broad range of interactions that are performed by a diverse group of users for all kinds of tasks and activities. The presented framework is also generative, in that it can stimulate creativity and innovation in research and design for a number of domains and disciplines, including data and information visualization, visual analytics, digital libraries, health informatics, learning sciences and technologies, personal information management, decision support, information systems, and knowledge management.
8.
Haworth, Robert; Parsons, Paul; Sedig, Kamran
Design of digital cognitive games: Some considerations Journal Article
In: International Journal of Cognitive Technology, vol. 18, no. 1, pp. 22–27, 2013.
Abstract | BibTeX | Tags: game design, learning
@article{Haworth2013,
title = {Design of digital cognitive games: Some considerations},
author = {Robert Haworth and Paul Parsons and Kamran Sedig},
year = {2013},
date = {2013-01-01},
journal = {International Journal of Cognitive Technology},
volume = {18},
number = {1},
pages = {22--27},
abstract = {Digital games that are used for purposes other than pure entertainment are growing in popularity. These include games that engage the player in making sense of climate change patterns, learning about complex mathematical structures, and investigating public health policies. Such games function to mediate, facilitate, support, and/or develop high-level cognitive activities, such as problem solving, planning, learning, and analytical reasoning, and are referred to in this paper as digital cognitive games (DCGs). Despite their growing popularity and recognized potential, the design of DCGs is often not well-informed by current research in relevant domains. This paper draws from research in the cognitive and learning sciences, game studies, and human-computer interaction design, to examine some components of DCGs that significantly influence cognitive processes, and thus affect the performance of cognitive activities. These include game content and its visual representation, interaction design and the core mechanic of DCGs, and interactivity of DCGs. Each component is discussed, and an existing DCG is briefly analyzed. An awareness of these components would benefit designers if DCGs are to achieve their desired cognitive effects and intended outcomes.},
keywords = {game design, learning},
pubstate = {published},
tppubtype = {article}
}
Digital games that are used for purposes other than pure entertainment are growing in popularity. These include games that engage the player in making sense of climate change patterns, learning about complex mathematical structures, and investigating public health policies. Such games function to mediate, facilitate, support, and/or develop high-level cognitive activities, such as problem solving, planning, learning, and analytical reasoning, and are referred to in this paper as digital cognitive games (DCGs). Despite their growing popularity and recognized potential, the design of DCGs is often not well-informed by current research in relevant domains. This paper draws from research in the cognitive and learning sciences, game studies, and human-computer interaction design, to examine some components of DCGs that significantly influence cognitive processes, and thus affect the performance of cognitive activities. These include game content and its visual representation, interaction design and the core mechanic of DCGs, and interactivity of DCGs. Each component is discussed, and an existing DCG is briefly analyzed. An awareness of these components would benefit designers if DCGs are to achieve their desired cognitive effects and intended outcomes.
2012
7.
Parsons, Paul; Sedig, Kamran
The Role of Interactive Representations in Cognitive Tools for Learning Book Section
In: Abramovich, S (Ed.): Computers in Education, pp. 27–46, Hauppauge, NY, 2012.
Links | BibTeX | Tags: distributed cognition, interaction, learning
@incollection{Parsons2012,
title = {The Role of Interactive Representations in Cognitive Tools for Learning},
author = {Paul Parsons and Kamran Sedig},
editor = {S Abramovich},
url = {https://www.novapublishers.com/catalog/product_info.php?products_id=29268},
year = {2012},
date = {2012-01-01},
booktitle = {Computers in Education},
pages = {27--46},
publisher = {Hauppauge},
address = {NY},
edition = {II},
keywords = {distributed cognition, interaction, learning},
pubstate = {published},
tppubtype = {incollection}
}
6.
Sedig, Kamran; Parsons, Paul
Enhancing the epistemic utility of physical information spaces through digital information interfaces Proceedings Article
In: IASTED Conference on Human-Computer Interaction, pp. 8, Baltimore, MD, 2012.
Abstract | Links | BibTeX | Tags: human-information interaction
@inproceedings{SedigParsons2012a,
title = {Enhancing the epistemic utility of physical information spaces through digital information interfaces},
author = {Kamran Sedig and Paul Parsons},
url = {http://www.actapress.com/Abstract.aspx?paperId=454080},
doi = {10.2316/P.2012.772-019},
year = {2012},
date = {2012-01-01},
booktitle = {IASTED Conference on Human-Computer Interaction},
pages = {8},
address = {Baltimore, MD},
abstract = {People perform many activities in physical spaces such as scientific museums, medical laboratories, and educational exhibits. Some activities performed in such spaces are for the purpose of making sense of the features of the space, learning about how elements within the space work, solving problems regarding relationships among items within the space, and so on. As all of these activities are fundamentally cognitive in nature, they may be labeled as cognitive activities (CAs). These activities involve and are related to knowledge of and/or knowing about physical spaces. Therefore, the degree to which physical spaces support such activities may be referred to as their epistemic utility. The epistemic utility of physical spaces has historically been limited due to the limited affordances that such spaces offer. Recent technological advances, however, provide opportunities for enhancing the epistemic utility of physical information spaces. Cognitive activity support tools (CASTs) are one such type of technology that can potentially enhance the epistemic utility of physical information spaces. The enhancement is in potential form as it depends upon the effective and proper design of CASTs. This paper draws upon research from the cognitive, information, and computer sciences to inform and motivate the conceptualization of CAST-augmented physical information spaces that have enhanced epistemic utility},
keywords = {human-information interaction},
pubstate = {published},
tppubtype = {inproceedings}
}
People perform many activities in physical spaces such as scientific museums, medical laboratories, and educational exhibits. Some activities performed in such spaces are for the purpose of making sense of the features of the space, learning about how elements within the space work, solving problems regarding relationships among items within the space, and so on. As all of these activities are fundamentally cognitive in nature, they may be labeled as cognitive activities (CAs). These activities involve and are related to knowledge of and/or knowing about physical spaces. Therefore, the degree to which physical spaces support such activities may be referred to as their epistemic utility. The epistemic utility of physical spaces has historically been limited due to the limited affordances that such spaces offer. Recent technological advances, however, provide opportunities for enhancing the epistemic utility of physical information spaces. Cognitive activity support tools (CASTs) are one such type of technology that can potentially enhance the epistemic utility of physical information spaces. The enhancement is in potential form as it depends upon the effective and proper design of CASTs. This paper draws upon research from the cognitive, information, and computer sciences to inform and motivate the conceptualization of CAST-augmented physical information spaces that have enhanced epistemic utility
5.
Parsons, Paul; Sedig, Kamran
Toward a holistic framework for human-information interaction Proceedings Article
In: Canadian Association for Information Science, pp. 3, Waterloo, ON, 2012.
Abstract | BibTeX | Tags: human-information interaction
@inproceedings{Parsons2012b,
title = {Toward a holistic framework for human-information interaction},
author = {Paul Parsons and Kamran Sedig},
year = {2012},
date = {2012-01-01},
booktitle = {Canadian Association for Information Science},
pages = {3},
address = {Waterloo, ON},
abstract = {In recent years many researchers have identified and emphasized the need for a deeper and more comprehensive understanding of how we use, think with, and interact with information (e.g., Fast and Sedig, 2005; Albers, 2008; Liang, 2009; Blandford and Attfield, 2010; Marchionini, 2008; Jones et al., 2006). One of the essential features of conducting research to this end is a systematic investigation of the cognitive issues involved in the performance of high level information-based activities (Albers, 2008). Such activities include sense making, problem solving, decision making, analyzing, forecasting, learning, and planning. In recent years, interactive tools have become deeply embedded in the performance of many of these activities. Examples include social network visualization tools, knowledge mapping tools, personal information management tools, and information visualization tools...},
keywords = {human-information interaction},
pubstate = {published},
tppubtype = {inproceedings}
}
In recent years many researchers have identified and emphasized the need for a deeper and more comprehensive understanding of how we use, think with, and interact with information (e.g., Fast and Sedig, 2005; Albers, 2008; Liang, 2009; Blandford and Attfield, 2010; Marchionini, 2008; Jones et al., 2006). One of the essential features of conducting research to this end is a systematic investigation of the cognitive issues involved in the performance of high level information-based activities (Albers, 2008). Such activities include sense making, problem solving, decision making, analyzing, forecasting, learning, and planning. In recent years, interactive tools have become deeply embedded in the performance of many of these activities. Examples include social network visualization tools, knowledge mapping tools, personal information management tools, and information visualization tools…
4.
Sedig, Kamran; Parsons, Paul; Babanski, Alex
Towards a characterization of interactivity in visual analytics Journal Article
In: Journal of Multimedia Processing Technologies, vol. 3, no. 1, pp. 12–28, 2012.
Abstract | Links | BibTeX | Tags: interactivity, visual analytics
@article{Sedig2012,
title = {Towards a characterization of interactivity in visual analytics},
author = {Kamran Sedig and Paul Parsons and Alex Babanski},
url = {https://www.dvclab.net/wp-content/uploads/2020/07/JMPT2012.pdf, Sedig et al.- 2012 - Interactivity Visual Analytics [PDF]},
year = {2012},
date = {2012-01-01},
journal = {Journal of Multimedia Processing Technologies},
volume = {3},
number = {1},
pages = {12--28},
abstract = {Designing effective visual analytics systems is challenging. Not only must each component be well understood and effectively designed on its own, but each must also operate in harmony with the rest. To a large extent, the quality of the relationships among components determines how well visual analytic activities are supported. In this paper, we define the quality of interaction among the components of visual analytics systems as interactivity. This paper draws on research from the areas of cognitive and perceptual psychology, human-information interaction, visualization sciences, and interaction design to examine some of the current challenges faced in discussing and characterizing interactivity. In doing so, this paper attempts to contribute to a characterization of interactivity in visual analytics.},
keywords = {interactivity, visual analytics},
pubstate = {published},
tppubtype = {article}
}
Designing effective visual analytics systems is challenging. Not only must each component be well understood and effectively designed on its own, but each must also operate in harmony with the rest. To a large extent, the quality of the relationships among components determines how well visual analytic activities are supported. In this paper, we define the quality of interaction among the components of visual analytics systems as interactivity. This paper draws on research from the areas of cognitive and perceptual psychology, human-information interaction, visualization sciences, and interaction design to examine some of the current challenges faced in discussing and characterizing interactivity. In doing so, this paper attempts to contribute to a characterization of interactivity in visual analytics.
3.
Sedig, Kamran; Parsons, Paul; Dittmer, Mark; Ola, Oluwakemi
Beyond information access: Support for complex cognitive activities in public health informatics tools Journal Article
In: Online Journal of Public Health Informatics, vol. 4, no. 3, pp. 23, 2012.
Abstract | Links | BibTeX | Tags: cognition, design, healthcare
@article{Sedig2012b,
title = {Beyond information access: Support for complex cognitive activities in public health informatics tools},
author = {Kamran Sedig and Paul Parsons and Mark Dittmer and Oluwakemi Ola},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3615827/},
year = {2012},
date = {2012-01-01},
journal = {Online Journal of Public Health Informatics},
volume = {4},
number = {3},
pages = {23},
abstract = {Public health professionals work with a variety of information sources to carry out their everyday activities. In recent years, interactive computational tools have become deeply embedded in such activities. Unlike the early days of computational tool use, the potential of tools nowadays is not limited to simply providing access to information; rather, they can act as powerful mediators of human-information discourse, enabling rich interaction with public health information. If public health informatics tools are designed and used properly, they can facilitate, enhance, and support the performance of complex cognitive activities that are essential to public health informatics, such as problem solving, forecasting, sense-making, and planning. However, the effective design and evaluation of public health informatics tools requires an understanding of the cognitive and perceptual issues pertaining to how humans work and think with information to perform such activities. This paper draws on research that has examined some of the relevant issues, including interaction design, complex cognition, and visual representations, to offer some human-centered design and evaluation considerations for public health informatics tools.},
keywords = {cognition, design, healthcare},
pubstate = {published},
tppubtype = {article}
}
Public health professionals work with a variety of information sources to carry out their everyday activities. In recent years, interactive computational tools have become deeply embedded in such activities. Unlike the early days of computational tool use, the potential of tools nowadays is not limited to simply providing access to information; rather, they can act as powerful mediators of human-information discourse, enabling rich interaction with public health information. If public health informatics tools are designed and used properly, they can facilitate, enhance, and support the performance of complex cognitive activities that are essential to public health informatics, such as problem solving, forecasting, sense-making, and planning. However, the effective design and evaluation of public health informatics tools requires an understanding of the cognitive and perceptual issues pertaining to how humans work and think with information to perform such activities. This paper draws on research that has examined some of the relevant issues, including interaction design, complex cognition, and visual representations, to offer some human-centered design and evaluation considerations for public health informatics tools.
2011
2.
Parsons, Paul; Sedig, Kamran
Human-information interaction: An emerging focus for educational cognitive tools Book Section
In: Mendez-Villa, A (Ed.): Education in a technological world: Communicating current and emerging research and technological efforts, pp. 245–251, Formatex, Badajoz, Spain, 2011.
Abstract | BibTeX | Tags: cognitive tool, distributed cognition, human-information interaction, interactivity, learning
@incollection{Parsons2011,
title = {Human-information interaction: An emerging focus for educational cognitive tools},
author = {Paul Parsons and Kamran Sedig},
editor = {A Mendez-Villa},
year = {2011},
date = {2011-01-01},
booktitle = {Education in a technological world: Communicating current and emerging research and technological efforts},
pages = {245--251},
publisher = {Formatex},
address = {Badajoz, Spain},
abstract = {Educational cognitive tools are interactive, computer-based tools that augment one’s mind to facilitate learning. Examples of these include interactive mathematical software, interactive physics simulations, and interactive biology visualizations. While using these tools a learner’s mind becomes coupled with the tool, forming a cognitive system, such that cognitive processes are distributed across this system. The coupling of this system is strong, as the cognitive tool actively contributes to information-processing tasks by serving a representational function. By representing information at their interface, cognitive tools provide learners with access to information. Additionally, as cognitive tools are interactive, learners can perform actions upon the represented information. These actions serve an epistemic function and can be considered part of thought itself. Epistemic actions are basic actions that a learner may perform on any interactive cognitive tool and thus are technology-independent. Therefore, there is a need for designers and educators to focus on the ways in which learners use, interact with, and think with information, independent of the technology that is mediating the interaction. This chapter examines the dynamics of human-information interaction as an emerging area of interest, the implications for educational cognitive tools, and some of its emerging research efforts.},
keywords = {cognitive tool, distributed cognition, human-information interaction, interactivity, learning},
pubstate = {published},
tppubtype = {incollection}
}
Educational cognitive tools are interactive, computer-based tools that augment one’s mind to facilitate learning. Examples of these include interactive mathematical software, interactive physics simulations, and interactive biology visualizations. While using these tools a learner’s mind becomes coupled with the tool, forming a cognitive system, such that cognitive processes are distributed across this system. The coupling of this system is strong, as the cognitive tool actively contributes to information-processing tasks by serving a representational function. By representing information at their interface, cognitive tools provide learners with access to information. Additionally, as cognitive tools are interactive, learners can perform actions upon the represented information. These actions serve an epistemic function and can be considered part of thought itself. Epistemic actions are basic actions that a learner may perform on any interactive cognitive tool and thus are technology-independent. Therefore, there is a need for designers and educators to focus on the ways in which learners use, interact with, and think with information, independent of the technology that is mediating the interaction. This chapter examines the dynamics of human-information interaction as an emerging area of interest, the implications for educational cognitive tools, and some of its emerging research efforts.
2010
1.
Liang, Hai-Ning; Parsons, Paul; Wu, H -C; Sedig, Kamran
An exploratory study of interactivity in visualization tools: ‘Flow’ of interaction Journal Article
In: Journal of Interactive Learning Research, vol. 21, no. 1, pp. 5–45, 2010.
Abstract | Links | BibTeX | Tags: cognitive tool, interaction, interactivity, visualization
@article{LiangParsons2010,
title = {An exploratory study of interactivity in visualization tools: 'Flow' of interaction},
author = {Hai-Ning Liang and Paul Parsons and H -C Wu and Kamran Sedig},
url = {http://www.editlib.org/p/32419
https://www.dvclab.net/wp-content/uploads/2019/02/JILR2010.pdf, Liang et al. - 2010 - flow of interaction},
year = {2010},
date = {2010-01-01},
journal = {Journal of Interactive Learning Research},
volume = {21},
number = {1},
pages = {5--45},
abstract = {This paper deals with the design of interactivity in visualization tools. There are several factors that can be used to guide the analysis and design of the interactivity of these tools. One such factor is flow, which is concerned with the duration of interaction with visual representations of information—interaction being the actions performed by users on these representations and the reactions given back by the representations. Four forms of flow can be identified: 1) continuous action, continuous reaction; 2) continuous action, discrete reaction; 3) discrete action, continuous reaction; and 4) discrete action, discrete reaction. Structuring micro-level interactions of tools based on these forms of flow can have varying effects on the cognitive processes of users. Based on this classification of flow, four versions of an interactive visualization tool were created and studied. The testbed for this study was 3D geometric solids—more specifically, Platonic and Archimedean solids. A multi-method empirical study was conducted to evaluate the usability of these four interfaces and their effect on learning, visual thinking, and exploration. This paper reports some findings of this study.},
keywords = {cognitive tool, interaction, interactivity, visualization},
pubstate = {published},
tppubtype = {article}
}
This paper deals with the design of interactivity in visualization tools. There are several factors that can be used to guide the analysis and design of the interactivity of these tools. One such factor is flow, which is concerned with the duration of interaction with visual representations of information—interaction being the actions performed by users on these representations and the reactions given back by the representations. Four forms of flow can be identified: 1) continuous action, continuous reaction; 2) continuous action, discrete reaction; 3) discrete action, continuous reaction; and 4) discrete action, discrete reaction. Structuring micro-level interactions of tools based on these forms of flow can have varying effects on the cognitive processes of users. Based on this classification of flow, four versions of an interactive visualization tool were created and studied. The testbed for this study was 3D geometric solids—more specifically, Platonic and Archimedean solids. A multi-method empirical study was conducted to evaluate the usability of these four interfaces and their effect on learning, visual thinking, and exploration. This paper reports some findings of this study.