CS295J/Contributions for class 12 - Revision history

Trevor O'Brien: /* Contributions */

2009-04-23T20:31:32Z

Contributions

← Older revision		Revision as of 20:31, 23 April 2009
Line 61:		Line 61:
	* System for isolating cognitive, perceptual, and motor tasks from an interface design to generate CPM_GOMS models for analysis.		* System for isolating cognitive, perceptual, and motor tasks from an interface design to generate CPM_GOMS models for analysis.
	* Design and quantitative evaluation of semi-automated techniques for extracting critical paths from an existing CPM_GOMS model.		* Design and quantitative evaluation of semi-automated techniques for extracting critical paths from an existing CPM_GOMS model.
	* Novel algorithm for analyzing and ~~optimizing critical~~ paths based on established research in cognitive science.		* Novel algorithm for analyzing empirically-collected critical paths and suggesting optimized paths based on established research in cognitive science.

	=== Specific Aims ===		=== Specific Aims ===

Jon Ericson: /* Interface Evaluation Using Parallel Cognitive Models (Jon and Adam) */

2009-04-17T17:20:02Z

Interface Evaluation Using Parallel Cognitive Models (Jon and Adam)

← Older revision		Revision as of 17:20, 17 April 2009
Line 141:		Line 141:
	* A set of usability principles that supersedes Human-Computer Interaction and is applicable in all varieties of product development.		* A set of usability principles that supersedes Human-Computer Interaction and is applicable in all varieties of product development.

	== Interface Evaluation Using Parallel Cognitive Models (Jon ~~and Adam~~) ==		== Interface Evaluation Using Parallel Cognitive Models (Adam and Jon) ==

	=== Summary ===		=== Summary ===
Line 147:		Line 147:
	Existing approaches for using cognitive models to evaluate user interfaces are based on extensive cognitive architectures that incorporate that integrate much of cognitive theory. The disadvantage of this approach is that modifying and using these models is resource intensive		Existing approaches for using cognitive models to evaluate user interfaces are based on extensive cognitive architectures that incorporate that integrate much of cognitive theory. The disadvantage of this approach is that modifying and using these models is resource intensive

	We propose a distributed approach whereby simple cognitive models of specific behaviors each evaluate an interface independently, and those scores are combined to give a general evaluation. This approach is more flexible, permits easier modification and use at multiple levels of detail.		We propose a distributed approach whereby simple cognitive models of specific behaviors each evaluate an interface independently, and those scores are combined to give a general evaluation. This approach is more flexible, and permits easier modification and use at multiple levels of detail.

	=== Input ===		=== Input ===

Jon Ericson at 17:06, 17 April 2009

2009-04-17T17:06:46Z

← Older revision		Revision as of 17:06, 17 April 2009
Line 140:		Line 140:
	* Efficient, profitable, and compatible usability application methods in business.		* Efficient, profitable, and compatible usability application methods in business.
	* A set of usability principles that supersedes Human-Computer Interaction and is applicable in all varieties of product development.		* A set of usability principles that supersedes Human-Computer Interaction and is applicable in all varieties of product development.

			== Interface Evaluation Using Parallel Cognitive Models (Jon and Adam) ==

			=== Summary ===

			Existing approaches for using cognitive models to evaluate user interfaces are based on extensive cognitive architectures that incorporate that integrate much of cognitive theory. The disadvantage of this approach is that modifying and using these models is resource intensive

			We propose a distributed approach whereby simple cognitive models of specific behaviors each evaluate an interface independently, and those scores are combined to give a general evaluation. This approach is more flexible, permits easier modification and use at multiple levels of detail.

			=== Input ===

			*Functions that the interface performs
			*Interface description
			*User traces

			=== Sample Modules ===

			*Exogenous attention
			**Question: To what extent does the interface draw your attention to what you need?
			**Need Interface display; user traces.

			*Automaticity
			**Question: How often is executive attention needed?
			**Need: Predictability given previous actions and information displayed

			*Fitts Law
			**Question: Time to move pointer from one operation location to the next?
			**Need a physical arrangement of elements and transition matrix (user traces?)

			*Memory Load
			**Question: How many things are remembered simultaneously?
			**Need Interval (average?) between presentation and use. User traces.

			*Affordances
			**Question: Are interactions with the interface “natural”?
			**Elements, their associated actions, and their functions

			*Interruptions
			**Question: How long for interruption recovery?
			**Need User traces and predictability given information displayed

			=== Output ===

			*Efficiency curve

Eric Sodomka: /* Proposal Overview */

2009-04-17T16:07:43Z

Proposal Overview

← Older revision		Revision as of 16:07, 17 April 2009
Line 9:		Line 9:
	Owner: Eric		Owner: Eric

	=== ~~Proposal Overview~~ ===		=== Summary ===
	Note: click here for [http://vrl.cs.brown.edu/wiki/images/b/b4/Flowchart.pdf flowchart].		Note: click here for [http://vrl.cs.brown.edu/wiki/images/b/b4/Flowchart.pdf flowchart].

E J Kalafarski: /* Summary */

2009-04-17T14:58:54Z

Summary

← Older revision		Revision as of 14:58, 17 April 2009
Line 97:		Line 97:

	===Summary===		===Summary===
	Established guidelines for designing human computer interfaces are based on experience, intuition and introspection. Because there is no integrated theoretical foundation, many ~~rule-sets~~ have emerged despite the absence of comparative ~~evaluations~~. We propose ~~to develop~~ a theoretical foundation for interface design, drawing on recent advances in cognitive ~~science – the~~ study of how people think, perceive and interact with the world. We will distill a broad range of principles and computational models of cognition that are relevant to interface design and use them to compare and unify existing guidelines. To validate our theoretical foundation, we will use our findings to develop a quantitative mechanism for assessing interface designs, identifying interface elements that are detrimental to user performance, and suggesting effective alternatives. Results from this system will be explored over a set of case studies, and the quantitative assessments output by this system will be compared to actual user performance.		Established guidelines for designing human-computer interfaces are based on experience, intuition and introspection. Because there is no integrated theoretical foundation, many rulesets have emerged despite the absence of comparative evaluation. We propose a theoretical foundation for interface design, drawing on recent advances in cognitive science—the study of how people think, perceive and interact with the world.

	~~Within this framework~~, we will ~~introduce novel techniques~~ for ~~collecting~~ and ~~filtering~~ user ~~interaction histories with respect~~ to ~~user goals~~. ~~In addition~~, we ~~propose to integrate data from multiple sensing technologies~~ -- ~~including pupil~~-~~tracking~~, ~~muscle-activity monitoring~~ and ~~auditory recognition -- with these interaction histories~~ to ~~analyze the explicit contributions~~ of perception, ~~cognition~~ and ~~motor skills with respect to user performance~~. ~~This data~~ will be ~~used~~ to ~~define~~ a ~~CPM-GOMS model~~ of ~~cognition for a given~~ interface, ~~providing a quantitative~~, ~~predictive~~, ~~cognition-based parameterization of usability~~. ~~From empirically collected data~~, ~~user trajectories through~~ the ~~model (critical paths) will be examined with respect~~ to the cognitive ~~principles obtained from our theoretical findings~~, ~~highlighting bottlenecks within the interface, and offering suggested alterations to the interface to induce more optimal user trajectories.~~		We will distill a broad range of principles and computational models of cognition that are relevant to interface design and use them to compare and unify existing guidelines. To validate our theoretical foundation, we will use our findings to develop a quantitative mechanism for assessing interface designs, identifying interface elements that are detrimental to user performance, and suggesting effective alternatives. Results from this system will be explored over a set of case studies, and the quantitative assessments output by this system will be compared to actual user performance.

			Cognition, in this broad sense, cannot be limited to internal processing. A central focus of our work will be to broaden the range of cognitive theories that are used in HCI design, and we will explore the effects of improvement on all "links" in the interaction "chain"—cognition, perception, and motor skills, the CPM of the so-called CPM-GOMs evaluation method. Few low-level theories of perception and action, such as Fitts's law, have garnered general acceptance in the HCI community due to their simple, quantitative nature, and widespread applicability. Our aim is to produce similar predictive models that apply to lower levels of perception as well as higher levels of cognition, including vision, learning, memory, attention, reasoning and task management.

			We will focus on generating an extensible, generalizable framework that can be applied to a broad range of interface design challenges. Interfaces exist everywhere in the modern world, and much research has accumulated regarding how people manage multiple tasks, how machines distribute tasks and work, and how devices communicate and anticipate user action effective. The promise of such a foundation is rich, and the potential benefits game-changing. We intend to do no less than provide new methodology for the examination of the human-computer system as a unified cognitive entity. [[User:E J Kalafarski\|E J Kalafarski]] 14:58, 17 April 2009 (UTC)

	====Input====		====Input====

E J Kalafarski: /* An Explicit, Cognition-Based Framework for Analyzing Interface Design and Predicting User Performance */

2009-04-17T14:47:07Z

An Explicit, Cognition-Based Framework for Analyzing Interface Design and Predicting User Performance

← Older revision		Revision as of 14:47, 17 April 2009
Line 93:		Line 93:
	* In the case of scientific applications, aid in the adoption of tools by domain scientists.		* In the case of scientific applications, aid in the adoption of tools by domain scientists.

	==~~An Explicit,~~ Cognition~~-Based Framework for Analyzing Interface Design~~ and ~~Predicting User Performance~~==		==A Unified Framework of Cognition in Analysis and Prediction in HCI==
	Owner: [[User:E J Kalafarski\|E J Kalafarski]] 14:25, 17 April 2009 (UTC)		Owner: [[User:E J Kalafarski\|E J Kalafarski]] 14:25, 17 April 2009 (UTC)

E J Kalafarski: /* Output */

2009-04-17T14:38:22Z

Output

← Older revision		Revision as of 14:38, 17 April 2009
Line 111:		Line 111:
	* Empirically observed critical path trajectories.		* Empirically observed critical path trajectories.
	* Cognition-based breakdown of user trajectories. Highlights bottlenecks, offers suggestions to improve bottlenecks.		* Cognition-based breakdown of user trajectories. Highlights bottlenecks, offers suggestions to improve bottlenecks.

			=== Contributions ===
			* The creation of a language for ''abstractly representing user interfaces'' in terms of the layout of graphical components and the functional relationships between these components.
			* A system for ''generating interaction histories'' within user interfaces to facilitate individual and collaborative scientific discovery, and to enable researchers to more easily document and analyze user behavior.
			* A design tool that can provide a designer with recommendations for interface improvements, based on a ''unified matrix'' of cognitive principles and heuristic design guidelines.

	===Specific Aims===		===Specific Aims===

E J Kalafarski: /* An Expliit, Cognition-Based Framework for Analyzing Interface Design and Predicting User Performance */

2009-04-17T14:30:38Z

An Expliit, Cognition-Based Framework for Analyzing Interface Design and Predicting User Performance

← Older revision		Revision as of 14:30, 17 April 2009
Line 93:		Line 93:
	* In the case of scientific applications, aid in the adoption of tools by domain scientists.		* In the case of scientific applications, aid in the adoption of tools by domain scientists.

	==An ~~Expliit~~, Cognition-Based Framework for Analyzing Interface Design and Predicting User Performance==		==An Explicit, Cognition-Based Framework for Analyzing Interface Design and Predicting User Performance==
	Owner: [[User:E J Kalafarski\|E J Kalafarski]] 14:25, 17 April 2009 (UTC)		Owner: [[User:E J Kalafarski\|E J Kalafarski]] 14:25, 17 April 2009 (UTC)

E J Kalafarski: /* An Expliit, Cognition-Based Framework for Analyzing Interface Design and Predicting User Performance */

2009-04-17T14:26:19Z

An Expliit, Cognition-Based Framework for Analyzing Interface Design and Predicting User Performance

← Older revision		Revision as of 14:26, 17 April 2009
Line 111:		Line 111:
	* Empirically observed critical path trajectories.		* Empirically observed critical path trajectories.
	* Cognition-based breakdown of user trajectories. Highlights bottlenecks, offers suggestions to improve bottlenecks.		* Cognition-based breakdown of user trajectories. Highlights bottlenecks, offers suggestions to improve bottlenecks.

	~~===Contributions===~~
	* Design and user-study evaluation of novel techniques for collecting and filtering user traces with respect to user goals.
	* Extensible, low-cost architecture for integrating pupil-tracking, muscle-activity monitoring, and auditory recognition with user traces in existing applications.
	* System for isolating cognitive, perceptual, and motor tasks from an interface design to generate CPM_GOMS models for analysis.
	* Design and quantitative evaluation of semi-automated techniques for extracting critical paths from an existing CPM_GOMS model.
	* Novel algorithm for analyzing and optimizing critical paths based on established research in cognitive science.

	===Specific Aims===		===Specific Aims===

E J Kalafarski: /* A Quantitative, Cognition-Based Framework for Analyzing and Predicting User Performance */

2009-04-17T14:25:51Z

A Quantitative, Cognition-Based Framework for Analyzing and Predicting User Performance

← Older revision		Revision as of 14:25, 17 April 2009
Line 92:		Line 92:
	* Software system/architecture that allows other researchers and developers to analyze interface design effectively.		* Software system/architecture that allows other researchers and developers to analyze interface design effectively.
	* In the case of scientific applications, aid in the adoption of tools by domain scientists.		* In the case of scientific applications, aid in the adoption of tools by domain scientists.

			==An Expliit, Cognition-Based Framework for Analyzing Interface Design and Predicting User Performance==
			Owner: [[User:E J Kalafarski\|E J Kalafarski]] 14:25, 17 April 2009 (UTC)

			===Summary===
			Established guidelines for designing human computer interfaces are based on experience, intuition and introspection. Because there is no integrated theoretical foundation, many rule-sets have emerged despite the absence of comparative evaluations. We propose to develop a theoretical foundation for interface design, drawing on recent advances in cognitive science – the study of how people think, perceive and interact with the world. We will distill a broad range of principles and computational models of cognition that are relevant to interface design and use them to compare and unify existing guidelines. To validate our theoretical foundation, we will use our findings to develop a quantitative mechanism for assessing interface designs, identifying interface elements that are detrimental to user performance, and suggesting effective alternatives. Results from this system will be explored over a set of case studies, and the quantitative assessments output by this system will be compared to actual user performance.

			Within this framework, we will introduce novel techniques for collecting and filtering user interaction histories with respect to user goals. In addition, we propose to integrate data from multiple sensing technologies -- including pupil-tracking, muscle-activity monitoring and auditory recognition -- with these interaction histories to analyze the explicit contributions of perception, cognition and motor skills with respect to user performance. This data will be used to define a CPM-GOMS model of cognition for a given interface, providing a quantitative, predictive, cognition-based parameterization of usability. From empirically collected data, user trajectories through the model (critical paths) will be examined with respect to the cognitive principles obtained from our theoretical findings, highlighting bottlenecks within the interface, and offering suggested alterations to the interface to induce more optimal user trajectories.

			====Input====
			* Interface specification (within, to begin with, narrow and realistic parameters)
			* User traces, including user-sensing data: interaction histories coupled with contextual information about the interface itself and the application to which it belongs.
			* High-level user goals and intent
			* Set of cognitive guidelines/heuristics (used to analyze and optimize critical paths)

			====Output====
			* CPM-GOMS-style breakdown of perceptual, motor and cognitive tasks.
			* Empirically observed critical path trajectories.
			* Cognition-based breakdown of user trajectories. Highlights bottlenecks, offers suggestions to improve bottlenecks.

			===Contributions===
			* Design and user-study evaluation of novel techniques for collecting and filtering user traces with respect to user goals.
			* Extensible, low-cost architecture for integrating pupil-tracking, muscle-activity monitoring, and auditory recognition with user traces in existing applications.
			* System for isolating cognitive, perceptual, and motor tasks from an interface design to generate CPM_GOMS models for analysis.
			* Design and quantitative evaluation of semi-automated techniques for extracting critical paths from an existing CPM_GOMS model.
			* Novel algorithm for analyzing and optimizing critical paths based on established research in cognitive science.

			===Specific Aims===
			* Incorporate interaction history mechanisms into a set of existing applications.
			* Perform user-study evaluation of history-collection techniques.
			* Distill a set of cognitive principles/models, and evaluate empirically?
			* Build/buy sensing system to include pupil-tracking, muscle-activity monitoring, auditory recognition.
			* Design techniques for manual/semi-automated/automated construction of CPM-GOMS model from interaction histories and sensing data.
			* Design system for posterior analysis of interaction history w.r.t. CPM_GOMS model, evaluating critical path trajectories.
			* Design cognition-based techniques for detecting bottlenecks in critical paths, and offering optimized alternatives.

			===Significance===
			* Merges disparate-but-related fields of usability and cognition.
			* Provide a quantitative, cognition-based mechanism for task analysis.
			* Software system/architecture that allows other researchers and developers to analyze interface design effectively.
			* Revise and provide theoretical foundations for industry-standard human usability guidelines.

			==="Big World" Goals===
			* Broader understanding of basic, reliable usability principles and more prevalent application of them.
			* Efficient, profitable, and compatible usability application methods in business.
			* A set of usability principles that supersedes Human-Computer Interaction and is applicable in all varieties of product development.