A METHOD FOR CATEGORIZING, DESCRIBING AND MODELING TYPES OF SYSTEM USERS

• US 20010011211A1
• Filed: 06/03/1998
• Published: 08/02/2001
• Est. Priority Date: 06/03/1998
• Status: Active Grant

• Current Assignee: AT&T Labs Incorporated (AT&T, Inc.)
• Original Assignee: SBC Technology Resources, Inc. (AT&T, Inc.)
• Inventors: BUSHEY, ROBERT R., MAUNEY, JENNIFER M.
• Granted Patent: US 6,405,159 B2
• Time in Patent Office: Days
• US Class Current: 703/22
• CPC Class Codes: G06F 8/38 for implementing user interfaces

Abstract

A method for categorizing, describing, and modeling types of system users where information from the models can be used in designing a user interface. Users may have improved performance using the user interface. A list of tentative behaviors of the users is created. This list is created by identifying the goals desired for the user interface or the user models, and listing expected and desired behaviors that are relevant to these goals. The list is revised to include only those behaviors that are important or frequent based on the goals. Categorizing the behaviors is performed by obtaining information from users regarding their characteristics and behaviors. Each user'"'"'s behavioral information is then converted to a score or value. The users are then mapped or charted based on which behaviors they exhibit. The mapping or charting is analyzed to identify clusters of users. These clusters define groups of users that have similar behaviors. The groups are then analyzed to produce descriptions of each group. This consists of selecting one or more users from each group and obtaining additional behavioral information. This additional behavioral information is analyzed to produce descriptions for each group. These descriptions are then used to formulate models of behaviors for each group. Information from these models can be used to design and create a user interface that helps increase user performance when using this user interface.

Claims

1. A method for modeling types of system users, the models being used to provide data for designing a system user interface, the method comprising:

categorizing behaviors of a plurality of types of users into two or more groups of users;

describing the behaviors of each group of users based on behaviors of selected users from each group; and

modeling the described behaviors of each group.

2. The method recited in

claim 1

wherein the behaviors include navigation behaviors.

3. The method recited in

claim 1

wherein the behaviors include parallel processing behaviors.

4. The method recited in

claim 1

wherein the behaviors include customer sales behaviors.

5. The method recited in

claim 1

wherein categorizing comprises charting the behaviors on a chart having two or more dimensions.

6. The method recited in

claim 5

wherein categorizing comprises charting the behaviors on a three dimensional chart.

7. The method recited in

claim 5

wherein categorizing comprises charting the behaviors on a four dimensional chart.

8. The method recited in

claim 5

wherein the dimensions include performance measures.

9. The method recited in

claim 5

wherein the dimensions include cognitive workload measures.

10. The method recited in

claim 5

wherein the dimensions include behavioral measures.

11. The method recited in

claim 5

wherein the dimensions include user characteristic measures.

12. The method recited in

claim 5

wherein the dimensions include a combination of performance, cognitive workload, behavioral, and user characteristic measures.

13. The method recited in

claim 1

wherein describing is related to examining the behaviors for similarities within each group.

14. The method recited in

claim 1

wherein describing is related to examining the behaviors for differences between each group.

15. The method recited in

claim 1

wherein describing comprises listing the tasks by frequency and importance and selecting from the most important and frequent tasks for detailed task analysis.

16. The method recited in

claim 15

wherein the detailed task analysis comprises capturing at least one of the perceptual, cognitive, and motor stages of human behavior.

17. The method recited in

claim 16

further comprising quantifying each stage as to processing speed and cognitive load.

18. The method recited in

claim 15

wherein the detailed task analysis is accomplished by using at least one of a GOMS and modified GOMS methodology.

19. The method recited in

claim 1

wherein the models include qualitative models.

20. The method recited in

claim 19

wherein the qualitative models include how the users within a specific group behave in certain situations.

21. The method recited in

claim 19

wherein the qualitative models include how the users within a specific group perform certain functions.

22. The method recited in

claim 1

wherein the models include quantitative models.

23. The method recited in

claim 22

wherein the quantitative models incorporate the capability to make numerical performance predictions.

24. The method recited in

claim 1

wherein the models of the behaviors are constructed in an interactive process that results in the models representing the strategies and activities for each group.

25. The method recited in

claim 24

further comprising validating the models.

26. The method recited in

claim 25

wherein validating the models uses actual data.

28. The method recited in

claim 1

further comprising creating a user interface using information from the models.

29. The method recited in

claim 28

wherein the plurality of users'"'"' performance is improved when using the user interface.

30. The method recited in

claim 14

further comprising designing a user interface using information from the models.

31. The method recited in

claim 30

wherein the plurality of users have improved performance using the user interface.

27. A method for modeling behaviors of interface users, the models being used to provide data for designing a system user interface, the method comprising:

creating a list of user behaviors;

identifying important behaviors based on desired goals for a system interface;

obtaining data related to the important behaviors from a plurality of users;

graphing the data, the axises of the graph related to two or more important behaviors of the plurality of users;

identifying clusters in the graphed data, the clusters representing groups of users with similar important behaviors;

selecting at least one user from each user group;

obtaining additional data from the selected users, the additional data related to the selected users'"'"' behaviors;

describing the selected users'"'"' behaviors based on analyzing the additional data; and

creating models of said selected users'"'"' behaviors based on the descriptions of the selected users'"'"' behaviors.