Data processing: artificial intelligence – Knowledge processing system
Reexamination Certificate
1998-06-01
2001-09-04
Davis, George B. (Department: 2122)
Data processing: artificial intelligence
Knowledge processing system
C706S047000, C434S322000, C434S365000
Reexamination Certificate
active
06285993
ABSTRACT:
BACKGROUND OF THE INVENTION
(a) Field of the Invention
The present invention relates in general to the analysis of how individuals receive, process and understand information. More particularly, it relates to learning models that use a wide range of input variables to analyze and determine the best methods by which individuals receive, process and understand information, thereby optimizing individual and/or group learning.
(b) Description of Related Art
People tend to differ widely in how they best receive and process information. For example, if a group of people are learning about ceramics in a classroom setting, one individual may best understand and process the information by listening to the instructor lecture. Another student may prefer to read the textbook, while still another may understand and retain the most information when they see photographs or diagrams illustrating the concepts. Others still may prefer an early morning class to an afternoon or evening class, or prefer studying in a large comfortable chair in a brightly lit room while listening to classical music.
The extent to which an individual receives sensory information in a format and setting that is compatible with how they best process information goes a long way towards determining how well that person learns. Formats and settings that deviate somewhat from a person's ideal can degrade that person's ability to learn. Formats and/or settings that deviate significantly from a person's ideal can actually prevent the person from learning. This situation can be seen in many schools where some children fail to learn, not because they do not have the intelligence to understand and process the lessons, but because the instruction is presented in a format and/or setting that deviates significantly from the particular child's ideal.
A considerable amount of research has been devoted to identifying a person's “learning style”, i.e., the various formats, environmental settings and other variables that are most compatible with how that person best understands and processes sensory information. So-called “learning style models” have been developed in which specific and varied information is gathered from an individual and used to extrapolate that person's learning style. The information may be gathered through direct observation of the person, paper and pen questionnaires, pencil-based answer sheets of the type that can be scanned into a computer scoring system, or computer assisted questionnaires in which the user answers the various test questions as they are presented on the computer screen. The questionnaires generally include a range of possible answers such as always, usually, sometimes, rarely and never.
The questionnaire answers are then analyzed, either manually or by computer, to produce a learning style profile. The learning style profile is then analyzed, again either manually or by computer, to produce a learning style report. Under the manual analysis technique, an individual specifically trained in the particular learning style model must interpret the profile in order to generate a report. Under a computer analysis technique, the profile data must be re-entered in order to produce the report. In either case, the learning style report identifies individual learning factors and may include suggestions for learning enhancements.
The above-described learning style model questionnaires can be extremely tedious for the person taking the test. In particular, they are typically lengthy and require good silent reading and comprehension skills and a long attention span in order to render relevant information. The options for administering any given questionnaire, or for analyzing questionnaire results, are generally limited and not very flexible. Accordingly, there is a need for a more flexible and user-friendly method of administering learning style model questionnaires and analyzing the results thereof.
SUMMARY OF THE INVENTION
The present invention provides a method and apparatus for gathering information related to individual learning styles that overcome the above-referenced shortcomings of known systems by providing an automated, more flexible and more user-friendly method of gathering learning style information in the form of a survey, and analyzing the results thereof. The method and apparatus are preferably embodied in a programmable computer that automatically and interactively administers the survey and analyzes the answers and the results. The computer preferably includes a display, a processor, a variety of output devices and a variety of input devices. The display and the output devices communicate inquiries to the individual in a variety of forms, including both visual communications and non-visual communications, and the individual may select whether he/she prefers to receive communications in a visual or non-visual format. The input devices receive the individual's responses to the inquiries via a variety of media, including keyboards, point-and-click devices or speech recognition devices, and the individual may select any of the available media to input his/her responses. The processor gathers the individual' responses, along with information on the individual's preferences for how he/she receives communications from the computer and provides inputs to the computer, and uses the aforementioned information to generate a learning style profile report and/or a learning style strategies report, said learning strategies including suggestions for enhancing the individual's learning.
Accordingly, the present invention may be embodied in an apparatus for modeling a person's learning style, wherein the apparatus includes a display, a first output device, a first input device, a second input device and a processor. The display provides visual communications that include inquiries that measure the person's learning style. The visual communications can include text, graphics, still pictures or moving pictures. The first output device provides non-visual communications that include inquiries that measure the person's learning style. The non-visual communications can include sound. The first input device receives inputs from the person, and these inputs include the person's responses to the inquiries. The second input device also receives inputs from the person, and these inputs also include responses to the inquiries. The processor is programmed with code capable of directing the processor through various steps including: generating the inquiries related to learning style; providing the inquiries to the display for visual communication of the inquiries to the person; providing the inquiries to the first output device for non-visual communication of the inquiries to the person; receiving from the first input device inputs from the person in response to the inquiries; and receiving from the second input device inputs from the person in response to the inquiries.
In another aspect of the present invention, the above-described processor is further programmed to receive from the first input device or the second input device a communication-selection-input made by the person. The processor uses the communication-selection-input to determine whether to provide the inquiries as either a visual communication at the display or a non-visual communication at the first output device.
The above-described processor may be further programmed to monitor the display, the first output device, the first input device and the second input device to gather information about the person's preferences for how he/she receives communications from the apparatus and how he/she provides inputs to the apparatus. The processor uses the information gathered from monitoring the display, the first output device, the first input device and the second input device in modeling the person's learning style.
In yet another aspect of the present invention, the above-described processor uses the inputs from the person to automatically generate a learning style profile r
Baker & Botts L.L.P.
Davis George B.
Raytheon Company
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