CN112069561B - User capability-man-machine interaction task model design method, system, storage medium and terminal - Google Patents
User capability-man-machine interaction task model design method, system, storage medium and terminal Download PDFInfo
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Abstract
The invention discloses a model design method, a system, a storage medium and a terminal, which are used for selecting design parameters of a man-machine interaction interface and navigation parameters of a ship, wherein the method comprises the following steps: extracting a plurality of motiles from a target task in a human-computer interaction interface; the duty ratio of each kinetin in the target task is calculated respectively, and a first calculation result is generated; respectively calculating weights of a plurality of user capacities in a target task according to the first calculation result, and generating a second calculation result; screening out target user capability from the plurality of user capability according to the second calculation result; searching a target parameter corresponding to the target user capacity in a database according to the target user capacity; the target parameters comprise design parameters of a man-machine interaction interface and navigation parameters of the ship. According to the invention, the human-computer interaction task is constructed through the kinetin solution, the mapping relation between the kinetin and the capability is established, the interface quality can be evaluated through table lookup, the capability required by the task can be conveniently and rapidly determined, and whether the interface design is reasonable or not is determined.
Description
Technical Field
The present invention relates to the field of man-machine interaction technologies, and in particular, to a method, a system, a storage medium, and a terminal for designing a user capability-man-machine interaction task model.
Background
The user's ability is affected by three factors, namely, environmental factors, human-machine interface factors and physiological and psychological factors, and their changes affect the user's ability, so that these three factors need to be controlled during research.
User capabilities can be divided into cognitive capabilities, operational capabilities, and social capabilities according to different user capability appearances. The most important influence on tasks is cognitive ability, which is the ability of human brain to process, store and extract information, such as observation ability, perception ability, attention, memory, thinking ability and the like, and typical cognitive ability aiming at the five parts is visual search ability, balanced cognitive load ability, selective attention ability, visual working memory ability and situation perception ability respectively.
Human-computer interaction tasks are affected by two factors, namely a use purpose and a use environment, and the changes of the human-computer interaction tasks can affect the tasks, so that the two factors need to be controlled.
The existing man-machine interaction task is complex, the required user capacity is not clear, the interface design has no design basis aiming at the user capacity, the design cost is high, and the evaluation is not facilitated; in addition, as the ship can shake to different degrees when sailing on water, the user capacity is affected to a certain extent, and the influence is not considered in the prior art, so that the applicability of the man-machine interaction interface on the marine equipment is not high.
Disclosure of Invention
The invention aims to provide a user capacity-man-machine interaction task model design method, a system, a storage medium and a terminal, which are used for solving the problems that in the prior art, the man-machine interaction interface design cost of marine equipment is high, the adaptability of the marine equipment is difficult to evaluate, and the influence of the navigation state of a ship on the interface effect is large.
The above object of the present invention can be achieved by the following technical solutions:
the invention provides a user capacity-man-machine interaction task model design method, which is used for selecting design parameters of a man-machine interaction interface and navigation parameters of a ship, and comprises the following steps: extracting a plurality of motiles from a target task in a human-computer interaction interface; calculating the duty ratio of each kinetin in the target task respectively, and generating a first calculation result; respectively calculating weights of a plurality of user capacities in the target task according to the first calculation result, and generating a second calculation result; screening target user capability from the plurality of user capability according to the second calculation result; searching a target parameter corresponding to the target user capacity in a database according to the target user capacity; the target parameters comprise design parameters of a man-machine interaction interface and navigation parameters of the ship.
Preferably, the extracting a plurality of motiles from the target task in the human-computer interaction interface includes: cutting the target task into at least one subtask according to preset conditions; and extracting a plurality of the motiles from the at least one subtask.
Preferably, the calculating weights of the plurality of user capacities in the target task according to the first calculation result, and generating a second calculation result includes: creating a mapping table according to the mapping relation between each kinetin and the user capacities; respectively calculating weights of the user capacities in the target tasks according to the mapping table and the first calculation result; and generating the second calculation result according to the weight of each user capability.
Preferably, the calculating the weights of the user capacities in the target task according to the mapping table and the first calculation result is performed by using a hierarchical analysis method.
Preferably, the database includes an experimental data table, and the experimental data table includes a plurality of first parameters and a plurality of second parameters, and each of the first parameters and each of the second parameters has an experimental performance value for characterizing man-machine interaction interface adaptability and guiding ship navigation states.
Preferably, the weight value of the target user capability is the largest one of the weight values of the plurality of user capabilities, and the target parameter includes the first parameter and the second parameter corresponding to the target user capability when the experimental performance value in the database is the largest.
Preferably, the experimental data table adopts normalization treatment.
The invention also provides a user capacity-man-machine interaction task model design system, which comprises: a module for performing any of the foregoing model design methods.
The present invention also provides a storage medium having a computer program stored thereon, wherein the storage medium is a computer-readable storage medium and the program when executed implements any of the foregoing model design methods.
The invention also provides a terminal comprising a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes any one of the model design methods when executing the computer program.
The invention has the characteristics and advantages that:
according to the invention, the human-computer interaction task is constructed through the kinetin solution, the mapping relation between the kinetin and the capability is established, the interface quality can be evaluated through table lookup, the capability required by the task can be conveniently and rapidly determined, and whether the interface design is reasonable or not is determined.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a model design method of the present invention;
FIG. 2 is a flow chart of the model design method of the present invention;
FIG. 3 is a flow chart of the model design method of the present invention;
FIG. 4 is a diagram of a hierarchical structure model of human-computer interaction tasks according to an embodiment of the invention;
fig. 5 is a block diagram of the structure of the terminal of the present invention.
Reference numerals and description:
10000. a terminal; 11000. a memory; 11100. a computer program; 12000. a processor; d1, kinetin; d2, kinetin; d3, kinetin; d4, kinetin; d5, kinetin; A. capability; v, capability; s, capability; m, ability; l, ability.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one
The invention provides a user capacity-man-machine interaction task model design method, please refer to fig. 1-3, which comprises the following steps:
s1, extracting a plurality of motiles from a target task in a human-computer interaction interface;
wherein, kinetin refers to the most basic element of human actions, and comprises 18 kinds of three kinds: the first type is the necessary action type (namely, the action of directly working) including air transport, holding, actual transport, assembly, application, disassembly, hand-off and inspection; the second category is auxiliary action category (i.e. does not work directly but helps the completion of the first category of actions), including find, select, plan, align, pre-pair, find; the third class is the ineffective action class (i.e., not beneficial to work, not fully redundant) and includes hold, rest, delay, and so delay. In the working method design, the third class must be eliminated and the second class must be compressed and properly configured as much as possible to ensure that the first class proceeds efficiently.
In some embodiments, referring to fig. 1 and 2, S1 includes:
s11, cutting a target task into at least one subtask according to preset conditions;
it will be appreciated by those skilled in the art that at least one target task is included in the human-machine interface, and that one target task may be manually cut or divided into at least one sub-task according to the needs of the user. Preferably, the number of target tasks is 15, wherein some target tasks can be manually cut into one subtask, and other target tasks can be manually cut into a plurality of subtasks.
S12, extracting a plurality of motiles from at least one subtask;
in some embodiments, the kinetin includes the following meta-operations: opening or entering a certain interface, performing element comparison, waiting for receiving information, plotting and dismissing by using a mouse, reporting target information or results, browsing menu elements or interface information, inputting information by using a keyboard, inputting information by using a mouse, observing operation results, selecting targets or objects, clicking a menu or button, listening to commands and the like.
S2, respectively calculating the duty ratio of each kinetin in the target task, and generating a first calculation result;
in some embodiments, the target task includes kinetin D1, kinetin D2, kinetin D3, kinetin D4, and kinetin D5, and the duty cycle of each kinetin in the target task is calculatedNamely, the ratio of the total number of the motiles D1, the total number of the motiles D2, the total number of the motiles D3, the total number of the motiles D4 and the total number of the motiles D5 in the target task to the total number of the motiles in the target task is calculated respectively, namely N D1 Total number of motilin D1/(total number of motilin D1+total number of motilin D2+total number of motilin D3+total number of motilin D4+total number of motilin D5); n (N) D2 Total number of motilin D2/(total number of motilin D1+total number of motilin D2+total number of motilin D3+total number of motilin D4+total number of motilin D5); n (N) D3 Total number of motilin D3/(total number of motilin D1+total number of motilin D2+total number of motilin D3+total number of motilin D4+total number of motilin D5); n (N) D4 Total number of motilin D4/(total number of motilin D1+total number of motilin D2+total number of motilin D3+total number of motilin D4+total number of motilin D5); n (N) D5 Total number of motilin D5/(total number of motilin D1+total number of motilin D2+total number of motilin D3+total number of motilin D4+total number of motilin D5).
S3, respectively calculating weights of the plurality of user capacities in the target task according to the first calculation result, and generating a second calculation result;
in some embodiments, referring to fig. 1 and 3, S3 includes:
s31, creating a mapping table according to the mapping relation between each kinetin and a plurality of user capacities;
in some embodiments, the user capabilities include situational awareness capability a, visual search capability V, selective attention capability S, visual work memory capability M, and balanced cognitive load capability L.
Further, the mapping relationship between each kinetin and the user capability is preset by the designer, for example, kinetin D1 can represent selective attention capability S, kinetin D2 can also represent selective attention capability S, kinetin D3 can represent visual search capability V, selective attention capability S, visual work memory capability M and balanced cognitive load capability L, kinetin D4 can represent visual search capability V, selective attention capability S, visual work memory capability M, and kinetin D5 can represent situation awareness capability a, selective attention capability S and balanced cognitive load capability L.
In some embodiments, the mapping table is already stored in the database in advance, so reading is more convenient and fast.
S32, respectively calculating weights of the user capacities in the target tasks according to the mapping table and the first calculation result;
specifically, the weight N of situation awareness capability A in target task A ＝N D5 Weight N of visual search capability V in target task A ＝N D3 +N D4 Weight N of selective attention capability S in target task S ＝N D1 +N D2 +N D3 +N D4 +N D5 Weight N of visual work memory capability M in target task M ＝N D3 +N D4 Balance weight N of cognitive load capacity L in target task L ＝N D3 +N D5 。
In some embodiments, the weights of the user capacities in the target task are calculated according to the mapping table and the first calculation result respectively by adopting a hierarchical analysis method, and further, the hierarchical structure model adopted by the target task is shown in fig. 4, and specifically, the hierarchical analysis method is as follows:
(1) Establishing a comparison matrix
Let c1=a, c2=v, c3=s, c4=m, c5=l
Wherein the method comprises the steps of
(2) Constructing a judgment matrix
S33, generating a second calculation result according to the weight of each user capability.
S4, screening out target user capacity from the plurality of user capacities according to a second calculation result;
in some embodiments, the second calculation result is calculated as the weight N of the situation awareness capability A in the target task A ＝N D5 Weight N of visual search capability V in target task = 0.1081 A ＝N D3 +N D4 Weight N of selective attention capability S in target task = 0.1881 S ＝N D1 +N D2 +N D3 +N D4 +N D5 Weight N of visual work memory M in target task = 0.3276 M ＝N D3 +N D4 = 0.1881, balancing the weight N of cognitive load capacity L in a target task L ＝N D3 +N D5 = 0.1881, i.e. the individual user capabilities are ordered as follows: selective attention S>Visual working memory m=visual search capacity v=balanced cognitive load capacity L>Situation awareness capability a. The user capability with the largest user capability ratio is thus screened out as the target user capability, i.e. the selective attention capability S is determined as the most important user capability for a certain man-machine interaction task.
S5, searching a target parameter corresponding to the target user capacity in a database according to the target user capacity;
the target parameters comprise design parameters of a man-machine interaction interface and navigation parameters of the ship. Specifically, the navigation parameters of the ship comprise three parameters of pitching, rolling and no-rolling, and the design parameters of the man-machine interaction interface are different according to different user capacities, for example, when the user capacity is situation awareness, the corresponding design parameters are shape complexity and color brightness; when the user capability is visual search capability, the corresponding design parameters are icon shape and icon color; when the user capacity is the selective attention capacity, the corresponding design parameters are shape complexity and color hue; when the user capacity is visual work memory capacity, the corresponding design parameters are icon shape and icon color; when the user capacity is the balanced cognitive load capacity, the corresponding design parameters are the icon shape and the icon color. Furthermore, each design parameter is further subdivided into different intervals, so that related data can be recorded during experiments. In some preferred embodiments, the roll angle of the vessel is no greater than ±22.7°, and the pitch angle of the vessel is no greater than ±6.19°.
The database comprises an experimental data table, the experimental data table comprises a plurality of first parameters and a plurality of second parameters, and each first parameter and each second parameter have an experimental performance value for representing the adaptability of the man-machine interaction interface and guiding the navigation state of the ship. Preferably, the experimental data table adopts normalization processing, namely, the maximum value of experimental performance in the data table corresponding to the same user capacity is mapped to be 1, the minimum value of experimental performance is mapped to be 0, and the rest intermediate values are mapped correspondingly. According to the invention, through the design, the target parameters can be quickly found out, the operation time is saved, and the working efficiency is improved.
In some embodiments, the weight value of the target user capability is a largest one of the weight values of the plurality of user capabilities, and the target parameter includes a first parameter and a second parameter corresponding to the target user capability when the experimental performance value in the database is largest. According to the invention, a reusable model is established through the design, so that the same model design method can be applied to different human-computer interaction interfaces, and the method is simple and efficient and can be recycled.
According to the invention, the human-computer interaction task is constructed through the kinetin solution, the mapping relation between the kinetin and the capability is established, the interface quality can be evaluated through table lookup, the capability required by the task can be conveniently and rapidly determined, and whether the interface design is reasonable or not is determined. In addition, the invention calculates the duty ratio of each user capability, then selects the target user capability, finally selects the optimal target parameter to improve the adaptability of the man-machine interaction interface, and simultaneously provides navigation parameter guidance for the ship for ensuring the friendliness of the man-machine interaction interface in the actual navigation process of the ship.
Second embodiment
The embodiment of the invention also provides a user capability-man-machine interaction task model design system, which comprises a module for executing the steps of the method in any embodiment of the first embodiment. Those skilled in the art will appreciate that the system provided by the present invention has the same advantages as those of the embodiment in the first embodiment, and will not be described herein.
Embodiment III
The present embodiment also provides a storage medium having stored thereon a computer program 11100, the storage medium being a computer readable storage medium and the program when executed by the processor 12000 implementing the steps of the method of any of the embodiments of the present embodiment. The computer readable storage medium may include, among other things, any type of disk including floppy disks, optical disks, DVDs, CD-ROMs, micro-drives, and magneto-optical disks, ROM, RAM, EPROM, EEPROM, DRAM, VRAM, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data. The specific implementation process may refer to the specific description of the method embodiment in the first embodiment, and will not be described herein.
It should be appreciated by those skilled in the art that the storage medium provided by the present invention has the same advantages as those of the embodiment in the first embodiment, and will not be described herein.
Fourth embodiment
The embodiment of the present invention also provides a terminal 10000, please refer to fig. 5, including a memory 11000, a processor 12000, and a computer program 11100 stored in the memory 11000 and capable of running on the processor 12000. Wherein the processor 12000, when executing the computer program 11100, implements the methods of any of the embodiments. The specific implementation process may refer to the specific description of the above method embodiment, and will not be described herein.
In the embodiment of the present invention, the processor 12000 is a control center of a computer system, and may be a processor of a physical machine or a processor of a virtual machine. In an embodiment of the present invention, at least one instruction is stored in the memory 11000, and the instruction is loaded and executed by the processor 12000 to implement the method in each embodiment described above.
In one embodiment of the invention, processor 12000 may include one or more processing cores, such as a 4-core processor, an 8-core processor, or the like. The processor 12000 may be implemented in at least one hardware form of DSP (Digital Signal Processing ), FPGA (Field-Programmable Gate Array, field programmable gate array), PLA (Programmable Logic Array ). The processor 12000 may also include a main processor and a coprocessor, where the main processor is a processor for processing data in an awake state, and is also called a CPU (Central Processing Unit ); a coprocessor is a low-power processor for processing data in a standby state.
Memory 11000 can include one or more computer-readable storage media, which can be non-transitory. Memory 11000 can also include high-speed random access memory, as well as nonvolatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments of the invention, a non-transitory computer readable storage medium in memory 11000 is used to store at least one instruction for execution by processor 12000 to implement the methods of embodiments of the invention.
It should be appreciated by those skilled in the art that the terminal 10000 provided by the present invention has the same advantages as those of the embodiment in the first embodiment, and will not be described herein.
The present invention is not limited to the above embodiments, but is capable of modification and variation in all aspects, including those of ordinary skill in the art, without departing from the spirit and scope of the present invention.
Claims (9)
1. A user capacity-man-machine interaction task model design method is used for selecting design parameters of a man-machine interaction interface and navigation parameters of a ship and is characterized by comprising the following steps:
extracting a plurality of motiles from a target task in a human-computer interaction interface;
calculating the duty ratio of each kinetin in the target task respectively, and generating a first calculation result;
respectively calculating weights of a plurality of user capacities in the target task according to the first calculation result, and generating a second calculation result;
screening target user capability from the plurality of user capability according to the second calculation result;
searching a target parameter corresponding to the target user capacity in a database according to the target user capacity;
the target parameters comprise design parameters of a man-machine interaction interface and navigation parameters of a ship;
the calculating weights of the plurality of user capacities in the target task according to the first calculation result respectively, and generating a second calculation result comprises:
creating a mapping table according to the mapping relation between each kinetin and the user capacities;
respectively calculating weights of the user capacities in the target tasks according to the mapping table and the first calculation result;
and generating the second calculation result according to the weight of each user capability.
2. The method for designing a user capability-human-computer interaction task model according to claim 1, wherein the extracting a plurality of motiles from a target task in a human-computer interaction interface comprises:
cutting the target task into at least one subtask according to preset conditions;
and extracting a plurality of the motiles from the at least one subtask.
3. The method for designing a task model for user capability-man-machine interaction according to claim 2, wherein the calculating weights of the user capability in the target task according to the mapping table and the first calculation result is performed by means of a hierarchical analysis method.
4. The user capacity-human interaction task model design method of claim 2, wherein the database comprises an experimental data table, the experimental data table comprising a plurality of first parameters and a plurality of second parameters, each of the first parameters and each of the second parameters having an experimental performance value for characterizing human-computer interaction interface adaptability and guiding ship navigation state.
5. The user capability-man-machine interaction task model design method according to claim 4, wherein the weight value of the target user capability is a largest one of the weight values of the plurality of user capabilities, and the target parameter includes the first parameter and the second parameter corresponding to the target user capability when the experimental performance value in the database is largest.
6. The user capability-human-computer interaction task model design method according to claim 4, wherein the experimental data table adopts normalization processing.
7. A user capability-human-computer interaction task model design system, comprising:
a module for performing the user capability-human interaction task model design method of any one of claims 1 to 6.
8. A storage medium having a computer program stored thereon, characterized in that the storage medium is a computer-readable storage medium, and that the program when executed implements the user capability-man-machine interaction task model design method according to any one of claims 1 to 6.
9. A terminal comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the user capability-man machine interaction task model design method according to any one of claims 1 to 6 when executing the computer program.
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