TWM645609U - Auxiliary interpretation system for learning assessment - Google Patents

Abstract

An auxiliary interpretation system for learning assessment is provided. The auxiliary interpretation system includes a handwriting input device for receiving a handwriting input from a user to generate handwriting data, wherein the handwriting input device includes a code point pen, a code point form with code point pattern and code point software, which applied to at least one of a test paper, a scale and an assessment form of learning or assessment, so as to generate the handwritten data for analysis or tracking of learning achievement, a handwriting recognition device for extracting at least one feature indicator for analysis or tracking of learning achievement according to the handwriting data, and an artificial intelligence processing circuit for determining whether the user has suffered from a possible situation according to the at least one feature indicator.

Description

Interpretation Assistance System for Learning Assessment

This creation refers to a reading assistance system for learning assessment, especially a reading assistance system for learning assessment based on handwritten materials.

Traditional learning assessment methods mainly rely on card readers to read the answers to picture cards, manual marking, or the use of electronic systems to fill in answers online. If you need to understand the learning effect, you need to manually scan and input. Furthermore, many current learning assessment tests rely on paper, so learning effectiveness still needs to be assessed manually and electronically. In addition, the traditional learning assessment system can scan students' homework or test papers into the system, and then read the students' homework or test paper scores to digitize the score numbers into statistics. There are also learning assessment systems that allow students to use ordinary paper test papers in learning tests, and use remote controls or tablets to enter answers one by one and send them to the assessment system. After completing the assessment test, the assessment system automatically Correct scores, perform rapid statistical analysis, and produce learning diagnostic analysis reports. However, the current method requires students to complete the paper test paper and then fill in the answers or corrected scores online or input them into the assessment system, and then let the system analyze and diagnose the learning effectiveness report. In view of this, there is a need for improvement in the existing technology.

Therefore, one of the main purposes of this creation is to provide an interpretation assistance system for learning assessment based on handwritten data to solve the above problems.

In order to achieve the above purpose, this invention provides a reading assistance system for learning assessment, including: a handwriting input device for accepting a user's handwriting input to generate handwritten data, wherein the handwriting input device includes a code point pen, Having a code point form and a code point software to apply to at least one of paper test papers, scales and evaluation forms for learning or assessment and to generate data for analyzing or tracking learning effectiveness. The handwritten data; a handwriting feature recognition device used to extract at least one characteristic index for analyzing or tracking learning effectiveness based on the handwritten data; and an artificial intelligence processing circuit used to determine the usage based on the at least one characteristic index belongs to a possible situation.

In this creation, the interpretation assistance system for learning assessment can provide users with the ability to use the handwritten data generated during the operation at the beginning of the test without changing the user's habits, by capturing Characteristic indicators in handwritten data can be used to evaluate learning effectiveness, and artificial intelligence processing circuits are used to determine whether the user belongs to a possible situation based on the characteristic indicators for subsequent tracking or suggestions of learning effectiveness.

1:Interpretation assistance system

10:Handwriting input device

100:Data transmission device

102:Writing device

104:Data collection device

106:Writing accessibility tab

108,70:Storage device

20:Handwriting feature recognition device

30:Artificial intelligence processing circuit

40:Cloud server

402:Cloud storage device

50:Digital converter

60: Electronic form interface

HWD: handwritten information

P1: coding pen

P2: Code point form

Figure 1 is a schematic diagram of the interpretation assistance system for learning assessment in this embodiment of the invention.

Figure 2 is a schematic diagram of an embodiment of the operation of the interpretation assistance system in Figure 1.

Certain words are used in the description and subsequent patent claims to refer to specific components. It will be understood by those of ordinary skill in the art that manufacturers may use different terms to refer to the same component. This specification and subsequent patent applications do not use differences in names as a way to distinguish components, but rather use differences in functions as a basis for distinction. Throughout the description The "includes" or "includes" mentioned in the patent application and subsequent patent applications are open-ended terms, so they should be interpreted as "including but not limited to". In addition, the term "coupling" here includes any direct and indirect means of electrical connection. Therefore, if a first device is coupled to a second device, it means that the first device can be directly electrically connected to the second device, or indirectly electrically connected to the second device through other devices or connections.

Please refer to Figure 1 , which is a schematic diagram of the interpretation assistance system 1 for learning assessment in this creative embodiment. Interpretation Assistance System 1 can be used to analyze and evaluate learning effectiveness. The interpretation assistance system 1 includes a handwriting input device 10, a handwriting feature recognition device 20, an artificial intelligence (AI) processing circuit 30, a cloud server 40, a digital converter 50, an electronic form interface 60 and an Storage device 70. The handwriting input device 10 is used to accept a user's handwriting input to generate handwriting data (or handwriting samples). The handwriting input device 10 can accept and generate corresponding handwriting data in response to user operations. For example, the handwriting input device 10 includes a data transmission device 100, a writing device 102, a data collection device 104, a writing assistance function tab 106 and a storage device 108. The user can operate the writing device 102 to perform handwriting actions on paper, so that the data collection device 104 can generate corresponding handwritten data accordingly. The user can also use the handwriting input device 10 to write or draw in combination with commonly used rating scales, forms, or pictures to generate corresponding handwritten data.

The data transmission device 100 can be used to transmit data. The handwriting data generated by the handwriting input device 10 can be transmitted to the handwriting feature recognition device 20 and the artificial intelligence processing circuit 30 through the data transmission device 100, or to the storage device 70 for temporary storage, or to Store it in the cloud server 40 for subsequent retrieval. The data transmission device 100 can transmit data through wireless transmission or wired transmission. The data transmission device 100 can comply with Bluetooth, infrared, Wi-Fi, fifth generation mobile communication network (5th Generation mobile communication, 5G), fifth generation mobile communication new radio (5G New Radio, 5G NR), long-distance communication, etc. Long Term Evolution (LTE), third generation (3G) mobile communication network, second generation (2G) mobile communication network, Global System for Mobile (GSM) system, wireless local area network ( Wireless LAN, WLAN), near field communication (near field communication, NFC) or wireless radio frequency (Radio Frequency Identification, RFID) standards specified wireless transmission technology, but not limited to this. The handwriting input device 10 may include a stylus, a stylus, an ultrasonic optical pen, an infrared optical pen, an ultrasonic optical pen, a reading pen, a code point pen, code point paper, code point software, a camera, a touch screen. At least one of a control panel, a touch screen, a drawing tablet, a writing pad, and an inertial sensor, but not limited to this. The handwritten data includes at least one of handwritten words, numbers, drawings, or any combination of the above. The handwritten information includes at least one stroke. The writing assistance function tab 106 may include storage, uploading, handwriting thickness selection, correction, step switching, form switching, color selection (such as black, blue, red, green), handwriting input device screen switching, handwriting recovery, handwriting recognition, etc. At least one of the functions, but not limited to this. The writing assistance function tab 106 can be combined with code point input technology to implement related functions.

The storage device 108 of the handwriting input device 10 can be used to store handwritten data generated by the handwriting input device 10 . For example, when the data transmission device 100 is in an offline or non-connected state, the handwriting data generated by the handwriting input device 10 can be stored in the storage device 108 first. When the data transmission device 100 is in a connected state, the handwritten data stored in the storage device 108 is transmitted to the handwriting feature recognition device 20, the artificial intelligence processing circuit 30, or to the storage device 70 or the cloud server 40 through the data transmission device 100. Storage. In other words, the user can operate the handwriting input device 10 to generate handwritten data and immediately transmit the generated handwritten data to the handwriting feature recognition device 20, the artificial intelligence processing circuit 30, the storage device 70 or the cloud server 40 through the data transmission device 100. Moreover, the user can also operate the handwriting input device 10 when offline to generate handwriting data and store it in the storage device 108, and then upload the handwriting data stored in the storage device 108 to the handwriting device through the data transmission device 100 when the connection is available. Feature recognition device 20, artificial intelligence Smart processing circuit 30, storage device 70 or cloud server 40.

The handwriting feature recognition device 20 is used to extract at least one feature index based on the handwriting data. The handwriting feature recognition device 20 analyzes the handwritten data and detects and extracts feature indicators in the handwritten data. The handwriting feature recognition device 20 can also detect and analyze the operation of the handwriting input device 10 to obtain feature indicators. The characteristic indicators may be sent to the artificial intelligence processing circuit 30 or to the storage device 70 or cloud server 40 for storage. The characteristic indicators can be used to analyze or track possible situations of learning effectiveness. The handwritten data includes at least one handwriting, and the characteristic index may include but is not limited to at least one of thickness, time, speed, pressure, color, and length of the handwriting of the handwritten data. For example, the handwriting feature recognition device 20 includes an image sensing device (not shown in the figure), which can be used to sense the thickness, time, speed, pressure, color, and length of the handwriting in the handwritten data. The image sensing device may include a charge coupled device image sensor (CCD) image sensor or a complementary metal oxide semiconductor (CMOS) image sensor, but is not limited thereto. Further, the characteristic indicators may include but are not limited to a total length of writing on paper, a stroke height, a stroke width, a stroke length, a stroke speed, a writing speed, a writing acceleration, one of the handwriting input device The length of time the writing device remains in the air, the length of time the writing device remains on the paper, the trajectory of a stroke, the inclination of a stroke, an azimuth angle, a variance coefficient, a peak speed, pressure applied while writing, or any of the foregoing. combination. For example, the digital converter 50 can be used to convert at least one of the thickness, time, speed, pressure, color and length of the handwriting of handwriting data into a total length, a stroke height, a stroke width, a stroke of writing on paper. Length, a stroke speed, a writing speed, a writing acceleration, a length of time that a writing device of the handwriting input device stays in the air, a length of time that the writing device stays on the paper, a trace of a handwriting, a slope of a stroke, a At least one of an azimuth angle, a variance coefficient, a peak velocity, and a writing pressure.

The artificial intelligence processing circuit 30 is used to determine whether the user belongs to a possible situation based on one or more characteristic indicators. The possible situations may include but are not limited to learning performance at different levels, assessment performance at different levels, personality traits, skills, physiological conditions, mental states, emotional states, organ functions, sensory perception, motor balance, language communication, and cognitive learning. At least one of, but not limited to, , social psychological and emotional development projects. The artificial intelligence processing circuit 30 may analyze the characteristic indicators to determine whether the user is judged to belong to the aforementioned possible situations. The artificial intelligence processing circuit 30 can use the Al analysis software and the Al algorithm to analyze one or more characteristic indicators to generate an Al analysis report and compare it with the pre-built clinical judgment database to determine whether the user belongs to The aforementioned possible scenarios are then used to provide learning tracking or suggestions.

The artificial intelligence processing circuit 30 may be a processor implemented by a convolutional neural network accelerator, a graphics processing unit, or a dedicated integrated circuit. The artificial intelligence processing circuit 30 can execute an AI analysis software and use an AI algorithm to analyze and classify one or more characteristic indicators to obtain calculation results and generate an analysis report to indicate whether the user belongs to a possible situation. The analysis report results output by the artificial intelligence processing circuit 30 can be used to assist the user in evaluation. In addition, by modularizing the data through the artificial intelligence processing circuit 30, the effects of self-evaluation and spatio-temporal comparison can be achieved. The handwriting data collected in this creative embodiment can also be used as a big data database to eliminate subjective judgment and integrate existing knowledge databases to generate learning suggestions. The artificial intelligence processing circuit 30 can use AI analysis software to analyze the correlation between multiple characteristic indicators. The artificial intelligence processing circuit 30 can be used to analyze the characteristic indicators to classify the possible situations. For example, the artificial intelligence processing circuit 30 can analyze the total length of the handwriting written on the paper, stroke height, stroke width, stroke length, stroke speed, writing speed, writing acceleration, the length of time the writing device stays in the air, and the time the writing device stays on the paper. At least one of the time length, handwriting trajectory, pen tilt, azimuth angle, variance coefficient, peak speed, and pressure applied when writing is used for classification purposes. Describe possible situations.

The artificial intelligence processing circuit 30 can analyze the characteristic indicators (experimental group) of handwritten data of one or more people (for example, at least one first user) who are known to belong to the possible situation and one person who does not have the known possible situation. Or the characteristic indicators of handwritten data of more than one person (for example, at least one second user) (control group), using the characteristic indicators of known possible situations as measurement indicators. The characteristic indicators can be analyzed by the artificial intelligence processing circuit 30 to analyze the characteristic indicators of the handwritten data of at least one first user that is known to belong to the possible situation and the characteristic indicators of the handwritten data of at least one second user that does not have the possible situation. to build. Further, the characteristic indicators of handwritten data of users known to belong to the possible scenario (for example, multiple first users) can be used as training data, and the artificial intelligence processing circuit 30 can execute the Al analysis software and use the Al The algorithm performs training operations on the aforementioned training data to generate an AI algorithm model as an evaluation and judgment database to determine whether it belongs to the possible situations and classify the possible situations. When the interpretation assistance system 1 is applied to a subsequent user (such as a second user), the artificial intelligence processing circuit 30 can analyze the characteristic indicators of the subsequent user's handwritten data through the AI calculation model established above to generate an Al analysis. Report to determine whether subsequent users fall into the aforementioned possible situations, in order to provide learning tracking or suggestions.

The analysis reports and judgment results generated by the artificial intelligence processing circuit 30 can be sent to the storage device 70 or the cloud server 40 for storage. The artificial intelligence processing circuit 30 can receive the feature index captured by the handwriting feature recognition device 20 through the data transmission device 100 and integrate it with an external information system. In addition, the handwriting feature recognition device 20 and the artificial intelligence processing circuit 30 can be installed in a desktop computer, a notebook computer, a smart phone or a tablet computer, but are not limited thereto. The handwriting feature recognition device 20 can be integrated into the handwriting input device 10. In this way, the feature indicators captured by the handwriting feature recognition device 20 can be stored in the storage device when the data transmission device 100 is in an offline or non-connected state. Set 108, when the data transmission device 100 is in a connected state, the characteristic index captured by the handwriting feature recognition device 20 or the characteristic index stored in the storage device 108 can be transmitted to the artificial intelligence processing circuit 30 through the data transmission device 100. Send it to the storage device 70 for storage or the cloud server 40 for storage for subsequent retrieval and processing. The handwriting feature recognition device 20 can also be integrated into the artificial intelligence processing circuit 30 .

Figure 2 is a schematic diagram of an operational embodiment of the interpretation assistance system 1 of Figure 1 . As shown in Figure 2, the handwriting input device 10 includes a code point pen P1, a code point form P2 with set code points, and a code point software (not shown in the figure). Codepoint software can generate codepoints of any size and arrange them at any interval. For example, the code point software can be applied to at least one of a paper test paper for learning or assessment, a scale, and an evaluation form, but is not limited to this. The user can use the code point pen P1 of the handwriting input device 10 to draw or fill in the code point form P2 with set code points, so that the code point software can read the code point data of the code point form to generate the corresponding handwritten data HWD. . In addition, you can also combine the writing accessibility tab to switch the coding point accessibility function during the answer process. It is assumed that the handwriting feature recognition device 20 and the artificial intelligence processing circuit 30 are installed in a desktop computer or a tablet computer. After the handwriting input device 10 receives the user's handwriting input and generates the handwriting data HWD, the handwriting data HWD can be transmitted to the handwriting feature recognition device 20 through the data transmission device 100 via a wireless transmission method (for example, Bluetooth wireless transmission method). When the data transmission device 100 is in a connected state, the handwriting data HWD generated by the handwriting input device 10 can be immediately transmitted to the handwriting feature recognition device 20 through the data transmission device 100 . If the data transmission device 100 is in an offline state, the handwriting data HWD generated by the handwriting input device 10 can be stored in the storage device 108 of the handwriting input device 10 . Then, when the data transmission device 100 is in a connected state, the handwritten data HWD stored in the storage device 108 is transmitted to the handwriting feature recognition device 20 through the data transmission device 100 . The handwriting feature recognition device 20 analyzes the handwritten data HWD and extracts at least one feature index from the handwritten data HWD. The feature index is sent to the artificial intelligence processing circuit 30 for analysis. The artificial intelligence processing circuit 30 can analyze the characteristic indicators and generate an Al analysis report to determine whether the user is judged to be a former Describe possible situations. The analysis reports and judgment results generated by the artificial intelligence processing circuit 30 can be sent to the cloud server 40 for storage for subsequent reference, learning tracking, or suggestions.

On the other hand, the feature indicators captured by the handwriting feature recognition device 20 can be provided to the electronic form interface 60 . The handwritten data generated by the handwriting input device 10 can be transmitted to the electronic form interface 60 through the data transmission device 100 . The electronic form interface 60 is used to present and display the received characteristic indicators or handwritten data for the user to view. The electronic form interface 60 may have user information of the user built-in. For example, the electronic form interface 60 can instantly display the total length of the handwriting data written on the paper, stroke height, stroke width, stroke length, stroke speed, writing speed, writing acceleration, the length of time the writing device stays in the air, and the time the writing device stays in the air. At least one of the length of time on paper, handwriting trajectory, pen tilt, azimuth angle, variance coefficient, peak speed, and pressure applied when writing. The electronic form interface 60 can provide data upload, temporary storage, deletion and other functions for the user to select and use. In addition, the cloud server 40 of the interpretation assistance system 1 can be set up independently. The cloud server 40 includes a cloud storage device 402, and the cloud storage device 402 resides in the cloud server 40. The interpretation assistance system 1 can remotely access the cloud storage device 402 of the cloud server 40 through the communication network, and the interpretation assistance system 1 can access the storage device 70 offline at any time to record, store or read data. The cloud storage device 402 can be used to store feature indicators captured by the handwriting feature recognition device 20, handwriting data of the handwriting input device 10, and/or data and judgment results processed by the artificial intelligence processing circuit 30. The storage device 70 may be used to store feature indicators captured by the handwriting feature recognition device 20 , handwriting data of the handwriting input device 10 and/or data processed by the artificial intelligence processing circuit 30 .

The aforementioned steps and/or processes (including suggested steps) can be implemented through a device. The device can be hardware, software, or firmware (which is a combination of hardware device and computer instructions and data, and computer instructions and data belong to the hardware device. read-only software), electronic systems, or a combination of the above-mentioned interpretation assistance systems. The above-mentioned processes and embodiments can be compiled into program codes or instructions and stored in a storage device 70 . artificial intelligence processing The circuit 30 can read and execute program codes or instructions from the storage device 70 to implement the above functions.

To sum up, this creative embodiment can provide the user with the ability to use the handwritten data generated during the operation at the beginning of the test without changing the user's habits, by retrieving the handwritten data. Characteristic indicators that can be used to evaluate learning effectiveness, and an artificial intelligence processing circuit is used to determine whether the user belongs to a possible situation based on the characteristic indicators for subsequent tracking or suggestions of learning effectiveness.

1:Interpretation assistance system

10:Handwriting input device

100:Data transmission device

102:Writing device

104:Data collection device

106:Writing accessibility tab

108,70:Storage device

20:Handwriting feature recognition device

30:Artificial intelligence processing circuit

40:Cloud server

402:Cloud storage device

50:Digital converter

60: Electronic form interface

Claims (17)

A reading assistance system for learning assessment, including: a handwriting input device used to accept a user's handwriting input to generate a handwritten data, wherein the handwriting input device includes a code point pen and a code point with a set of code points A form and a code point software to be applied to at least one of paper test papers, scales and evaluation forms for learning or assessment and to generate the handwritten data for analyzing or tracking learning effectiveness; a handwriting feature recognition A device used to extract at least one characteristic index for analyzing or tracking learning effectiveness based on the handwritten data; and an artificial intelligence processing circuit used to determine whether the user belongs to a possible situation based on the at least one characteristic index. For the interpretation assistance system described in Item 1 of the patent application, the handwritten data includes at least one of a handwritten text, a number, and a drawing. For the interpretation assistance system described in Item 1 of the patent application, the code point software is used to generate a plurality of code points and the plurality of code points are arranged at an interval. The interpretation assistance system as described in item 1 of the patent application, wherein the handwriting input device includes a writing assistance function tab, and the writing assistance function tab includes storage, uploading, handwriting thickness selection, erasure, step switching, form switching, At least one of the functions of color selection, handwriting system screen switching, handwriting recovery, handwriting recognition, etc. The interpretation assistance system as described in item 1 of the patent application, wherein the handwriting input device includes a data transmission device for transmitting the handwriting data generated by the handwriting input device to The handwriting feature recognition device. The interpretation assistance system as described in item 5 of the patent application, wherein the handwriting input device further includes a first storage device for storing the handwritten data, wherein the first storage device is in an offline state when the data transmission device Store the handwriting data generated by the handwriting input device, and when the data transmission device is in a connected state, the data transmission device transmits the handwriting data stored in the first storage device to the handwriting feature recognition device. The interpretation assistance system as described in item 1 of the patent application, wherein the at least one characteristic index includes at least one of the thickness, a time, a speed, a pressure, a color and a length of the handwriting of the handwritten data. . For example, in the interpretation assistance system described in Item 7 of the patent application, the handwriting feature recognition device includes an image sensing device for sensing the thickness, time, speed, and pressure of the handwriting of the handwritten data. At least one of the color and the length. The interpretation assistance system as described in item 1 of the patent application, wherein the at least one characteristic index includes a total length of writing, a stroke height, a stroke width, a stroke length, a stroke speed, a writing speed, a writing speed Acceleration, the length of time a writing device of the handwriting input device stays in the air, the length of time the writing device stays on the paper, a trace of a handwriting, an inclination of a stroke, an azimuth angle, a variance coefficient, a peak speed and a Apply pressure to at least one of these while writing. For example, the interpretation assistance system described in item 9 of the patent application scope also includes: A digital converter used to convert at least one of the thickness, a time, a speed, a pressure, a color and a length of the handwriting of the handwritten data into the total length, the stroke height and the stroke width , the stroke length, the stroke speed, the writing speed, the writing acceleration, the length of time the writing device stays in the air, the length of time the writing device stays on the paper, the handwriting trajectory, the inclination of the pen, the orientation At least one of the angle, the coefficient of variance, the peak velocity, and the pressure applied while writing. For example, the interpretation assistance system described in item 1 of the patent application scope, wherein the characteristic index is analyzed by the artificial intelligence processing circuit to analyze the characteristic index of the handwritten data of at least one first user that is known to belong to the possible situation and does not have the above-mentioned Characteristic indicators of at least one second user's handwritten data of possible situations are established. For the interpretation assistance system described in item 1 of the patent application, the possible situations include a different level of learning performance, a different level of assessment performance, a personality trait, a skill, a physiological condition, a mental state, and an emotion. State, at least one of an organ function, a sensory perception, a motor balance, a language communication, a cognitive learning, a social psychology, and an emotional development item. For example, in the interpretation assistance system described in Item 1 of the patent application, the artificial intelligence processing circuit executes an artificial intelligence analysis software to analyze the at least one characteristic index and generate an analysis report to indicate whether the user belongs to the possible situation. The interpretation assistance system described in item 1 of the patent application, wherein the artificial intelligence processing circuit executes an artificial intelligence analysis software to analyze the at least one characteristic index to apply it to the classification Describe possible situations. The interpretation assistance system described in Item 1 of the patent application further includes: an electronic form interface for displaying the at least one characteristic index or the handwritten data. The interpretation assistance system described in item 1 of the patent application further includes: a storage device used to store at least one of the handwritten data, the at least one characteristic index, and a judgment result generated by the artificial intelligence processing circuit. One. The interpretation assistance system described in item 1 of the patent application further includes: a cloud server including a cloud storage device, the cloud storage device is used to store the handwritten data, the at least one feature index and the artificial intelligence processing At least one of the judgment results produced by the circuit.

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