CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to Korean Patent Application No. KR 10-2018-0054280, filed May 11, 2018 and Korean Patent Application No. KR 10-2019-0006407, filed on Jan. 17, 2019. The entire contents of the above applications are incorporated herein by reference.

BACKGROUND

The present invention relates to a diagnostic test, in particular a diagnostic test method, apparatus and computer program providing a personalized study plan through cognitive and behavioral analysis of a learner who uses a data input device such as a smart pen and a stylus pen by using data obtained from the data input device.

Typically, a learner may solve questions of a diagnostic test and an instructor may grade the learner's answers to diagnose the learner through the learner's performance. With an increasing use of smart devices such as smartphones and tablet PCs these days, smart pens are increasingly used as means of input onto a touch screen of a smart device and an environment is being created in which a smart pen can be used for learning. This has enabled a learner to write on a particular type of a printed material with a smart pen, solve a question on the printed material, or mark an answer. A smart pen can create digital data from learner's notes based on recognition of a pattern including the dot pattern developed by Anoto.

Conventional tests of a learner focus only on whether the learner's answer is correct or not, without reviewing the process of the learner solving the question. Since diagnostic tests where a learner uses a smart pen also focus only on whether the learner's answer is correct or not, it can be said that the diagnostic tests still consist of evaluation of performances focused on results.

With the diagnostic tests, it is not possible to evaluate a learner by various standards. Accordingly, they can only obtain the learner's performance result and just provide exercise questions similar to the one that the learner presented an incorrect answer to. In addition, since diagnostic tests where a learner is diagnosed depending only on whether the learner's answer is correct or not even in an environment where the learner can learn using a smart pen do not sufficiently use a variety of data obtainable from a smart pen, which is a further advanced learning tool, an improved diagnostic test using it is in demand.

Meanwhile, with the rise of massively open online courses (MOOCs), use of data analysis for personalizing computer-based education is coming into wider use. However, the MOOCs are used only for a small portion of the student community. In particular, most students at the middle and high school levels still perform their tasks in an offline (classroom)-based educational environment that uses writing instruments and paper as the main tools to take tests. Since there has been no data collection mechanism operable in the environment, no benefits from personalization by data analysis could be had and evaluating test performances served as a considerable burden. Accordingly, provision of personalized education for a learner through analysis of data of a smart pen is in need.

SUMMARY

Aspects of the present invention has an object of diagnosing a user through the user's behavior pattern using a data input device.

The object of the present invention is to provide a system helping students achieve a better test result through a derivation of cognitive and behavioral factors that affect students' performances and a recommendation engine that can output personalized score improvement strategies. The system may be implemented through a data-driven and algorithmically calculated relationship between cognitive and behavioral factors associated with test-taking behavior and data specific about each student that are collected by a data input device such as a smart pen.

In an advancement from existing diagnostic tests focusing on result, aspects of the present invention is intended to perform a diagnostic test focused on process where it is determined whether a learner efficiently solves a question, solves a question quickly without hesitation, or has a difficulty “in regard to a particular concept or process” and where the student's behavior pattern is compared with those of excelling students to find difference between them.

Another aspect of the present invention is intended to perform analysis of cognition and behavior of a learner to determine “why” the learner exhibits a particular behavior pattern in regard to a particular concept or process. Provision of a personalized study plan to the learner through the cognition and behavior analysis is intended.

The present invention has been derived to achieve the objects above and suggests an invention capable of providing a personalized study plan to a user by a diagnostic test using a data input device.

An embodiment of the present invention sets forth a diagnostic test method using a data input device, comprising: obtaining input data based on information inputted by a user for at least one question with the data input device; creating test behavior data on the user from the obtained input data; and analyzing cognition and behavior of the user based on metadata on the at least one question and/or the created test behavior data.

A variety of input devices such as a smart pen and a stylus pen may be used as the data input device. The description below is focused on cases where a smart pen is used, but the present invention is not limited thereto. The diagnosis and analysis can be made in the same manner in cases where tests are taken using fingers in mobile devices (e.g., tablet PCs) or the like.

In a diagnostic test method using a data input device according to an embodiment of the present invention, the input data may comprise coordinate values of points forming a plurality of strokes and information on the time when the points are inputted, and the test behavior data may comprise a plurality of behavioral metrics.

In a diagnostic test method using a data input device according to an embodiment of the present invention, the analyzing cognition and behavior of the user may comprise: obtaining test behavior data for the at least one question from each of a plurality of users including the user; identifying at least one behavioral metric associated with each of at least one cognitive and behavioral diagnostic (CBD) factor; calculating z-score of the at least one behavioral metric of the user, the z-score being the value of the difference between the value (X) of the at least one behavioral metric of the user and the mean value (μ) of the at least one behavioral metric associated with the CBD factor of the plurality of users divided by the standard deviation value (σ) of the at least one behavioral metric associated with the CBD factor of the plurality of users; normalizing the z-score of the least one behavioral metric; calculating the weighted average of the normalized z-score based on a predetermined weight for the at least one behavioral metric; and determining a value of the CBD factor of the user from the calculated weighted average.

In a diagnostic test method using a data input device according to an embodiment of the present invention, the at least one CBD factor may comprise confidence, grit, reasoning, concept memory, deep understanding, calculation ability, ability to understand question, test-taking strategy, etc. and each of the CBD factors may be expressed with a function based on at least one different behavioral metric and/or metadata on the question.

Another embodiment of the present invention sets forth a diagnostic test method using a data input device comprising: obtaining the input data based on information inputted by a user for at least one question with the data input device; creating test behavior data on the user from the obtained input data; and providing a personalized study plan to the user based on metadata on the at least one question and/or the created test behavior data.

A diagnostic test method using a data input device according to another embodiment of the present invention may further comprise analyzing cognition and behavior of the user based on metadata on the at least one question and/or the created test behavior data.

In a diagnostic test method using a data input device according to another embodiment of the present invention, the providing a personalized study plan to the user may comprise: determining a value of at least one cognitive and behavioral diagnostic (CBD) factor for the at least one question for a plurality of users including the user; calculating, for each of the at least one CBD factor, a similarity among at least two questions comprising the at least one question and a similarity among the plurality of users; calculating, for each of the at least one CBD factor, a cognitive gap metric by using the similarity among the at least two questions and the similarity among the plurality of users; and recommending a question to the user based on the calculated cognitive gap metric.

In a diagnostic test method using a data input device according to another embodiment of the present invention, the calculating a similarity among at least two questions comprising the at least one question and a similarity among the plurality of users may comprise applying a cosine similarity function.

In a diagnostic test method using a smart pen according to another embodiment of the present invention, the recommending a question to the user may comprise: producing the calculated cognitive gap metric for each of combinations of the user and the at least one question; identifying a question having the highest cognitive gap metric based on the calculated cognitive gap metric; and recommending the identified question to the user.

An embodiment of the present invention sets forth a diagnostic test apparatus using a data input device comprising a memory and a processor, wherein the processor is configured to obtain the input data based on information inputted by a user for at least one question with the data input device, create test behavior data on the user from the obtained input data, and analyze cognition and behavior of the user based on metadata on the at least one question and/or the created test behavior data.

In a diagnostic test apparatus according to an embodiment of the present invention, the processor may be further configured to provide a personalized study plan to the user based on the cognition and behavior analysis.

In a diagnostic test apparatus according to an embodiment of the present invention, the processor may be further configured to obtain test behavior data for the at least one question from each of a plurality of users including the user, identify at least one behavioral metric associated with each of at least one cognitive and behavioral diagnostic (CBD) factor, calculate z-score of the at least one behavioral metric of the user, the z-score being the value of the difference between the value (X) of the at least one behavioral metric of the user and the mean value (μ) of the at least one behavioral metric associated with the CBD factor of the plurality of users divided by the standard deviation value (σ) of the at least one behavioral metric associated with the CBD factor of the plurality of users, normalize the z-score of the least one behavioral metric, calculate the weighted average of the normalized z-score based on a predetermined weight for the at least one behavioral metric, and determine a value of the CBD factor of the user from the calculated weighted average.

In a diagnostic test apparatus according to an embodiment of the present invention, the processor may be further configured to determine a value of at least one cognitive and behavioral diagnostic (CBD) factor for the at least one question for a plurality of users including the user, calculate, for each of the at least one CBD factor, a similarity among at least two questions comprising the at least one question and a similarity among the plurality of users, calculate, for each of the at least one CBD factor, a cognitive gap metric by using the similarity among the at least two questions and the similarity among the plurality of users, and recommend a question to the user based on the calculated cognitive gap metric.

Another embodiment of the present invention sets forth a computer program stored in a medium to perform a diagnostic test method using a data input device, wherein the computer program comprises instructions to cause a computer or a processor to obtain input data inputted by a user for at least one question with the data input device, create test behavior data on the user from the obtained input data, analyze cognition and behavior of the user based on metadata on the at least one question and/or the created test behavior data, and provide a personalized study plan to the user based on the cognition and behavior analysis.

A computer program stored in a medium according to another embodiment of the present invention may comprise instructions to perform each step of the above-mentioned diagnostic test methods using a data input device.

In a diagnostic test method using a smart pen according to an embodiment of the present invention, the creating test behavior data may comprise calculating a total time of use of the smart pen by the user, and it may comprise calculating a time of preparation by the user before inputting information on the at least one question and calculating a total time of input of information by the user with the smart pen.

In a diagnostic test apparatus according to another embodiment of the present invention, wherein to create test behavior data, the processor may be further configured, for the purpose of calculating a total time of use of the smart pen by the user, to calculate a time of preparation by the user before inputting information using the smart pen and calculate a total time of input of information by the user with the smart pen.

By way of the present invention, it is possible to provide a cognitive and behavioral analysis result and a personalized study plan to a learner using a data input device through cognitive and behavioral analysis of the learner.

Additionally, the present invention is capable of providing a personalized study plan to a learner through machine learning algorithm using artificial intelligence.

