JP2010054874A - Learning machine, and program for controlling the same - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To change a first question setting way and a second question setting way for randomly setting questions in accordance with the movement of a learning machine so that questions that a user cannot possibly predict are set. <P>SOLUTION: A learning machine for randomly setting questions is provided. The learning machine has a detecting means for detecting the motion applied to the learning machine and, according to the motion applied to the learning machine and detected by the detecting means, a first question setting way or a second question setting way for randomly setting questions or both of them are changed. As a result, by having the user conduct in an appropriate manner, such as shaking or tilting the learning machine randomly, questions that the user cannot possibly predict can be set. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a learning machine for randomly asking questions and a program for controlling the same.

  In recent years, various devices have been carried by downsizing of devices, and there are an increasing number of portable devices that can be operated while standing up. However, it is unstable to operate the device while standing, especially if the device is operated with both hands when operating the device in a situation where a rapid acceleration is applied to the user as in a train. It is very dangerous because the body cannot be fixed because it cannot hold the strap, and it cannot respond to sudden shaking of the car body.

  Also, when operating the device while the user is moving, it is necessary to move the cursor, etc. during the operation to select a menu or to check the selected menu, so it is necessary to keep an eye on the display of the device. is there. However, if attention is paid to the display unit in this way, it becomes inadvertent in the forward direction, so it becomes impossible to notice what is approaching from the front, which is very dangerous.

  In addition, while the user is moving, it will vibrate due to walking and shaking of the moving means, and the cursor and operation buttons to be operated will become smaller due to the downsizing of the equipment, so vibration during movement In some situations, it becomes difficult to operate small operation buttons.

  In view of such circumstances, Patent Documents 1 to 3 disclose portable devices that execute functions by shaking or tilting the portable device.

  On the other hand, in order to improve the learning effect of the user in the learning machine, there is a learning machine that gives a question to the user, and various questioning methods have been proposed for the question.

  Patent Document 4 includes a display unit on all surfaces of a regular polyhedron device, displays different problems on each display unit, rolls the device, and issues the problem displayed on the upper surface to the user. A learning device for answering has been proposed.

  In Patent Document 5, each question is leveled in advance, the user's level is determined by first executing a simulation test, and a question of a selection question format suitable for the user's ability is presented. A learning machine that improves the learning effect has been proposed. In addition, this learning machine stores the degree of frequent questions, and skips questions with a high degree of frequent questions.

  Patent Document 6 proposes an electronic learning machine that levels each problem in advance, randomly selects a problem from all levels, and gives the same number of questions from each level.

Patent Document 7 proposes a learning machine that compares the order of learning subjects determined in advance with the order of subjects that the user has learned in the past so that the subjects to be studied are not biased.
JP-A-2005-237014 JP 2003-162371 A JP 2002-330210 A JP 2003-91229 A JP2000-284680 JP-A-5-27660 JP 5-11681 A

  However, the learning device described in Patent Document 4 requires a place to roll the device, and the user cannot learn while moving.

  Moreover, since the learning machine described in Patent Document 5 has a problem in a selection method such as five choices according to the level of the user, the user can predict a rough question content, and there is a questioning method. Since it is not changed and is limited to the selection problem, it is not possible to deal with problems such as the hole-filling method, and it is impossible to ask questions of various question formats, so the learning effect cannot be improved.

  Similarly, since the electronic learning machine described in Patent Document 6 is given questions from all levels for each subject, the user can predict a rough question range, and the learning effect cannot be improved. In addition, since it is known in advance that questions are given based on the degree of difficulty, the user can predict a rough question tendency.

  In addition, since the learning machine described in Patent Document 7 determines a subject to be used by using a history of a subject learned by the user in the past, the user can predict a subject to be presented next to a certain extent, and the learning effect is reduced. I can't improve.

  Further, in a general learning machine, when selecting a question, a question range is selected using a cursor key or the like, so that the user can predict which range of questions will be asked.

  In view of the above problems, the present invention can change the question range and the question method without operating the menu screen by changing the question method and / or the question range based on the movement of the mobile device. The user can give unpredictable questions with a simple operation.

  A learning machine for randomly asking questions, comprising motion detection means for detecting a motion applied to the learning machine, and based on the motion applied to the learning machine detected by the motion detection means, We propose a learning machine characterized by changing the first questioning method and / or the second questioning method to ask questions randomly.

  Here, the change of the first questioning method is to change the question that is given between attributes of problems that are not related to the superordinate concept and subordinate concept, such as by subject, difficulty, school, age, and question type. The change in the second questioning method is a superordinate concept, subordinate concept or class (such as level 1 and level 2, XX university and △ university). Etc.) is to change the question to be asked between the attributes of the problems that are related.

  The movement of the learning machine refers to the number of times the learning machine is shaken by the user, strength (acceleration), direction, rhythm or inclination of the learning machine, orientation with respect to the ground, angular velocity, angular acceleration, and other movements of the learning machine. Means all the changes that occur.

  In addition, the motion detection means is an acceleration sensor, and the first and second questioning methods for randomly asking questions based on the number of times the learning machine is shaken are changed to give questions.

  Here, the acceleration sensor detects acceleration, and measures, for example, the amount of displacement of a weight attached to a spring to estimate the acceleration applied to the weight. Accelerometers are divided into several types depending on the method of detecting displacement, and MEMS (micro electro mechanical systems) sensors that make a speed detection mechanism by a semiconductor process are common, and the performance can be measured in the range of ± several G. , Acceleration change from 0Hz to several hundred Hz can be measured. Here, 0 Hz indicates a state in which only gravitational acceleration is applied, and the direction (posture) with respect to the ground can also be measured from the sum of the acceleration vectors in the orthogonal X, Y, and Z directions at this time. Other acceleration sensors include electrodynamic sensors, strain gauge sensors, and piezoelectric sensors.

  In addition, an acceleration sensor is provided, and the first and second questioning methods for randomly asking questions based on the strength at which the learning machine is shaken or the rhythm at which the learning machine is shaken are changed to give questions. May be. Here, the rhythm refers to a rhythmic rhythm in which vibration intensity repeats regularly, a quantitative rhythm in which vibration intensity is irregular, and the like.

  In addition, a gyro sensor that detects the tilt is provided, and the learning machine randomly changes the first question method or the second question method based on the tilt angle tilted with respect to the ground so that the questions are given. May be.

  Here, the gyro sensor is a sensor that can measure the tilt of the device by measuring the magnitude of the angular velocity, and since it is small in size, a vibration gyro is often used for an electronic device. The vibration gyro sensor outputs the magnitude of the angular velocity by detecting the Coriolis force generated by the rotation of the vibrator. Other gyro sensors include a rotary type, an optical type, and a fluid type.

  Further, the first questioning method or the second questioning method for randomly asking questions is changed based on the vibration direction of the learning machine.

  A learning machine for randomly asking questions, comprising motion detection means for detecting the movement of the learning machine, wherein questions are randomly given based on a simulation using a signal obtained from the motion detection means. We propose a learning machine with features. Here, simulation refers to a method of determining a questioning method by calculating an equation of motion based on a physical law.

  The motion detection means is an acceleration sensor, and a learning machine is proposed in which the simulation is performed based on vibrations of the learning machine.

  The motion detection means is a gyro sensor that detects the inclination of the learning machine, and proposes a learning machine that performs the simulation based on the inclination of the learning machine.

  Further, as the motion detection means, both an acceleration sensor and a gyro sensor may be provided, and a parameter related to the question probability of the simulation may be changed based on the inclination of the learning machine obtained from the gyro sensor.

  Further, a display unit may be provided, and a conceptual diagram or simulation corresponding to the simulation may be displayed on the display unit.

  According to the present invention, since the questioning method can be changed and the questioning can be made random by detecting the movement of the device, the user can give a question that cannot be predicted by a simple operation method.

<First embodiment>
In the present embodiment, a learning machine is proposed in which the first questioning method or the second questioning method is changed according to the number of times the learning device 100 is shaken, and questions are given randomly. The appearance of the learning machine according to the first embodiment of the present invention will be described below with reference to FIG.

  The learning device 100 according to the first embodiment causes a problem by pressing a display unit 200 that displays an operation screen, a problem, and the like, a sound generation unit 201 that emits sound, and an operation unit 300 that performs selection and input. And a shuffle button 301 for giving an instruction to shuffle. In addition, a touch pad 302 is provided that can move a cursor and input a traced trace by tracing with a pen or a finger.

  Here, as a method of shuffling the problem, the problem is randomly generated by using an existing method such as a method in which a number is assigned to the problem in advance and a random number is generated, or a problem is randomly asked based on a specific function. Turn into.

  Next, the internal structure of the learning machine 100 will be described with reference to FIG. The learning device 100 includes a display unit 200 that outputs image information and a sound generation unit 201 that outputs sound information. Further, an operation unit 300 for inputting information by a user operation, a shuffle button 301, a touch pad 302, and an acceleration sensor that is fixedly installed on the learning device 100 and detects an acceleration that the learning device 100 moves. 303. In addition, a built-in memory 500 for storing a user's usage history (referred to as an operation history such as subject selection / function selection), questions / answers history, questions / dictionary information, etc., a portable memory, the Internet, etc. An external connection unit 501 that outputs information input from the network to the built-in memory 500, outputs the contents of the built-in memory 500, and stores the information so that it can be stored in a storage device or the like installed outside is provided. . Here, the connection to the network may be wireless or wired. In addition, output to the display unit 200 and the sound generation unit 201, input signals from the operation unit 300, the shuffle button 301, the touch pad 302, and the acceleration sensor 303, and input / output of information to the built-in memory 500 and the external connection unit 501 An I / O (Input / Output) port 400 for controlling the I / O, a CPU 600 (Central Processing Unit) for processing information input / output to / from the I / O port 400, and a battery 700 for supplying power to each unit.

  Here, the display unit 200 may be composed of, for example, an LCD (Liquid Crystal Display), an organic EL (Electro Luminescence) display, or the like, and is a touch panel. The screen is directly displayed by tracing the screen with a pen or a finger. Can be operated or input can be performed.

  In addition, information input from the external connection unit 501 may be directly output to the I / O port 400 without using the internal memory 500. In this case, the internal memory 500 may not be provided.

  Further, the shuffle button 301 is preferably provided in a range where each finger can reach so that it can be easily pushed even if the learning machine 100 is held with one hand, and more preferably, the shuffle button 301 is pressed with the thumb of the left hand or the right hand as shown in FIG. It is preferable to be provided at a position where it can be formed. When the display unit 200 is a touch panel, the shuffle button 301 may be displayed on the display unit 200.

  The problems obtained from the built-in memory 500 and the external connection unit 501 are assigned attributes as shown in FIGS. 4 and 5, and the problems divided by subject as shown in FIG. 4 are further subdivided into chapters and sections. Has been. Further, as shown in FIG. 5, the collection of questions for entrance examinations may be subdivided by school, by year, by difficulty, and by question format.

  In addition, the difficulty level may be uniform throughout the school, or the difficulty level may be determined for each school according to the questions raised at that school, and may be divided into the difficulty levels within the school. . In addition, the qualification problem collection is broken down by year, item, and difficulty level. Further, an attribute may be assigned so as to identify whether the problem is obtained from the built-in memory 500 or the external connection unit 501. The problem category is not limited to the above. If the attribute can be classified according to a certain category, it may be subdivided according to the category.

  Next, a flow until the learning device 100 of the present invention shuffles the problem for each subject and randomly questions will be described with reference to FIG. First, in step 100 (hereinafter abbreviated as S100), the shuffle button 301 is pressed to shift to a random questioning mode.

  Next, in S101, the learning machine 100 is shaken, the number of times of shaking with a certain level or more detected by the acceleration sensor 303 is counted, and if it is determined that the number of times of shaking is 4 or less, the process proceeds to S104. Shuffle problems in clauses. Here, if it is not detected that the learning device 100 is shaken within a certain time, the process proceeds to S102 to prompt the operation of the learning device 100. Next, when it is determined that the number of shakes is 5 times or more and less than 10 times, the process proceeds to S105, and the problem in Chapter 1 which is a wider range than Section 1 is shuffled. If it is determined that the number of shakes is 10 or more, the process proceeds to S106, and all problems in the subject are shuffled. In this manner, the questioning method is determined based on the number of times the learning device 100 is shaken in S107, and when the range in which the problem is shuffled is determined, the process proceeds to S108 and the shuffled question is given.

  In this way, the simple method of shaking the learning machine 100 can change the questioning method and randomize the questions, so that it can be easily operated with one hand, and the problem can be solved without operating the operation menu. Since the questions are given randomly, the user can give questions that cannot be predicted.

  In the above example, if the number of counts is 4 or less, all problems in the subject are shuffled if it is within 1 section, 5 times or less and less than 10 times, and within 1 chapter or 10 times or more, the count number is less than 4 times. If it is within 1 section, if it is 5 times or less and less than 10 times, within 1 chapter, if it is 10 times or more and less than 15 times, all within the subject, if it is 15 times or more, from all ranges regardless of the subject, etc. By setting the upper limit without being limited to 10 times, the number of ranges to be shuffled can be set more variously without being limited to three as in the above embodiment.

  In the above example, if the number of counts is 4 or less, all problems in the subject are shuffled within 1 section, 5 times or less and less than 10 times within 1 chapter and 10 times or more, but The relationship may be different for each operation.

  Further, the case where the question to be asked is displayed on the display unit 200 has been described. However, when the question can be given only by speech, such as an English listening question, the question is given only by the speech generating unit 201. In this case, the learning machine 100 does not have to include the display unit 200.

  Further, when obtaining a problem to be asked from the external connection unit 501, the built-in memory 500 may not be provided in the learning device 100, and may be given from a problem obtained from the external connection unit 501. When both the built-in memory 500 and the external connection unit 501 are provided, the problem obtained from the external connection unit 501 may be given priority.

  Further, when the learning device 100 is connected to a network network such as the Internet through the external connection unit 501, only information (the number of vibrations) related to the movement of the learning device 100 is transmitted, and on the network network based on the information. The configuration may be such that questions are randomly asked from problems stored in the database. As a result, the device can be miniaturized, questions can be asked from various problems, and the predictability of the user is lowered.

  With the above configuration, the questioning method and questioning method can be changed with only a simple operation of shaking the learning machine, and the user operates without looking at the menu screen, so the user can predict Can make impossible questions.

<Second Embodiment>
Next, with reference to FIG. 7, description will be given of a flow until the invention according to the second embodiment of the present invention shuffles problems according to difficulty levels and randomly questions. This embodiment is the same as the first embodiment in that the questioning method is randomly changed according to the appearance, circuit configuration, and number of vibrations, and detects minute vibrations that are not intended by the user, such as vibrations caused by human walking. An embodiment in which the questioning method is changed will be described.

  First, in S200, after performing an operation for starting counting (such as pressing the shuffle button 301), vibration caused by human walking or minute vibration (first vibration) felt when riding on a moving body such as a car or a train. Vibration smaller than the vibration detection threshold set in one embodiment) is detected, and the number of times is counted in S201.

  Next, when the counted number of vibrations is 5n + 1 (n is a positive integer), the process proceeds to S202 and the level 1 problem is shuffled. When the counted number of vibrations is 5n + 2, the process proceeds to S203 and the level 2 problem is shuffled. If the counted number of vibrations is 5n + 3, the process proceeds to S204 and the level 3 problem is shuffled. If the counted number of vibrations is 5n + 4, the process proceeds to S205 and the level 4 problem is shuffled. When 5 is 5n, the process proceeds to S206, where the level 5 problem is shuffled and the order of the questions to be asked is determined.

  Next, in S207, the user presses the shuffle button 301 to shift to a random questioning mode, determines the questioning method based on the number of vibrations counted when the shuffle button 301 is pressed (S208), and the shuffled problem Questions randomly (S209).

  As described above, in the above embodiment, the difficulty level is set to 5; however, by using a function called an + b (a, n, and b are positive integers) and changing a and b respectively, The number is not limited to five as in the above embodiment, and more versatile settings can be made. In this way, the function used may be any function as long as it has a certain regularity. By using the function and associating the number of vibrations with the changed questioning method and the questioning method, a more general purpose It is possible to make a highly specific setting.

  As described above, according to the present embodiment, by counting the vibrations that the user does not intend to generate, the questioning method in which the problem is presented is changed, so that the user can make an unpredictable question. Can do.

<Third embodiment>
Next, the flow until the invention according to the third embodiment of the present invention shuffles the problems for each subject and questions them randomly will be described with reference to FIG. This embodiment is the same as the first embodiment in that the questioning method and range are randomly changed according to the appearance, the circuit configuration, and the number of vibrations, and an embodiment in which the questioning difficulty level is changed according to the direction of vibration will be described.

  First, in S300, the user presses the shuffle button 301 and shifts to a mode in which random questions are given.

  Next, the learning machine 100 is shaken in S301, and the vibration direction detected by the acceleration sensor 303 is detected. Here, if the vibration direction includes a certain vertical component or more, the process proceeds to S304, and if the downward vibration is detected, the question level is lowered (S305), and if the upward vibration is detected, the question level is increased. (S306) The final difficulty level of questions is determined when the vibration stops (S307).

  If the vibration direction includes a horizontal component, the process proceeds to S308, the number of times the acceleration sensor 303 is shaken at a certain level or more is counted, and if it is determined that the number of shakes is 4 or less, the process proceeds to S309. , Shuffle the problems in section 1. If it is determined that the number of shakes is 5 times or more and less than 10 times, the process proceeds to S310 to shuffle the problems in Chapter 1, which is wider than Section 1. If it is determined that the number of shakes is 10 or more, the process proceeds to S311 to shuffle all problems in the subject and determine the range of questions to be asked (S312).

  Next, when the range for shuffling the problem is determined, the process proceeds to S313, where the difficulty level determined in S307 is extracted from the questioning methods determined in S312 and the problem is shuffled and presented randomly.

  Here, the vertical direction refers to the X direction in FIG. 1, the vertical upward direction refers to the negative direction of the X direction, and the vertical downward direction refers to the positive direction of the X direction. The horizontal direction refers to the Y direction in FIG. However, the direction need not be limited to this, and it is sufficient that each direction is orthogonal, such as the X, Y, and Z directions shown in FIG. 1, and the number of vibrations is counted in order to change the questioning method according to these directions. Any setting may be used as long as the two directions for detecting vibrations are different in order to change the direction to perform and the difficulty level of the questions.

  By adopting such a configuration, the user can swing the learning machine only to make the question difficulty level intended by the user to some extent, and can give an unintended question as to the questioning method. Can make impossible questions.

<Fourth embodiment>
Next, with reference to FIG. 9 and FIG. 10, description will be given of a flow in which questions are randomly asked by changing the questioning method in the invention according to the fourth embodiment of the present invention. This embodiment is the same as the first embodiment in appearance and circuit configuration, and an embodiment in which the questioning method is changed depending on the vibration intensity will be described.

  FIG. 9 shows an example of a waveform detected by the acceleration sensor 303 when the learning device 100 is shaken by the user. Here, a plurality of thresholds having different magnitudes (here, thresholds 1 and 2 are t1 and t2, respectively, and t1 <t2) are determined with respect to the amplitude of the output obtained from the acceleration sensor.

  FIG. 10 is a flowchart for determining a question assignment method. First, in S400, the user presses the shuffle button 301 to shift to a mode in which a random question is given.

  Next, in S 401, the learning device 100 is shaken, and vibrations shaken at a certain level or more detected by the acceleration sensor 303 are detected. Next, when it is determined that the maximum amplitude of the detected vibration waveform is less than the threshold value 1 (less than t1), the process proceeds to S404, and the problem is shuffled according to the degree of difficulty. If it is determined that the maximum amplitude is greater than or equal to threshold 1 and less than threshold 2 (from t1 to t2), the process proceeds to S405 and the problem is shuffled for each school. If it is determined that the amplitude is greater than or equal to the threshold value 2 (t2 or greater), the process proceeds to S406, where the problem is shuffled according to the year of question. Next, when the questioning method for setting the question is determined, the process proceeds to S407, and the shuffled question is randomly asked.

  Here, in the present embodiment, the predetermined threshold value is two, but by further increasing the number of threshold values, finer control can be performed, and the types of question methods that can be changed are the same as the number of question methods in this embodiment. It can be increased from 3.

  With such a configuration, the questioning method can be changed with a small number of times of shaking the learning machine in order to change the questioning method, and the questioning method can be changed with a simpler operation.

<Fifth embodiment>
Next, with reference to FIG. 11, FIG. 12, and FIG. 13, in the invention according to the fifth embodiment of the present invention, the flow up to the assignment will be described. The external appearance of this embodiment is the same as that of the first embodiment, and the circuit configuration includes a gyro sensor 304 that detects an inclination angle instead of the acceleration sensor 303 of the learning machine of the first embodiment as shown in FIG. The questioning method is changed according to the inclination angle of the learning device 100 with respect to the ground, and the questions are given randomly.

  FIG. 12 is a diagram showing how the inclination angle with respect to the ground is detected in the learning device 100 of the present embodiment. Here, FIG. 12 shows the movement in the YZ plane inclined about the X axis of FIG. 1, and the ground is in the minus direction of the Z direction as shown. The Y axis is horizontal to the ground, and the angle θ when rotated counterclockwise is set as the plus direction. When the learning device 100 is held horizontally with the ground, the inclination angle θ is set to 0 °.

  Next, the question determination method of this embodiment will be described with reference to FIG. FIG. 13 is a flowchart for determining the questioning method. First, in S500, the user presses the shuffle button 301 and shifts to a mode in which a random questioning is performed. Next, in S502, the inclination angle θ when the rotary motion of the learning machine 100 stops (or when the angular acceleration decreases) is determined. If the inclination angle is 0 ° to 90 °, the process proceeds to S503 and the problem of level 1 occurs. If the tilt angle is 90 ° to 180 °, the process proceeds to S504 to shuffle the level 2 problem. If the tilt angle is 0 ° to −90 °, the process proceeds to S505 to shuffle the level 3 problem. When the tilt angle is -90 ° to -180 °, the process proceeds to S205, and the order of the questions to be asked is determined by shuffling the level 4 problem.

  Next, the questioning method is determined in S507, and the shuffled questions are randomly given (S508).

  The above is the description of the question determination method of the present embodiment. The direction of detecting the tilt nucleus is not limited to the X axis in FIG. 1 as the rotation axis, but the tilt nucleus is detected in the XZ plane with the Y axis as the rotation axis. Needless to say, it can be set.

  Further, in the present embodiment, the range of the tilt angle is divided into four every 90 °, but may be divided in more detail every 30 °, and the tilt angle from 0 ° to 180 ° may be divided. It may be set so that only a certain range of tilt angles is detected.

<Sixth embodiment>
Next, with reference to FIG. 14, in the invention according to the sixth embodiment of the present invention, the first question method and the second question method are changed randomly according to the direction, strength, and number of vibrations of the learning machine. The flow to perform will be described. This embodiment has the same appearance and circuit configuration as the first embodiment, and the learning machine 100 has a vertical direction, a horizontal direction, and a normal direction (the X-axis direction, Y-axis direction, and Z-axis direction in FIG. The embodiment in the case where the first questioning method and the second questioning method are changed by detecting the vibration of the meaning) will be described.

  FIG. 14 is a question assignment method determination flow. First, in S600, the shuffle button 301 is pressed to shift to a random question assignment mode. Next, in step S601, the learning device 100 is shaken, and vibrations with a certain level or more detected by the acceleration sensor 303 are detected. Here, when the vertical direction component of a certain size or more in the vibration direction is included, the process proceeds to S605 and the strength of the vertical direction component is recognized.

  Here, as in the fourth embodiment, if it is determined that the maximum amplitude of the detected vibration is less than the predetermined threshold 1, the process proceeds to S606, and the problem is shuffled for each question type. If it is determined that the maximum amplitude is greater than or equal to the predetermined threshold value threshold 1 and less than the threshold value 2, the process proceeds to S607 and the problem is shuffled for each school. If it is determined that the amplitude is equal to or greater than the predetermined threshold value 2, the process proceeds to S <b> 608 and the problem is shuffled according to the year of question. In step S609, a final first questioning method is determined.

  If the horizontal direction component of a certain magnitude or more is included in the vibration direction, the number of times of horizontal shaking is counted in S610, and if it is determined that the number of times of shaking is 4 or less, the process proceeds to S611. , Shuffle the problems in section 1. If it is determined that the number of shakes is 5 times or more and less than 10 times, the process proceeds to S612 and the problem in Chapter 1 which is wider than Section 1 is shuffled. If it is determined that the number of shakes is 10 or more, the process proceeds to S613 to shuffle all problems in the subject. In S614, the final second questioning method is determined.

  If the vibration direction includes a normal direction component of a certain magnitude or more, if a downward vibration (Z-axis direction minus direction) is detected, the first questioning method determined in S609 and S614 The question level is lowered due to the problem of the second question method (S616), and if an upward vibration (in the Z-axis direction plus direction) is detected, the question level is raised (S617), and finally when the vibration stops A difficult question difficulty level is determined (S618).

  Then, the questions are started from the first question method, the second question method, and the difficulty level determined in S609, S614, and S618 (S619).

  In this way, by changing the first question method and the second question method according to the direction and strength of the learning machine 100, the questions that are unpredictable by the user are given questions. Can improve the learning effect.

<Seventh embodiment>
Next, with reference to FIG. 15, FIG. 16, and FIG. 17, in the invention according to the seventh embodiment of the present invention, the flow up to the assignment will be described. The external appearance of this embodiment is the same as that of the first embodiment, and the circuit configuration further includes a gyro sensor 304 for detecting the tilt angle in the learning machine of the first embodiment as shown in FIG. The questions are changed randomly by performing a simulation using information about the questions.

  FIG. 16 is a diagram showing the concept of the simulation according to the present embodiment, in which the question questions and the question order are determined from the magnitude of the vibration of the learning machine 100. The outline of this simulation will be described below.

  In the present embodiment, an explanation will be given using world history as an example of the subject. The question to be presented is recognized as a question ball 801 and stored in a question box 802 classified by unit and difficulty level.

  Then, when the learning device 100 is shaken and the direction and magnitude of acceleration are given from the acceleration sensor 303, the question table 803 is shaken vertically according to the information, and the question ball 801 jumps out of the question box 802.

  When the question ball 801 comes out on the question table 803 by shaking the learning machine 100, the question table 803 is inclined toward the question box 804, so that the question ball 801 always falls into the question box 804. By memorizing the dropped order, the questions to be asked and the order are determined.

  Here, as the difficulty level of the problem box 802 increases, the height of the wall increases. If the learning machine 100 is shaken strongly and no large acceleration is applied, the problem ball 801 comes out of the problem box 802 with a high difficulty level. It is designed not to come.

  The above is the description of the outline of the simulation of the questioning method according to the present embodiment. Specifically, what kind of law is used for the simulation will be described.

  First, the mass m is given to the problem ball 801 as a parameter, and it is assumed that the problem ball 801 is subjected to the same acceleration as gravity. Then, the question table 803 vibrates according to the acceleration obtained from the acceleration sensor 303, and the motion of the problem ball 801 is simulated from the equation of motion related to the problem ball 801.

  Next, as a result of the simulation, when the problem ball 801 jumps out of the problem box 802 having the set height wall, the problem ball 801 falls on the question table 803. Here, the coefficient of restitution of the question table 803 is set to 0, and when the question ball 801 falls on the question table 803, it does not bounce off and does not bounce out of the question table 803.

  Then, the motion ball 801 that has fallen on the question table 803 is simulated in motion by calculating an equation of motion according to the inclination of the question table 803, and finally falls in the question box 804.

  As described above, as a simulated method, the questioning method is determined by physically simulating the movement of the problem ball 801 based on a realistic physical law (such as the same gravitational acceleration).

  Here, assuming such a physical simulation, it is necessary to raise the problem ball 801 to the height of the problem box 802 by increasing the height of the wall of the problem box 802. A large acceleration is required. Therefore, by increasing the height of the wall of the problem box 802 having a high difficulty level, in order to give a problem with a high difficulty level, the learning machine 100 has to be greatly vibrated in order to give a large acceleration accordingly. Can be.

  In addition, the mass m of the problem ball 801 is changed according to the difficulty level of the problem, the mass m is increased for those having a higher difficulty level, and in order to give a higher acceleration in order to give a problem with a higher difficulty level. The learning machine 100 may have to be vibrated greatly.

  Here, the relationship between the height of the wall of the problem box 802 and the mass m of the problem ball 801 and the difficulty level can be set in various ways, and the problem wall with a lower difficulty level sets the wall height of the problem box 802 higher. However, the mass m of the problem ball 801 may be set to be heavy.

  In the above, the motion of the problem ball 801 is physically simulated by defining the mass of the problem ball 801 and solving the equation of motion, but instead of defining the mass of the problem ball 801, the probability of appearance of each problem ball 801 is set. It may be provided and statistically simulated.

  In this case, the acceleration obtained from the acceleration sensor 303 when the learning device 100 is shaken is converted into an appearance probability corresponding to the magnitude, and the problem ball 801 set to an appearance probability higher than the converted appearance probability is displayed. Jump out of the problem box 802.

  Based on such a simulation, a problem ball with a high appearance probability appears even if the learning machine 100 is shaken small, but a problem ball with a low appearance probability can be prevented from appearing unless the learning machine 100 is shaken greatly. .

  The tilt of the learning device 100 may be detected by the gyro sensor 304, the question table 803 may be tilted according to the tilt, and the question ball 801 may be output from the question box 802. In this case, the simulation can be performed by calculating the equation of motion based on the gravitational acceleration and the inclination based on the mass of the problem ball 801 as in the physical simulation.

  In addition, both the acceleration sensor 303 and the gyro sensor 304 are provided. The inclination of the question table 803 is changed in accordance with the inclination of the learning device 100 obtained from the gyro sensor 304, and the simulation parameters are changed, so that each problem box 802 is displayed. The appearance probability of the incoming problem ball 801 may be changed.

  Next, the question flow of this embodiment will be described with reference to FIG. First, in S700, the user presses the shuffle button 301 and shifts to a mode in which random questions are given.

  In step S <b> 701, the learning device 100 is moved, and vibrations shaken at a certain level or more by the acceleration sensor 303 or a gradient greater than a certain value is detected by the gyro sensor 304. Here, if a vibration above a certain level is detected, a simulation is performed to determine a problem to be presented (S703).

  Next, in step S704, the order of the problem balls 801 that have fallen into the question box 804 by the simulation is sequentially stored. The simulation is continued until n question balls 801 are dropped, and the order of the question balls 801 dropped in the question box 804 is stored (S705). Here, n is an arbitrary number set in advance. Finally, questions are started in the order determined by the simulation and the questions (S706).

  With such a configuration, an unpredictable question can be given only by a simple operation in which the user shakes or tilts the learning device 100.

  Here, when the learning device 100 includes the display unit 200, a conceptual diagram of the simulation may be visualized and displayed on the display unit 200 as shown in FIG. By doing in this way, it can be confirmed how many problem balls 801 have jumped out from which problem box 802, the degree of shuffle can be confirmed, and the visual fun can be expressed.

<Eighth embodiment>
Next, a flow until the invention according to the eighth embodiment of the present invention shuffles a problem and randomly questions will be described with reference to FIGS. The present embodiment is the same as the first embodiment in appearance and circuit configuration, and an embodiment in which the questioning method is changed according to the rhythm of shaking the learning machine will be described.

  FIG. 18 is a question assignment method determination flow. First, in S800, the shuffle button 301 is pressed to shift to a mode in which a random question is given.

  Next, in step S <b> 801, the learning machine 100 is shaken, and vibrations with a certain level or more detected by the acceleration sensor 303 are detected. In step S803, the detected vibration waveform shape is stored. The shape to be stored is like the waveform shape shown in FIG. 19, and a certain threshold value (t3) is determined in advance, and the time indicating the maximum value having a positive value that is equal to or greater than the threshold value is determined. Remember. Then, T1, T2, T3, and T4, which are the differences of the stored times, are obtained by calculation.

  In S804, pattern matching with a previously stored rhythm (for example, 2 + 3 + 3 time signature, 3 + 2 + 3 time signature, 3 + 2 + 2 time signature, etc.) is performed by calculating the obtained T1, T2, T3, and T4. It is determined whether they are similar (S805).

  For example, if it is determined that the shape of the stored waveform is 2 + 3 + 3, the process proceeds to S806 and a challenge problem is given. On the other hand, if it is determined that the stored waveform shape is 3 + 2 + 3 time signature, the process proceeds to S807, and the confidence recovery problem is given. If it is determined that the stored waveform shape is 3 + 2 + 2 time signature, the process proceeds to S808, and the revenge problem is set. Then, the problem is shuffled by the questioning method determined in S809, and the questioning is started (S810).

  Here, the challenge problem means a question from a range that has not been asked yet, the revenge problem means a question that has been picked up from a problem that has been tested in the past and made a mistake, and the confidence recovery problem means a past test. It means that the question is given from the correct answer.

  The above is the description of the embodiment according to the present invention. In all of the above examples, the relationship between the information related to the movement of the learning machine 100 and the questioning method determined based on the information is not limited to the above examples. Further, the correspondence relationship may be changed every time for each operation. By doing so, the predictability of the user is further reduced.

  In addition, it should be considered that the embodiments disclosed herein are illustrative and non-restrictive in every respect. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims. Further, it goes without saying that the present invention includes even a part of the plurality of embodiments combined.

  The embodiment described above is also realized by a program for causing the learning machine to function. In this case, the program may be stored in a recording medium readable by an information processing apparatus such as a computer. Further, the read program may be downloaded to a program storage area (not shown) and executed.

  It can be used for a learning machine that questions various questions randomly.

It is an external view of the learning machine of this invention. It is a block diagram which shows the internal structure of the learning machine which concerns on 1st embodiment of this invention. It is a figure showing the position of the shuffle button of the learning machine which concerns on 1st embodiment of this invention. It is a figure showing an example of the attribute of the problem concerning a first embodiment of the present invention. It is a figure showing an example of the attribute of the problem concerning a first embodiment of the present invention. It is a flowchart of a question method determination flow according to the first embodiment of the present invention. It is a flowchart of the question method determination flow which concerns on 2nd embodiment of this invention. It is a flowchart of the question method determination flow which concerns on 3rd embodiment of this invention. FIG. 10 is a diagram illustrating an example of a waveform detected by an acceleration sensor according to the fourth embodiment of the present invention. It is a flowchart of the question method determination flow which concerns on 4th embodiment of this invention. It is a block diagram which shows the internal structure of the learning machine which concerns on 5th embodiment of this invention. It is the figure which showed an example which detects the inclination | tilt angle which concerns on 5th embodiment of this invention. It is a flowchart of the question method determination flow which concerns on 5th embodiment of this invention. It is a flowchart of the question method determination flow which concerns on 6th embodiment of this invention. It is a block diagram which shows the internal structure of the learning machine which concerns on 6th embodiment of this invention. It is a conceptual diagram of the simulation which concerns on 7th embodiment of this invention. It is a flowchart of the question method determination flow which concerns on 7th embodiment of this invention. It is a flowchart of the question method determination flow which concerns on 8th embodiment of this invention. FIG. 20 is a diagram illustrating an example of a waveform detected by an acceleration sensor according to the eighth embodiment of the present invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Learning machine 200 Display part 201 Voice generation part 300 Operation part 301 Shuffle button 302 Touchpad 303 Acceleration sensor 304 Gyro sensor 400 I / O port 500 Built-in memory 501 External connection part 600 CPU
700 Battery 801 Question ball 802 Question box 803 Question table 804 Question box

Claims (12)

A learning machine that questions questions randomly,
Comprising a motion detection means for detecting a motion applied to the learning machine;
Based on the motion applied to the learning machine detected by the motion detection means, the first questioning method and / or the second questioning method for randomly asking a question are changed and the questions are given. To learn. The motion detection means is an acceleration sensor;
The learning machine according to claim 1, wherein the first questioning method or the second questioning method in which questions are randomly given based on the number of times the learning machine is shaken changes the questioning method. The motion detection means is an acceleration sensor;
The learning machine according to claim 1, wherein the first questioning method or the second questioning method in which questions are randomly given based on the strength with which the learning machine is shaken changes the questioning method. The motion detection means is a gyro sensor that detects inclination,
2. The method according to claim 1, wherein the learning machine issues a question by changing a first questioning method or a second questioning method in which questions are randomly given based on an inclination angle inclined with respect to the ground. Learning machine. The motion detection means is an acceleration sensor;
The learning machine according to claim 1, wherein the learning machine changes the first questioning method or the second questioning method in which questions are randomly given based on a rhythm that is shaken. The motion detection means is an acceleration sensor;
The learning machine according to claim 1, wherein the first questioning method or the second questioning method for randomly asking questions is changed based on the vibration direction of the learning machine. A learning machine that questions questions randomly,
Comprising a motion detection means for detecting a motion applied to the learning machine;
A learning machine that randomly questions a problem based on a simulation using a signal obtained from the motion detection means. The motion detection means is an acceleration sensor;
The learning machine according to claim 7, wherein the simulation is performed based on vibrations of the learning machine. The motion detection means is a gyro sensor that detects the inclination of the learning machine,
The learning machine according to claim 7, wherein the simulation is performed based on an inclination of the learning machine. As the motion detection means, both an acceleration sensor and a gyro sensor are provided,
The learning machine according to claim 8, wherein a parameter relating to a question probability of the simulation is changed based on an inclination of the learning machine obtained from the gyro sensor. A display unit;
The learning machine according to claim 7, wherein a conceptual diagram or an animation corresponding to the simulation is displayed on the display unit.   The program for controlling a control part in order to make it function as a learning machine of Claim 1-11.