Low-forgetting-degree English annotation mode recommendation method and system based on AHP method

Abstract

The invention provides a low-forgetting-degree English annotation mode recommendation method and system based on an AHP method, and belongs to the field of optimization and intelligent decision theory. According to the method, firstly, five key factors influencing the English vocabulary memory forgetting rate are analyzed and pointed out in detail from the perspective of an English learner; then, a weight matrix, capable of passing consistency detection, of each influence factor is constructed through an analytic hierarchy process, and normalization processing is carried out on actual influence factor values of the weight matrix based on fuzzy logic; and obtaining an English vocabulary memory forgetting degree estimated value of the English learner in the corresponding annotation mode according to the weight matrix passing the consistency detection and the normalized influence factor score values in the different text annotation modes. And taking the annotation mode with the lowest word English word memory forgetting degree estimation as an optimal recommended annotation mode, thereby assisting an English learner in vocabulary learning. Finally, the recommendation algorithm provided by the invention is subjected to experimental verification for one month through experiments, and the experimental result proves the effectiveness of the method.

Description

Technical Field

[0001] The present invention belongs to the field of optimization and intelligent decision-making theory, and specifically relates to a method for recommending low-forgetting English annotation methods based on the AHP method. Background Art

[0002] English vocabulary plays a vital role in the process of English learning. The size of vocabulary directly affects students' English listening, speaking, reading and writing abilities, and thus affects their interest and enthusiasm in learning English. However, difficulty in memorizing vocabulary and easy forgetting are common problems and challenges faced by most students in the process of learning English vocabulary. According to the primacy effect proposed by American psychologist Lachins, initial recognition is crucial when memorizing new words, and text annotation is one of the most commonly used and effective methods for students to memorize vocabulary for the first time. Text annotation is one of the most widely used vocabulary teaching methods in English teaching (Boersetal, 2017; Ko, 2012). According to different definitions, text annotation can be divided into three types: native language annotation, English annotation, and simultaneous native language and English annotation (Zhang Chao, Ma Rong, 2021).

[0003] Generally speaking, the choice of annotation method has a profound impact on English vocabulary acquisition. In explaining vocabulary acquisition, Nagata (1999) argued that the choice of annotation method is sometimes more effective than using a dictionary. This is because an optimized annotation method can quickly capture English learners' attention. Furthermore, an appropriate annotation method can quickly connect English learners' semantics and enable vocabulary acquisition through repeated exposure and deep processing. Zhang Jing (2018) and Meng Chunguo, Chen Liping, and others (2015) also found that optimized annotation methods can, to a certain extent, promote incidental vocabulary acquisition among English learners.

[0004] On the other hand, English vocabulary memorization itself follows certain patterns. Exploring the impact of vocabulary memorization patterns on English vocabulary learning can effectively assist in English vocabulary memorization. Generally speaking, vocabulary memorization patterns follow the famous Ebbinghaus forgetting curve: immediately after completing vocabulary memorization, memory retention is 100%, 58.2% after 20 minutes, 44.2% after one hour, only 35.8% after 8-9 hours, and only 25.4% after a week. This suggests that vocabulary memorization patterns decline over time, initially increasing rapidly and then decreasing. Clearly, this forgetting pattern can be effectively applied to English vocabulary teaching. Specifically, in vocabulary teaching, learners can use the forgetting curve to predict their own forgetting rate, set appropriate memorization time points, and conduct vocabulary consolidation and review to enhance memory, thereby transforming short-term vocabulary memory into long-term memory. For example, Wang Ning (2021) identified vocabulary memorization patterns based on the Ebbinghaus forgetting curve and applied them to student vocabulary memorization training. Their research shows that spaced repetition memorization methods are more effective than cramming and concentrated memorization methods. Xie Jie (2020) studied the effects of the Ebbinghaus forgetting curve on high school students' English vocabulary memorization and found that this forgetting pattern has a positive impact on vocabulary memorization and even vocabulary application in daily life. In addition, some studies have suggested that the Ebbinghaus forgetting curve can accurately interpret the brain's forgetting process, including the time and speed of forgetting (Jin Xinyue, 2019).

[0005] However, existing research rarely focuses on the relationship between text annotation style and vocabulary retention. It fails to consider how students can reduce the tendency to forget vocabulary by choosing annotation styles when they first learn vocabulary. There are also no theories or methods recommending low-forgetability English annotation styles. Furthermore, the choice of annotation style itself is a complex issue. The factors influencing the tendency to forget English vocabulary memory involve multiple indicators and dimensions, and the degree of influence varies for different students. Summary of the Invention

[0006] In order to overcome the shortcomings of the prior art, the present invention proposes a method for recommending low-forgetting English annotation methods based on the AHP method, comprising the following steps:

[0007] Step 1: Determine the factors that influence the choice of English annotation method;

[0008] Step 2: construct the comparison matrix of influencing factors;

[0009] Step 3: Obtain the weight matrix of influencing factors and perform a consistency check on it. If it passes, save the weight matrix. Otherwise, repeat steps 2 and 3 until it passes the consistency check.

[0010] Step 4: For incoming English learners, first give them a score based on the influencing factors;

[0011] Step 5: Based on fuzzy logic theory, construct a normalization function of the influencing factors and normalize the score values of the above influencing factors;

[0012] Step 6: Based on the weight matrix that has passed the consistency test and the normalized influencing factor scores under different text annotation methods, an estimated value of the English vocabulary memory forgetting degree of English learners under the corresponding annotation method is obtained;

[0013] Step seven: compare the estimated values of English vocabulary memory forgetting obtained under the different text annotation methods, and finally select the annotation method with the smallest estimated value as the optimal annotation method for the English learner.

[0014] Furthermore, the influencing factors in step one include: English proficiency L, learning habits H, learning ability C, language environment E, and native language transfer M.

[0015] Furthermore, the comparison matrix of influencing factors in step 2 is as follows:

[0016]

[0017] In the above formula, L, H, C, E and M represent English proficiency, learning habits, learning ability, language environment and mother tongue transfer respectively, c LL , c LH , c LC , c LE , c LM They respectively represent the degree of influence of English proficiency relative to English proficiency, learning habits, learning ability, language environment and mother tongue transfer on vocabulary memory when choosing the text annotation method. The interpretation principles of other symbolic meanings are the same.

[0018] Furthermore, based on the constructed influencing factor comparison matrix, each column of the matrix is processed as follows:

[0019]

[0020] Sum each row of matrix (2) and then obtain its average value to obtain the weight matrix W of each influencing factor as shown below:

[0021] W=(w L w H w C w E w M ) (3)

[0022] For convenience, each element in the influencing factor weight matrix W is denoted as w i(i=L,H,C,E,M), where L is English proficiency, H is learning habits, C is learning ability, E is language environment, and M is mother tongue transfer.

[0023] Furthermore, the consistency of each weight in the weight matrix is checked. To this end, the following operations are performed:

[0024]

[0025] Let each element in the matrix W' be w i '(i=L,H,C,E,M), w i 'with w i Perform quotient operation and finally obtain the maximum eigenvalue of the weight matrix as follows:

[0026]

[0027] Then, the consistency index CI was calculated according to the following formula (6):

[0028]

[0029] In the above formula, n is the number of weight matrix items;

[0030] Finally, the consistency detection index CR of formula (7) is obtained:

[0031]

[0032] Among them, RI is a constant.

[0033] Furthermore, the normalization calculation formula is as follows:

[0034] f:(x∈R)→(x U ∈[0,1]) (8)

[0035] In the formula, x represents the variable to be normalized, f(·) represents the normalization function, and x U Represents the influencing factors after normalization;

[0036]

[0037] Among them, a, b, c, d are constants; thus, we can get the current English learner U i The normalized influencing factor measurement values of vocabulary memory forgetting are as follows:

[0038]

[0039] Where, represents the self-rating value of each influencing factor obtained in step 5, and Represent learner Ui Normalized influencing factor values of influencing factors L, H, C, E, and M, where L is English proficiency, H is learning habits, C is learning ability, E is language environment, and M is mother tongue transfer.

[0040] Furthermore, annotation methods include native language annotation, English annotation, and native language and English mixed annotation.

[0041] Furthermore, the estimated value of the English vocabulary memory forgetting degree of English learners is obtained. The specific process is as follows:

[0042] The learner U is obtained according to the following formula i Estimated value of English vocabulary memory forgetting degree when selecting annotation method mo

[0043]

[0044] Where mo, mo∈{M',S',H'} denotes the annotation methods as native language annotation, English annotation, and native language and English mixed annotation respectively.

[0045] Furthermore, the annotation method corresponding to the lowest estimated value of English vocabulary memory forgetting degree is selected as the best recommended annotation method mo * ,Right now:

[0046]

[0047] The present invention also provides a low-forgetting English annotation method recommendation system based on the AHP method, comprising:

[0048] The processor and the memory are used to store program instructions, and the processor is used to call the stored instructions in the memory to execute a low-forgetting English annotation method recommendation method based on the AHP method as described in the above technical solution.

[0049] Compared with the prior art, the beneficial effect of the present invention is that the annotation method recommendation algorithm of the present invention can effectively reduce the rate of forgetting of students' vocabulary memory, thereby assisting English learners in vocabulary memory. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a flowchart of the present invention.

[0051] Figure 2 Schematic diagram of the normalized function of factors affecting vocabulary memory forgetting. DETAILED DESCRIPTION

[0052] The present invention will be further described below with reference to the accompanying drawings.

[0053] In order to effectively estimate the influence of different annotation methods on the tendency of forgetting English vocabulary memory, the present invention proposes a method for recommending low-forgetting English annotation methods based on the AHP method. The AHP method is a decision analysis method that combines qualitative and quantitative methods, which can effectively and uniformly handle qualitative and quantitative factors in the decision-making process. For the method for recommending low-forgetting English annotation methods of this patent, the advantage of using the AHP method is that it is still effective when the unique subjective judgment of English learners constitutes the main component of the factors affecting vocabulary memory forgetting. The block diagram of the method for recommending low-forgetting English annotation methods based on the AHP method proposed by the present invention is shown in the figure. Figure 1 As shown in the figure, it includes the target layer, standard layer and decision layer from top to bottom. Specifically, the present invention includes the following steps:

[0054] Step 1: compare the influence of various factors on the tendency of forgetting English vocabulary memory, so as to obtain the comparison matrix of the factors;

[0055] Step 2: construct the comparison matrix of influencing factors;

[0056] Step 3: Obtain the weight matrix of influencing factors and perform a consistency check on it. If it passes, save the weight matrix. Otherwise, repeat steps 2 and 3 until it passes the consistency check.

[0057] Step 4: For incoming English learners, first assign influencing factor scores;

[0058] Step 5: Based on fuzzy logic theory, construct a normalization function of the influencing factors and normalize the score values of the influencing factors;

[0059] Step 6: Based on the weight matrix that has passed the consistency test and the normalized influencing factor scores under different text annotation methods, an estimated value of the English vocabulary memory forgetting degree of English learners under the corresponding annotation method is obtained;

[0060] Step 7: Compare the estimated values of English vocabulary memory forgetting obtained under the different text annotation methods, and finally select the annotation method with the smallest estimated value as the optimal annotation method for the English learner.

[0061] It should be noted that in step 1, to minimize English vocabulary forgetting, different factors influence the selection of text annotation methods, which constitute the standard layer of the annotation method recommendation method. This paper proposes five main factors: English proficiency (L), learning habits (H), learning ability (C), language environment (E), and mother tongue transfer (M).

[0062] It should be noted that in step 2, to quantitatively estimate the impact of the aforementioned factors on the selected annotation method, it is necessary to first obtain the corresponding weights for each factor. Based on the subjective judgment of English learners during their actual learning process, a pairwise comparison is performed to determine the relative strength of each factor's impact on vocabulary memory and forgetting, and this is quantitatively expressed in the form of an influence factor comparison matrix. Subsequently, a weight matrix of influencing factors that satisfies consistency testing is obtained, providing a quantitative basis for annotation method recommendations.

[0063] To this end, we first construct an influencing factor comparison matrix as shown in formula (1) to compare the relative strength of the influence of different influencing factors on the tendency of forgetting English vocabulary memory. Generally speaking, its value can be an integer between 1 and 9.

[0064]

[0065] In the above formula, L, H, C, E and M represent English proficiency, learning habits, learning ability, language environment and mother tongue transfer respectively, c LL , c LH , c LC , c LE , c LM They respectively represent the degree of influence of English proficiency relative to English proficiency, learning habits, learning ability, language environment and mother tongue transfer on vocabulary memory when choosing the text annotation method. The interpretation principles of other symbolic meanings are similar.

[0066] According to the influencing factor comparison matrix constructed above, each column of the matrix is further processed as follows:

[0067]

[0068] Sum each row of matrix (2), then get its average value, and add a column to get the weight matrix W of each influencing factor as shown below:

[0069] W=(w L w H w C w E w M ) (3)

[0070] For convenience, each element in the matrix W is denoted as w i (i=L,H,C,E,M).

[0071] To ensure the validity of the weight matrix of the above-mentioned influencing factors, it is necessary to perform consistency testing on each weight. To this end, the following operations are performed:

[0072]

[0073] Let each element in the matrix W' be w i '(i=L,H,C,E,M), by w i 'with w i Perform quotient operation and finally obtain the maximum eigenvalue of the weight matrix as follows:

[0074]

[0075] It should be noted that the main purpose of step 2 is to pave the way for the consistency check of the weight matrix in step 3, so as to obtain a weight matrix that meets the consistency check.

[0076] Then, the consistency index (CI) was calculated according to the following formula (6):

[0077]

[0078] In the above formula, n is the number of weight matrix items.

[0079] Finally, the consistency detection indicators are obtained as follows:

[0080]

[0081] In formula (7), RI is the consistency detection index of any pairwise comparison matrix. Its value is related to the number of comparison items, which can be seen in Table 1. For this patent, it is obvious that 1.12 should be adopted.

[0082] Table 1 Relationship between consistency index and number of items

[0083]

[0084] Finally, the obtained consistency detection index CR is compared with 0.10. If it is less than 0.10, it is considered acceptable; otherwise, it indicates that the weight matrix is unreasonable, and the influencing factor comparison matrix should be reconstructed to obtain the influencing factor weight matrix.

[0085] It should be noted that in step 4, the English learners who arrive are first asked to self-rate the five influencing factors based on their own experience.

[0086] It should be noted that in step 5, the self-scoring values of each influencing factor are normalized mainly based on fuzzy logic. The specific steps are as follows.

[0087] After obtaining the weight matrix corresponding to the influencing factors, the influence of different annotation methods on the memory and forgetting of English vocabulary can be estimated based on the current English learner's English level (L), learning habits (H), learning ability (C), language environment (E), and mother tongue transfer (M). However, each influencing factor has different dimensions and units and must be normalized. To this end, this patent designs a normalization method based on fuzzy logic to normalize each influencing factor. Specifically, a normalization function with the following form is constructed:

[0088] f:(x∈R)→(x U ∈[0,1]) (8)

[0089] In the formula, x represents the variable to be normalized, f(·) represents the normalization function, and x U Represents the influencing factors after normalization.

[0090]

[0091] Among them, f(·) is a general fuzzy logic membership function, and the specific values of a, b, c, and d are related to the application. Thus, the current English learner (assuming U i )The normalized factors affecting vocabulary memory forgetting are as follows:

[0092]

[0093] Where, represents the self-rating value of each influencing factor obtained in step 5, and Represent learner U i Normalized values of influencing factors L, H, C, E and M.

[0094] It should be noted that the main purpose of step 6 is to obtain an estimated value of the English learner's vocabulary memory forgetting degree. The specific process is as follows:

[0095] The English learner U is obtained according to the following formula i Estimated value of English vocabulary memory forgetting degree using annotation method mo

[0096]

[0097] Where mo, mo∈{M',S',H'} denotes the annotation mode, which can be native language annotation, English annotation, and native language and English mixed annotation respectively.

[0098] It should be noted that in step 7, according to (11), the English learner U iThe influence of the forgetting tendency of English vocabulary memory under three different annotation methods. Finally, the annotation method corresponding to the minimum estimated value of the forgetting tendency of English vocabulary memory is selected as the recommended annotation method, namely:

[0099]

[0100] On the other hand, an embodiment of the present invention further provides a low-forgetting English annotation method recommendation system based on the AHP method, comprising:

[0101] The processor and the memory are used to store program instructions, and the processor is used to call the stored instructions in the memory to execute a low-forgetting English annotation method recommendation method based on the AHP method as described in the above technical solution.

[0102] The English annotation method recommendation method proposed by the present invention is intended to obtain an annotation method that is conducive to improving English vocabulary memory by estimating the influence of the annotation method to be selected on the forgetting trend of English vocabulary memory. The entire system is divided into a target layer, a criterion layer and an indicator layer from a system perspective. This reflects the concept of this recommendation method (and system) to measure the efficiency of English learners' annotation methods from the perspective of different annotation methods. In order to facilitate English learners to select the annotation method that suits them, the influence weight matrix determination mechanism provided by the present invention determines the influence weights of different annotation methods on the forgetting trend of English vocabulary memory, and obtains the annotation method recommendation threshold based on the weights and in combination with the historical data in the vocabulary memory process of English learners. Therefore, for different English learners, the degree of influence of their annotation methods on English vocabulary memory is evaluated, and the influence under different annotation methods is compared to determine the optimal annotation method to be selected.

[0103] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for recommending low-forgetting English annotations based on the AHP method, characterized by: The steps include: Step 1: Determine the factors that influence the choice of English annotation method; Step 2: construct the comparison matrix of influencing factors; Step 3: Obtain the weight matrix of influencing factors and perform a consistency check on it. If it passes, save the weight matrix. Otherwise, repeat steps 2 and 3 until it passes the consistency check. Step 4: For incoming English learners, first give them a score based on the influencing factors; Step 5: Based on fuzzy logic theory, construct normalization functions of different influencing factors and normalize the score values of the above influencing factors; Step 6: Based on the weight matrix that has passed the consistency test and the normalized influencing factor scores under different text annotation methods, an estimated value of the English vocabulary memory forgetting degree of English learners under the corresponding annotation method is obtained; Step seven: compare the estimated values of English vocabulary memory forgetting obtained under the different text annotation methods, and finally select the annotation method with the smallest estimated value as the optimal annotation method for the English learner.

2. The method for recommending low-forgettability English annotations based on the AHP method according to claim 1, characterized in that: The influencing factors in step one include: English proficiency L, learning habits H, learning ability C, language environment E, and mother tongue transfer M.

3. The method for recommending low-forgettability English annotations based on the AHP method according to claim 1, characterized in that: The comparison matrix of influencing factors in step 2 is as follows: In the above formula, L, H, C, E and M represent English proficiency, learning habits, learning ability, language environment and mother tongue transfer respectively, c LL , c LH , c LC , c LE , c LM They respectively represent the degree of influence of English proficiency relative to English proficiency, learning habits, learning ability, language environment and mother tongue transfer on vocabulary memory when choosing the text annotation method. The interpretation principles of other symbolic meanings are the same.

4. The method for recommending low-forgettability English annotations based on the AHP method according to claim 3, characterized in that: According to the constructed influencing factor comparison matrix, each column of the matrix is first processed as follows: Sum each row of matrix (2) and then obtain its average value to obtain the influencing factor weight matrix W as shown below: In=(in L In H In C In E In M ) (3) For convenience, each element in the influencing factor weight matrix W is denoted as w i (i=L,H,C,E,M), where L is English proficiency, H is learning habits, C is learning ability, E is language environment, and M is mother tongue transfer.

5. The method for recommending low-forgettability English annotations based on the AHP method according to claim 4, characterized in that: Perform consistency check on each weight in the influencing factor weight matrix. To do this, perform the following operations: Let each element in the matrix W' be w i '(i=L,H,C,E,M), w i 'with w i Perform quotient operation and finally obtain the maximum characteristic root of the influencing factor weight matrix as follows: Then, the consistency index CI was calculated according to the following formula (6): In the above formula, n is the number of weight matrix items; Finally, the consistency detection index CR of formula (7) is obtained: Among them, RI is a constant.

6. The method for recommending low-forgettability English annotations based on the AHP method according to claim 1, characterized in that: The normalization calculation formula is as follows: f:(x∈R)→(x U ∈[0,1]) (8) In the formula, x represents the variable to be normalized, f(·) represents the normalization function, and x U Represents the influencing factors after normalization; Among them, a, b, c, d are constants; thus, we can get the current English learner U i The normalized influencing factor measurement values of vocabulary memory forgetting are as follows: Where, represents the self-rating value of each influencing factor obtained in step 5, and Represent learner U i The normalized influencing factor values of L, H, C, E and M are shown, where L is English proficiency, H is learning habits, C is learning ability, E is language environment, and M is mother tongue transfer.

7. The method for recommending low-forgettability English annotations based on the AHP method according to claim 1, characterized in that: Annotation methods include native language annotation, English annotation, and native language and English mixed annotation.

8. The method for recommending low-forgettability English annotations based on the AHP method according to claim 6, characterized in that: The estimated value of English vocabulary memory forgetting degree of English learners is obtained by the following process: The learner U is obtained according to the following formula i Estimated value of English vocabulary memory forgetting degree when selecting annotation method mo Where mo, mo∈{M',S',H'} denotes the annotation methods as native language annotation, English annotation, and native language and English mixed annotation respectively.

9. The method for recommending low-forgettability English annotations based on the AHP method according to claim 8, characterized in that: Select the annotation method corresponding to the lowest estimated value of English vocabulary memory forgetting as the best recommended annotation method * ,Right now:

10. A low-forgetting English annotation recommendation system based on the AHP method, characterized by: include: A processor and a memory, the memory is used to store program instructions, and the processor is used to call the stored instructions in the memory to execute a low-forgetting English annotation method recommendation method based on the AHP method as described in any one of claims 1 to 9.

Images