







































 

 

 

 

 

The Non-Intellectual Norm of Middle 

School Students’ Mathematics Learning and 

Its Grade Evaluation Standard: 

Taking Tianjin as an Example

Guangming Wang,
1
 Jian Li,

2
 Jingxian Jian

3
 

 
1. Tianjin Normal University, Tianjin 300387, China 

2. People’s Education Press, Beijing 100081, China 

3. Nankai Elementary School, Tianjin Eco-City, Tianjin 300467, China

Abstract. Using the “Middle School Student Mathematics Learning Non-

intellectual Questionnaire,” a total of 1,400 middle school students in 11 
districts and counties of Tianjin were surveyed. According to the data, 

using the raw score normalization method and the formula “T = 

50+10×Z”, the non-intellectual overall and sub-dimension norm table of 
middle school student math learning were established, and the corre-

sponding grade evaluation standard was determined. Using the results 
of this study, two types of application case analysis of class and individ-

ual were carried out, and corresponding suggestions were put forward 

based on the analysis results. 

Best Evidence in Chinese Education 2021; 7(1):907-922. 

Doi: 10.15354/bece.21.ar007. 

How to Cite: Wang, G., Li, J. & Jian, J. (2021). The non-intellectual norm of middle 

school students’ mathematics learning and its grade evaluation standard: Taking 

Tianjin as an example. Best Evidence in Chinese Education, 7(1):907-922. 

Keywords: Middle School Student; Mathematics; Non-Intellectual; Norm; Grade 

Evaluation Standard

 
 
 
 

 

About the Authors: Jian Li, Postdoctoral Research Station Researcher, Institute of Curriculum and Textbooks, 

People’s Education Press, Beijing 100081, China. Email: 471460647@qq.com; 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No.1, 2021 908 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

About the Authors: Jingxian Jian, Math Teacher, Nankai Elementary School, Tianjin Eco-City, Tianjin 300467, 

China. Email: 541151139@qq.com. 

Correspondence to: Guangming Wang, Professor, Chief, Faculty of Education, Tianjin Normal University, Tianjin 
300387, China. Email: bd690310@163.com. 

Funding: This study was supported by the Tianjin Teaching Achievement Cultivation Project “Development and 
Practical Application of Mathematics Learning Evaluation Tools” (project #: PYJJ-036). 

Conflict of Interests: None. 
 

© 2021 Insights Publisher. All rights reserved. 

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Crea-

tive Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-

nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided 

the original work is attributed by the Insights Publisher. 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 909 

ON-INTELLECTUAL factors, as an essential part of influencing students’ 

learning and development, have received extensive attention in the fields of 

education and psychology. Studies have shown that there is a positive correla-

tion between non-intellectual factors of mathematics learning and mathematics academ-

ic performance (Lv et al., 1995; Wang, 2004; Zhang, 2012). Besides, non-intellectual 

factors are important influencing factors of mathematics learning efficiency (Wang et 

al., 2014; Wang et al., 2015; Wang et al., 2017; Wang & Yang, 2015). Although there 

are many non-intellectual evaluations of middle school students’ mathematics learning 

in previous studies (Cao et al., 2015; Yang et al., 2015), they lacked a unified evalua-

tion basis and reference, and the measurement results cannot be analyzed under the 

same reference standard. Therefore, it is indispensable to study the non-intellectual 

norm of middle school students in mathematics. Based on the “Middle School Student 

Mathematics Learning Non-intellectual Questionnaire,” this study established the mid-

dle school student math learning non-intellectual norm and its grade evaluation standard 

and conducted a case analysis of this result. 

Methods 

Research Tools 

This study chose the “middle school student math learning non-intellectual question-

naire” as the survey tool. The questionnaire is a five-level Likert scale, consisting of 

five main dimensions (motivation, emotion, attitude, willpower, personality) and poly-

graph questions, all of which have good reliability and validity (Wang & Li, 2020). 

Sample Selection 

The study selected 1,400 6th- and 7th-grade students in 11 districts and counties of 

Tianjin to conduct a survey, and a total of 1,400 questionnaires were returned. First, 

through manual inspection, 56 questionnaires with regular and identical answers were 

deleted; then, 58 invalid questionnaires were deleted with the help of polygraph ques-

tions, and finally, 1,286 valid questionnaires were obtained, with an effective rate of 

91.86%. 

Data Processing 

When entering data, the A-E options were counted as 5-1 point, and the reverse ques-

tions were counted as 1-5 points. After data entry was completed, use SPSS software 

for data processing. Calculating the sufficient sample’s percentile rank determined the 

correspondence between the original score and the percentile rank. And then checked 

the normal distribution table with the help of percentile rank to get its corresponding 

standard score. To ensure the convenience of reading the score, the standard score was 

converted using the formula “T=50+10×Z” to establish a non-intellectual norm table. 

 

N 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 910 

Table 1. Non-Intellectual Level Evaluation Standards for Mathematics Learn-
ing. 

Grade T Score Raw Score X Percentile Rank PR 

Low-Level T < 32 X < 128 PR < 3.27 

Middle and Lower 32 ≤ T < 44 128 ≤ X < 157 3.27 ≤ PR < 26.83 

Middle 44 ≤ T < 56 157 ≤ X < 181 26.83 ≤ PR < 70.53 

Middle and Upper 56 ≤ T < 68 181 ≤ X < 201 70.53 ≤ PR < 95.80 

Excellent T ≥ 68 X ≥ 201 PR ≥ 95.80 

 

 

 

Table 2. “Motivation” Dimension Grade Evaluation Standards. 

Grade T Score Raw Score X Percentile Rank PR 

Low-Level T < 32 X < 31 PR < 3.27 

Middle and Lower 32 ≤ T < 44 31 ≤ X < 40 3.27 ≤ PR < 25.74 

Middle 44 ≤ T < 56 40 ≤ X < 47 25.74 ≤ PR < 69.52 

Middle and Upper 56 ≤ T < 68 47 ≤ X < 54 69.52 ≤ PR < 96.19 

Excellent T ≥ 68 X ≥ 54 PR ≥ 96.19 

 

 

 

 

Figure 1. The T-Score Chart of the Sub-Dimension of the “Motivation”. 

 

 

 

 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 911 

According to the normal distribution theory, 99.74% of the values under the 

standard normal distribution fall within the interval [-3, 3], so first divided [-3, 3] into 

five equal intervals, and then used the formula “T=50+ 10×Z” to get the corresponding 

T score interval, and then divided it into five different levels. Finally, the T score inter-

val was converted into a percentile grade interval to complete the grade evaluation 

standard’s establishment. 

Results 

Mathematics Learning Non-Intellectual Norm and Its 

Grade Evaluation Standard 

A middle school student’s mathematics learning non-intellectual norm (table omitted) 

and its corresponding Grade Evaluation Standard (see Table 1) are established accord-

ing to the norm’s construction method through data sorting and analysis. The research 

was carried out from five main dimensions to diagnose the non-intellectual influence of 

students’ mathematics learning more precisely. 

“Motivation” Dimension Norm and Its Grade Evaluation 

Standard 

According to the norm construction method, we established the “motivation” dimension 

norm (table omitted). Second, divided the “motivation” dimension horizontally, and 

then formulated the corresponding grade evaluation standard (see Table 2). Finally, we 

calculated the average scores of students of different levels in the sub-dimensions of 

“cognitive motivation,” “extrinsic motivation,” and “achievement need” under the “mo-

tivation” dimension (see Figure 1). 

Based on Figure 1, combined with the definition of the concepts and questions 

of the sub-dimensions of mathematics learning motivation (Wang & Li, 2020), students 

of different levels have the following characteristics: “Excellent” students are curious 

about mathematics and like to study and explore; They have a vital purpose in learning 

mathematics and are eager to highlight their talents in mathematics learning. “Middle 

and upper” students are interested in exploring mathematics knowledge, are motivated 

to learn, and like to participate in activities that can show their mathematics learning 

ability. “Middle” students have specific goals and motivation to learn mathematics and 

show interest in learning mathematics and a desire to succeed. “Middle and lower” stu-

dents do not like to participate in math learning activities, show less desire for perfor-

mance, do not like inquiry, and are more inclined to accept learning. “Low-level” stu-

dents lack interest in mathematics learning, hardly participate in math learning activities, 

and are unwilling to show their mathematics learning ability. 

 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 912 

Table 3. “Emotion” Dimension Grade Evaluation Standard. 

Grade T Score Raw Score X Percentile Rank PR 

Low-Level T < 32 X < 25 PR < 3.03 

Middle and Lower 32 ≤ T < 44 25 ≤ X < 33 3.03 ≤ PR < 23.59 

Middle 44 ≤ T < 56 33 ≤ X < 41 23.59 ≤ PR < 72.08 

Middle and Upper 56 ≤ T < 68 41 ≤ X < 48 72.08 ≤ PR < 96.35 

Excellent T ≥ 68 X ≥ 48 PR ≥ 96.35 

 

 

 

 

 

Figure 2. The T-Score Chart of the Sub-Dimension of the “Emotion”. 

 

 

 

 

Table 4.”Attitude” Dimension Grade Evaluation Standard. 

Grade T Score Raw Score X Percentile Rank PR 

Low-Level T < 32 X < 32 PR < 3.19 

Middle and Lower 32 ≤ T < 44 32 ≤ X < 39 3.19 ≤ PR < 24.57 

Middle 44 ≤ T < 56 39 ≤ X < 45 24.57 ≤ PR < 69.75 

Middle and Upper 56 ≤ T < 68 45 ≤ X < 49 69.75 ≤ PR < 93.39 

Excellent T ≥ 68 X ≥ 49 PR ≥ 93.39 

 

 

 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 913 

 

Figure 3. The T-Score Chart of the Sub-Dimension of the “Attitude”. 

 

 

 

 

Table 5. “Willpower” Dimension Grade Evaluation Standards. 

Grade T Score Raw Score X Percentile Rank PR 

Low-Level T < 32 X < 17 PR < 2.72 

Middle and Lower 32 ≤ T < 44 17 ≤ X < 23 2.72 ≤ PR < 25.27 

Middle 44 ≤ T < 56 23 ≤ X < 28 25.27 ≤ PR < 72.38 

Middle and Upper 56 ≤ T < 68 28 ≤ X < 32 72.38 ≤ PR < 96.35 

Excellent T ≥ 68 X ≥ 32 PR ≥ 96.35 

 

 

 

 

Table 6. “Personality” Dimension Grade Evaluation Standards. 

Grade T Score Raw Score X Percentile Rank PR 

Low-Level T < 32 X < 15 PR < 3.27 

Middle and Lower 32 ≤ T < 44 15 ≤ X < 20 3.27 ≤ PR < 26.59 

Middle 44 ≤ T < 56 20 ≤ X < 24 26.59 ≤ PR < 71.23 

Middle and Upper 56 ≤ T < 68 24 ≤ X < 27 71.23 ≤ PR < 92.22 

Excellent T ≥ 68 X ≥ 27 PR ≥ 92.22 

 

 

 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 914 

 

Figure 4. The T-Score Chart of the Sub-Dimension of the “Willpower”. 

 

 

 

 

Figure 5. The T-Score Chart of the Sub-Dimension of the “Personality”. 

 

 

 

 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 915 

“Emotion” Dimension Norm and Its Grade Evaluation 

Standard 

First, establish the “emotion” dimension norm according to the norm construction 

method (table omitted). Secondly, divide the “emotion” dimension horizontally, and 

then formulate the corresponding grade evaluation standard (see Table 3). Finally, cal-

culate the average scores of students of different levels in the sub-dimensions of “emo-

tional stability,” “learning anxiety,” and “learning efficacy” under the “emotion” di-

mension (see Figure 2). 

Based on Figure 2, combined with the conceptual definition and questions of 

each sub-dimension of emotion (Wang & Li, 2020), it was found that students of differ-

ent levels have the following characteristics: “Excellent” students have reasonable con-

trol over their emotions and can effectively control and regulate their emotions; they 

like to learn mathematics, basically do not have negative emotions, and have a high 

sense of learning efficiency. “Middle and upper” level students understand themselves 

and occasionally produce destructive emotions but can control and adjust them in time; 

they have less negative emotions when learning mathematics, they recognize their abil-

ity to learn mathematics, and have the confidence to learn math well. “Middle” students 

can be aware of their destructive emotions and control them, but will not adjust them; 

they will become anxious because they are worried about not being able to learn math-

ematics and are optimistic about their ability to learn mathematics, but think they need 

to work hard. “Middle and lower” students can perceive their own deficient or exces-

sive emotions, but they cannot control and regulate them well and need help from others. 

They will have negative emotions such as fear and tension when they study mathemat-

ics, and they lack confidence in their math level. “Low-level” students will have defi-

cient or excessive emotions due to learning mathematics, but they can hardly perceive 

and control their emotions and need guidance from others; they have repulsive emotions 

toward math learning and lack positive emotional experience. 

“Attitude” Dimension Norm and Its Grade Evaluation 

Standard 

According to the norm construction method, establish the “attitude” dimension norm 

(table omitted). Secondly, divide the “attitude” dimension horizontally, and then formu-

late the corresponding grade evaluation standard (see Table 4). Finally, calculate the 

average scores of students of different levels in the sub-dimensions of “view of mathe-

matics,” “belief in learning,” and “sense of learning responsibility” under the “attitude” 

dimension (see Figure 3). 

Based on Figure 3, combined with the concept definition and questions of each 

sub-dimension of attitude (Wang & Li, 2020), it is found that students of different lev-

els have the following characteristics: “Excellent” students believe that mathematics is a 

valuable subject; mathematics learning should be systematic and comprehensive, and 

rules and skills need to be summarized in time; learning mathematics must emphasize 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 916 

methods, strive to avoid errors, and always actively complete mathematics tasks with 

quality and quantity. The “Middle and upper” level students have a more objective un-

derstanding of mathematics knowledge and value; they believe that learning mathemat-

ics must know how to summarize the methods that suit them and actively complete 

math learning tasks. “Middle” students can correctly understand mathematics and the 

meaning of learning mathematics, but their learning enthusiasm is average; they think 

that learning mathematics does not require too many skills, and students can complete 

learning tasks but lack initiative. “Middle and lower” students have a somewhat subjec-

tive and one-sided understanding of mathematics knowledge and value; they believe 

that they can learn mathematics by rote and can complete their learning tasks under su-

pervision. “Low-level” students have some deviations in their understanding of mathe-

matics; they think that learning mathematics is meaningless and cannot understand 

mathematics more profoundly, and they think that mathematics learning does not need 

to be methodological and hardly complete the learning tasks actively. 

“Willpower” Dimension Norm and Its Grade Evaluation 

Standard 

According to the norm construction method, establish the dimension norm of “willpow-

er” (table omitted). Secondly, divide the dimension of “willpower” horizontally, and 

then formulate the corresponding grade evaluation standard (see Table 5). Finally, cal-

culate the average scores of students of different levels in the sub-dimensions of “self-

discipline” and “persistence” under the “willpower” dimension (see Figure 4). 

Based on Figure 4, combined with the definition of the concepts and questions 

of the sub-dimensions of willpower (Wang & Li, 2020), it is found that students of dif-

ferent levels have the following characteristics: “Excellent” students can formulate cor-

responding math learning plans and review plans based on their own and can complete 

learning tasks in strict accordance with the plan and review them in time, never give up 

quickly, and have a persevering learning spirit. “Middle and upper” level students are 

able to complete their self-made study plan more seriously, remind themselves to con-

centrate when studying mathematics, maintain a state of listening carefully, and be able 

to persist in studying mathematics. “Middle” students can basically implement their 

mathematics learning plan, and sometimes the plan will fail or appear without conscien-

tiousness; when learning mathematics, they cannot maintain the learning state for a long 

time and occasionally need teacher reminders. “Middle and lower” students will occa-

sionally implement mathematics study plans carefully; they cannot guarantee full ener-

gy, comfortable slack, and lack of perseverance when studying mathematics. “Low-

level” students seldom study and review as planned and hardly make a study plan; they 

tend to get distracted when studying mathematics and tend to give up or escape when 

they encounter learning difficulties. 

“Personality” Dimension Norm and Its Grade Evalua-

tion Standard 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 917 

 

Figure 6. The T-Score Chart of Five Main Dimensions of Non-Intellectual 
Mathematics Learning of the Tested Class. 

 

 

 

According to the norm construction method, establish the “personality” dimension norm 

(table omitted). Secondly, divide the “personality” dimension horizontally, and then 

formulate the corresponding grade evaluation standard (see Table 6). Finally, calculate 

the average scores of students of different levels in the sub-dimensions of “questioning 

spirit” and “competitive spirit” under the “personality” dimension (see Figure 5). 

Based on Figure 5, combined with the definition of the concept of each sub-

dimension of personality and the questions (Wang & Li, 2020), it is found that students 

of different levels have the following characteristics: “Excellent” students are good at 

asking questions; when they are inconsistent with others or books, they dare to question 

teachers or authorities; they are not to be left behind in mathematics learning, strive to 

show themselves, be aggressive, and eager to surpass others. “Middle and upper” stu-

dents, when they are inconsistent with others or books, often have questions, ask ques-

tions, like competition, and hope to surpass other students. “Middle” students can show 

a psychological tendency to surpass others, and occasionally ask questions when their 

views are inconsistent with those of others or books. “Middle and lower” students occa-

sionally have questions when studying mathematics, but they rarely raise doubts; alt-

hough they want to surpass others in mathematics learning, they are not good at ex-

pressing themselves. “Low-level” grade students are not good at expressing their opin-

ions, basically do not ask questions, have no willingness to show, surpass others, and do 

not care about math scores. 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 918 

Application Cases of Norm and Grade Evaluation 

Standard 

Class Application Case 

Non-Intellectual Diagnosis of Mathematics in the Sub-

ject’s Class 

In this study, a total of 44 7th-grade students from Tianjin of China were selected as 

subjects, and 40 valid questionnaires were returned, with an effective rate of 90.9%. 

The 40 students in the class were regarded as a whole, and a comparative analysis with 

the students in the city was carried out to understand the group’s general level of non-

intellectual mathematics learning. The original non-intellectual average score of math-

ematics learning among the subjects was 166.10, which exceeded 42.15% of middle 

school students in Tianjin of China. Comparing it with Table 1, the subjects’ non-

intellectual mathematics learning was at the middle level in Tianjin. The non-

intellectual dimension T scores of the subjects in mathematics learning were: 49.70 

(motivation), 48.67 (emotion), 55.04 (attitude), 49.03 (willpower), 49.80 (personality). 

Starting from the five main dimensions, further diagnosis and analysis of the subject 

class were made. From Figure 6, in the dimension of motivation, the subject’s class 

was equivalent to the “middle” level of middle school students in Tianjin; it was slight-

ly lower than the “middle” level of middle school students in the city in terms of emo-

tion, willpower, and personality; The class of the subjects was significantly higher than 

the “middle” level of the city’s middle school students. 

Suggestions for Improvement of Non-Intellectual Mathe-

matics Learning in the Tested Class 

The analysis shows that the subjects’ non-intellectual math learning is at the “middle” 

level in Tianjin as a whole, and the five main dimensions of motivation, emotion, atti-

tude, willpower, and personality are all at the “middle” level in Tianjin. Overall, the 

students in this class have a strong sense of responsibility for learning and are competi-

tive; their learning anxiety, persistence, and questioning spirit are slightly lower than 

Tianjin’s “middle” level. In mathematics teaching, teachers should enhance students’ 

perception of the intrinsic value and fun of mathematics learning and guide students to 

effectively regulate and monitor their learning activities through positive learning atti-

tudes and emotional experience (Du & Liu, 2017). It is also suggested that the teacher 

make full use of the students’ strong sense of responsibility and competitive spirit. 

Studying mathematics often encounters difficult problems, and some students tend to be 

afraid of difficulties and give up. In response to this kind of phenomenon, on the one 

hand, teachers can provide students with “scaffolding” to reduce the difficulty of the 

problem; on the other hand, they can help students improve their ability to learn math- 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 919 

 

Figure 7. The T-Score Chart of the 13 Sub-Dimensions of Non-Intellectual 
Mathematics Learning of Individual Subjects. 

 

 

 

ematics to achieve the purpose of solving problems. Besides, teachers should also pay 

attention to encouraging students to speak positively, question boldly, and always pay 

attention to students’ psychological state to help students with learning difficulties deal 

with destructive emotions in time. 

Individual Application Cases 

Non-Intellectual Diagnosis of Subject’s Individual Math-

ematics Learning 

After understanding the situation with the tested class’s mathematics teacher and ob-

taining the students’ consent, a tested class student who had studied hard but had not 

satisfactory results was selected as the research object. The non-intellectual dimension 

T scores of the student’s mathematics were: 55.10 (cognitive motivation), 47.60 (exter-

nal motivation), 50.30 (achievement need), 61.60 (emotional stability), 55.60 (learning 

anxiety), 56.90 (sense of learning efficacy), 52.80 (view of mathematics), 59.30 (learn-

ing belief), 58.80 (learning responsibility), 49.80 (self-discipline), 44.70 (persistence), 

54.30 (competitive spirit), 51.60 (questioning spirit). The overall original average score 

of the student’s non-intellectual math learning was 176. According to Table 1, he was 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 920 

at the “middle” level of Tianjin middle school student, and further diagnosis and analy-

sis of each sub-dimension would be continued. 

Figure 7 shows the T scores of the thirteen sub-dimensions of non-intellectual 

mathematics learning. Simultaneously, combined with the data analysis in Table 2 to 

Table 6, this student’s cognitive motivation was significantly higher than the city’s 

“middle” students’ level. The external motivation was slightly lower than the level of 

the city’s “middle” students. Achievement needs to be comparable to the average level 

of the city’s “intermediate” students. The students’ emotional stability, learning anxiety, 

and sense of learning efficacy were significantly higher than the city’s “middle” level 

students but slightly lower than the city’s “middle and upper” level students. The stu-

dents’ learning beliefs and responsibility was slightly lower than the city’s “middle and 

upper” students and significantly higher than the city’s “middle” level students. The 

student’s view of mathematics was slightly higher than the level of the city’s “middle” 

students and lower than the city’s “middle and upper” students. The student’s self-

discipline was slightly lower than the city’s “middle” level students, and its persistence 

was lower than the city’s “middle” level students. The students’ questioning spirit and 

competitive spirit were slightly higher than those of the city’s “middle” level students. 

Suggestions for Non-Intellectual Improvement of Subject’ 

Individual Mathematics Learning 

The non-intellectual level of the student’s mathematics learning is at the “middle” level 

in Tianjin, and the dimensions of motivation, willpower, and personality are all at the 

“middle” level in Tianjin, while the two dimensions of emotion and attitude are at the 

“middle” level in Tianjin. The analysis shows that this student’s external motivation 

sub-dimensions and persistence sub-dimensions need to be further improved. Studies 

have shown that learning motivation can directly affect academic achievement and indi-

rectly affect academic achievement by transforming motivations and learning behavior 

(Gao & Chen, 2017). Therefore, learning motivation can directly or indirectly affect 

students’ mathematics learning performance. So it is necessary to strengthen students’ 

learning motivation for students’ math learning. 

The external motivations of students’ math learning mainly come from schools, 

teachers, and parents. Many schools will commend students with outstanding perfor-

mance or progress, which is an effective way to strengthen students’ external motiva-

tion. In addition, because students’ persistence in learning is affected by many factors, 

teachers and parents can also stimulate their motivation through spiritual rewards. 

When students learn mathematics, teachers and parents should be good at discovering 

students’ progress and shining points and giving timely praise and encouragement to be 

spiritually encouraged and affirmed and then more motivated to learn mathematics. 

Simultaneously, teachers are the guides and collaborators of students, and they have a 

significant influence on students (Gao & Chen, 2017). In the process of mathematics 

learning, teachers should consciously cultivate students’ perseverance character; pay 

attention to the differences between individuals and teach students per their aptitude; 



Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 921 

encourage students to find role models in the class and learn from the students with 

strong willpower around them; thereby creating a good class learning atmosphere. 

Establish a non-intellectual norm for middle school students' math learning, so 

as to facilitate the comparison between different dimensions of non-intellectual factors 

of students’ math learning. After the subjects were tested, some studies only performed 

descriptive statistics and level comparisons of questionnaire scores. It is difficult to use 

the scores of subjects to explain their objective performance level on non-intellectual. 

This research makes up for this deficiency. However, norm research results have certain 

regional and time-sensitive limitations. These research results are based on middle 

school students in Tianjin of China, so they can only be used for reference in Tianjin 

and other areas with similar education levels. With the rapid development of the times, 

the non-intellectual factors of students’ mathematics learning in different periods may 

also undergo group changes. Therefore, the norm and grade evaluation standard estab-

lished by our study need to be updated regularly. 

 

 

 

 

 

 

 

References

Cao, R., Yu, C., & Yu, Y. (2015). Revision and 

preliminary application of the scale of math-

ematics learning attitudes for high school 

students. Journal of Mathematics Education, 

24(6):57-60. [Chinese] 

http://www.cqvip.com/qk/91144x/201506/6

67628101.html  

Du, X., & Liu, J. (2017). Study on the relation-

ship between “mathematics interest,” “math-

ematics self-efficacy,” “learning persistence,” 

and “mathematics achievement” of eighth-

grade students. Journal of Mathematics Ed-

ucation, 26(2):29-34. [Chinese] 

http://www.cnki.com.cn/Article/CJFDTotal-

SXYB201702006.htm  

Gao, H., & Chen, K. (2017). Research status and 

prospects of self-efficacy in mathematics. 

Journal of Mathematics Education, 

26(1):76-81. [Chinese] 

http://www.cnki.com.cn/Article/CJFDTotal-

SXYB201701018.htm  

Lv, S., Fu, M., Sun, M., & Wang, Z. (1995). A 

cross-cultural study on the influence of Ti-

betan and Han students’ intellectual and 

non-intellectual factors on mathematical 

ability development. Educational Research, 

1995, 2(1):70-74. [Chinese] 

http://www.cqvip.com/qk/96925x/199501/1

003278659.html  

Wang, G., & Li, S. (2020). Compilation of a 

questionnaire on non-intellectual factors in 

mathematics learning for junior high school 

students. Journal of Mathematics Education, 

29(1):29-39. [Chinese] 

http://www.cqvip.com/qk/91144x/202001/7

100993971.html  

Wang, G., & Yang, R. (2015). Research on Psy-

chological Factors of Minority Mathematics 

Learning Based on NVivo10 Qualitative 

Analysis. Journal of Research on Education 

for Ethnic Minorities, 26(1):81-84. [Chinese] 

DOI: https://doi.org/10.15946/j.cnki.1001-

7178.2015.01.014  

http://www.cqvip.com/qk/91144x/201506/667628101.html
http://www.cqvip.com/qk/91144x/201506/667628101.html
http://www.cnki.com.cn/Article/CJFDTotal-SXYB201702006.htm
http://www.cnki.com.cn/Article/CJFDTotal-SXYB201702006.htm
http://www.cnki.com.cn/Article/CJFDTotal-SXYB201701018.htm
http://www.cnki.com.cn/Article/CJFDTotal-SXYB201701018.htm
http://www.cqvip.com/qk/96925x/199501/1003278659.html
http://www.cqvip.com/qk/96925x/199501/1003278659.html
http://www.cqvip.com/qk/91144x/202001/7100993971.html
http://www.cqvip.com/qk/91144x/202001/7100993971.html
https://doi.org/10.15946/j.cnki.1001-7178.2015.01.014
https://doi.org/10.15946/j.cnki.1001-7178.2015.01.014


Wang et al. Non-Intellectual Norm of Middle School Students’ Mathematics Learning. 

Vol.7, No. 1, 2021 922 

Wang, G., Liu, X., & Li, J. (2017). Research on 

the Norm of High School Students’ Mathe-

matical Learning Non-intellectual Features 

and Their Level Standards: Taking Tianjin 

as an example. Journal of Tianjin Normal 

University (Elementary Education Edition), 

18(3):50-59. [Chinese] DOI: 

https://doi.org/10.16826/j.cnki.1009-

7228.2017.03.011  

Wang, G., She, W., & Song, J. (2014). High-

efficiency mathematics learning mental 

structure model based on NVivo10 qualita-

tive analysis. Studies of Psychology and Be-

havior, 12(1):74-79. [Chinese] 

http://www.cqvip.com/qk/87994x/201401/4

8585961.html  

Wang, G., Song, J., & Wang, Z. (2015). Devel-

opment of a questionnaire on non-

intelligence characteristics of high school 

students’ mathematics learning. Journal of 

Mathematics Education, 24(3):17-27. [Chi-

nese] 

https://www.airitilibrary.com/Publication/al

DetailedMesh?docid=sxjyxb201503004  

Wang, Y. (2004). Non-intellectual factors and 

students’ mathematics learning. Journal of 

Chengdu Normal University, 20(12):84-86. 

[Chinese] DOI: 

https://doi.org/10.3969/j.issn.1000-

5757.2004.12.041  

Yang, H., Liu, D., & Yang, R. (2015). The rela-

tionship between learning interest, self-

efficacy, learning strategy, and performance: 

A study on junior high school mathematics 

learning based on Kolb learning style. Edu-

cational Science Research, 26(10): 52-57. 

[Chinese] 

http://www.cqvip.com/qk/83877x/201510/6

66377515.html  

Zhang, G. (2012). Higher mathematics teaching 

should pay attention to the cultivation of 

students’ non-intelligence factors. Educa-

tional Exploration, 23(4):66-67. [Chinese] 

DOI: https://doi.org/10.3969/j.issn.1002-

0845.2012.04.027 

Received: 25 December 2020 

Revised: 11 January 2021 

Accepted: 20 January 2021 

 

 

The Chinese version of this article has been published in Theory and Practice of Education 2020, 

40(20):44-48. The English version has been authorized for being publication in BECE by the author(s) 

and the Chinese journal. 

王光明, 李健, 简婧娴. (2020). 初中生数学学习非智力水平常模及其等级评价标准研究: 以天津市
为例 . 教育理论与实践, 40(20):44-48. 

 

https://doi.org/10.16826/j.cnki.1009-7228.2017.03.011
https://doi.org/10.16826/j.cnki.1009-7228.2017.03.011
http://www.cqvip.com/qk/87994x/201401/48585961.html
http://www.cqvip.com/qk/87994x/201401/48585961.html
https://www.airitilibrary.com/Publication/alDetailedMesh?docid=sxjyxb201503004
https://www.airitilibrary.com/Publication/alDetailedMesh?docid=sxjyxb201503004
https://doi.org/10.3969/j.issn.1000-5757.2004.12.041
https://doi.org/10.3969/j.issn.1000-5757.2004.12.041
http://www.cqvip.com/qk/83877x/201510/666377515.html
http://www.cqvip.com/qk/83877x/201510/666377515.html
https://doi.org/10.3969/j.issn.1002-0845.2012.04.027
https://doi.org/10.3969/j.issn.1002-0845.2012.04.027

	Article-GuangmingWang-BECE_title_29Jan2021
	Article-GuangmingWang-BECE_Maintext29Jan2021

