• 沒有找到結果。

This study has conducted analyses to examine the issue of whether any gender and location differences exist in students’ mathematics achievement using Item Response Theory and test statistics method. Performance comparisons among males and females, and students from urban and rural schools were made for sample of 482 7TH graders in Mongolia.

According to the first objective of the study there was no significant gender difference in mathematics achievement among Mongolian 8th graders. However, it had small difference favoring boys. This finding supports the findings of several previous studies which carried out by Fierros, (1999), Zhang and Manon (2000) and Johnson (2000) and Erickan, McCreith, and Lapointe, (2005). Interestingly, Examining differences by content area reveals males scored higher on average than females in all mathematics content areas (algebra, arithmetic, proportionality and probability and statistics) with the exception of geometry in which female students scored higher. This finding is exactly parallel to the study carried out by Catherine T.Amelink (2009).

Hence, we may conclude that girls have better geometric ability than boys.

To the second objective, research has also found there is a statistically significant difference in math achievement between students from rural and urban schools. This is parallel to the findings of Lindberg and Wilson (1985), and Raul Ramos and his colleagues (2012) and Jennifer Lawless (2009) which say that students from small rural schools performed worse than those attending large urban schools. This might be caused of several reasons as follow. Firstly, it is due to the distance and environment problem. Five rural schools were sampled in this study 3 of those are located over 1000 km far away from the urban area. Some evidence say that the support from the state and federal recourse come to the rural schools slowly. Therefore children from rural area still need to do house chores and help out on the farm and take care of the domestic animals. Moreover, rural schools have lack of classroom equipments and latest trend in technology compare to urban schools. For example: Students from urban schools have greater access to many resources and therefore have opportunities that

are not as easily accessible to rural students (Jennifer Lawless). Secondly, rural schools might be short of qualified teachers.

Surprisingly, in some rural schools, one teacher provides 2-3 different classes at the same time which means rural schools have lack of number of professional teachers for particular subjects.

To the third objective, Mongolian math items had higher item difficulty index versus TIMSS mathematics items for 8TH grade. However, the hardest item was found among TIMSS items. Furthermore, Mongolian students haven’t been experienced in PISA or TIMSS yet. So, it could be a signal that claims Mongolia should participate in TIMMS or PISA to evaluate its national curriculum on several particular subjects comparing other participating countries’ experience.

According to the item analysis results from the five content categories that measured students’ levels of mathematics knowledge. While 77.7% of students answered the statistics and probability items correctly, only 54.4% answered the geometry items correctly and 63.8% answered the proportionality items correctly.

Moreover only 52.8% answered the algebra items correctly and 64.3% answered the arithmetic items correctly. Furthermore 45.8% or 221 of students answered less than 18 items correctly and, only one student answered all 30 items correctly. According to frequency table (Table) 38.1% or 184 of students answered 18-23 items correctly and while 13.7% or 28 of students answered 24-26 items correctly. Therefore, mean mathematics ability of the 7th graders is -0.021 which is very low, while all students’

ability was found between 2.665 and -2.043. Hence, we conclude in any case, the low correct response rates, particularly to the geometry and algebra items, indicated that many 7th graders lack knowledge of basic mathematics concept.

Based on these findings, several future paths of research are opened up. Firstly, present study supports a hypothesis that girls may perform on geometry better than boys. So this result encourages us to investigate what factors could possibly be strong predictor of girls’ knowledge of geometry which makes them perform better than boys.

Secondly, however, such studies will require larger database regarding the information needed to capture the characteristics of the areas in which the students are resident.

This kind of data would enable us to investigate which geographical location or environment can have an impact on student’s educational outcomes and what standard

demographic characteristics such as gender, ethnicity, and family background could possibly be strong predictor of mathematics ability. In this respect, it is important to develop new ways to assess the impact of mathematical education on the young.

References

Ainara Gonzalez de San Roman & Sara de la Rica (2010). The Impact of Social norms and the Mother’s transmission of role attitudes.

Alspaugh, J. W. (1992). Socioeconomic measures and achievement: Urban vs. rural.

Rural Educator, 13, 2-7.

Alspaugh, J.W., & Harting, R.D. (1995). Transition effects of school grade-level organization on student achievement. Journal of Research and Development in Education, 28, 145-149.

Beaton, A.E.; Mullis,I.V.; Martin,M.O.; Gonzales , E.J.; Kelly, D.L.; Smith, T.A.

(1996). Mathematics achievement in the middle school years: IEA’s Third International Mathematics and Science Study. Boston: TIMSS International study Center Boston College

Bock, R. D. (1997). A brief history of item response theory. Educational Measurement:

Issues and Practice, 16, 21-33.

Bock, R. D., & Aitkin, M. (1981). Marginal maximum likelihood estimation of item parameters: application of an EM algorithm. Psychometrika, 46, 443-459.

Christina Stage (2000). Predicting Gender Differences in WORD Items:

A Comparison of Item Response Theory and Classical Test Theory.

Chrostowski, S. J., & Smith, T. A. (2000). TIMSS 1999 international mathematics report: Findings from IEA‘s Repeat of the Third International Mathematics and Science Study at the eighth grade. Chestnut Hill, MA: Boston College.

C. Howley, Research About Mathematics Achievement in the Rural Circumstance.

(Athens, OH: Ohio University, Appalachian Collaborative Center for the Study of Learning, Assessment, and Instruction in Mathematics, 2002), available at

http://acclaim.coe.ohiou.edu/rc/rc_sub/pub/3_wp/CBH_WP1.pdf).

Coe, P., Howley, C. B., & Hughes, M. (1989a). The condition of rural education in Kentucky: A profile. Charleston, WV: Appalachia Educational Laboratory. (ERIC Document Reproduction Service No. ED 319 579)

Coe, P., Howley, C. B., & Hughes, M. (1989b). The condition of rural education in Virginia: A profile. Charleston, WV: Appalachia Educational Laboratory. (ERIC Document Reproduction Service No. ED 319 577)

Ercikan, K.; McCreith, T. and Lapointe, V. (2005). Factors associated with

mathematics achievement and participation in advanced mathematics courses:

An examination of gender differences from an international perspective. School Science and Mathematics v105 n1 p5.

Edington, E.D. (1981). ACT scores of incoming freshmen to New Mexico State University by high school size. (ERIC Document Reproduction Service No.

ED 272354).

E. Bouck, How Size and Setting Impact Education in Rural Schools. Rural Educator, vol. 25, no.3 (2004): 38-42.

Fierros, E.G. (1999). Examining Gender Differences in Mathematics Achievement on the Third International Mathematics and Science Study (TIMSS).

Gila Hanna & Toronto (2000). Declining Gender Difference from FIMS to TIMSS.

Guiso, L., Monte, F., Sapienza, P. & Zingales, L. (2008). Culture, Gender and Math.

Science, 320(5880): 1164-1165.

Haller, E. J., Monk, D. H., & Tien, L.T. (1993). Small schools and higher order thinking skills. Journal of Research in Rural Education,

Johnson, R. M. (2000). Gender Differences in Mathematics Performance: Walberg’s Educational Productivity Model and the NELS: 88 Database.

J.Serrita Jane, Thomas F.Oltmanns & Susan C. South, Eric Turkheimer (2007).

Journal of Abnormal Psychology, Vol. 116, No. 1, 106-175

Khattri, N., Riley, K. W., & Kane, M. B. (1997). Students at risk in poor, rural areas: Journal of Research in Rural Education, 13, 79-100.

Lawless, J. (2009). Advantages and Disadvantages of Attending Rural and Urban Middle Schools.

Linden, W. J., & Hambleton, R. K. (Eds.) (1997). Handbook of modern item response theory. New York, NY: Springer-Verlag.

Mellenbergh, G.J. (1994). A unidimensional latent trait model for continuous item responses. Multivariate Behavioral Research, 29, 223-236.

Mullis, I. V. S., Martin, M.O., Fierros, E.G., Goldberg, A. L., & Stemler, S. E. (2000).

Gender differences in achievement: IEA’s Third International Mathematics and Science Study (TIMSS). Chestnut Hill, MA: Boston College.

Mullis, I. V. S., Martin, M. O., Gonzalez, E. J., & Chrostowski, S. J. (2004). TIMSS 2003 international mathematics report: Finding from IEA’s Trends in

International Mathematics and Science Study at the fourth and eighth grades.

Chestnut Hill, MA: Boston College.

Ou Lydia Liu, Mark Wilson. (2008). A Multidimensional Rasch Analysis of Gender Differences in PISA Mathematics. Journal of Applied Measurement, (1), 18-35 Rasch, G (1960). Probabilistic models for some intelligence and attainment tests.

Chicago: MESA.

Stevenson, H. W., Chen, C., & Booth, J. (1990). Influence of schooling and urban-rural residence on gender differences in cognitive abilities and academic achievement.

Sunha Kim & Mido Chang (2010). Computer games for the Math Achievement of Diverse Students. Educational Technology & Society, 13 (3), 224-232

TIMSS (2000). Gender differences in achievement TIMSS. (2000).

TIMSS (2007). International Students Achievement in Mathematics. (2007).

TIMSS (2008). International Students Achievement in Advanced Mathematics (2008).

TIMSS (2011), Trends in International Mathematics and Science Study Encyclopedia- 2011.

Thissen, D & Steinberg, L. (1988). Data analysis using item response theory.

Psychological Bulletin, 104, 385-395.

Thissen, D. & Orlando, M. (2001). Chapter 3- Item response theory for items scored in two categories. In D.Thissen & H.Wainer (Eds.), Test Scoring. Hillsdale, NJ:

Erlbaum.

Tinsley, H.E.A. (1992). Psychometric theory and counceling psychology research. In S.D.Brown & R.W.Lent (Eds.), Handbook of counseling psychology (2nd ed., pp.

37-70), New York, NY: Wiley.

Thompson, T., & Dinnel, D. L. (2007). Poor performance in Mathematics.

Educational Psychology, 27,377-399.

Wright, B.D. (1997). A history of social science measurement. Educational Measurement: Issue and Practice, 16, 21-33.

Xitao Fan & Micheal J.Chen (1999). Academic achievement of rural school students:

A Multi-year comparison with their peers in suburban and urban schools.

Journal of Research in Rural Education, Spring, 1999, Vol. 15, No, 1, 31-46 Young, D. J. (1998). Rural and Urban Differences in Student Achievement in Science

and Mathematics: A Multilevel Analysis. School Effectiveness and School Improvement, 9(4), 386-412.

Zhang, L. and Manon, J. (2000). Gender and Achievement—Understanding Gender Differences and Similarities in Mathematics Assessment.

Zhang, L. and Lee, K.A., 2011. Decomposing achievement gaps among OECD countries. Asia Pacific Education Review 12 (3), pp. 463-474.

Appendix “A”

Table 9: Test reliability

Test information Number of items Number of students Reliability

Mathematics 30 482 0.779

Table 10: Each item’s reliability

Item Reliability Item Reliability

1 0.777 16 0.775

2 0.779 17 0.784

3 0.773 18 0.774

4 0.789 19 0.768

5 0.780 20 0.772

6 0.782 21 0.768

7 0.772 22 0.780

8 0.775 23 0.786

9 0.767 24 0.768

10 0.769 25 0.767

11 0.768 26 0.768

12 0.771 27 0.765

13 0.774 28 0.770

14 0.773 29 0.774

15 0.765 30 0.771

Table 11: Score frequency

Appendix “B”

Item 1

Two groups of tourists each have 60 people. If of the first group and of the second group board buses to travel to a museum, how many more people in the first group board buses than in the second group?

A. 2 B. 4 C. 5 D. 45 IRT

parameters

a b c PIRT

0.679 0.199 0.320 0.628

Options analysis

Options Total

Number of students

57 104 305 15 482

Percentage

11.82% 21.57% 63.27% 3.11% 100.00%

Figure 3

Item 2

In a discuss-throwing competition, the winning throw was 61. 60 m. The second –place throw was 59.72 m. How much longer was the winning throw than the second-place throw?

A. 1.18 m B. 1. 88 m C. 1. 98 m D. 2.18 m

IRT parameters

a b c PIRT

0.447 -2.585 0.283 0.898

Options analysis

Options Total

Number of

students 16 433 24 9 482

Percentage

3.31% 89.83% 4.97% 1.86% 100.00%

Figure 4

Item 3

In a bag of cards are green are yellow are white and are blue. If someone takes a card from the bag without looking, which color is it most likely to be?

A. White B. Blue C. Green D. Yellow IRT

parameters

a b c PIRT

0.729 -0.393 0.343 0.733

Options analysis

Options Total

Number of

students 355 15 17 94 482

Percentage 73.65% 3.11% 3.52% 19.50% 100.00%

Figure 5

Item 4 1. What is the size of angle ACD?

A. 44 B. 126 C. 136 D. 150 IRT

parameters

a b c PIRT

0.685 2.972 0.347 0.377

Options analysis

Options Total

Number of students

251 28 182 19 482

Percentage 52.07% 5.80% 3.77% 3.94% 100.00%

Figure 6

Item 5

Which of the following are most likely to be the coordinates of point P?

A. (8, 12) B. (8, 8) C. (12, 8) D. (12, 12) IRT

parameters

a b c PIRT

0.379 0.960 0.322 0.566

Option analysis

Options Total

Number of students

274 29 155 24 482

Percentage 57.1% 6.01% 32.15% 4.97% 100.00%

Figure 7

Item 6 The table represents a relation between x and y.

x y

1 1

2 ?

4 7

7 14

What is the missing number in the table?

A. 2 B. 3 C. 4 D. 5 IRT

parameters

a b c PIRT

0.954 1.840 0.285 0.353

Option analysis

Options Total

Number of

students 109 174 157 42 482

Percentage 22.61% 36.1% 32.57% 8.71% 100.00%

Figure 8

Item 7

The length of a rectangle is 6 cm, and its perimeter is 16 cm. What is the area of the rectangle in square centimeters?

A. 12 B. 22 C. 24 D. 48 IRT

parameters

a b c PIRT

0.863 -1.104 0.236 0.823

Option analysis

Options Total

Number of

students 395 39 25 22 482

Percentage 81.95% 8.09% 5.18% 4.56% 100.00%

Figure 9

Item 8 >7 is equivalent to

A. x< B. x> C. x>14 D. x<14 IRT

parameters

a b c PIRT

0.840 0.840 0.380 0.559

Option analysis

Options Total

Number of

students 52 104 274 52 482

Percentage 10.78% 21.57% 56.84% 10.78% 100.00%

Figure 10

Item 9

Last year there were 1172 students at Beaton High School. This year there are 15 percent more students than last year. Approximately how many students are at Beaton High School this year?

A. 1800 B. 1600 C. 1500 D. 1400 IRT

parameters

a b c PIRT

0.814 -0.279 0.184 0.650

Option analysis

Options Total

Number of

students 68 66 36 312 482

Percentage 14.10% 13.69% 7.46% 64.73% 100.00%

Figure 11

Item 10 The table shows a relation between x and y.

x 2 3 4 5

y 7 10 13 16

Which of these equations express this relation?

A. y=x+5 B. y= (x+1) C. y=x-5 D. y=3x+1

IRT parameters

a b c PIRT

0.836 0.228 0.228 0.575

Option analysis

Options Total

Number of

students 91 67 44 280 482

Percentage 18.87% 13.90% 9.12% 58.09% 100.00%

Figure 12

Item 11

A class has 28 students. The ratio of girls to boy is 4:3. How many girls are in the class?

A. 13 B. 14 C. 15 D. 16 IRT

parameters

a b c PIRT

0.960 0.305 0.275 0.567

Option analysis

Options Total

Number of

students 77 70 59 279 482

Percentage 15.97% 14.52% 12.24% 57.88% 100.00%

Figure 13

Item 12

A newspaper reported that about 18200 trees had been planted in the park. The number was rounded to the nearest hundred. Which of these could have been the actual number of trees planted?

A. 18043 B. 18189 C. 18289 D. 18328 IRT

parameters

a b c PIRT

0.852 -0.432 0.301 0.728

Option analysis

Options Total

Number of

students 60 352 46 23 482

Percentage 12.44% 73.02% 9.54% 4.77% 100.00%

Figure 14

Item 13

“n” is a number. When n is multiplied by 7, and 6 is then added, the result is 41. Which of these equations represents this relation?

A. 7n+6=41 B. 7n x 6=41 C. 7+(6n)=41 D. 7(n+6)=41 IRT

parameters

a b c PIRT

0.690 -1.070 0.287 0.810

Option analysis

Options Total

Number of students

389 42 34 17 482

Percentage 80.70% 8.71% 7.05% 3.52% 100.00%

Figure 15

Item 14

A drawer contains 28 pens; some white, some blue, some red, and some gray.

If the probability of selecting a blue pen is , how many blue pens are in the drawer?

A. 4 B. 6 C. 8 D. 10 IRT

parameters

a b c PIRT

0.659 -1.200 0.287 0.822

Option analysis

Options Total

Number of

students 28 42 396 16 482

Percentage 5.80% 8.71% 82.15% 3.31% 100.00%

Figure 16

Item 15

Which of these expressions is equivalent to y3?

A. y+y+y B. y x y x y C. 3y D. y2+y IRT

parameters

a b c PIRT

1.139 -0.724 0.172 0.758

Option analysis

Options Total

Number of

students 58 363 32 29 482

Percentage 12.03% 75.31% 6.63% 6.01% 100.00%

Figure 17

Item 16 Please simplify the expression.

5(a+2)+(a+2)

A. 6a+12 B. 10+5a C. 6(a+2) D. a2+5a+12 IRT

parameters

a b c PIRT

1.029 1.681 0.116 0.210

Option analysis

Options Total

Number of

students 249 72 103 58 482

Percentage 51.65% 14.93% 21.36% 12.03% 100.00%

Figure 18

Item 17 Please simplify the expression.

2x (x+1)-4x(2-x)

A. 6x2-6x B. x2 C. 6x(x-1) D. 6x IRT

parameters

a b c PIRT

1.709 2.044 0.155 0.180

Option analysis

Options Total

Number of

students 336 43 89 14 482

Percentage 69.70% 8.92% 18.46% 2.90% 100.00%

Figure 19

Item 18 Please find the correct.

c4 x □ = c12

A. c3 B. c8 C. c48 D. c412 IRT

parameters

a b c PIRT

0.626 -0.189 0.304 0.680

Option analysis

Options Total

Number of

students 122 329 20 11 482

Percentage 25.41% 68.25% 4.14% 2.28% 100.00%

Figure 20

Item 19 Please quadrate using a suitable formula.

(x+5)2

A. 2x +10 B. x+25 C. x2+25 D. x2+10x+25 IRT

parameters

a b c PIRT

1.007 0.080 0.219 0.591

Option analysis

Options Total

Number of

students 61 37 99 285 482

Percentage 12.65% 7.67% 20.53% 58.28% 100.00%

Figure 21

Item 20 Please simplify the fraction.

ab + a2 a2

A. ab B. C. ab +a4 D. a3b+a2 IRT

parameters

a b c PIRT

1.428 1.208 0.181 0.306

Option analysis

Options Total

Number of

students 246 150 59 27 482

Percentage 51.03% 31.12% 12.24% 5.60% 100.00%

Figure 22

Item 21

Two photographers took 657 photos in total. One photographer took 63 more photos than another. How many photos did each photographer take?

A. 360 and 297 B. 345 and 408 C. 247 and 410 D. 307 and 350 IRT

parameters

a b c PIRT

1.051 -0.335 0.250 0.697

Option analysis

Options Total

Number of

students 336 76 53 17 482

Percentage 69.70% 15.76% 10.99% 35.26% 100.00%

Figure 23

Item 22 Please find c.

A. c=5 B. c=25 C. c=31 D. c=√527 IRT

parameters

a b c PIRT

0.463 1.878 0.256 0.410

Option analysis

Options Total

Number of

students 49 199 188 46 482

Percentage 10.16% 41.28% 39.00% 9.54% 100.00%

Figure 24

Item 23 Please compute the inequality.

% x>-1

A. x>

-% B. x>9 C. x> - 9 D. x< 9 IRT

parameters

a b c PIRT

1.279 2.243 0.395 0.414

Option analysis

Options Total

Number of

students 153 85 205 39 482

Percentage 31.74% 17.63% 42.53% 8.09% 100.00%

Figure 25

Item 24

What value of “x” makes the following equation true?

& = 9

A. 1 B. 5 C. 12 D. 24 IRT

parameters

a b c PIRT

1.461 -0.696 0.300 0.802

Option analysis

Options Total

Number of

students 34 42 387 19 482

Percentage 7.05% 8.71% 80.29% 3.94% 100.00%

Figure 26

Item 25

Please find equivalent of following expression: 9a2+6ab+b2 A. (9a+b)2 B. (3a2+b2)2 C. (3a+b)2 D. (3a+b)(3a-b) IRT

parameters

a b c PIRT

1.021 -0.307 0.219 0.677

Option analysis

Options Total

Number of

students 68 38 326 50 482

Percentage 14.10% 7.88% 67.63% 10.37% 100.00%

Figure 27

Item 26 What is 30 % of 185=?

A. 5.55 B. 55.5 C. 555 D. 5.55.

IRT parameters

a b c PIRT

1.636 -0.313 0.297 0.721

Option analysis

Options Total

Number of

students 69 349 37 27 482

Percentage 14.31% 72.40% 7.67% 5.60% 100.00%

Figure 28

Item 27 Please calculate following expression.

4( :)(= ?

A. ) B. 7 C. ( ) D. 12 IRT

parameters

a b c PIRT

2.177 -0.449 0.261 0.744

Option analysis

Options Total

Number of

students 57 360 53 12 482

Percentage 11.82% 74.68% 10.99% 2.48% 100.00%

Figure 29

Item 28

A bakery made 350 cupcakes. They sold 280 of those cupcakes. What percentage of the cupcakes did they sell?

A. 20% B. 70% C. 80% D. 125%

IRT parameters

a b c PIRT

0.750 -0.449 0.216 0.693

Option analysis

Options Total

Number of

students 34 96 333 19 482

Percentage 7.05% 19.91% 69.08% 3.94% 100.00%

Figure 30

Item 29 Please find the largest one.

A. B. 0.21 C. D.

IRT parameters

a b c PIRT

0.800 1.913 0.133 0.229

Option analysis

Options Total

Number of

students 238 88 110 46 482

Percentage 49.37% 18.25% 22.82% 9.54% 100.00%

Figure 31

Item 30 Please find the correct one.

A. 23 x 27=221

C. 23 x 27=210 B. 23 x 27=410

D. 23 x 27=237 IRT

parameters

a b c PIRT

0.687 0.106 0.189 0.573

Option analysis

Options Total

Number of

students 64 135 276 7 482

Percentage 13.27% 28.00% 57.26% 1.45% 100.00%

Figure 32

相關文件