探討適性U-learning數學步道對不同學習風格學生數學學習成效及學習態度之影響－ 以國小五年級面積單元為例

U-learning

ii U-learning U-learning U-learning U-learning U-learning 29 27 1. 2. 3. 4. 5. a. U-learning

iv

Abstract

The effect of adaptive U-learning mathematics path for

different learning style students - using Area unit in the fifth

grade as an example

Abstract

The purposes of this research are probing into the adaptive U-learning mathematics path and traditional teaching about the teaching effect of applying to the fifth grade mathematics course. In order to achieve the goal of studying, the researcher is based on knowledge structure to construct “the adaptive U-learning mathematics path system“ combining ubiquitous learning in mathematics situation with the computerized adaptive diagnostic test and adaptive remedial learning. The teaching designs are including the self-edited teaching material, the self-edited remedial material, and the self-edited teaching and remedial multimedia material. As for assessment, it is the self-edited computerized adaptive test. Finally, the researcher conducts the adaptive U-learning mathematics path and traditional teaching to discuss the effects of learning and remedial instruction for different learning style students. Furthermore, the research also evaluates the effect of the adaptive U-learning mathematics path and the attitude towards learning mathematics.

The methodology of this study is the nonequivalent quasi-experimental design. The subjects are fifth grade students from one elementary school in Taichung City. It is to assign two classes; one is the experimental group to be taught with the model of adaptive U-learning mathematics path instruction (29 students). The other one is the control group to be taught with traditional instruction (27 students).

The results of this study show as follows:

1. There are insignificant differences shown in the learning achievement of the experimental group and the control group with different learning styles, but be significant differences shown with different learning model. The average score of the

experimental group is better than the control group.

2. There are insignificant differences shown in the remedial achievement of the experimental group and the control group with different learning styles, but be significant differences shown with different remedial model. The average score of the experimental group is better than the control group.

3. There are insignificant differences shown in the mathematics learning attitude of the experimental group and the control group with different learning styles, but be significant differences shown with different learning and remedial model. The average score of the experimental group is better than the control group.

4. There are not significant differences shown in the follow up effects of the experimental group and the control group with different learning styles, neither be significant differences shown with different learning and remedial model. However the average score of the experimental group is better than the control group. 5. As for the students of the experimental group:

a. There are significant differences shown in the learning achievement of high, medium, and low ability students in the experimental group.

b. There are significant differences shown in the remedial achievement of medium and low ability students in the experimental group, not the high ones.

Key words: U-learning, mathematics path, computerized adaptive diagnosis test, area, learning style, mathematics learning attitude

vi ... 1 ... 1 ... 5 ... 7 ... 9 ... 13 ... 15 ... 15 ... 25 ... 31 ... 37 ... 41 ... 41 ... 45 ... 47 ... 51 ... 65 ... 75 ... 77 ... 77 .. 83 .. 89 .. 95 ... 101 ... 103 ... 103 ... 105 ... 108 ...115 ...116 ...118 ...119 OT ... 120 ... 121 ... 125 ... 127 ... 142

2-1-1 ...16 2-1-2 ...20 2-1-2 ( ) ...21 2-1-2 ( ) ...22 2-1-2 ( ) ...23 2-3-1 ...32 3-4-1 ...53 3-4-2 ...54 3-5-1 ...68 4-1-1 ...77 4-1-2 .78 4-1-3 .79 4-1-4 ...79 4-1-5 ...80 4-1-6 ...80 4-1-7 ...81 4-1-8 ...81 4-1-9 ...82 4-2-1 ...84 4-2-2 ...85 4-2-3 .85 4-2-4 ...86 4-2-5 ...86 4-2-6 ...87 4-2-7 ...87

viii 4-2-8 ...87 4-2-9 ...88 4-3-1 ...89 4-3-2 .90 4-3-3 .91 4-3-4 ...91 4-3-5 ...92 4-3-6 ...92 4-3-7 ...93 4-3-8 ...93 4-3-9 ...93 4-4-1 ...95 4-4-2 .96 4-4-3 .96 4-4-4 ...97 4-4-5 ...97 4-4-6 ...98 4-4-7 ...98 4-4-8 ...98 4-4-9 ...99 4-5-1 U-learning t ...101 4-5-2 U-learning t ...102

3-1-1 ...42 3-1-2 ...43 3-3-1 ...48 3-4-1 ...51 3-4-2 ...55 3-4-3 ...56 3-4-4 ...56 3-4-5 - ...57 3-4-6 ...58 3-4-7 ...58 3-4-8 ...59 3-4-9 ...59 3-4-10 ...60 3-4-11 ...60 3-4-12 ...61 3-4-13 ...61 3-4-14 ...62 3-4-15 ...62 3-4-16 ...63 3-4-17 ...63 3-5-1 U-learning ...66

2003

ubiquitous learning, U-learning

……

situated learning 2002 2005 1. 2. 3. 4. 2005 2006 2007 2007 U-learning E-learning 2009 2009 2009 U-learning U-learning

U-learning

U-learning

wireless lan radio frequency

identification, RFID RFID

tag reader

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2005

2006 1999 ATI aptitude treatment interaction

U-learning

knowledge structure based adaptive testing, KSAT 2008

U-learning U-learning

2003 5-n-16 5-s-05 5-a-04 U-learning KSAT 2003 2004 2005 2005 KSAT U-learning U-learning U-learning U-learning

1-1 1-2 1-3 2-1 2-2 2-3 3-1 3-2 3-3 4-1 4-2 4-3 U-learning

5-1 U-learning

2003 5-n-16 5-s-05 5-a-04 1987 1996

2000 1995

-

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2007

knowledge structure based adaptive testing, KSAT

2009

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2003 5-n-16 5-s-05 5-a-04 1. 56 49 2. 3.

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2. 3. 4. 2003

1997 1995a 1998

1. 1995a 2. 1995a 1995b 1998 1. 2. 3.

1995 Piaget et al.(1960) (Hall,1984) Hildreth(1980) chunking squeezing rearrange 1995b

1991

1996 1989 2-1-2 2-1-2 Herstein(1981) Kouba et al(1988) 1. 2. Woodward and Byrd(1983)

1992 1996 1. 2. 3. 4. 5.

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2000 2000 …… 1998 2000 2002 1998

1. 2. 3. 4. 1995 Piaget stage of concrete operations …… Bruner Bruner, 1960 1985 John Dewey facilitator 1998

1985

constructivist cognition

situated context (Brown, Collins,

& Duguid, 1989) person-plus-the-surround (Brown, et al., 1989) Brown 1989 2001 1990 1995 1998

1994 1995

computer aided learning,

CAL E-learning M-learning

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tablet PC

web pad PDA

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mobile web access (Chen & Kotz, 2000; Yang, et al., 2005)

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Laerhoven, 2001; Dey & Abowd, 2000) context

information

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2005 Ubiquitous U-learning (Bekkestua, 2003) 2005 U-learning U-learning U-learning U-learning U-learning U-learning

U-learning U-learning U-learning U-learning 2003 U-learning Sharples(2000)

Weiser(1991) ubiquitous computing

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IR bluetooth

wireless lan radio frequency identification,

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2005

2006

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1. 2. 0.5 3 1. 2. U-learning KSAT 2 KSAT 1 3-4-2 1. 5-n-16 5-s-05 5-a-04 1. 2. 3. 4. 5. 6. 1.5

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Microsoft Excel Microsoft Windows Apple Macintosh

……

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U-learning

1.1

U-learning SPSS α _{0.05 4-1-1 4-1-2 4-1-3} 4-1-1 : III F 259.009 1 259.009 1.430 .239 437.886 2 218.943 1.209 .310 5000.554 1 5000.554 27.609 .000 * _{178.754 2 89.377 .493 .614} * _{344.236 2 172.118 .950 .396} * _{40.034 1 40.034 .221 .641}

III F * * 74.788 2 37.394 .206 .814 6882.680 38 181.123 246027.000 50 21442.980 49 a. R = .679 R = .586 4-1-1 F .950 p .396 .05 F .221 p .641 .05 F .206 p .814 .05 4-1-2 : 71.8000 17.45566 5 68.6000 19.97332 10 77.6000 23.08535 10 U-learning 72.8400 20.43012 25 63.0000 21.41650 7 69.3000 17.08833 10 49.5000 19.19077 8 61.2000 20.13703 25

4-1-3 : III F 10205.130 1 10205.130 59.634 .000 1656.876 1 1656.876 9.682 .003 391.070 2 195.535 1.143 .328 * _{431.990 2 215.995 1.262 .293} 7358.570 43 171.130 246027.000 50 21442.980 49 a. R = .657 R = .609 4-1-3 F 1.262 p=.293 .05

1.2

4-1-3 4-1-4 : 66.6667 19.53241 12 68.9500 18.09471 20 65.1111 25.30261 18 67.0200 20.91917 50

4-1-5 : III F 12000.809 1 12000.809 59.355 .000 218.780 2 109.390 .541 .586 9300.585 46 202.187 246027.000 50 21442.980 49 a R = .566 R = .538 4-1-5 F .541 p .586 .05 4-1-6 95% 69.135 a 4.117 60.848 77.423 68.229 a 3.181 61.826 74.632 64.266 a 3.353 57.517 71.016 a = 48.9400. 4-1-6

1.3

4-1-7 : U-learning 72.8400 20.43012 25 61.2000 20.13703 25 67.0200 20.91917 50 4-1-8 : III F 11621.485 1 11621.485 67.202 .000 1391.490 1 1391.490 8.046 .007 8127.875 47 172.934 246027.000 50 21442.980 49 a R = .621 R = .605 4-1-8 F 8.046 p .007 .05

4-1-9 95% U-learning _{72.299 a 2.631 67.006 77.591} 61.741 a 2.631 56.449 67.034 a = 48.9400. 4-1-9 U-learning 72.299 61.741 U-learning

U-learning

2.1

U-learning SPSS α _0.05

4-2-1 : III F 312.621 1 312.621 3.181 .082 294.002 2 147.001 1.496 .237 9200.948 1 9200.948 93.626 .000 * _{200.979 2 100.489 1.023 .369} * _{207.558 2 103.779 1.056 .358} * _{276.962 1 276.962 2.818 .101} * * _{240.299 2 120.150 1.223 .306} 3734.385 38 98.273 318599.000 50 19215.780 49 a. R = .806 R = .749 4-2-1 F 1.056 p .358 .05 F .2.818 p .101 .05 F 1.223 p .306 .05

4-2-2 : 86.0000 11.20268 5 83.3000 17.53124 10 82.3000 19.60754 10 U-learning 83.4400 16.80050 25 74.4286 25.91561 7 77.5000 13.85841 10 60.8750 22.44000 8 71.3200 21.02126 25 4-2-3 : III F 11707.009 1 11707.009 116.954 .000 1013.85 1 1013.85 10.131 .032 267.546 2 133.773 1.336 .273 * _{137.571 2 68.785 .687 .508} 4304.280 43 100.100 318599.000 50 19215.780 49 a. R = .776 R = .745 4-2-3 F=.687 p=.508 .05

2.2

4-2-3 4-2-4 : 79.2500 21.15366 12 80.4000 15.66558 20 72.7778 23.04103 18 77.3800 19.80300 50 4-2-5 : III F 14037.010 1 14037.010 141.194 .000 264.723 2 132.362 1.331 .274 4573.151 46 99.416 318599.000 50 19215.780 49 a R = .762 R = .746 4-2-5 F 1.331 p .274 .05

4-2-6 95% 79.537 a 2.878 73.743 85.331 78.833 a 2.233 74.338 83.329 74.327 a 2.354 69.590 79.065 a =67.0200 4-2-6

2.3

4-2-7 : U-learning 83.4400 16.80050 25 71.3200 21.02126 25 77.3800 19.80300 50 4-2-8 : III F 12632.667 1 12632.667 125.078 .000 90.941 1 90.941 9.132 .034 4746.933 47 100.999 318599.000 50 19215.780 49 a R = .753 R = .742

4-2-8 F .900 p .034 .05 4-2-9 95% U-learning _{78.785 a 2.053 74.656 82.915} 70.975 a 2.053 71.845 80.104 a = 67.0200. 4-2-9 U-learning 78.785 70.975 U-learning

U-learning

3.1

U-learning SPSS α _0.05 4-3-1 : III F 2.147 1 2.147 .018 .894 19.511 2 9.756 .082 .921 306.119 1 306.119 2.586 .116 * _{10.969 2 5.485 .046 .955} * _{16.766 2 16.766 .060 .942} * _{14.174 1 7.087 .142 .709}

III F * * 10.889 2 5.444 .046 .955 4380.067 37 118.380 473605.920 49 8513.097 48 a R = .485 R = .333 4-3-1 F .060 p .942 .05 F .142 p .709 .05 F .046 p .955 .05 4-3-2 : 3.9760 .43334 5 4.5533 .24758 12 4.2291 .34778 11 U-learning 4.3229 .38348 28 3.4940 .20452 5 3.8340 .55448 10 3.6767 .76758 6 3.7081 .56009 21

4-3-3 : III F 474.677 1 474.677 4.500 .040 847.773 1 847.773 8.037 .007 528.116 2 264.058 2.503 .094 * 59.106 2 29.553 .280 .757 4430.062 42 105.478 473605.920 49 8513.097 48 a R = .480 R = .405 4-3-3 F=.280 p=.757 .05

3.2

4-3-3 4-3-4 : 3.7350 .40815 10 4.2264 .54614 22 4.0341 .57772 17 4.0594 .55490 49

4-3-5 : III F 1983.658 1 1983.658 16.044 .000 392.158 2 196.079 1.586 .216 5563.768 45 123.639 473605.920 49 8513.097 48 a R = .346 R = .303 4-3-5 F 1.586 p .216 .05 4-3-6 95% 92.037 a 3.567 84.853 99.221 99.791 a 2.406 94.946 104.637 97.533 a 2.703 92.090 102.977 a = 97.6359 120 4-3-6

3.3

4-3-7 : U-learning 4.3229 .38348 28 3.7081 .56009 21 4.0594 .55490 49 4 44 4閾閾閾閾3333閾閾閾閾8888 : III F 872.153 1 872.153 7.978 .007 927.249 1 927.249 8.482 .006 5028.677 46 109.319 473605.920 49 8513.097 48 a R = .409 R = .384 4-3-8 F 8.482 p .006 .05 4 44 4閾閾閾閾3333閾閾閾閾峯峯峯峯 95% U-learning _{101.730 a 2.101 97.500 105.959} 91.686 a 2.473 86.709 96.664 a = 97.6359 120

4-3-9 U-learning 101.730

91.686 U-learning

U-learning

4.1

U-learning SPSS α _0.05 4-4-1 : III F 193.670 1 193.670 .758 .390 59.176 2 29.588 .116 .891 2658.509 1 2658.509 10.400 .003 * 808.328 2 404.164 1.581 .219 * 31.543 2 15.772 .062 .940 * 32.592 1 32.592 .127 .723 * * 663.349 2 331.675 1.297 .285 9458.437 37 255.633 298997.000 49 19760.245 48 a R = .521 R = .379

4-4-1 F .062 p .940 .05 F .127 p .723 .05 F 1.297 p .285 .05 4-4-2 : 87.6000 7.82943 5 72.2000 27.13260 10 84.1000 16.92762 10 U-learning 80.0400 20.93140 25 73.8333 24.37553 6 71.5000 16.37919 10 67.5000 19.47893 8 70.7500 18.86854 24 4-4-3 : III F 7297.929 1 7297.929 30.071 .000 1332.880 1 1332.880 5.492 .024 856.363 2 428.182 1.764 .184 * 531.077 2 265.538 1.094 .344 10193.105 42 242.693 298997.000 49 19760.245 48 a R = .484 R = .410 4-4-3 F=1.094 p=.344 .05

4.2

4-4-3 4-4-4 : 80.0909 19.32074 11 71.8500 21.81568 20 76.7222 19.49300 18 75.4898 20.28970 49 4-4-5 : III F 7509.315 1 7509.315 28.819 .000 724.340 2 362.170 1.390 .260 11725.755 45 260.572 298997.000 49 19760.245 48 a R = .407 R = .367 4-4-5 F 1.390 p .260 .05

4-4-6 95% 81.487 a 4.874 71.670 91.304 71.492 a 3.610 64.221 78.764 76.266 a 3.806 68.601 83.931 a = 49.2449. 4-4-6

4.3

4-4-7 : U-learning 80.0400 20.93140 25 70.7500 18.86854 24 75.4898 20.28970 49 4-4-8 : III F 7210.891 1 7210.891 28.862 .000 957.526 1 957.526 3.833 .056 11492.569 46 249.838 298997.000 49 19760.245 48 a R = .418 R = .393

4-4-8 F 3.833 p .056 .05 4-4-9 95% U-learning _{79.822 a 3.162 73.458 86.186} 70.977 a 3.227 64.482 77.472 a = 49.2449. 4-4-9 U-learning 79.822 70.977 U-learning

U-learning 33% 33% t

5.1

U-learning

- -- SPSS t 4-5-1 4-5-1 U-learning t 95% _t – -13.875 8.675 3.067 -21.128 -6.621 -4.523 7 .003 – -31.000 11.726 3.908 -40.013 -21.986 -7.931 8 .000 – -24.000 17.541 6.201 -38.665 -9.334 -3.870 7 .006 4-5-1 p=.003 p=.000 p=.006 U-learning U-learning

5.2

U-learning

- -- SPSS t 4-5-2 4-5-2 U-learning t 95% _t -3.875 7.376 2.607 -10.041 2.291 -1.486 7 .181 -10.666 8.874 2.958 -17.487 -3.845 -3.606 8 .007 -17.250 13.456 4.757 -28.499 -6.000 -3.626 7 .008 4-5-2 p=.181 p=.007 p=.008 U-learning U-learning

KSAT U-learning

U-learning U-learning U-learning U-learning U-learning

U-learning U-learning U-learning U-learning U-learning U-learning

1. U-learning 2. U-learning 3. 4. U-learning 5. 6. U-learning

1. U-learning U-learning U-learning 2. U-learning U-learning 3. 4. 5. 6.

1987 1995 75 12-22 1995 20 113-145 2000 10 29-31 2003 WISCS 2003 2002 2004 2005 2007 2008 11 08 http://content.edu.tw/primary/math/jm_jh/math/s3high/s303.htm 1998 37 5 47-53 2006 1994 25 38-44 2002 150 54-60 2007 - “ ” 8 2 191-197 饋008 10 ( ) 饋008

2006 -2006 — 2010 U-learning NSC-98-2511-S-142-003 2003 2002 1989 183 - 219 1992 NSC-75-0111-S-153-001 2003 1995 Irsp 2003 I NSC-91-2520-S-142-001 2004 II NSC-92-2521-S-142-003 2005 III NSC-93-2521-S-142-004 2005

1996 ─ ₃ 1998 64 10-24 1995 2004 2003 2004 2009 ─ 2001 I NSC-89-2511-S-152-021 1996 85 2 1997 2002 2 105-111 1985 18 191-227 2001 2001 5 18 http://www.nmh.gov.tw/edu/basis3/25/gz12.htm 1995 35 2-7 2007

2005 64 89-101 2005 2007 2009 U-learning -1985 2004 2002 k- 6 2005 2006 2 23 http://www.nici.nat.gov.tw/content/application/nici/generala/guest-cnt-browse.p hp?cntgrp_ordinal=1002006100110003&cnt_id=758 2005 峯0 饋00恒 6 饋峯 http://epaper.hrd.gov.tw/峯0/EDM峯0閾0恒01.htm 2009 U-learning GCCCE 2009 2009 U-learning 2000 web-bbs 22

6-11 1995a ─ 1995b 35 14-19 1998 11 573 - 602 1999 12 407- 436 1990 41 4 6-13 1999 1996 2007 1991 2005 2001

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B01 B02 B03 B04 B05 B06 B07 B08 B09 B10 B11 B12 B13 B14 B15 B16 B17 B18 B19 B20 B21

Cronbach's Alpha ITEM PCT PEARSON 0.9210 1 MATH01 59.9 0.331 0.9208 -0.0002 2 MATH02 90.1 0.407 0.9195 -0.0015 3 MATH03 92 0.388 0.9198 -0.0012 4 MATH04 93.9 0.377 0.9199 -0.0011 5 MATH05 81.7 0.515 0.9183 -0.0027 6 MATH06 87 0.535 0.9183 -0.0027 7 MATH07 87.8 0.502 0.9186 -0.0024 8 MATH08 63 0.454 0.9191 -0.0019 9 MATH09 51.1 0.3 0.9213 0.0003 10 MATH10 67.9 0.429 0.9194 -0.0016 11 MATH11 90.5 0.546 0.9184 -0.0026 12 MATH12 72.9 0.513 0.9183 -0.0027 13 MATH13 84.4 0.505 0.9185 -0.0025 14 MATH14 77.1 0.623 0.9169 -0.0041 15 MATH15 83.6 0.626 0.9172 -0.0038 16 MATH16 81.7 0.615 0.9172 -0.0038 17 MATH17 76 0.595 0.9173 -0.0037 18 MATH18 68.3 0.361 0.9203 -0.0007 19 MATH19 39.3 0.31 0.9211 0.0001 20 MATH20 85.5 0.293 0.9206 -0.0004 21 MATH21 78.6 0.546 0.9179 -0.0031 22 MATH22 61.8 0.437 0.9193 -0.0017 23 MATH23 38.2 0.411 0.9197 -0.0013 24 MATH24 26 0.279 0.9212 0.0002 25 MATH25 53.1 0.478 0.9188 -0.0022 26 MATH26 65.3 0.517 0.9182 -0.0028 27 MATH27 82.4 0.619 0.9172 -0.0038 28 MATH28 82.1 0.671 0.9166 -0.0044 29 MATH29 74.8 0.566 0.9176 -0.0034 30 MATH30 71.8 0.455 0.9190 -0.0020 31 MATH31 76 0.552 0.9178 -0.0032 32 MATH32 71.8 0.466 0.9189 -0.0021

33 MATH33 81.7 0.581 0.9176 -0.0034

34 MATH34 61.5 0.493 0.9186 -0.0024

35 MATH35 70.6 0.539 0.9179 -0.0031

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Q1 7.403 *** .496 ** Q13 9.986 *** .483 ** Q2 10.907 *** .517 ** Q14 8.756 *** .496 ** Q3 7.806 *** .465 ** Q15 6.076 *** .389 ** Q4 4.984 *** .335 ** Q16 12.692 *** .618 ** Q5 13.140 *** .637 ** Q17 9.265 *** .565 ** Q6 7.955 *** .395 ** Q18 9.119 *** .533 ** Q7 8.102 *** .484 ** Q19 11.982 *** .622 ** Q8 9.991 *** .569 ** Q20 12.394 *** .667 ** Q9 9.531 *** .537 ** Q21 14.139 *** .691 ** Q10 10.546 *** .601 ** Q22 11.259 *** .591 ** Q11 11.214 *** .568 ** Q23 11.526 *** .678 ** Q12 11.171 *** .592 ** Q24 9.784 *** .632 **