学習者データを「見る」：外国語教師のためのデータの入力、分析、解釈方法

外国語教育メディア学会（LET）第62回（2023 年度）全国研究大会
ワークショップ
2023/08/07

Transcript

1. ֶशऀσʔλΛʮݟΔʯ ―֎ࠃޠڭࢣͷͨΊͷσʔλͷೖྗɺ෼ੳɺղऍํ๏― Ӝ໺ ݚʢ๺ւֶԂେֶʣ email: urano@hgu.jp LET2023 @ Waseda University ɹɹ2023. 8. 7. https://www.urano-ken.com/research/let2023
2. ຊ೔ͷࢿྉ
3. ͸͡Ίʹ • ࠓ೔ͷ͓࿩͸ɺҎԼͷϫʔΫγϣοϓͷ಺༰ Λ૊Έ߹ΘͤͯΞοϓσʔτͨ͠΋ͷͰ͢ • 2013/08/07. ༗ҙੑͱޮՌྔʹ͍͔ͭͯͬ͠Γߟ͑ͯΈΑ͏. ֎ࠃޠڭҭϝ σΟΞֶձୈ53ճશࠃݚڀେձ @ தژֶӃେֶ • 2014/10/26. ӳޠतۀΛݟͭΊ௚͢ํ๏ɿςετσʔλͷݟํΛ஌Ζ͏. શࠃ ӳޠڭҭֶձɾখֶߍӳޠڭҭֶձୈ2ճӳޠڭҭηϛφʔˏؔ੢େֶ • 2016/08/07. ྔతσʔλΛѻ͏ͱ͖ʹ஌͓͖͍ͬͯͨ͜ͱɿσʔλͷ෼෍ɺ ༗ҙੑɺޮՌྔɺ৴པ۠ؒ. ֎ࠃޠڭҭϝσΟΞֶձୈ56ճશࠃݚڀେձˏ ૣҴాେֶ • 2019/08/06. ֎ࠃޠڭҭʢݚڀʣʹ͓͚Δྔతσʔλͷࢹ֮Խͱղऍ. FLEAT VII / LET2019 @ Waseda University
4. ࢲͨͪ֎ࠃޠڭࢣ͸ɺݚڀ͚ͩͰͳ͘ڭҭ࣮ફͷ৔ʹ͓ ͍ͯ΋ɺֶशऀͷ஌ࣝɾೳྗΛ਺ྔԽͨ͠σʔλΛѻͬ ͍ͯ·͢ɻຊϫʔΫγϣοϓͰ͸ɺ༷ʑͳάϥϑΛ༻͍ ͯσʔλΛࢹ֮Խ͢Δҙٛ΍σʔλͷ෼෍ʹؔ͢Δجຊ తͳࢦඪʹֶ͍ͭͯͼɺݚڀɾڭҭͷ྆໘Ͱֶशऀσʔ λΛΑΓਂ͘ཧղ͢Δ͜ͱΛ໨ࢦ͠·͢ɻ ཁࢫ
5. ࢲͨͪ֎ࠃޠڭࢣ͸ɺݚڀ͚ͩͰͳ͘ڭҭ࣮ફͷ৔ʹ͓ ͍ͯ΋ɺֶशऀͷ஌ࣝɾೳྗΛ਺ྔԽͨ͠σʔλΛѻͬ ͍ͯ·͢ɻຊϫʔΫγϣοϓͰ͸ɺ༷ʑͳάϥϑΛ༻͍ ͯσʔλΛࢹ֮Խ͢Δҙٛ΍σʔλͷ෼෍ʹؔ͢Δجຊ తͳࢦඪʹֶ͍ͭͯͼɺݚڀɾڭҭͷ྆໘Ͱֶशऀσʔ λΛΑΓਂ͘ཧղ͢Δ͜ͱΛ໨ࢦ͠·͢ɻ ཁࢫ
6. ՍۭͷσʔλΛ ༻ҙ͠·ͨ͠
7. Name* Test A খ૔ ರ 70 Տ੢ େޒ࿠ 38 খਿ Ꮺ 58 ௶Ҫ ج༞ 48 ӬҪ ج༞ 28 ڮޱ ๏࢚ 54 ݪ ཽ໵ 58 ޿੉ ༎ 38 ౻ా ࢰಐ 42 ຊؒ խ඙ 47 ٶ࡚ ৎ༤ 78 ଜҪ ࿣࿠ 68 ࢁ࡚ ޹ଠ࿠ 40 ԣҪ ޛࢤ 50 ґా ༸հ 68 एࢁ ప 57 ༗അ Ղ೫ 64 ࿨ઘ ګࢠ 76 ؠҪ ඒՂ 43 ߐ઒ ༝Ӊ 90 ਆ୩ ࣿق 58 ๺઒ ઍՂࢠ 38 ࡔా Ѫࡊ 38 ਿా ඒՂ 43 ⁋ຊ ᜫ 58 ౔୩ ே߳ 60 Ӭ੉ ͘ΔΈ 48 দ໦ ಹಸ 45 ଜҪ ݁ࢠ 24 ए௬ ·Έ 36 *ʮͳΜͪΌͬͯݸਓ৘ใʯͰੜ੒ http://kazina.com/dummy/
8. Group A Test A খ૔ ರ 70 Տ੢ େޒ࿠ 38 খਿ Ꮺ 58 ௶Ҫ ج༞ 48 ӬҪ ج༞ 28 ڮޱ ๏࢚ 54 ݪ ཽ໵ 58 ޿੉ ༎ 38 ౻ా ࢰಐ 42 ຊؒ խ඙ 47 ٶ࡚ ৎ༤ 78 ଜҪ ࿣࿠ 68 ࢁ࡚ ޹ଠ࿠ 40 ԣҪ ޛࢤ 50 ґా ༸հ 68 एࢁ ప 57 ༗അ Ղ೫ 64 ࿨ઘ ګࢠ 76 ؠҪ ඒՂ 43 ߐ઒ ༝Ӊ 90 ਆ୩ ࣿق 58 ๺઒ ઍՂࢠ 38 ࡔా Ѫࡊ 38 ਿా ඒՂ 43 ⁋ຊ ᜫ 58 ౔୩ ே߳ 60 Ӭ੉ ͘ΔΈ 48 দ໦ ಹಸ 45 ଜҪ ݁ࢠ 24 ए௬ ·Έ 36 Group B Test A ؠӬ ࿡࿠ 52 ২໦ ҭೋ 59 ย੉ ཽ໵ 61 ࡔݩ ᠳଠ 76 ౡଜ ༏ 45 ৓ా ௕ར 68 ௕୔ ஌࢙ 63 দҪ Ұಙ 69 ࡾݪ ༟࣍࿠ 43 क԰ ཽ࣍ 51 ੨໺ Έ͋ 36 ஑୩ ༏ 51 ؠ୩ ౧ࢠ 39 ্ݪ ܠࢠ 71 ߐޱ Ί͙Έ 26 ٴ઒ ͳͭΈ 79 େ௩ ·͞Έ 55 Ԭ໺ ࿏ࢠ 61 ֯ా ౧ࢠ 89 ઒୺ ݁ҥ 51 ਆށ ࡊʑඒ 71 ֎ࢁ Έ͋ 63 রҪ Έ͖ 41 ࠜ؛ ༏ 41 ࠜ؛ ྱࢠ 83 Ӌా ѥر 93 ෱࢜ ΈΏ͖ 47 ෍ࢪ ༑߳ 37 ଜా จੈ 52 ٢Ӭ ܙས߳ 41
9. Group A Test A খ૔ ರ 70 Տ੢ େޒ࿠ 38 খਿ Ꮺ 58 ௶Ҫ ج༞ 48 ӬҪ ج༞ 28 ڮޱ ๏࢚ 54 ݪ ཽ໵ 58 ޿੉ ༎ 38 ౻ా ࢰಐ 42 ຊؒ խ඙ 47 ٶ࡚ ৎ༤ 78 ଜҪ ࿣࿠ 68 ࢁ࡚ ޹ଠ࿠ 40 ԣҪ ޛࢤ 50 ґా ༸հ 68 एࢁ ప 57 ༗അ Ղ೫ 64 ࿨ઘ ګࢠ 76 ؠҪ ඒՂ 43 ߐ઒ ༝Ӊ 90 ਆ୩ ࣿق 58 ๺઒ ઍՂࢠ 38 ࡔా Ѫࡊ 38 ਿా ඒՂ 43 ⁋ຊ ᜫ 58 ౔୩ ே߳ 60 Ӭ੉ ͘ΔΈ 48 দ໦ ಹಸ 45 ଜҪ ݁ࢠ 24 ए௬ ·Έ 36 Group B Test A ؠӬ ࿡࿠ 52 ২໦ ҭೋ 59 ย੉ ཽ໵ 61 ࡔݩ ᠳଠ 76 ౡଜ ༏ 45 ৓ా ௕ར 68 ௕୔ ஌࢙ 63 দҪ Ұಙ 69 ࡾݪ ༟࣍࿠ 43 क԰ ཽ࣍ 51 ੨໺ Έ͋ 36 ஑୩ ༏ 51 ؠ୩ ౧ࢠ 39 ্ݪ ܠࢠ 71 ߐޱ Ί͙Έ 26 ٴ઒ ͳͭΈ 79 େ௩ ·͞Έ 55 Ԭ໺ ࿏ࢠ 61 ֯ా ౧ࢠ 89 ઒୺ ݁ҥ 51 ਆށ ࡊʑඒ 71 ֎ࢁ Έ͋ 63 রҪ Έ͖ 41 ࠜ؛ ༏ 41 ࠜ؛ ྱࢠ 83 Ӌా ѥر 93 ෱࢜ ΈΏ͖ 47 ෍ࢪ ༑߳ 37 ଜా จੈ 52 ٢Ӭ ܙས߳ 41 ൺ΂ͯΈΑ͏
10. Group A Test A খ૔ ರ 70 Տ੢ େޒ࿠ 38 খਿ Ꮺ 58 ௶Ҫ ج༞ 48 ӬҪ ج༞ 28 ڮޱ ๏࢚ 54 ݪ ཽ໵ 58 ޿੉ ༎ 38 ౻ా ࢰಐ 42 ຊؒ խ඙ 47 ٶ࡚ ৎ༤ 78 ଜҪ ࿣࿠ 68 ࢁ࡚ ޹ଠ࿠ 40 ԣҪ ޛࢤ 50 ґా ༸հ 68 एࢁ ప 57 ༗അ Ղ೫ 64 ࿨ઘ ګࢠ 76 ؠҪ ඒՂ 43 ߐ઒ ༝Ӊ 90 ਆ୩ ࣿق 58 ๺઒ ઍՂࢠ 38 ࡔా Ѫࡊ 38 ਿా ඒՂ 43 ⁋ຊ ᜫ 58 ౔୩ ே߳ 60 Ӭ੉ ͘ΔΈ 48 দ໦ ಹಸ 45 ଜҪ ݁ࢠ 24 ए௬ ·Έ 36 Group B Test A ؠӬ ࿡࿠ 52 ২໦ ҭೋ 59 ย੉ ཽ໵ 61 ࡔݩ ᠳଠ 76 ౡଜ ༏ 45 ৓ా ௕ར 68 ௕୔ ஌࢙ 63 দҪ Ұಙ 69 ࡾݪ ༟࣍࿠ 43 क԰ ཽ࣍ 51 ੨໺ Έ͋ 36 ஑୩ ༏ 51 ؠ୩ ౧ࢠ 39 ্ݪ ܠࢠ 71 ߐޱ Ί͙Έ 26 ٴ઒ ͳͭΈ 79 େ௩ ·͞Έ 55 Ԭ໺ ࿏ࢠ 61 ֯ా ౧ࢠ 89 ઒୺ ݁ҥ 51 ਆށ ࡊʑඒ 71 ֎ࢁ Έ͋ 63 রҪ Έ͖ 41 ࠜ؛ ༏ 41 ࠜ؛ ྱࢠ 83 Ӌా ѥر 93 ෱࢜ ΈΏ͖ 47 ෍ࢪ ༑߳ 37 ଜా จੈ 52 ٢Ӭ ܙས߳ 41 ൺ΂ͯΈΑ͏ How?
11. ݸʑͷ਺஋Λݟͯ΋ ਺ྔσʔλͷཧղ͸೉͍͠
12. • σʔλΛཁ໿͢Δ • σʔλΛਤͰද͢ ਺ྔσʔλΛཧղ͢Δํ๏
13. • σʔλΛཁ໿͢Δ • σʔλΛਤͰද͢ ਺ྔσʔλΛཧղ͢Δํ๏
14. σʔλΛཁ໿͢Δ σʔλͷத৺ͱ ͹Β͖ͭ
15. ฏۉ஋ (mean) ͢΂ͯͷσʔλͷ߹ܭΛσʔλͷݸ਺Ͱ 
 ׂͬͨ΋ͷ தԝ஋ (median) ͢΂ͯͷσʔλΛখ͍͞ॱʢ·ͨ͸େ͖͍ॱʣʹ ฒ΂ͨͱ͖ɺਅΜதʹདྷΔ஋ ࠷ස஋ (mode) ͢΂ͯͷσʔλͷதͰग़ݱճ਺͕࠷΋ଟ͍஋ σʔλͷத৺
16. Group A Group B ฏۉ஋ 52.1 57.1 தԝ஋ 49.0 53.5 ࠷ස஋ 38, 58 41, 51 σʔλͷத৺
17. ൣғ (range) ࠷େ஋ͱ࠷খ஋ͷ෯ ࢛෼Ґൣғ (IQR) σʔλͷ্Ґ25ˋͱԼҐ25ˋͷ෯ 
 ʢinterquartile rangeʣ ෼ࢄ (variance) ݸʑͷ਺஋ͱฏۉ஋ʢmeanʣͷڑ཭Λදͨ͠ 
 σʔλͷ෼෍౓߹͍Λࣔ͢਺஋ ඪ४ภࠩ (SD) ෼ࢄͷฏํࠜʢstandard deviationʣ σʔλͷ͹Β͖ͭ
18. Group A Group B ൣғ 66.0 67.0 ࢛෼Ґൣғ 19.0 25.3 ෼ࢄ 235 279 ඪ४ภࠩ 15.3 16.7 σʔλͷ͹Β͖ͭ
19. • ݸʑͷ਺஋ͱฏۉ஋ͱͷࠩΛ̎৐͠ɺ߹ܭΛ ࣗ༝౓ʢਓ਺−̍ʣͰׂͬͨ΋ͷͷฏํࠜ Group A Test A খ૔ ರ 70 Տ੢ େޒ࿠ 38 খਿ Ꮺ 58 ௶Ҫ ج༞ 48 ӬҪ ج༞ 28 ڮޱ ๏࢚ 54 ݪ ཽ໵ 58 ޿੉ ༎ 38 ౻ా ࢰಐ 42 (70–52.1)2 = 320.4 (38–52.1)2 = 198.8 (58–52.1)2 = 034.8 . . . ߹ܭ 6828.7 / 29 = 235.4 √ 235.4 = 15.3 ←ʢ෼ࢄʣ ඪ४ภࠩ Group A ฏۉ஋ 52.1 ඪ४ภࠩ 15.3
20. 0 20 40 60 80 100 0.00 0.01 0.02 0.03 0.04 0 20 40 60 80 100 0.00 0.01 0.02 0.03 0.04 ฏۉ஋ = 50 ͷ৔߹ ඪ४ภࠩ = 10 ඪ४ภࠩ = 20 34.1% 13.6% 34.1% 34.1% 13.6% 34.1% 13.6% 13.6% ඪ४ภࠩ
21. 0 20 40 60 80 100 0.00 0.01 0.02 0.03 0.04 0 20 40 60 80 100 0.00 0.01 0.02 0.03 0.04 ฏۉ஋ = 50 ͷ৔߹ ඪ४ภࠩ = 10 ඪ४ภࠩ = 20 ඪ४ภࠩ
22. ʢ٢ా, 1998, p. 173ʣ ඪ४ภࠩ
23. ʢ٢ా, 1998, p. 173ʣ ࠩ͸ಉ͡ ඪ४ภࠩ
24. ॏͳΓͷྔ͕ҧ͏ ඪ४ภࠩ
25. Group A Group B ฏۉ஋ 52.1 57.1 ඪ४ภࠩ 15.3 16.7
26. Group A Group B Group A Group B ฏۉ஋ 52.1 57.1 ඪ४ภࠩ 15.3 16.7 0 20 40 60 80 100 0.000 0.005 0.010 0.015 0.020 0.025 0.030 0 20 40 60 80 100 0.000 0.005 0.010 0.015 0.020 0.025 0.030
27. Group A Group B ฏۉ஋ 52.1 57.1 ඪ४ภࠩ 15.3 16.7 Group A Group B 0 20 40 60 80 100 0.000 0.005 0.010 0.015 0.020 0.025 0.030 0 20 40 60 80 100 0.000 0.005 0.010 0.015 0.020 0.025 0.030
28. Group A Group B ฏۉ஋ 52.1 57.1 ඪ४ภࠩ 15.3 16.7 Group A Group B ฏۉ஋ͷࠩ 0 20 40 60 80 100 0.000 0.005 0.010 0.015 0.020 0.025 0.030 0 20 40 60 80 100 0.000 0.005 0.010 0.015 0.020 0.025 0.030 ෼෍ͷҧ͍
29. • ฏۉ஋ͷൺֱ͚ͩͰ͸ෆे෼ • σʔλͷ෼෍ʢ͹Β͖ͭʣ΋߹Θͤͯݕ౼ • ෼෍ͷॏͳΓ͕গͳ͍ํ͕͕ࠩେ͖͍ ݴ͑ͦ͏ͳ͜ͱ
30. • ฏۉ஋ͱඪ४ภࠩΛར༻ͨ͠ཁ໿͸ 
 σʔλͷਖ਼ن෼෍͕લఏʢ̎ͭલͷεϥΠυࢀরʣ • ਖ਼ن෼෍Ͱͳ͍৔߹ɺཁ໿͕࣮ଶͱҟͳΔ 
 Մೳੑ͕͋Δ ஫ҙࣄ߲
31. • σʔλΛཁ໿͢Δ • σʔλΛਤͰද͢ ਺ྔσʔλΛཧղ͢Δํ๏
32. • ώετάϥϜʢhistogramʣ • ີ౓ۂઢʢdensityʣ • σʔλ఺ʗ๘܈ਤʢbeeswarmʣ • ശͻ͛ਤʢboxplotʣ • ϰΝΠΦϦϯਤʢviolin plotʣ σʔλΛਤͰද͢
33. ώετάϥϜ (Histogram) B A 20 40 60 80 100 Score Group
34. ີ౓ۂઢ (Density) B A 30 60 90 Score Group
35. ີ౓ۂઢ (Density) B A 30 60 90 Score Group
36. σʔλ఺ʗ๘܈ਤ (Beeswarm) 20 40 60 80 A B Group Score
37. ശͻ͛ਤ (Box Plot) 20 40 60 80 A B Group Score
38. 20 40 60 80 A B Group Score ശͻ͛ਤ (Box Plot) தԝ஋
39. 20 40 60 80 A B Group Score ശͻ͛ਤ (Box Plot) ࢛෼Ґൣғ
40. 20 40 60 80 A B Group Score ശͻ͛ਤ (Box Plot) ࢛෼Ґൣғͷ1.5ഒͷ࠷େ஋ ಉ࠷খ஋
41. 20 40 60 80 A B Group Score ശͻ͛ਤ (Box Plot) ֎Ε஋
42. ϰΝΠΦϦϯਤ (Violin Plot) 20 40 60 80 A B Group Score ີ౓ۂઢΛॎʹͯ͠ࠨӈରশʹͨ͠΋ͷ
43. • ऩूͨ͠σʔλʹͲͷΑ͏ͳಛ௃͕͋Δ͔ɺ ͬ͘͟Γ೺Ѳ͢Δ͜ͱ͕Ͱ͖Δ • ฏۉ஋ͱඪ४ภ͚ࠩͩͰ͸ݟ͑ͳ͍΋ͷ͕ 
 ݟ͑Δ • ݫີͳൺֱ΍෼ੳʹ͸ద͞ͳ͍ σʔλΛਤͰද͢
44. ࣮ࡍʹ ΍ͬͯΈ·͠ΐ͏
46. • Φʔϓϯιʔεͷ౷ܭϓϩάϥϛϯάݴޠ 
 ɹɹΛ࢖͍΍͍͢ܗʹͨ͠ιϑτ΢ΣΞ • GUIͷͨΊ௚ײతʹ࢖͑Δ • ΦʔϓϯιʔεͰແྉͰ࢖͑Δ • ϒϥ΢βͰ࢖͑ΔΫϥ΢υ൛ʢϕʔλʣ΋
47. https://www.jamovi.org
48. • Must-read (1) • ࣳా੐࢘. (2021/2022). jamovi׬શ߈ུΨΠυ. 
 https://bookdown.org/sbtseiji/ jamovi_complete_guide/
49. • Must-read (2) • Navarro, D. J., & Foxcroft, D. R. (2019). Learning statistics with jamovi: A tutorial for psychology students and other beginners. (Version 0.70). 
 DOI: 10.24384/hgc3-7p15 • ೔ຊޠ༁΋͋Γ·͢: • ࣳా੐࢘༁. jamoviͰֶͿ৺ཧ౷ܭ. 
 https://bookdown.org/sbtseiji/lswjamoviJ/
50. ஫ҙ఺ᶃ
51. ஫ҙ఺ᶃ
52. • ϑΝΠϧಡΈࠐΈ࣌ʹࣗಈత ʹ൑அ͞ΕΔม਺ͷछྨ͕ؒ ҧ͍ͬͯΔ͜ͱ͕͋Δɻ • Continuous ࿈ଓม਺ • Ordinal ॱংม਺ • Nominal ໊ٛม਺ ஫ҙ఺ᶃ
53. • ͜͜·Ͱʹग़͖ͯͨ͢΂ͯͷ਺஋ͱάϥϑΛ 
 ࠶ݱ͠·͠ΐ͏ • ฏۉ஋ɺதԝ஋ɺ࠷ස஋ • ൣғɺ࢛෼Ґൣғɺ෼ࢄɺඪ४ภࠩ • ώετάϥϜɺີ౓ۂઢɺσʔλ఺ɺ 
 ശͻ͛ਤɺϰΝΠΦϦϯਤ ϋϯζΦϯᶃ
54. • Group A ͱ Group B ͷ Test A ͷείΞ • www.urano-ken.com/research/let2023/ • μ΢ϯϩʔυ >> urano1.csv 
 https://www.urano-ken.com/wp-content/uploads/2023/08/urano1.csv ϋϯζΦϯᶃ
55. • ࢄ෍ਤ σʔλΛਤͰද͢ʢ௥Ճʣ
56. Group A Test A Test B খ૔ ರ 70 56 Տ੢ େޒ࿠ 38 83 খਿ Ꮺ 58 74 ௶Ҫ ج༞ 48 73 ӬҪ ج༞ 28 65 ڮޱ ๏࢚ 54 49 ݪ ཽ໵ 58 53 ޿੉ ༎ 38 39 ౻ా ࢰಐ 42 41 ຊؒ խ඙ 47 60 ٶ࡚ ৎ༤ 78 54 ଜҪ ࿣࿠ 68 80 ࢁ࡚ ޹ଠ࿠ 40 48 ԣҪ ޛࢤ 50 84 ґా ༸հ 68 55 एࢁ ప 57 30 ༗അ Ղ೫ 64 68 ࿨ઘ ګࢠ 76 71 ؠҪ ඒՂ 43 36 ߐ઒ ༝Ӊ 90 64 ਆ୩ ࣿق 58 41 ๺઒ ઍՂࢠ 38 63 ࡔా Ѫࡊ 38 48 ਿా ඒՂ 43 31 ⁋ຊ ᜫ 58 67 ౔୩ ே߳ 60 52 Ӭ੉ ͘ΔΈ 48 40 দ໦ ಹಸ 45 48 ଜҪ ݁ࢠ 24 65 ए௬ ·Έ 36 88
57. Group A Test A Test B খ૔ ರ 70 56 Տ੢ େޒ࿠ 38 83 খਿ Ꮺ 58 74 ௶Ҫ ج༞ 48 73 ӬҪ ج༞ 28 65 ڮޱ ๏࢚ 54 49 ݪ ཽ໵ 58 53 ޿੉ ༎ 38 39 ౻ా ࢰಐ 42 41 ຊؒ խ඙ 47 60 ٶ࡚ ৎ༤ 78 54 ଜҪ ࿣࿠ 68 80 ࢁ࡚ ޹ଠ࿠ 40 48 ԣҪ ޛࢤ 50 84 ґా ༸հ 68 55 एࢁ ప 57 30 ༗അ Ղ೫ 64 68 ࿨ઘ ګࢠ 76 71 ؠҪ ඒՂ 43 36 ߐ઒ ༝Ӊ 90 64 ਆ୩ ࣿق 58 41 ๺઒ ઍՂࢠ 38 63 ࡔా Ѫࡊ 38 48 ਿా ඒՂ 43 31 ⁋ຊ ᜫ 58 67 ౔୩ ே߳ 60 52 Ӭ੉ ͘ΔΈ 48 40 দ໦ ಹಸ 45 48 ଜҪ ݁ࢠ 24 65 ए௬ ·Έ 36 88 Test A Test B ฏۉ஋ 52.1 57.5 ඪ४ภࠩ 15.3 16.0
58. ࢄ෍ਤ (Scatter Plot) Test A Test B
59. Class A Test A Test B খ૔ ರ 70 56 Տ੢ େޒ࿠ 38 83 খਿ Ꮺ 58 74 ௶Ҫ ج༞ 48 73 ӬҪ ج༞ 28 65 ڮޱ ๏࢚ 54 49 ݪ ཽ໵ 58 53 ޿੉ ༎ 38 39 ౻ా ࢰಐ 42 41 ຊؒ խ඙ 47 60 ٶ࡚ ৎ༤ 78 54 ଜҪ ࿣࿠ 68 80 ࢁ࡚ ޹ଠ࿠ 40 48 ԣҪ ޛࢤ 50 84 ґా ༸հ 68 55 एࢁ ప 57 30 ༗അ Ղ೫ 64 68 ࿨ઘ ګࢠ 76 71 ؠҪ ඒՂ 43 36 ߐ઒ ༝Ӊ 90 64 ਆ୩ ࣿق 58 41 ๺઒ ઍՂࢠ 38 63 ࡔా Ѫࡊ 38 48 ਿా ඒՂ 43 31 ⁋ຊ ᜫ 58 67 ౔୩ ே߳ 60 52 Ӭ੉ ͘ΔΈ 48 40 দ໦ ಹಸ 45 48 ଜҪ ݁ࢠ 24 65 ए௬ ·Έ 36 88 Test A Test B ฏۉ஋ 52.1 57.5 ඪ४ภࠩ 15.3 16.0
60. ࢄ෍ਤ (Scatter Plot) Test A Test B খ૔͞Μ 70 56
61. Test A = ࣄલςετ Test B = ࣄޙςετ ͱԾఆ͢Δͱ
62. ࢄ෍ਤ (Scatter Plot) Test A Test B ಘ఺্ঢ
63. ࢄ෍ਤ (Scatter Plot) Test A Test B ए௬͞Μ 36⾭88
64. ࢄ෍ਤ (Scatter Plot) Test A Test B ଜҪ͞Μ 24⾭65
65. ࢄ෍ਤ (Scatter Plot) Test A Test B ಘ఺Լ߱
66. ࢄ෍ਤ (Scatter Plot) Test A Test B ߐ઒͞Μ 90↘︎64
67. • ࢄ෍ਤ͸̎ͭͷม਺ʢςετʣͷؔ܎ͷڧ͞ ʢʹ૬ؔʣΛݟΔͨΊʹ࢖ΘΕ·͕͢ • ݸʑͷσʔλʢֶशऀʣ͕̎ͭͷม਺ 
 ʢςετʣͰͲͷΑ͏ʹৼΔ෣͍ͬͯΔ͔Λ 
 ݟΔͨΊʹ΋࢖͑·͢ σʔλΛਤͰද͢ʢ௥Ճʣ
68. • ࢄ෍ਤΛඳ͍ͯΈ·͠ΐ͏ • Group A ͷ Test A ͱ Test B ͷείΞ • www.urano-ken.com/research/let2023/ • μ΢ϯϩʔυ >> urano2.csv 
 https://www.urano-ken.com/wp-content/uploads/2023/08/urano2.csv ϋϯζΦϯᶄ
69. jamovi Ͱग़ྗ ஫ҙ఺ᶄ
70. Test A Test B Microsoft Excel Ͱग़ྗ ஫ҙ఺ᶄ
71. • jamovi ͸౷ܭॲཧ΍άϥϑͷ࡞੒ΛGUIͰ ߦͬͯ͘ΕΔศརͳΞϓϦέʔγϣϯͰ͢ • ศར͞ͷτϨʔυΦϑͱͯ͠ɺάϥϑͰͷ 
 ࡉ͔͍ௐ੔͸Ͱ͖·ͤΜ ஫ҙ఺ᶄ
72. ͓·͚
73. σʔλͷೖྗํ๏ • ೖྗํ๏Λม͑ͯΈΑ͏ • ηΫγϣϯ͝ͱͷಘ఺ • ̍໰ͣͭͷಘ఺ • ղ౴ͦͷ΋ͷ
74. ̋̋தֶߍ
    ୈֶ̎ظதؒࢼݧ ֶ
    ೥ ̏ Ϋϥε 2 ࢯ
    ໊ Ken Urano ̍
    Ϧεχϯά໰୊
    ์ૹΛௌ͖ɺ࣍ͷ࣭໰ʹ൪߸Ͱ౴͑ͳ͍͞ɻ 1. What does Tora-san do? ᶃ He is a salesman. ᶄ He is a fisherman. ᶅ He is an entertainer. ᶆ He is a traveler. 2. Where does he live? ᶃ In Tokyo. ᶄ In Sapporo. ᶅ In Osaka. ᶆ He doesn’t have a home. ʲղ౴ཝʳ 1 3 2 4 ̎
    ࣍ͷจͷ ( ) ಺͔Βద੾ͳޠΛબͼɺ൪߸Ͱ౴͑ͳ͍͞ɻ 1. Atsushi has already ( ᶃ eat ᶄ eating ᶅ eaten ) all the chocolate. 2. We call ( ᶃ he ᶄ his ᶅ him ) a chocolate monster. ʲղ౴ཝʳ 1 3 2 3 ̏
    ࣍ͷจΛಡΜͰɺԼͷ໰͍ʹ౴͑ͳ͍͞ɻ Today we live in the age of beer. In addition to major beer manufacturers, there are hundreds of small breweries all over Japan. They are called microbreweries and the beer they produce is becoming more and more popular because of its high quality. 1. Do you like beer? 2. What is your favorite brand? ʲղ౴ཝʳ 1 Yes, of course! 2 Sapporo Classic. ̐
    ࣍ͷ೔ຊจΛӳޠʹ௚͠ͳ͍͞ɻ 1. Θͨ͠͸͜ͷ͋ͱߴాഅ৔Ͱͨ͘͞Μ͓ञΛҿΈ͍ͨɻ 2. ࢓ࣄ͕଴͍ͬͯΔͷͰࡳຈʹؼΓͨ͘ͳ͍ɻ ʲղ౴ཝʳ 1 I am so ready to go to Takadanobaba and get drunk. 2 I don’t want to go back to Sapporo because there are so many things to do there. 10 20 20 30 80
75. ̋̋தֶߍ
    ୈֶ̎ظதؒࢼݧ ֶ
    ೥ ̏ Ϋϥε 2 ࢯ
    ໊ Ken Urano ̍
    Ϧεχϯά໰୊
    ์ૹΛௌ͖ɺ࣍ͷ࣭໰ʹ൪߸Ͱ౴͑ͳ͍͞ɻ 1. What does Tora-san do? ᶃ He is a salesman. ᶄ He is a fisherman. ᶅ He is an entertainer. ᶆ He is a traveler. 2. Where does he live? ᶃ In Tokyo. ᶄ In Sapporo. ᶅ In Osaka. ᶆ He doesn’t have a home. ʲղ౴ཝʳ 1 3 2 4 ̎
    ࣍ͷจͷ ( ) ಺͔Βద੾ͳޠΛબͼɺ൪߸Ͱ౴͑ͳ͍͞ɻ 1. Atsushi has already ( ᶃ eat ᶄ eating ᶅ eaten ) all the chocolate. 2. We call ( ᶃ he ᶄ his ᶅ him ) a chocolate monster. ʲղ౴ཝʳ 1 3 2 3 ̏
    ࣍ͷจΛಡΜͰɺԼͷ໰͍ʹ౴͑ͳ͍͞ɻ Today we live in the age of beer. In addition to major beer manufacturers, there are hundreds of small breweries all over Japan. They are called microbreweries and the beer they produce is becoming more and more popular because of its high quality. 1. Do you like beer? 2. What is your favorite brand? ʲղ౴ཝʳ 1 Yes, of course! 2 Sapporo Classic. ̐
    ࣍ͷ೔ຊจΛӳޠʹ௚͠ͳ͍͞ɻ 1. Θͨ͠͸͜ͷ͋ͱߴాഅ৔Ͱͨ͘͞Μ͓ञΛҿΈ͍ͨɻ 2. ࢓ࣄ͕଴͍ͬͯΔͷͰࡳຈʹؼΓͨ͘ͳ͍ɻ ʲղ౴ཝʳ 1 I am so ready to go to Takadanobaba and get drunk. 2 I don’t want to go back to Sapporo because there are so many things to do there. 10 20 20 30 80 ߹ܭ఺ ηΫγϣϯ ͝ͱͷಘ఺
76. • ࠓ೔ͷ࿩͸͜Ε·Ͱ͢΂ͯ߹ܭ఺ͷ͜ͱ • ηΫγϣϯ͝ͱͷಘ఺ͱ͍͏৘ใΛ͢Ͱ ʹࣦ͍ͬͯΔ • ͭ·Γ߹ܭ఺͸͢Ͱʹཁ໿͞Ε͍ͯΔ • ՄೳͰ͋Ε͹ཁ໿લͷ৘ใ΋ه࿥͓ͯ͠ ͖͍ͨ ߹ܭ఺
77. ηΫγϣϯ͝ͱͷಘ఺ • ߹ܭ఺Λܭࢉ͢ΔखؒΛল͚Δ • ߹ܭ఺ͷܭࢉϛεΛ๷͛Δ • ֶशऀʹ͍ͭͯΑΓৄ͘͠ཧղͰ͖Δ • ηΫγϣϯؒͷಘ఺ൺֱ • ฏۉͱඪ४ภࠩͰཁ໿ • ࢄ෍ਤͰՄࢹԽͯ͠ݸʑͷֶशऀͷ ֬ೝ
78. • ฏۉͱඪ४ภࠩͰཁ໿ • ࢄ෍ਤͰࢹ֮Խ • ʮ͜ͷΫϥε͸Ϧεχϯάͱൺ΂ͯϦʔ σΟϯά͕ۤखͳΑ͏ͩʯ • ʮจ๏ηΫγϣϯ͸σʔλͷ͹Β͖͕ͭ େ͖͍ͳʯ • ʮଜҪ͞Μ͸Ϧεχϯά͕ۤखͳͷ͔ͳʯ • ʮߐ઒͞Μ͸୯ޠ͕Μ͹ͬͯΔͳʯ ηΫγϣϯ͝ͱͷಘ఺
79. • ηΫγϣϯؒΛൺֱ͢Δ͜ͱͰৼΓฦΔ • ςετ໰୊ʢͷྑ͠ѱ͠ʣ • ֶश಺༰ • ࢦಋํ๏ɺֶशํ๏ • ֶशऀͷݸੑʢֶशελΠϧʣ ηΫγϣϯ͝ͱͷಘ఺
80. 10 20 20 30 80 ̍໰ͣͭͷ ಘ఺ 0 10 10 10 10 10 20 10 ̍໰ͣͭͷ ಘ఺ ̋̋தֶߍ
    ୈֶ̎ظதؒࢼݧ ֶ
    ೥ ̏ Ϋϥε 2 ࢯ
    ໊ Ken Urano ̍
    Ϧεχϯά໰୊
    ์ૹΛௌ͖ɺ࣍ͷ࣭໰ʹ൪߸Ͱ౴͑ͳ͍͞ɻ 1. What does Tora-san do? ᶃ He is a salesman. ᶄ He is a fisherman. ᶅ He is an entertainer. ᶆ He is a traveler. 2. Where does he live? ᶃ In Tokyo. ᶄ In Sapporo. ᶅ In Osaka. ᶆ He doesn’t have a home. ʲղ౴ཝʳ 1 3 2 4 ̎
    ࣍ͷจͷ ( ) ಺͔Βద੾ͳޠΛબͼɺ൪߸Ͱ౴͑ͳ͍͞ɻ 1. Atsushi has already ( ᶃ eat ᶄ eating ᶅ eaten ) all the chocolate. 2. We call ( ᶃ he ᶄ his ᶅ him ) a chocolate monster. ʲղ౴ཝʳ 1 3 2 3 ̏
    ࣍ͷจΛಡΜͰɺԼͷ໰͍ʹ౴͑ͳ͍͞ɻ Today we live in the age of beer. In addition to major beer manufacturers, there are hundreds of small breweries all over Japan. They are called microbreweries and the beer they produce is becoming more and more popular because of its high quality. 1. Do you like beer? 2. What is your favorite brand? ʲղ౴ཝʳ 1 Yes, of course! 2 Sapporo Classic. ̐
    ࣍ͷ೔ຊจΛӳޠʹ௚͠ͳ͍͞ɻ 1. Θͨ͠͸͜ͷ͋ͱߴాഅ৔Ͱͨ͘͞Μ͓ञΛҿΈ͍ͨɻ 2. ࢓ࣄ͕଴͍ͬͯΔͷͰࡳຈʹؼΓͨ͘ͳ͍ɻ ʲղ౴ཝʳ 1 I am so ready to go to Takadanobaba and get drunk. 2 I don’t want to go back to Sapporo because there are so many things to do there.
81. ͍ • ֶशऀʹ͍ͭͯ͞Βʹৄ͘͠ཧղͰ͖Δ • ςετ໰୊ͷධՁ͕Ͱ͖Δ • ೉қ౓ʢItem Facilityʣ • หผྗʢItem Discriminationʣ • ֶशऀͷೳྗΛ൑ผ͢Δਫ਼౓ ̍໰ͣͭͷಘ఺
82. • ޡ౴෼ੳ͕Ͱ͖Δ • બ୒ࢶͷྑ͠ѱ͠ΛධՁͰ͖Δ ʢDistractor Analysisʣ • ϚʔΫγʔτͷར༻ ղ౴ͦͷ΋ͷͷه࿥
83. σʔλͷཁ໿ ߹ܭ఺ ηΫγϣϯ͝ͱͷಘ఺ ̍໰ͣͭͷಘ఺ ղ౴ͦͷ΋ͷ ৘ใ͕ଟ͍ ৘ใ͕গͳ͍ ੔ཧ͢Δͱ
84. http://www.langtest.jp
85. • σʔλ෼ੳ͕ͳΜͰ΋ 
 Ͱ͖ͪΌ͏΋ͷ͍͢͝ 
 ΢ΣϒΞϓϦ • ςετͷ߲໨෼ੳ΋ 
 Ͱ͖·͢ • ਫຊಞ͞Μʢؔ੢େֶʣ ͕։ൃ͠ɺແྉͰެ։ • ͓ྱ͸Ϗʔϧ͔നϫΠϯ 
 ʢḺυωʣͰ
86. • σʔλ෼ੳ͕ͳΜͰ΋ 
 Ͱ͖ͪΌ͏΋ͷ͍͢͝ 
 ΢ΣϒΞϓϦ • ςετͷ߲໨෼ੳ΋ 
 Ͱ͖·͢ • ਫຊಞ͞Μʢؔ੢େֶʣ ͕։ൃ͠ɺແྉͰެ։ • ͓ྱ͸Ϗʔϧ͔നϫΠϯ 
 ʢḺυωʣͰ
89. ࣮ࡍͷղ౴ͱਖ਼ղ (answer keys) Λೖྗ͢Δ͚ͩͰɺ جຊతͳ߲໨෼ੳΛࣗಈͰ ߦͬͯ͘Ε·͢
90. • ਺ྔσʔλΛཧղ͢Δ • σʔλΛཁ໿͢Δ • σʔλΛਤͰද͢ • ϋϯζΦϯ (jamovi) • σʔλͷೖྗํ๏Λ࠶ߟ͢Δ • ςετͷ߲໨෼ੳ (langtest.jp) Ken Urano urano@hgu.jp https://www.urano-ken.com/research/let2023 ֶशऀσʔλΛʮݟΔʯ ―֎ࠃޠڭࢣͷͨΊͷσʔλͷೖྗɺ෼ੳɺղऍํ๏―