導入的概念地図法における概念分岐とクロスリンクについて

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ᑟධⓗᴫᛕᆅᅗἲ䛻䛚䛡䜛ᴫᛕศᒱ䛸䜽䝻䝇䝸䞁䜽䛻䛴䛔䛶

About the Concept Divergence and the Crosslink in Introductory

Concept Map Method

ⓙᕝ㻌 㡰

Jun Minagawa

せ⣙

ᑟධⓗᴫᛕᆅᅗἲ䠄Introductory Concept Map Method䠅䛻䛚䛔䛶䛿䚸Ꮫ⩦⤖ᯝ䛾ᡂ⦼䛻 ᙳ㡪䜢୚䛘䜛⊂❧ኚᩘ䛿䚸ṇ཯ᛂᩘ䚸ᴫᛕศᒱᩘ䚸䜽䝻䝇䝸䞁䜽ᩘ䛷䛒䜛䛣䛸䛜♧䛥䜜䛯䠄ⓙᕝ䠗 2009䠅䚹༑ศ䛻Ꮫ⩦䜢㐍䜑䛯ሙྜ䚸ᴫᛕศᒱ䛸䜽䝻䝇䝸䞁䜽䛸䛜ฟ⌧䛧䚸䛣䜜䜙䛜㔜ᅇᖐศᯒ䛻䛚 䛡䜛⊂❧ኚᩘ䛸䛺䜚䛘䜛䚹௚᪉䚸ṇ཯ᛂᩘ䛾䜏䛜ጇᙜ䛺⊂❧ኚᩘ䛸䛧䛶㔜ᅇᖐศᯒ䛻䛚䛔䛶᥇ᢥ 䛥䜜䜛ሗ࿌䜒ᩓぢ䛥䜜䜛䚹䛭䛣䛷ᮏ◊✲䛻䛚䛔䛶䛿䚸ពᅗⓗ䛻ඛ⾜◊✲䛻䛚䛡䜛Ꮫ⩦᫬㛫䜘䜚䜔 䜔▷䛟䛧䛶䚸᭱ึ䛾཯ᛂ䛷䛒䜛ṇ㐃᝿ᩘ䛜㔜せ䛺ᙺ๭䜢ᯝ䛯䛩᮲௳䜢タᐃ䛧ᐇ㦂䜢⾜䛳䛯䚹⤖ ᯝ䛿௬ㄝ㏻䜚ṇ㐃᝿ᩘ䛾䜏䛜㔜ᅇᖐศᯒ䛻䛚䛡䜛⊂❧ኚᩘ䛸䛧䛶᥇ᢥ䛥䜜䛯䚹ྠ᫬䛻Ꮫ⩦䛜䜘 䜚ᐃ╔䛧䛶䛔䜛䛸⪃䛘䜙䜜䜛ᐇ㦂ཧຍ⪅䛾᪉䛜䚸ṇ㐃᝿ᩘ䚸ศᒱᩘ䚸䜽䝻䝇䝸䞁䜽ᩘ䛜ከ䛔ഴྥ䛜 䜏䜙䜜䚸௬ㄝ䛿ᨭᣢ䛥䜜䛯䚹 䜻䞊䝽䞊䝗䠖ᑟධⓗᴫᛕᆅᅗἲ䚸㐃᝿ㄢ㢟䚸ศᒱ䚸䜽䝻䝇䝸䞁䜽 䛿䛨䜑䛻

ᴫᛕᆅᅗἲ䠄concept mapping䠅䛿䚸Novak & Gowin (1984)䛻䜘䛳䛶㛤Ⓨ䛥䜜䛯ㄆ▱ᵓ㐀䛾 እᅾ໬᪉␎䛷䛒䜚䚸䛛䛴䜘䜚ጇᙜ䛺ㄆ▱ᵓ㐀ᙧᡂ䛾䛯䜑䛾Ꮫ⩦᪉␎䛷䛒䜛䚹Novak 䜙䛿ᴫᛕ㛫 䛾య⣔ᛶ䚸䛸䜚䜟䛡ୖ఩ᴫᛕ䛛䜙ୗ఩ᴫᛕ䜈䛸⮳䜛㝵ᒙⓗయ⣔ᛶ䜢㔜ど䛧䛯䛜䚸䛭䛾ᚋ䛾ᒎ㛤䛻 䛚䛔䛶㠀㝵ᒙⓗ䛺ᴫᛕᆅᅗ䜒Ꮡᅾ䛧ᚓ䜛䛣䛸䛜ุ᫂䛧䚸䜎䛯Novak ⮬㌟䜒ᴫᛕᆅᅗᏛ⩦䜈䛾ᑟ ධ㐣⛬䛷㐃᝿ㄢ㢟䜢⾜䛖䛣䛸䜒ᥦ᱌䛧䛶䛔䜛䚹䛥䜙䛻䛭䛾ᚋ䚸㐃᝿ㄢ㢟⮬య䜢ᴫᛕᆅᅗ䛸䛩䜛ព ぢ䜒⌧䜜䚸ᴫᛕᆅᅗ䛸䛔䛖ᴫᛕ⮬య䛾ព࿡䛜ᣑᩓ䛩䜛䛻⮳䛳䛯䚹 䛭䛾䜘䛖䛺୰䛷ⓙᕝ(2009)䛿䚸㐃᝿ㄢ㢟䜢✚ᴟⓗ䛻ά⏝䛧䚸㐃᝿㐣⛬䛻䛚䛡䜛㝵ᒙᛶ䚸ᴫᛕ ศᒱ⌧㇟䠄㐃᝿䛥䜜䛯୍䛴䛾ᴫᛕ䛛䜙䚸஧䛴௨ୖ䛾ู䛾ᴫᛕ䛜㐃᝿䛥䜜䜛䛣䛸䠅䚸䜽䝻䝇䝸䞁䜻䞁䜾 䠄ᴫᛕ㐃᝿䛜㐍䜣䛷䛔䜛᭱୰䛻䚸␗䛺䜛ୖ఩ᴫᛕ䛻ᒓ䛩䜛ୗ఩ᴫᛕ㛫䛾⧅䛜䜚䛜ぢ䛔䛰䛥䜜䜛䛣 䛸䚹䛭䛾ሙྜ䚸䛭䜜䜙䜢䝸䞁䜽䛩䜛䚹䠅䛺䛹䜢᳨ウ䛩䜛䛣䛸䛻䜘䛳䛶䚸Ꮫ⩦⪅䛾ㄆ▱ᵓ㐀䜢▱䜛ᡭ䛜 䛛䜚䛜ᚓ䜙䜜䜛䛣䛸䜢ぢฟ䛧䚸䛣䛾䜘䛖䛺ព࿡䛷䛾㐃᝿ㄢ㢟䜢䛂ᑟධⓗᴫᛕᆅᅗ(introductory 1 _{ᒣ㝧Ꮫᅬ▷ᮇ኱Ꮫᗂඣᩍ⫱Ꮫ⛉}

concept map)䛃䛸⛠䛧䛯䚹 䛣䛾◊✲䛻䛚䛔䛶ⓙᕝ䛿䚸ᙜヱศ㔝䛾ヨ㦂ᚓⅬ䜢ᚑᒓኚᩘ䛸䛩䜛㔜ᅇᖐศᯒ䛻䛚䛔䛶䚸ᴫᛕ ศᒱ⌧㇟䛸䜽䝻䝇䝸䞁䜻䞁䜾⌧㇟䛸䛜䚸⊂❧ኚᩘ䛸䛧䛶᭷ຠ䛺䛣䛸䜢ぢฟ䛧䛯䚹䛣䛾⌧㇟䛿䚸ᴫᛕ⩌ 䛾Ꮫ⩦䛜㐍䜏䚸༢䛺䜛ṇ䛧䛔㐃᝿ㄒᩘ䠄௨ୗ䚸ṇ㐃᝿ᩘ䠅䛻䜘䛳䛶ヨ㦂ᚓⅬ䛜ㄝ᫂䛥䜜䛺䛟䛺䛳 䛯䛣䛸䜢ព࿡䛩䜛䛷䛒䜝䛖䛸⪃䛘䜙䜜䜛䚹ᴫᛕศᒱ⌧㇟䜒䜽䝻䝇䝸䞁䜻䞁䜾䜒䚸ᴫᛕ㛫䛾㛵㐃䛜య⣔ ⓗ䛻⌮ゎ䛷䛝䛯䛸䛝䛻⌧䜜䜔䛩䛔䛸⪃䛘䜙䜜䜛䛛䜙䚸㏫䛻䚸Ꮫ⩦⪅䛾༢ඖ⌮ゎ䛜㐍䜎䛪䚸㐃᝿ㄒ 䜒༢䛺䜛ᶵᲔⓗᏛ⩦䛻䜘䛳䛶ᬯグ䛧䛯䛰䛡䛾ሙྜ䚸ṇ㐃᝿ᩘ䛿䝔䝇䝖ᙧᘧ䛜グ᠈䛛䜙䛾෌⏕䞉෌ ௵䜢ಁ䛩䛣䛸䛜୰ᚰ䛾ᙧᘧ䛻䛚䛔䛶䛿䚸㧗ᚓⅬ䛻⤖䜃䛴䛝䜔䛩䛟䚸䛛䛴䛭䛾䜘䛖䛺ሙྜ䛻䛿ᴫᛕ ศᒱ⌧㇟䜒䜽䝻䝇䝸䞁䜻䞁䜾䜒䚸ෆᐜ䜢య⣔ⓗ䛻⌮ゎ䛧䛯Ꮫ⩦⪅䛻䛚䛔䛶䛾䜏㝈ᐃⓗ䛻⏕䛨䜛䛰 䛡䛷䛒䜝䛖䛛䜙䚸㔜ᅇᖐศᯒ䛻䛚䛔䛶ṇ㐃᝿ᩘ䛜᭷ຠ䛺⊂❧ኚᩘ䛸䛺䜛䛣䛸䛜⪃䛘䜙䜜䜛䚹 ᩍ⛉᭩䛾ෆᐜᢕᥱ䛸⌮ゎ䛸䛾㛵㐃䛛䜙䚸Ꮫ⩦⤒㐣䛻క䛖ᑟධⓗᴫᛕᆅᅗ䛻䛚䛔䛶䛿䚸ྛせ⣲ 䛿ḟ䛾䜘䛖䛻ኚ໬䛩䜛䛸⪃䛘䜙䜜䜛䚹 䜎䛪䚸ṇ㐃᝿ᩘ䛿ቑຍ䛩䜛䛷䛒䜝䛖䚹䛯䛰䛧Ꮫ⩦䛾᭱ึ䛾ẁ㝵䛻䛚䛔䛶䛿䚸䜎䛯Ꮫ⩦⪅䛻䜘䛳 䛶䛿䚸ᴫᛕྠኈ䛾⧅䛜䜚䜢୸ᬯグ䛩䜛⪅䜒ྵ䜎䜜䜛䛷䛒䜝䛖䚹ḟ䛻䚸᝿㉳䛩䜛ᴫᛕ䛾ᩘ䛜ቑຍ䛩 䜛䛻䛴䜜䛶䚸ᴫᛕศᒱ⌧㇟䛜⏕䛨䛶䛟䜛䛷䛒䜝䛖䚹䛭䛧䛶᭱ᚋ䛻䚸␗䛺䛳䛯ୖ఩ᴫᛕ䛾ୗ఩ᴫᛕ 㛫䛻᭷ព࿡䛺㐃⤖䛜ぢ䛔䛰䛥䜜䚸䜽䝻䝇䝸䞁䜽䛜⏕䛨䜛䛷䛒䜝䛖䚹䛣䛾䜽䝻䝇䝸䞁䜽䛿䚸Novak 䠃 Gowin(1984)䛻䜘䜜䜀䛂๰㐀ᛶ䜢⾲䛩䛃䛸䛾䛣䛸䛷䛒䜛䛛䜙䚸Ꮫ⩦䛜┦ᙜ䛻㐍䜣䛰⪅䛻䛚䛔䛶䛾 䜏⏕䛨䜛ྍ⬟ᛶ䛜㧗䛔䚹 䛭䛣䛷௒ᅇ䛿ពᅗⓗ䛻䚸ᴫᛕ㛫㛵ಀ⌮ゎ䜢ၥ䛖ᢥ୍ᘧ䝔䝇䝖䛾௦䜟䜚䛻䚸⥲ྜⓗ䛻▱㆑䜢ၥ䛖 ᙧᘧ䛾䝔䝇䝖䜢⏝ព䛧䚸㔜ᅇᖐศᯒ䛻䛚䛡䜛⊂❧ኚᩘ䛻䛴䛔䛶᳨ウ䛧䛯䚹௬ㄝ䛿䛣䛾ሙྜ䚸ୗグ 䛾䛸䛚䜚䛷䛒䜛䚹 ௬㻌 ㄝ 䠍䠊 Ꮫ⩦䛾⛬ᗘ䜢஦ᚋ䝔䝇䝖䛾ᡂ⦼䛷ศ๭䛧䛯ሙྜ䚸䠏⩌䛾ᚓⅬᕪ䛻㛵䛧䛶䛿஦ᚋ䝔䝇䝖ㄢ 㢟௨እ䛿䚸᫂░䛺᪉䛛䜙ṇ㐃᝿ᩘ䚸ศᒱᩘ䚸䜽䝻䝇䝸䞁䜽ᩘ䛾㡰䛻䛺䜛䛷䛒䜝䛖䚹 䠎䠊 ㅮ⩏䞉Ꮫ⩦᫬㛫䛜ẚ㍑ⓗᑡ䛺䛔ሙྜ䚸䛒䜛䛔䛿Ꮫ⩦⪅䛻ᶵᲔⓗ䛺ᬯグᏛ⩦䜢⾜䛖⪅䛜 ከ䛔ሙྜ䚸ศᒱᩘ䜔䜽䝻䝇䝸䞁䜽ᩘ䛿඲యⓗ䛻ᑡ䛺䛟䛺䜛䛸⪃䛘䜙䜜䜛䛯䜑䚸㔜ᅇᖐศᯒ 䛻䛚䛔䛶ṇ㐃᝿ᩘ䛜᭷ຠ䛺⊂❧ኚᩘ䛻䛺䜛䛷䛒䜝䛖 ௨ୖ䛾௬ㄝ䜢䜒䛸䛻䚸ᐇ㦂䜢⾜䛖䚹䛺䛚ᐇ㦂䛿䚸䛒䛟䜎䛷ㅮ⩏䛾୍⎔䛷䛒䜚䚸Ꮫ⏕䛾Ꮫ⩦䛾䛯䜑䛾 సᴗ䛷䛒䜛䚹 ᪉ἲ ᐇ㦂᪥᫬㻌2015 ᖺ 12 ᭶㻌 2 ᪥㛫 ᐇ㦂ሙᡤ㻌 ᒸᒣ┴ෆ㻌 X ኱Ꮫ Y Ꮫ㒊㻌 ᩍᐊෆ ᐇ㦂ཧຍ⪅㻌 ᒸᒣ┴ෆX ኱Ꮫ➨ 2 ᏛᖺᏛ⏕䚹⏨Ꮚ 3 ྡ䚸ዪᏊ 18 ྡ䚸ィ 21 ྡ䚹 ᡭ⥆䛝 ㏻ᖖ䛾ᤵᴗ᫬㛫䜢ά⏝䛧䛯䚹9 ᭶䛛䜙 3 䛛᭶㛫䚸ᩍᤵ䛧䛶䛝䛯Ⓨ㐩ᚰ⌮Ꮫ䛾ෆᐜ䜢⏝䛔䛯

㐃䛾䛒䜛ㄒྃ䛜ぢ䛴䛡䜙䜜䛯䜙䛭䜜䜙䜢⥺䛷⤖䜃䛺䛥䛔䚹䛭䛾㝿䚸⤖䜣䛰⌮⏤䜒᭩䛟䛣䛸䚹䛃 2 ᪥┠䠖䠄୍㐌㛫ᚋ䚹ண࿌䛺䛧䠅ヨ㦂๓ᶍᨃ䝔䝇䝖䛸⛠䛧䛶䚸䛂Ⓨ㐩ᚰ⌮Ꮫ䛃䛾䝔䝇䝖䜢⾜䛳䛯䚹ෆᐜ 䛿䚸෌ㄆၥ㢟䞉෌⏕ၥ㢟䚸ྛ10 ၥ䚸ྜィ 20 ၥ䚸ྛ 1 Ⅼ䛷䛒䛳䛯䚹 ⤖ᯝ 䜎䛪䝔䝇䝖⤖ᯝ䛿᭱㧗 15 Ⅼ䛷䛒䛳䛯䚹䛭䛣䛷஦ᚋⓗ䛻䠑Ⅼ้䜏䛻ୗ䠄0䡚5 Ⅼᮍ‶䠗5 ྡ䠅䚸୰ 䠄䠑䡚10 Ⅼᮍ‶䠗5 ྡ䠅䚸ୖ䠄10 Ⅼ䡚15 Ⅼ䠗11 ྡ䠅䛻⩌ศ䛡䛧䛯䚹 ⩌ูᚓⅬ䛿Table 1䡚Table4,Figure 1䡚Figure 4 䛾䛸䛚䜚䛷䛒䜛䚹

Figure 1 㻌 3 ⩌䛾䝔䝇䝖ᡂ⦼㻌 㻌 Figure 2㻌 ṇ㐃᝿ᩘ㻌 㻌 㻌 㻌 㻌 Figure 3 ศᒱᩘ TABLE 1 䝔䝇䝖ᚓⅬ 㻌 ୗ ୰ ୖ M 1.9 6.6 12.3 SD 1.2 0.5 1.8 TABLE 2 ṇ㐃᝿ᩘ 㻌 ୗ ୰㻌 ୖ M 1.2 8.4 12.5 SD 1.6 3.1 3.3 TABLE 4 䜽䝻䝇䝸䞁䜽ᩘ 㻌 ୗ ୰ ୖ M 0.0 0.4 1.2 SD 0.0 0.9 2.0 TABLE㻌 3 ศᒱᩘ 㻌 ୗ ୰ ୖ M 0.0 1.0 3.5 SD 0.0 1.0 3.1 0 2 4 6 8 10 12 14 ୗ ୰ ୖ

ṇ㐃᝿ᩘ

Figure 4 䜽䝻䝇䝸䞁䜽ᩘ ྛ せ ᅉ 䛾 ศ ᩓ ศ ᯒ 䜢 ⾜ 䛳 䛯 䛸 䛣 䜝 䚸 ᡂ ⦼ ู 3 ⩌ 䛾 䝔 䝇 䝖 ᚓ Ⅼ 䛿 ᭷ ព 䛷 䛒 䛳 䛯 (F(2,18)=93.7,p<.001)䚹Tukey 䛾᪉ἲ䛻䜘䜛ከ㔜ẚ㍑䛾⤖ᯝ䠄௨ୗ䚸ྠ䛨䠅䚸ୖ䠚୰䠚ୗ䛷䛒䛳 䛯䚹 ṇ㐃᝿ᩘ䛻䛚䛔䛶䚸3 ⩌䛾ᕪ䛿᭷ព䛷䛒䛳䛯䠄F(2,18)=25.5,p<.001䠅䚹ୖ䠚୰䠚ୗ䛷䛒䛳䛯䚹 ศᒱᩘ䛻䛚䛔䛶䛿5%Ỉ‽䛷ᕪ䛜ぢ䛔䛰䛥䜜䛯䠄F(2,18)=4.2,p<.05䠅䚹ୖ䠚୰䠚ୗ䛸䛺䛳䛯䚹 䜽䝻䝇䝸䞁䜽ᩘ䛻㛵䛧䛶䛿䚸䠏⩌㛫䛻᭷ពᕪ䛿ぢ䛔䛰䛫䛺䛛䛳䛯(p>.05)䚹 ḟ䛻䚸㔜ᅇᖐศᯒ䛾⤖ᯝ䛻䛴䛔䛶᳨ウ䛩䜛䚹 䝇䝔䝑䝥䝽䜲䝈᪉ᘧ䛾㔜ᅇᖐศᯒ䜢⾜䛳䛯䛸䛣䜝䚸䝰䝕䝹䛾୰䛻ᢞධ䛥䜜䛯⊂❧ኚᩘ䛿ṇ㐃᝿ ᩘ䛾䜏䛷䛒䛳䛯䚹䛣䛾᫬ᶆ‽⦅ᅇᖐಀᩘ䃑䛿0.8 䛸䛺䛳䛯䚹䠄Table 7 ཧ↷䠅 Table 6 ྛኚᩘ㛫䛾┦㛵ಀᩘ 䝔䝇䝖ᚓⅬ ṇ㐃᝿ᩘ ศᒱᩘ 䜽䝻䝇ᩘ 䝔䝇䝖ᚓⅬ 1 ṇ㐃᝿ᩘ .80*** 1 ศᒱᩘ .62** .62** 1 䜽䝻䝇ᩘ .33 .35 .27 1 ***p<.001, **p<.01 Table 7 ṇ㐃᝿ᩘ䛾䃑䚸t䚸ཬ䜃᭷ព☜⋡䡌䛸VIF 㻌 䃑 䡐 䡌 VIF ṇ㐃᝿ᩘ 0.8 5.71 0.001 1.00

⪃㻌 ᐹ ศᩓศᯒ䛾⤖ᯝཬ䜃㔜ᅇᖐศᯒ䛾⤖ᯝ䛸䜒䛻䚸➹⪅䛾௬ㄝ䜢ᨭᣢ䛧䛯䚹䛣䜜䛿䛔䜟䜀༑ศ䛺 ⌮ゎ䜢ᚓ䜛䛯䜑䛻䛿䜎䛪᫬㛫䜢䛛䛡䛶ಶ䚻䛾ᴫᛕ⌮ゎ䜢㐍䜑䜛䛣䛸䚸ᣦᑟ䛻䛚䛔䛶䛿ᴫᛕ㛫㛵 ಀ䛾⌮ゎ䜢ಁ㐍䛩䜛᪉ᘧ䜢⏝䛔䜛䛣䛸䛾኱ษ䛥䜢ព࿡䛧䛶䛔䜛䛸⪃䛘䜙䜜䜛䚹䜎䛯䚸ᐇ㦂ཧຍ⪅䛾 ᩘ䛾ၥ㢟䜒⤫ィⓗ䛺⤖ᯝ䛻ᙳ㡪䛧䛯䛣䛸䛿ணᮇ䛥䜜䛯䛣䛸䛷䛒䛳䛯䚹 䜽䝻䝇䝸䞁䜽ᩘ䜒ศᒱᩘ䜒䚸㔜ᅇᖐศᯒ䛻䛚䛡䜛⊂❧ኚᩘ䛻䛿᥇⏝䛥䜜䛺䛛䛳䛯䛜䚸⾲䜒䜾䝷䝣 䜒ᡂ⦼ඃ⚽⪅䛾⩌䛻䛚䛔䛶䚸䛭䜜௨እ䛾⩌䜢ୖᅇ䛳䛶䛔䜛䛣䛸䜢♧䛧䛶䛔䜛䚹≉䛻ศᒱᩘ䛿3 ⩌ 䛻᭷ពᕪ䛜ぢ䛔䛰䛥䜜䛯䚹 ௒ᅇ䛿༢⣧䛺䝔䝇䝖ၥ㢟䛾ሙྜ䚸ᶵᲔⓗグ᠈䛻㢗䜛Ꮫ⏕䛾Ꮡᅾ䜒᝿ᐃ䛧䛴䛴䚸䛒䛘䛶ṇ㐃᝿ ᩘ䛜᭱䜒኱䛝䛺ព࿡䜢᭷䛩䜛᮲௳䜢ぢฟ䛧䛯䚹௒ᚋ䛿෌䜃䚸ᣦᑟἲ䚸䝔䝇䝖ၥ㢟䚸ᣦᑟ᫬㛫䜢᳨ ウ䛧䚸䜘䜚῝䛔ㄆ▱ⓗ᝟ሗฎ⌮䜢せ䛩䜛⤖ᯝ䛸䛺䜛᮲௳䜢䛥䜙䛻᳨ウ䛩䜛ᚲせ䛜䛒䜛䛜䛭䜜䛿䛣 䜜䛛䜙䛾ㄢ㢟䛷䛒䜛䚹 ᘬ⏝䞉ཧ⪃ᩥ⊩

Ausubel,D.P. 1968㻌Educational Psychology: A Cognitive View. New York:Holt,Rinehart & Winston. Stewart,J. 1980 Techniques for Assesing and Representing Information in Cognitive Structure,

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Novak,J.D. & Gowin,D.B. 1984 Learning How to Learn. Cambridge University Press.

Okebukola,P.A. 1990 Attaining Meaningful Learning of Concepts in Genetics and Ecology: An Examination of the Potency of the CONCEPT-MAPPING Technique. Journal of Research in Science Teaching, 27,493-504 ⓙᕝ 㡰㻌 1999 ᴫᛕᆅᅗసᡂἲ䛻䛚䛡䜛䝸䞁䜽䝷䝧䝹సᡂ䛾ຠᯝ䛻䛴䛔䛶㻌 ᩍ⫱ᚰ⌮Ꮫ◊✲㻌 ,47,66-72 ⓙᕝ 㡰㻌 2009 ᑟධⓗᴫᛕᆅᅗ䛾ㅖせ⣲䛸ᢥ୍ᘧ䝔䝇䝖ᡂ⦼䛸䛾㛵ಀ㻌 ᮾிᮍ᮶኱Ꮫ◊✲⣖せ㻌 2,33-39 క ᾈ⨾䞉ⓙᕝ 㡰㻌 2010㻌 䛂኱Ꮫⱥㄒ⛉ヨ㦂䛾㡿ᇦูᚓⅬ䛸௚ᩍ⛉䛾ᚓⅬ䛸䛾㛵㐃䛻䛴䛔䛶Ɇᩍ⫱ᚰ⌮Ꮫヨ㦂 ᚓⅬ䜢౛䛸䛧䛶Ɇ䛃㻌 㻌 ᪥ᮏᩍ⫱ᚰ⌮Ꮫ఍➨ 52 ᅇ⥲఍Ⓨ⾲ㄽᩥ㻌 ⓙᕝ 㡰䞉క ᾈ⨾㻌 2012㻌 㐃᝿ㄢ㢟䛻䛚䛡䜛㐃᝿ㄒ㛫㛵ಀ䛻䛴䛔䛶㻌 ᪥ᮏㄆ▱ᚰ⌮Ꮫ఍➨㻌 㻌 㻌 㻌10 ᅇ኱఍Ⓨ⾲ㄽᩥ ⓙᕝ 㡰䞉క ᾈ⨾㻌 2013a㻌 యไ໬䛥䜜䛯グ᠈䛛䜙䛾᝿㉳㡰ᗎ㻌 ᪥ᮏㄆ▱ᚰ⌮Ꮫ఍➨ 11 ᅇ኱఍Ⓨ⾲ㄽᩥ ⓙ ᕝ㡰䞉క ᾈ⨾㻌 2013b యไ໬䛥䜜䛯グ᠈䛛䜙䛾᝿㉳䛻䛚䛡䜛᝿㉳㡰఩䛾ၥ㢟㻌 ᪥ᮏᩍ⫱ᚰ⌮Ꮫ఍➨ 55 ᅇ ⥲఍Ⓨ⾲ㄽᩥ

In Introductory Concept Map Method, it was shown that the autonomous

variable that influenced the result of the study result was a positive,

reactive number, number of concept divergences, and number of crosslinks

(Minagawa;2009). The concept divergence and the crosslink appear when

study is advanced enough, these become the autonomous variables in the

multiple regression analysis, and it gets it. On the other hand, the report for

which only a positive, reactive number is adopted as an appropriate

autonomous variable in the multiple regression analysis is seen here and

there. Then, it intentionally shortened a little in the present study than the

study time in the previous work, the condition that the number of positive

association that was the first reaction plays an important role was set, and

it experimented. As for the result, only the number of positive association

was adopted as an autonomous variable in the multiple regression analysis

according to the hypothesis. The experiment participant regarded that

study was more established at the same time was supported, and the

tendency with a lot of number of positive association, number of divergences,

and numbers of crosslinks was seen, and the hypothesis was supported.