Vita:QuILT - Laptörténet

Pitlik, 2019. február 3., 10:54-n

2019-02-03T10:54:46Z

Pitlik, 2019. február 3., 10:51-n

2019-02-03T10:51:16Z

Pitlik, 2019. február 3., 10:35-n

2019-02-03T10:35:03Z

Pitlik, 2019. február 3., 10:33-n

2019-02-03T10:33:39Z

Pitlik, 2019. február 3., 10:24-n

2019-02-03T10:24:46Z

Pitlik, 2019. február 3., 10:23-n

2019-02-03T10:23:55Z

Pitlik, 2019. február 3., 10:23-n

2019-02-03T10:23:45Z

Pitlik, 2019. február 3., 09:14-n

2019-02-03T09:14:28Z

Pitlik: Új oldal, tartalma: „# Question/remark from independent Readers: Where is the professional content in the QuILT system? *Answer by the QuILT editorial board: Informatikai aspektusok a nem…”

2019-02-03T09:13:41Z

Új oldal, tartalma: „# Question/remark from independent Readers: Where is the professional content in the QuILT system? *Answer by the QuILT editorial board: Informatikai aspektusok a nem…”

Új lap

# Question/remark from independent Readers: Where is the professional content in the QuILT system?
*Answer by the QuILT editorial board:
Informatikai aspektusok a nem közvetlenül informatikai képzésekben, avagy a QuILT rendszer filozófiája: a tartalom mindenkor röptében illik, hogy keletkezzen! A deklarációk kora már vélhetően régen lejárt. A szómágikus agónia minden nap, mindenhol tetten érhető... A big-data-alapú világban BÁRKIT képessé lehet tenni, min. annyi deklaráció gyors felismerésére, amit eddig az "ige"-hirdetés keretében (talán nem is olyan néha ráadásul még nem is ritkán tévesen) hirdettek az arra felkentek. A konduktorok világa a big-data erőterekben a képessé válás elősegítése a szuverenitásra. A tudás immár nem a deklaráció képessége, hanem a deklarációk levezetésének képessége és a deklarációk egyedi visszaellenőrzésének, együttes konzisztenciájának levezetése. A fentiek/alábbiak hathatnak deklarációknak - de nem azok - "csak" vélelmek, melyek közös bizonyításra várnak, mely vagy megerősítő vagy elvető eredményre vezet - de a lényeg a bizonyítással töltött idő és a megtett út. A deklarációk elfogadása a hit világa. A knuth-i világ az, ahol tudásnak csak az számít, ami forráskódba át lehet írni. A bizonyítás folyamata már ma is forráskód, mely üzemanyaga az adat... Az oktatás során adatokat kell előállítani, feltárni és egyedül/közösen értelmezni. Bármilyen szómágikus deklarációt meg kell kísérelni bizonyítani - s közben persze el is lehet hinni, vagy éppen elvetni - szubjektíven, de a végső = objektív eredmény és az oda vezető út a lényeg. Akinek adatai vannak, az mindenhez ért, akinek deklarációi vannak, az néhány prófétán túl, folyamatos és súlyos hitelesség vesztések kockázatával áll szemben... Még a mindig részleges adatok alapján is fennáll a hitelességvesztés látszólagos veszélye, de ott, ahol az adatok alapján sem végleges, csak temporális deklarációk születnek, ott a módosítás szükségszerűségének felismerése nem vezet arcvesztéshez, hanem a személyiségfejlődés szerves része minden változás...

@@ 1. sor: / 1. sor: @@
 # '''Question/remark from independent Readers: Where is the professional content (like quality assurance, service design) in the QuILT-system?
 '''
-*Strategic answer by the QuILT editorial board: The question affects more than just the Quilt-system, it belongs also each course where the new approaches (like big-data and/or data mining) can still not be identified and the role of these new keywords should be found as soon as possible - but without any conflicts between the classic and the new teaching/learning strategies. The QuILT-system tries to generate content elements (like wiki-articles as specific definitions - still remaining in the world of the magic of words) during the logged actions catalyzed through the conductors. The time of the declarations (c.f. https://miau.my-x.hu/mediawiki/index.php/QuILT-parallelisms#Practice_before_Theory_with_experimental_possibility_for_the_theoretical_aspects) is probably over. The agony of the magic of words can always be seen overall. Everybody can be supported/conducted to become capable deriving of declarations based on the big-data-oriented world. The classic (text-oriented) declarations got created by human individuals in an intuitive way - mostly not failure-free. The classic validation could be ensured through the canon - it means: through subjective force fields. In contrary to the classic ways, conductors supports Students to become a sovereign individuals being capable of deriving of declarations instead of repeating them. The deriving of declarations is not a simple action, it involves quality assurance processes (c.f. plausibility and/or consistence checks). The above and the below listed sentences could be seen as a set of declarations, but these are not the same type of declarations as in the classic practices. Each derived declaration in the world of the data mining is "just" an assumption needed to always be discussed, to accept or reject in a temporary way. The important message is the flow, or with other words: the way during derivations will be executed. To accept a classic declaration is a kind of faith-driven action. The KNUTH-oriented world needs and supports objective evidenced where knowledge is what can be transformed into source codes. The evidence proving can be automated (even here and now) and the fuel of the new world are the data-assets. During learning processes it is necessary to produce data and to explore data sources in order to interpret them. The declarations based on the classic way should always be re-proven - and it is not relevant whether somebody believes them or not in a subjective way because the objective way of the derivations is the focused competence. Who has data is competent (in each aspect), however: who just has declarations will have problems with more and more high frequency. The data assets will always be partial and therefore the quality of the derived declarations is always critical. But the development of the personality needs the capability of handling with this kind of change management.
+*Strategic answer by the QuILT editorial board: The question affects more than just the Quilt-system, it belongs also each course where the new approaches (like big-data and/or data mining) can still not be identified and the role of these new keywords should be found as soon as possible - but without any conflicts between the classic and the new teaching/learning strategies. The QuILT-system tries to generate content elements (like wiki-articles as specific definitions - still remaining in the world of the magic of words) during the logged actions catalyzed through the conductors. The time of the declarations (c.f. https://miau.my-x.hu/mediawiki/index.php/QuILT-parallelisms#Practice_before_Theory_with_experimental_possibility_for_the_theoretical_aspects) is probably over. The agony of the magic of words can always be seen overall. Everybody can be supported/conducted to become capable deriving of declarations based on the big-data-oriented world. The classic (text-oriented) declarations got created by human individuals in an intuitive way - mostly not failure-free. The classic validation could be ensured through the canon - it means: through subjective force fields. In contrary to the classic ways, conductors supports Students to become a sovereign individuals being capable of deriving of declarations instead of repeating them. The deriving of declarations is not a simple action, it involves quality assurance processes (c.f. plausibility and/or consistence checks). The above and the below listed sentences could be seen as a set of declarations, but these are not the same type of declarations as in the classic practices. Each derived declaration in the world of the data mining is "just" an assumption needed to always be discussed, to accept or reject in a temporary way. The important message is the flow, or with other words: the way during derivations will be executed. To accept a classic declaration is a kind of faith-driven action. The KNUTH-oriented world needs and supports objective evidence where knowledge is what can be transformed into source codes. The evidence proving can be automated (even here and now) and the fuel of the new world are the data-assets. During learning processes it is necessary to produce data and to explore data sources in order to interpret them. The declarations based on the classic way should always be re-proven - and it is not relevant whether somebody believes them or not in a subjective way because the objective way of the derivations is the focused competence. Who has data is competent (in each aspect), however: who just has declarations will have problems with more and more high frequency. The data assets will always be partial and therefore the quality of the derived declarations is always critical. But the development of the personality needs the capability of handling with this kind of change management.
 *Operative answer by the QuILT editorial board: Students will be capable of identifying relevant keywords and defining them (c.f. wiki-articles with high-sophisticated definition structures and quality assurance techniques). Parallel, Students will be capable of creating expert systems both in a classic (manual-driven) and in a modern (inductive) way. Students will also be capable of checking consistence of expert systems and/or data assets. Students will be capable of modelling - in a context-free way but always for a chosen/given context/content/course... Quasi independent from the content/context, Students will be capable of an objective evaluating performances coming from own activities and/or from activities of other Students/Experts.

@@ 2. sor: / 2. sor: @@
 '''
 *Strategic answer by the QuILT editorial board: The question affects more than just the Quilt-system, it belongs also each course where the new approaches (like big-data and/or data mining) can still not be identified and the role of these new keywords should be found as soon as possible - but without any conflicts between the classic and the new teaching/learning strategies. The QuILT-system tries to generate content elements (like wiki-articles as specific definitions - still remaining in the world of the magic of words) during the logged actions catalyzed through the conductors. The time of the declarations (c.f. https://miau.my-x.hu/mediawiki/index.php/QuILT-parallelisms#Practice_before_Theory_with_experimental_possibility_for_the_theoretical_aspects) is probably over. The agony of the magic of words can always be seen overall. Everybody can be supported/conducted to become capable deriving of declarations based on the big-data-oriented world. The classic (text-oriented) declarations got created by human individuals in an intuitive way - mostly not failure-free. The classic validation could be ensured through the canon - it means: through subjective force fields. In contrary to the classic ways, conductors supports Students to become a sovereign individuals being capable of deriving of declarations instead of repeating them. The deriving of declarations is not a simple action, it involves quality assurance processes (c.f. plausibility and/or consistence checks). The above and the below listed sentences could be seen as a set of declarations, but these are not the same type of declarations as in the classic practices. Each derived declaration in the world of the data mining is "just" an assumption needed to always be discussed, to accept or reject in a temporary way. The important message is the flow, or with other words: the way during derivations will be executed. To accept a classic declaration is a kind of faith-driven action. The KNUTH-oriented world needs and supports objective evidenced where knowledge is what can be transformed into source codes. The evidence proving can be automated (even here and now) and the fuel of the new world are the data-assets. During learning processes it is necessary to produce data and to explore data sources in order to interpret them. The declarations based on the classic way should always be re-proven - and it is not relevant whether somebody believes them or not in a subjective way because the objective way of the derivations is the focused competence. Who has data is competent (in each aspect), however: who just has declarations will have problems with more and more high frequency. The data assets will always be partial and therefore the quality of the derived declarations is always critical. But the development of the personality needs the capability of handling with this kind of change management.
-*Operative answer by the QuILT editorial board: Students will be capable identifying of relevant keywords and defining them (c.f. wiki-articles with high-sophisticated definition structures and quality assurance techniques). Parallel, Students will be capable of creating expert systems both in a classic (manual-driven) and in a modern (inductive) way. Students will also be capable of checking consistence of expert systems and/or data assets. Students will be capable of modelling - in a context-free way but always for a chosen/given context/content/course... Quasi independent from the content/context, Students will be capable of an objective evaluating performances coming from own activities and/or from activities of other Students/Experts.
+*Operative answer by the QuILT editorial board: Students will be capable of identifying relevant keywords and defining them (c.f. wiki-articles with high-sophisticated definition structures and quality assurance techniques). Parallel, Students will be capable of creating expert systems both in a classic (manual-driven) and in a modern (inductive) way. Students will also be capable of checking consistence of expert systems and/or data assets. Students will be capable of modelling - in a context-free way but always for a chosen/given context/content/course... Quasi independent from the content/context, Students will be capable of an objective evaluating performances coming from own activities and/or from activities of other Students/Experts.

@@ 2. sor: / 2. sor: @@
 '''
 *Strategic answer by the QuILT editorial board: The question affects more than just the Quilt-system, it belongs also each course where the new approaches (like big-data and/or data mining) can still not be identified and the role of these new keywords should be found as soon as possible - but without any conflicts between the classic and the new teaching/learning strategies. The QuILT-system tries to generate content elements (like wiki-articles as specific definitions - still remaining in the world of the magic of words) during the logged actions catalyzed through the conductors. The time of the declarations (c.f. https://miau.my-x.hu/mediawiki/index.php/QuILT-parallelisms#Practice_before_Theory_with_experimental_possibility_for_the_theoretical_aspects) is probably over. The agony of the magic of words can always be seen overall. Everybody can be supported/conducted to become capable deriving of declarations based on the big-data-oriented world. The classic (text-oriented) declarations got created by human individuals in an intuitive way - mostly not failure-free. The classic validation could be ensured through the canon - it means: through subjective force fields. In contrary to the classic ways, conductors supports Students to become a sovereign individuals being capable of deriving of declarations instead of repeating them. The deriving of declarations is not a simple action, it involves quality assurance processes (c.f. plausibility and/or consistence checks). The above and the below listed sentences could be seen as a set of declarations, but these are not the same type of declarations as in the classic practices. Each derived declaration in the world of the data mining is "just" an assumption needed to always be discussed, to accept or reject in a temporary way. The important message is the flow, or with other words: the way during derivations will be executed. To accept a classic declaration is a kind of faith-driven action. The KNUTH-oriented world needs and supports objective evidenced where knowledge is what can be transformed into source codes. The evidence proving can be automated (even here and now) and the fuel of the new world are the data-assets. During learning processes it is necessary to produce data and to explore data sources in order to interpret them. The declarations based on the classic way should always be re-proven - and it is not relevant whether somebody believes them or not in a subjective way because the objective way of the derivations is the focused competence. Who has data is competent (in each aspect), however: who just has declarations will have problems with more and more high frequency. The data assets will always be partial and therefore the quality of the derived declarations is always critical. But the development of the personality needs the capability of handling with this kind of change management.
-*Operative answer by the QuILT editorial board: Students will be capable identifying of relevant keywords and defining them (c.f. wiki-articles with high-sophisticated definition structures and quality assurance techniques). Parallel, Students will be capable of creating expert systems both in a classic (manual-driven) and in a modern (inductive) way. Students will also be capable of checking consistence of expert systems and/or data assets. Students will be capable of modelling - in a context-free way but always for a chosen/given context/content/course...
+*Operative answer by the QuILT editorial board: Students will be capable identifying of relevant keywords and defining them (c.f. wiki-articles with high-sophisticated definition structures and quality assurance techniques). Parallel, Students will be capable of creating expert systems both in a classic (manual-driven) and in a modern (inductive) way. Students will also be capable of checking consistence of expert systems and/or data assets. Students will be capable of modelling - in a context-free way but always for a chosen/given context/content/course... Quasi independent from the content/context, Students will be capable of an objective evaluating performances coming from own activities and/or from activities of other Students/Experts.

@@ 1. sor: / 1. sor: @@
 # '''Question/remark from independent Readers: Where is the professional content (like quality assurance, service design) in the QuILT-system?
 '''
-*Answer by the QuILT editorial board: The question affects more than just the Quilt-system, it belongs also each course where the new approaches (like big-data and/or data mining) can still not be identified and the role of these new keywords should be found as soon as possible - but without any conflicts between the classic and the new teaching/learning strategies. The QuILT-system tries to generate content elements (like wiki-articles as specific definitions - still remaining in the world of the magic of words) during the logged actions catalyzed through the conductors. The time of the declarations (c.f. https://miau.my-x.hu/mediawiki/index.php/QuILT-parallelisms#Practice_before_Theory_with_experimental_possibility_for_the_theoretical_aspects) is probably over. The agony of the magic of words can always be seen overall. Everybody can be supported/conducted to become capable deriving of declarations based on the big-data-oriented world. The classic (text-oriented) declarations got created by human individuals in an intuitive way - mostly not failure-free. The classic validation could be ensured through the canon - it means: through subjective force fields. In contrary to the classic ways, conductors supports Students to become a sovereign individuals being capable of deriving of declarations instead of repeating them. The deriving of declarations is not a simple action, it involves quality assurance processes (c.f. plausibility and/or consistence checks). The above and the below listed sentences could be seen as a set of declarations, but these are not the same type of declarations as in the classic practices. Each derived declaration in the world of the data mining is "just" an assumption needed to always be discussed, to accept or reject in a temporary way. The important message is the flow, or with other words: the way during derivations will be executed. To accept a classic declaration is a kind of faith-driven action. The KNUTH-oriented world needs and supports objective evidenced where knowledge is what can be transformed into source codes. The evidence proving can be automated (even here and now) and the fuel of the new world are the data-assets. During learning processes it is necessary to produce data and to explore data sources in order to interpret them. The declarations based on the classic way should always be re-proven - and it is not relevant whether somebody believes them or not in a subjective way because the objective way of the derivations is the focused competence. Who has data is competent (in each aspect), however: who just has declarations will have problems with more and more high frequency. The data assets will always be partial and therefore the quality of the derived declarations is always critical. But the development of the personality needs the capability of handling with this kind of change management.
+*Strategic answer by the QuILT editorial board: The question affects more than just the Quilt-system, it belongs also each course where the new approaches (like big-data and/or data mining) can still not be identified and the role of these new keywords should be found as soon as possible - but without any conflicts between the classic and the new teaching/learning strategies. The QuILT-system tries to generate content elements (like wiki-articles as specific definitions - still remaining in the world of the magic of words) during the logged actions catalyzed through the conductors. The time of the declarations (c.f. https://miau.my-x.hu/mediawiki/index.php/QuILT-parallelisms#Practice_before_Theory_with_experimental_possibility_for_the_theoretical_aspects) is probably over. The agony of the magic of words can always be seen overall. Everybody can be supported/conducted to become capable deriving of declarations based on the big-data-oriented world. The classic (text-oriented) declarations got created by human individuals in an intuitive way - mostly not failure-free. The classic validation could be ensured through the canon - it means: through subjective force fields. In contrary to the classic ways, conductors supports Students to become a sovereign individuals being capable of deriving of declarations instead of repeating them. The deriving of declarations is not a simple action, it involves quality assurance processes (c.f. plausibility and/or consistence checks). The above and the below listed sentences could be seen as a set of declarations, but these are not the same type of declarations as in the classic practices. Each derived declaration in the world of the data mining is "just" an assumption needed to always be discussed, to accept or reject in a temporary way. The important message is the flow, or with other words: the way during derivations will be executed. To accept a classic declaration is a kind of faith-driven action. The KNUTH-oriented world needs and supports objective evidenced where knowledge is what can be transformed into source codes. The evidence proving can be automated (even here and now) and the fuel of the new world are the data-assets. During learning processes it is necessary to produce data and to explore data sources in order to interpret them. The declarations based on the classic way should always be re-proven - and it is not relevant whether somebody believes them or not in a subjective way because the objective way of the derivations is the focused competence. Who has data is competent (in each aspect), however: who just has declarations will have problems with more and more high frequency. The data assets will always be partial and therefore the quality of the derived declarations is always critical. But the development of the personality needs the capability of handling with this kind of change management.

@@ 1. sor: / 1. sor: @@
 # '''Question/remark from independent Readers: Where is the professional content (like quality assurance, service design) in the QuILT-system?
 '''
-*Answer by the QuILT editorial board: The question affects more than just the Quilt-system, it belongs also each course where the new approaches (like big-data and/or data mining) can still not be identified and the role of these new keywords should be found as soon as possible - but without any conflicts between the classic and the new teaching/learning strategies. The QuILT-systems tries to generate content elements (like wiki-articles as specific definitions - still remaining in the world of the magic of words) during the logged actions catalyzed through the conductors. The time of the declarations (c.f. https://miau.my-x.hu/mediawiki/index.php/QuILT-parallelisms#Practice_before_Theory_with_experimental_possibility_for_the_theoretical_aspects) is probably over. The agony of the magic of words can always be seen overall. Everybody can be supported/conducted to become capable deriving of declarations based on the big-data-oriented world. The classic (text-oriented) declarations got created by human individuals in an intuitive way - mostly not failure-free. The classic validation could be ensured through the canon - it means: through subjective force fields. In contrary to the classic ways, conductors supports Students to become a sovereign individuals being capable of deriving of declarations instead of repeating them. The deriving of declarations is not a simple action, it involves quality assurance processes (c.f. plausibility and/or consistence checks). The above and the below listed sentences could be seen as a set of declarations, but these are not the same type of declarations as in the classic practices. Each derived declaration in the world of the data mining is "just" an assumption needed to always be discussed, to accept or reject in a temporary way. The important message is the flow, or with other words: the way during derivations will be executed. To accept a classic declaration is a kind of faith-driven action. The KNUTH-oriented world needs and supports objective evidenced where knowledge is what can be transformed into source codes. The evidence proving can be automated (even here and now) and the fuel of the new world are the data-assets. During learning processes it is necessary to produce data and to explore data sources in order to interpret them. The declarations based on the classic way should always be re-proven - and it is not relevant whether somebody believes them or not in a subjective way because the objective way of the derivations is the focused competence. Who has data is competent (in each aspect), however: who just has declarations will have problems with more and more high frequency. The data assets will always be partial and therefore the quality of the derived declarations is always critical. But the development of the personality needs the capability of handling with this kind of change management.
+*Answer by the QuILT editorial board: The question affects more than just the Quilt-system, it belongs also each course where the new approaches (like big-data and/or data mining) can still not be identified and the role of these new keywords should be found as soon as possible - but without any conflicts between the classic and the new teaching/learning strategies. The QuILT-system tries to generate content elements (like wiki-articles as specific definitions - still remaining in the world of the magic of words) during the logged actions catalyzed through the conductors. The time of the declarations (c.f. https://miau.my-x.hu/mediawiki/index.php/QuILT-parallelisms#Practice_before_Theory_with_experimental_possibility_for_the_theoretical_aspects) is probably over. The agony of the magic of words can always be seen overall. Everybody can be supported/conducted to become capable deriving of declarations based on the big-data-oriented world. The classic (text-oriented) declarations got created by human individuals in an intuitive way - mostly not failure-free. The classic validation could be ensured through the canon - it means: through subjective force fields. In contrary to the classic ways, conductors supports Students to become a sovereign individuals being capable of deriving of declarations instead of repeating them. The deriving of declarations is not a simple action, it involves quality assurance processes (c.f. plausibility and/or consistence checks). The above and the below listed sentences could be seen as a set of declarations, but these are not the same type of declarations as in the classic practices. Each derived declaration in the world of the data mining is "just" an assumption needed to always be discussed, to accept or reject in a temporary way. The important message is the flow, or with other words: the way during derivations will be executed. To accept a classic declaration is a kind of faith-driven action. The KNUTH-oriented world needs and supports objective evidenced where knowledge is what can be transformed into source codes. The evidence proving can be automated (even here and now) and the fuel of the new world are the data-assets. During learning processes it is necessary to produce data and to explore data sources in order to interpret them. The declarations based on the classic way should always be re-proven - and it is not relevant whether somebody believes them or not in a subjective way because the objective way of the derivations is the focused competence. Who has data is competent (in each aspect), however: who just has declarations will have problems with more and more high frequency. The data assets will always be partial and therefore the quality of the derived declarations is always critical. But the development of the personality needs the capability of handling with this kind of change management.

@@ 1. sor: / 1. sor: @@
-# Question/remark from independent Readers: Where is the professional content in the QuILT system?
+# '''Question/remark from independent Readers: Where is the professional content in the QuILT system?
 *Answer by the QuILT editorial board:
 Informatikai aspektusok a nem közvetlenül informatikai képzésekben, avagy a QuILT rendszer filozófiája: a tartalom mindenkor röptében illik, hogy keletkezzen! A deklarációk kora már vélhetően régen lejárt. A szómágikus agónia minden nap, mindenhol tetten érhető... A big-data-alapú világban BÁRKIT képessé lehet tenni, min. annyi deklaráció gyors felismerésére, amit eddig az "ige"-hirdetés keretében (talán nem is olyan néha ráadásul még nem is ritkán tévesen) hirdettek az arra felkentek. A konduktorok világa a big-data erőterekben a képessé válás elősegítése a szuverenitásra. A tudás immár nem a deklaráció képessége, hanem a deklarációk levezetésének képessége és a deklarációk egyedi visszaellenőrzésének, együttes konzisztenciájának levezetése. A fentiek/alábbiak hathatnak deklarációknak - de nem azok - "csak" vélelmek, melyek közös bizonyításra várnak, mely vagy megerősítő vagy elvető eredményre vezet - de a lényeg a bizonyítással töltött idő és a megtett út. A deklarációk elfogadása a hit világa. A knuth-i világ az, ahol tudásnak csak az számít, ami forráskódba át lehet írni. A bizonyítás folyamata már ma is forráskód, mely üzemanyaga az adat... Az oktatás során adatokat kell előállítani, feltárni és egyedül/közösen értelmezni. Bármilyen szómágikus deklarációt meg kell kísérelni bizonyítani - s közben persze el is lehet hinni, vagy éppen elvetni - szubjektíven, de a végső = objektív eredmény és az oda vezető út a lényeg. Akinek adatai vannak, az mindenhez ért, akinek deklarációi vannak, az néhány prófétán túl, folyamatos és súlyos hitelesség vesztések kockázatával áll szemben... Még a mindig részleges adatok alapján is fennáll a hitelességvesztés látszólagos veszélye, de ott, ahol az adatok alapján sem végleges, csak temporális deklarációk születnek, ott a módosítás szükségszerűségének felismerése nem vezet arcvesztéshez, hanem a személyiségfejlődés szerves része minden változás...