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Experimental and Theoretical Psychology
Home Page > Research > KOGNI > KOGNI2 Instruction
KOGNI2 Instruction
Introduction
Users from abroad might experience some problems when trying to use KOGNI2 because the instruction file KOGNI.TXT gives explanation only in German language. Therefore, the following text gives an explanation of how to install and how to use KOGNI2 software.
Installation
The program has to be installed in a folder called KOGNI. Within this folder, the program KOGNI2.EXE expects an input-file called KOGNI.DAT which contains the data to be analyzed.
Description of files in the folder
BEISPL.DAT: Sample data-set KOGNI.DAT: data-set to be used for data analysis (overwrite it with your own data!) KOGNI.LOG: Results of data-analysis in detailed form KOGNI.ERG: Results of data-analysis in compact form (useful for subsequent analyses) KOGNI.TXT: German instruction KOGNI2.EXE: The program ready to use KOGNI2.PAS: The program's source code (in TurboPascal)
Structure of input-file KOGNI.DAT
The input-file KOGNI.DAT must have the following structure:
Line 1: short text for description of the data - up to your choice Line 2: number of persons #p (which is equivalent to number of data-sets) Line 3: leave free Line 4: short description of person #1 or data-set #1 Line 5: number of generated concepts #c, space, number of groups constructed #g Line 6: leave free Line 7: concept c1: for each of the #g groups, code a 1 if the group has the concept c1 otherwise code 0 Line 8: concept c2: for each of the #g groups, code a 1 if the group has the concept c2 otherwise code 0 Line 9 etc. (repeat this until your last concept - you should produce as many lines as your number of generated concepts #c determines - Then: leave free line; next Line: start the same procedure with the next data set, i.e. - short description of person #2 or data-set #2 - number of generated concepts #c, space, number of groups constructed #g - leave free
Detailed explanation of example data set (BEISPL.DAT)
Imagine a setting where you give to a subject 30 concepts from a certain domain or mixed between different domains (instead of presenting the concepts to the subject, you could also let subjects generate the concepts of a given domain by themselves).
Then you give the subject a sorting task, that is, tell the subject he or she should sort the concepts in as many as possible ways. In our example data-set, there are data from two subjects: The first subject received/produced 30 concepts which were then grouped to 7 groups; the second subject received/produced 25 concepts which were then grouped to 3 groups.
Beispiel-Datei zu KOGNI2 <- Line 1: Title
2 <- number of subjects/data-sets
<- leave free
set 1, see FUNKE & HUSSY (1977) <- comment on data-set #1
30 7 <- 30 concepts, 7 groups
<- leave free
1 0 0 0 0 1 1 <- concept 1 of 30: used in groups 1, 6 & 7
0 0 0 0 0 0 0 <- concept 2 of 30: never used
0 0 0 0 1 0 0 <- concept 3 of 30: used in group 5
0 0 0 0 1 0 0 <- etc. etc.
0 0 0 0 0 0 0
0 0 0 0 1 0 0
0 0 0 0 1 0 0
0 0 0 0 1 0 0
0 0 0 0 0 1 0
0 0 0 0 0 0 0
0 1 0 0 0 0 0
1 0 0 0 0 0 0
0 0 0 0 0 0 0
0 1 0 0 0 0 0
0 0 0 0 0 1 0
0 0 0 0 0 1 0
0 0 0 0 0 1 0
0 0 0 0 0 1 0
1 0 0 0 0 0 0
0 1 0 0 0 0 0
0 0 0 0 1 0 0
0 0 0 1 0 0 0
0 0 0 1 0 0 0
0 0 0 0 1 0 0
0 0 1 0 0 0 0
1 0 0 0 0 0 1
0 0 1 0 0 0 0
1 0 0 0 0 0 1
0 0 1 0 0 0 0
0 0 0 1 0 0 0 <- concept 30 of 30: used in group 1
<- leave free
set 2 is complete fictitious <- description for data-set #2
25 3 <- 25 concepts, 3 groups
<- leave free
0 1 1 <- concept 1 of 25: used in groups 2 & 3
1 1 0 <- concept 2 of 25: used in groups 1 & 2
0 1 0 <- etc.
0 1 0
0 0 1
0 1 0
1 1 0
1 1 0
0 1 1
1 0 1
0 1 0
0 0 1
0 0 0
0 1 0
0 0 0
0 0 0
1 1 1
0 0 0
1 0 0
0 1 1
0 0 0
1 0 0
0 0 0
0 0 0
1 0 1
Output of sample data-set to be found in KOGNI.LOG
==============================================
Ergebnis-Datei für KOGNI2
==============================================
K O G N I 2
Ein Computerprogramm für die Berechnung
verschiedener Maße zur Erfassung
kognitiver Komplexitäten
==============================================
(C) 1977 und 1994
Reprogrammierung durch
Thomas Krüger
nach dem FORTRAN Programm
K O G N I
von Joachim Funke
==============================================
Bestimmt werden:
KK1: Bereichswissen
KK2: Bereichsgruppierung
KK3: dimensionale Komplexität
KK4: Dispersion
KK5: kognitive Independenz
KK6: relative kognitive Independenz
KK7: relativierte kognitive Independenz
Bedeutung der Maße siehe:
SCOTT,W.A. (1963).Cognitive complexity and cog-
nitive flexibility. Sociometry, 25, 405-414
HUSSY,W.(1977). Ein Beitrag zur Operationali-
sierung und Quantifizierung kognitiver Kom-
plexität. Archiv für Psychologie, 129, 226-241
============================================
Datenbezeichnung: Beispiel-Datei zu KOGNI2
Insgesamt Pers.: 2
============================================
VPn 1: Person 1 vgl. FUNKE und HUSSY (1977)
Anzahl Objekte: 30
Anzahl Gruppen: 7
KK1: 30.000
KK2: 7.000
KK3: 79.522
KK4: 3.256
KK5: 5.846
KK6: 0.835
KK7: 2.082
--------------------------------------------
VPn 2: Person 2 ist frei erfunden
Anzahl Objekte: 25
Anzahl Gruppen: 3
KK1: 25.000
KK2: 3.000
KK3: 87.404
KK4: 3.559
KK5: 2.873
KK6: 0.958
KK7: 1.813
--------------------------------------------
============================================
Output of sample data-set to be found in KOGNI.ERG
1 30 7 79.522 3.256 5.846 0.835 2.082 2 25 3 87.404 3.559 2.873 0.958 1.813
As you see, this is an abridged output compared to the long version given in KOGNI.LOG. It is better suited for subsequent data analysis with statistical packages like SPSS because of its rectangular data format, each line representing 1 subject/data-set containing current number, number of concepts, number of groups, KK3, KK4, KK5, KK6 and KK7.
Have fun with the program KOGNI2 and give feedback if you found the software useful! Mail either to Joachim Funke or Thomas Krüger.
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Last modified on 30.11.2001 by JF. |