chess {pks} | R Documentation |
Held, Schrepp and Fries (1995) derive several knowledge structures for the representation of 92 responses to 16 chess problems. See Schrepp, Held and Albert (1999) for a detailed description of these problems.
data(chess)
A list consisting of four components:
dst1
a state-by-problem indicator matrix representing the knowledge structure DST1.
dst3
the knowledge structure DST3.
dst4
the knowledge structure DST4.
N.R
a named numeric vector. The names denote response patterns, the values denote their frequencies.
Held, T., Schrepp, M., & Fries, S. (1995). Methoden zur Bestimmung von Wissensstrukturen – eine Vergleichsstudie. Zeitschrift fuer Experimentelle Psychologie, 42, 205–236.
Schrepp, M., Held, T., & Albert, D. (1999). Component-based construction of surmise relations for chess problems. In D. Albert & J. Lukas (Eds.), Knowledge spaces: Theories, empirical research, and applications (pp. 41–66). Mahwah, NJ: Erlbaum.
data(chess) chess$dst1 # knowledge structure DST1 chess$dst3 # knowledge structure DST3 chess$dst4 # knowledge structure DST4 chess$N.R # response patterns ## Precedence relation (Held et al., 1995, p. 215) and knowledge space B <- as.binmat(c("1000000000000000", # s "1100000011000110", # gs "1110000011000110", # egs "1001000011000110", # eegs "0000100010000000", # cs "1110110011000111", # gcs "0000001010000100", # ts "1110000111000110", # ges "0000000010000000", # f "1000000011000110", # gf "1000000011100110", # gff "1110001011010110", # ggff "1111001011101111", # ggf "0000000000000100", # ff "0000000000000010", # tf "1000000010000111")) # tff K <- as.binmat(closure(as.pattern(B, as.set = TRUE)) + set(set())) all(sort(as.pattern(chess$dst3)) == sort(as.pattern(K)))