Showing papers on "Meaningful learning published in 1969"
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TL;DR: This paper investigated the difference in retroactive inhibition between meaningful and rote learning and found that meaningful learning can achieve more stable knowledge which is less vulnerable to interference learning compared with rote.
Abstract: The present study aimed at investigating the difference in retroactive inhibition between meaningful and rote learning.Ss, who were university students, were required to learn a series of 3 lists of paired-associates. S-term of each pair was a word and R-term was a NS or a combination of 2 or 3 NSs with English connectives (see Table 1). According to the kind of list, Ss were classified into 3 groups: M-M gr., Ss of which could learn both the second and third lists meaningfully, M-R gr., who could learn the second meaningfully but not the third, and R-R gr., who could learn neither of them meaningfully (Table 4).Ss learned Lists 1, 2 and 3 successively. After that, they were required to relearn List 2 and List 3. In each test session, which was given after the learning of one list, Ss were given a test of the list learned immediately before and tests of the other lists learned previously (Table 3). Performance of Ss at the test immediately after the original learning (List 2 or 3) and that of after the interference learning (List 3 or 2, respectively) were compared, in order to clarify the effect of retroactive inhibition.The results were as follows:1) When the original learning had been meaningful, the effect of retroactive inhibition was very small (Table 6 & 7). The mean reduction ratio in number of complete correct response was only 5.2%. In case of rote learning, however, the effect was much larger, i.e., mean reduction ratio was 53.6% (Table 9).2) Meaningfulness in interference learning was irrelevant to the size of the effect of retroactive inhibition (also Table 6-9).These results suggested that meaningful learning, compared with rote learning, can achieve more stable knowledge which is less vulnerable to interference learning.