STM & LTM Research

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  • Created by: lauren
  • Created on: 17-04-14 13:23
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  • Memory
    • STM
      • Capacity
        • Miller (1956)
          • Immediate Digit Span
            • ppts read a list of 1 syllable words/digits and asked to repeat immediately
              • Start with short list that gets longer until impossible to recall in serial order.
            • 7 +/- 2 items (between 5 & 9) Chunking improved number of digits recalled
            • Number of digits recalled increased with age
      • Duration
        • Peterson & Peterson (1959)
          • Trigrams
            • Showed trigram then asked to count backwards in threes from a large number for different amounts of time (2,6,9...18 seconds) - Distractor task
            • Approx 80% of trigrams recaled crrectly after 3 seconds of counting. Fell to fewer than 10% recalled correctly after 18secs.
            • Short term memory less than 20secs. Needs to be repeated to go into LTM otherwise it decays/gets displaced
      • Encoding
        • Baddeley (1966)
          • Cat/Mat Study
            • investigating whether encoding in STM is acoustic or semantic (by meaning)
            • ppts divided into 4 groups & each group heard a different list of five words
              • LIST A: acoustically similar 3 letter words eg. cat, mat sat
              • LIST B:  acoustically dissimilar 3 letter words eg. pit, day, cow
              • LIST C: Semantically similar (mean the same) words eg.big, huge, large
              • LIST D: Semantically dissimilar words eg. hot, safe, late
            • List A - 55% accurate ListB, C & D - up to 75% accurate
              • Encoding in STM is primarily acoustic as recall significantly lower for list A. Acoustic similarity causes most interference in recall. Recall is better in other conditions can conclude theres some semantic encoding in STM  & shuld not ignore that some encoding is visual, eg. facial recognition
    • LTM
      • Capacity
        • Difficult to estimate how much info can be stored in LTM as no one runs out of space. Therefore, it appears LTM has unlimited capacity.
      • Duration
        • Bahrick et al (1975)
          • Recall & Recognition with Graduates
            • investigators tracked down graduates from an American high school over 50 year period. 392 graduates shown photos from high school yearbook.
              • Recognition Group: each photo given with a list of names and ppts asked to match names to faces.
              • Recall group: ppts asked to name people in photos without a list of names.
            • Recognition Group: 60% accurate after 47 years
              • Recall Group: less than 20% accurate after 47 years
            • People can remember certain information for nearly a lifetime and very LTM seems to be better measured by recog tests rather than recall
      • Encoding
        • Baddeley (1966)
          • 'Cat/Mat' Study
            • Same as STM study except 20 minute delay between hearing the word list and recall
            • 55% correct - semantically similar 85% correct semantically dissimilar
            • LTM primarily uses semantic encoding as ppts struggled recalling words in the correct order when had similar meanings
            • Cat/Mat Study
              • investigating whether encoding in STM is acoustic or semantic (by meaning)
              • ppts divided into 4 groups & each group heard a different list of five words
                • LIST A: acoustically similar 3 letter words eg. cat, mat sat
                • LIST B:  acoustically dissimilar 3 letter words eg. pit, day, cow
                • LIST C: Semantically similar (mean the same) words eg.big, huge, large
                • LIST D: Semantically dissimilar words eg. hot, safe, late
              • List A - 55% accurate ListB, C & D - up to 75% accurate
                • Encoding in STM is primarily acoustic as recall significantly lower for list A. Acoustic similarity causes most interference in recall. Recall is better in other conditions can conclude theres some semantic encoding in STM  & shuld not ignore that some encoding is visual, eg. facial recognition

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