The experiment seeks to measure the ability to distinguish and memorise the items one saw. There were sixty-seven participants all of them third year students who take the course Advance Topics in Cognition laboratory. Age and sex were not considered as variables and as such were ignored in the analysis of the results.
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The experiment was to use simple objects that might confuse the participants and be tricky to remember (high in conceptual distinctiveness) and some that would be easier to remember (or low in conceptual distinctiveness). Participants would be presented with items and then they would be asked if they have seen the item before in the experiment (old item) or haven’t (new item).
Human memory accesses or scans items in memory in a short-term old-new recognition memory task as proposed by Sternberg in the Sternberg paradigm. Different people scan their memory in different ways with different results with others being better than others in the scanning process (Sternberg, 1966).
The participants were presented with list of items and they were to identify if the item presented was from a previously presented list or if it was a new item. This was to give a result and enable a probe on the habits of the human brain in analysis and scanning of items and memory of the same.
The standard result having been declared by Stenberg, suggested that the mind scans all items in the mind to figure out whether the new item belongs to an old list of to a new list, hence, the more the items the more the response time needed to figure out. This is whether the target list is new or not.
This leads to exhaustion of the brain a factor which further reduces the time needed to respond to the item. Limited capacity parallel access theory and familiarity-based decision making theory have similar results with Sternberg’s RT. The exhaustive search shows consistent results with the mean RT too.
Limited capacity parallel access theory however differs in that it assumes that the items are accessed simultaneously but the memory comparison rate decreases as the set size increases. The simultaneous access causes the brain to reduce the effective time taken to compare the item with the items on the other lists.
On the other hand, the familiarity-based decision making theory the participants compare the target item to a global composite of all the items in memory; if the familiarity or similarity of the target to this composite memory reaches some threshold then the participants will identify whether the item belongs to the old list or it belongs to the new list (Nosofsky, 2011).
Should we obtain standard results in the experiment as of the above theories, it will indicate that the basic underlying architecture of memory access does not vary between the different item types (James, 2001).
If the slope sizes are different then this means that accessing the different items has different “costs”, either in terms of the time necessary to scan each item (i.e., a serial exhaustive model account), the capacity limitation placed on the rate of processing (i.e., a parallel model account) or the rate at which memory for individual items decreases with an item’s lag or its position on the list (i.e., a familiarity-based account).
- The total number of participants was 67, that is, all the 3rd year students enrolled in the Advanced Topics in Cognition Laboratory classes.
- Participants were tested in groups on lab computers running a MATLAB-based experiment designed using the Psychophysics toolbox (Brainard, 1997; Pelli, 1991).
- Objects used included items which were low in conceptual distinctiveness [earrings, fish hooks, salt & pepper shakers, child sip cups, computer keys, jack-o-lanterns, keyboards, microwaves) or high in conceptual distinctiveness [car fronts, juices, mp3 players, road signs, bill money, cigarette packs, coins, muffins] or
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The experiment started by displaying to the participants the various items of study. They were given 500ms to view the items and scan them in their memory.
After that, they would be asked to present the items they had scanned (saw during the first procedure), for this they were given 1000ms with 200ms break after each presentation. The memory set was varying in a range of 1 to 5. After the final study item was presented to the participant, an asterisk was placed for 1000ms to signal that the next digit presented was the test probe .
The item then had to remain on the screen until the participant made a response. This however was marked by as asterisk to indicate that more time was needed by the participant to identify the item. One was required to identify the item being presented to them if they had seen it before they would press the left button but if they think it was a new item then they would press the right button.
There were 67 participants but only 53 tests were regarded for analysis. This is because 12 of the data files were lost due to the computer error and 2 of the participants results were cancelled after they were found to be less than the average accuracy of all participants 3 x the standard deviation minus.
The major analysis was to focus on size 2 to 5 and as such we had trials which were had RT that were less that 200msec or greater than 3 x the std + the average of each of the investigated conditions. 1.24% of the trials were removed using this method.
Within each set size, we then compute the median RT for each set size x condition (high v/s low conceptual distinctiveness) x probe (present v/s absent) condition. Set size 1 was excluded from further analysis due to a lack of meaningful RT differences between the probe present and probe absent trials.
The High CD condition replicates the standard observed lag functions (e.g., Monsell, 1978)
The Low CD condition does the same but there is a slight increase in RT for long lists at lags 2 and 3. Note that because the probe’s lag position was not controlled but was just randomly allocated from trial to trial, there are markedly fewer trials at this point (N ~= 85) than at other points (e.g., lag 1, set size 1, N ~= 400). Consequently, the observed lag effect is not significant.
The questions in the questioner were open ended and difficult terms were defined to enhance the understanding of the questions. Simple and easy to conceptualize language was used in designing the questions. This was in a bid to enhance a clear understanding on the side of the respondent regardless of their literacy level.
Data obtained from the report was presented in form of tables and graphs. This was done to enhance ease in understanding as well as conceptualization of the results obtained. Tables and graphs aided in the summarization of information since they presented them in the simplest form possible (Little, 2011).
The briefing of results widened the scope of individuals able to access as well as understands the results. The complexity and tediousness that come with reading large volumes of text is thus reduced. A lot of information can hence be obtained by only a glance at the tables and graphs.
If the experiment gets results that are not concordant with the Stenberg result then this would provide a strong evidence against the above three mentioned theories. The standard Sternberg result is unable to adjudicate between these theories.
The slope of the set size function can still provide insight into how different types of stimuli are accessed or into how different clinical populations access items in memory (e.g., people with mental retardation have steeper set size slopes than people without mental retardation, Harris & Fleer, 1974).
This lab experiment will focus on the former by comparing lists of items which are conceptually similar and lists of items which are conceptually distinct.
In the present experiment, we compare old-new recognition performance for conceptually similar and conceptually distinctive items by using the Sternberg paradigm and varying a) the set size presented on each trial, b) whether the probe is present or absent on each trial and c) the category of items presented on each trial (i.e., either conceptually distinctive or conceptually similar items will be presented on each trial).
We are specifically interested in whether a) both types of items result in the standard Sternberg result and b) whether the slope of the set size function is equivalent between both types of items.
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