The SAM model faces serious problems in accounting for long-term recency data<ref name=BjorkWhitten1974 /> and long-range contiguity data.<ref name=HowardKahana1999 /> While both of these effects are observed, the short-term store cannot account for the effects. Since a distracting task after the presentation of word pairs or large interpresentation intervals filled with distractors would be expected to displace the last few studied items from the short-term store, recency effects are still observed. According to the rules of the short-term store, recency and contiguity effects should be eliminated with these distractors as the most recently studied items would no longer be present in the short-term memory. Currently, the SAM model competes with single-store free recall models of memory, such as the Temporal Context Model.<ref name=HowardKahana2002/> In this study the impact of age and level of maturation on participants ability to recall images from STM was investigated. It was hypothesised that students who fell in the age bracket of sixteen and 18 years would have greater recall ability and perform better on the STM recall imagery test than, eleven to thirteen year old.
Additionally, the original model assumes that items in a particular list the only significant associations between items are those formed during the study portion of an experiment. In other words, it does not account for the effects of prior knowledge about to-be-studied items. A more recent extension of the model incorporates various features which allow the model to account for memory store for the effects of prior semantic knowledge and prior episodic knowledge. For years there has been investigation regarding the level and capacity of STM. past research that has influenced the experiment is Atkinson–Shiffrin memory model. The model asserts. The experiment is focusing on the 'short term store', which holds information for the duration of twelve seconds and has a capacity of 7 ± 2 items. this has influenced the researches amount of images presented and how long they are viewed for. The extension proposes a store for preexisting semantic associations; a contextual drift mechanism allowing for decontextualisation of knowledge, e.g. if you first learned a banana was a fruit because you put it in the same class as apple, you do not always have to think of apples to know bananas are fruits; a memory search mechanism that uses both episodic and semantic associations, as opposed to a unitary mechanism; and a large lexicon including both words from prior lists and unpresented words.<ref name=SirotinKimballKahana2005 />
