4 THE CAUSES AND CONSEQUENCES

Of REMINDING

,\ aron S lkni ~l mi ll anJ Brian 1-1. Ro'>s

We survive and thrive by making efficient use of ou r knowledge. W hen specific prior events arc relevant to current si tuations, aspects of those past eve nts are retr ieved and gUide uS through the present. Someti me this remembering is deliberate, but often we are reminded less by force of our own will than by the sti mulus itself. Such instances of remind­ing reflect fundamental principles of associat ion by sim ilari ty, as noted by early theorists in psychology (James, 1890; Woodworth, In ]). Reminding is ubiquitous in higher cognit ion and daily li fe , and ha fo und a home in theoret ical developments ra nging fro m psychology to artificial intelligence.

It is thus surprising to find li ttle mention of the concept of remind­ing in the literature on human memory. This absence likely reflects a histor ical shorthand in memory research, whereby study phases of exper iments are considered to be encod ing eve nts and tests to be retrieval events . Current resea rch has dispenseJ with part of this false dichotomy: Tests are now known to be po tent learning events (Bjork, 1975; Karpicke & Roediger, 2008). The goal of th is chapter is to con­sider the place of retrieval in learning events , and to demonstrate that the concept of reminding provides a useful unify ing theme for mem­ory phenomena that otherwise lack theore tical coherence. As we will demonstrate, the consequences of reminding ca n only be understood by jointly conSidering the inherent trade-off between condit ions that

71

72 • Aaron S. B~ni alJl in and Bri an H. Ros"

promote likely reminding and conditions that promote potent remind­ing. This theoret ical position follows natura lly from the seminal work by the honoree of th is fes tschrift, which both demonst rated the pow­erful mnemonic consequences of retri eval (Bjork, 1975; Whitten & Bjork, 1977) and considered the t rade-off between li kely and powerful ret rieva l opportunities (Finley, Benjam in, Hays, Bjork, & Kornell, 2010; La ndauer & Bj ork, 1978).

RL\tlNDIJ'\G IN I IIGH FR COGNITION

In many areas of higher-level cognitio n, research has emphasized the abstract kn owledge people might use in accomplishing the task- rules or prototypes in categorization, domain -general p roblem -solving strat­egies. and generalized k nowledge schem as. However, in each area, researchers have fo und it important to eschew an exclusive focus on abstract knowledge and consider how people mi ght rely on the memor y for specitic earlier case:. to accomplish the tasks. Reminding is thought to be the mechanism by which these relevant specific instances are b rought to mind. In this section, we layout three domains in which reminding has played a role in ul1derstanding phenomena in b igher­level cognit ion .

Con cept LC(l l'll i lig

oncepts are the bas ic building blocks of cognit ion. They are critical in all cognjtive areas, so ho'''' they are acquired has long been of interet.t. Bruner, Good now, and Austin (1956) proposed an active hypothesis­test ing ro le for the learn er: the generation an d test ing of rules about what features or combinations offeatu res a llow accurate determ ination of whether an item is or is not a member of a con cept. Rosch ([ 975; Rosch & Mervis, 1975) later argued that concept representations should not be thought of as rul es , bu t as prototypes-a set of features that vary in how typ ical they arc of category members. Rather tha n either belong­ing or not belonging to the category, members could differ in how good a member they were as a funct ion 01' how many prototype features they contained. Thus, a robin is a typical bird because it has the most com­mon bi rd fea tures (feathered, Winged , small; ilies, sings, eab worms, nest s in trees) , whereas a peng uin is a les!> t ypical bird because it is large, does nl)t t1y, and eats fi sh. New items are class ified by the prototype they are most simi lar to, and th is same representation is llsed to classify all the instances in the category.

This reliance on building up and using abst ract knowledge was chal­lenged by both Medin (Medin & Schaffer, 1978) and Brooks (1978) ,

'Ih", Cau~cs anJ Consequences of Rern inding • 73

who argued that pro toty pe views are inadequate as conceptual repre­sentations. Rather, people often use much more specific knowledge in making classification judgments . The th rust of th is exemplar view is that our memory is constantl y encoding specific knowledge, with items conSist ing of related featu res and connections to context, and that the presentation of a new item prohes memory for similar knowledge. The retrieval of simila r items provides a useful means of determ ini ng cate­gory membership; items that are very similar are likely to be in the same category. The importance of this proposal is twofold. First, because it avoids the need for a generalitation mechanism for prototypes, the assumption is simply that people store ill formation about specific items from their interactions with these items. Second, it allows for add ress­ing the various complexit ies one fi nds in categories , such as correlations among feat ures. For exa mple, typical birds are small and sing, but it wo uld be unusua l for a large bird to sing. The set of exemplars encodes these correlations.

The exemplar view is powerful, and has genera lly proven superior to prototype views in di rect comparisons (e .g., Murph y, 2002; Ross & Makin, 1999). In the case of a new item that is ve ry typica l, it will be similar to many earl ier items and thus easy to qu ick ly claSSify. An atypical item wi ll be sim ilar to far fewer items, a nd will be more dif­ficult to claSS ify. TIle exem plar view has been extended in a number of ways, including provid ing an independent means of assessing simi­la rity (Nosofsky, 1986) and a learn ing model that tunes the weigh t of various fea tures (Krusch ke, 1992). More recentl y, hybrid models have been in troduced that include an exemplar component along w ith a rule learni ng m odule (Erickson & Krusch ke, 1998). Some recent mod­els challenge some aspects of how the speci fic knowledge of exemplars may influence classificat ion (e.g., Love, Med in, & Gureckis, 2004), but no one quest ions the idea that specific knowledge influen ces classifica­tion. Even real-world tasks have shown large intluences of thi !> sort-for example, diagnose!> by physician s wit h much experience in d iagnosing dermatology cases are influenced by similar ities to recently seen spe­cific cases (Broo ks , Norman , & Allen, 1991).

For unusua l items, or items early in learning, remindings are particu­larly common. They ca n influence classification and affect lea rners' u nder­standing of the category (e .g., Ross, Perkins , & Tenpenny, 1991). Even if a simple rule is given to learners and applied to new items, those new items that are very similar to earlier items m ay be classified differently than the rule predic ts (Allen & Brooks, 1991). This research shows the impor­tance ofspecific rem indings in understanding classification behavior, and reveals that such behavior relies on more than abstract knowledge.

N • Aa ron S. BenJa mi n a nd Bria n H Ross

Problem Solvillg {}y A Il a logy

Problem solving is ubiquitous and important in everyday cogn itive activi­ties. Early developments in the field emphasized a characterizat ion based on a representation of the problem as a problem space (the knowledge one has of the relevant world states and operators for tran sfo rming states) and the search of this space to find the goal slale (Newell & Simon, 1972). Problem solving by analogy occurs when we try to solve a new problem by reference to an earlier problem and its solution. For example, students asked to solve a homework problem in a math course often look back through the book for similar examples . Problem solving often involves being remi nded ofan earl ier experience and adapting it to the current situation.

Gick and Holyoak (1980, 1983) presented a series of studies that examined how people solve problems by analogy. The target pro blem was Duncker's tu mor problem: A palient has a t umor th at cannot be operated on, and the x-ray strength that can kill the tumor would also kill healthy tissue, resulting in death . The convergence solution is to position a <;e t or lower-intensit r machines a round the body and have them converge at the tumor. Before attempting a solution to this prob­lem, some subjects read a story about a genera l attacking a fort ress tha t had roads to it m ined to allow on ly sm all work de tail s. He succeeded by split ting up his forces and havi ng them converge on the fortress . Having this earlier experience increased the use of the co nvergence strategy for the tumor p roblem from 10 to 30%, but even th is success rate is unimpress ive. Perhaps they did not understand the story? No, when asked to sum marize the story, perform ance was no beller. Perhaps they did not understand the principle? NQ, when the principle was made explicit ("The genera l attribu ted his success to an important principle: If you need a la rge force to accomplish some purpose, but are prevented from applying such a force, man y smal l fo rces applied si multaneously from different directions m ay work just as well"), performance wa~ no better. Perhaps they did no t t hink back to the ea rl ie r problem (i.e., ge t reminded)? Yes, when told they might want to use the earlier general story, perform ance increased to an impressive 80%.

Remind ings are critical in learning through analogical problem solving. W ithout a teacher to tell the learner what earlier example to use, remind ings determin e whether the learner tries to apply an appro­priate earlier solution that might help solve t he current problem and perhaps help to learn to solve problems of this type, or tries to apply an inappropriate earlier solution unsuccessfully.

What affects which earlier experiences people get reminded of? Remindin gs are memory retrievals-the solver p robes memory with

rile Cau, es UIl J Conscq ut: nces l ) f Re m ind ing • 75

an initial analysis of the problem and retrieves exper iences that match this in some respects. Experts may be able to make a deep analysis of a problem to be rem inded of earlier problems with the same deep struc­ture. However, novices often have more superficial analyses and char­acterize the problem in terms of the particula r objects mentioned in the problem, such as the par ticu la r story content of a word problem (Chi, Feltovich, & Glaser, 1981; Ross, 1984). Although theories differ on what in fl uences remind ing, all propose that the remembering of an ear­lier example critically influences cLlrrent problem solving (see Reeves & Weisberg, 1994, for a critical review). In addition, to the extent that remindings allow comparisons that might promote gen eralization, th ey may play an important role in learning within a domain (e.g., Gick & Holyoak, 1983; Ross & Kennedy, 1990).

Remindings are an impor tant aspect or problem solving by analogy, a prevalent means of problem solving. In m any cases, people do not reI}' on abstract knowledge, such as problem schemas or general rules, but th ink back to a specific ea rlier example and LIse that to help solve a

current problem.

Ulldersta ll di/lg

One can th ink of the goal of understanding as the construction of an integrated representat ion that combines an input with prior knm...·ledge. Early theories that attempted to bri ng prior knowledge to bear ran into a major obstacle-so much knowledge and so many in ferences were needed that processing would not be possible in any reasonable time, for either people or m achines (Rumelhart & O rtony, 1977; Schank & Abelson, 1977). ll1e schema was an attempt to overcome this obstacle (e.g., Rumelhart & Ortony, 1977) . A schema is a generalized knowledge structure that is used for unders tanding. Ra ther than combining all the relevant prior knowledge each t ime it is needed, the schema comes prepackaged: Those situations one h as faced a number of times before access a schema that already contains the relevant pr ior knowledge, inferences, a nd slots for understanding that particula r situation. For example, one has general knowledge of a buying/selU ng situation, with an understanding that the buyer gives some money (a func t ion of what is being bought), the seller su rrenders ownership of the item, and so on. For routine events that include knowledge very similar from time to time (e.g., going to a restaurant), even greater amounts of prior knowl­edge can be speCi fi ed (Schank & Abelson , 1977).

Schemas have become an important idea in a wide variety of psy­chological domains, as well as in art ificial intelligence. Psychological research has foun d evidence of the existence and use of such abstract

76 • Aaron S. Benjam in and !ir ian H Ross

knowledge str uctures (e .g., Bower, Black, & Turn er, 1979). However, there have also been ind ications in both psychological domains and artificial intelligence research that these large knowledge structures may sometimes be too large or inflexible, and that sometimes spec ific experiences may playa role. For exam ple, Bower et al. (1979) fou nd confusions in recalling informati on from schemata that sha red simi­lar parts , such as waiting rooms for doctors and dentists, sugges ting that the overall "script" might be composed of smaller parts that are used across similar situations (such as waiting rooms and payments for health professionals). Schank (1982) argued that computer progra ms intended to acquire structures must build them up from specific earlier experiences. In processing a new exper ience, one might be guided by the general knowledge, but might also activate the specific earlier expe­riences if the situation is new or unusual. For example, if a restaurant experience involved someone choking on a chicken bone, a si mi lar ear­lie r experience m ight well be thought of and the relevant information utilized . A si milar use of remind ings can underlie p roblem solving by novices, as noted earlier (e.g. , Ross, 1984).

he idea of using spec ific episodes for understanding has been very influent ial in machine learni ng, leading to a new area of research called case-based reasoning. It allows the analysis of current situat ions to be processed in terms of ea rlier cases rat her than by abstract knowledge alone. Earlier cases might help in a variet)' of ways, such as foc USing on the important aspects, helping J evise a pl an, or providing information about what led to fail ure in a previous sim ilar situation. Even in rela­tively si mple reacU ng comprehension situations, people may t bink back to earlier texts to help interpret the current one (Gentner, Ratlerman n, & Forbus, 1993; Ross & Bradshaw, 1994).

REM [NDING [1\ SIM PLE Mb\10RY TASKS

The preceding examples reveal how mem ories fo r individual events and stimuli subserve a var iety of intellectual sk i! Is , and sugges t that remind ing is the mechanism by which those memories are efficient ly uti lized . If rem inding underlies those many cogn itive capacities, then we should be able to detect footprints of it in basic memory tasks. The type of rem inding we all experience occurs not only when being at a wedding reminds us offunny things t hat happened at a previous wed­di ng, but also when digging an old toy out of th e attic remind s us of a ch ild hood experience with that lay. Rem ind ing takes place not only for complex situations and mappings, but a lso-and maybe even more frequently-for simple individual elements in our lives. Basic memory

The Causes and Conseguences 01 Remi ndin g • II

parad igms, in which people are ~sked to remember st imuli li ke words and pictu res, seem a fer ti le ground for seeking evidence for reminding for simple materials.

We star t that search in tasks in wh.ich related materials are presented at different times , and conc; ider four common experimental paradigms. In each case we ask: If rem ind ing were taking place, what would t he consequences be? Two fundamental considerat ions from well -estab­lished memo ry research guide how we answer that question (Benjamin & Tullis, 2010). Fir st, because we forge t things, reminding is less likely at longer intervals. Second, although longer interval:, dec rease the proba­bility of reminding, they increase the mne mon ic potency of rem ind ing. That is, because more laborious ret r ieval enhances memory more than easy retr ieval (Gardiner, Cra ik, & Bleasdale, 197 1; Ka rpicke & Roediger, 2008; Slamecka & Graf, 1978), difficult reminding enhances memory more for the reminded (i.e., ret rieved ) event than does easy rem inding. Thus, the product of rem inding can reveal a trade -ofF between likely and potent re tr ie\'al: if the rem indin g cue is too late, little reminding occurs and consequently litt le benefit accrues; if rem inding is too ~oon, reminding occurs but the benefits are m ini mal.

,\Jc/Ilo ryfor Repealed Malerials

The most straightforward case of relat ionship is iden tity, and so the best remind i ng cue for a previou<; event is likely to be a repeti tion of that event. The mos t com monly employed repetit ion paradigm is one in which the lag between the repet itions is var ied; such experiments reveal the ubiqu itous spaci ng a nd lag effec ts , in which greaLer dis­tance between th e repeated events leads to superi or memory for the event (Ebbinghaus, 1885/ 1962; Melton, 1970) . Predomi nant explana­tions fo r this effec t include a role for the greater encod ing variab il ity afforded by more temporally variable study contexts (Bower, 1972; Estes, 1955) as well as the attenuated processing induced by close rep­etitions (H intzman, 1974), but the effec ts may be more parsimoniously Llnderstood by conSidering the consequences of remindi ng (Benjamin & Tull is, 2010 ; Hintzma n, 2004).

Let us conside r what the benefits of rem ind in g wo uld look like in such a paracUgm. As outl ined ea riler, the probabili ty of rem inding decreases with increasing intervals and the potency of the remi ndi ng increases with increaSing interval (d iffic ulty) . TI1erefore, there should be a sweet spot at which the probability and potency of remind ing com­bine to produce maximal benefib - that is, spacing functions ShOlllJ be nonmonotonic with lag. I n addition, because performance reflects not the increasing independence of events (as in encod in g variability

78 • Aaron~. Benjam i_n and Brian H. Ross

theories) , but rather reveals a joint function of their dependence (which promotes probable reminding) and independence (which promotes difficult retrieval and thus powerful reminding), such theories can accommodate superaddit ive levels ofperfo rmance. Thi s is true because, although events can be no more independent than perfec tly uncorre ­lated-an assum ption that leads encoding variability to be inconsistent with superadditivity-theories that postulate interaction between the two events, like reminding, are not limited in that way. These two phe­nomena are shown in Figure 4.1, which plots data simulated from a reminding model of repetition proposed by Benjamin and Tullis (2010). Finally, because association is at the heart of reminding, no benefits should be apparent for unrelated materials-that is, materials that are unlikely to remind the learner of each other.

Each of these predictions is borne out in da ta. Spacing funct ions can be and often a re nonmonotonic (Benjamin & TuJi is , 2010 ; Peterson, Wampler, Kirkpatrick, & Saltzm an, 1963), reveali ng that , once the prob­ability of remi nding is suffi ciently low, the ne t benefits sta rt to decrease with additional spacing. In addi tion, superaddit ivity is ubiquitous (Begg & Green, 1988; Benjamin & Tu llis , 2010), revealing itself at lags as short as five interven ing items and evident in more than 60% of experimen­tal conditions in the li te rat u reo Finally, no spacing benefit is evident for unrelated words (Ross & Landauer, 1978); that is, the probability of

05

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~ ~

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0. 2 0 2 4 6 !l 10 12

Ldg Between PI and P2

Figure 4.1 Predicted performance for the rem inding model proposed by Benjamin and Tullis (2010) . Solid line represents memory for the item presented at PI as a function of th e interval between PI and P2. Dashed lined represents the superaddilivity baseline (i.e., the probab il ity sum ­mation of remembering one of two things). Baseline performance is set to 0 2, the forgetting rate is 0.7, and the probability of reminding is 0.9.

The Ca uses and Conseq uences of Reminding • 79

remembering one of two different words does not vary with the i ntervaJ between the words. According to rem inding theory, such a result is the ob '.'ious consequence of the fac t that the second word does not remind the reader of the ti rs t, and thus does not initiate retrieval of it.

Evidence for the theoretica l value of reminding is also apparent in tasks in which items are repeated and memory is tested by evaluating judgments of the recency of an item's occu rrence (Hintzman, 2010) and memory for the frequency of an item's occurrence (Hintzman, 2004). In each of these tasks, as in recognition more generally, other perspectives have failed to provide an adequate account of ex tant phenomena.

,"femoryJor Selllantically Related Materials

One benefit of th ink ing about repetition as si mila r ity- induced remind­ing is that the principles generalize easily to near-repetition paradigms, in which synonyms or related words are presented. The same principles applied to repetition paradigms can be used to de rive simple predic ­tions about the effects of lag of memory for related materials , and about the effects of pure versus near repeti tion on memory.

Because associates are less s im ilar to one anot her than are repeti­tion s, both the probability of rem inding a nd the potency of remind ­ing are changed. For exam ple, a second presentation of king is likely to remind one of an earlier presentation of ki ng, but it could also remind one ofqueen . Ifone had seen queen earlier in the list, a later presentation of king would be expected to have d ifferent consequences than ham­burger for remind ing. 1he probability of a word rem indi ng the learner of a related word from earlier in the list wou ld drop off more qUickl y than would the probability of a repet it ion doing so, but the potency of the reminding would be commensurately greater. The net effect is that the "sweet spot" in the trade-off is ea rlier in t ime than fo r repetitions. This effect can be seen in the top panel of Figure 4 .2 , in which two lag functions are simulated from the Benjamin and Tullis (2009) model­one of which has a very high probability of reminding (as one would expect for repet itions), and one of which has a slightly lower probability of reminding (as one would expect for related associates). Note that, as expected, the performance m aximum is earlier in time (in fact, at the shortest interval) for associates than for repetitions.

These predictions can be compared to data from an experiment reported by Hintzman et al. (1975, depic ted in the bottom panel of Figure 4.2). One noteworthy feature of t hese results is that, if the pre ­sentation of t he two events is close together in ti me, memory for the first word is superior if the second word is an associate than if it is a repetition . This reflects the fact that event dissi m ilari ty fosters more

---

80 • Aaron S. Bt:njamin and Brian H . Ross

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0.35 +1---------_ OJ Repeated

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0. 2 +!-----.----~----~---_,------._---~ o 2 4 6 8 to 12

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0 9 I ~

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0.75 +1---.-----r----.-----,.----,------.__--I -5 o 5 10 15 20 25 30

Lag Between PI and P2

Figure 4.2 Top pa nel: Predicted performance of the rem in ding model for memory for an event at PI fol lowing a repetition (darker line) or fol lowing a presentation of a related associate (lighter line). Bottompanel: Datafrom an experiment by Hintzman (1975) showing a simi lar pattern tor analogous conditions

poten t relr ieva l- thus, being reminded of an event by an associate involves more laborious and thus more mnemon ically enha ncing retrieval. However, because reminding is increasingly u nlikely at long lags, the ea rl ier advantage of dissimila rity becomes a disadvantage as t he in terval is increased. Picki ng a cue for maximal mnemonic enhancement of the reminded event must thus be tied to the requi red interval between learning opportunities.

-nle Causes a nd Cn n, cg uences of Rel1l inJ ing • 81

teant illg ill A-B A-C Paired-Associlltc tasks

There is a large literature on the effects of cue repetition in the literature on proactive and retroactive interference in pai red-associate learning (Keppel, 1968). That perspective is quite clear: Because increasing the nu mber of associates to a common retr ieval cue has negative effects on the ret rieval of any given ta rget item (see also Anderson, 1974), COI1 ­

ditions under which cues are repeated should lead to poorer memory for the associated targets. For example, studying apple-mail followed by apple-house should make it more difficult to remember mail when presented wiLh apple on a later test. In more abst racl terms, memory for B given A followi ng study of A-B A-C lists shou ld be infe rior than following study of A-B D-C lists . Because the C target does not share a common cue with B, learni ng the D-C list should be less interfering than learning the A-C list.

In contrast to th is prediction, experiments with th is protocol often reveal a retroactive fac ilitation efFect, in which A-B A-C lists lead to superior memory fo r B (Bruce & Weaver, 1973; Robbins & Bray, "1974). This phenomenon even appears in the learnin g of complex, rea l­world materials: Learners showed better memory for a tex t about Zen Buddhism when learning of a con flicting text on Buddhism was inter­polated between st udy and test than when it was not (Allsubel, Stager, & Gaite , 1968) . Educational programs that employ this concept have been Similarly successful: Students showed better retention of materials from a seventh-grade science curriculum when they had a second year of sci­ence (i n eighth grade) , even when the specific content was not repeated (Arzi , Ben-Zvi, & GaDiel , 1985).

These phenomena follow naturally from the idea of reminding. Because new infor mation invites rem inding of previously studied and related material, that reminding can indeed fos ter superior memory for the original information. Such a claim does not conflict with the idea that additional retroac tive interference is also promoted by such encounters; whether the benefi cial effects of reminding are sufficient to overcome the deleterious effects of interference is li kely a complex function of the materials and scheduling oflearning and tes ti ng events, as well as the goals of the learner. It is interesting to note that the very condition that enhances interference-namely, simi larity-is also the facto r that enhances the likelihood of reminding. This combination of effects makes good cogn itive sense: When mater iab are similar, 1I nder­standing them often requires generalization or contrast among the competing pieces of information, and reminding allows us to engage in such processes even when the components are temporalJy disparate.

82 • Aaron S. Benja min and Bri an H . Ross

Menl(Jrv (a /" L. ists of Sema lll ic Associates / - ­

A cu rrently popula r word list learning paradigm involves the study of long lists of associates to a common unstudied word . Following such study, incorrect reca ll and recognition of the common unstudied word are often apparent (Gallo, 2006; Roediger & McDermott, 1995). O ne proposed basis for th is effect is that each associate in the list "activates" the common word somewhat, and that the net effect of these relations is to boost act ivat ion to a point where the rememberer is likely to attri­bute it to having been studied (Gallo & Roediger, 2002). This theory can be nJra med in terms of remind ing and, in doing so, can avoid the theoretical mu rk iness of what act ivat ion is or how it is monitored. Each item in the list has some probability of reminding the learner of the common associate, and the large numb er of items makes rem inding h i.ghly likely Monitori ng is then an issue of source monitor ing: If the learner can disc rim inate between retr ieved (i.e., remin ded) and seen words, then incorrect recall and recognition can be avoided . Consistent w ith th is interpretation, manipula tio ns that enhance memory for act u­ally studied list members decrease fa lse memory (Benjamin, 2001), as do manipu lat ions t hat en ha nce the distinct iveness of such information (Dodson & Schacter, 2001).

The only difference between remindi ng, as we have laid it out in p revious sections , and reminding in such tasks concerns what is being reminded. In repetition, nea r-repet it ion, and paired-associate pa ra­digms, that remind ing is episodiC: Single events t hat occurred preYi­ously in the experiment are ret r"ieved . In sem antic associate paradigms, the reminding is semantic: Individua l concepts or words are retrieved from our knowledge, rathe r than from ou r memory for the exper iment. A similar type of semantic reminding may be at work in the classic paradigm of Bower, Clark, Lesgold, and W inzenz (1 969), in \·vhich the provision of organ izational information at encodi ng led to superior memory for the material than when that inform at ion was absent or unorganized. In a second, less well-known experiment, Bower et al. prOVided organ izational information in a later, separate list . That case also led to sup erior recall, and Bower et al. primarily attributed that enha ncemen t to the benefi ts proVided by an effective retrieva l plan (see Benjami n, 2008) . However, they also noted the possibility of a "media­tional" interpretation, in wh ich the presentation of the associated terms du ring the later list inspired covert rehearsal of mem bers from the fi rst list. Th is al ternative interpretation is rooted in the concept of rem ind­ing, and illustrates the wide breadth of paradigms for which the idea m ight prove llSefUl. In th is case, a direct comparison of a retrieval

Th e: CI LLSCS and Con sequences of ReTl1ln d in ll • 83

organization explanation and a remindi ng explanation would require a condition in which associated, but not hierarchical, cues were pre­sented du ring the second list.

THE PURPOSE OF REMINDING

We have outlined here principles that guide reminding, rules that deter­mine the mnemonic consequences of reminding, and the higher-level cognitive capacities th at reminding appears to support. If reminding is a basic bUilding block of cognition, rather than just another boutique theoretical concept, we should be able to make sense out if its role in terms of general evolutionary pr inciples of the m ind. This short con­cluding section outlines our ideas about what that role is.

We start from the perspecti ve that the mi nd is cons tant ly engaged in two parallel but somewh at con fl icting goals . First, pattern match ­ing mechanisms take the bewildering amount of input to our senses and reduce it to manageable propor tio ns by rel at ing that input to our prior knowledge. O ur assessment (understanding) of a situa tion and the actions we take depend upon access to appropriate and go al­relevant information. Second, info rmation is constantl y scru tin ized in order to tune th ose pattern matching mechan ism ~ . Situations and objects that are com mon ly encountered are biased in favor of, and dimensi ons that identi fy critical di ffe rences a re enh anced relat ive to ones that do not contrib ute to importa nt distinction s. In order to extract such dimensions, common charac teristics of related sti mul i must be identified and distin ct ive characte ris tics of similar but crit i­cally di ffere nt stimul i mus t be iden ti fi ed. Often, this occ u rs when the world copresents such st imuli . An ar t ga llery that features modern art allows us to generali ze ac ross the dimensions t hat un iquely iden ­tify such art. Sim ila rly, watch ing a baseball ga me att unes us to subtle but important di fferences bet ween pitchers, such as their arm angles, windups, and pick-off motions, that we wou ld not othe rwise be likel y to attend to.

Reminding is what affords these opportunities at a distance. Even if we cannot visit a museum, occasional exposure to modem a rt-and the attendant remind ing that ensues-allows us to compare art works directly (i f imperfectly) even when our experi ences occur at d ifferent times. Similarly, we can lea rn about baseball withou t watch ing a dozen pitchers at one time. Remind ing allows the past to be par t of the pres ­ent, and so affords us the cha nce to generalize and cont rast episodes that occur at di fferent points in our day, or in our life.

8,l • Aa ron S. Ih: nj<1 mll1 and Brian H . R()"

Rern indings ;11~0 afford oppor tunit ies to learn in unexpected ways. If we were to purge from our memory all characteristi cs of stimuli that we deemed irrelevant upon our encou nter with that stimuli , we would be unable to test new hypo theses about the com position of categories or inferential rule!> for a given problem w ithout revisit ing those stim uli. Reminding is thus also a hedge against changing ideas and chang ing goals: Characteristics of potential romant ic par tners th at are important to a college student might, for example, differ from ones important to a person seeking to have child ren in the near futu re. We cannot antici­pate all our future goals, but retaining in di vid ual prior exper iences pro­vides the potential for oll r learning objectives to change in arbit rary and unanticipated ways. Remindings prov ide one means by which this

potential can be realized.

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