IMPLICIT PROCESSES UNDERLYING JUDGMENTS ABOUT FELING OF KNOWING ON HAPTIC PATTERN RECOGNITION

У статті здійснений аналіз проходження  моніторингу та тактильного розпізнавання як імпліцитних, або імпліцитних процесів. Викладено результати експериментального дослідження щодо прогностичної валідності та міри реалістичності моніторингу імпліцитного тактильного розпізнавання.

Ключові слова: моніторинг, судження про відчуття знання (FOKs), тактильне розпізнавання.

The article analyzes the passage of metamemory monitoring and haptic recognition as an implicit or implicit processes. The results of experimental research on the predictive validity and realism  of monitoring measure of  implicit haptic recognition.

Keywords: monitoring, feeling of knowing judgments (FOKs), haptic recognition

Introduction

The main goal of study was an investigation of the special aspect of haptic identification, namely correlation of subjective knowledge about haptic objects with which people contacts in everyday life to actual information about these objects. Haptic identification is studied in the aspect of metamemory judgments, such as judgment about feeling of knowing (Feeling of knowing judgments) and judgment of retrospective confidence (Retrospective confidence judgments), because these judgments are most optimal for the function of monitoring in the process of haptic identification, as to the process of structurization and collection of information about reproductive possibilities of our memory. Haptic identification will be studied as identification of number of properties of common haptic objects i.e. material which they were made, that in our research named as haptic patterns.  Also implicit and explicit processes will be investigated during haptic identification by conducting correlation measures with speeded and unspeeded metamemory judgments, it gives an opportunity to discover role of these processes in metamemory and identification performance and their intercorrelation.

Identification is the first stage of naming process and have place when person identifies object as a member of a particular class of objects. Object can be recognized without its name being activated (not retrieved or even learned) but identification is obligatory i.e. recognition of a familiar object cannot be prevented (Jonsson, 2005).

The haptic identification process starting from haptic perception, matching with previous experience and response generation. Previously, we review the process of haptic perception, perhaps, major of these ones.

In haptic discovering Klatzky & Lederman (1990) introduced a notion of “exploratory procedures” as a manipulations or manual activities that are intentionally perceptual and executed in specific ways according to the perceptual objective. These exploratory procedures aimed to recover a particular object property are specific and predictable. They include lateral motion hence comprising skin contact and motion across and orthogonal to the surface, static contact for discovering temperature, enclosure for global shape and volume, pressure for hardness, holding (or hefting) for weight, contour following for encoding of precise contour or along edge. All these procedures conjunct into some repertoire, but person implicitly, according to his or her experience/knowledge chooses several (some but not all can be combined simultaneously) appropriate to perceived object, that is sufficient in order to satisfy a particular goal. Choosing of procedure depends on number of demands, like time, direct/indirect perception etc. and these procedures, according to constraints (demands), can change to more sufficient that convey greater result of exploring.

In perceiving and identifying, also extracting haptic information from products Holbrook and Hirschman (1982) mentioned  two types if information that can be elicited – one is intrinsic and specific structural properties of object exists in goal-directed evaluation of object, and another  is autotelic form of information are related to the sensory experience and hedonic appreciation of the product. Both autotelic/instrumental information can be compensated in sufficient for person way when barrier of perceiving exists: retrieval from memories or from another modality (when person isn’t haptically motivated). Also there is theoretical evidence, those persons who have problems in perceiving (if there are someconstraints, barriers) haptic properties (instrumental information) stimulate retrieval of information about the category or the product’s haptic properties stored in memory: person would be more likely to trigger past experiences that would compensate for the lack of actual touch.. But products that have more salient material properties (solid instead granular (e.g. cereal, toothpaste)) led to greater use of haptic information during product evaluation end its proceeds faster.  In our prior experiment we examined that participants are able to produce less number of characteristics due to less salient (or granular) material. In that way if participant have problems with extracting properties he might refer to explicit (referential) processing during retrieve information. It can be longer and confidence would be depending on individual experience of processing of common haptic objects. But if person refers to external compensatory (information from other domains) it increases role of implicit conclusions, and be more confident in their judgments.

Tactile information is almost memorizing and remembering implicitly, because it is a type of sensory memory and generally processing is independent of attention to the stimulus  At developmental psychology acquisition of haptic knowledge is named as habituation as a form of non-associative learning that occurs during repeated presentation of a stimulus and causes a decrease in reaction to these stimulus. Habituation is also proclaimed to be a form a implicit learning which is commonly the case with continually repeated stimuli  that follows spontaneous recovery and becomes more rapid. Also implicit memory can be referred to as the unconscious recollection of previously presented information  And it has been linked to phenomena such as skill acquisition, priming, and classical conditioning. Piaget (1970) discoursed about sensorimotor (or perceptive) skill acquisition and noted that it is unconscious, but in consequent life in won’t able to be comprehended or verbalized, cause it going to be blocked on integration into the conscious mind by an higher rank idea (knowledge) about his/her object managing (behavior). If these lower sensorimotor schemes contradict their idea the child does not formulate sensible hypothesis and they will be eliminated conscious or unconscious repression (as sample can be when child knows only (higher idea) that salt is white and salty for taste, but nothing about its haptic traits). It can become conscious only when later transferred in conceptual scope (explicit recall). If haptic identification like some sensorimotor scheme of haptic processing skill acquisition, apparently, it passes same process of interiorization, also stays unconscious. Hence, haptic processing can be both implicit (fast, unintentional, spontaneous, and automatic).

Jacoby. have suggested that “implicit memory” is synonymous with “automaticity.” And presumably implicit like automatic processes can be fast. He also mentioned that recognition memory decisions refer to automatic use of memory  and rely on familiarity. Stimuli are more perceptually identifiable if they are more familiar, i.e. easier to perceive – relied on fluency heuristic. And recognition is relatively fast and both lead to facilitation and to interference i.e. more amount of errors Jacoby, (1991). Yonelinas, Jacoby, (1995)  examined “action slips” like fluent, unintentional or automatic actions as expressions of implicit memory processes and tried to distinguish role of habits versus intentions in making an actions, and used short-response (300, 450 and 550 msc) deadline instructions to examine their automatics. In our study we will be using such kind of restrictions too.

Our experiment oriented on investigating monitoring aspect of metamemory, hence  focuses on two types of metamemory judgments about haptic identification, namely Feeling of Knowing judgments (i.e., predictions of the future retrieval or recognition (identification) of a currently unrecalled memory) and Retrospective Confidence judgments in retrieved answers (i.e., how sure a person is that some retrieved information from memory is correct.

The feeling-of-knowing judgments were the first systematically explored experimentally, by Joseph Hart, in 1965 as valid predictors of behaviour. He gave people a recall test, when they could not answer a question, he asked them whether they felt they knew the answer anyway. The feeling that they knew it corresponded to their later choosing the correct answer on a multiply-choice format memory test. Hart (1965) showed that feeling-of-knowing judgments did indeed predict the likelihood of correct recognition and also above chance recognition (Hart, 1967) for general knowledge materials, an observation replicated many times (see Nelson, 1988; Schwartz, 1994). He used RJR (Recollection-Judgment-Recognition) technique; in our study we will be using FOK judgments without previous recollection to investigate predictive capabilities in haptic identification.

Metcalfe et al. (1993) crucial factor influencing the magnitude of feeling-of-knowing judgments was the number of repetitions of the cue (which presumably would boost cue familiarity), rather than the retrievability of the sought-after target. .Also priming effect leads to enhancing  feeling-of-knowing judgments and confirms cue-familiarity heuristic.

Second is partial target accessibility argues that main source of information for making feeling-of knowing judgments is partial knowledge about the target. Partial target information (e.g. gaining a prompt like sphere of application) may be sufficient that he or she will assign the item a high feeling of knowing. Phenomenologically, the judgments often feel more intuitive and less deliberative; however, even if people are less analytic about making these judgments partial information may give rise to a diffuse feeling that one knows more than nothing, and in many cases, one would be correct to inflate one’s feeling of knowing (Metcalfe J, Schwartz BL, and Joaquim SG (1993)

Schwartz & Metcalfe (1992) discovered that cue familiarity hypothesis is more relevant to generating of FOKs. It takes place when cue priming and general questions priming are used and they determine increasing FOKs.. It is supported by Metcalfe, Schwartz, and Joaquim (1993) where FOKs were directly related to the number of presentations (and thereby the familiarity) of the cues.. Similar results gained in study of King, Zechmeister and Shaughnessy (1980) where high accurate FOKs produced by retrieval practice that was traced to subjects’ knowledge of their previous recall performance. These facts can be our hypothesis about common (familiar) haptic objects have a high potential of cue familiarity and may determine high FOKs.

Also by investigating metamemory monitoring on perceptual identification first study was obtained by Nelson & Gerler (1984) where it can be employed successfully as a criterion test for the feeling of knowing. Gained results showed low feeling of knowing accuracy was for predicting perceptual identification on all items and nonsignificant correlation (Nelson & Gerler, 1984). Also in perceptual identification with near-threshold priming have an intention to gain low FOKs. High FOK rating indicates that a lesser amount of additional information is needed to produce memory retrieval  and that a low FOK rating indicates that a greater amount of additional information needs to be input into memory to produce retrieval. In previous study on haptic identification FOKs were high and high accurate, then we can assume that respondents are familiar with common haptic patterns and can operate by judgments well.  But if priming  is indicator of implicit processes, we can use time measures to investigate role of these processes in haptic identification(Jameson et al., 1990).

The main goal of study is to differentiate implicit and explicit metacognitive processes during implicit and explicit haptic identification. In our experiment we will be operating by time measures in both cases.

Initially, there are many discrepancies in comprehending of two modes of cognition and metacognition. Jacoby & Brooks, 1984 suggest about nonanalytic versus analytic cognition, experiential versus rational systems was mentioned by Epstein & Pacini (1999) heuristic versus systematic processes by  Johnson, Hashtroudi, & Lindsay, (1993)., heuristic versus deliberate modes of thought are investigated by Kahneman, 2003,  Posner & Snyder, 1975 suggest about automatic and controlled processes, experience-based versus information based processes propoused by Kelley & Jacoby, (1996b); Koriat & Levy-Sadot, (1999).

As we said previously first group of processes (implicit) are fast, automatic, effortless, associative, operated  by habit and low-controllable and another (explicit)  are slower, deliberate,  high-controlled, more conscious, relatively flexible.

Koriat and Levy-Sadot, 2000 suggest about unconscious and conscious monitoring, cause if metacognitive monitoring is defined as knowledge about one’s own knowledge, there are possibility that such knowledge might also be implicit and unconscious and also  have unconscious beliefs about their own conscious or unconscious beliefs.  But FOKs are information-based, they refer to the content of the solicited target, resulting in an educated inference about the plausibility that the information will be recalled or recognized in the future. Also, Reder and Ritter (1992) have suggested that people’s feelings of knowing indicate to them that there is something in memory to be found, and hence these feeling states – especially the fast feelings of knowing – provide information that people use to determine whether they will or will not attempt. But (Koriat, 1991) argued, the implicit use of the cue-familiarity heuristic can result in a conscious FOK. He suggested that even if  priming does enhance conscious FOK, then there is no reason why such FOK could not guide the deliberate, controlled choice of a particular strategy of answering a question (Schwartz,, & Metcalfe, 1992). But still, if we will operate fast FOKs to implicit identification it can be some basis of it and explain their nature, cause solicited target is presumably are well known, and decision making wouldn’t cross threshold of consciousness. Really, such cues as accessibility, ease of retrieval, cue familiarity and the ease or fluency of processing of a presented item can support a heuristic for monitoring one’s own knowledge. And this heuristics are also inferential in nature,  they are used implicitly or unconsciously, and their effects are relatively automatic (Jacoby & Brooks, 1984Kelley & Jacoby, 1996a). Koriat, (2009) suggests that FOKs are understood as experiencing of intuitive feelings rather than as logical deductions. As nonanalytic heuristics FOK may be able to account for the direct, unmediated quality of metacognitive judgments. But  non-analytic use of cue familiarity as basis of FOK are different from the explicit use of familiarity (educated probability judgment about the likelihood of recognizing ). It occurs when the content of the retrieved information is consulted, the monitoring process changes its quality from an automatic, nonanalytic process, to a deliberate, inferential process of probability estimation (see Jacoby & Brooks, 1984). The experience then is more like a judgment of knowing than a feeling of knowing. Content-based inferences require more time and more effort than nonanalytic, heuristic-driven FOKs (Kelley & Jacoby, 1996b). So, as conclusion the main condition of stimulating implicit basis of FOKs will be operating by time restrictions where short time measures will not allow an opportunity for analytic deducing during assessing on haptic identification.

Method

This experiment investigates haptic recognition in the context of metamemory, namely  how phenomena of implicit and explicit recognition interrelated to implicit and explicit memory monitoring processes. A key indicator of monitoring realism is the degree of realism judgments, i.e. calibration  mere of RCJs and predictive validity of FOKs. These indexes are measured according to the implicit processes in judgments and implicit recognition, according to the explicit recognition and explicit processes in metamemory judgments, according to the explicit processes in judgments making and implicit recognition. The role of intrinsic factors in the making of metamemory judgments compared to implicit/explicit recognition of solid and granular patterns.

 

Participants

Forty students (24 women and 16 men, mean age = 19.56 years, SD = 1.24) participated in the experiment. Participants were divided into three experimental groups: the first group, where participants made implicit judgments in implicit recognition (12 women and 8 men), and the third – made explicit judgments related to implicit recognition (12 women and 8 men).

 

Materials

The 56 haptic patterns used as test stimuli and consist of 21 granular (i.e. sawdust, starch, sugar) and 35 solid patterns (such as leather, rubber, glass, etc.) (see Appendix A). The haptic patterns were all common everyday products. All stimuli were randomized and distracters from the same category were used (Appendix B).

 

Procedure

At the initial stage of the experiment respondents provided information about background data and completed credentials into individual cards.

FOKs phase. The first phase of FOK judgments included assessment of the probability of future pattern recognition among the other three. Evaluation was carried out on a computer using software «E-prime». Three names of objects’ material appeared on screen, the goal was as fast as possible estimate the percentage they feel they recognize the material of the fourth object represented among the three. After instruction appeared name of studied fourth material, and then they made their assessment. Participants used the keyboard where they were instructed to press a button corresponded to a particular percentage area shown on the screen where the key “1” = 10%, the key “2” = 20%, … key “9” = 90%, “0” = 100%. In group I evaluation time took 750ms and if it lasted longer, the program provided feedback that the respondent have to be faster in the assessment. In and group II respondents encouraged to think carefully before making the evaluation, the evaluation time was 30 seconds.  Each participant in each group evaluated 17 objects (9 granular and 8 solid), the names of materials for distracters were randomized, order of presentation stimuli was also randomized. Before testing the participants were a series of training evaluation of three objects, then they proceeded to the experiment.

Recognition phase commenced after making FOKs for all 17 stimuli. Participants recognized materials in a specially equipped place where every four objects were presented in special containers (cups) that were fixed in the box, allowing a comfortable and rapid exploring of objects. Respondents had to use both hands for recognition. Each object and corresponding distracters were consistent with previous analog in FOK phase. Location of studied object among distracters and order of presentation of objects were randomized. The participants were instructed to point the location of recognized pattern among other three, namely specify corresponded number (№ 1, № 2, № 3, № 4). In group I recognition time was limited and to study each pattern was attached to 1.5 seconds (total of 6 seconds), after ending of time the experimenter called material name and participant had to specify the number immediately. In group II study was limited to 20 seconds but after calling material name the respondents were asked to think carefully and said the number without a time limitation. Before the recognition phase, the respondents held a series of training sessions of three samples, then study started.

Measurements of time in recognition phase and in group I and in group II were performed using 2 stopwatches: the first measurement started immediately after the announcement of the name of the material by the experimenter and fixed after calling the number that corresponded to the pattern’s placement. The procedure of the experiment, the time for recognition and  assessing determined in pilot study which was attended by 8 people.

Results

All effects declared reliable from initial analyses of variance (ANOVA) have p less than the alpha level of .05. All correlation coefficients are Goodman-Kruskal gamma correlations, which are the best of the available measures of metamemory accuracy.

Data analysis carried out according to the groups: Group I – implicit judgments (implicit processes) and implicit recognition (implicit processes); Group III – explicit judgments and implicit recognition. Average means of judgments, recognition performance, (G) Goodman-Kruskal gamma correlations and O/U index shown in Table 1.

Table 1

Mean values for: (1) FOK judgments, (2) recognition performance, (3) retrospective confidence judgments,  (4) predictive validity of the FOK judgments (Gamma correlation) (5), retrospective validity of the RCJs (Gamma correlation), (6) O/U index calculated between recognition accuracy and retrospective confidence judgments.

Group І Group ІІ Group ІІІ
Mean (SD) Mean (SD) Mean (SD)
  1. FOKs
54.89 (23.97) 58.16 (22.07) 55.63 (20.26)
  1. Recognition performance
43.63 (34.64) 61.86 (32.81) 40.22 (27.20)
  1. Predictive validity of the FOKs (G)
.63* (.12) .47*(.16) .43*(.22)

Note. * Indicates that the value is significantly different from zero as measured by one-sample t-test (all p’s < .001; calculated for the gamma correlations and the O/U indexes)

 

Recognition performance

Mean recognition performance in group I was 43.63% (SD = 34.64, n = 340).. Mean recognition performance in group II was40.22 % (SD = 27.20, n=340). Between performance in group I and group II (F (1. 37) = 3.17, p > .05) there are also significant differences (F (1. 37) = 17.63, p <.05). These findings contradict our hypothesis that there is no difference in means of performance of implicit and explicit recognition.

Predictive validity of the feeling of knowing judgments

Gamma correlations between FOKs and recognition performance were calculated for each participant. Mean values ​​for the group I was 54.89 (SD = 23.97, n = 308) and the value of gamma correlation between recognition performance was average G (20) = 0. 63 (SD = 0.12) at the alpha level of significance p <.001. To make a statistical measurement means of judgments which assessment did not exceed 750 ms were taken into account, as a result 32 means of judgments were rejected. Correlations were conducted between the judgments we needed (n = 296) and their corresponding recognized and unrecognized patterns. This manipulation is made to maintain the accuracy of results and avoid exposure errors, as expected, that after a given time may be encouraged explicit processes. In group III the average ratings of judgments were 55.63 (SD = 20.26). We selected 254 propositions (eliminated 86) and correlation conducted with relevant recognized and unrecognized patterns, which was low G (28) = .43 (SD = .22) level of significance p <.001.

Безымянный

Figure 1.Feeling of knowing judgments plotted against actual proportion of correct answers per probability category. The diagonal presents the prefect calibration. The dash line shows the calibration curve for responses that were scored with correct recognition in Group I; the dotty line shows the calibration curve for Group II.

 

FOK judgments proceeded reassessment in group I  and for most categories (except for 40%, 50%, 100%) of group II, which is shown in Figure 1.

Table 2. shows no significant differences in judgments FOKs between groups (p> .05.). Differences exist and are significant at p <.01 between group I and group II (F (1. 37) = 12.67).. There are differences in means of judgments and recognition performance where the group I and group II performance FOKs were inflated. This is confirmed by multivariate analysis, which were significant differences between the performance and FOKs in group I (F (1. 37) = 8.13, p <.05) and group II (F (1. 37) = 10.49, p <.05).

Discussion

 

Predictive validity of the feeling of knowing judgments

Thus, we determined that FOKs judgments indexes did not differ among groups. However, we can assume that these judgments tend to involve implicit processes, in the group II 25% of judgments were made within 750ms, while the group I was only 9% higher than the time limit of producing implicit judgments. Also in the group with implicit judgments and implicit recognition, which presumably implicit processes indicators predictive validity were average G (20) = 0. 63 (SD = 0.12) but higher according to the explicit recognition and evaluation, so we can assume that between these phenomena are interrelated. However, implicit FOKs is inflated according to implicit recognition and these differences are statistically significant, which likely indicates the existence of revaluation metamemory opportunities.

The high correlation judgments about sense knowledge likely to show the relationship implicit object level processes and implicit metamemory monitoring processes. Common basis FOKs and recognition performance – “familiarity of stimuli” most evident in implicit monitoring. Familiarity in the recognition process reflects the rapid and automatic level, so this explains the high correlation with rated FOKs, as they are stipulated as non-analytic heuristic reasoning processes (Koriat, 2009; Mandler, 1980; Medina, 2008). The cause of correlations FOKs and recognition performance is that judgments about knowledge relating to the assessment of “know” that corresponds to implicit memory, as opposed to the concept of “remembering” that occurs when playing all data associated with the target (the causes, conditions, features, etc.). recognition is the opposite, where familiarity is a foundation key of its performance. On the other hand play (which corresponds to the notion of “mind”) provides recognition performance, since it reflects the power trace memory and familiar stimuli, which as stated earlier may be a common basis of metamemory monitoring and recognition (Graf та Shacter,  1985; Tulving, 2005).

However, the recallability of the stimulus could be a cause of inflated ratings FOKs. We found proofs in the results of Yaniv, I., & Meyer, D. E. (1987) where the recallability was in touch with FOKs. Recallable objects that need more time to decode gaining higher rankings FOKs, it is also increasingly reflected in studies Lupker, S. J., Harbluk, J. L “and Patrick, A. S. (1991). So this explains the correlation with lower performance. Explicit recognition was productive, but less correlated with monitoring, since we have assumed that the basis FOKs are implicit processes because of the presence of realistic claim is impossible. Also limited in time produce judgments could provoke “the illusion of knowledge”, which is manifested in the failure to identify their own incompetence. This is due to lack of skills recognition, which leads not only to the deprivation of their ability to provide correct answers, but also to limit the knowledge that they give wrong answers (Dunning, та співавт. 2003).. This may explain the implicit dependence of the monitoring processes implicit recognition as a limited performance over time was worse compared to explicit recognition.

Conclusions

During the study we found that between explicit an implicit  are statistically significant differences: productivity is higher in explicit recognition. We assumed that during reflection, categorization, discrimination, comparizing (and others). recognizing some patterns among existing other is better, because explicit processes are key to its passage. On the other hand, these results could be due to the fact that automatic implicit processes lead to a lot of mistakes because the choice recognition becomes automatic and interferred character.

Predictive validity of implicit FOKs on implicit recognition is higher compared to explicit recognition. We can conclude that conditionality implicit monitoring of future recognition processes implicit object level metamemory.

Also during further analysis, we found that according to realistics of metamemory judgments, the implicit FOKs is inflated by implicit recognition performance. Probable cause of this is the presence of “illusion of knowing”.

References

  1. Dunning, D., & Johnson, K., Ehringer, J., & Kruger, J. (2003). Why people fail to recognize their own incompetence. Current Directions in Psychological Science, 12, 83–87.
  2. Graham, G., & Neisser, J. (2000). Probing for relevance: What metacognition tells us about the power of consciousness. Consciousness and Cognition, 9, 172–177.
  3. Jacoby, L. L. (1991). A Process Dissociation Framework: Separating Automatic from Intentional Uses of Memory. Journal Of Memory And Language 30, 513-541.
  4. Jacoby, L. L., & Brooks, L. R. (1984). Nonanalytic cognition: Memory, perception and concept learning. In G. H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (Vol. 18, pp. 1–47). San Diego, CA: Academic Press.
  5. Jacoby, L. L., Toth, J. P., & Yonelinas, A. P. (1993). Separating conscious and unconscious influences of memory: Measuring recollection. Journal of Experimental Psychology. General. 122, 139-154.
  6. Jonsson, F. (2005) Olfactory Metacognition A Metamemory Perspective on Odor Naming. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Social Sciences,  10, 11.
  7. Kelley, C. M., & Jacoby, L. L. (1996b). Memory attributions: Remembering, knowing, and feeling of knowing. In L. M. Reder (Ed.), Implicit memory and metacognition (pp. 287–308). Hillsdale, NJ: Lawrence Erlbaum Associates Inc.
  8. Klatsky, R. L. & Lederman, S. J. (2003) Haptic Perception. Encyclopedia of Cognitive Science (508 – 512). MacMillan Press
  9. Klatzky, R. L. & Lederman, J. S. and Matula E. D. (1993), Haptic Exploration in the Presence of Vision, Journal of Experimental Psychology: Human Perception and Performance, 19, 726–43.
  10. Klatzky, R. L. & Lederman, S. (1995). Identifying objects from a haptic glance. Perception & Psychophysics, 57, 1111-1123.
  11. Koriat, A. & Levy-Sadot, R. (2000) Conscious and Unconscious Metacognition: A Rejoinder. Consciousness and Cognition 9, 193–202  doi:10.1006/ccog.2000.0436.
  12. Koriat, A. (1997). Monitoring one’s own knowledge during study: A cue-utilization approach to judgments of learning. Journal of Experimental Psychology: General, 126, 349-370.
  13. Koriat, A. (2000). The feeling of knowing: Some metatheoretical implications for consciousness and control. Consciousness and Cognition, 9, 149-171.
  14. Koriat, A., & Levy-Sadot, R. (1999). Processes underlying metacognitive judgments:  Information-based and experience-based monitoring of one’s own knowledge. In S. Chaiken, & Y. Trope (Eds.), Dual process theories in social psychology New York: Guilford Publications, 483-502.
  15. Koriat, A., (2009) Metamemory: The feeling of knowing and its vagaries Psychology: IUPsyS Global Resource. http://ebook.lib.sjtu.edu.cn/iupsys/Proc/ mont2/mpv2ch21.html.
  16. Lederman, S. J., and Klatzky, R. L. (1990). Haptic object classification: Knowledge-driven exploration. Cognitive Psychology, 22, 421-459.
  17. Lupker, S. J., Harbluk, J. L„ & Patrick, A. S. (1991). Memory for things forgotten. Journal of Experimental Psychology: Learning, Memory, and Cognition, 17. 897-907.
  18. Mandler, G. (1980). Recognizing: The judgment of previous occurrence. Psych Rev. 87, 252–271.
  19. Medina, J. J. (2008). The biology of recognition memory.Psychiatric Times. Retrieved March 14, 2009, із http://www.brainrules.net/pdf/JohnMedina.
  20. v, J. (2000). Metamemory: Theory and data. In E. Tulving & F.I.M. Craik (Eds.), The Oxford Handbook of Memory, pp. 197-211. New York: Oxford University Press.
  21. Metcalfe, J., Bennett L. Schwartz, and Scott G. Joaquim (1993) The Cue-Familiarity Heuristic in Metacognition. Journal of Experimental Psychology Learning, Memory, and Cognition, 19, 4, 851-861.
  22. Posner, M. I., & Snyder, C. R. (1975). Attention and cognitive control. In R. L. Solso (Ed.), Information processing and cognition Hillsdale, NJ: Erlbaum. 55-85.
  23. Reder, L. M. & Ritter, F. E. (1992). What determines initial feeling ofknowing? Familiarity with question terms, not with the answer. Journal ofExperimental Psychology: Learning, Memory, and Cognition, 18, 435- 452.
  24. Winkler, I., Nelson, C. (2005). From Sensory to Long-Term Memory Evidence from Auditory Memory Reactivation Studies. Experimental Psychology 52, 1, 3–20.
  25. Yaniv, I., & Meyer, D. E. (1987) Activation and metacognition of inaccessible stored information: Potential bases for incubation effects in problem solving. Journal of Experimental Psychology: Learning, Memory, and Cognition. 13, 187-205.
  26. Yonelinas, A. P., Jacoby, L. L. (1995).  Dissociating automatic and controlled processes in a memory-search task: Beyond implicit memory. Psychol Res, 57, 156-165.

 

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