Sequence learning
Sequence learning is inherent to human ability because it is an integrated part of conscious and nonconscious learning as well as activities. Sequences of information or sequences of actions are used in various everyday tasks: "from sequencing sounds in speech, to sequencing movements in typing or playing instruments, to sequencing actions in driving an automobile."[1] Sequence learning can be used to study skill acquisition and used in studies of various groups ranging from neuropsychological patients to infants.[1] According to Ritter and Nerb, “The order in which material is presented can strongly influence what is learned, how fast performance increases, and sometimes even whether the material is learned at all.”[2] Sequence learning, more known and understood as a form of explicit learning, is now also being studied as a form of implicit learning as well as other forms of learning. Sequence learning can also be referred to by sequential behavior, behavior sequencing, and serial order in behavior.
History
In first half of the 20th century, Margaret Floy Washburn, John B. Watson, and other behaviorists believed behavioral sequencing to be governed by the reflex chain, which states that stimulation cause by an initial movement triggers an additional movement, which triggers another additional movement, and so on. In 1951, Karl Lashley, a neurophysiologist at Harvard University, published, “The Problem of Serial Order in Behavior,” addressing the current beliefs about sequence learning and introducing his hypothesis. He criticized the previous view on the basis of six lines of evidence:
- “(1) Movements can occur even when sensory feedback is interrupted. (2) Some movement sequences occur too quickly for elements of the sequences to be triggered by feedback from the preceding elements. (3) Errors in behavior suggest internal plans for what will be done later. (4) The time to initiate a movement sequence can increase with the length or complexity of the sequence. (5) The properties of movements occurring early in a sequence can anticipate later features. (6) Neural activity can indicate preparation of upcoming behavior events, including upcoming behavior events in the relatively long-term future.”[3]
Hierarchical organization of plans
Karl Lashley negated that sequence learning, or behavioral sequencing or serial order in behavior, is not attributed from sensory feedback. Rather, he proposed that there are plans for behavior since the nervous system prepares for some behaviors but not others. He said that there was a hierarchical organization of plans. He came up with several lines of evidence.
The first evidence states that the context changes functional interpretations of the same behaviors. Such as the way “wright, right, right, rite, and write” are interpreted based on the context of the sentence. “Right” can be interpreted as a direction or as something good depending on the context. A second line of evidence says that errors are involved in human behavior as hierarchical organization. In addition, “hierarchical organization of plans comes from the timing of behavioral sequences.” The larger the phrase, the longer response time, which factors into “’decoding’” or “’unpacking’” hierarchical plans. Another source of evidence is derived from how easy or hard it is to learn a sequence. The mind can create a “memory for what is about to happen” as well as a “memory for what has happened.” The final source of evidence for the hierarchical organization of plans is characterized by chunking (psychology). This skill puts single units into a unit comprised of multiple units.[3]
Types of sequence learning
There are two broad categories of sequence learning – explicit and implicit – with subcategories. Explicit sequence learning was known and studied from the discovering of sequence learning. However recently, implicit sequence learning has gained more attention and research. A form of implicit learning, implicit sequence learning refers to the underlying methods of learning that people are unaware of; in other words, learning without knowing. Hsiang-Ling Jennifer Lin states that the exact properties and number of mechanisms of implicit learning are debated by researchers.[4] Other forms of implicit sequence learning include motor sequence learning, temporal sequence learning, and Associative Sequence Learning.
Sequence learning problems
Sequence learning problems are used to better understand the different types of sequence learning. There are four basic sequence learning problems: sequence prediction, sequence generation, sequence recognition, and sequential decision making. These “problems” show how sequences are formulated. They show the patterns sequences follow and how these different sequence learning problems are related to each other.
Sequence prediction attempts to predict the next immediate element of a sequence based on all of the preceding elements. Sequence generation is basically the same as sequence prediction where a sequence attempts to be pieced together one by one the way it naturally occurs. Sequence recognition takes certain criteria and determines whether or not the sequence is legitimate. Sequential decision making or sequence generation through actions breaks down into three variations: goal-oriented, trajectory-oriented, and reinforcement-maximizing. These three variations all want to pick an action(s) or step(s) that will lead to the goal in the future.[5]
These sequence learning problems reflect hierarchical organization of plans because each element in the sequences build on the previous elements.
Alfred L. Yarbus
In a classic experiment, Yarbus (1967) demonstrated that though the subjects viewing portraits report to apprehend the portrait as a whole, their eye movements successively fixated at the most informative parts of the image. These observations suggest that underlying an apparently parallel process of face perception, a serial oculomotor process is concealed. It is a common observation that when a skill is being acquired, we are more attentive in the initial phase, but after repeated practice, the skill becomes nearly automatic (Fitts, 1964), this is also known as unconscious competence. We can then concentrate on learning a new action while performing previously learned actions skillfully. Thus it appears that a neural code or representation for the learnt skill is created in our brain, which is usually called procedural memory. The procedural memory encodes procedures or algorithms rather than facts.
Ongoing research
There are many other areas of application for sequence learning. Research work on sequence learning has been going on in several disciplines such as artificial intelligence, neural networks, cognitive science (sequence learning aspects in skill acquisition), and engineering[6]. How humans learn sequential procedures has been a long-standing research problem in cognitive science and currently is a major topic in neuroscience.
References
- ^ a b Clegg, Benjamin A (1). "Sequence learning". Trends in Cognitive Sciences. 2 (8): 275–281. doi:10.1016/S1364-6613(98)01202-9.
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ignored (help) - ^ In order to learn : how the sequence of topics influences learning. Oxford [u.a.]: Oxford Univ. Press. 2007. ISBN 9780195178845.
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(help) - ^ a b Rosenbaum, David (2007). "The problem of serial order in behavior: Lashley's legacy". Human Movement Science. 26 (4): 525–554. doi:10.1016/j.humov.2007.04.001.
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- ^ Sun, Ron. "Introduction to Sequence Learning". Retrieved 30 June 2011.
- ^ Ron Sun and C. Lee Giles (August 2001). "Sequence Learning: From Recognition and Prediction to Sequential Decision Making" (PDF). Retrieved 2007-05-05.
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Further reading
- (eds.), Ron Sun, C. Lee Giles (2001). Sequence learning paradigms, algorithms, and applications. Berlin: Springer. ISBN 3540415971.
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has generic name (help)CS1 maint: multiple names: authors list (link)</ref> - Bengio, [edited by] Joseph Keshet, Samy (2009). Automatic speech and speaker recognition large margin and kernel methods. Chichester, U.K.: J. Wiley & Sons. ISBN 9780470742044.
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has generic name (help)CS1 maint: multiple names: authors list (link)</ref> - Genetic Programming Theory and Practice VIII. Springer-Verlag New York Inc. 2010. ISBN 9781441977465.</ref>
- Smilkstein, Rita. We're born to learn : using the brain's natural learning process to create today's curriculum (2nd ed. ed.). Thousand Oaks, California: Corwin Press. ISBN 9781412979382.
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has extra text (help)</ref> - Rowland LA, and DR Shanks (2006). Journal of Experimental Psychology. Human Perception and Performance. 32 (2): 287–299. ISSN 0096-1523. OCLC 109192123.
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ignored (help)</ref> - Spiegel, R, and IP McLaren (2006). Journal of Experimental Psychology. Animal Behavior Processes. 32 (2): 150–163. ISSN 0097-7403. OCLC 109191993.
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ignored (help)CS1 maint: multiple names: authors list (link)</ref> - Savion-Lemieux, T, JA Bailey, and VB Penhune (2009). Experimental Brain Research. 195 (2): 293–306. ISSN 0014-4819. OCLC 319879934.
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ignored (help)CS1 maint: multiple names: authors list (link)</ref> - Gagliardi, C, A Tavano, A.C Turconi, U Pozzoli, and R Borgatti (2011). Pediatric Neurology. 44 (3): 207–213. ISSN 0887-8994. OCLC 701964470.
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(help)CS1 maint: multiple names: authors list (link)</ref> - Song, S, JH J. Howard, and DV Howard (2008). Experimental Brain Research. 189 (2): 145–158. ISSN 0014-4819. OCLC 264650127.
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ignored (help)CS1 maint: multiple names: authors list (link)</ref> - Simon, JR, M Stollstorff, LC Westbay, CJ Vaidya, JH J. Howard, and DV Howard (1). Behavioural Brain Research. 216 (1): 452–457. ISSN 0166-4328. OCLC 680073165.
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ignored (help)CS1 maint: multiple names: authors list (link)</ref> - Bo, J, and RD Seidler (2010). Experimental Brain Research. 201 (4): 837–851. ISSN 0014-4819. OCLC 603785018.
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ignored (help)CS1 maint: multiple names: authors list (link)</ref> - Swett, Bruce (25). "The neural substrates of graphomotor sequence learning". Dissertation. Retrieved 30 June 2011.
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ignored (help)</ref> - Malmgren, Helge (1997). "Perceptual fulfilment and temporal sequence learning". University of Gothenburg. Department of Philosophy. Retrieved 30 June 2011.</ref>
- Gureckis, Tod Matthew (2005). "Mechanisms and constraints underlying implicit sequence learning". Retrieved 30 June 2011.</ref>
- Song, Sunbin, James H. Howard, Jr, and Darlene V. Howard (2007). "Implicit probabilistic sequence learning is independent of explicit awareness". Cold Spring Harbor Laboratory Press. Retrieved 30 June 2011.
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: CS1 maint: multiple names: authors list (link)</ref> - Seidler, R. D. (2005). "Neural correlates of encoding and expression in implicit sequence learning". Experimental Brain Research. Springer-Verlag. pp. 114–124. doi:10.1007/s00221-005-2284-z. Retrieved 30 June 2011.
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ignored (help)</ref> - Vidoni, Eric D (25). "Motor sequence learning occurs despite disrupted visual and proprioceptive feedback". Behavioral and Brain Functions. p. 32. doi:10.1186/1744-9081-4-32.
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ignored (help)CS1 maint: unflagged free DOI (link)</ref> - Sun, Ron (2001). "Sequence Learning: From Recognition and Prediction to Sequential Decision Making" (PDF). IEEE INTELLIGENT SYSTEMS. Retrieved 30 June 2011.
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ignored (help)</ref> - Landau, Susan M. (2006). "Sequence learning in pianists and nonpianists: An fMRI study of motor expertise" (PDF). Retrieved 30 June 2011.
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