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--- instructional_design:structural_learning [2011/03/16 08:53]
jpetrovic [What is structural learning theory?]
+++ instructional_design:structural_learning [2023/06/19 18:03] (current)
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 ===== What is structural learning theory? =====
-Structural learning theory suggests that structures (problems) that a learner must learn, need to be formed as rules. Those rules can be simplified into **lower-order rules** (//atomic components//) which represent most basic concepts learner needs to know when dealing with a problem from given domain. By combining these atomic components and application of more complicated to lower order rules new **higher-order rules** are derived. Higher-order rules are rules which can have other rules as inputs or outputs and they can be used to solve complex problems in the whole domain.
+Structural learning theory suggests that structures (problems) that a learner must learn, need to be formed as **rules** performed on a **domain**.
-Rules, according to the structural learning theory have three parameters:
+A domain here is defined as a set of characterizing **inputs** and **outputs**. Inputs and outputs can be anything, even a process, an idea or a concept. For example:
+  * list of verbs (input) -> present participles (output).
+Operations performed on given inputs are called rules, and they generate unique outputs. Rules can contain different levels of abstraction and are always defined with three parameters:
   * **domain** - its allowed **inputs**,
   * **range** - its expected outputs, and
   * **procedure** - the sequence of **operations** to perform **on the inputs**.
-In accordance with structural learning theory, first step in instructional design or learning is **definition of the problem domain through structural analysis**. Problem domain can be both well- and ill-defined((An ill-defined domain is one in which rules are quite simple, yet there is no direct complete solution like chess, or poetry writing.)). In case of an ill-defined domain, it should be divided into well-defined sub-domains which can generate at least one rule. Domain sets the inputs and desired outputs for problem solving.
+For example: a rule //form present participle// has the domain of all English verbs, the range of present participles and the procedure of adding "-ing" ending to the verb.
-Domain definition is followed by **construction of hierarchy of rules** for well-defined domains. Rules should be explained on prototype problems, but can also leave some **gaps** in problem solving procedure, which **are then converted into higher-order problems** containing gap rules. Higher-order rules are then used to fill the gap, but can also validate lower level rules.
+Rules can be simplified into **lower-order rules** (//atomic components//) which represent most basic concepts learner needs to know when dealing with a problem from given domain. By combining these atomic components and application of more complicated to lower order rules new **higher-order rules** are derived. Higher-order rules are rules which can have other rules as inputs or outputs (for example mathematical theorems) and they can be used to solve complex problems in the whole domain.
-An important part of the theory is also **prior knowledge (rules)** of the learner, that will **enable construction of new rules**. This knowledge can be examined by instructor, that can be both human or artificial.
+Structural learning theory further attempts to identify components crucial for solving the given problem and is based on the procedure called //structural analysis//. Structural analysis is performed in the following steps:
-Structural learning theory's applications have been made in **mathematics** and **language learning**.
+  - The first step is to identify problem domain inputs and outputs, or even only outputs (representative problems).
+  - Rules should be defined and explained on each representative problem. Problem domain can be both well- and ill-defined((An ill-defined domain is one in which rules are quite simple, yet there is no direct complete solution like chess, or poetry writing.)). In case of an ill-defined domain, it should be divided into well-defined sub-domains which can generate at least one solution rule.
+  - Each solution rule should be converted into a new higher-order problem and new higher-order rules for solving them.
+  - Redundant rules should be eliminated and the whole process repeated until simple enough rules are reached.
+An important part of the theory is also **prior knowledge (rules)** of the learner, that will **enable construction of new rules**. This knowledge can be examined by instructor, that can be both human or artificial.
 ===== What is the practical meaning of structural learning theory? =====
+An example of application of structural learning on learning how to subtract:((Suggested by Scandura in [[http://books.google.hr/books?id=qlF9AAAAMAAJ&q=Problem+Solving:+A+Structural/Process+Approach+with+Instructional+Applications&dq=Problem+Solving:+A+Structural/Process+Approach+with+Instructional+Applications&hl=hr&ei=GpuATeSrMs7esgbhvfT4Bg&sa=X&oi=book_result&ct=result&resnum=2&ved=0CCwQ6AEwAQ|Scandura, J.M. Problem Solving: A Structural/Process Approach with Instructional Applications. NY: Academic Press. 1977.]]. Cited in [[http://tip.psychology.org/scandura.html|TIP: Structural Learning Theory (J. Scandura)]]. Retrieved March 16, 2011.))
+  - Select a representative sample of subtraction problems such as 9-5, 248-13, or 801-302.
+  - Identify the minimal capabilities of the learners: be able to recognize the digits 0-9, minus sign, column and rows. Then identify rules for solving each of the subtraction problems. For example, one of the rules can be that if the last digit of the minuend is smaller than a corresponding digit of the subtrahend, the next left digit in minuend is decremented by one.
+  - Identify higher-order rules and eliminate other rules they subsume. For subtraction this means the rule mentioned under (2) should be generalized for any digit of the minuend and corresponding digit of the subtrahend, not just the last one.
+  - Reconsider the resulting rules from (3) and generalize them to account for all problems within the domain. In the case of subtraction we could generalize the problem to subtraction of numbers in different bases.
+Structural learning theory's applications have been made in **mathematics** and **language learning**.
 ===== Criticisms =====
@@ Line 34: / Line 50: @@
 ===== Keywords and most important names =====
+  * **Structural learning theory**, **rules**, **domain**, **range**, **procedures**
+  * [[http://www.scandura.com/|Joseph Scandura]]
 ===== Bibliography =====
+[[http://www.scandura.com/Articles/172-SLT%20Current%20Status%20and%20New%20Perspectives.pdf|Scandura, J. M. Structural Learning Theory: Current Status and New Perspectives. Instructional Science 29, no. 4 : 311–336. 2001.]]
 [[http://web.cortland.edu/frieda/id/IDtheories/4.html|Instructional Design Theory Database Project: Structural Learning Theory.]] Retrieved March 15, 2011.
 [[http://www.odu.edu/educ/roverbau/Class_Websites/761_Spring_04/Assets/course_docs/ID_Theory_Reps_Sp04/Scandura_Chapman.pdf|Scandura, J. M. Structural learning theory. Instructional Design Theories and Models: An Overview of Their Current Status: p215–245. 1984.]]
+[[http://tip.psychology.org/scandura.html|TIP: Structural Learning Theory (J. Scandura).]] Retrieved March 16, 2011.
 ===== Read more =====
-Reigeluth, Charles M. Instructional-design Theories and Models: An overview of their current status. Routledge, 1983.
+[[http://books.google.com/books?id=AbJc4Kg6XQoC|Reigeluth, Charles M. Instructional-design Theories and Models: An overview of their current status. Routledge, 1983.]]
+[[http://books.google.com/books?id=pCoEAQAAIAAJ|Scandura, J.M. & Scandura, A. Structural Learning and Concrete Operations: An Approach to Piagetian Conservation. NY: Praeger. 1980.]]
+[[http://books.google.com/books?id=O43KPQAACAAJ|Scandura, J.M. Structural Learning I: Theory and Research. London: Gordon & Breach. 1973.]]
+[[http://www.amazon.com/dp/0677151101|Scandura, J.M. Structural Learning II: Issues and Approaches. London: Gordon & Breach. 1976.]]

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