Theory Wiki - User contributions [en]

A word-experience model of Chinese character learning

2007-04-06T23:57:08Z

Erik-Reichle:

ABSTRACT

Computational models of learning can advance the science of learning by making explicit assumptions about the learning process, thereby providing model-based hypotheses that can be tested by data. Our intention is to demonstrate how a model that we have developed for English word reading (Reichle & Perfetti, 2003) can be applied to learning to read characters in Chinese. The basic model assumptions are: (1) that the ability to read words is acquired on a word-by-word basis, and (2) that the generalized (robust) learning of a word is the result of many different encoding (reading) contexts whose variability becomes less important with repeated encounters. On this account, a robust, context-general word representation results from an extraction of a stable form from its many experienced variations. The application of this model to Chinese character learning is especially compelling because, more than with alphabetic learning, which provides generalizations across words, Chinese learning is character-by-character. The proposed modeling project will thus result in a computational framework for examining the consequences of contextual variability on the learning and retention of lexical information in a specific academic domain—the acquisition of a second language. The project will also provide a more general analytical framework for examining the factors that contribute to robust learning across many domains.

Refinement and Fluency

2007-04-06T23:55:54Z

Erik-Reichle: /* Descendents */

== The PSLC Refinement and Fluency cluster ==

=== Abstract ===
The studies in this cluster concern the design and organization of instructional activities to facilitate the acquisition, [[refinement]], and fluent control of critical [[knowledge components]]. The research of the cluster addresses a series of core propositions, including but not limited to the following.

1. task analysis: To design effective instruction, we must analyze learning tasks into their simplest components.

2. fluency from basics: For true fluency, higher level skills must be grounded on well-practiced lower level skills.

3. scheduling of practice: [[Optimized scheduling]] of [[practice]] uses principles of memory to maximize robust learning and achieve mastery.

4. [[explicit instruction]]: Explicit rule-based instruction facilitates the acquisition of specific skills, but only if the rules are simple.

5. [[implicit instruction]]: On the other hand, implicit instruction or exposure serves to foster the development of initial familiarity with larger patterns.

6. immediacy of feedback: A corollary of the emphasis on in vivo evaluation, scheduling, and explicit instruction is the idea that immediate feedback facilitates learning.

7. [[cue validity]]: In both explicit and implicit instruction, cue validity plays a central role in determining ease of learning of knowledge components.

8. focusing: Instruction that focuses the learner's attention on valid cues leads to more robust learning than unfocused instruction or instruction that focuses on less valid cues.

9. learning to learn: The acquisition of skills such as analysis, help-seeking, or advance organizers can promote future learning.

10. [[transfer]]: A learner's earlier knowledge places strong constraints on new learning, promoting some forms of learning, while blocking others.

The overall hypothesis is that instruction that systematically reflects the complex [[features]] of targeted knowledge in relation to the learner’s existing knowledge leads to more robust learning than instruction that does not. The principle is that the gap between targeted knowledge and existing knowledge needs to be directly reflected in the organization of instructional events. This organization includes the structure of knowledge components selected for instruction, the scheduling of learning events, practice, recall opportunities, explicit and implicit presentations, and other activities.

This hypothesis can be rephrased in terms of the PSLC general hypothesis, which is that [[robust learning]] occurs when the [[learning event space]] is designed to include appropriate target paths, and when students are encouraged to take those paths. The studies in this cluster focus on the formulation of well specified target paths with highly predictable learning outcomes.

===Significance===
A core theme in this cluster is that instruction in basic skills can facilitate the acquisition and refinement of knowledge and prepare the learner for [[fluency]]-enhancing practice. Instruction that provides practice and feedback for basic skills on a schedule that closely matches observed student abilities is important for this goal, and can be effectively delivered by computer. In the area of second language learning, the strengths of computerized instruction are matched by certain weaknesses. In particular, computerized tutors are not yet good at speech recognition, making it difficult to assess student production. Moreover, contact with a human teacher can increase the breadth of language usage, as well as motivation. Therefore, an optimal environment for language learning would combine the strengths of computerized instruction with those of classroom instruction. It is possible that a similar analysis will apply to science and math.

=== Glossary ===
[[:Category:Refinement and Fluency|Refinement and Fluency]] glossary.

=== Research question ===
The overall research question is how can instruction optimally organize the presentation of complex targeted knowledge, taking into account the learner’s existing knowledge as well as an analysis of the target domain? In examining this general question, the studies focus on the following dimensions of instructional organization, among others: the demands placed on learners of specific knowledge components, the scheduling of practice, the timing and extent of explicit teaching events relative to implicit learning opportunities, and the role of feedback.

=== Independent variables ===
At a general level, the research varies the organization of instructional events. This organization variable is typically based on alternative analyses of task demands, relevant knowledge components, and learner background.

=== Dependent variables ===
The dependent variables in these studies assess learner performance during learning events and following learning. Typical measures are percentage correct and number of learning trials or time to reach a given standard of performance. Response times are also measured in some cases.

=== Hypotheses ===
The overall hypothesis is that instruction that systematically reflects the complex features of targeted knowledge in relation to the learner’s existing knowledge leads to more robust learning than instruction that does not. A corollary of this hypothesis is that learning is increased by instructional activities that require the learner to attend to the relevant knowledge components of a learning task.

Specific hypotheses about the organization of instruction derive from task analyses of specific domain knowledge and the existing knowledge of the learner. A background assumption for most studies is that fluency is grounded in well-practiced lower level skills. A few examples of specific hypotheses are as follows:

1. scheduling of practice hypothesis: The optimal scheduling of practice uses principles of memory consolidation to maximize robust learning and achieve mastery.

2. Resonance hypothesis: The acquisition of knowledge components can be facilitated by evoking associations between divergent coding systems.

3. explicit instruction hypothesis: Explicit rule-based instruction facilitates the acquisition of specific skills, but only if the rules are simple.

4. implicit instruction hypothesis: Implicit instruction or exposure serves to foster the development of initial familiarity with larger patterns.

5. Feedback hypothesis: Instruction that provides immediate, diagnostic feedback will be superior to instruction that does not.

6. cue validity hypothesis: In both explicit and implicit instruction, cue validity plays a central role in determining ease of learning of knowledge components.

7. Focusing hypothesis: Instruction that focuses the learner's attention on valid cues will lead to more robust learning than unfocused instruction or instruction that focuses on less valid cues.

8. learning to learn hypothesis: The acquisition of skills such as analysis, help-seeking, or advance organizers can promote future learning.

9. Learner knowledge hypothesis: A learner's existing knowledge places strong constraints on new learning, promoting some forms of learning, while blocking others.

=== Explanation ===
All knowledge involves content and procedures that are specific to a domain. An analysis of the domain reveals the complexities that a learner of a given background will face and the knowledge components that are part of the overall complexity. Accordingly, the organization of instruction is critical in allowing the learner to attend to the critical valid features of knowledge components and to integrated them in authentic performance. Acquiring valid features and strengthening their associations facilitates retrieval during subsequent assessment and instruction, leading to more robust learning. Additionally, robust learning is increased by the scheduling of learning events that promotes the [[long-term retention]] of the associations.

=== Descendents ===

Explicit instruction and manipulations of attention & discrimination
* [[Intelligent_Writing_Tutor | First language effects on second language grammar acquisition]] (Mitamura-Wylie)
* [[Learning the role of radicals in reading Chinese]] (Liu et al.)
* [[Basic skills training|French dictation training]] (MacWhinney)
* [[Chinese pinyin dictation]] (Zhang-MacWhinney)
* [[A_Multimodal_%28Handwriting%29_Interface_for_Solving_Equations| A multimodal (handwriting) interface for solving equations]] (Anthony, Yang, & Koedinger) [Was in CL]
*[[Note-Taking_Technologies | Note-taking Project Page (Bauer & Koedinger)]]
**[[Note-Taking: Restriction and Selection]] (completed)
**[[Note-Taking: Focusing On Concepts]] (planned)
**[[Note-Taking: Focusing On Quantity]] (planned)
*[[A word-experience model of Chinese character learning]] (Reichle, Perfetti, & Liu)

Optimal scheduling & fluency pressure
* [[Optimizing the practice schedule]] (Pavlik et al.)
* [[French gender cues | French Grammatical Gender Cue Learning Through Optimized Practice]] (Presson-MacWhinney)
* [[Japanese fluency]] (Yoshimura-MacWhinney)
* [[Providing optimal support for robust learning of syntactic constructions in ESL]] (Levin, Frishkoff, De Jong, Pavlik)
* [[Fostering fluency in second language learning]] (De Jong, Perfetti)

Knowledge accessibility including background knowledge & knowledge suppression
* [[Using syntactic priming to increase robust learning]] (De Jong, Perfetti, DeKeyser)

Active processing including learner control
* [[Mental rotations during vocabulary training]] (Tokowicz-Degani)

Novel knowledge component and cognitive task analysis
* [[The_Help_Tutor__Roll_Aleven_McLaren|Tutoring a meta-cognitive skill: Help-seeking (Roll, Aleven & McLaren)]] [Was in Coordinative Learning and in Interactive Communication]
* [[Composition_Effect__Kao_Roll|What is difficult about composite problems? (Kao, Roll)]]
* [[Arithmetical fluency project]] (Fiez)

=== Annotated bibliography ===
Forthcoming

[[Category:Cluster]]

Refinement and Fluency

2007-04-06T23:54:42Z

Erik-Reichle: /* Descendents */

== The PSLC Refinement and Fluency cluster ==

=== Abstract ===
The studies in this cluster concern the design and organization of instructional activities to facilitate the acquisition, [[refinement]], and fluent control of critical [[knowledge components]]. The research of the cluster addresses a series of core propositions, including but not limited to the following.

1. task analysis: To design effective instruction, we must analyze learning tasks into their simplest components.

2. fluency from basics: For true fluency, higher level skills must be grounded on well-practiced lower level skills.

3. scheduling of practice: [[Optimized scheduling]] of [[practice]] uses principles of memory to maximize robust learning and achieve mastery.

4. [[explicit instruction]]: Explicit rule-based instruction facilitates the acquisition of specific skills, but only if the rules are simple.

5. [[implicit instruction]]: On the other hand, implicit instruction or exposure serves to foster the development of initial familiarity with larger patterns.

6. immediacy of feedback: A corollary of the emphasis on in vivo evaluation, scheduling, and explicit instruction is the idea that immediate feedback facilitates learning.

7. [[cue validity]]: In both explicit and implicit instruction, cue validity plays a central role in determining ease of learning of knowledge components.

8. focusing: Instruction that focuses the learner's attention on valid cues leads to more robust learning than unfocused instruction or instruction that focuses on less valid cues.

9. learning to learn: The acquisition of skills such as analysis, help-seeking, or advance organizers can promote future learning.

10. [[transfer]]: A learner's earlier knowledge places strong constraints on new learning, promoting some forms of learning, while blocking others.

The overall hypothesis is that instruction that systematically reflects the complex [[features]] of targeted knowledge in relation to the learner’s existing knowledge leads to more robust learning than instruction that does not. The principle is that the gap between targeted knowledge and existing knowledge needs to be directly reflected in the organization of instructional events. This organization includes the structure of knowledge components selected for instruction, the scheduling of learning events, practice, recall opportunities, explicit and implicit presentations, and other activities.

This hypothesis can be rephrased in terms of the PSLC general hypothesis, which is that [[robust learning]] occurs when the [[learning event space]] is designed to include appropriate target paths, and when students are encouraged to take those paths. The studies in this cluster focus on the formulation of well specified target paths with highly predictable learning outcomes.

===Significance===
A core theme in this cluster is that instruction in basic skills can facilitate the acquisition and refinement of knowledge and prepare the learner for [[fluency]]-enhancing practice. Instruction that provides practice and feedback for basic skills on a schedule that closely matches observed student abilities is important for this goal, and can be effectively delivered by computer. In the area of second language learning, the strengths of computerized instruction are matched by certain weaknesses. In particular, computerized tutors are not yet good at speech recognition, making it difficult to assess student production. Moreover, contact with a human teacher can increase the breadth of language usage, as well as motivation. Therefore, an optimal environment for language learning would combine the strengths of computerized instruction with those of classroom instruction. It is possible that a similar analysis will apply to science and math.

=== Glossary ===
[[:Category:Refinement and Fluency|Refinement and Fluency]] glossary.

=== Research question ===
The overall research question is how can instruction optimally organize the presentation of complex targeted knowledge, taking into account the learner’s existing knowledge as well as an analysis of the target domain? In examining this general question, the studies focus on the following dimensions of instructional organization, among others: the demands placed on learners of specific knowledge components, the scheduling of practice, the timing and extent of explicit teaching events relative to implicit learning opportunities, and the role of feedback.

=== Independent variables ===
At a general level, the research varies the organization of instructional events. This organization variable is typically based on alternative analyses of task demands, relevant knowledge components, and learner background.

=== Dependent variables ===
The dependent variables in these studies assess learner performance during learning events and following learning. Typical measures are percentage correct and number of learning trials or time to reach a given standard of performance. Response times are also measured in some cases.

=== Hypotheses ===
The overall hypothesis is that instruction that systematically reflects the complex features of targeted knowledge in relation to the learner’s existing knowledge leads to more robust learning than instruction that does not. A corollary of this hypothesis is that learning is increased by instructional activities that require the learner to attend to the relevant knowledge components of a learning task.

Specific hypotheses about the organization of instruction derive from task analyses of specific domain knowledge and the existing knowledge of the learner. A background assumption for most studies is that fluency is grounded in well-practiced lower level skills. A few examples of specific hypotheses are as follows:

1. scheduling of practice hypothesis: The optimal scheduling of practice uses principles of memory consolidation to maximize robust learning and achieve mastery.

2. Resonance hypothesis: The acquisition of knowledge components can be facilitated by evoking associations between divergent coding systems.

3. explicit instruction hypothesis: Explicit rule-based instruction facilitates the acquisition of specific skills, but only if the rules are simple.

4. implicit instruction hypothesis: Implicit instruction or exposure serves to foster the development of initial familiarity with larger patterns.

5. Feedback hypothesis: Instruction that provides immediate, diagnostic feedback will be superior to instruction that does not.

6. cue validity hypothesis: In both explicit and implicit instruction, cue validity plays a central role in determining ease of learning of knowledge components.

7. Focusing hypothesis: Instruction that focuses the learner's attention on valid cues will lead to more robust learning than unfocused instruction or instruction that focuses on less valid cues.

8. learning to learn hypothesis: The acquisition of skills such as analysis, help-seeking, or advance organizers can promote future learning.

9. Learner knowledge hypothesis: A learner's existing knowledge places strong constraints on new learning, promoting some forms of learning, while blocking others.

=== Explanation ===
All knowledge involves content and procedures that are specific to a domain. An analysis of the domain reveals the complexities that a learner of a given background will face and the knowledge components that are part of the overall complexity. Accordingly, the organization of instruction is critical in allowing the learner to attend to the critical valid features of knowledge components and to integrated them in authentic performance. Acquiring valid features and strengthening their associations facilitates retrieval during subsequent assessment and instruction, leading to more robust learning. Additionally, robust learning is increased by the scheduling of learning events that promotes the [[long-term retention]] of the associations.

=== Descendents ===

Explicit instruction and manipulations of attention & discrimination
* [[Intelligent_Writing_Tutor | First language effects on second language grammar acquisition]] (Mitamura-Wylie)
* [[Learning the role of radicals in reading Chinese]] (Liu et al.)
* [[Basic skills training|French dictation training]] (MacWhinney)
* [[Chinese pinyin dictation]] (Zhang-MacWhinney)
* [[A_Multimodal_%28Handwriting%29_Interface_for_Solving_Equations| A multimodal (handwriting) interface for solving equations]] (Anthony, Yang, & Koedinger) [Was in CL]
*[[Note-Taking_Technologies | Note-taking Project Page (Bauer & Koedinger)]]
**[[Note-Taking: Restriction and Selection]] (completed)
**[[Note-Taking: Focusing On Concepts]] (planned)
**[[Note-Taking: Focusing On Quantity]] (planned)
*[[A word-experience model of Chinese character learning]] (planned)

Optimal scheduling & fluency pressure
* [[Optimizing the practice schedule]] (Pavlik et al.)
* [[French gender cues | French Grammatical Gender Cue Learning Through Optimized Practice]] (Presson-MacWhinney)
* [[Japanese fluency]] (Yoshimura-MacWhinney)
* [[Providing optimal support for robust learning of syntactic constructions in ESL]] (Levin, Frishkoff, De Jong, Pavlik)
* [[Fostering fluency in second language learning]] (De Jong, Perfetti)

Knowledge accessibility including background knowledge & knowledge suppression
* [[Using syntactic priming to increase robust learning]] (De Jong, Perfetti, DeKeyser)

Active processing including learner control
* [[Mental rotations during vocabulary training]] (Tokowicz-Degani)

Novel knowledge component and cognitive task analysis
* [[The_Help_Tutor__Roll_Aleven_McLaren|Tutoring a meta-cognitive skill: Help-seeking (Roll, Aleven & McLaren)]] [Was in Coordinative Learning and in Interactive Communication]
* [[Composition_Effect__Kao_Roll|What is difficult about composite problems? (Kao, Roll)]]
* [[Arithmetical fluency project]] (Fiez)

=== Annotated bibliography ===
Forthcoming

[[Category:Cluster]]

Refinement and Fluency

2007-04-06T23:54:09Z

Erik-Reichle: /* Descendents */

== The PSLC Refinement and Fluency cluster ==

=== Abstract ===
The studies in this cluster concern the design and organization of instructional activities to facilitate the acquisition, [[refinement]], and fluent control of critical [[knowledge components]]. The research of the cluster addresses a series of core propositions, including but not limited to the following.

1. task analysis: To design effective instruction, we must analyze learning tasks into their simplest components.

2. fluency from basics: For true fluency, higher level skills must be grounded on well-practiced lower level skills.

3. scheduling of practice: [[Optimized scheduling]] of [[practice]] uses principles of memory to maximize robust learning and achieve mastery.

4. [[explicit instruction]]: Explicit rule-based instruction facilitates the acquisition of specific skills, but only if the rules are simple.

5. [[implicit instruction]]: On the other hand, implicit instruction or exposure serves to foster the development of initial familiarity with larger patterns.

6. immediacy of feedback: A corollary of the emphasis on in vivo evaluation, scheduling, and explicit instruction is the idea that immediate feedback facilitates learning.

7. [[cue validity]]: In both explicit and implicit instruction, cue validity plays a central role in determining ease of learning of knowledge components.

8. focusing: Instruction that focuses the learner's attention on valid cues leads to more robust learning than unfocused instruction or instruction that focuses on less valid cues.

9. learning to learn: The acquisition of skills such as analysis, help-seeking, or advance organizers can promote future learning.

10. [[transfer]]: A learner's earlier knowledge places strong constraints on new learning, promoting some forms of learning, while blocking others.

The overall hypothesis is that instruction that systematically reflects the complex [[features]] of targeted knowledge in relation to the learner’s existing knowledge leads to more robust learning than instruction that does not. The principle is that the gap between targeted knowledge and existing knowledge needs to be directly reflected in the organization of instructional events. This organization includes the structure of knowledge components selected for instruction, the scheduling of learning events, practice, recall opportunities, explicit and implicit presentations, and other activities.

This hypothesis can be rephrased in terms of the PSLC general hypothesis, which is that [[robust learning]] occurs when the [[learning event space]] is designed to include appropriate target paths, and when students are encouraged to take those paths. The studies in this cluster focus on the formulation of well specified target paths with highly predictable learning outcomes.

===Significance===
A core theme in this cluster is that instruction in basic skills can facilitate the acquisition and refinement of knowledge and prepare the learner for [[fluency]]-enhancing practice. Instruction that provides practice and feedback for basic skills on a schedule that closely matches observed student abilities is important for this goal, and can be effectively delivered by computer. In the area of second language learning, the strengths of computerized instruction are matched by certain weaknesses. In particular, computerized tutors are not yet good at speech recognition, making it difficult to assess student production. Moreover, contact with a human teacher can increase the breadth of language usage, as well as motivation. Therefore, an optimal environment for language learning would combine the strengths of computerized instruction with those of classroom instruction. It is possible that a similar analysis will apply to science and math.

=== Glossary ===
[[:Category:Refinement and Fluency|Refinement and Fluency]] glossary.

=== Research question ===
The overall research question is how can instruction optimally organize the presentation of complex targeted knowledge, taking into account the learner’s existing knowledge as well as an analysis of the target domain? In examining this general question, the studies focus on the following dimensions of instructional organization, among others: the demands placed on learners of specific knowledge components, the scheduling of practice, the timing and extent of explicit teaching events relative to implicit learning opportunities, and the role of feedback.

=== Independent variables ===
At a general level, the research varies the organization of instructional events. This organization variable is typically based on alternative analyses of task demands, relevant knowledge components, and learner background.

=== Dependent variables ===
The dependent variables in these studies assess learner performance during learning events and following learning. Typical measures are percentage correct and number of learning trials or time to reach a given standard of performance. Response times are also measured in some cases.

=== Hypotheses ===
The overall hypothesis is that instruction that systematically reflects the complex features of targeted knowledge in relation to the learner’s existing knowledge leads to more robust learning than instruction that does not. A corollary of this hypothesis is that learning is increased by instructional activities that require the learner to attend to the relevant knowledge components of a learning task.

Specific hypotheses about the organization of instruction derive from task analyses of specific domain knowledge and the existing knowledge of the learner. A background assumption for most studies is that fluency is grounded in well-practiced lower level skills. A few examples of specific hypotheses are as follows:

1. scheduling of practice hypothesis: The optimal scheduling of practice uses principles of memory consolidation to maximize robust learning and achieve mastery.

2. Resonance hypothesis: The acquisition of knowledge components can be facilitated by evoking associations between divergent coding systems.

3. explicit instruction hypothesis: Explicit rule-based instruction facilitates the acquisition of specific skills, but only if the rules are simple.

4. implicit instruction hypothesis: Implicit instruction or exposure serves to foster the development of initial familiarity with larger patterns.

5. Feedback hypothesis: Instruction that provides immediate, diagnostic feedback will be superior to instruction that does not.

6. cue validity hypothesis: In both explicit and implicit instruction, cue validity plays a central role in determining ease of learning of knowledge components.

7. Focusing hypothesis: Instruction that focuses the learner's attention on valid cues will lead to more robust learning than unfocused instruction or instruction that focuses on less valid cues.

8. learning to learn hypothesis: The acquisition of skills such as analysis, help-seeking, or advance organizers can promote future learning.

9. Learner knowledge hypothesis: A learner's existing knowledge places strong constraints on new learning, promoting some forms of learning, while blocking others.

=== Explanation ===
All knowledge involves content and procedures that are specific to a domain. An analysis of the domain reveals the complexities that a learner of a given background will face and the knowledge components that are part of the overall complexity. Accordingly, the organization of instruction is critical in allowing the learner to attend to the critical valid features of knowledge components and to integrated them in authentic performance. Acquiring valid features and strengthening their associations facilitates retrieval during subsequent assessment and instruction, leading to more robust learning. Additionally, robust learning is increased by the scheduling of learning events that promotes the [[long-term retention]] of the associations.

=== Descendents ===

Explicit instruction and manipulations of attention & discrimination
* [[Intelligent_Writing_Tutor | First language effects on second language grammar acquisition]] (Mitamura-Wylie)
* [[Learning the role of radicals in reading Chinese]] (Liu et al.)
* [[Basic skills training|French dictation training]] (MacWhinney)
* [[Chinese pinyin dictation]] (Zhang-MacWhinney)
* [[A_Multimodal_%28Handwriting%29_Interface_for_Solving_Equations| A multimodal (handwriting) interface for solving equations]] (Anthony, Yang, & Koedinger) [Was in CL]
*[[Note-Taking_Technologies | Note-taking Project Page (Bauer & Koedinger)]]
**[[Note-Taking: Restriction and Selection]] (completed)
**[[Note-Taking: Focusing On Concepts]] (planned)
**[[Note-Taking: Focusing On Quantity]] (planned)
**[[A word-experience model of Chinese character learning]] (planned)

Optimal scheduling & fluency pressure
* [[Optimizing the practice schedule]] (Pavlik et al.)
* [[French gender cues | French Grammatical Gender Cue Learning Through Optimized Practice]] (Presson-MacWhinney)
* [[Japanese fluency]] (Yoshimura-MacWhinney)
* [[Providing optimal support for robust learning of syntactic constructions in ESL]] (Levin, Frishkoff, De Jong, Pavlik)
* [[Fostering fluency in second language learning]] (De Jong, Perfetti)

Knowledge accessibility including background knowledge & knowledge suppression
* [[Using syntactic priming to increase robust learning]] (De Jong, Perfetti, DeKeyser)

Active processing including learner control
* [[Mental rotations during vocabulary training]] (Tokowicz-Degani)

Novel knowledge component and cognitive task analysis
* [[The_Help_Tutor__Roll_Aleven_McLaren|Tutoring a meta-cognitive skill: Help-seeking (Roll, Aleven & McLaren)]] [Was in Coordinative Learning and in Interactive Communication]
* [[Composition_Effect__Kao_Roll|What is difficult about composite problems? (Kao, Roll)]]
* [[Arithmetical fluency project]] (Fiez)

=== Annotated bibliography ===
Forthcoming

[[Category:Cluster]]