Difference between revisions of "Understanding paired associate transfer effects based on shared stimulus components"

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=== Applying optimal scheduling of practice in the Chinese Learnlab study ===
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{| class="wikitable"  border="1" style="margin: 2em auto 2em auto"
 
+
|-
Under Construction
+
! PIs
 +
| Pavlik, MacWhinney, Bolster, Koedinger
 +
|-
 +
! Faculty
 +
| MacWhinney, Koedinger
 +
|-
 +
! Postdocs
 +
| Pavlik
 +
|-
 +
! Others with > 160 hours
 +
| Bolster, Dozzi
 +
|-
 +
! Learnlab
 +
| None (stimuli from Chinese learnlab)
 +
|-
 +
! Number of participants
 +
| 80
 +
|-
 +
! Total Participant Hours
 +
| 80
 +
|-
 +
! Datashop?
 +
| Yes
 +
|}
  
 
=== Abstract ===
 
=== Abstract ===
  
Over the course of approximately 448 practice trials of Chinese vocabulary practice, certain scedules of practice were delivered to test several transfer hypotheses implied (but not implmemented) by the model of practice used for in-vivo experiment optimal training schedules.  
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Over the course of approximately 448 practice trials of Chinese vocabulary practice, certain schedules of practice were delivered to test several [[transfer]] hypotheses implied (but not implemented) by the model of practice used for in-vivo experiment optimal training schedules.  
  
These schedules made use of the fact that there are 6 ways to test (Pinyin->English, Sound->English, Hanzi->English, English->Pinyin, Sound->Pinyin, Hanzi->Pinyin) vocabulary knowledge given current tutor capability. There were 21 total within-subjects conditions each with a particular sequence of the 6 types of trials. For instance, to look for unit learning we compared a condition where subjects practiced a Hanzi-Pinyin pair with a study (a presentation of the entire pair) followed by a drill 4 trials later with a condition where the preparation was identical expect that prior to Hanzi->Pinyin practice subjects had 2 trials of English->Pinyin practice for the same word. In this case, if the Hanzi->Pinyin practice benefits from prior English->Pinyin practice it seems to imply that the Pinyin response is being learned as a unit somewhat independently of any particualr association.
+
These schedules made use of the fact that there are 6 ways to test (Pinyin->English, Sound->English, Hanzi->English, English->Pinyin, Sound->Pinyin, Hanzi->Pinyin) vocabulary knowledge given current tutor capability. There were 21 total within-subjects conditions each with a particular sequence of the 6 types of trials. For instance, to look for unit learning we compared a condition where subjects practiced a Hanzi-Pinyin pair with a study (a presentation of the entire pair) followed by a drill 4 trials later with a condition where the preparation was identical expect that prior to Hanzi->Pinyin practice subjects had 2 trials of English->Pinyin practice for the same word. In this case, if the Hanzi->Pinyin practice benefits from prior English->Pinyin practice it seems to imply that the Pinyin response is being learned as a unit somewhat independently of any particular association.
  
There were 3 main hypotheses described below, which we call unit knowledge component learning, resonant learning, and stimulus mapping.
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There were 3 main hypotheses described below, which we call unit [[knowledge component]] learning, resonant learning, and stimulus mapping.
  
 
In all three cases the hypothesis was confirmed.
 
In all three cases the hypothesis was confirmed.
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=== Glossary ===
 
=== Glossary ===
 
* [[Optimal Spacing Interval]]
 
* [[Optimal Spacing Interval]]
* [[Expanding Spacing Interval]]
 
* [[Wide Spacing Interval]]
 
* [[Narrow Spacing Interval]]
 
 
* [[Pinyin]]
 
* [[Pinyin]]
 
* [[Hanzi]]
 
* [[Hanzi]]
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=== Research question ===
 
=== Research question ===
  
What sorts of complexity needs to be accounted for to make the ACT-R delcarative memory model adequately represent the various common types of transfer in vocabulary learning?
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What sorts of complexity needs to be accounted for to make the ACT-R [[declarative]] memory model adequately represent the various common types of transfer in vocabulary learning?
  
 
=== Background and significance ===
 
=== Background and significance ===
  
There is a venerable literature (Soloman & Asch, 1962) on effects like those described in this work, but there appears to be no unified modeling of such phenomena in the context of a practice scheduling algorithm. The assumption is that increased accuracy of the model will increase the accuracy of the predictions it makes when calcualting schedules during in-vivo learning.
+
There is a venerable literature (e.g. Soloman & Asch, 1962) on effects like those described in this work, but there appears to be no unified [[modeling]] of such phenomena in the context of a practice scheduling algorithm. The assumption is that increased accuracy of the model will increase the accuracy of the predictions it makes when calculating schedules during in-vivo learning.
  
For example, based on the idea that there is desireable difficulty for practice, one might assume that it is better to start by giving Foreign->English drill and then reverse to English->Foreign drill after an initial proficiency is reached. Unfortuantely, determining this initial proficiency necessary befire tranistioning to a more difficut task must be done on a case by case basis unless there is a detailed model that encompasses both tasks. This study helps to provide such a model.
+
For example, based on the idea that there is desirable difficulty for practice, one might assume that it is better to start by giving Foreign->English drill and then reverse to English->Foreign drill after an initial proficiency is reached. Unfortunately, determining this initial proficiency necessary before transitioning to a more difficult task must be done on a case by case basis unless there is a detailed model that encompasses both tasks. This study helps to provide such a model.
  
 
=== Dependent variables ===
 
=== Dependent variables ===
Measures of normal and robust learning.
+
 
 +
Naive subjects were screened for no prior Chinese experience. Effects of conditions were assessed approximately one minute after treatments.
 +
 
 +
[[Transfer]] was measured in the unit knowledge component learning conditions and in the resonant learning conditions.
  
 
=== Independent variables ===
 
=== Independent variables ===
Alternative structures of [[instructional schedule]] for [[knowledge component training]] based on the predictions of an ACT-R based cognitive model. Further independent variables include how the material is presented for each learning event and the assumptions of the model used to presents schedule the learning. The assumptions of the model include alternative analyses of task demands, the structure of relevant knowledge components, and learner background.
+
Alternative structures of [[instructional schedule]] for [[knowledge component training]] based on the predictions of an ACT-R based cognitive model. In this study the manipulations all involved the effects of having related (but not identical practice) prior to some comparison practice.
  
 
=== Hypothesis ===
 
=== Hypothesis ===
Robust learning is increased by instructional activities that require the learner to  attend to the relevant knowledge components of a learning task.
+
;Unit knowledge component learning:This hypothesis proposes that the stimulus items (sound file, Hanzi character, pinyin, or English) are learned as individual components somewhat independent of the pairings they occur in. Supports the notion of knowledge decomposition.
 +
;Resonant learning:This hypothesis proposes that people spontaneously recall related knowledge components (spreading activation) when prompted to recall a specific pair. Further, this covert practice results in measurable learning
 +
;Stimulus mapping:This is the straightforward notion that learning of the connection between an orthography and a sound is advantaged because there are mapping rules (knowledge components) that allow this conversion.
  
 
=== Findings ===
 
=== Findings ===
 +
All three hypotheses were confirmed. A paper is in preparation describing these important results.
  
 
=== Explanation ===
 
=== Explanation ===
Attention to features of the task domain as a knowledge component is processed leads to associating those features with the knowledge component.  If the features are valid, then forming or strengthening such associations facilitates retrieval during subsequent assessment or instruction, and thus leads to more robust learning.
 
  
=== Descendents ===
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;Unit knowledge component learning:The results supporting knowledge component learning appear to suggest that unitary knowledge (a pinyin response for instance) learned in one context applies directly to other contexts that require the same knowledge components.
 +
;Resonant learning:These results show that learning is an active process that is not constrained by the specific stimulus demand, but rather extends to other recently learned information. The result also suggests that building more complex relational knowledge structures may have advantages due to improved reflective learning.
 +
;Stimulus mapping:This result implies that rules(procedures) are learned which result in a general abilities to translate between certain vocabulary representations (primarily orthography-phonology).
 +
 
 +
=== Descendants ===
  
 
[[Optimizing the practice schedule]]
 
[[Optimizing the practice schedule]]
  
 
=== Annotated bibliography ===
 
=== Annotated bibliography ===
Forthcoming
 
  
[[Category:Study]]
+
*Pavlik Jr., P. I. (2006). Transfer effects in Chinese vocabulary learning. In R. Sun (Ed.), Proceedings of the Twenty-Eighth Annual Conference of the Cognitive Science Society (pp. 2579). Mahwah, NJ: Lawrence Erlbaum. [http://www.learnlab.org/uploads/mypslc/publications/pavlik-transfereffects.pdf (Article and pilot study for work above)]
  
 
[[Category:Study]]
 
[[Category:Study]]

Latest revision as of 11:28, 3 December 2007

PIs Pavlik, MacWhinney, Bolster, Koedinger
Faculty MacWhinney, Koedinger
Postdocs Pavlik
Others with > 160 hours Bolster, Dozzi
Learnlab None (stimuli from Chinese learnlab)
Number of participants 80
Total Participant Hours 80
Datashop? Yes

Abstract

Over the course of approximately 448 practice trials of Chinese vocabulary practice, certain schedules of practice were delivered to test several transfer hypotheses implied (but not implemented) by the model of practice used for in-vivo experiment optimal training schedules.

These schedules made use of the fact that there are 6 ways to test (Pinyin->English, Sound->English, Hanzi->English, English->Pinyin, Sound->Pinyin, Hanzi->Pinyin) vocabulary knowledge given current tutor capability. There were 21 total within-subjects conditions each with a particular sequence of the 6 types of trials. For instance, to look for unit learning we compared a condition where subjects practiced a Hanzi-Pinyin pair with a study (a presentation of the entire pair) followed by a drill 4 trials later with a condition where the preparation was identical expect that prior to Hanzi->Pinyin practice subjects had 2 trials of English->Pinyin practice for the same word. In this case, if the Hanzi->Pinyin practice benefits from prior English->Pinyin practice it seems to imply that the Pinyin response is being learned as a unit somewhat independently of any particular association.

There were 3 main hypotheses described below, which we call unit knowledge component learning, resonant learning, and stimulus mapping.

In all three cases the hypothesis was confirmed.

Glossary

Research question

What sorts of complexity needs to be accounted for to make the ACT-R declarative memory model adequately represent the various common types of transfer in vocabulary learning?

Background and significance

There is a venerable literature (e.g. Soloman & Asch, 1962) on effects like those described in this work, but there appears to be no unified modeling of such phenomena in the context of a practice scheduling algorithm. The assumption is that increased accuracy of the model will increase the accuracy of the predictions it makes when calculating schedules during in-vivo learning.

For example, based on the idea that there is desirable difficulty for practice, one might assume that it is better to start by giving Foreign->English drill and then reverse to English->Foreign drill after an initial proficiency is reached. Unfortunately, determining this initial proficiency necessary before transitioning to a more difficult task must be done on a case by case basis unless there is a detailed model that encompasses both tasks. This study helps to provide such a model.

Dependent variables

Naive subjects were screened for no prior Chinese experience. Effects of conditions were assessed approximately one minute after treatments.

Transfer was measured in the unit knowledge component learning conditions and in the resonant learning conditions.

Independent variables

Alternative structures of instructional schedule for knowledge component training based on the predictions of an ACT-R based cognitive model. In this study the manipulations all involved the effects of having related (but not identical practice) prior to some comparison practice.

Hypothesis

Unit knowledge component learning
This hypothesis proposes that the stimulus items (sound file, Hanzi character, pinyin, or English) are learned as individual components somewhat independent of the pairings they occur in. Supports the notion of knowledge decomposition.
Resonant learning
This hypothesis proposes that people spontaneously recall related knowledge components (spreading activation) when prompted to recall a specific pair. Further, this covert practice results in measurable learning.
Stimulus mapping
This is the straightforward notion that learning of the connection between an orthography and a sound is advantaged because there are mapping rules (knowledge components) that allow this conversion.

Findings

All three hypotheses were confirmed. A paper is in preparation describing these important results.

Explanation

Unit knowledge component learning
The results supporting knowledge component learning appear to suggest that unitary knowledge (a pinyin response for instance) learned in one context applies directly to other contexts that require the same knowledge components.
Resonant learning
These results show that learning is an active process that is not constrained by the specific stimulus demand, but rather extends to other recently learned information. The result also suggests that building more complex relational knowledge structures may have advantages due to improved reflective learning.
Stimulus mapping
This result implies that rules(procedures) are learned which result in a general abilities to translate between certain vocabulary representations (primarily orthography-phonology).

Descendants

Optimizing the practice schedule

Annotated bibliography

  • Pavlik Jr., P. I. (2006). Transfer effects in Chinese vocabulary learning. In R. Sun (Ed.), Proceedings of the Twenty-Eighth Annual Conference of the Cognitive Science Society (pp. 2579). Mahwah, NJ: Lawrence Erlbaum. (Article and pilot study for work above)