According to cognitive load theory (CLT), there exists an inverse relationship between the concentration of technological tools in educational setting...
GMAT Information and Ideas : (Ideas) Questions
According to cognitive load theory (CLT), there exists an inverse relationship between the concentration of technological tools in educational settings (including digital devices and interactive learning platforms) and students' achievement of profound learning outcomes. This theory attributes such outcomes to mental overload, as learners find it challenging to simultaneously manage various information channels. Two key indicators that demonstrate profound learning are metacognitive awareness (learners' capacity to observe and regulate their cognitive processes) and knowledge transfer ability (capability to utilize learned concepts in novel situations). In their comprehensive study examining more than 800 educational environments, Martinez and team assert that their findings challenge the predictions of CLT.
Which discovery would provide the strongest evidence for Martinez and team's assertion?
Martinez and team discovered a positive relationship between technological tool concentration and both metacognitive awareness and knowledge transfer ability.
Martinez and team discovered a negative relationship between profound learning outcomes and technological tool concentration.
Martinez and team discovered a positive relationship between profound learning outcomes and metacognitive awareness.
Martinez and team discovered a negative relationship between profound learning outcomes and both metacognitive awareness and knowledge transfer ability.
Step 1: Decode and Map the Passage
Create Passage Analysis Table
| Text from Passage | Analysis |
|---|---|
| "According to cognitive load theory (CLT), there exists an inverse relationship between the concentration of technological tools in educational settings (including digital devices and interactive learning platforms) and students' achievement of profound learning outcomes." |
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| "This theory attributes such outcomes to mental overload, as learners find it challenging to simultaneously manage various information channels." |
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| "Two key indicators that demonstrate profound learning are metacognitive awareness (learners' capacity to observe and regulate their cognitive processes) and knowledge transfer ability (capability to utilize learned concepts in novel situations)." |
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| "In their comprehensive study examining more than 800 educational environments, Martinez and team assert that their findings challenge the predictions of CLT." |
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Provide Passage Architecture & Core Elements
Main Point: Martinez and team's comprehensive study challenges cognitive load theory's prediction that increased technology use harms deep learning outcomes.
Argument Flow: The passage first establishes CLT's central claim that more technology leads to worse learning outcomes due to mental overload. It then defines what profound learning looks like through two specific indicators. Finally, it presents Martinez's research as directly challenging these established predictions.
Step 2: Interpret the Question Precisely
What's being asked? Which discovery would provide the strongest evidence for Martinez's assertion that their findings challenge CLT
What type of answer do we need? A specific research finding that would directly contradict CLT's predictions
Any limiting keywords? "strongest evidence" means we need the most direct contradiction of CLT's core claim
Step 3: Prethink the Answer
- Since CLT predicts an inverse relationship between tech tools and deep learning outcomes, Martinez's challenge would need to show the opposite
- The strongest evidence would be discovering a positive relationship between technology concentration and the specific indicators of profound learning: metacognitive awareness and knowledge transfer ability
- The right answer should show Martinez found that MORE technology actually leads to BETTER outcomes on the measures that CLT says should get worse
Martinez and team discovered a positive relationship between technological tool concentration and both metacognitive awareness and knowledge transfer ability.
- Shows positive relationship between tech tools and both learning indicators
- Directly contradicts CLT's inverse relationship prediction
- Provides strongest possible evidence by addressing both specific measures of profound learning
Martinez and team discovered a negative relationship between profound learning outcomes and technological tool concentration.
- Shows negative relationship between tech tools and deep learning
- This would actually SUPPORT CLT, not challenge it
Martinez and team discovered a positive relationship between profound learning outcomes and metacognitive awareness.
- Shows relationship between the two learning indicators themselves
- Doesn't address technology tools at all, so can't challenge CLT's tech-learning relationship
Martinez and team discovered a negative relationship between profound learning outcomes and both metacognitive awareness and knowledge transfer ability.
- Shows negative relationship between learning outcomes and their own indicators
- This doesn't make logical sense and doesn't address technology at all