The Effect of Manipulating Task Complexity Along Resource-Dispersing Dimension on L2 Written Performance from the Perspective of Complexity Theory
Bibliographic record
Abstract
From the perspective of complexity theory and based on Robinson's Cognition Hypothesis and the Triadic Componential Framework, this paper investigated the effect of manipulating task complexity along resource-dispersing dimension on L2 written performance. The results showed that: 1) Significant interactive effects were found between the two variables (i.e. task structure and planning). 2) Without planning, the accuracy and fluency of written output in tasks without structural constraint were significantly higher, while the syntactic complexity was lower. 3) Planning had no significant effect on accuracy. In macro-structure given task, planning promoted fluency and lexical complexity, but did not affect syntactic complexity. The result only partially supports the Cognition Hypothesis. Combined with previous research, it can be found that written output in tasks is nonlinear, multidimensional and self-adaptive. Researchers and teachers are suggested to fully consider task characteristics and individual differences, and not to take task complexity as the sole criterion when designing writing tasks.   
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".