Results 191 to 200 of about 30,508 (218)

MetaComb: a meta-learning framework for drug combination response prediction from cell lines to patients. [PDF]

Front Genet
Guo C, Li T, Deng X, Ma Y, He F, Diao L, Wang Z, Li D, Liu Z.   +8 more
europepmc   +1 more source

Heutagogy: A Comprehensive Review of Self-Determined Learning in Contemporary Education. [PDF]

Cureus
Panta R.
europepmc   +1 more source

AI-driven CRISPR screening: optimizing gene editing through automation and intelligent decision support. [PDF]

J Transl Med
Zhao Y, Li X, Du Y.
europepmc   +1 more source

Techniques for mitigating overfitting in machine learning: a comprehensive review, taxonomy, and practical guide. [PDF]

Front Artif Intell
Sheppert AP.
europepmc   +1 more source

Priming iTBS for lower limb rehabilitation after stroke: Protocol for a randomized controlled trial on efficacy and neuroplasticity. [PDF]

PLoS One
Pan Z, Lu J, Sun Y, Qian Y, Shao Y, Chen C, Liu H, Zhang J, Huang Z, Sun L, Yu K, Zhou Y, Wang H, Su B.   +13 more
europepmc   +1 more source

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Action Learning, Fragmentation, and the Interaction of Single-, Double-, and Triple-Loop Change

The Journal of Applied Behavioral Science, 1999
The action-learning framework is traditionally used to summarize complex change efforts as one of three methods: single-, double-, or triple-loop. Although this summary is quite useful for some kinds of organizational analysis, it can oversimplify and thus ignore the fragmented, contradictory nature of change.
Erica Gabrielle Foldy, W. E. Douglas Creed   +1 more
openaire   +1 more source

Single, Double & Triple Loop Learning In Engineering Design Assessments A Case Study

2022
Rehman, Naveed Ur, Gabriel, Carlo
openaire   +1 more source

Trial of a Workshop Adapting Single-/Double-loop Learning for Nursery Student Teachers

CHUGOKUGAKUEN Journal, 2020
Sasaki, Hironori, Sasaki, Hironori
openaire   +1 more source

Revitalizing double‐loop learning in organizational contexts: A systematic review and research agenda

European Management Review, 2023
Mercedes-Victoria Auqui-Caceres, Andrea Furlan   +1 more
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