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Charles Warfield

Biographic Data

ID6650560
NAMECharles Warfield
GIVEN NAMESCharles
FAMILY NAMEWarfield
SIGNATUREWARFIELD C
AFFILIATIONSWestern Michigan University
VERIFIEDNo
TOTAL WORKS3
TOTAL CITATIONS2
WORKS AS AUTHOR3
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2004
LATEST PUBLICATION YEAR2008
H-INDEX1
  • The Fidelity—Adaptation Relationship in Non-Evidence-Based Programs and its Implication for Program Evaluation

    Open Access•Jianping Shen, Huilan Yang et al.•ARTICLE•Evaluation•2008•References: 3

    Based on our experience in helping design, implement, and evaluate a non-evidence-based program, we explore a non-conventional fidelity and adaptation relationship and its implications for program evaluation.We find that in non-evidence-based interventions, program fidelity and adaptation may not be competitors but serve to complement each other.This non-conventional relationship leads to expanded roles of evaluation in program design and impleme…

  • Multilevel Evaluation Alignment

    Open Access•Hua Yang, Jia Shen et al.•ARTICLE•American Journal of Evaluation•2004•Cited by: 1•References: 2

  • Multilevel Evaluation Alignment

    Open Access•Huilan Yang, Jianping Shen et al.•ARTICLE•American Journal of Evaluation•2004•Cited by: 1

    Using the evaluation work on the W.K. Kellogg Foundation’s Unleashing Resources Initiative as an example, in this article we explicate a general four-step model appropriate for multilevel evaluation alignment. We review the relevant literature, argue for the need for evaluation alignment in a multilevel context, explain the four-step model, discuss the benefits of the model, and address the issues that one should pay attention to when implementin…

  • Multilevel Evaluation Alignment

    Open Access•Hua Yang, Jia Shen et al.•ARTICLE•American Journal of Evaluation•2004•Cited by: 1•References: 2

  • Multilevel Evaluation Alignment

    Open Access•Huilan Yang, Jianping Shen et al.•ARTICLE•American Journal of Evaluation•2004•Cited by: 1

    Using the evaluation work on the W.K. Kellogg Foundation’s Unleashing Resources Initiative as an example, in this article we explicate a general four-step model appropriate for multilevel evaluation alignment. We review the relevant literature, argue for the need for evaluation alignment in a multilevel context, explain the four-step model, discuss the benefits of the model, and address the issues that one should pay attention to when implementin…

  • Multilevel Evaluation Alignment

    Open Access•Hua Yang, Jia Shen et al.•ARTICLE•American Journal of Evaluation•2004•Cited by: 1•References: 2

  • Multilevel Evaluation Alignment

    Open Access•Huilan Yang, Jianping Shen et al.•ARTICLE•American Journal of Evaluation•2004•Cited by: 1

    Using the evaluation work on the W.K. Kellogg Foundation’s Unleashing Resources Initiative as an example, in this article we explicate a general four-step model appropriate for multilevel evaluation alignment. We review the relevant literature, argue for the need for evaluation alignment in a multilevel context, explain the four-step model, discuss the benefits of the model, and address the issues that one should pay attention to when implementin…

  • The Fidelity—Adaptation Relationship in Non-Evidence-Based Programs and its Implication for Program Evaluation

    Open Access•Jianping Shen, Huilan Yang et al.•ARTICLE•Evaluation•2008•References: 3

    Based on our experience in helping design, implement, and evaluate a non-evidence-based program, we explore a non-conventional fidelity and adaptation relationship and its implications for program evaluation.We find that in non-evidence-based interventions, program fidelity and adaptation may not be competitors but serve to complement each other.This non-conventional relationship leads to expanded roles of evaluation in program design and impleme…

Computer Science (3 works) · Engineering (3 works) · Evaluation and Performance Assessment (3 works) · Context (archaeology (2 works) · Epistemology (2 works) · Explication (2 works) · Foundation (evidence (2 works) · Machine learning (2 works) · Management science (2 works) · Multilevel model (2 works)

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