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LAWS6032 Chap.9 Evaluation Research and Proposal Integration

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Chapter 9 of 9 · LAWS6032

Evaluation Research and Proposal Integration

Evaluation begins with the decision to be supported: whether a program is needed, evaluable, implemented, effective or worth its resources. Different evaluation types require different criteria and evidence. The chapter then reconnects the whole unit in a research proposal, aligning rationale, literature, question, design, data, analysis, ethics, practical needs, limitations and the contribution to crime policy.

In this chapter

What this chapter covers

  • 01

    Needs and target-population assessment

  • 02

    Evaluability and program definition

  • 03

    Process evaluation and implementation fidelity

  • 04

    Outcome evaluation and counterfactuals

  • 05

    Economic assessment and valued outcomes

  • 06

    Logic models linking inputs to outcomes

  • 07

    Commissioner interests and evaluation independence

  • 08

    Proposal coherence from rationale to claim

Worked example · free

Planning a court-reminder evaluation

Q [8 marks]. A new reminder service is operating, but its reach and delivery are unclear. Build a proposal that supports the next policy decision without prematurely claiming impact. The marks shown here are not a University assessment scheme.
  • +2Review the need and program theory, then ask whether eligible defendants receive the planned service and how they experience it.
  • +2Analyse delivery records for reach and fidelity, and conduct purposive interviews across successful and failed contacts.
  • +2Address consent, linkage, legal vulnerability, service dependence and commissioner influence on reporting.
  • +2Conclude on implementation knowledge needed before a later outcome evaluation rather than claiming causal effect on attendance.
The design is a process evaluation because program reach and operation remain uncertain. Administrative and interview evidence have separate roles, ethical risks are explicit, and the contribution is readiness for a stronger later outcome study.
Sia tip — Name the policy decision first. It will tell you whether the evaluation should examine need, delivery, outcome or cost.
Glossary

Key terms

Needs assessment
An evaluation of the nature, scale and distribution of a problem and whether a proposed response is required.
Evaluability assessment
An assessment of whether a program is sufficiently defined, feasible and supported by data to undergo meaningful evaluation.
Process evaluation
An examination of implementation, activities, outputs, reach, fidelity and barriers to delivery.
Outcome evaluation
An assessment of whether intended outcomes changed and whether the design supports attributing change to the program.
Economic assessment
An evaluation comparing program resources or costs with specified outcomes or benefits.
Program logic
A model linking resources, activities, outputs, outcomes and assumptions about how change should occur.
Implementation fidelity
The degree to which a program is delivered consistently with its intended model.
FAQ

Evaluation Research and Proposal Integration FAQ

How do I choose an evaluation type?

Start with the decision. If the problem or population is unclear, assess need. If the program is vague, assess evaluability. If delivery is uncertain, examine process. If implementation is established and a credible comparison exists, examine outcomes. Add economic assessment when resource value is the decision.

Why is process evidence needed in an outcome study?

Without implementation evidence, an absent effect is ambiguous. The program theory may be wrong, or eligible people may never receive the intended service. Reach, fidelity and exposure help distinguish theory failure from delivery failure and explain variation in outcomes.

How can commissioners affect an evaluation?

Funders and administering agencies provide access and operational knowledge, but may prefer favourable questions, short timeframes or selective publication. Agree evaluation criteria, governance, data rights and reporting independence early, and document stakeholder roles transparently.

What makes a research proposal coherent?

Each section should create the need for the next: the literature establishes a consequential gap, the question defines the evidence required, the design produces that evidence, analysis supports a bounded claim, and ethics and feasibility make the plan responsible and executable.

How should the proposal conclusion be written?

State the knowledge the design can produce, the policy decision it can improve and the uncertainty that remains. Trace every conclusion verb backward to analysis, data and design. Remove statewide, causal or representative claims when the planned sample or comparison cannot earn them.

How can I test proposal feasibility before submission?

Build a short dependency list covering access permission, recruitment, records, measures, software, time and ethical review. For each dependency, name evidence that it is realistic and a narrower fallback question. Feasibility improves when the fallback still produces useful policy knowledge rather than merely shrinking the sample without changing the claim.

Study strategy

Assessment move

Make a decision tree beginning with need, evaluability, process, outcome and cost. For each branch, write the core question, preferred evidence and most common overclaim. Practise drawing a logic model for a simple justice program and identify an assumption between every arrow. Then choose measures for inputs, activities, outputs and outcomes without confusing them.

For proposal revision, colour-code the rationale, research question, sample, measurement, analysis and conclusion. The same concepts should recur consistently across colours. Remove any method that lacks a named purpose and any claim unsupported by the planned comparison. Write limitations as mechanisms with consequences and mitigations.

Close the proposal by explaining how the study would improve a specific policy decision while preserving the uncertainty that requires later research. Perform a commissioner audit by listing who funds, administers, participates in and is affected by the program, then decide who helps define success and who controls publication.

Build a data-availability timeline before promising outcomes that cannot emerge within the study period. For every proposed measure, classify it as an input, activity, output or outcome. Read the completed proposal backward from conclusion to rationale. Each claim should point to an analysis, dataset, design choice and question.

Any broken link signals scope creep or an unsupported promise that should be removed rather than disguised with stronger language.

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