Lecture note on evaluation research for housing studies dissertation project study

Lecture note on evaluation research for housing studies dissertation project study

 

In the context of study of research types, please clarify four main ideas of evaluation research and offer 4 main how-to advices on research methods practices in the context of Housing Studies dissertation project works.

 

Evaluation research is a form of applied research that systematically judges the merit, implementation, effects, and value for money of a policy, programme, service, or intervention. In Housing Studies, it can assess, for example, whether a public-rental allocation reform, estate renewal scheme, rental subsidy, or community-support initiative actually works for its intended residents.

Four main ideas

Evaluation focus	Core question	Housing Studies illustration
Needs assessment	What problem exists, for whom, how large is it, and what service or policy is needed?	Identify whether elderly tenants in a particular estate lack accessible facilities, social support, or affordable housing alternatives.
Process / implementation evaluation	Was the intervention delivered as designed, to the intended people, and with adequate quality?	Examine whether an estate-redevelopment consultation process reached tenants, provided understandable information, and handled relocation consistently.
Outcome / effectiveness evaluation	Did the intervention achieve its immediate stated objectives?	Test whether a rental-support programme reduced rent arrears, housing stress, overcrowding, or waiting-time dissatisfaction among eligible households.
Impact and efficiency evaluation	What wider or longer-term changes can plausibly be attributed to the intervention, and were the benefits worth the resources used?	Assess whether redevelopment improved residents’ wellbeing and neighbourhood cohesion relative to costs, while also identifying unintended effects such as displacement or weakened social networks.

These categories are related but not interchangeable. Process evaluation concerns how delivery occurred; outcome evaluation concerns the changes observed; impact evaluation asks whether the intervention caused those changes; and economic evaluation asks whether the benefits justify costs.

Four practical method advices

1.    Start with a clear programme theory and evaluative questions.
Draw a simple logic model: inputs → activities → outputs → short-term outcomes → longer-term impacts. Then state the evaluation criteria and indicators before data collection. For an estate renewal study, inputs may be public funding and staff; activities may be rehousing and consultation; outputs may be households relocated; and outcomes may include housing satisfaction, travel accessibility, and perceived community belonging.

2.    Match the design to the claim you want to make.
Use qualitative methods—semi-structured interviews, focus groups, observation, document analysis—when asking “how?”, “why?”, or exploring residents’ lived experience. Use surveys and administrative/ statistical data for prevalence, group differences, and associations. If the dissertation evaluates both measurable outcomes and residents’ explanations, a mixed-methods design is often appropriate; housing-research design guidance specifically supports combining quantitative comparisons with on-the-ground qualitative evidence. Avoid causal wording such as “the policy caused improved wellbeing” unless the design supports it. Stronger options include pre/ post measures, a comparison estate or eligible non-recipient group, matching, or longitudinal follow-up.

3.    Build a defensible sampling and measurement plan.
Define the population precisely: for example, “tenants aged 60+ relocated from Estate X between 2024 and 2026.” State inclusion and exclusion criteria, recruitment route, expected sample size, and sampling logic. Use probability sampling where you need generalisable estimates; use purposive sampling where you need information-rich participants, such as relocated tenants, social workers, housing officers, and community leaders. Probability and purposive selection are both established foundations in mixed-methods research. Operationalise abstract terms. “Housing satisfaction” might be measured through affordability, unit condition, crowding, accessibility, safety, estate facilities, and neighbourhood attachment—not one vague question.

4.    Treat ethics, triangulation, and limitations as central—not appendices.
Housing topics can expose financial hardship, insecure tenancy, family conflict, disability, and distrust of authorities. Obtain informed consent, avoid collecting unnecessary identifiers, anonymise quotations and locations where needed, make participation voluntary, and ensure that residents understand participation will not affect housing eligibility or services. Ethics in mixed-methods work spans design, participant selection, data collection and analysis, researcher–participant relationships, and reporting. Triangulate: compare resident accounts, survey patterns, policy documents, administrative data, and site observations. Report disagreement rather than hiding it—for example, a policy may meet its target number of relocated households while interviewees report poor communication or loss of informal support networks.

A dissertation-ready structure

A concise evaluation-research proposal could use this sequence:

1.    Define the policy/programme and its target population.

2.    State the evaluative purpose: need, implementation, outcome, impact, efficiency—or a justified combination.

3.    Develop a logic model and 3–5 focused evaluation questions.

4.    Select qualitative, quantitative, or mixed methods aligned to each question.

5.    Specify sampling, indicators, analysis methods, ethics, and limitations.

6.    Present findings by evaluation criterion, then make evidence-based recommendations.

For a Housing Studies dissertation, a manageable scope is usually one intervention, one locality or estate cluster, one defined population, and two or three evaluation dimensions—for instance, process, resident outcomes, and unintended consequences. This is more feasible and analytically stronger than trying to assess every citywide housing-policy effect.