Turning the discrepancy model into an instrument you can actually administer
Introduction
Topics 12 and 13 gave you the concept of need and three approaches for diagnosing it. This topic covers the single most common tool used to operationalise all of that in the field: the needs survey. Where Topic 13's approaches (performance, task, competency) tell you what kind of gap you are looking for, a needs survey is the concrete instrument that gathers data from a group of people — farmers, extension officers, trainees — to locate and rank those gaps in practice.
This topic focuses specifically on the survey as one data-gathering method within a larger needs assessment process. Topic 15 will broaden out to the full range of data collection methods; this topic goes deep on surveys because they are the tool most directly built on the discrepancy model already established in Topic 12.
๐ฏ Learning Outcomes
- Place the needs survey within Witkin and Altschuld's three-phase model of needs assessment.
- Explain the Borich needs assessment model and how a Mean Weighted Discrepancy Score (MWDS) is calculated.
- Identify when a survey is the appropriate tool versus alternatives like interviews or group techniques.
- Cross-connect this topic to Topic 12's discrepancy definition and forward to Topic 15 and Practical 1.
๐ Why This Matters
The Borich (1980) model has been used for over four decades to determine the professional development needs of agricultural educators, and remains one of the most widely applied needs-assessment instruments in agricultural-education research today — including in Indian extension research published in the ICAR-affiliated literature. Learning it here gives you a tool you are likely to encounter again directly in research methods and possibly in your own dissertation work.
1. Where the Needs Survey Fits: Witkin and Altschuld's Three Phases
Belle Ruth Witkin and James Altschuld's Planning and Conducting Needs Assessments: A Practical Guide (1995) is the standard reference for structuring a needs assessment project. It defines a needs assessment as a systematic set of procedures for setting priorities and making decisions about programme improvement, built around three phases:
Phase 1 — Pre-assessment
Exploratory: define the purpose, identify what information already exists, and decide on appropriate methods before collecting new data.
Phase 2 — Assessment ← the survey sits here
Data gathering and analysis. The needs survey is the most common quantitative instrument used in this phase.
Phase 3 — Post-assessment
Setting priorities, communicating results, and evaluating the needs assessment process itself for effectiveness.
Cross-reference: This three-phase structure parallels Topic 9's 8-step design process (needs assessment is itself Step 1 of that sequence) and is exactly what you practised, at least informally, in Practical 1.
2. The Borich Model: Designing a Needs Survey Instrument
George Borich's (1980) needs assessment model, originally published in the Journal of Teacher Education, is the standard method for designing a needs-survey questionnaire in agricultural extension and education research. Respondents rate each competency or item on two paired scales — most commonly:
- Importance of the competency/skill to their job, and
- Ability (their current proficiency at it) — or equivalently, "what is" versus "what should be", echoing Topic 12's discrepancy definition directly.
For each item, a discrepancy score is calculated (importance rating minus ability rating), then weighted by the mean importance rating across all respondents, and finally averaged across the sample to produce a Mean Weighted Discrepancy Score (MWDS) for each competency. Items with the highest MWDS represent the highest-priority training needs — the logic being that a large gap on a competency people also consider highly important deserves more attention than an equally large gap on something unimportant.
⚠️ Why Weight by Importance at All?
A raw discrepancy score alone can mislead priority-setting: a competency rated as low-importance can still show a large "what is/what should be" gap without being a genuine training priority. Weighting the discrepancy by importance keeps the survey anchored to Topic 12's caution that a felt gap is not automatically a priority need — it must also matter to the role.
3. When a Survey Is (and Isn't) the Right Tool
Surveys using the Borich approach work best when the competencies or skill areas to be rated are already reasonably well known or defined in advance — for example, when Topic 13's task analysis has already produced a list of tasks and KSAs to rate. When the needs themselves are not yet known or well defined, other Phase 2 techniques are usually preferred first:
| Technique | Best Used When |
|---|---|
| Needs Survey (Borich-type) | The list of competencies/skills is already known; you need to rank and prioritise them across a group. |
| Interviews | Needs are not yet clearly defined; you need depth and context from a smaller number of respondents. |
| Nominal Group Technique | You need a structured group process to surface and rank needs when they are not predetermined. |
| Delphi Technique | You need convergent expert opinion gathered over multiple rounds, especially with geographically dispersed experts. |
Cross-reference: Topic 15 (Data Collection Methods in Identifying Needs) develops this fuller toolkit; this topic deliberately narrows in on the survey because of its direct, formal link to Topic 12's discrepancy model.
๐พ Extension Angle
Needs-survey studies using the Borich model are common in agricultural extension research: studies have applied it to identify the training needs of agricultural extension agents by rating their perceived competence against the importance of specific extension competencies, generating a ranked MWDS list that directly informs which topics an in-service training programme should prioritise.
๐ฎ๐ณ Indian Institutional Context
The Borich model and Mean Weighted Discrepancy Score approach appear directly in Indian agricultural extension research, including studies published in ICAR's Journal of Agricultural Extension Management and the Indian Journal of Extension Education, which have used MWDS rankings to identify training needs of extension functionaries and agricultural research students. This makes the Borich approach directly usable — not just as an imported Western model — in Krishi Vigyan Kendra or State Agricultural University training-needs studies you may encounter or conduct yourself.
๐ Beyond Agriculture
Corporate training needs surveys frequently use the same paired importance/ability logic, even without naming Borich directly — asking employees or managers to rate both how important a skill is to the role and how well it is currently performed, then prioritising training investment toward the largest weighted gaps. The underlying mathematics of the MWDS transfers unchanged across sectors.
Frequently Asked Questions
- Witkin, B. R., & Altschuld, J. W. (1995). Planning and Conducting Needs Assessments: A Practical Guide. Thousand Oaks, CA: Sage Publications.
- Borich, G. D. (1980). A needs assessment model for conducting follow-up studies. Journal of Teacher Education, 31(3), 39–42.
- Benge, M., Harder, A., & Warner, L. (2019). Conducting the Needs Assessment #1: Introduction (WC340). Gainesville, FL: University of Florida, IFAS Extension. [Applies Witkin & Altschuld, 1995, directly to Extension practice.]
- Khalil, A. H. O. (2018). Training needs identification of agricultural extension agents. Journal of Agricultural Extension Management, 19(2). [Illustrative application of the Borich model in extension research.]
- McKim, B. R., & Saucier, P. R. (2011). An Excel-based mean weighted discrepancy score calculator. Journal of Extension, 49(2), Article 2TOT8.