Course Introduction
Computer-Assisted Personal Interviewing (CAPI) has transformed survey research by enabling organizations to replace paper-based questionnaires with structured digital instruments, automated interview logic, and integrated fieldwork monitoring systems. Effective CAPI implementation requires more than digitizing existing questions; it involves translating research objectives into reliable questionnaire logic, configuring validation rules, preparing digital devices, training interviewers, and establishing robust quality assurance procedures. This course equips participants with the knowledge and practical skills needed to design, program, test, deploy, and manage CAPI surveys for research, monitoring, evaluation, and evidence-based decision-making.
The course introduces the principles and operational components of CAPI systems, including digital questionnaire architecture, interview navigation, question types, response coding, skip logic, consistency checks, calculated variables, and structured data capture. Participants learn how to translate survey specifications into functional digital questionnaires that guide interviewers through complex interview sequences while minimizing avoidable errors. The training emphasizes the relationship between questionnaire design, respondent experience, data accuracy, and analytical requirements, helping participants understand how programming decisions influence the quality and usability of collected information.
A central component of the programme focuses on advanced questionnaire programming and testing. Participants explore conditional question display, branching logic, mandatory responses, range checks, date validation, repeatable sections, roster structures, and calculations appropriate to different survey designs. Practical exercises address household surveys, individual interviews, customer satisfaction studies, baseline assessments, service delivery evaluations, and socioeconomic research. Participants learn to identify programming defects, ambiguous response categories, contradictory validation conditions, and navigation problems through systematic testing, pilot interviews, and iterative refinement before questionnaires are released for operational use.
The training also examines the management of fieldwork operations, including interviewer recruitment and preparation, assignment planning, geographic coverage, sample tracking, interview scheduling, and daily progress monitoring. Participants explore how field supervisors can review completed interviews, identify missing or suspicious information, investigate unusual interview patterns, and provide timely feedback to enumerators. Additional attention is given to non-response management, callbacks, incomplete interviews, device readiness, synchronization procedures, and escalation of technical problems. These practices support consistent survey implementation across teams and locations while improving operational visibility and adherence to approved research protocols.
Data quality, research ethics, and information security are integrated throughout the course. Participants learn to establish quality standards for completeness, consistency, validity, timeliness, and appropriate documentation. They examine informed consent procedures, confidentiality, responsible handling of sensitive information, access controls, and secure transfer of survey records. The programme also addresses the appropriate use of paradata, such as interview timestamps and duration, to identify potential quality concerns without relying on a single indicator as proof of interviewer misconduct or respondent error. Participants develop a balanced approach to quality assurance that combines automated checks, supervisory review, field verification, and documented corrective action.
By the end of the training, participants will be better prepared to manage the complete CAPI implementation cycle, from questionnaire specifications and programming through field deployment, supervision, data review, and preparation of research-ready datasets. They will understand how to coordinate technical and field teams, establish practical monitoring procedures, and resolve common operational challenges. The skills developed are applicable to national household surveys, public health research, market research, customer experience studies, programme evaluations, and development assessments. The course promotes efficient field operations, reliable data collection, ethical interviewing, and stronger evidence for organizational planning and policy decisions.
Duration
5 days
Who Should Attend
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Survey researchers responsible for designing and implementing digital data collection instruments.
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Questionnaire programmers configuring CAPI forms, interview logic, and validation rules.
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Monitoring and evaluation officers conducting baseline, midline, endline, and impact assessment surveys.
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Fieldwork managers coordinating enumerators, assignments, timelines, and geographic coverage.
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Field supervisors responsible for reviewing interviews and maintaining data collection standards.
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Enumerators transitioning from paper-based interviewing to computer-assisted personal interviewing.
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Statisticians and research analysts who need to align questionnaire structures with analytical requirements.
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Data managers responsible for data quality, exports, documentation, and secure data handling.
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Research coordinators overseeing household, socioeconomic, public health, or service delivery surveys.
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Government statistical personnel involved in official surveys and population-level data collection.
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NGO and development programme staff conducting community assessments and beneficiary surveys.
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Market research professionals implementing customer, consumer, and product research studies.
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Academic researchers and postgraduate students using digital instruments for field-based research.
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Information technology professionals supporting survey platforms, devices, and field data workflows.
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Consultants and technical advisers responsible for survey methodology, digital implementation, and quality assurance.
Course Objectives
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Explain the principles, architecture, and operational requirements of CAPI systems and assess how computer-assisted interviewing can improve survey efficiency, consistency, and data reliability.
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Translate research objectives, survey methodology, questionnaire specifications, and analytical requirements into well-structured digital instruments with clear question sequencing and response options.
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Program questionnaire logic using conditional displays, skip patterns, required fields, validation rules, calculated variables, and repeatable structures appropriate to the selected CAPI platform.
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Design and test digital questionnaires for usability, logical consistency, respondent comprehension, interview duration, and accurate capture of household or individual-level information.
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Establish structured procedures for pilot testing, defect identification, questionnaire revision, version control, and final approval before field deployment.
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Organize fieldwork assignments, interviewer responsibilities, sample tracking, callback procedures, and daily reporting to support coordinated survey implementation across teams.
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Apply field supervision and quality assurance techniques to identify incomplete interviews, inconsistent responses, unusual data patterns, and operational deviations requiring investigation.
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Use available paradata and field monitoring indicators responsibly to assess interview progress, support supervision, and identify potential quality issues without drawing unsupported conclusions.
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Implement ethical interviewing and information protection procedures covering informed consent, confidentiality, sensitive data, secure device use, and appropriate access to survey records.
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Prepare a practical CAPI implementation plan covering questionnaire development, technical testing, interviewer training, deployment, field monitoring, data management, and final dataset delivery.
Comprehensive Course Outline
Module 1: Foundations of CAPI and Digital Survey Operations
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Introduction to computer-assisted personal interviewing, its core principles, and its role in modern household, social, health, and market research.
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Comparison of paper-based surveys and CAPI workflows, including data entry, questionnaire control, quality assurance, and operational efficiency.
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Overview of CAPI platform components, including questionnaire designers, interviewer applications, management interfaces, data storage, and export functions.
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Assessment of survey objectives, target populations, sampling procedures, field conditions, device requirements, and connectivity constraints before implementation.
Module 2: Questionnaire Design and Programming Specifications
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Translation of research questions, indicators, hypotheses, and survey protocols into clear questionnaire sections and digital data collection requirements.
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Development of question wording, response categories, reference periods, variable naming conventions, interviewer instructions, and coding standards.
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Design of interview flow, respondent screening, informed consent, household rosters, individual modules, and questionnaire termination conditions.
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Preparation of programming specifications, data dictionaries, logic diagrams, and acceptance criteria to guide development and testing.
Module 3: Core CAPI Questionnaire Programming
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Configuration of text, numeric, date, single-choice, multiple-choice, and other supported question types according to survey information requirements.
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Programming of skip patterns, conditional relevance rules, branching logic, and dynamic question displays based on earlier responses.
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Implementation of mandatory responses, range checks, cross-field validation, date restrictions, and consistency messages to prevent avoidable errors.
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Development of calculated variables, derived indicators, repeatable groups, and roster-based structures where supported by the chosen platform.
Module 4: Advanced Logic, Usability, and Interview Flow
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Design of complex eligibility rules, nested conditions, respondent-specific question paths, and multi-stage interview sequences.
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Application of appropriate validation logic for household size, ages, dates, income, expenditure, employment, and other related measurements.
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Improvement of interview navigation through clear prompts, logical section transitions, progress indicators, and user-friendly error messages.
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Assessment of accessibility, translation requirements, local terminology, respondent burden, and usability across different devices and field environments.
Module 5: Questionnaire Testing, Piloting, and Version Control
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Development of systematic test cases covering expected responses, edge cases, missing information, complex branching, and questionnaire completion.
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Conduct of technical testing and pilot interviews to assess functionality, question comprehension, interview duration, and operational feasibility.
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Identification and correction of logic defects, duplicate fields, inconsistent response categories, calculation errors, and confusing navigation.
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Implementation of controlled questionnaire revisions, version documentation, approval procedures, and release readiness checks before deployment.
Module 6: Fieldwork Planning and Enumerator Management
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Development of fieldwork schedules, team structures, interviewer assignments, geographic coverage plans, and daily implementation targets.
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Preparation of enumerator training, interview protocols, device orientation, respondent engagement techniques, and standardized field procedures.
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Management of sample disposition, contact attempts, callbacks, refusals, unavailable respondents, and other non-response situations.
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Establishment of field communication channels, technical support arrangements, escalation procedures, and daily team reporting routines.
Module 7: Field Supervision and Real-Time Progress Monitoring
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Use of available management dashboards and reporting functions to monitor assignments, completed interviews, outstanding work, and submission progress.
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Review of completed interviews for missing answers, contradictory responses, unusual values, and adherence to questionnaire and sampling procedures.
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Assessment of available paradata, including interview duration and timestamps, to identify patterns that may warrant additional quality checks.
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Design of supervisory feedback, verification, corrective action, and documentation procedures to address field problems consistently and transparently.
Module 8: Data Quality, Ethics, and Information Security
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Establishment of data quality standards covering completeness, accuracy, consistency, validity, timeliness, and traceability of collected information.
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Application of informed consent, voluntary participation, confidentiality, respondent safeguarding, and ethical management of sensitive questions.
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Implementation of device security, user access controls, secure data transfer, backup procedures, and organizational information protection policies.
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Development of procedures for resolving data discrepancies, documenting approved corrections, managing incidents, and preserving research integrity.
Module 9: Data Management, Export, and Analysis Preparation
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Review of submitted interview records, questionnaire structures, variable formats, response codes, and relationships between linked survey modules.
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Preparation of structured data exports using the formats and interfaces available in the selected CAPI platform.
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Development of codebooks, metadata, processing logs, and data cleaning procedures that support reproducibility and analytical transparency.
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Preparation of datasets for analysis using R, Stata, SPSS, Python, or spreadsheet tools, including checks for missing values, duplicates, and inconsistent records.
Module 10: Integrated CAPI Implementation and Capstone Exercise
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Development of a complete digital questionnaire prototype incorporating screening, core interview modules, validation rules, and programmed navigation.
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Execution of an end-to-end simulation covering interviewer login, interview administration, data submission, supervisor review, and quality issue resolution.
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Preparation of a fieldwork management plan that defines team responsibilities, assignment procedures, monitoring indicators, data protection, and escalation pathways.
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Presentation of the final implementation design, review of lessons learned, documentation of outstanding risks, and development of a prioritized improvement roadmap.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
