Advanced Monitoring and Evaluation

Explore the results chain, showing how inputs and resources drive activities, outputs, outcomes, and impact. Understand the logical order connecting each level and why breaking the chain prevents impact.

Explore the result chain in monitoring and evaluation, from inputs and activities to outputs, outcomes, and impact, using an education project for vulnerable children as a practical example.

Explore the logical framework, a project management tool that links means and ends in a four-by-four matrix, and the rogue frame, a dynamic system for planning, monitoring, and evaluating projects.

Trace the origins and history of the logical framework from NASA development to USAID adoption in the 1970s, solving vague planning, unclear responsibilities, and adversarial evaluations.

Explore the logical framework, or rock frame, a 4x4 matrix guiding monitoring and evaluation with project summary, indicators, means of verification, and risk and assumptions, from goal to activities.

Define indicators in a log frame and distinguish quantitative and qualitative measures, direct and indirect indicators, to track activities, outputs, outcomes, and impact through monitoring and evaluation.

Develop smart indicators that are specific, measurable, attainable, relevant, and time-bound, ensuring single measurements with the same unit, and practical data collection.

Identify means of verification as the sources of information for indicators, such as progress reports, survey reports, and government documents, to measure indicators in monitoring and evaluation.

Identify risks and assumptions at each project logic level, including outcome and go levels, and frame external factors positively to support success.

Explore how assumptions drive a bottom-up logical framework from activities to impact, showing how fulfilled assumptions yield outputs, outcomes, and project impact.

Design a project logical framework that links goal, outcomes, outputs, and activities with indicators, means of verification, and assumptions for improving education access to vulnerable orphans.

Develop a logical framework for a dairy value chain project, linking goal to outputs, indicators, verification, and assumptions. Pursue two objectives: boost milk production and establish a dairy market system.

Use the logical framework to design proposals for fundraising, define objectives and indicators, budget by objectives and activities, schedule activities, and guide monitoring and evaluation.

Explore the monitoring and evaluation framework, a table that defines the program's system, responsibilities, data flows, indicators, tools, and reporting timelines to inform decisions and guide implementation.

Explore the harmony framework structure and its log frame alignment, detailing intervention logic, indicators, baselines, targets, data sources, frequency of measurement, and reporting responsibilities.

Learn to document a monitoring and evaluation framework with indicators, baselines, targets, data sources, and annual reporting timelines, using grade six outcomes and reading proficiency indicators.

Learn monitoring and evaluation methods for data collection, including direct observation, surveys, interviews, focus group discussions, and pile ranking exercises, with thematic data analysis.

Direct observation records observable features at project sites using structured or informal checklists, collecting qualitative and quantitative data without asking questions.

Explore surveys and interviews to collect information on predetermined topics, capturing feelings and perceptions with guided questions; use key informant interviews for qualitative depth and surveys for quantitative insight.

Use focus group discussion as a semi-structured, qualitative method in monitoring and evaluation, gathering eight to twelve participants sharing characteristics to discuss guided issues, ensuring balanced participation for data triangulation.

Use the planking exercise to categorize roles by gender, collecting qualitative and quantitative indicators to measure project impact and participants' understanding of behaviors.

Use data triangulation to combine qualitative and quantitative monitoring and evaluation methods—interviews, surveys, focus groups, observations, and pile ranking—for stronger conclusions and better project management.

Explore how monitoring and evaluation tools guide data collection, align with indicators, and ensure concise, good enough information using questionnaires, focus group guides, interview guides, observation checklists, and sign-in sheets.

Use data types to choose monitoring and evaluation tools. Distinguish quantitative data with numerical responses and close-ended questions from qualitative data with detailed narratives and open-ended responses.

The tools' choice in monitoring and evaluation depends on data type (quantitative or qualitative) and data collection method, guiding questionnaires, focus group discussion guide, or observation checklist.

Explore how a questionnaire uses open ended and closed questions with yes or no options, alternatives, and recant scales to guide data collection in surveys for monitoring and evaluation.

Design questionnaire for monitoring and evaluation by reviewing log frame indicators, covering qualitative and quantitative indicators across outcomes, outputs, impacts; group questions into sections, pretest, deploy with odk or kobo.

Design effective questionnaires by keeping questions simple and short, avoiding wrong, ambiguous, and leading questions, to reliably extract high-quality monitoring and evaluation data.

Develop practical questionnaires anchored to the log frame, designing baseline and post-distribution monitoring tools to improve education access for vulnerable orphans and track cash use, attendance, and well-being.

Outline a focus group discussion guide based on the Harvard guide, using open-ended questions to elicit qualitative data, with consent, anonymity, group rules, ownership, indicators, and recording methods.

Design a practical focus group discussion guide using the logical framework to measure indicators and impact. Enforce confidentiality, set ground rules, and prepare questions to assess project performance.

Master key informant interviews with community leaders or experts to gain insights, structure introductions and probing questions, and use face to face or telephone methods with notes for needs assessments.

Develop a practical key informant interview guide and rapid questionnaire to assess multi-sector needs during COVID-19, integrating quantitative survey data with qualitative insights.

An observation checklist serves as a harmony tool, guiding trained observers to list and record what they see, using yes/no, blank entries, or notes within a guided protocol.

Advanced monitoring and evaluation presents a sample observation checklist for water, sanitation, and hygiene projects. Observers record site elements, such as water points and latrines, with yes/no options and notes.

Ensure beneficiaries sign in sheets and consent for name and photo use in reports; collect essential details like date, venue, location, participants' demographics, training type, and status.

Design a training sign-in sheet capturing country, venue, date, participant name, designation, phone, gender, age, and signature, with GPS coordinates and a consent column for photo and name use.

Learn how indicators can be misinterpreted, too numerous or few, data reporting errors, and incompatibility with standards, which hinder informing decisions and consistent reporting in monitoring and evaluation.

Sign up for Kobo Toolbox by selecting between humanitarian organization and researcher plans, then complete the form with a unique username, email, and password, and activate via email link.

log into Kobo Toolbox via the browser, choose your role (humanitarian organization or researcher), enter username and password, then access account settings or log out.

Take a quick tour of Kobo Toolbox interface, explore the project and library modules, create and deploy questionnaires, archive inactive projects, search efficiently, and access help and user settings.

Create a new project in Kobo Toolbox by uploading an XLS form, building from scratch, or using a template, then add description, sector, and country before deploying.

Learn to author xls forms with Excel for ODC data collection by building a workbook with survey, choices, and settings sheets to define questions and options.

Learn to structure an XLSForm with minimum columns across the survey, choices, and settings sheets, using type, name, and label (lowercase with underscores) and form_title and form_id as unique identifiers.

Explore the XLSForm question types in Kobo toolbox, from integer and decimal numbers to text, date, time, image, audio, video, GPS, and calculations, including single and multiple selections.

Learn how to author a first simple XLSForm with a text name field and a select one gender question, including variable names, labels, and a form id for COBOL toolbox.

Deploy an XLSForm in Kobo Toolbox by creating a project, uploading the form from your machine, deploying from draft, and previewing before data collection, with options to download and clone.

Download and install the Kobo Toolbox Android app on a mobile device, navigate its forms and settings tabs, and prepare to connect the ODC hub to the online server.

Open the android Kobo collect app, access server settings, and configure the URL for Kobo Toolbox or humanitarian response, then enter your username and password to access forms.

Test the new xls form with the Cobo Toolbox mobile app, re-approve it on online server, upload the form, deploy the project, and send finalized data from the mobile device.

Delete saved and blank forms in the Kobo collect mobile app from the final tab, using select all and the delete button; refresh to sync with the online server.

Open the submission on the Kobo Toolbox online server, choose data formats (xls, csv), export the file with headers, then download and open in Excel for analysis.

Learn to name variables in XLSForm with unique, letter- or underscore-starting names, avoiding starting with numbers. Capture metadata such as start and end times, device ID, and audit data.

Learn how the note question type in xls form ordering uses metadata to display on-screen instructions with a name and label, and does not collect an answer.

This lecture explains configuring a date question in xls form to capture day, month, and year, and using appearance options to display month or year only on mobile.

Suppress the calendar in the date question by setting the appearance to no calendar, enabling a birth date picker with date, month, and year selection and easy navigation on mobile.

Learn how to use time question types to record the exact time a respondent reports to work, using a mobile time picker to select hours and minutes.

Use the date-time question type to capture date and time in one step on the Kobo Correct mobile app, with separate date and time selections and a combined option.

Learn how to configure text questions in Kobo survey forms, including setting the type to text, naming the respondent, and using appearance to restrict input to numbers for phone fields.

Learn how to create integer questions that restrict input to whole numbers, using an integer type and a numeric mobile keyboard (for example, number of household members).

Explore how a decimal question type captures fractions like 0.5 and 1.7 for the cost of water per liter in USD, and why decimals suit currency data over integers.

Explore calculate type questions by multiplying water cost per liter by daily liters. Use Dora curly bracket references in Excel form and practice basic operators to compute daily water expenditure.

Learn to design select-one questions from a list of options, enforce a single response, reuse choices across questions, and label with groups like gender in COBOL Android Hub.

Master the select_multiple question type to let respondents choose multiple answers. Capture multiple economic activities shaping livelihoods and implement the format in xls forms and Android Kobo.

The lecture explains how audio, video, and image questions function in an xls form, including recording audio, recording video, and taking or attaching images using cobalt app on Android.

Learn how to control image pixels at capture time by setting a maximum pixel size via parameters, ensuring uploads meet external system requirements with the ODC Android app.

Use the image question type with signature or draw appearances to capture signatures or sketches, up to 1080 pixels wide, with height auto-adjusted, stored as images in Kobo Toolbox.

Rank type questions let respondents order items by preference; using colors red, green, and yellow, you drag to top your favorite and confirm in the Kobo Android app.

Define a range question from 0 to 17 with a one-step interval in xlsx form, detailing start, end, and step. Show how the Kobo Connect app presents these options.

Explore a range with a five-star rating appearance that collects responses for child school performance. Set the range from 1 to 5 with step 1 to enable star scoring.

Explore the question type range by switching between picker and vertical appearances, showing how the same range shifts from horizontal to vertical and uses a picker for rating (1–5).

Explore how hidden questions in surveys capture start and end times, date, and gps coordinates, plus background audio for transcription, enhancing data quality in advanced monitoring and evaluation.

Geopoint records GPS location—latitude, longitude, and altitude—with about ten meter accuracy, and you can save points before or after the survey in the XLS form.

Learn how trigger and acknowledge questions confirm information with a checkbox to proceed, recording confirmation as text, and are used to ensure conditions are met before continuing in data collection.

Improve data quality by making survey questions required in xls forms, ensuring respondents cannot skip essential items and must answer key questions before moving forward.

Identify how to select representative samples from a population for monitoring and evaluation, using simple random sampling and purposive sampling to inform need assessments and post distribution monitoring.

Determine sample size for representative random sampling and randomly draw samples with equal probability to generalize findings, guided by confidence intervals and levels (for example, 95%), using simple calculators.

Purposive sampling uses the researcher’s judgment to select informants or cases, such as community leaders for key informant interviews or outliers, to document change and analyze successes or failures.

Explore research ethics and informed consent in monitoring and evaluation, as you implement field tools, ensure voluntary participation, and obtain signed consent for surveys, focus groups, and interviews.

Researchers introduce themselves, the organization, and the project to obtain informed consent from beneficiaries or respondents for surveys, focus groups, or interviews, outlining duration, procedures, selection, withdrawal, voluntariness, and confidentiality.

Identify and prevent research misconduct in monitoring and evaluation by recognizing fabrication, falsification, and plagiarism, and ensure accurate, properly referenced data to inform sound decisions.

Identify four factors driving poor data quality, respondents' motivation and recall, enumerator mistakes and faking interviews, supervisor quality control lapses, and poorly designed mobile forms with incorrect skip patterns.

Monitor data quality daily during collection to identify and rectify issues. Use back checks, high frequency checks, response quality checks, and GPS verification to flag anomalies and protect data integrity.

Explore the data analysis process, including means, medians, modes, and standard deviation, and visualize results with charts and tables. Interpret findings to inform timely decisions in quantitative and qualitative analyses.

Analyze quantitative data using mean, frequency, percentage range, standard deviation, and cross tabulation; visualize with bar charts, pie charts, and scatter plots for monitoring and evaluation presentations to stakeholders.

Explore how mean, standard deviation, frequency, percentage, and range measure and interpret quantitative data in monitoring and evaluation, with household expenditure examples and baseline comparisons.

Explore how bar charts visualize percentage-based responses across subgroups or time, including best practices, alternatives for many items, and interpreting baseline versus current status in monitoring and evaluation.

Explains how stacked bar charts visualize variation across subgroups by showing parts of a whole, with totals summing to 100 and examples from debt questions in baseline surveys.

Explore how pie charts visualize subgroup composition in monitoring and evaluation, with up to five categories totaling 100%, using percentages inside and outside slices.

Learn how to use line graphs to track changes over time, plotting data points against months, years, or quarters, and compare up to five trends for clear visualization.

Explore scatter plots as a data visualization tool that reveals relationships between two continuous variables, identifies patterns and outliers, and uses regression lines to predict trends in health projects.

Learn cross tabulation by placing a variable in rows and another in columns, with cells showing counts or percentages; illustrated by disability status by gender and meals by household category.

Explore qualitative data analysis using focus group discussions and key informant interviews to identify themes through content analysis, and support themes with participant quotations while protecting anonymity.

Promote accountability by using power responsibly and establishing stakeholder channels for issues and feedback, enabling transparent responses, reducing harm, and strengthening stakeholder relationships and project support.

Enhance accountability by sharing project information with beneficiaries, including start and end dates, objectives, activities, budget, donors, and community contribution via meetings, notice boards, groups, bulk messaging, and social media.

Enable beneficiary feedback through toll-free reporting, a field helpdesk, and suggestion boxes. Include direct interviews, consultative meetings, and monitoring and evaluation questions, plus digital options like email and WhatsApp.

Explain the varieties of beneficiary feedback, including information requests, assistance requests, satisfaction reports, safety concerns, staff behavior complaints, and program compliments, all conveyed through available channels.

Receive complaints and feedback through multiple channels, acknowledge receipt, and register them in a database; process and resolve issues, escalate sensitive cases, and disseminate donor reports while protecting beneficiaries' confidentiality.

Explore a stage-based complaints and feedback database that records mode, provider, project, description, resolution actions, status, and satisfaction, with an Excel tool for accountability.

Pay attention to what you hear and see from beneficiaries and non-beneficiaries, documenting formal and informal feedback. Respond promptly, use feedback to improve projects, and maintain clear communication throughout.