DGB 3: Crowdsourcing, Surveys and Digital Projects

← Digital Literacy – Year 3

Digital projects can be created by many contributors. Crowdsourcing and surveys can collect ideas, observations or opinions at scale, but good results require clear questions, roles, data protection, quality checks and a transparent method for combining contributions.

Curriculum reference

Area	Classification
Competence area	Communication
Perspectives	G, I
Focus	Collaboration on digital projects using crowdsourcing, surveys and multiple contributors
Competence	Plan digital projects with multiple contributors, collect and combine contributions in a structured way and use crowdsourcing and surveys responsibly.

Learning objectives

Students can:

explain collaboration with several contributors;
describe crowdsourcing as a strategy for collecting many contributions;
plan a survey for a clear purpose;
distinguish open and closed question types;
collect, sort and combine contributions systematically;
assign roles and responsibilities in a group project;
recognise quality, bias and participation problems;
apply data-minimisation and fairness principles;
document decisions and revisions in collaborative work;
reflect on group process and final product separately.

Learning content

Digital projects as shared products

A shared digital product can be a presentation, map, data set, guide, media collection or website. Collaboration works best when the goal, structure and responsibilities are agreed before contributions are gathered.

Organising multiple contributors

Roles may include coordination, research, editing, design, technical management and quality checking. Version history and shared naming rules help prevent conflicting copies.

Crowdsourcing as a strategy

Crowdsourcing invites contributions from a larger group. It can increase variety and coverage, but participation is often uneven and contributions may vary in quality.

Surveys as a collaborative method

A survey should begin with a clear question. Questions should be understandable, neutral and limited to necessary information. Answer options should fit the intended analysis.

Collecting, organising and combining contributions

Raw contributions need categories, quality checks and a transparent method for selecting or summarising them. Contributions should not be altered in misleading ways.

Opportunities of collaborative digital work

Many people can contribute different knowledge, experiences and creative ideas. Digital tools can make distributed work visible and allow feedback throughout the process.

Challenges and risks

Duplicate work, unclear responsibility, unreliable contributions, group pressure, unfair workload and privacy problems can reduce quality. A project plan should address these issues.

Privacy, fairness and responsibility

Collect only data needed for the project, explain the purpose, avoid unnecessary personal information and give contributors appropriate recognition.

Examples of community projects

Collaborative mapping, school surveys, citizen-science observations and shared knowledge collections show how many small contributions can form a useful whole.

Classroom activities

Develop project ideas together

Turn a broad issue into a shared digital project with a clear product and audience.

Expected outcome: A project brief.

Assign roles and tasks

Create a role plan with responsibilities, deadlines and handover points.

Expected outcome: A team plan.

Prepare a crowdsourcing activity

Define what contributions are requested and how they will be checked.

Expected outcome: A contribution guide.

Design a survey

Write a short survey with neutral wording and only necessary data.

Expected outcome: A privacy-conscious questionnaire.

Collect contributions visibly

Use an approved collaborative tool to gather contributions and track progress.

Expected outcome: An organised contribution collection.

Sort and evaluate results

Create categories or a spreadsheet and explain how contributions are summarised.

Expected outcome: A transparent evaluation.

Create a shared digital artefact

Combine contributions into one coherent product with a consistent structure.

Expected outcome: A collaborative artefact.

Consider privacy and fairness

Review the project for unnecessary data, unequal workload and unclear attribution.

Expected outcome: A fairness and privacy check.

Reflect on collaboration

Evaluate what worked in the process and what should change next time.

Expected outcome: A process review.

Reflect on evidence quality

Explain why many responses do not automatically mean a representative survey.

Expected outcome: A methodological reflection.

Self-check

I can explain crowdsourcing and surveys.
I can plan roles in a collaborative project.
I can write clear and neutral survey questions.
I can organise and combine contributions transparently.
I consider privacy, fairness and attribution.
I can distinguish the quality of the product from the quality of the collaboration process.