Remote Work Impact on Productivity

• A university team is studying the impact of remote work on productivity.
• They are gathering quantitative and qualitative data from employees across industries.
• The aim is to understand employees' experiences and challenges with remote work.

The team:

• Amira (Lead Inquirer) designs the inquiry framework and oversees data collection.
• Ben (Survey Coordinator) creates and distributes online questionnaires.
• Chloe (Interview Facilitator) conducts in-depth interviews with selected participants.
• Derek (Data Analyst) processes and interprets findings.

The inquiry seeks to answer:

• How remote work influences employee productivity.
• What challenges remote workers encounter.
• How employees perceive remote work compared to office work.

Choosing a Data Collection Method:

Surveys:

• Quick, reaches large groups and gathers numerical data
• May lack depth and detailed insights

Interviews:

• Allows in-depth responses and uncovers detailed experiences
• Time-consuming, fewer participants

Observation:

• Captures real-time work habits and environment
• Requires access to workspaces and raises privacy concerns

Discussion points for choosing a data collection method:

• What data collection method should they prioritize and why?
• How could they combine multiple methods for richer inquiry insights?

Designing a Questionnaire & Interview Guide:

• Ben is preparing an online survey using Google Forms.
• Chloe is structuring an interview guide.

Survey Sample Questions:

• On a scale of 1-5, how productive do you feel when working remotely? (Likert Scale)
• What challenges do you face while working remotely? (Multiple Choice)
• Do you prefer remote work over office work? (Yes/No)
• Why do you feel this way about remote work? (Open-ended)

Interview Sample Questions:

• Can you describe your typical workday when working remotely?
• How do distractions at home compare to distractions in an office?
• What strategies help you stay productive while working remotely?

Discussion points for designing questionnaires and interviews:

• How do survey and interview questions differ in collecting inquiry data?
• Why is it important to use a mix of question types?

Analysing the Inquiry Data:

• Derek has received 100 survey responses and conducted 5 in-depth interviews.
• He now needs to analyse the data.

Quantitative Analysis (Survey Data):

• Step 1: Count responses for each question.
• Step 2: Calculate percentages (e.g., 70% of employees feel more productive remotely).
• Step 3: Create visual representations (bar charts, pie charts).

Qualitative Analysis (Interview Data):

• Step 1: Read all responses and highlight common themes.
• Step 2: Group similar responses into categories (e.g., "Distractions," "Time Management").
• Step 3: Use direct quotes to support findings.

Discussion points for analysing inquiry data:

• Why is it important to analyse both quantitative and qualitative data in an inquiry?
• How should Derek present his findings for clarity?

Key Takeaways:

• Different inquiry methods offer unique strengths (combining them leads to stronger insights).
• Effective questionnaires balance closed and open-ended questions.
• Data analysis involves organizing, summarizing, and visualizing findings.
• The choice of methods should align with the inquiry question and available resources.
• By working through these steps, the inquiry team ensures a structured, reliable approach to data collection and analysis.