Data Collection & Analysis Challenges

• 25 questions encourage students to critically think through data collection and analysis challenges.
• Questions include a mix of open-ended and multiple-choice to cater to different engagement levels.

Understanding Data Collection Methods

• Questionnaires and interviews have key differences.
• One method is better than the other to understand something like why people shop online.
• Collecting data with Questionnaires is more efficient when there is only one week to work with.
• Interviews collect qualitative data.
• Ensuring questionnaire results aren't biased is important.

Designing Questionnaire & Interview Questions

• Some questions are more effective questionnaire questions than others.
• Improving questions makes them more useful for data collection.
• Leading questions in interviews should be avoided.
• A type of question allows respondents to express their thoughts in detail.
• Some interview questions are better than others depending on the research question.

Sampling & Selecting Participants

• Having a diverse sample when collecting data is important.
• Some sampling methods are more efficient for a study on student shopping habits.
• Purposive sampling is more efficient when selecting students who shop online frequently.
• Choosing only classmates for a study on online shopping will affect the results.
• Certain people should be in the sample group when studying the effects of online shopping on small businesses.
• When you only have the time to survey 20 people, there are factors to consider when selecting participants.

Analysing Questionnaire Data (Quantitative)

• There is a way to present the information if 75% of respondents say they shop online.
• Calculating percentages in questionnaire analysis is important.
• Using a paragraph, summarize questionnaire results with 30 respondents.
• Certain statements are a good way to present questionnaire findings.
• Raw numbers without percentages can affect the results.

Analysing Interview Data (Qualitative)

• Summarizing findings is important when participants mention a key factor.

• Looking for patterns when analysing interview responses is important.

• The most efficient way to present qualitative data is grouping common answers into themes (e.g., convenience, price, variety)

• Finding the common themes in interview data of price, variety, and convenience; reporting these findings is important.

• There are some challenges of analysing qualitative data; and overcoming them is important.

• Assign students a set of questions to discuss possible answers.

• Students are encouraged to justify their answers using real-life reasoning.

• Ask students to write responses to five selected questions that relate to their own research projects.

• Students exchange answers and give constructive feedback.

• These 25 questions help students critically engage with data collection and analysis challenges, while making the learning practical and interactive.