2.4 Online data collection Flashcards

1
Q

Advantages of traditional data collection

A
  • Recruitment criteria
  • careful responding
  • Ppts complete the study once
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2
Q

What are the challenges of traditional data collection?

A
  • Time (recruiting, no shows, ppts money, lateness)
  • Costs (printing costs, travel/postage cost)
  • Data management (data entry, scoring/response scale)
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3
Q

Name 3 broad challenges of online data collection?

A
  • stimulus presentation
  • Multiple submissions
  • Data quality concerns
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4
Q

What can be the issues with stimulus presentation?

A
  • is the presentation the same on all devices (e.g. screen resolution, timing, viewing distance)
  • Does the ppts see/hear what the researcher intended?
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4
Q

Name 7 data quality concerns

A
  • Experimenter absent
  • Less committed
  • Divided attention
  • Higher drop-out rates (10-20%)
  • Missing data (tech glitches, inattention)
  • Outliers
  • Response patterns in questionnaires
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5
Q

Advantages of online data collection for ppts

A
  • Anonymity (more likely to answer truthfully)
  • Convenience
  • Provide information at their own pace
  • Increased sense of control
  • Incentives (cash, vouchers, prize draws, ppts credits)
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6
Q

How do we address issues of stimulus presentation?

A
  • depends on RQ
  • Practice trails
  • Screen calibration
  • Viewing distance
  • timing
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7
Q

What is screen calibration?

A

The process of adjusting a device’s color settings to ensure the colors displayed on the screen accurately represent the intended colors in an image

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8
Q

How do we address the issue of divided attention?

A
  • Recruitment services (approval rates, previous number of submissions)
  • attention checks
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9
Q

How do we address high drop-out rates?

A
  • Predetermine sample size
  • Encourage ppts (incentives)
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10
Q

How do we address missing values?

A
  • depends on the research Qu
  • If has variable that you need then keep
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11
Q

How do we address the issues of Outliers?

A
  • researchers decides what is an outlier, before you look at the data
  • Justification backed up by evidence
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