Asking learners to teach: An initial exploration of development of student contributed content for a qualitative data analysis class
Location
1054
Format Type
Event
Format Type
Panel
Start Date
January 2019
End Date
January 2019
Abstract
Qualitative researchers and students of qualitative methods have an increasing number of program choices for data analysis software (QDAS). Although there are similarities among these, our experience suggests each new program has enough unique attributes to result in a “learning curve.” This curve can create frustration and a feeling of loss of control during data processing and analysis, and increase the stressors already associated with student research, including pressure over grades and time frames. Prior research suggests that relatable role models can be effective and credible sources of encouragement for individuals learning new skills.
The purpose of this panel is to describe incorporation of student-contributed content in a qualitative data analysis class. Students in this hybrid course were assigned to create periodic screencast recordings while working with a QDAS program to capture their efforts and responses as they progressed over time from novice to more comfortable users. The instructor’s aim is to incorporate this content into future versions of the online course content, so subsequent students might view role model who demonstrate a range of responses from frustration to confidence. Panel presenters include the instructor and students, represented both in person and via contributed content created for this presentation.
Keywords
Qualitative data analysis; qualitative research instruction
Asking learners to teach: An initial exploration of development of student contributed content for a qualitative data analysis class
1054
Qualitative researchers and students of qualitative methods have an increasing number of program choices for data analysis software (QDAS). Although there are similarities among these, our experience suggests each new program has enough unique attributes to result in a “learning curve.” This curve can create frustration and a feeling of loss of control during data processing and analysis, and increase the stressors already associated with student research, including pressure over grades and time frames. Prior research suggests that relatable role models can be effective and credible sources of encouragement for individuals learning new skills.
The purpose of this panel is to describe incorporation of student-contributed content in a qualitative data analysis class. Students in this hybrid course were assigned to create periodic screencast recordings while working with a QDAS program to capture their efforts and responses as they progressed over time from novice to more comfortable users. The instructor’s aim is to incorporate this content into future versions of the online course content, so subsequent students might view role model who demonstrate a range of responses from frustration to confidence. Panel presenters include the instructor and students, represented both in person and via contributed content created for this presentation.
Comments
Breakout Session D