ACSPRI Conferences, RC33 Eighth International Conference on Social Science Methodology

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Effectiveness of Technological Tools for Teaching QRM Online

Barbara Kawulich

Building: Law Building
Room: Breakout 8 - Law Building, Room 100
Date: 2012-07-12 01:30 PM – 03:00 PM
Last modified: 2011-12-15


Technology increasingly plays a part in how we teach qualitative research methods (QRM). As students, particularly working professionals, seek more convenient venues through which to access education, they frequently gravitate toward online learning opportunities. This serves as a challenge to the instructors who teach qualitative research. Online teaching of theoretical concepts can be challenging, and the quality of the learning experience in traditional, many times, relies upon student interaction and discussion. How can we effectively teach, such topics as theoretical frameworks, ethics, data collection and analysis, in an online environment? How do we make such instruction meaningful? How do we hold students’ attention and make online learning a quality experience?
Using a variety of technological tools and approaches to presenting course content, this instructor taught a doctoral level qualitative course online in Spring, 2012. Podcasts (both audio and video), avatar videos, screen captures, glogs, and interactive synchronous discussions were used to supplement the typical discussion boards, chat rooms for group work, e-textual content, and PowerPoint with voice over used in online environments. A variety of novel, sometimes free or inexpensive, options are available to assist the online instructor to provide quality instruction. These will be discussed within the framework of a collaborative learning context.
The primary questions guiding this study were: What are the students’ experiences in learning QRM in an online environment during this course? How effective did they find the use of technology to be in enhancing their learning experience? How can student feedback be used to inform (and improve) my practice? Qualitative data from interviews, focus groups, student reflections and discussion posts constitute the basis for thematic data analysis. Results of the data analysis and interpretation will be used to improve the course delivery in future semesters.