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Neuman, Delia – Educational Technology, Research and Development, 1989
Describes a naturalistic paradigm and discusses the value of using a naturalistic, or qualitative, approach to study the effectiveness of computer-based instruction (CBI) and to design effective courseware. Topics discussed include data collection; data analysis; and findings of naturalistic studies of CBI effectiveness. (53 references) (LRW)
Descriptors: Computer Assisted Instruction, Courseware, Data Analysis, Instructional Effectiveness
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Scott, M. M.; Hatfield, James G. – Journal of Educational Measurement, 1985
Differences in agreement between observers and analysts of naturalistic narrative data cause problems in observation research. This paper discusses the advantages and disadvantages of several possible solutions. (Author/GDC)
Descriptors: Behavioral Science Research, Data Analysis, Data Collection, Interrater Reliability
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Biklen, Sari Knapp; Bogdan, Robert – New Directions for Program Evaluation, 1986
If one undertakes naturalistic evaluation without formal training, there are some important considerations and sources of information to keep in mind. Labor intensive qualitative approaches are discussed in terms of field relations, data collection and analysis, and writing. (Author/LMO)
Descriptors: Data Analysis, Data Collection, Ethnography, Field Studies
Johnson, Stephen M.; Bolstad, Orin D. – 1972
An attempt at defining and describing those factors which most often jeopardize the validity of naturalistic behavioral data is presented. A number of investigations from many laboratories which demonstrate these methodological problems are reviewed. Next, suggestions, implementations, and testing of effectiveness of various solutions to these…
Descriptors: Behavioral Science Research, Children, Classification, Data Analysis
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Westbrook, Lynn – Library & Information Science Research, 1994
Examines the basic tenets of qualitative, or naturalistic, research methods in terms of their grounding in social science and their value to library and information science research. Topics discussed include the research problems; data collection, including interviews; data analysis, including content analysis; theory development; and ensuring…
Descriptors: Content Analysis, Data Analysis, Integrity, Interviews
Hatch, J. Amos – 1985
This paper describes data gathering and analytic procedures, and then presents examples regarding how each fits into the naturalistic research model. From the interactionist perspective, called symbolic interactionism, meaning is of central importance. Naturalistic inquiry is a way of doing social science research which provides the methodological…
Descriptors: Data Analysis, Educational Research, Elementary Secondary Education, Ethnography
Lundsteen, Sara W. – 1986
Ethnographic research (1) observes human behavior in its natural setting over a substantial period of time, (2) claims that classes of events are better understood through intensive examination of carefully selected particular cases, (3) incorporates as many of the complexities and variables into a setting as possible, and (4) is usually comprised…
Descriptors: Behavior Patterns, Creative Thinking, Data Analysis, Data Collection
Pearsol, James A. – 1985
This paper describes the practical steps employed in controlling interview data generated from a research project investigating teachers' perspectives on the worth of a sex equity educational demonstration project. These perspectives were then considered as value frameworks that might be used to formulate and interpret a naturalistic-responsive…
Descriptors: Cluster Grouping, Data Analysis, Data Collection, Demonstration Programs
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Hernon, Peter; McClure, Charles R. – Library and Information Science Research, 1987
Discusses issues relating to the reliability, validity, utility, and information value of unobtrusive testing of library reference services; provides suggestions for practical applications of these criteria; applies study findings to library decision making and planning; and identifies topics for further methodological refinement. (Author/CLB)
Descriptors: Data Analysis, Data Collection, Data Interpretation, Experimenter Characteristics