Browsing by Author "Kosiak, Jennifer Jean"

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Using asynchronous discussions to facilitate collaborative problem solving in college algebra
(Montana State University - Bozeman, College of Letters & Science, 2004) Kosiak, Jennifer Jean; Chairperson, Graduate Committee: Linda M. Simonsen
This research study was conducted to investigate the nature and quality of online mathematical communication that occurred during collaborative problem solving and its effect on mathematical achievement in college algebra. Two intact sections of college algebra were randomly assigned to either a treatment group (online group work) or control group (individual seatwork). Both sections of college algebra met face-to-face and were taught by the same instructor. Students in the treatment group (n = 26) were placed into six collaborative groups. Four week-long online tasks designed according to the Treisman Workshop Model were assigned throughout the semester. These tasks were to be addressed collaboratively, with each student required to post three messages to their groupαs online folder. Students in the control group (n = 30) were assigned the same four tasks, but were required to work on these tasks individually. Two content analysis techniques were utilized to answer the primary research question. The online transcripts of the treatment group were coded using the framework developed by Stacey and Gooding (1998) which examined the patterns of interactions. Results from this analysis revealed that the majority of the messages sent were coded as thinking aloud followed by responding, explaining with evidence, and questioning. Each message was also ranked according to Gunawardena, Lowe, and Andersonαs (1997) Interaction Analysis Model. One in five messages was ranked as a high level message exhibiting evidence of the co-construction of knowledge. As indicated by the groupαs average high and highest phase level reached, it was found that in 19 of the 24 problem solving episodes (six groups by four tasks) clear evidence of the co-construction of mathematical knowledge was shown. Analysis of covariance (ANCOVA) was used to analyze mathematical achievement differences between the treatment and control groups. ANCOVA was performed on the raw scores of the final examination and researcher-designed problem solving examination using the pretest scores as the covariate. The treatment group performed as well or better on both measures of achievement. After controlling for initial differences in mathematical ability, the treatment group performed significantly better than the control group on the final examination.