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- Creators: Chassin, Laurie
Description
The discussion board is a facet of online education that continues to confound students, educators, and researchers alike. Currently, the majority of research insists that instructors should structure and control online discussions as well as evaluate such discussions. However, the existing literature has yet to compare the various strategies that instructors have identified and employed to facilitate discussion board participation. How should instructors communicate their expectations online? Should instructors create detailed instructions that outline and model exactly how students should participate, or should generalized instructions be communicated? An experiment was conducted in an online course for undergraduate students at Arizona State University. Three variations of instructional conditions were developed for use in the experiment: (1) detailed, (2) general, and (3) limited. The results of the experiment indentified a pedagogically valuable finding that should positively influence the design of future online courses that utilize discussion boards.
ContributorsButler, Nicholas Dale (Author) / Waldron, Vincent (Thesis advisor) / Kassing, Jeffrey (Committee member) / Wise, John (Committee member) / Arizona State University (Publisher)
Created2012
Description
Time metric is an important consideration for all longitudinal models because it can influence the interpretation of estimates, parameter estimate accuracy, and model convergence in longitudinal models with latent variables. Currently, the literature on latent difference score (LDS) models does not discuss the importance of time metric. Furthermore, there is little research using simulations to investigate LDS models. This study examined the influence of time metric on model estimation, interpretation, parameter estimate accuracy, and convergence in LDS models using empirical simulations. Results indicated that for a time structure with a true time metric where participants had different starting points and unequally spaced intervals, LDS models fit with a restructured and less informative time metric resulted in biased parameter estimates. However, models examined using the true time metric were less likely to converge than models using the restructured time metric, likely due to missing data. Where participants had different starting points but equally spaced intervals, LDS models fit with a restructured time metric resulted in biased estimates of intercept means, but all other parameter estimates were unbiased, and models examined using the true time metric had less convergence than the restructured time metric as well due to missing data. The findings of this study support prior research on time metric in longitudinal models, and further research should examine these findings under alternative conditions. The importance of these findings for substantive researchers is discussed.
ContributorsO'Rourke, Holly P (Author) / Grimm, Kevin J. (Thesis advisor) / Mackinnon, David P (Thesis advisor) / Chassin, Laurie (Committee member) / Aiken, Leona S. (Committee member) / Arizona State University (Publisher)
Created2016