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Late Registration’s Influence on Academic Outcomes

Late Registration’s Influence on Academic Outcomes. Evan Picton, Research Analyst Wenatchee Valley College. Do students who register early for their courses do better than students who register later?

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Late Registration’s Influence on Academic Outcomes

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  1. Late Registration’s Influence on Academic Outcomes Evan Picton, Research Analyst Wenatchee Valley College

  2. Do students who register early for their courses do better than students who register later? • What variables should be controlled for in order to isolate the unique variance associated with registration time? • What analysis should be used? • What students should be included in this analysis? • What outcome should be used? • How should early versus late registration be determined? Research Question

  3. Population: Credit Students (No Basic Skills, ESL or Continuing Education Students) • Primary Statistical Analysis: Multiple Regression • Outcome: Decimal Grade earned (excludes pass/fail classes) & Quarter GPA • Goal: Develop two separate models to predict these outcomes using time of registration • Nature of Research: Exploratory, not confirmation of an existing model • Control Variables identified using simple correlational analysis and iterative regression modeling Research Design

  4. Modeled as a Continuous Variable (days) not a Dichotomous “On Time/Late” variable. • Collapsing a continuous variable, like time, into categories is problematic. • Loss of information about individual differences, loss of effect size and power, the occurrence of spurious main effects or interactions, risk of overlooking non-linear effects (attached PDF - MacCallumet al, 2002) Primary Predictor: Time of Registration

  5. -Utilized daily enrollment snapshots pulled from a database that was constantly being updated with the latest enrollment information. These snapshots were pulled during the interval of time between the first possible date of registration to the registration deadline of spring quarter. Determining Date of Registration

  6. Population: Credit Students Outcome Variable: Decimal Grade Earned

  7. Population: Credit Students Outcome Variable: Quarter GPA

  8. Control Variables

  9. Descriptive Statistics for Sample

  10. -The process for identifying significant control variables involved first separately looking at the zero order level correlations that all the controls had with the outcome variable of decimal grade earned. The variables with no significant relationship at that level were removed. The next step involved putting the remaining predictors into a preliminary regression model predicting decimal grade earned. The registration time variable was included in this early model. The controls that accounted for significant outcome variance at this step were retained and are listed in the table below. Results: Significant Predictors(for decimal grade model)

  11. -The first order effects model accounted for a very modest amount of variance in Decimal Grade Earned. Results: Decimal Grade Prediction Model

  12. -Decimal grade earned had a gradual relationship with registration time Results: Decimal Grade Model Coefficients

  13. -The relationship between Days Registered and the outcome of Decimal Grade earned was, once control variables were accounted for, gradual. The relationship was also linear. Adding a quadratic term to the model (Days*Days) did not improve the predictive power of the model in a meaningful way. The same result was found for the cubic term.Furthermore, the Days variable did not interact with any of the other predictors used in this model. Primary Predictor of Interest: Days Registered Before Deadline(decimal grade model)

  14. -The first order effects model accounted for a very modest amount of variance in Quarter GPA. Results: Quarter GPA Prediction Model

  15. -Quarter GPA had a gradual relationship with registration time Results: Quarter GPA Model Coefficients

  16. -Different results than what requestors expected. Relatively low amount of variance accounted for. -First Time Spring Students vs. First Time Fall Students -Students seem to need to register very early for it to have an impact - within the first week of registration. Cause and effect unclear -Did not extensively explore interactions between the other predictors. (Math*RS) -Consistent with your college? -This research will be repeated for Fall quarter 2012. Students have a long interval of time to register for Fall Quarter. Difficult to predict how this might impact the relationship between days registered before deadline and academic outcomes. Discussion

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