Using Quantitative Data To Evaluate Tutoring, SI & Study Groups

Key Takeaway  What statistics are commonly used in learning assistance programs in order to demonstrate program effectiveness?  What data is needed in order to use a variety of stats for evaluation?  The webinar focuses on answering these key questions while also promoting participants' confidence in quantitative evaluations for their programs. Challenge Some evaluation challenges involve the very core of an evaluation: getting the student demographic and performance data.  Many learning assistance programs do not automatically have access to the information they need in order to demonstrate that their tutoring, SI, and study groups are effectively helping students stay in their classes and earn better grades.  We'll discuss how to access that data and also talk about options for using that information in a variety of ways -- including how to know what to ask for when you need someone else to run the statistical computations for you. Overview Evaluating tutoring programs, Supplemental Instruction (SI), student study groups, and other forms of academic assistance related to courses are not new practices. What may be newer, however, is some increased attention on the sophistication of those evaluation formats. Qualitative evaluation such as satisfaction surveys and narratives about students’ successes and comparative evaluation (e.g., accreditations and certifications) are still appropriate and relevant measures of successful academic assistance for students. However, many programs find themselves being asked for something more quantitative and more sophisticated than numerical summaries of clients’ grades and service usage. “All of our developmental math students have low ACTs. How can I show their good progress?”“What can I do to satisfy funding requirements for statistical data?”“I am confident that the students we tutor are benefitting as they get more help, but can I prove it?”“What measures can I use to show student improvement on such a limited A-F grade scale?”In this webinar, we will explicitly address a program’s access to, the creation of, and protection of student data. We will also discuss the basic descriptive kinds of information most programs generate. The focus will then turn to additional statistics that can clarify and confirm program impacts on student academic performance and persistence. Note: For captioning, please contact us 7 days in advance. 303.955.0415 or support@ieinfo.org Objectives Understand how to create, access and protect student data Review basic descriptive statistics related to program clients Learn how to use most common t-tests appropriately Learn how to compute ANOVA when necessary Determine appropriate methods for correlation and partial correlation Find computational assistance for statistical calculations Who Should Attend Any educator interested in learning how to assess academic support programs