SAS Skill Learning and Certification Preparation in a Graduate School Setting Christine Bonney Michael Keith Michael Keith University of Pennsylvania Graduate School of Education

Introduction  Brief Background  2005: Experimental course reclassified as EDUC625: Data Analysis and Processing and became an official graduate course on UPenn’s academic course roster  Fall 2011: EDUC625 Professor introduced students to the SAS ® Base Programming Certification exam  Spring 2012: Virtual study group was created to prepare interested students to take certification exam

Introduction (cont’d)  Brief Background (continued)  May 2012: Only two of the seven individuals passed the exam.  Summer 2012: EDUC625 course curriculum revised by professor and two teaching assistants  Semester-long course created with goal of teaching graduate students SAS programming skills and preparing them to take the SAS ® Base Programming for SAS ® 9 exam

Course Design, Materials, and Activities  Overview and Logistics  Students will learn to use SAS ® software to effectively interpret data and evaluate and apply contemporary statistical methods  Prerequisite for course is successful completion of a graduate-level course in statistics (or an equivalent)  Class meets in person once a week for two hours in a computer lab and for one hour online

Course Design, Materials, and Activities (cont’d)  Lectures  First hour of each two-hour class meeting used for lecture  Covers information from assigned readings  Content derived from material from e-learning courses SAS ® Programming 1: Essentials and SAS ® Programming 2: Data Manipulation Techniques, and from materials from previous semesters

Course Design, Materials, and Activities (cont’d)  In-Class Laboratory Sessions  Held second hour of the two-hour class meeting time  Each lab consists of three different “levels”  Based on questions from e-learning courses SAS ® Programming 1: Essentials and SAS ® Programming 2: Data Manipulation Techniques, and from readings assigned during previous week  Labs are hand-on

Course Design, Materials, and Activities (cont’d)  Virtual Laboratory Sessions  Purpose: To answer students’ questions pertaining to anything covered throughout the course and to review and give further examples of the concepts covered in the lectures and readings  Class meets online for approximately one hour  Rely on the GoToMeeting software and the SAS ® OnDemand for Academics application platforms  Students phone in to call line or use a computer with a microphone and speakers for the audio portion, and use the computer for the visual portion of the lab (via screen sharing)

Course Design, Materials, and Activities (cont’d)  SAS® OnDemand for Academics  Provided free as part of UPenn’s academic software license  Allows students greater access to SAS ® software

Course Design, Materials, and Activities (cont’d)  Assigned Readings  Two chapters assigned from SAS ® Base Certification Prep Guide each week  Reading topics follow chapters laid out in the SAS ® Base Certification Prep Guide, with corresponding readings from Learning SAS ® by Example (Cody, 2007)

Course Design, Materials, and Activities (cont’d)  Take-home Problem Sets  Assigned each week and to be turned in at beginning of the next class session  Typically consist of ten SAS ® Base Programming exam-style multiple-choice questions  Based on questions from e-learning courses SAS ® Programming 1: Essentials and SAS ® Programming 2: Data Manipulation Techniques

Course Design, Materials, and Activities (cont’d)  Midterm and Final Exams  Midterm exam comprised of 50 SAS ® Base Programming exam- style multiple-choice questions – administered in-class, with two hours to complete.  Final exam comprised of take-home programming tasks similar to those completed in the in-class labs, with up to one week to complete.

Results and Future Plans  Class Results: Course Exams  Midterm Exam: Range – 69% - 100% | Median – 90%  Final Exam: Range – 73% - 100% | Median – 98%

Results and Future Plans (cont’d)  Class Results: SAS® Base Certification Exam  One month after course ended, 11 of 26 students from course took the SAS ® Base Programming for SAS ® 9 certification exam.  Ten of the 11 students passed the exam!  Certification Exam: Range – 50% - 93% | Median – 90%

Results and Future Plans (cont’d)  SAS Advanced Programming Course  Similar course based on SAS ® Certification Prep Guide: Advanced Programming for SAS ® 9 (Third Edition) textbook  Prepare students to take the SAS ® Advanced Programming for SAS ® 9 certification exam  Cover topics including: integration of SQL, macro processing, and advanced SAS programming techniques

Reflections and Conclusions  Successes  Goal of adequately preparing students for SAS ® Base Programming for SAS ® 9 exam was achieved

Reflections and Conclusions  Tips and Points for Improvement  Important for an instructor to be strategic in constructing the syllabus (e.g. timing and balance)  Requires an effort to align SAS supplementary materials with SAS ® Base Certification Prep Guide  Advantageous for both the instructor and teaching assistants to sit for the actual SAS ® Base Certification exam  Extend reach across and beyond the University

References  Citrix Online, LLC. (2012). GoToMeeting [Software]. Available from  Cody, Ron Learning SAS ® by Example: A Programmer’s Guide. Cary, NC; SAS Institute Inc.  Ensor, Michelle & Farmer, Susan SAS ® Programming 1: Essentials Instructor’s Guide. Cary, NC; SAS Institute Inc.  McAfee, Rob & Passarella, Kathy SAS ® Programming 2: Data Manipulation Techniques Instructor’s Guide. Cary, NC; SAS Institute Inc.  SAS Institute Inc SAS ® Certification Practice Exam: Base Programming for SAS ® 9. Cary, NC: SAS Institute Inc.  SAS Institute Inc SAS ® Certification Prep Guide: Advanced Programming for SAS ® 9, Third Edition. Cary, NC: SAS Institute, Inc.  SAS Institute Inc SAS ® Certification Prep Guide: Base Programming for SAS ® 9, Third Edition. Cary, NC: SAS Institute Inc.  SAS Institute, Inc. (2012). SAS OnDemand for Academics [Software]. Available from

Acknowledgements  Yuqing Liu – UPenn GSE Student  Michelle Munoz-Miller – ANALYTICA, Inc.  Mackson Ncube – ANALYTICA, Inc.  Herbert Turner, Ph.D. – Course instructor for EDUC625 Contact Information Christine Bonney Michael Keith

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