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SAS Skill Learning and Certification Preparation in a Graduate School Setting Christine Bonney Michael Keith Michael Keith University of Pennsylvania Graduate School of Education
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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
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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
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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
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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
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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
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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)
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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
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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)
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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
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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.
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Results and Future Plans Class Results: Course Exams Midterm Exam: Range – 69% - 100% | Median – 90% Final Exam: Range – 73% - 100% | Median – 98%
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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%
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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
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Reflections and Conclusions Successes Goal of adequately preparing students for SAS ® Base Programming for SAS ® 9 exam was achieved
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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
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References Citrix Online, LLC. (2012). GoToMeeting [Software]. Available from http://www.gotomeeting.com/fec/online_meeting Cody, Ron. 2007. Learning SAS ® by Example: A Programmer’s Guide. Cary, NC; SAS Institute Inc. Ensor, Michelle & Farmer, Susan. 2009. SAS ® Programming 1: Essentials Instructor’s Guide. Cary, NC; SAS Institute Inc. McAfee, Rob & Passarella, Kathy. 2009. SAS ® Programming 2: Data Manipulation Techniques Instructor’s Guide. Cary, NC; SAS Institute Inc. SAS Institute Inc. 2007. SAS ® Certification Practice Exam: Base Programming for SAS ® 9. Cary, NC: SAS Institute Inc. SAS Institute Inc. 2011. SAS ® Certification Prep Guide: Advanced Programming for SAS ® 9, Third Edition. Cary, NC: SAS Institute, Inc. SAS Institute Inc. 2011. 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 http://www.sas.com/govedu/edu/programs/od_academics.html
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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 christine.bonney@uphs.upenn.edu Michael Keith mikeith@gse.upenn.edu
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