Download
slide1 n.
Skip this Video
Loading SlideShow in 5 Seconds..
Math Redesign Models Sue Sherry Northern Virginia Community College Annandale, Virginia August 18, 2011 PowerPoint Presentation
Download Presentation
Math Redesign Models Sue Sherry Northern Virginia Community College Annandale, Virginia August 18, 2011

Math Redesign Models Sue Sherry Northern Virginia Community College Annandale, Virginia August 18, 2011

384 Views Download Presentation
Download Presentation

Math Redesign Models Sue Sherry Northern Virginia Community College Annandale, Virginia August 18, 2011

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Math Redesign ModelsSue SherryNorthern Virginia Community CollegeAnnandale, VirginiaAugust 18, 2011

  2. Reasons for Math Redesign • Developmental math failure rates typically 50% + • Students had to take entire course even though only deficient in certain topics • Students had to learn at the same pace with same instructional strategies as whole class • Math serves as roadblock to educational goals • Math requirements delay admissions into certain programs such as health science.

  3. NCAT National Center for Academic Transformation • Independent non-profit organization founded by Dr. Carol Twigg • Promotes course redesign with technology to improve learning outcomes and reduce costs • 1999-2003 Program in Course Redesign assisted 30 colleges: improved student learning with cost reductions of 20% to 77% • Current initiatives: Roadmap to Redesign, Colleagues Committed to Redesign, Changing the Equation: Redesigning Developmental Math

  4. Redesign Models • Linked Workshop • Buffet • Supplemental • Fully Online • Replacement • Emporium

  5. NCAT Innovative Redesign Practices • Undergraduate Learning Assistant • Creating “small” within “large” • New Instructional Roles • Freshman Don’t Do Optional • Modularization • Avoiding “either/or” Choices

  6. MyMathLab & Other Software Packages • Increased pass rates and retention rates • Promotes active learning with student engagement • On-demand individualized assistance • 24/7 access to online learning resources • Supports different learning styles and rates • Immediate feedback • Consistent course content • Course management to monitor student progress • Automatic grading of homework, quizzes & exams

  7. Linked Workshop Model • Retains basic structure of college-level course • Replaces developmental course with just-in-time workshops to address core math deficiencies • Workshops consist of computer-based instruction, small group activities and test reviews • Facilitated by students trained and supervised by faculty • Activities designed so that students use concepts in next class session

  8. Austin Peay State UniversityLinked Workshop Model • Eliminated Elementary & Intermediate Algebra • Developed Enhanced “E” sections of Fundamentals of Math (Math for Poets) & Elements of Statistics • Structured Learning Assistance (SLA) leaders were embedded in classrooms & served as peer tutors • SLA leaders facilitated workshops and provided prompt feedback on all learning activities • Standardize group activities=consistency across all sections

  9. APSU Linked Workshop Challenges • Identifying competencies & requisite skills needed for core courses • Developing SLA workshop materials • Building faculty consensus • SLA staffing issues • Purely E-sections vs. combined E-sections

  10. APSU Linked Workshop Results Developmental students in Mathematical Thoughts Pass rate: 33% to 71% Developmental students in Elements of Statistics Pass rate: 23% to 54% Reduced sections: 52 sections of developmental math replaced with 13 E-sections of Fundamentals of Math and 21 E-sections of Elements of Statistics Freed 70 classrooms, saved $110,000 a year = Cost reduction of 52%

  11. Buffet Model • Customizes the learning environment for each student based on background, learning preference, academic or professional goals • Requires online assessment of student’s learning style and study skills • Includes lectures, discovery labs, team/group labs, videos, active problem-solving, GTA or self-graded HW, individual or group projects • Initial in-class orientation re buffet structure, content, learning contract, paths & modules

  12. Ohio State UniversityBuffet Model for Stat • OSU serves 3,000 Intro Statistics students a year • Student Learning Styles Inventory: Sensing vs. Intuition Group vs. Individual learner Active vs. Reflective learners • Three Course components (eight possible paths) Lecture: concepts (reflective learner) vs. group problems solving (active learner) Problem Solving: in-class vs. out-of-class activities Lab: hands-on with data gathering (sensing learners) vs. data is provided (intuitive learners)

  13. OSU Buffet Model for Stat • Course was modularized into 5 modules • Student must show level of proficiency before moving to next module • Offload course grading to software • Created a statistics Help Room • Instituted certificate process for TAs • Matched TAs teaching styles to delivery options

  14. OSU Buffet Model Challenges • Designing assignments with equitable difficulty since students selected paths perceived to be less difficult • Integration of learning objectives and learning activities was labor intensive • Initial coding of course components by learning objective was very labor intensive • Initial student online orientations were problematic – then face-to-face then streamlined online process

  15. OSU Buffet Model Results • Identified deficiencies early = lower failure and withdrawal rates Failure rates: 7% to 3% Withdrawal rates: 11% to 8% Incomplete rates: 2% to 1% • Increased student choices re paths = increased student satisfaction and learning • Reduced in-class sessions, more efficient use of TAs Cost savings: 25%

  16. OSU Stat Resources • Dr. Dennis Pearl involved with CAUSE: Center for Advancement of Undergraduate Statistics provides workshops, webinars, online resources and grants Website: www.causeweb.org • Educational Learning Lab – Dr. Bruce Tuckman interests in motivation and cognitive processes and their application in motivation strategies; procrastination and methods to overcome it. His books include: Strategies of School Success and Motivation Strategies: Your Guide to Success

  17. Supplemental Model • Retains basic structure of traditional course particularly number of class meetings • Supplements lectures and textbooks with tech-based out-of-class activities to increase student engagement & prepare students for class • Create active learning environment within the large lecture hall setting

  18. Carnegie Mellon UniversitySupplemental Model for Stat Goals of Redesign • Develop student interest in and skills for solving statistical problems before learning quantitative aspects of stat reasoning • Increase student understanding and skill level at end of course and ability to transfer statistical skills to future classes and to real world • Substitute technology “capital” for faculty & TA “capital”

  19. CMU Supplemental Model for Stat • Developed activities and HW that were more open-ended, exploratory & active with timely tutoring assistance • Created “real world situation” labs • Formed team of faculty, cognitive scientists, human-computer interaction experts • Developed automated, intelligent tutoring system StatTutor which provides “scaffolding”: monitors students’ work, provides feedback when they pursue unproductive paths, answers student questions, tracks individual student’s acquisition of skills in statistical inference

  20. CMU Supplemental Model for Stat Challenges • Software development • Professional preparation of TAs • Incorporating student input into design • Transition from pilot to full implementation • Computer laboratory availability Results • Improvement over traditional student on variety of final exam questions • Increased number of Statistics majors coincident with project design • Cost savings of 25%

  21. CMU Open Learning Initiative • Dr. Joel Smith: “Experts in academic fields often lose sight of how novices learn” • OLI courses also developed by content-savy faculty, cognitive scientists, human-computer interaction specialists • OLI courses contain embedded assessment component and provide instructors & student with continuous feedback • Report feedback is “dashboard for instructors” – determine which portions of course students comprehend • OLI + Instruction = “killer application”, faster completion plus better retention

  22. CMU Open Learning Initiative

  23. CMU Open Learning Initiative OLI course development » Collection of interaction level student data » Evaluate and improve courses » Create rigorous, theory-based experiments » Pave way to understanding of robust learning Current OLI courses: Engineering Statics, French, Physics, Biology, Chemistry, Biochemistry, Economics, Comp. Discrete Math, Logic & Proofs, Empirical Research Methods, and Visual Communication Design CC-OLI consortium of 40 com colleges, use Cognitive Tutor

  24. Fully Online Model • Eliminates all in-class meetings • Moves learning experiences online • Uses web-based, multimedia resources & commercial software • Automatically evaluated assessments with guided feedback • Links to additional resources • Alternate staffing models

  25. Rio Salado CollegeFully Online Model • Redesigned four Developmental Math courses • Increased class size from 35 to 100 per instructor • Added Course Assistant to troubleshoot tech questions, monitor students’ progress and alert instructor to difficulties with material, contact non-attending students • Increase in student success rate: 59% to 68% • Cost savings: 30%

  26. Rio Salado CollegeFully Online Model Challenges • Identifying and training candidates for Course Assistant • Finding best match between instructor and redesign format • Reducing student dissatisfaction rate related to communication • Determining appropriate number of students per instructor (100 then down to 50)

  27. Rio Salado College Fully Online Model Initiatives • RSC plans to pilot a program of Online Learning Communities which pair online Developmental Math courses with Online College Success courses: CPD 115 Creating College Success focuses on methods for selecting and developing effective academic strategies, increasing self-awareness and improving self-management skills CPD 150 Strategies for College Success focuses on college orientation and personal growth, study skills development, and educational & career planning.

  28. Replacement Model • Reduces the number of in-class meetings but does not eliminate all in-class meetings • Replaces (rather than supplements) some in-class time with online, interactive learning activities. • Assumes certain activities are better accomplished online individually or in small groups • Considers why and how often classes need to meet face-to-face

  29. Riverside City CollegeReplacement Model • Redesign of Elementary Algebra 3,600 students • Encourage students to take active role in learning according to preferred learning styles • Move from seat-time model to subject mastery model • Two lecture hours plus two hour interactive lab • Switched from ALEKS to MyMathLab for better text book correlation • Due to budget cuts class size rose from 45 to 60 • Cost savings 41%, mixed results

  30. Riverside City CollegeReplacement Model RCC offers: MTH 63 a five credit Arithmetic and MTH 64 a five credit Pre-Algebra or MTH 90 with six modules, self paced & students only take a final exam for each module Community for Academic Progress offers MTH 63 with a one credit Reading Strategies for Textbooks to lower math anxiety about solving math word problems while increasing reading comprehension.

  31. Moreno Valley CollegeTeam-based Learning Program • Pilot of Elementary Algebra course • Student utilized Netbooks funded by Verizon and a grant • Students read & study assignment, take quiz on Netbook, automatically graded, team review quiz material and later complete HW. Teams then take a 10 questions quiz on “scratchers” • Website: www.teambasedlearning.org

  32. Moreno Valley CollegeTeam-based Learning Program

  33. Hagerstown Community CollegeReplacement Model • Enroll over 700 College Algebra students a year • Class 75 minutes and lab 90 minutes with same instructor • All homework, tests & quizzes use MyMathLab • Fall 2006 pass rate 53.1% to 64.5%; Spring 2011 pass rate was 64.1% • Highest pass rate of 74.5% was fall 2007 when students spent 4 hours with instructors rather than 3 • Pilot with Trigsted e-book designed for the way students think and behave online

  34. Math Redesign – Other Initiatives Community College Research Center – more dev. math students do not sign up for 1st class or subsequent class than are lost to failing grades. The more courses in sequence, the more chances that students disappear. Carnegie Foundation for Advancement of Teaching created pathways: Statway- El. Algebra through Stat in one year by blending the necessary algebra topics www.carnegiefoundation.org/statway Quantway - foundations of math literacy › STEM path or other college level math courses

  35. Emporium Model • Lectures replaced with learning resource center model w interactive software and on-demand personalized assistance • Software includes tutorials, videos, animations, practice exercises and tests, homework help, online quizzes and tests • Students choose resources according to preferred learning style • Staff includes faculty, peer tutors, TAs, lab assistants • Versions: Fixed, Flexible or combination

  36. Emporium Model Benefits • Students: active participants not passive observers • Greater flexibility to schedule coursework • Reduce time spent on repeat course or material; instead complete only needed modules • Students move to desired major more quickly • Save tuition by taking fewer dev math credits • Access to variety of learning resources • On-demand individual assistance

  37. Emporium Model Results Virginia Tech Spacious 537 computer Emporium lab open 24/7 Started with 2,000 student Linear Algebra (pass rate 80%- 87%) Va Tech faculty developed courseware w Scholar software Current 7 math courses via emporium, 4 affiliate Orientation then directly to practice quiz Tutors take weekly quiz on 7 courses Lab staff have semi-monthly meeting

  38. Emporium Model Results University of Alabama Mediocre results until reinstatement of required lab attendance (& other initiatives) led to 60%+ pass rate Cost savings was 33% Jackson State Community College Pass rates spring 2008: Basic Math 41% vs. 54%, El. Algebra 32% to 66%, Int. Algebra 48% to 44% Fall 2008 pass rate of all dev. Math was 57% Cost saving 20%

  39. Emporium Model Results Cleveland State Community Pass rates 2008: El. Algebra 50% to 68%; Int. Algebra 57% to 74%; # Students who passed Dev Math incr. 29%, # who exited dev math incr. 32% Cost savings 19% Now all math classes delivered via this model Chattanooga State Community College Int. Algebra 2005 to 2007 pass rates were 51%, Fall 2011 pass rate was 67% Redesigned 11 math courses in 2 years

  40. Emporium Model: Lessons Learned • Get policies in order for all situations • Appropriate staff with good attitude is crucial • Adequate training and review of skills for lab staff • Scheduled Orientation and Learning contracts • Must get 100% on syllabus quiz before starting course • Run the labs like a prison • Use software that correlates to texts • Student might use lab cups as spittoons!

  41. Math Department Future Endeavors • Incorporate Student Development course components within Developmental Math classes with “Ten Minute Student Success Exercises” • Pilot Pre-calculus classes with Trigsted e-text combined with traditional model • Incorporate Carnegie Mellon’s Open Learning Initiative courseware within Into Statistics course • Incorporate some Team-based techniques within various math classes

  42. NCAT Changing the Equation: Redesigning Developmental Math • In this program 38 institutions redesigned developmental math using the Emporium Model • Modularization: 6 to 31 modules in 5 to 400 sections • NOVA offers 10 modules in 330 sections • Individual modules MTE 1, MTE 2, … MTH 9 etc. • Shell Courses MTT 1, MTT 2, MTT 3, MTT4 • Average cost saving 27%, NOVA instructional expense reduction 33%

  43. Acknowledgements Developmental Math Redesign Staff Dr. Joyce Samuels Loudon Provost Developmental Math Managers Marty Bredeck Annandale Tonia Vaughn Alexandria Pat Lazzarino Manassas Jane Serbousek Loudon Theresa Overton Woodbridge Lab Assistants, Administrative Assistants, Faculty

  44. Acknowledgements Developmental Math Redesign Staff Dr. Joyce Samuels Theresa Overton DMR Coordinator Developmental Math Managers Marty Bredeck Annandale Tonia Vaughn Alexandria Pat Lazzarino & Manassas Bill Ruffle Jane Serbousek Loudon Teresa Overton Woodbridge Faculty, Lab Staff, Administrative Assistants

  45. Resources • Center for Advancement of Undergraduate Statistics Education: www.causeweb.org • Carnegie Foundation for the Advancement of Teaching: www.carnegiefoundation.org/statway/ • Community College Open Learning Initiative:oli.web.cmu.edu/openlearning/initiative/ • National Center of Academic Transformation: www.thencat.org • Team Based Learning: www.teambasedlearning.org • Trigsted e-text: www.pearsonhighered.com