1. INTEGRATING “SMART” MATERIALS INTO A FIRST-YEAR ENGINEERING CURRICULUM: A CASE STUDY  Luke Penrod  Diana Talley  Jeff Froyd  Rita Caso  Dimitris Lagoudas  Terry Kohutek http://crcd.tamu.edu

2. Development of a Multidisciplinary Curriculum for Intelligent Systems (MCIS)  Rita M. Caso  Jeffery E. Froyd  Dimitris C. Lagoudas  Othon K. Rediniotis  Thomas W. Strganac  John L. Valasek  John D. Whitcomb Work was partially supported by NSF CRCD Award # 0088118. Their support is gratefully acknowledged.

3. Texas A&M University Goals of MCIS Effort at TAMU  Develop new curriculum track on Intelligent Systems emphasizing aerospace technologies.  Increase knowledge and interest in using smart materials to design intelligent systems.  Include a 2 semester design course and a one-on-one directed studies course with a faculty member.  Offer an “Intelligent Systems Track” Certificate.  15 hour program  Includes recognition on transcript URICA and design team Synthetic Jet Actuator

4. Texas A&M University Courses Impacted  AERO 101 - Introduction to Aerospace Engineering (F01)  ENGR 111/112 - Foundations of Engineering I/II (F01/S02)  ENGR 211/213/214 - Basic engineering science courses (S02, F02)  AERO 302 - Aerospace Engineering Laboratory I (S02)  AERO 304/306 - Structural Mechanics I/II (F01, F02)  AERO 401/402 - Senior design sequence (F03, S04)  AERO 404 - Mechanics of Advanced Aerospace Structures (F02)  AERO 405 - Aerospace Structural Design (F01)  AERO 420 - Aeroelasticity (S02)  AERO 489* - Special Topic: MEMS for Aerospace Engineering (F01)  AERO 489* - Special Topic: Aerospace Intelligent Systems (S02) *New Course

5. Texas A&M University Foundations of Engineering (ENGR 111/112) Activities with Shape Memory Alloys (SMA) Heat Engine Demo: SMA Efficiency/ Thermodynamics Butterfly Demonstration: SMA Linear Actuator Thermobile ™ Demo: SMA Properties/ Thermodynamics Stiquito Project: Application of SMA

6. Texas A&M University ENGR 111/112 Project Walking Robot  Robot (Stiquito) specifications:  Must be actuated by SMAs  Goal is maximum distance in 3 minutes  Only contact can come from ground  Must be an autonomous system  Assigned to 11 four-person student teams in ENGR 112 (24 teams participated in Engr 111 in the previous semester)  Maximum distance traveled was 48cm.

7. Texas A&M University How did it happen?  Luke Penrod, graduate student, volunteered to develop materials and projects for first-year engineering course and coordinated material development.  Diana Talley, undergraduate student on summer research project, assembled possible materials on shape memory alloys (SMAs) for use in first-year engineering course. One of the possible projects was a Stiquito robot kit that was commercially available.  Jeff Froyd approached Terry Kohutek, first-year engineering course coordinator, about incorporating SMA material into ENGR 111 and Terry accepted

8. Texas A&M University How did it happen? (continued)  Luke worked with Terry to develop specifications for a Stiquito robot project.  Luke developed a PowerPoint presentation on SMAs.  Showed applications for SMAs, e.g., SMA jacket that remembers its shape  Described the material structure of a SMA  Luke worked with Terry to implement and evaluate student robot project.  After two semesters, Terry now uses the Stiquito project and PowerPoint presentation in his class.

9. Texas A&M University CRCD Intelligent Systems Curriculum Impact Assessment and Evaluation of YEAR 1 OUTCOMES-Design Knowledge (Implemented 1 and/or Projected ) CRCD Intelligent Systems Curriculum Impact Assessment and Evaluation of YEAR 1 OUTCOMES-Design Knowledge (Implemented 1 and/or Projected ) FOCI STUDENT OUTCOME MEASUREMENT Interest  Retention in Major  Pre-Post Attitude Survey results (Fr, Soph)  Enrollment in Project courses  Targeted class activities feedback (Fr) Content Knowledge  Targeted parts of class-embedded tests, assignments & projects Engineering & Design Process Skills  Design Knowledge baseline pre-test (Fr, Sr)  Engineering /Design Process Performance assessment (Fr)  Design Product assessment Levels at which Implemented ( i.e., Fr=Freshman, Soph=Sophomore, Sr=Senior)

10. Texas A&M University CRCD Intelligent Systems Curriculum Impact on Design Knowledge  To be examine changes over time in students’ design knowledge, benchmark measures were taken for: Freshmen: Beginning and ending first year Seniors: Beginning 1 st semester of Aero Design and ending 2 nd semester of Aero Design  A slightly adapted version of the TIDEE Team-Based Design Knowledge Assessment Test and Scoring Rubric was used to measure Engineering Design Process Teamwork Communication.

11. Texas A&M University CRCD Intelligent Systems Curriculum Impact on Design Knowledge:Team Design Process, Teamwork & Communication 1 Freshman vs. Senior Baselines ( Early Fall 2001) AERO CRCD Students 0—5.5 Scale Design Process Team Work Communication* Freshmen 2 (n=88) Mean Scores 4 2.712.591.62 Std. Dev.1.140.950.76 Seniors 3 (n=23) Mean Scores 3.302.302.04 Std. Dev.1.150.790.85 1 TAMU AERO CRCD Adapted TIDEE Project Mid Program Assessment Instrument #1, Design knowledge * Validity in question. Question universally misinterpreted. Scores Scaled 0 – 5.5, with 0=no knowledge & 5.5=exceptional knowledge

12. Texas A&M University CRCD Intelligent Systems Curriculum Impact on Design Knowledge : Freshman Benchmarks Freshman Team-Based Design Knowledge Pre & ** Post Assessment -0.5 0.5 1.5 2.5 3.5 4.5 5.5 DesignTeamworkCommunication* Question Topics Scores Pre TestPost Test. ** Post Test was given to a different set of Freshman * Validity in question. Question universally misinterpreted. Scores Scaled 0 – 5.5, with 0=no knowledge & 5.5=exceptional knowledge *

13. Texas A&M University CRCD Intelligent Systems Curriculum Impact on Design Knowledge : Senior Benchmarks Senior Team-Based Design Knowledge : Pre & Post Assessment -0.5 0.5 1.5 2.5 3.5 4.5 5.5 DesignTeamworkCommunication* Question Topic Score Pre TestPost Test * Validity in question. Question universally misinterpreted. Scores Scaled 0 – 5.5, with 0=no knowledge & 5.5=exceptional knowledge