The Design and Experimental Evaluation of a Scaffolded Software Environment to Improve Engineering Students' Disciplinary Problem‐Solving Skills

Background Introductory gateway engineering courses are notorious for their high attrition rates. Deficiencies in students' problem-solving processes may contribute to their failure in these courses. In an empirical study of student problem solving, we observed that students struggle because of misconceptions regarding the basic syntax and semantics of disciplinary diagrams and corresponding mathematical equations. Purpose(Hypothesis) We hypothesize that a scaffolded software environment that provides dynamically-generated feedback on the syntactic and semantic correctness of students' evolving disciplinary diagrams and mathematical equations can improve engineering students' problem-solving abilities. Design/Method We iteratively developed ChemProV, a software environment to assist chemical engineering students in solving material balance problems. To evaluate ChemProV's effectiveness, we performed two between subjects experimental studies. The first study compared a preliminary version of the ChemProV to pen-and-paper. The second study compared a redesigned version of ChemProV with dynamic feedback to the same version of ChemProV without dynamic feedback. Results While it did not uncover any significant differences, the first study provided insight into how to improve ChemProV's dynamic feedback mechanism. The second study found that the “feedback” version of ChemProV promoted a statistically-significant advantage in problem-solving accuracy, significantly more time-on-task, and a transfer-of-training to an unscaffolded problem-solving situation. Conclusion A scaffolded software environment like ChemProV can serve as a valuable aid in helping students learn engineering problem-solving skills. Its software design approach can be used as a model for designing educationally-effective software environments for other engineering disciplines.

[1]  Christopher D. Hundhausen,et al.  AC 2007-1550: VISUAL LEARNING IN A MATERIAL/ENERGY BALANCE CLASS , 2007 .

[2]  Elliot Soloway,et al.  Pocket PiCoMap: a case study in designing and assessing a handheld concept mapping tool for learners , 2003, CHI '03.

[3]  Michelene T. H. Chi,et al.  Expertise in Problem Solving. , 1981 .

[4]  T. J. Anderson,et al.  Graduation rates, grade-point average, and changes of major of female and minority students entering engineering , 2005, Proceedings Frontiers in Education 35th Annual Conference.

[5]  Susan E. Newman,et al.  Cognitive Apprenticeship: Teaching the Craft of Reading, Writing, and Mathematics. Technical Report No. 403. , 1987 .

[6]  Tom Routen,et al.  Intelligent Tutoring Systems , 1996, Lecture Notes in Computer Science.

[7]  Christopher D. Hundhausen,et al.  The design of an online environment to support pedagogical code reviews , 2010, SIGCSE.

[8]  Steve Nelson,et al.  Instructional Time as a Factor in Increasing Student Achievement. , 1990 .

[9]  Daniel D. Suthers,et al.  Kukakuka: An Online Environment for Artifact-Centered Discourse. , 2002 .

[10]  Jeremy Roschelle,et al.  SIMCALC : Accelerating Students’ Engagement With the Mathematics of Change , 2000 .

[11]  Carolyn Penstein Rosé,et al.  The Architecture of Why2-Atlas: A Coach for Qualitative Physics Essay Writing , 2002, Intelligent Tutoring Systems.

[12]  GianMario Besana,et al.  Together is better: strengthening the confidence of women in computer science via a learning community , 2004 .

[13]  J. Roschelle Designing for cognitive communication: epistemic fidelity or mediating collaborative inquiry? , 1997, Computers, Communication and Mental Models.

[14]  Alison Castro Superfine,et al.  Translation between external representation systems in mathematics: All-or-none or skill conglomerate? , 2009 .

[15]  R. Atkinson,et al.  An Example Order for Cognitive Skill Acquisition , 2010 .

[16]  V. Shute Focus on Formative Feedback , 2007 .

[17]  R. Atkinson,et al.  Structuring the Transition From Example Study to Problem Solving in Cognitive Skill Acquisition: A Cognitive Load Perspective , 2003 .

[18]  Etienne Wenger,et al.  Situated Learning: Legitimate Peripheral Participation , 1991 .

[19]  Ann L. Brown,et al.  How people learn: Brain, mind, experience, and school. , 1999 .

[20]  Christopher D. Hundhausen,et al.  Exploring studio-based instructional models for computing education , 2008, SIGCSE '08.

[21]  Daniel D. Suthers,et al.  Comparing the roles of representations in face-to-face and online computer supported collaborative learning , 2003, Comput. Educ..

[22]  John R. Anderson,et al.  Cognitive Tutors: Lessons Learned , 1995 .

[23]  Daniel D. Suthers,et al.  An integrated approach to implementing collaborative inquiry in the classroom , 1997, CSCL.

[24]  Orit Hazzan,et al.  Problem-solving strategies , 1986 .

[25]  Jörg Wittwer,et al.  Can tutored problem solving benefit from faded worked-out examples? , 2007 .

[26]  Kevin Dahm,et al.  IS PROCESS SIMULATION USED EFFECTIVELY IN ChE COURSES , 2002 .

[27]  Daniel D. Suthers Representational and Advisory Guidance for Learning: Alternate Roles for AI. , 1999 .

[28]  John R. Anderson,et al.  Skill Acquisition and the LISP Tutor , 1989, Cogn. Sci..

[29]  J. Daugherty,et al.  Professional Development for Teachers of Engineering: Research and Related Activities , 2009 .

[30]  V. Aleven,et al.  Help Seeking and Help Design in Interactive Learning Environments , 2003 .

[31]  R. W. Rousseau,et al.  Elementary principles of chemical processes , 1978 .

[32]  John R. Anderson,et al.  The Transfer of Cognitive Skill , 1989 .

[33]  Ronan G. Reilly,et al.  Examining the role of self-regulated learning on introductory programming performance , 2005, ICER '05.

[34]  R. Felder,et al.  Applications, Reliability and Validity of the Index of Learning Styles* , 2005 .

[35]  Christopher D. Hundhausen,et al.  Designing, visualizing, and discussing algorithms within a CS 1 studio experience: An empirical study , 2008, Comput. Educ..

[36]  Joseph Krajcik,et al.  A Scaffolding Design Framework for Software to Support Science Inquiry , 2004, The Journal of the Learning Sciences.

[37]  Elliot Soloway,et al.  Learning theory in practice: case studies of learner-centered design , 1996, CHI.

[38]  Mark Guzdial,et al.  Software-Realized Scaffolding to Facilitate Programming for Science Learning , 1994, Interact. Learn. Environ..

[39]  Pawan Agarwal THE DESIGN AND EMPIRICAL EVALUATION OF A CHEMICAL PROCESS VISUALIZATION TOOL TO HELP INTRODUCTORY CHEMICAL ENGINEERING STUDENTS SOLVE MATERIAL BALANCE PROBLEMS , 2009 .

[40]  Joanne Gainen,et al.  Barriers to Success in Quantitative Gatekeeper Courses. , 1995 .

[41]  Frank E. Ritter,et al.  In order to learn : how the sequence of topics influences learning , 2007 .

[42]  Joseph Krajcik,et al.  A Case Study to Distill Structural Scaffolding Guidelines for Scaffolded Software Environments , 2002, CHI.

[43]  Dorothea P. Simon,et al.  Expert and Novice Performance in Solving Physics Problems , 1980, Science.

[44]  M. Cole,et al.  Mind in society: The development of higher psychological processes. L. S. Vygotsky. , 1978 .

[45]  Robert B. Kozma,et al.  Representational Resources for Constructing Shared Understandings in the High School Chemistry Classroom , 2008 .