Seattle, Washington
June 14, 2015
June 14, 2015
June 17, 2015
978-0-692-50180-1
2153-5965
Engineering Physics & Physics
Diversity
23
26.380.1 - 26.380.23
10.18260/p.23719
https://peer.asee.org/23719
783
Dr. Masi is the Director of Education Innovation and Assessment Initiatives in Arts, Sciences and Engineering at the University of Rochester.
Dan Watson, Professor of Physics and Astronomy, is currently chair of the Department of Physics and Astronomy at the University of Rochester. His research centers on the formation of planets and stars, and on the development of detectors and instruments for infrared astronomy. His educational activities include mastery learning, tutorial learning, and the application of online resources and assessment in physics and astronomy courses, both for STEM students and non-majors.
Prof. Bodek received his B.S. in Physics (1968) from the Massachusetts Institute of Technology, and his Ph.D. in Physics (1972) also from MIT. He was a postdoctoral associate at MIT (1972-74) and a Robert E. Millikan Fellow at Caltech (1974-77). Prof. Bodek joined the University as an Assistant Professor of Physics in 1977. He was promoted to Associate Professor in 1980 and to Professor in 1987. Prof. Bodek was appointed as an Alfred P. Sloan Fellow (1979-81); NSF-JSPS Fellow, KEK, Japan (1986); and Fellow of the American Physical Society (1985). He served as a project director at the Department of Energy (1990-91), was Associate Chair (1995-98) and then Chair of the Department of Physics and Astronomy (1998-2007). He is on the editorial board of theEuropean Physics Journal C. Prof. Bodek was awarded the 2004 APS W.KH. Panofsky Prize in Experimental Particle Physics "for his broad, sustained, and insightful contributions to elucidating the structure of the nucleon, using a wide variety of probes, tools, and methods at many laboratories." In 2004, Prof. Bodek received the University of Rochester Award for Excellence in Graduate Teaching. His doctoral thesis provided some of the evidence of the quark's existence that was the basis for the 1990 Nobel Prize in Physics. Prof. Bodek's research interest is in the field of Experimental High Energy Physics.
Dev Ashish Khaitan is a doctoral student in the University of Rochester Department of Physics.
Erik Garcell is a doctoral student in the University of Rochester Department of Physics.
Comparison of Mastery Learning and Traditional Lecture-Exam Models in a Large Enrollment Physics CourseThis study describes the impact of two pedagogical models, mastery and self-paced learningversus traditional lecture and exam, on student performance, study behavior and confidence in anintroductory physics course. The introductory mechanics course, required of most engineeringmajors, posed a challenge for many students, particularly those with weaker high school mathbackground. The “control” course was designed as a traditional lecture and recitation course withtwo major exams. The “experimental” course was designed as self-paced, mastery instructionwhere students were required to pass each of 17 module exams with 90% score. To comparegroups, both received the same final exam.A quasi-experimental design was used. In order to ensure homogeneity between groups, a pre-course basic math test and Force Concept Inventory (FCI) test were given and SAT Math, ACTMath, and calculus course grades were reviewed. Final exam results showed that the masterygroup mean was significantly higher (M=67.4, SD=15.7, N=151) than that for the traditionalgroup (M=60.6, SD=17.5, N=160) (t(309)=2.179, p<0.001). At-risk students in the masterycourse also performed statistically better than a comparative group in the traditional course. Pre-and post course written surveys revealed that the mastery group’s mean confidence in physicsskills was statistically higher than traditional group mean by the end of course (Bandura 1973,1995). Observations of student study processes showed a greater prevalence of “deep learning”strategies used by mastery group compared to traditional group (Lai and Biggs 1994).This study confirms previous studies that found that the mastery learning approach, includingBloom’s mastery model and Keller’s personalized system of instruction (PSI) (Bloom 1973,1976, 1980; Keller 1974, 1980), improves student performance, attitude and confidence inphysics and other sciences (Diegelman-Parente 2011; Kulik et al. 1990; Leonard 2010; Zeilik1981) and in engineering (Capaldi 2014; Sangelkar 2014; Wankat and Oreovicz, 1984, 1993,2001). This study extends previous works by providing a full description of implementation in alarge enrollment, one-term course, often considered a challenge for mastery learning use. Thisstudy extends previous works by establishing a stronger connection between mastery learningand deep learning models. This study recommends that the mastery approach, popular in the1970s, should be revived given its positive impact on at-risk student performance.Sources cited:Bandura, A. (1973). Self-efficacy: Toward a unifying theory of behavioral change.Psychological Review, 84, 191-215.Bandura, A. (1995). Self-efficacy: The exercise of control. New York: Freeman.Bloom, B. (1976). Human characteristics and school learning. New York: McGraw Hill.Bloom, B. (1980). The new direction in educational research: Alterable variables. Phi DeltaKappan, 62, 382-385.Bloom, B., T. Hastings and G. Madaus (1973). Learning for mastery. National Laboratory forHigher Education, 1973.Capaldi, F. (2014). Mastery Learning in Statics Using the STEMSI Online LearningEnvironment. Proceedings of 2014 Zone I Conference of the ASEE, Feb. 14, 2014.Diegelman-Parente, A. (2011). The Use of Mastery Learning with Competency-Based Gradingin an Organic Chemistry Course. Journal of College Science Teaching, 40(5), 2011, 50-58.Keller, F. (1981). PSI and educational reform. Journal of College Science Teaching, 11(1), 37-38.Keller, F., J.G. Sherman and C. Martuscelli Bori (1974). PSI, the Keller Plan Handbook: Essayson a personalized system of instruction. Menlo Park, Calif.: WA Benjamin, 1974.Kulik, C. C., J.A. Kulik and R.L. Bangert-Drowns (1990). Effectiveness of mastery learningprograms: A meta-analysis. Review of Educational Research, 60(2), 265-299.Lai, P. and J. Biggs (1994). Who Benefits from Mastery Learning? Contemporary EducationalPsychology, 19, pp. 13-23.Leonard, W. J. (2010). Work in progress — Application of Mastery Learning in an introductorymathematical physics course. ASEE/IEEE Frontiers in Engineering Education AnnualConference 2010,” Arlington, VA, Oct. 27-30, 2010.Sangelkar, S., O. Ashour, R. Warley and O. Onipede (2014). Mastery Learning in Engineering:A Case Study in Statics. ASEE Annual Conference 2014, Indianapolis, IN, June 15-18, 2014.Wankat, P. and F. Oreovicz (1993). Teaching Engineering. McGraw-Hill, New York, 1993.Wankat, P. and F. Oreovicz (1984). Teaching Prospective Faculty Members About Teaching: AGraduate Engineering Course. Engr. Education, 75(2), Nov. 1984, pp. 85-85.Wankat, P. and F. Oreovicz (2001). Mastery Learning. ASEE Prism 11(3), 2001, pp. 35.Zeilik, M. (1981). Flexible, Mastery-Oriented Astrophysics. American Journal of Physics, 49,827-829.
Masi, B., & Watson, D. M., & Bodek, A., & Khaitan, D. A., & Garcell, E. (2015, June), Comparison of Mastery Learning and Traditional Lecture–Exam Models in a Large Enrollment Physics Course Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.23719
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