No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The effect of grading incentive on student discourse in Peer Instruction
1.E. Mazur, Peer Instruction: A User’s Manual (Prentice Hall, Upper Saddle River, NJ, 1991).
2.Although the basic vote counting function described in this article is present in all CRS systems, vendors seek to distinguish their systems by including special options such as numeric entry, student confidence rating, LCD display on response pads, elaborate statistical packages for analyzing responses, seamless integration with POWERPOINT, and grade book synchronization with campus WEBCT and BLACKBOARD systems. Most systems, like the one used in this study distributed by eInstruction (einstruction.com), can assign 0 to 100% credit for incorrect CRS responses. Compact radio frequency based systems eliminate the troublesome installation issues found with the early line-of-sight infrared based systems and are now the industry standard. Most publishers offer discounted systems as an incentive for textbook adoption.
3.D. E. Meltzer and K. Manivannan, “Transforming the lecture-hall environment: The fully interactive physics lecture,” Am. J. Phys.0002-9505 70(6), 639–654 (2002).
4.A. P. Fagen, C. H. Crouch, and E. Mazur, “Peer Instruction: Results from a range of classrooms,” Phys. Teach.0031-921X 40, 206–209 (2002).
5.J. Poulis, E. Robens, and M. Gilbert, “Physics lecturing with audience paced feedback,” Am. J. Phys.0002-9505 66(5), 439–441 (1998).
7.S. P. Rao and S. E. DiCarlo, “Peer Instruction improves performance on quizzes,” Adv. Physiology Educ. 24, 51–55 (2000).
8.L. A. Van Dijk, G. C. Van Der Berg, and H. Van Keulen, “Interactive lectures in engineering education,” Eur. J. Eng. Educ.0304-3797 26(1), 15–28 (2001).
9.L. C. Scharmann, M. C. James, and A. S. Smith, “Assessment in college science courses,” in Reform in Undergraduate Science Teaching for the 21st Century, edited by D. W. Sunal and E. L. Wright (Information Age Publishing, Greenwich, 2004), Vol. 1, Chap. 8, pp. 137–152.
10.V. L. Dickinson and L. B. Flick, “Beating the system: Course structure and student strategies in a traditional introductory undergraduate physics course for nonmajors,” Sch. Sci. Math.0036-6803 98(5), 238–246 (1998).
11.D. Boud, R. Cohen, and J. Sampson, “Peer learning and assessment,” Assessment & Evaluation in Higher Educ. 24(4), 413–426 (1999).
12.S. Kaartinen and K. Kumpulainen, “Collaborative inquiry and the construction of explanations in the learning of science,” Learn. Instr.0959-4752 12, 189–212 (2002).
13.Pearson’s is a measure of the degree of linear relationship between two variables. A correlation of would indicate a perfect positive linear relationship. Correlations above 0.9 are considered very high. The high correlation between tabulators in this study indicates that the criteria for tabulating conversations were well defined.
14.The F test is a test for the statistical significance of an observed difference between the means of two samples. The numbers in parentheses indicate the number of groups minus one and the sample size minus the number of groups, respectively. The power of a test is the probability that a statistical finding occurred by chance. A value of 0.008 indicates less than a 1% probability that the observed difference in group means occurred by chance.
Article metrics loading...
Full text loading...
Most read this month