First Quantitative Measurement of Motivation. Study of the Effects of Active Learning Strategies
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Scientific Study from the year 2013 in the subject Pedagogy - Miscellaneous Topics, course: Process Control, language: English, abstract: Most freshmen in engineering departments link an equation learned in a course as a unique theory specific to the subject and fail to realize that it is part of a more general notion that can be applied to a wide variety of natural phenomena. The students are able to use formulas related to the theory perfectly, but sometimes fail to understand what the basic concepts hidden behind the applications are. As a result, many students do not know how to apply similar formulas in other courses in the department. On the other hand, engineers are problem solvers; they need good critical and creative thinking skills to increase the performance of a process or design a new plant under technical, social, economic, regulatory, and environmental constraints. By consequence, how can engineering students be taught to achieve these goals? Literature has shown that effective teachers have succeeded in making students feel good about school and learning, thus increasing student achievement. Moreover, students in an actively taught class do a better job of learning (memorizing) the material they are exposed to, compared to those in a passively taught section. It is also agreed that motivation is probably the most important factor that educators can target in order to improve learning. The main objective of this investigation is to quantify the effects of an active learning strategy on the motivation of students in a process control course. Different from the qualitative methodologies previously presented in the literature, the objective of this first quantitate method is an attempt to measure the impact of an active learning strategy on the motivation of students by introducing a motivation factor for each student calculated from the Final Grade Point (FGP) and the Cumulative Grade point average CGPA. In the first part of the investigation, the R
Zin Eddine Dadach obtained his Bachelor's degree in Refining and Petro-chemistry from the Algerian Institute of Petroleum in 1980. He received his Master's degree in Chemical Engineering from Stevens Institute of Technology (Hoboken, N.J.; USA) in 1984. In a pioneering research study, experimental data for the absorption rates of CO2, H2S, and a mixture of both in hindered amine, 2-amino-2-methyl-1-propanol (AMP) aqueous solutions (0.03 M, 0.1 M, 0.2 M and 0.3 M) were investigated for the first time. Dr. Dadach obtained his Ph.D. degree in Chemical Engineering from Laval University (Quebec, Canada) in 1994. In the dissertation work, Markov chains and Monte Carlo technique were used to stochastically simulate glucose yield during cellulose acid hydrolysis by using model compound cellobiose and cotton crystallinity data. Simulation results were compared to experimental data. He worked in an organic materials department at the Osaka National Research Institute (Osaka, Japan) for two years where he developed a FORTRAN program on Markov analysis of DNA sequences of psbA genes of Synechocystis PCC 6803 in order to determine which genes might be responsible for divergent behavior of transcription in response to light intensity. Since he joined the Higher Colleges of Technology (Abu Dhabi, UAE) in 2005, Dr. Dadach has developed active learning strategies to enhance the intrinsic motivation of students. In a recent published article, he presented a new tool to quantify the effects of an active learning strategy on the motivation of students. He supervised a number of student's final industrial projects including Stripper High Differential Pressure, Sea water back pressure tower foaming, Effluent system salt formation, Carbon Capture and Storage strategies, Hysys simulation of chemical processes, and exergy analysis of power generation plants
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