Objectives: To discuss the behavior of three different learning domains and effective assessment of each domain. Materials and Methods: Learning domains have always played an important role in evaluating the student's knowledge and skills. The learning domains can be incorporated, while designing the course outcomes of all the courses in a program; however, the assessment of learning domains practiced in many higher education programs resulted in vague assessment methods and as a result, they failed to show concrete continual quality improvement (CQI). Hence, the authors have developed an assessment method, which is more holistic to assess the cognitive, affective, and psychomotor behaviors individually. Results: It is expected that the proposed method will allow one to objectively evaluate whether the students have achieved the criteria, subsequently facilitating CQI implementation within the program and produce qualifi ed graduates.
Conclusion:The proposed assessment method for learning domains will encourage readers to use reliable and valid assessments in higher education by discriminating between assessing skills, knowledge, and attitudes. This paper will inspire its readers to enhance association of teaching and learning. Application: Though, the examples used in the proposed method are taken from engineering education, this proposed assessment method can be applied to any higher education programs in medical, pharmaceutical technology, physiotherapy, bio-technology, etc.
A biogeography-based optimization (BBO) algorithm was used for tuning the parameters of a proportional integral derivative (PID) controller-based power system stabilizer (PSS). The proposed method minimizes the low frequency electromechanical oscillations (0.1-2.5 Hz) and enhances the stability of the power system by optimally tuning the PID parameters. This was achieved by minimizing the objective function of the integral square error for various disturbances. The performance of the BBO algorithm was tested on a single machine infinite bus system for a different range of operating conditions and the results were compared with particle swam optimization, adaptation law, and conventional PSS. The result analysis concluded that the BBO algorithm damps out the low frequency oscillations in the rotor of the synchronous machine effectively when compared to other methods. The algorithms were simulated with MATLAB/Simulink. The results from the simulation showed that the proposed controller yields a fast convergence rate and better dynamic performance.
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