Assessment of Student Program Outcomes through a Comprehensive Exit Strategy

AbstractChoosing methods to assess student program outcomes is a matter of balancing best practices against the constraints imposed by the respective education authorities mainly the Engineering Accreditation Council (EAC) for engineering degrees offered by institutions of higher education in Malaysia. Methods that directly measure student learning and yield the most rigorous results are usually the most time consuming and may require the expertise of educational researchers or outside consultants. Currently, the Department of Electrical, Electronics and Systems Engineering at UKM use their classroom and existing grading practices to collect data that will contribute to assess student learning directly, but this requires extra time and effort. In addition, mechanisms to adequately report the findings need to be properly implemented. Another mechanism that could be used to assess student program outcomes is through a thoroughly designed student exit strategy. The exit strategy implemented this academic year involves two parts; exit survey and exit test. This is a Continuous Quality Improvement (CQI) effort done since the past two academic years that enables the department to assess student program outcomes directly and indirectly in one approach. The exit strategy has proven successful as a valid measurement of student program outcomes. The exit strategy which combines both direct and indirect assessment forms a comprehensive and robust tool to effectively measure student program outcomes

Faculty of Engineering and Built Environment Academicians’ Actual Hours of Workload

AbstractThis paper presents the results of a study on the actual notional hours of workload for academicians at the Faculty of Engineering and Built Environment (FKAB) of University Kebangsaan Malaysia. The study is aimed at ascertaining the hours allocated for teaching, supervising postgraduate and undergraduate students, conducting research, publishing, attending conference, providing consultation as well as public services. The study involved 29 academicians comprising Professors, Associate Professors, and lecturer (with and without PhD) from all five departments namely Mechanical and Materials Engineering, Electrical, Electronics and Systems Engineering, Civil and Structural Engineering, Chemical and Process Engineering and Architecture. The time allocated by each respondent for teaching:research:services is compared to the percentage agreed in the academicians Performance Assessment Report (LNP), that is 30%:60%:10%. Results from the study indicated that 62.1% of the respondents devoted 40hours more than the designated time per week. This issue is critical and has to be rectified in a systematic and strategic manne

Automatic clustering of generalized regression neural network by similarity index based fuzzy c-means clustering

In general regression neural networks (GRNN), one drawback is that the number of training vectors is proportional to the number of hidden nodes, thus a large number of training vectors produce a larger architecture, which is a major disadvantage for many applications. In this paper we proposed an efficient clustering technique referred to as 'similarity index fuzzy c-means clustering'. This technique uses the conventional fuzzy c-means clustering preceded by a technique based on similarity indexing to automatically cluster input data which are relevant to the system. The technique employs a one-pass similarity measures on the data to calculate the similarity index. This index indicates the degree of similarity in which data is clustered. Similar data then undergoes fuzzy c-means iterative process to determine their cluster centers. We applied the technique for system identification and modeling and found the results to be encouraging and efficient. This algorithm offers better performance than conventional algorithm which using energy only. The vocabulary for the experiment includes English digit from 1 to 9. These experimental results were conducted by 360 utterances from a male speaker. Experimental results show that the accuracy of the algorithm is quite acceptable

Keberkesanan kaedah pengukuran dan penilaian hasil pembelajaran- hasil program (CO-PO)

Pembelajaran Berasaskan Hasil (PBH) merupakan satu pendekatan menyeluruh bagi mengurus dan mengendalikan proses pengajaran dan pembelajaran yang fokusnya adalah untuk menghasilkan pelajar yang berjaya mendemonstrasikan hasil pembelajaran dengan berkesan. Penilaian dan pengukuran ialah dua aspek penting dan dititikberatkan dalam PBH bagi memastikan hasil pembelajaran kursus (CO) dan seterusnya hasil program (PO) dicapai. Justeru, satu kaedah yang menggabungkan dua kaedah penilaian langsung dan tidak langsung telah dibangunkan untuk tujuan tersebut. Kaedah tidak langsung dikenali sebagai Penilaian Kendiri Pelajar (PKP) dan kaedah langsung merupakan kaedah penilaian summatif yang menggunakan gred akhir (GA). PKP adalah sebuah instrumen untuk menilai pencapaian pelajar secara kendiri berdasarkan sasaran CO yang telah digariskan dalam setiap kursus. Di Jabatan Kejuruteraan Elektrik, Elektronik dan Sistem, PKP telah digunakan untuk mengukur pencapaian CO secara tidak langsung dan seterusnya dikaitkan dengan pencapaian hasil program (PO). Kertas kerja ini bertujuan mengkaji keberkesanan instrumen PKP serta pencapaian GA sebagai kaedah mengukur pencapaian CO-PO. Tujuh kursus yang ditawarkan pada Semester 2 Sesi 2008/2009 telah dipilih secara rawak untuk tujuan kajian. Analisis maklum balas PKP serta perbandingan dengan GA menunjukkan kaedah ini adalah kurang sesuai untuk mengukur dan menilai pencapaian CO-PO. Walau bagaimanapun, gabungan kedua-duanya didapati sesuai untuk memantau dan menilai pengendalian sesuatu kursus di mana perbezaan besar (>10%) antara keputusan PKP akhir dengan GA boleh dijadikan sebagai petunjuk keperluan melakukan penambahbaikan terhadap pengendalian kursus tersebut. Kesimpulannya, satu penambahbaikan diperlukan untuk memastikan CO-PO dapat diukur dan dinilai secara lebih objektif dan langsung

Direct model reference adaptive controller based-on neural-fuzzy techniques for nonlinear dynamical systems

This paper presents a direct neural-fuzzy-based Model Reference Adaptive Controller (MRAC) for nonlinear dynamical systems with unknown parameters. The two-phase learning is implemented to perform structure identification and parameter estimation for the controller. In the first phase, similarity index-based fuzzy c-means clustering technique extracts the fuzzy rules in the premise part for the neural-fuzzy controller. This technique enables the recruitment of rule parameters in accordance to the number of clusters and kernel centers it automatically generated. In the second phase, the parameters of the controller are directly tuned from the training data via the tracking error. The consequent parts of the rules are thus determined. This iterative process employs Radial Basis Function Neural Network (RBFNN) structure with a reference model to provide a closed-loop performance feedback

Optimization of N-Channel trench power MOSFET using 2k factorial design method

The main objective of this research is to optimize the trench depth, trench width, epitaxial resistivity and epitaxial thickness in trench power MOSFET so as to obtain high breakdown voltage but low on-resistance. Optimisation of these parameters are based on 2k factorial design method for achieving specific on-resistance 0.1 mΩcm2 and blocking voltage higher than 30 V. ATHENA and ATLAS software from Silvaco Int. were used for fabrication simulation and device electrical characterisation. The results obtained were, the optimisation value for trench width was 1.25 μm, trench depth was 1.25 μm, epitaxial thickness was 4.75 μm and epitaxial resistivity was 0.32 Ωcm. The predictive value of breakdown voltage was 39.41 V and significant to factors trench depth, epitaxial thickness and epitaxial resistivity. The predictive value for on-resistance was 0.105 mΩcm2 with significant to factors trench depth, epitaxial thickness and epitaxial resistivity. In conclusion, 2k factorial design method is successfully utilised in optimizing n-channel trench power MOSFET

A Secure and Robust Compressed Domain Video Steganography for Intra- and Inter-Frames Using Embedding-Based Byte Differencing (EBBD) Scheme.

This paper presents a novel secure and robust steganographic technique in the compressed video domain namely embedding-based byte differencing (EBBD). Unlike most of the current video steganographic techniques which take into account only the intra frames for data embedding, the proposed EBBD technique aims to hide information in both intra and inter frames. The information is embedded into a compressed video by simultaneously manipulating the quantized AC coefficients (AC-QTCs) of luminance components of the frames during MPEG-2 encoding process. Later, during the decoding process, the embedded information can be detected and extracted completely. Furthermore, the EBBD basically deals with two security concepts: data encryption and data concealing. Hence, during the embedding process, secret data is encrypted using the simplified data encryption standard (S-DES) algorithm to provide better security to the implemented system. The security of the method lies in selecting candidate AC-QTCs within each non-overlapping 8 × 8 sub-block using a pseudo random key. Basic performance of this steganographic technique verified through experiments on various existing MPEG-2 encoded videos over a wide range of embedded payload rates. Overall, the experimental results verify the excellent performance of the proposed EBBD with a better trade-off in terms of imperceptibility and payload, as compared with previous techniques while at the same time ensuring minimal bitrate increase and negligible degradation of PSNR values