Khairiyah Mohd-Yusof

Cooperative Problem-Based Learning (CPBL): A practical PBL model for engineering courses

Problem-Based Learning (PBL) is an inductive learning approach that uses a realistic problem as the starting point of learning. Unlike in medical education, which is more easily adaptable to PBL, implementing PBL in engineering courses in the traditional semester system set-up is challenging. While PBL is normally implemented in small groups of up to ten students with a dedicated tutor during PBL sessions in medical education, this is not plausible in engineering education because of the high enrollment and large class sizes. In a typical engineering course, implementation of PBL consisting of students in small groups in medium to large classes is more practical. However, this type of implementation is more difficult to monitor, and thus requires good support and guidance in ensuring commitment and accountability of each student towards learning in his/her group. To provide the required support, Cooperative Learning (CL) is identified to have the much needed elements to develop the small student groups to functional learning teams. Combining both CL and PBL results in a Cooperative Problem-Based Learning (CPBL) model that provides a step by step guide for students to go through the PBL cycle in their teams, according to CL principles. Suitable for implementation in medium to large classes (approximately 40–60 students for one floating facilitator), with small groups consisting of 3–5 students, the CPBL model is designed to develop the students in the whole class into a learning community. This paper provides a detailed description of the CPBL model. A sample implementation in a third year Chemical Engineering course, Process Control and Dynamics, is also described.

Comparison of melt flow index of propylene polymerisation in loop reactors using first principles and artificial neural network models

The inability to measure product quality in polymerisation industries on-line causes major difficulties. There are no on-line instruments to measure resin characteristics that define polymer quality, such as melt flow index (MFI) and density. MFI always often have to be evaluated in a time consuming and manpower intensive lab analysis. In most plants, MFI is measured only several times a day using a manual analytical test. An on-line MFI measurement is essential in fulfilling customer requirements and preventing losses. This paper presents models for soft sensors to measure MFI in industrial polypropylene loop reactors using first principle (FP) model and artificial neural network (ANN) model. For the FP model, two industrial interconnected loop reactors for propylene polymerisation are modelled as two continuous stirred tank reactors (CSTRs) in series. The mathematical models of nonlinear differential equations which describe the polymerisation process were solved numerically. The ANN model of the two loop reactors are developed by employing the concept of Feed- Forward Back Propagation (FFBP) network architecture using Levenberg-Marquardt training method. The ANN model act as estimator to predict the polymer MFI. Both models are developed and simulated in MATLAB. The simulation results of the MFI between FPM and ANN model are compared and analysed. The prediction of the ANN model is found to be more accurate compare to the MFI calculated by the FP model. The ANN model prediction is good within the range of training data. The CPU time recorded that ANN model is much faster than FP model.

Sustaining Change for PBL at the Course Level

Problem based learning (PBL) has always been acknowledged as a powerful approach to develop students’ learning, professional skills, and positive attitudes (Mohd-Yusof et al., 2016; Duderstadt, 2008; Strobel, 2007; Polanco, Claderon, & Delgado, 2001; Woods et al., 2000; Barrows & Tamblyn, 1980). However, being highly student-centred, it is seen to be more difficult to implement compared to other active learning approaches. The need for proper planning and preparation also renders PBL to be difficult to sustain, especially in the absence of institutional support, acknowledgement, and reward.

Web 2.0 applications for engineering education: Faculty members’ perception, barriers, and solutions

Despite increasing the number of engineering departments and students in Iran, the quality of education is less than satisfactory. Regarding the huge potential of Web 2.0 applications, which is also known as Web 2.0 tools, Web 2.0 services, or social media, for improving the quality of teaching and learning, this study was undertaken to investigate the perception of the faculty members toward using these technologies for teaching and learning engineering, the ways they use these tools for educational aims, and the factors that influence. The systematic design of grounded theory method was followed to achieve the research objectives. In addition, the required data was collected through interview and questionnaire and NVivo 8 software was used to facilitate data analysis process. The results show that the faculty members use some of these applications occasionally for the sole purpose of obtaining information. The traditional teaching method, which is influenced by the instructors’ traditional mindset, traditional curricula, and organizational disregard for the quality of teaching, are the most salient factors. Also, instructors’ emotional barriers and limited access to these tools in Iran are subsidiary factors influencing the failure to use these tools for teaching engineering.

Analyzsing Qualitative Data Systematically Using Thematic Analysis for Deodorizer Troubleshooting in Palm Oil Refining

Troubleshooting the deodoriser in palm oil refining is challenging because of complex design of vacuum system. Not all the required information to develop a good troubleshooting system can be obtained from documents and the literature. A mistake in corrective action may cause failure in plant operation and final oil quality. Since experienced plant workers have in-depth knowledge on the specific equipment and process that they are in-charge of, systematic knowledge acquisition from them can be used to develop a fuzzy logic- based troubleshooting system. This system can help other less experienced staff in identifying root cause of deodoriser failure before taking any corrective action. The qualitative data obtained from interviewing the plant experts must be analysed systematically to ensure that the information obtained are trustworthy. Therefore, this study implemented thematic analysis to sort knowledge based on a theme of the root cause of deodoriser failure. The thematic analysis consists of 5 steps, which are data familiarisation, code generation, theme searching, reviewing and description. Fifteen plant workers (includes engineer, supervisor, technician and operators) were interviewed to develop themes. The useful information is captured from the interview session through code generation. Two senior managers verified the final themes, and the theme is further described based on the theoretical knowledge and process description. The final themes presented as thematic tree provide fault propagation, while troubleshooting table has information on root cause and its necessary action. The main themes presented the root cause of deodoriser failure based on critical location, i.e. ejector. The documented thematic analysis can assist inexperienced workers to learn the prior knowledge of deodoriser failure sources from troubleshooting table and thematic tree.

Characteristics of Student Centred Learning from the Perspective of Engineering Lecturers

Student Centred Learning (SCL) approach is recommended worldwide in higher education. However, many engineering educators are reluctant to shift from teacher-centred to SCL approach because they perceive that effective teaching must heavily involve lectures and knowledge must be transmitted to the learners by the lecturer. This research seeks to identify engineering lecturers’ perspective on the characteristics of meaningful learning. The characteristics are compared to SCL characteristics as outlined by the How People Learn framework. Using data collected among engineering lecturers over two years at the beginning of training workshops on SCL conducted in various universities throughout Malaysia, the data is analyzed qualitatively using thematic analysis. The results show the positive characteristics mentioned are SCL-related approaches, proving that SCL is a relevant teaching and learning approach in engineering because it is not only recommended by experts but also concurred by engineering lecturers when seen from their own learning perspective.

Motivating Engineering Students to Engage in Learning Computer Programming

Motivation is essential for successful engagement in learning. This factor is especially important in courses that are considered difficult and require high cognitive engagement such as computer programming. One of the approaches to motivate engineering students in learning is to create an effective learning environment. This paper presents a qualitative study on undergraduate engineering students’ motivation towards learning programming based on the How People Learn (HPL) framework. The HPL framework comprises of elements that can be considered by instructors to design an effective learning environment. The methods designed for this study are observations and interviews while thematic analysis is employed in analysing the data. Findings based on lenses of the HPL framework are presented. Several recommendations for improving the learning environment are summarized as part of the outcomes of the study.