A learning methodology using Matlab/Simulink for undergraduate electrical engineering courses attending to learner satisfaction outcomes

Learner-centred approaches follow the prevailing tendency in modern University reforms which are primarily concerned about “how people learn”. The methodologies can be learner-centred in the sense of placing the student as the main actor of the teaching–learning process by increasing his interactivity and participation, but also considering what is relevant for the student by measuring the learner satisfaction. In order to promote both aspects, this paper proposes a synchronous software-based active methodology that makes use of the simulations to show a virtual scenario to the students and challenge them to predict and discuss the evolution of the scenario. The proposed methodology improves the visual interface, promotes discussion both among students and with the teacher in a brainstorming stage and shows real-world examples. This software-based methodology has been implemented into an Electric Machinery course at the University of Seville (Spain), and the evaluation has been carried out considering both the affective and cognitive domains. Principal components analysis proves to be useful to highlight the dimensions with a higher influence on learner satisfaction and the affective and cognitive results confirm the successful implementation of the proposal.     

Characteristics of learning computer-controlled mechanisms by teachers and students in a common laboratory environment

Growing popularity of robotics education motivates developing its didactics and studying it in teacher training programs. This paper presents a study conducted in the Department of Education in Technology and Science, Technion, in which university students and school pupils cope with robotics challenges of designing, building and operating computer-controlled mechanisms. The university students were involved in developing robot prototypes and related instructional materials, and assisted in teaching robotics and guiding projects to middle school and high school pupils. The study focused on behaviors of the two groups of learners and aimed to elicit and analyze typical characteristics of learning in the developed robotics environment. We collected qualitative data on learning through robot design and experimentation activities and, by means of the ground theory method, elicited and analyzed typical behavioral characteristics of students’ and pupils’ learning: self-confidence, help, collaboration, interest, seriousness, self-dependence, learning effort, responsibility, coping with learning pressure, learning through observation, and perseverance. As found, the behavior characteristics evolve in the course of robotics studies and their evolution can give indication on the development of the desired competences.     

Evaluating students with online testing modules in engineering economics: A comparision of student performance with online testing and with traditional assessments

Abstract

Engineering economics courses often require students to take time-constrained, in-class exams in which they solve problems by hand, possibly referring to interest rate tables. Many students rely on partial credit to successfully pass exams. Outside of the classroom, professionals rely on computers to solve engineering economics problems, which raises the question of whether engineering economics courses are correctly assessing student performance. This article describes the study of a large engineering economics class using a non-conventional testing method. Student performance was evaluated using online testing modules with a stringent passing criterion, and the tests could be taken multiple times. The questions for each testing attempt were pulled from a database so that students received a new question every time. We compare the performance of students who were assessed using traditional methods with the performance of students assessed with these online testing modules. Our analysis shows that, overall, students who were assessed using the online testing modules earned better grades than students who were assessed via traditional methods. The analysis also discusses several benefits and drawbacks to using online assessments compared with traditional methods. The online assessment method could be useful in large engineering courses that are formula-based.     

A hybrid PSO algorithm for a multi-objective assembly line balancing problem with flexible operation times,sequence-dependent setup times and learning effect

This paper addresses multi-objective (MO) optimization of a single-model assembly line balancing problem (ALBP) where the operation times of tasks are unknown variables and the only known information is the lower and upper bounds for operation time of each task. Three objectives are simultaneously considered as follows: (1) minimizing the cycle time, (2) minimizing the total equipment cost, and (3) minimizing the smoothness index. In order to reflect the real industrial settings adequately, it is assumed that the task time is dependent on worker(s) (or machine(s)) learning for the same or similar activity and sequence-dependent setup time exists between tasks. Finding an optimal solution for this complicated problem especially for large-sized problems in reasonable computational time is cumbersome. Therefore, we propose a new solution method based on the combination of particle swarm optimization (PSO) algorithm with variable neighborhood search (VNS) to solve the problem. The performance of the proposed hybrid algorithm is examined over several test problems in terms of solution quality and running time. Comparison with an existing multi-objective evolutionary computation method in the literature shows the superior efficiency of our proposed PSO/VNS algorithm.