Category Archives: Education

On the use of flipped classroom for control engineering classes and its problem with the required (longer) time for learning

Y. Kim and C. Ahn, Effect of Combined Use of Flipped Learning and Inquiry-Based Learning on a System Modeling and Control Course, IEEE Transactions on Education, vol. 61, no. 2, pp. 136-142, DOI: 10.1109/TE.2017.2774194.

Contribution: This paper illustrates how to design and implement curricula in terms of the combined use of flipped learning and inquiry-based learning in an engineering course. Background: Elementary courses in engineering schools are conventional and foundational, and involve a considerable amount of knowledge. Throughout such courses, students are also expected to develop insight, which cannot be obtained by only listening to instructors. Having relevant discussions is also difficult for most instructors. Intended Outcomes: The combined use of flipped learning and inquiry-based learning would be beneficial to broaden student achievement. Application Design: Based on an epistemological approach about knowledge and knowing, this paper applies the combined use of flipped learning and inquiry-based learning to enhance student knowledge and advance ways of thinking on a System Modeling and Control course. Findings: The extended learning time and the collective responsibility for learning are discussed as critical issues in applying the combined use of flipped learning and inquiry-based learning in an engineering school.

Interesting study about the concepts to be taught in control system engineering

R. M. Reck, Common Learning Objectives for Undergraduate Control Systems Laboratories,IEEE Transactions on Education, vol. 60, no. 4, pp. 257-264, DOI: 10.1109/TE.2017.2681624.

Course objectives, like research objectives and product requirements, help provide clarity and direction for faculty and students. Unfortunately, course and laboratory objectives are not always clearly stated. Without a clear set of objectives, it can be hard to design a learning experience and determine whether students are achieving the intended outcomes of the course or laboratory. In this paper, a common set of laboratory objectives, concepts, and components of a laboratory apparatus for undergraduate control systems laboratories were identified. A panel of 40 control systems faculty members completed a multi-round Delphi survey to bring them toward consensus on the common aspects of their laboratories. These panelists identified 15 laboratory objectives, 26 concepts, and 15 components common to their laboratories. Then an 45 additional faculty members and practitioners completed a follow-up survey to gather feedback on the results. In both surveys, each participant rated the importance of each item. While average ratings differed slightly between the two groups, the order in which the items were ranked was similar. Important examples of common learning objectives include connecting theory to what is implemented in the laboratory, designing controllers, and modeling systems. The most common component in both groups was MathWorks software. Some of the common concepts include block diagrams, stability, and PID control. Defining common aspects of undergraduate control systems laboratories enables common development, detailed comparisons, and simplified adaptation of equipment and experiments between campuses and programs.

An interesting simulation educational software for control systems engineering based on controlling a quadrotor

S. Khan, M. H. Jaffery, A. Hanif and M. R. Asif, Teaching Tool for a Control Systems Laboratory Using a Quadrotor as a Plant in MATLAB, IEEE Transactions on Education, vol. 60, no. 4, pp. 249-256, DOI: 10.1109/TE.2017.2653762.

This paper presents a MATLAB-based application to teach the guidance, navigation, and control concepts of a quadrotor to undergraduate students, using a graphical user interface (GUI) and 3-D animations. The Simulink quadrotor model is controlled by a proportional integral derivative controller and a linear quadratic regulator controller. The GUI layout’s many components can be easily programmed to perform various experiments by considering the simulation of the quadrotor as a plant; it incorporates control systems (CS) fundamentals such as time domain response, transfer function and state-space form, pole-zero location, root locus, frequency domain response, steady-state error, position and disturbance response, controller design and tuning, unity, and the use of a Kalman filter as a feedback sensor. 3-D animations are used to display the quadrotor flying in any given condition selected by the user. For each simulation, users can view the output response in the form of 3-D animations, and can run time plots. The quadrotor educational tool (QET) helps students in the CS laboratory understand basic CS concepts. The QET was evaluated based on student feedback, grades, satisfaction, and interest in CS.

Modelling the implicit complexity of problem solving in exams

A. Shoufan, “Toward Modeling the Intrinsic Complexity of Test Problems,” in IEEE Transactions on Education, vol. 60, no. 2, pp. 157-163, May 2017.
DOI: 10.1109/TE.2016.2611666.

The concept of intrinsic complexity explains why different problems of the same type, tackled by the same problem solver, can require different times to solve and yield solutions of different quality. This paper proposes a general four-step approach that can be used to establish a model for the intrinsic complexity of a problem class in terms of solving time. Such a model allows prediction of the time to solve new problems in the same class and helps instructors develop more reliable test problems. A complexity model, furthermore, enhances understanding of the problem and can point to new aspects interesting for education and research. Students can use complexity models to assess and improve their learning level. The approach is explained using the K-map minimization problem as a case study. The implications of this research for other problems in electrical and computer engineering education are highlighted. An important aim of this paper is to stimulate future research in this area. An ideal outcome of such research is to provide complexity models for many, or even all, relevant problem classes in various electrical and computer engineering courses.

Personalizing the assessments generated automatically for students in order to minimize plagiarism: the case of programming

S. Manoharan, “Personalized Assessment as a Means to Mitigate Plagiarism,” in IEEE Transactions on Education, vol. 60, no. 2, pp. 112-119, May 2017.
DOI: 10.1109/TE.2016.2604210.

Although every educational institution has a code of academic honesty, they still encounter incidents of plagiarism. These are difficult and time-consuming to detect and deal with. This paper explores the use of personalized assessments with the goal of reducing incidents of plagiarism, proposing a personalized assessment software framework through which each student receives a unique problem set. The framework not only auto-generates the problem set but also auto-marks the solutions when submitted. The experience of using this framework is discussed, from the perspective of both students and staff, particularly with respect to its ability to mitigate plagiarism. A comparison of personalized and traditional assignments in the same class confirms that the former had far fewer observed plagiarism incidents. Although personalized assessment may not be cost-effective in all courses (such as language courses), it still can be effective in areas such as mathematics, engineering, science, and computing. This paper concludes that personalized assessment is a promising approach to counter plagiarism.

A method to predict the grading of students during a course

Yannick Meier, Jie Xu, Onur Atan, and Mihaela van der Schaar, Predicting Grades, in IEEE Transactions on Signal Processing , vol.64, no.4, pp.959-972, Feb.15, 2016, DOI: 10.1109/TSP.2015.2496278.

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To increase efficacy in traditional classroom courses as well as in Massive Open Online Courses (MOOCs), automated systems supporting the instructor are needed. One important problem is to automatically detect students that are going to do poorly in a course early enough to be able to take remedial actions. Existing grade prediction systems focus on maximizing the accuracy of the prediction while overseeing the importance of issuing timely and personalized predictions. This paper proposes an algorithm that predicts the final grade of each student in a class. It issues a prediction for each student individually, when the expected accuracy of the prediction is sufficient. The algorithm learns online what is the optimal prediction and time to issue a prediction based on past history of students’ performance in a course. We derive a confidence estimate for the prediction accuracy and demonstrate the performance of our algorithm on a dataset obtained based on the performance of approximately 700 UCLA undergraduate students who have taken an introductory digital signal processing over the past seven years. We demonstrate that for 85% of the students we can predict with 76% accuracy whether they are going do well or poorly in the class after the fourth course week. Using data obtained from a pilot course, our methodology suggests that it is effective to perform early in-class assessments such as quizzes, which result in timely performance prediction for each student, thereby enabling timely interventions by the instructor (at the student or class level) when necessary.

What students value the most in an engineering lab (and some related work on laboratory practices)

Nikolic, S.; Ritz, C.; Vial, P.J.; Ros, M.; Stirling, D., Decoding Student Satisfaction: How to Manage and Improve the Laboratory Experience, in Education, IEEE Transactions on , vol.58, no.3, pp.151-158, Aug. 2015, DOI: 10.1109/TE.2014.2346474

The laboratory plays an important role in teaching engineering skills. An Electrical Engineering department at an Australian University implemented a reform to monitor and improve student satisfaction with the teaching laboratories. A Laboratory Manager was employed to oversee the quality of 27 courses containing instructional laboratories. Student satisfaction surveys were carried out on all relevant laboratories every year, and the data were used for continuous improvement. This paper will investigate the reforms that were implemented and outline a number of the improvements made. It also examines the program’s overall impact on: (1) overall satisfaction; (2) laboratory notes; (3) learning experiences; (4) computer facilities; (5) engineering equipment; and (6) condition of the laboratory. Student satisfaction with the laboratories increased by 32% between 2007 and 2013. The results show that the laboratory notes (activity and clarity) and the quality of the equipment used are among the most influential factors on student satisfaction. In particular, it is important to have notes or resources that explain in some detail how to use and troubleshoot equipment and software used in the laboratory.

Demonstration that students benefit from using colors while teaching electrical circuit analysis

Reisslein, J.; Johnson, A.M.; Reisslein, M., (2015), Color Coding of Circuit Quantities in Introductory Circuit Analysis Instruction, Education, IEEE Transactions on , vol.58, no.1, pp.7,14, DOI: 10.1109/TE.2014.2312674

Learning the analysis of electrical circuits represented by circuit diagrams is often challenging for novice students. An open research question in electrical circuit analysis instruction is whether color coding of the mathematical symbols (variables) that denote electrical quantities can improve circuit analysis learning. The present study compared two groups of high school students undergoing their first introductory learning of electrical circuit analysis. One group learned with circuit variables in black font. The other group learned with colored circuit variables, with blue font indicating variables related to voltage, red font indicating those related to current, and black font indicating those related to resistance. The color group achieved significantly higher post-test scores, gave higher ratings for liking the instruction and finding it helpful, and had lower ratings of cognitive load than the black-font group. These results indicate that color coding of the notations for quantities in electrical circuit diagrams aids the circuit analysis learning of novice students.