The use of virtual learning environments to aid teaching of heat transfer and Artificial Neural Network modelling in Bioprocess Engineering
Brian Freeland, Sumsun Naher, Greg Foley and Dermot Brabazon
School of Mechanical and manufacturing Engineering &
School of Biotechnology, Dublin City University, Ireland.
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Paper Type: Practitioner
Keywords: Virtual instruments, engineering laboratory practicals, labview, artificial neural networks.
Abstract
High quality laboratory practical’s for undergraduate students require extensive demonstrator resources to implement on a week to week basis. This can be difficult to maintain over the course of a semester. This paper presents work in which an alternative technique to the traditional approach was developed. A virtual learning environment was employed to implement the entire lab, reducing demonstrator involvement and ensuring a constant quality of explanation and demonstration of concepts was provided to each group of students. This new laboratory practical was developed to demonstrate heat transfer and artificial neural network modelling to bio process engineering students. The use of this virtual environment approach allowed the inclusion of the application of industrial process monitoring and data acquisition in the teaching process. A full user interface was constructed that the students navigate through; this interface guided students through the entire lab, teaching heat transfer and artificial neural network concepts along with the general data collection and machine setup procedures. The virtual environment was constructed, with students learning styles in mind, providing information in both a global and sequential manner. This approach was seen to useful in terms of enabling student engagement.
National Instruments LabView software was selected as the programming environment as it allowed easy integration with data acquisition and analysis with high quality graphical user interfaces. This work shows how it is possible to attain low cost multifunctional data acquisition and device control to develop educational resources. Safety features were inbuilt into the program to ensure students could not damage the heat transfer rig, or injure themselves from the rig overheating, or malfunctioning. Trajan was used to simulate the artificial neural network models. The lab practical has been run quite efficiently over the course of the semester and it was seen that the use of a virtual learning environment engages the students more than traditional techniques, reduced the demonstrator workload, and provided increased student interactivity with industrial equipment. Evidence of this is presented in student and staff surveys as well as student learning outcome results.
1 Introduction
Interest in teaching techniques for engineering has increased over the years. There is constant work being carried out in researching how best to present classical theories to students. There is an aim to try and match their learning styles with teaching styles and questions have been posed of how best universities can equip students for industry. More and more practical based teaching method are employed either using virtual laboratories [2] or using full laboratory practical’s [3]. In Biotechnology and the processing industries the requirement for graduates to be able to problem solve and work with processing equipment is critical. Therefore, hands-on experience on processing equipment during their undergraduate studies is a requirement. To this end the BSc degree program in Biotechnology in Dublin City University offers a considerable amount of its teaching time to laboratory practicals. However due to resource restrictions it is not practical to offer undergraduate students full access to the schools bioreactors. It was decided to develop a new third year engineering laboratory to teach heat transfer and artificial neural networks while demonstrating the use of bio processing equipment to biotechnology students. This new laboratory utilises a virtual learning environment that can integrate with low cost data acquisition and control equipment to offer a hands on fully interactive computer program and lab equipment driven practical.
The aim of teaching through the use of a virtual environment was to provide a visual based lab that would reflect the systems in use in industry while also offering a consistent and quality teaching platform that would guide students sequentially through the lab using a custom built user interface. It was expected that using a graphical user interface should reduce the require demonstrator involvement, while providing experience with industrial specification user interfaces.
1.1 Student assessment
In order to assess the learning styles of a significant sample of the Biotechnology student population, the 2nd year students were given Fielders learning styles questionnaire [4]. The outcome of this questionnaire would be used to evaluate the type of teaching that best suits biotechnology students. The survey was conducted by 86% of the total class. The survey results showed that 80% of student’s surveyed are strongly visual learners, i.e. they learn better by reading charts and diagrams to explain concepts rather than presented in a verbal manner. Most of students are balanced between sequential and global, meaning that they like to be presented the full picture of concepts at the start of a lesson and then, introduced to the concept piece by piece. 75% of the class are active learners, with the rest balanced and a small percentage reflective. Its surprising that some students are reflective as studies have show that the engineering and science students are heavily active based learners rather than reflective.
Figure 1: BT2 Visual/Verbal learning style
Figure 2: BT2 Sequential/Global learning style
Figure 3: BT2 Active/Reflective learning style
Figure 4: BT2 Sensing/Intuitive learning style
From the results of the fielder surveys it can be determined that laboratory practical’s and teaching using problem based learning, are techniques that would best suit, biotechnology students. These results also ties in well with general engineering students, who have been seen to be more active and visual learners [5]. As a result of these surveys, the new laboratory practical was designed to provide information in a sequential manner, using a lot of visual aids to explain the main concepts. Students should have a lot of input into the practical, and have a sense of ownership over the practical and their work, this was seen to be a beneficial motivating factor with the design and build heat exchanger project in previous years [6].
2. Implementation
Labview was chosen for the user interface, data acquisition and machine control programming environment because of its straight forward integration with data acquisition equipment and its easy to use graphical user interface. It utilises a graphical programming language using icons rather than calling text. It operates in parallel rather than sequentially this offers operational speed advantages as functions can execute as soon all their terminals have received information. Programs developed in Labview are called vi’s or “virtual instruments”.
2.1 Bioreactor operation
The completed rig seen in Figure 6 is composed of a stainless steel jacketed vessel (1), agitator (2), coolant tank (3), coolant pump (4), thermocouples (5a), coolant flow meter (5b), tachometer (5c) and ancillary pipe fittings.
Figure 6: Completed Rig
The pump, valves and agitation speed can be set manually by the students, from the instruction given in the laboratory interface, for safety reasons the steam lines are automatically controlled by the program. A low cost national instruments multifunction data acquisition card (USB 6008) interfaces with the sensors and controls the steam valves. A low cost RS232 Pico Technology thermocouple data logger relays temperature readings to the computer. Both devices integrated seamlessly into the labview programming environment and provided reliable information and control of the equipment. All the process variables; coolant flow rate, agitation speed, process fluid bulk temperature and coolant jacket input temperature were monitored and recorded automatically. These variables along with calculated values are automatically stored into a .txt file for analysis. While designing the bioreactor and labview program there was a lot of thought given to allowing students “hands on” access to as much of the equipment as possible. This was made possible by writing “fail safe” systems into the labview program.
2.2 Lab structure
The laboratory practical is run over a full day every week in semester 2. One group of four students participate each week. The Labview user interface drives the lab, almost all the required information is provided to students via the interface, a small supplementary manual to demonstrate the use of the Trajan neural network simulator software is provided. The basic structure of the lab is as follows;
1. From the main welcome screen, students can study the relevant theory.
2. The rig operation is guided through in a sequential manner.
3. Heat transfer experiments are performed for varying process parameters (selected by the students).
4. The experimental results can be reviewed via an “Analysis screen”, students perform heat transfer calculations.
5. The experimental data gained by the students is automatically added to previous groups collected data. This is then exported to Trajan artificial neural network simulation software.
6. An appropriate artificial neural network model is generated by the students, based on the theory provided to them earlier.
7. Instead of a laboratory report the students filled in a workbook. This was used along with an online version of the virtual environment as study for a laboratory exam given at the end of semester.
2.3 Virtual environment implementation
The lab is started from the welcome screen in the labview interface; all options can be accessed from there, except the ANN model development, which uses Trajan neural network simulator software. The students are offered all relevant theory, to aid the global learners and demonstrated the rigs operation in a sequential manner. Screen shot of various parts of the program can be seen in the following figures. An emphasise was placed on making the experimentation screens as close to industrial specification machine status and control displays as possible as seen in figures 9 and 10. This was in keeping with the projects aims to offer students experience with industrial specification industrial equipment. As a whole the Labview programming environment proved a straight forward platform to produce a high quality interactive user interface. The finished executable program and code can be downloaded from the web [9].
Figure 7: Welcome Screen
Figure 8: Theory
Figure 9: Rig operation and current state
Figure 10: Data Analysis
3. Results
The exams are currently being graded and will be displayed in the presentation. Using the virtual learning environment dramatically reduced the demonstrator’s workload, as students were guided through every aspect of the practical. All student groups were able to successfully navigate the program and set up the bioreactor using the step by step instructions. Students were able to grasp a complicated subject matter such as Artificial neural networks within a single day’s demonstration, and they seemed genuinely enthusiastic about using a different, more “Hi-tec” learning technique. Based on the success of this project, it has been decided to develop more virtual learning environment based laboratory practicals.
References
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