Chasing Higher Solar Cell Efficiencies - IEEE Xplore Digital Library

Chasing Higher Solar Cell Efficiencies Engaging Students in Learning how Solar Cells are Manufactured Dr Alison Lennon

Dr Malcolm Abbott and Dr Keith McIntosh

School of Photovoltaic and Renewable Energy Engineering UNSW Sydney, NSW, Australia [email protected]

PV Lighthouse Coledale, NSW, Australia

Abstract— Education and training of engineers to support the growth of new and rapidly evolving technologies represents a challenge for tertiary education institutions. Cloud-based learning resources enable rapid updating of information, selfpaced learning and do not require classroom attendance. However, the completion rate of massive open on-line courses is low demonstrating the challenge of making these resources engaging. We report here the use of a cloud-based simulation that used the game elements of personal performance tracking and leaderboards to engage tertiary students in their learning of how silicon solar cells are produced in a manufacturing environment. The simulation was used in a blended mode where students participated in classroom activities comprising lectures and tutorials, and on-line simulations. Initial findings suggest that the game elements were engaging for many in the on-campus group, however further studies are required to ensure that effective learning occurs and to evaluate the relative engagement from different student cohorts.

the use of corrosive chemicals (e.g., hydrofluoric acid) and a clean environment to ensure cells of sufficient efficiency. These factors present challenges for the training of engineers as many manufacturers are often not receptive to having student groups visiting their production lines or working in short-term internships. Additionally, many manufacturing facilities are located remote from the educational institutions which have developed research expertise and educational programs in silicon PV.

Keywords—gamification; blended learning; manufacturing; photovoltaic engineering

education;

I. INTRODUCTION The use of renewable resources for the generation of electrical power is essential for sustainable development. The energy of sunlight can be harvested by photovoltaics and, during the last fifty years, energy conversion devices fabricated on crystalline silicon wafers have transitioned from laboratory experiments to cover rooftops world-wide. The continued learning from increased manufacturing volume has resulted in silicon photovoltaic-generated electricity prices being comparable to those for electricity generated from fossil fuels. This is resulting in a rapid increase in manufacturing with the annual production in 2014 of 50 GW expected to grow to ~ 220 GW by 2030 (see Fig. 1). This massive growth in manufacturing necessitates the education and training of engineers, technicians and sales and marketing personnel. The “workhorse” of the silicon photovoltaics manufacturing industry is the screen-printed solar cell. This technology, which dates back to the 1970’s [1], has been continually refined over the years with specialized turnkey line equipment now being readily available to perform many of the steps. The manufacturing process integrates many diverse processes ranging from wet chemical etching, solid state diffusion, plasma physics and screen-printing. In addition to its multidisciplinary nature, the process requires

In this paper we describe the use of a cloud-based simulation with gaming elements to teach people how these cells are manufactured in a way in which students can be engaged, work at their own pace whilst still able to learn the necessary fundamentals. The simulation, which is called “PV Factory” is used in an on-campus blended learning environment where third year engineering students participate in lectures and tutorials, whilst using the simulation to learn about the manufacturing process and develop experience in optimizing silicon PV production lines. As trainee engineers they work in a virtual factory where they fabricate batches of solar cells and learn how to optimize their production process. The efficiency of the produced cells is measured and the virtual engineers compete on a leaderboard for the most efficient batch of solar cells. They can also track their own personal performance through graphs of daily and progressive cell efficiencies.

Fig. 1. Cumulative installed module power calculated with a logistic growth approximation for different regions based on the IEA predictions (from [2]).

978-1-4673-9226-6/15/$31.00 ©2015 IEEE 10-12 December 2015, United International College, Zhuhai, China 2015 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE) Page 267

II. GAMIFICATION IN EDUCATION For many years now, people have enriched their physical lives with a virtual environment in which they are exposed to a wide range of knowledge and develop strategies and problem solving abilities. They mine, build cities, worlds and empires, establish communities and wage wars engineering weapons from a knowledge of the different materials that they have mined. This style of learning is attracting many young people, and researchers are now urging educators to embrace electronic games such as Minecraft as a tool with which to teach maths, design, engineering and geography [3], the game presenting a far more interesting environment than whiteboards staring down at rows of desks. Many studies have explored how electronic games can be used in education. Games can provide immediate feedback, information on demand, self-regulated learning, cyclic development of expertise and team collaboration [4, 5], however concerns have been raised about the quality of educative content, learning transfer, learning assessment and the implications of involving teachers in the medium [6]. So, rather than necessarily embrace games as a way of learning, another approach is to use game elements and game mechanics such as leaderboards, badges and levels in nongame settings in order to increase engagement and motivation. This approach is referred to as “gamification” [7, 8]. Domínguez et al. investigated the use of gamification in e-learning platforms for tertiary students. They found that although leaderboards motivated some students because they saw their achievements instantly recognized by their peers, others reported that the game elements were not sufficiently motivating or that they did not like to compete with their classmates. Domínguez et al. concluded that: (i) the way technology was employed was key to a positive student response; (ii) immediate feedback to participating in game events was critical; and (iii) delays due to teacher assessment could detract from the immediacy of feedback. Educating photovoltaic engineers within a tertiary education institution is challenging due to the difficulty of providing students with a factory floor experience, as described earlier, but also due to the changes that are occurring in higher education institutions. Attendance at lectures has fallen in recent years as students look to use electronically-available resources where possible. Many institutions are exploring the use of Massive Open On-line Courses (MOOCs) that allow students to work at their own pace and location. Whilst there is great enthusiasm by what can be provided by MOOCs, their completion rates have been reported to be as low as 7% [9, 10] highlighting the challenges associated with making the on-line educational experience more engaging. It is proposed here that the use of gaming elements in online simulations can make the learning experience more engaging, and thereby result in more effective learning. Although we describe experiences arising from a blended learning class run on campus, gamified simulations may be able to be embedded in MOOCs thereby eliminating the need for participants in a course to be present at a university

campus in order to effectively complete the requirements of the course. III.

CLOUD-BASED SIMULATION FOR ON-LINE LEARNING

A. Cloud Environment Cloud software is being increasingly used for many applications. It brings many practical benefits, which include version control, ease of software update, software security (e.g., confidential algorithms), monitoring of learning and gaming. From an education perspective there are many positives in this list and already MOOCs are creatively exploring this space using quizzes that adapt to both a single participant’s and a group’s previous responses, group collaborative activities and discussions. The use of on-line simulations extends this suite of learning tools to include gamification, where participants in the simulation can compete with each other in terms of a measurable metric. In the case of PV Factory [11], the selected metric is cell efficiency and users explore how they can change the chemical and physical processes to improve cell efficiency. As they optimise the process the expectation is that they learn what is critical for the optimization of the individual processes. An equally relevant measurable metric would be profitability, as explored by Cotter in his Virtual Manufacturing Execution System (VMES) [12]. Users access PV Factory using a web browser. The software runs on a server ensuring that the simulation algorithms remain secure. To ensure fast response times, some functionality is written in javascript which is automatically downloaded and cached on the user’s browser to minimize the number of requests and the volume of information sent to and from the server via the internet. A further advantage of cloud-based tools for on-line learning is that data can be collected from the class cohort. In the case of on-line simulations, performance and usage data can be collected and used to refine the teaching practices and mode of delivery (see e.g., [11]). B. PV Factory The PV Factory simulation was developed by PV Lighthouse, an Australian company that specializes in providing cloud-based electronic resources for PV scientists and engineers, in collaboration with teaching academics from the School of Photovoltaic and Renewable Energy Engineering at UNSW in Australia. Since 4 January it has been publically available. It has also been used for the teaching of PV Manufacturing courses at both UNSW in Australia and at Arizona State University in the US, with other tertiary educational institutions also now planning to integrate it into their teaching programs. PV Factory attempts to reproduce the manufacturing environment in which a PV engineer would work. There is firstly the Office where the engineer plans his/her work, manages the batches of the cells that have been produced and compares performance with both historical records (see Fig. 2) for their production line and competitors (the “leaderboard”). The trainee engineer can then make batches


of solar cells on the Production Line, choosing the type of silicon wafer and then selecting the parameters for each of the processing steps which are depicted as a sequence of icons (see Fig. 3). He/she can process each batch step by step, characterizing the cells at various stages in the Characterisation Lab. Once the batch of cells has been fabricated, the currentvoltage response of each cell is measured using an IV tester located on the server and the results are presented to the engineer to analyze in order to ascertain the areas in which cell performance can be improved. Current-voltage, quantum efficiency (see Fig. 4), reflectance and doping profiles can be measured on selected cells using the Characterisation Lab. At any time the engineer can use PV Factory’s Library to learn about the different processes. There are very few up-todate text books on silicon PV manufacturing available due to the rapidly-evolving process engineering that has occurred in the last 10 years, so on-line technical resources that can be readily updated are arguably the best way in which to disseminate information. Furthermore, video resources can be used to enhance the learning experience and give trainee engineers a sense of what it is like on a factory floor.

Fig. 2. Example graph of progressive efficiency as a function of the number of batches produced.

Fig. 3. Screen shot showing the steps in the production process, the completed steps indicated by green icons, the current step by red and the remaining steps in blue.

Fig. 4. Quantum efficiency and reflection curve generated by PV Factory for a fabricated cell.

IV. INTEGRATING ON-LINE AND CLASSROOM LEARNING At UNSW, PV Factory has been used as an on-line resource in the teaching of a PV Technology and Manufacturing course which is a core course for 3rd year engineering students in UNSW’s Photovoltaics and Solar Energy undergraduate program. During the 12-week semester, students worked through the steps of making screen-printed solar cells, attending classes which mixed lectures with PV Factory exercises where students learned how to optimize individual steps of the manufacturing process (see Fig. 5). The performance of each of the steps required to fabricate silicon solar cells depends on many parameters. For example, a surface texturing step which is performed to reduce front surface reflection, depends on the concentration of the chemicals used (e.g., potassium hydroxide and isopropanol), the bath temperature, duration of texturing and exhaust rates. It is not immediately obvious to a trainee engineer which of these steps is most critical to the optimal performance of the process. In the class, students learn how to perform multiple factor response curves to determine the relationship between input factors (i.e., process variables) and responses (measured outputs from a process). In the case of the surface texturing example, students can perform a series of simulations where they vary input parameters and use the Characterisation Lab to measure the front surface reflectance. The resulting multiple factor response curve can then help them determine which input factor is the most critical determinant for low front surface reflectance. During the semester, the class worked through each of the process steps shown in Fig. 3. Each week students would undertake a PV Factory activity based on a single process, with each activity being designed around a number of specific learning outcomes. This approach was adopted in order to encourage students to use a systematic approach to optimization. They worked in pairs with the objective of further developing their collaborative skills and performance on the weekly activity was assessed by a short oral quiz under the supervision of teaching staff and PhD student assistants. The course culminated in a final assignment where the class was presented with a production line in a poorly performing state and the students worked in their


groups to improve their production performance. Throughout this exercise the students competed on both the global (all users) and class leaderboard. The incentive to attain the honour of heading the leaderboard spurring students to spend many hours working through the effects of different process parameters and the interrelationships between different processes. V. ROLE OF GAMIFICATION IN PV FACTORY The leaderboard was introduced in PV Factory to reflect the competitive silicon PV manufacturing environment where companies compete for record cell and module efficiencies for branding advantages. The motivation for adding a leaderboard was to engage students in a similar environment where competition between their classmates would encourage them to strive to achieve higher solar cell efficiencies. In 2014 when PV Factory was introduced into the UNSW teaching program, the leaderboard was not available to students during their final assignment. Substantially the same final assignment was set in 2015 but in this case a class leaderboard was available. Although efficiencies on the two assignments cannot be numerically compared because the algorithm was changed between the running of the 2014 and 2015 assignments, Fig. 5 shows that the class distribution of final cell efficiencies (normalized to the maximum efficiency obtained on the assignment) was characterized by a greater clustering of final efficiencies close to the higher limit of the simulation in 2015. This can be interpreted as more students being motivated to continue optimizing their production process because they could see that higher efficiencies were possible. It should be noted that even without the leaderboard, sharing of ideas occurs because the students meet in lectures and tutorials during the teaching semester and so a wider spread of results would be expected if this social interaction was not present in the absence of a leaderboard. Perhaps one of the more interesting observations about the influence of the leaderboard on performance on the simulation exercise was that, although 25% of the students enrolled in the class were female, there was only 1 female student in the top 20 on the leaderboard and none in the top 10. Also some high achieving female students did not appear to engage in the competition electing to process only a couple of hundred batches and being satisfied with a lower final efficiency whereas the male students actively competing on the leaderboard fabricated over 2000 batches of solar cells each in some cases.

VI. EVIDENCE FOR EFFECTIVE LEARNING AND STUDENT ENGAGEMENT It is difficult to provide objective measures of student engagement and effective learning without well-controlled large group studies. Evidence of interest in using PV Factory can be obtained from Google Analytics. Since it was made publically-available on 4 January 2015, 3,354 users (independent devices) from 85 countries have used PV Factory and over 1.2 million virtual solar cells. Combined, these cells would produce 32 MW of (virtual) electric power under ‘one-sun’ conditions. When PV Factory was first integrated into the teaching program at UNSW in 2014 (without a leaderboard), the final assignment was left unchanged from the previous year. Student performance on this assignment was ~ 6% higher when PV Factory was used in place of a very similar simulation which was not deployed on the cloud [11]. This suggests that there was either an increased engagement in the course or that there was improved productivity by using the on-line simulation, which included more comprehensive cell characterisation capabilities. Introduction of a leaderboard during assignments in 2015 has resulted in some students completing many more batches of virtual solar cells than in the previous year, however it is difficult to assess whether this has resulted in more effective learning. Also the leaderboard experience from 2015 is suggesting that male engineering students respond well to the competitive environment spending much more time on the activity than their female peers. This differing response by male and female students needs to be investigated further if gamification is to be used more widely to engage students in more effective learning at tertiary institutions. Although not explored in this study, the blended learning environment may also provide the essential elements of conventional classroom teaching to those students who feel challenged by leaderboard competition between classmates.

Simulation statistics from the 2015 class also suggest that use of a leaderboard does little to engage weaker students and may actually provide a disincentive making those students feeling less adequate. In an informal survey conducted during class before completion of the final assignment in 2015, students were asked why they did not like the leaderboard. Many responded that “they didn’t like it because they weren’t in the top ten”. Fig. 5. Students participating in a PV Factory activity during a classroom exercise at UNSW.


of Photovoltaic and Renewable Energy Engineering and PV Lighthouse. Responsibility for the views, information or advice expressed herein is not accepted by the Australian Government or PV Lighthouse. REFERENCES

Fig. 6. Frequency histogram of average cell efficiencies (normalized to the maximum obtained efficiency) of the optimized production lines from the 2014 assignment (with no leaderboard) and the 2015 assignment (with a leaderboard).

VII. CONCLUSIONS New models for education are required as tertiary education is becoming increasingly international and, especially for science and engineering, having a greater emphasis being placed on practical relevance to industry. New industries can develop very rapidly and so educational institutions need to adapt quickly to the challenges of educating engineers and scientists to support these industries. On-line education is an excellent way in which up-to-date information can be made available to students and trainee engineers, however the challenge is to provide that education in an engaging and effective way. This study has evaluated the use of cloud-based simulation using gaming elements to make it engaging to learn how silicon solar cells are manufactured. Photovoltaics is a rapidly evolving and growing industry and so training engineers can present challenges. On-line education has the advantage that it can adapt quickly to changes and education can potentially be provided internationally (i.e., remote from manufacturing facilities). The experience of using the PV Factory simulation within a university blended teaching program has demonstrated the potential of using gamification in on-line simulations for engineering education. The game elements of personal progress tracking and leaderboarding can make the learning experience more engaging, however it is not clear from this study that gamification engages all cohorts within a class. The blended learning environment used in the UNSW course helped to ensure that learning outcomes were achieved to a satisfactory level with the classroom environment providing an interactive environment for those students that were challenged by the use of game elements such as leaderboards. More research is required to ascertain these elements are generally effective in improving the learning experience in on-line education.

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ACKNOWLEDGMENT The development of PV Factory was supported by the Australian Renewable Energy Agency (ARENA), the School
