Company: School of Physics and Astronomy, Cardiff University
Author: Dr Richard James Lewis
NI Product(s) Used: LabVIEW NXG, myDAQ, Vision
Industry: Higher Education
Challenge
At Cardiff University School of Physics and Astronomy, we needed to build upon our award-winning, LabVIEW-centric, problem- and project-based learning (PBL and PjBL) MSc teaching to accommodate an expansion of student numbers and merging of our physics- and astrophysics-based degree schemes.
We wanted to continue to deliver best-in-class problem- and project-based learning while adapting to a larger and more diverse cohort. To accomplish this, we implemented an innovative "applications-first" approach to teaching based around the LabVIEW NXG programming environment.
LabVIEW NXG provides significant enhancements and improvements over traditional LabVIEW that suggested a "start useful, stay useful" applications-first approach to LabVIEW teaching. We have therefore completely overhauled our core PBL and PjBL core module to adopt this new model.
To our knowledge, this is the first such implementation of LabVIEW NXG in a higher education environment in the world.
Michelson Interferometer as a LIGO Analogue: prototyped in LabVIEW NXG 2.1 within an MSc Physics micro-project in autumn 2018 and incorporated as part of a National Space Centre “Space Lates” event in January 2019. Our student-lead micro-projects are designed to mesh with the University’s active research and outreach programmes.
Application Overview
Historically, MSc Physics (and related physics-based MSc) students have all been taught LabVIEW 2015 to support learning in a PBL and PjBL environment. Combined with a unique research-group cohort structure and ethos, we empower students to take ownership of their learning. This has been a recognised excellent and award-winning educational model.
Students spend 100 hours learning LabVIEW 2015 in a PBL laboratory environment, and in parallel undertake 100 hours of PjBL in student-lead micro-projects. The entirety of this learning takes place within a core autumn semester module.
When considering the physics- and astrophysics-based MSc cohorts, two factors became apparent: (a.) it would be pedagogically difficult to re-implement the LabVIEW 2015 course in a relevant way for physics and astrophysics students simultaneously due to the very physics-centric nature of the old course, and (b.) the logistics of providing student-bespoke material becomes more difficult as the number of students in the cohort increases. An additional constraint was the requirement to maintain our high level of student satisfaction.
In terms of implementation, the three-way choice was between: (i.) continuing to run the old course with minor adaptations, (ii.) switching to Python as the common language of instruction, or (iii.) adopting a radically different model with LabVIEW NXG.
Overall, LabVIEW NXG was chosen as the language of instruction since it allowed us to address both our pedagogical and logistical needs simultaneously. An additional advantage was the ability to retain our DAQmx- and IMAQx-based equipment and experiments in-place with little in the way of re-writing required.
Our implementation was logistically much easier, as we were deploying one module compared to keeping comparable standards in two parallel but different modules. We were able to retain our courses' USPs while maintaining the MSc community feel, student feedback, and overall satisfaction.
Migrating to LabVIEW NXG from LabVIEW 2015 afforded an opportunity to thoroughly review and enhance the structure of our course. Since LabVIEW NXG allows easier access to data and a superior development environment, it was possible to put applications at the centre of the PBL component of the course from week 1 onwards.
Impact
Problem-Based Learning Impact
NXG allowed an "applications-first" syllabus structure, which dramatically increased teaching and learning efficiency.
We implemented an "everything in the project" approach to the generation of learning materials. Example VIs, applications, supplementary material and even the assessment scripts were all contained within a session's NXG project. Leveraging NXG's friendly UI based on a single tabbed window, we have essentially eliminated the small "micro pauses" inherent to switching into / between / out of traditional LabVIEW materials. Every contact session benefitted from an increase in fluency and reduction in "dead" time.
The user interface for LabVIEW NXG is much more logically arranged and intuitive compared to traditional LabVIEW. There are far fewer pauses in the workflow when a student works within a single tabbed window as opposed to hunting through multiple open windows.
The ability to zoom NXG code made video capture more effective than traditional LabVIEW. With NXG it was feasible to simultaneously project, stream, and capture NXG development within a contact session. The quality of the NXG UI and vector-based G code meant that videos had a consistent polish throughout. Students could review videos during contact sessions, empowering them to solve problems by themselves and reducing supervisory load.
The zoom function in LabVIEW NXG is a killer feature on the Diagram, allowing simple and effective removal of visual clutter during contact sessions. It is particularly useful when capturing the session videos, resulting in much higher-quality and easier to follow video resources.
Project-Based Learning Impact
NXG had a transformative effect on the efficiency and depth of the NXG-based micro-projects. Students made use of their NXG skills in the PjBL component of the course much earlier (week 1) than with traditional LabVIEW (week 4).
NXG is intuitive to use; students explored the language during micro-projects to greater depth than in previous years. Students found required nodes, examples, or other resources efficiently and with less supervisor input. One micro-project group ported an application from LabVIEW 2015 without having being shown how to do it.
Our NXG-based micro-projects progressed faster and further than previous years; image analysis projects with Vision were particularly accelerated. The "Cloud Chamber 3D Track Reconstruction" group accomplished in three weeks what had taken a previous group an entire semester using traditional LabVIEW.
Cloud Chamber 3D Track Reconstruction: cloud chamber track identification and capture in LabVIEW NXG 2.1 for an MSc Physics micro-project. The data acquisition and analysis pipelines were rapidly developed by the project students using the Vision toolkit.
What's Next?
Application Concept Notes
We did not take lightly the decision to thoroughly revise an established and effective LabVIEW-based course on a core MSc module. The primary difference between the old and new course structure is the movement from a traditional programming-concepts-first syllabus to an applications-first, programming-concepts-in-parallel model.
Why not implement this structure with traditional LabVIEW?
It is possible that this could be done, but the advantage of using NXG instead is that NXG is designed from the ground-up to prioritise access to data and to get equipment working as soon as it is plugged in. This design choice, together with the zoom feature (which utterly transforms how an instructor presents) and superior and more consistent NXG UI made it a more efficient choice.
There are fewer bottlenecks with NXG on the road from basic applications through code drag-and-drop, to mastery of the language. Given that our module is 11 weeks in length, every extra efficiency counts.
Attachments
Author Contact Details
Dr Richard Lewis CPhys MInstP FHEA
Director of Postgraduate Studies
School of Physics and Astronomy
Cardiff University
Tel: +44(0)29 2087 5433
Web: http://www.cardiff.ac.uk/people/view/913813-lewis-richard
Email: LewisR54@cardiff.ac.uk
Cardiff University is a registered charity no. 1136855