Exclusively inclusive?..

Software has the potential to be custom tailored and can be designed to integrate any special requirements needed from the users, either from the design of the interface through to the overall functionality of the software.  This can include the specific customisation of the interface to overcome certain disabilities (Keates, John Clarkson, & Robinson, 2002) such as visual or aural difficulties that the students may have, through to specifically tailoring computers for users with motor control difficulties such as cerebral palsy.

However when adopting proprietary software, such as Physion, we don’t always have this luxury to tailor the interface.  There are a wide multitude of disabilities and learning difficulties that students face (Phipps, Sutherland, & Seale, 2002), some of which I believe the use of Physion helps to overcome.  As Physion is a highly graphical and interactive space it removes most of the barriers associated with language.  This could be beneficial for dyslexic and international students who may struggle with comprehension and reading.  “Dyslexia is not associated with general cognitive impairment…” (Langdon & Thimbleby, 2010) and so by eliminating the reading component and replacing it with graphic modelling and interactive physics this should facilitate learning for students.  Similarly through the use of highly contrasting colours against a white background, this can eliminate issues with colour blindness, something that both of my brothers suffer from.

The Disability Discrimination Act (DDA, 1995) was created to remove barriers and social exclusion of people with various disabilities, this legislation and the development of appropriate ICT strategies (Abascal & Nicolle, 2005) have helped create a more inclusive education system.  Inclusiveness isn’t just about including people with disabilities, some people are introverts (Waite, Wheeler, & Bromfield, 2007) and studies have shown that the inclusion of ICT strategies in the classroom can help with learning and focus by creating less distractions and increasing focus on controlled activities.

In my lectures there are several students that have a wide range of learning disabilities and their support plans all spell out specifically how we as lecturers and as a University can support them in their learning: this level of planning makes the class feel very inclusive.  I make every effort to support the students in the classroom through the design of my lectures (HEA,2011 – V1) and by offering additional 1 to 1 sessions where I can.

On the whole I think the Physion TEL intervention will create a more inclusive learning experience that will break down some of the barriers to learning that some students may face.  When I began creating the original intervention I hadn’t specifically designed the session to be more inclusive, but on reflection there are a lot of components in there that have been made more inclusive subconsciously.  Part of this will perhaps be because both of my brothers are colour blind, so I tend to think about differentiating between red and greens automatically.  Also, because of the teaching I do with the British Red Cross I tend to design sessions to be inclusive without consciously setting out do so.

Whilst I feel that the intervention itself is very inclusive, this is in part because it is targeted at a small group of students and I’m physically present to help fix things during the session if things go off the rails.

The software is run from a CDROM so it’s hard for students to mess with settings and kill the program, but what about if I use remote delivery?  For this I could use pre-recorded screencasts to take the students through each stage in a step-by-step basis, or perhaps employ a technology I widely used in industry for real time screen casting such as Webex or Adobe Connect.  What about students who don’t use PC’s and so who can’t perhaps use Physion?

I think short term the use of Physion will be perfect for the development of the programme, but perhaps long term a more inclusive environment such as a web based experience could be beneficial, this will allow the lecture to be platform independent and also allow it to be run on systems that have been tailored specifically for students needs (HEA, 2011 – A4).

References:

Abascal, J., & Nicolle, C. (2005). Moving towards inclusive design guidelines for socially and ethically aware HCI. Interacting with Computers, 17(5), 484-505. doi: 10.1016/j.intcom.2005.03.002

DDA. (1995). The Disability Discrimination Act.  UK: Department for Education and Employment,.

HEA. (2011). The UK Professional Standards Framework for teaching and supporting learning in higher education   Retrieved from http://www.heacademy.ac.uk/assets/documents/ukpsf/ukpsf.pdf

Keates, S., John Clarkson, P., & Robinson, P. (2002). Developing a practical inclusive interface design approach. Interacting with Computers, 14(4), 271-299. doi: 10.1016/s0953-5438(01)00054-6

Langdon, P., & Thimbleby, H. (2010). Inclusion and interaction: Designing interaction for inclusive populations. Interacting with Computers, 22(6), 439-448. doi: 10.1016/j.intcom.2010.08.007

Phipps, L., Sutherland, A., & Seale, J. (2002). Access All Areas: disability, technology and learning. Oxford: Association for Learning Technology.

Waite, S. J., Wheeler, S., & Bromfield, C. (2007). Our flexible friend: The implications of individual differences for information technology teaching. Computers & Education, 48(1), 80-99. doi: 10.1016/j.compedu.2005.01.001

Literature review…

One of the key drivers of this project was the on-going observation by the Institution of Structural Engineers (IStructE) and industry that the quality of graduates has been on the constant decline for the past 40 years or so; specifically the ability for graduates to understand structural behaviour.  This is notable in articles, publications, and reports published by the professional bodies, starting with the highly graphical tests of (Brohn & Cowan, 1977a, 1977b) who concluded that graduates “…did not have a sound understanding of structural behaviour.”  This criticism has continued to be banded about within the structural engineering circles since this report with concerning regularity.  One of the key skills of a structural engineer is to identify the difference between a structure and a mechanism, and this skill was shown to be lacking by modern graduates through the tests of graduates undertaken by (Morreau, 1990).

Indeed during his time as President of the IStructE Graeme Owens dedicated (and still does) a considerable amount of time and effort to addressing these inadequacies in the teaching of structural behaviour (Owens, 2011).   Indeed (Owens, 2010) notes that “At worst, when tested on a qualitative understanding of structural behaviour, many students with good degrees from universities with strong reputation score zero!”

This is symbolised most recently by the paper competition arranged by Owens to identify best teaching practices from the UK universities.  Equally (Cook, 2011) correctly identifies that for a structural engineer to be successful they must have a core understanding of structural behaviour.  One could perhaps be forgiven for believing this to be a problem solely constrained to the UK educational system, but (Aparicio & Ruiz-Teran, 2007) also notes that this is a crisis affecting the industry far beyond just the UK and indeed could potentially expand to other portions of Western society.

Methods of teaching?

Traditional methods of teaching structural analysis are highly numerical, with little or no consideration given to the qualitative aspects of the structure (Brohn & Cowan, 1977a).  Modern software packages are incredibly powerful and the engineering design has become less about the analysis (MacLeod, 1995) and more about the understanding of the results being presented, but this can only happen when a strong understanding of structural behaviour is present in the students.

It is worth noting that typically structural engineering analysis is taken as a quantitive process, with the students determining numerical values to a series of problems, one of the recommendations of (Brohn & Cowan, 1977a) report and from (Curtin, 1991) was that equal measure should also be given to qualitative analysis: this was one of the reasons for the creation of my real time physics models as they allow the student to experience behaviour in its truest representation.  One of the challenges facing lecturers when trying to develop assistive learning technologies is that the nature of the technology changes quickly (Law, 2011) and the technology is difficult to describe in a meaningful manner due to it frequently becoming obsolete in a short period of time.

Puzzles?

Puzzles are widely used in the teaching and learning of STEM subjects, most typically Mathematics (Levitin & Levitin, 2011) where they are used to improve logic skills.  Recent years have seen a development and expansion of these puzzles into the broader STEM disciplines (Badger, Sangwin, Ventura-Medina, & Thomas, 2012) to allow specific puzzles to be tailored into subject specific areas.  The success of a puzzle is largely dependent on having four defining qualities (Michalewicz & Michalewicz, 2008):

1.) Generality:

Educational puzzles should explain some universal mathematical problem.

2.) Simplicity:

Education puzzles should be easy to state and remember, if puzzles are easy to remember then this can increase the chance that the solution too will be remembered in the future.

3.) Eureka factor:

Puzzles should by their very nature be puzzling, and consequently frustrating to a degree.  The result should be interesting as sometimes it may feel counter-intuitive but should ultimately end with a Eureka! moment.

4.) Entertainment factor:

For a puzzle to be effective it should be entertaining, students may lose interest if puzzles are not fun!

Essentially the nature of my chosen intervention requires the use of a real time physics simulation of various different structures, initially to explore the behaviour, then as the student’s confidence grows to identify and solve a puzzle.  It could be argued that the use of puzzles has several similarities to Problem Based Learning (Dym, Agogino, Frey, & Leifer, 2005)  but it also has several distinct differences, in this instance for example the puzzle is a closed solution and does not necessarily require the user to acquire new information in order to solve the problem.  Also the student can work in isolation or as a group for my puzzles in an informal playful manner (Hodkinson, Colley, & Malcolm, 2003), but the advantages of group working are primarily for benefits through peer to peer reflection (Atkins & Murphy, 1993).

Simulations.

Civil Engineering courses have historically used simulations (Cullingford, Mawdesley, & Davies, 1979) and visualisation techniques (Bagchi, 2011; Townsend & Wood, 1978) in a wide variety of settings from blended learning (Wall & Ahmed, 2008), to business games (Pasin & Giroux, 2011), through to virtual environment simulations (Freitas & Neumann, 2009).  One of the key elements of these types of simulations is that they model something realistically, but in a simplified manner (Kolfschoten, Frantzeskaki, Haan, & Verbraeck, 2008) to provide summative feedback (Oraifige, Heesom, & Felton, 2009) as they respond to various inputs and stimulus provided by students using digital technologies (JISC, 2010) to help encourage their learning through accumulation of experience (Kolb, 1984; Moon, 2004).

The assessment of pedagogical benefit of games (Kebritchi & Hirumi, 2008) and puzzles has been frequently considered within STEM projects, but through combining these with a formal reflective process (Mawdesley, Long, Al-jibouri, & Scott, 2011) the benefits can be increased.   Indeed traditional teaching material is static, and through the introduction of dynamic content (Ploetzner, Lippitsch, Galmbacher, Heuer, & Scherrer, 2009) the behaviour of the structures should be better visualised by the students, particularly the removal of language barriers (Phipps, Sutherland, & Seale, 2002) break the simulations down to their simplest component: their behaviour.

It is hoped that by getting the students engaged within the puzzle environment that they may eventually feel comfortable enough to develop their own puzzles to test each other with, this level of collaboration (Triantafyllakos, Palaigeorgiou, & Tsoukalas, 2011) should lead to better reflections (Moon, 2001) on how they feel they learn structural behaviour and to identify tricky areas to test their puzzles with.

When using real time physics if a mistake is made then the puzzles will collapse in real time, one point to note is that (Huei-Tse, 2012) identified in large user games, specifically MMORPG’s that students were more actively engaged in ‘battles’ rather than problem solving areas.  This destructive type of behaviour could perhaps be capitalised on within the puzzles to get the students to identify the quickest way to make a structure fail through the removal of the fewest elements.  Indeed if a community could be constructed which required the engagement of the players in a multiplayer environment this could help create better engagement with the students and a more positive outlook to gaming as a valid method of learning (Hainey, Connolly, Stansfield, & Boyle, 2011) and increase social interaction as the community grows.

Even for non-engineers, watching the real time collapse of the structures can be seen to be quite fun, particularly as some of the Physion models can fail in quite spectacular fashion.  The benefits of fun should not be overlooked when teaching and learning.  Ebner (2007) found that the introduction of simulations into Civil Engineering lectures the outputs from the students improved and there was a distinct increase in ‘joy’ based on (Nielsen, 2002).

During a recent essay competition (Collins & Davies, 2009) one of the things noted by engineering students as to what made a good engineering lecturer was the use of real examples, indeed good teaching as described by (Ramsden, 2003) also notes that making the “material being taught stimulating and interesting” is a key contributor to good practice in teaching and learning, both of these positive qualities can be seen in the use of real time physics and the puzzles.

Summary.

From this literature review it is clear that for modern graduates understanding structural behaviour is a problem within the industry that must be addressed by the universities.  One method worth considering is the integration of structural simulations that are fun and engaging in a real time physics environment, particularly when combined with the use of puzzles both created by the lecturers and also by other students.  The development of such a resource will be the primary focus of my ALT teaching intervention.

References:

Aparicio, A. C., & Ruiz-Teran, A. M. (2007). Tradition and innovation in teaching structural design in civil engineering. Journal of Professional Issues in Engineering Education and Practice, 133(4), 340-349. doi: 10.1061/(asce)1052-3928(2007)133:4(340)

Atkins, S., & Murphy, K. (1993). Reflection: a review of the literature. Journal of Advanced Nursing, 18(8), 1188-1192. doi: 10.1046/j.1365-2648.1993.18081188.x

Badger, M., Sangwin, C. J., Ventura-Medina, E., & Thomas, C. R. (2012). A guide to puzzle-based learning in STEM subjects. Birmingham: University of Birmingham.

Bagchi, D. (2011, 14-16 July 2011). Integrating Simulations to Increase Efficacy of the Teaching-Learning Process. Paper presented at the Technology for Education (T4E), 2011 IEEE International Conference on.

Brohn, D. M., & Cowan, J. (1977a). Teaching towards an improved understanding of structural behaviour. The Structural Engineer, 55(1), 9-17.

Brohn, D. M., & Cowan, J. (1977b). Teaching towards an improved understanding of structural behaviour. The Structural Engineer, 55(1), 496-515.

Collins, K., & Davies, J. (2009). Feedback through student essay competitions: what makes a good engineering lecturer? Engineering Education, 4(1), 8-15.

Cook, M. (2011). Engineers are not made in heaven. The Structural Engineer, 89(13), 12-13.

Cullingford, G., Mawdesley, M. J., & Davies, P. (1979). Some experiences with computer based games in civil engineering teaching. Computers & Education, 3(3), 159-164. doi: 10.1016/0360-1315(79)90041-1

Curtin, W. G. (1991). Qualitative analysis of structures. The Structural Engineer, 69(7), 157.

Dym, C. L., Agogino, A. M., Frey, D. D., & Leifer, L. J. (2005). Engineering design thinking, teaching, and learning. Journal of Engineering Education, 94(1), 103-120.

Ebner, M., & Holzinger, A. (2007). Successful implementation of user-centered game based learning in higher education: An example from civil engineering. Computers & Education, 49(3), 873-890. doi: 10.1016/j.compedu.2005.11.026

Freitas, S. d., & Neumann, T. (2009). The use of ‘exploratory learning’ for supporting immersive learning in virtual environments. Computers & Education, 52(2), 343-352. doi: 10.1016/j.compedu.2008.09.010

Hainey, T., Connolly, T., Stansfield, M., & Boyle, E. (2011). The differences in motivations of online game players and offline game players: A combined analysis of three studies at higher education level. Computers & Education, 57(4), 2197-2211. doi: 10.1016/j.compedu.2011.06.001

Hodkinson, P., Colley, H., & Malcolm, J. (2003). The Interrelationships Between Informal And Formal Learning. Journal of Workplace Learning, 15(7/8), 313-318.

Huei-Tse, H. (2012). Exploring the behavioral patterns of learners in an educational massively multiple online role-playing game (MMORPG). Computers & Education, 58(4), 1225-1233. doi: 10.1016/j.compedu.2011.11.015

JISC. (2010). Effective Assessment in a Digital Age: A guide to technology-enhanced assessment and feedback. Bristol: JISC.

Kebritchi, M., & Hirumi, A. (2008). Examining the pedagogical foundations of modern educational computer games. Computers & Education, 51(4), 1729-1743. doi: 10.1016/j.compedu.2008.05.004

Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. New Jersey: Prentice-Hall.

Kolfschoten, G., Frantzeskaki, N., Haan, A. d., & Verbraeck, A. (2008). Collaborative modelling lab to increase learning engagement. Engineering Education, 3(2), 21-27.

Law, S. (2011). Recognising excellence in teaching and learning   Retrieved from http://www.heacademy.ac.uk/assets/documents/ukpsf/recognising-excellence.pdf

Levitin, A., & Levitin, M. (2011). Algorithmic Puzzles. Oxford: Oxford University Press.

MacLeod, I. A. (1995). A strategy for the use of computers in structural engineering. The Structural Engineer, 73(21), 366-370.

Mawdesley, M., Long, G., Al-jibouri, S., & Scott, D. (2011). The enhancement of simulation based learning exercises through formalised reflection, focus groups and group presentation. Computers & Education, 56(1), 44-52. doi: 10.1016/j.compedu.2010.05.005

Michalewicz, Z., & Michalewicz, M. (2008). Puzzle-based learning: An introduction to critical thinking, mathematics, and problem solving. Melbourne: Hybrid Publishers.

Moon, J. (2001). PDP Working Paper 4 Reflection in Higher Education Learning  Retrieved 1st October 2011, from https://http://www.york.ac.uk/admin/hr/researcher-development/students/resources/pgwt/reflectivepractice.pdf

Moon, J. (2004). A handbook of reflective and experiential learning: Theory and practice. London: Routledge.

Morreau, P. M. (1990). Understanding Structural Behaviour. The Structural Engineer, 68(15), 299-300.

Nielsen, J. (2002). User Empowerment and the Fun Factor  Retrieved 6th May 2012, from http://www.useit.com/alertbox/20020707.html

Oraifige, A., Heesom, D., & Felton, A. (2009). Technology supported learning (TSL) for formative assessment. Engineering Education, 4(1), 61-67.

Owens, G. (2010). Structural engineering education in the 21st century: the way forward. [Viewpoint]. The Structural Engineer, 88(1), 15.

Owens, G. (2011). Transforming undergraduate structural engineering education in the 21st Century. The Structural Engineer, 89(2), 18-20.

Pasin, F., & Giroux, H. l. n. (2011). The impact of a simulation game on operations management education. Computers & Education, 57(1), 1240-1254. doi: 10.1016/j.compedu.2010.12.006

Phipps, L., Sutherland, A., & Seale, J. (2002). Access All Areas: disability, technology and learning. Oxford: Association for Learning Technology.

Ploetzner, R., Lippitsch, S., Galmbacher, M., Heuer, D., & Scherrer, S. (2009). Students’ difficulties in learning from dynamic visualisations and how they may be overcome. Computers in Human Behavior, 25(1), 56-65. doi: 10.1016/j.chb.2008.06.006

Ramsden, P. (2003). The nature of good teaching in higher education Learning to Teach in Higher Education (Third ed., pp. 84-105). London: RoutledgeFalmer.

Townsend, P., & Wood, R. D. (1978). Learning an appreciation of structural behaviour using interactive computer graphics. Computers & Education, 2(3), 213-220. doi: 10.1016/0360-1315(78)90013-1

Triantafyllakos, G., Palaigeorgiou, G., & Tsoukalas, I. A. (2011). Designing educational software with students through collaborative design games: The We Design & Play framework. Computers & Education, 56(1), 227-242. doi: 10.1016/j.compedu.2010.08.002

Wall, J., & Ahmed, V. (2008). Use of a simulation game in delivering blended lifelong learning in the construction industry – Opportunities and Challenges. Computers & Education, 50(4), 1383-1393. doi: 10.1016/j.compedu.2006.12.012

5/6 – Pick a winner…

A key aspect of using technology successfully in any problem, is ensuring that you not only understand what it is that you wish to achieve, but that you also select an appropriate technology to evaluate the problem. This blog post aims to demonstrate (briefly) the evaluation process that I’ve been through when selecting what tools to consider for my ALT module. I’ve spent a lot of time on this and I get the feeling that perhaps others have just selected a piece of software and run with it and have been out of the blocks much quicker, perhaps I’ve wasted time ensuring that I not only understand my problem at a pedagogical level but also that I’ve selected the correct technology to answer these challenges, but I get twitchy if I don’t fully understand something before I implement it.

There is a plethora of simulation and modelling software options available in the market, each package varies in complexity, cost, capabilities, and user experience.  The ability to be able to correctly assess physics in real world engineering problems brings huge financial savings to a project and can save time through the reduction of physical prototyping: fundamentally it’s a cornerstone of engineering education.  This blog post is going to take a very quick whistle stop tour of a selection of available options that I’ve considered for my ALT project to use for the teaching of structural behaviour through using puzzles.

I think its important when selecting technologies to consider what outcomes you want to ensure that the technology solves the problem seamlessly rather than becoming the problem itself.

Autodesk Inventor:

Autodesk provide free licences for the majority of their software for students during their academic life.  Autodesk is a market leader in CAD and modelling software and this free licencing offers the students the ability to learn industry standard modelling and analysis environments whilst at University.  Autodesk Inventor is widely used throughout industry and can be used to model mechanisms and a wide variety of multi-physics.

Given that the Inventor can model very complex arrangements with a variety of physics (mechanical, stresses, thermal, magnetism, etc…) it almost goes without saying that it has a steep and complex learning curve and it is for this reason that I feel that it is perhaps not suitable for use in teaching early undergraduates structural behaviour.

Pros: Free for students, extensive, multi-physics. 

Cons: Complicated to learn, needs a powerful PC, lack of real time physics.

Link: http://usa.autodesk.com/autodesk-inventor/

Solidworks:

Solidworks is similar in some ways to Inventor, using a modelling environment to create geometries that can then have their physics behaviour modelled in a simulation environment.

The University has several licences scattered around the campus of Solidworks, with product designers and the mechanical engineers making strong use of the package.  It offers many of the benefits of Inventor, but comes with an additional negative component in that if students want to work through the puzzles or learn the environment at home they must buy a student licence which costs £89 per annum.

Pros: Available on campus, extensive, multi-physics. 

Cons: Complicated, needs a powerful PC, costs £89 for a student licence for 12 months, lack of real time physics.

Link: http://www.solidworks.com/

COMSOL:

COMSOL is a multi-platform piece of software available for both PCs and Macs which has extensive modules for considering different physics environments.  Whilst the level of modelling available for multi-physics problems is as comprehensive as it is impressive, trying to obtain licences for students is complex with very little information being available.  Other users within the department have used COMSOL within their PhD’s and through discussions it would feel well suited to this environment, however it is perhaps overkill with regards complexity for Year 1 students.

Pros: Extensive, multi-physics.

Cons: Not widely available on campus, difficult to learn, potentially expensive, lack of real time physics.

Link: http://www.uk.comsol.com/

ANSYS:

ANSYS is used extensively within CSE on a wide variety of courses from Civil Engineering through to Aeromechanical courses.  It is a powerful FEA software that is used throughout industry and can be used to simulate a large variety of engineering problems.

It has multi-physics capabilities, but they do not happen in real time.  ANSYS is normally taught in the final year of our degrees due to the complexity of the modelling process, whilst the initial creation of the models is fairly straightforward, experience has taught us that students can struggle to debug and fix their models when errors occur.

Pros: Available on campus, multi-physics, mechanisms.

Cons: Difficult to learn, lack of real time physics, ITS are unable to source the student licences for our students.

Link: http://www.ansys.com/

Algodoo:

Algodoo is a real time physics environment that can be used to teach students in STEM related disciplines.  It has a simple environment that is easily learned, complete with interactive lessons that have already been created.

The education licence has the added ability to attach graphing output and traces to show the behaviour of the components.  This package has lots of potential in teaching structural behaviour and the interactiveness and general playfulness of the software will encourage students to explore and tinker with the puzzles and exercises.

Pros: Specifically designed with pedagogical intent, simple to use, encourages playfulness, can graph and plot movement and behaviours in real time, student puzzles can be created.

Cons: Not widely available on campus and comes at a cost that varies depending on number of seats purchased. 

Link: http://www.algodoo.com/wiki/Home

Physion:

Physion is a free piece of software that is created with the intention of creating fun mechanisms and other physics based environments.  It has a simple interface, which whilst not as playful as Algodoo is more than functional.  The learning curve needed is minimal and students can be up and running quickly with the software.

The level of hardware required is minimal which fits well with the IT provision on campus, although this may need to be run from USB sticks or a custom CDROM.  The software has a strong community growing which shares and creates their models and this could be an opportunity for the students to interact and contribute.

Pros: Free software, existing community, simple to learn, real time physics, allows the students to create puzzles and models of their own.

Cons: Environment is not as friendly as Algodoo, ability to copy and paste components can take longer to create models.

Link: http://physion.net/

Mathematica:

Mathematica is a maths based piece of software which encourages the creation of CDF documents which can be opened by anyone who has the CDF player software which is free of charge.  This is a similar concept to PDF’s except that CDF’s are live documents that can be interacted with by the user, typically through the use of sliders.  I wanted to include one of these simulations within this blog post, but unfortunately this isn’t allowed with the free version of WordPress, although it can be easily achieved using Bloggr or another blogging platform through the use of <iframe> tags, this is a little disappointing in fairness.  I’m hoping to run similar tests once Blackboard gets upgraded to v9.

CDF documents are created by proficient users and then contained within a simple module that allows students to adjust parameters and view the effects of these changes through interactive graphics.  The creation of the simulations requires a lot of effort from the lecturer, but this can create a fun experience for the student and several textbooks have now been written using CDF format with positive feedback.  Indeed one mathematics textbook now sells more copies in the CDF format than it does in the equivalent paper version.

Pros: Free CDF player software, simulations can be tailored to suit the pedagogical aims.

Cons: Lecturer requires a full licence of Mathematica (£895), puzzles and simulations are bounded and whilst are still playful they are not as interactive as Physion and Algodoo.

Link: http://www.wolfram.com/mathematica/

Summary:

There is a growing market in Physics and simulation software available on the market, ranging from freeware through to pieces of software that cost tens of thousands of pounds.  The use of real time physics is becoming more common in the classroom and is allowing students of all levels to visualise what the influencing factors are when designing, modelling, and learning the given topic.

Inventor, COMSOL, ANSYS and Solidworks all offer comprehensive analysis environments, but due to their steep learning curves and complexity they are not suitable for our first year students.  It would take longer to learn the software than it would to learn the actual physics behind the structural behaviour that we are attempting to teach.

However, due to the existing licences of ANSYS and the ability for students to access free copies of Inventor, these are both strong candidates for expanding some of the final year material either within structures or perhaps more appropriately through specifically tailored dissertation topics.

For the purposes of teaching first year structural behaviour there are three strong contenders within the technologies considered: Mathematica, Algodoo, and Physion.  For the initial pilot study which is what this ALT module is considering Physion has been selected due to its free costs, simplicity to learn and ease of distribution.  However I am also in the process of writing several CDF documents with intention of embedding these within our BlackBoard VLE and I continue to evaluate the Algodoo for Education that I’ve purchased during their 50% off Easter sale.

Intervention…

I’ve spent some time reviewing the literature, speaking with other IStructE members, employers, and lecturers about what the inadequacies are relating to the modern civil engineering graduate and this keeps coming back to the same point that: modern graduates from all UK Universities don’t appear to have the grasp of structural behaviour that perhaps their equivalents from 20 years ago had.  GIven that the understanding of the graduates from 20 years ago was more comprehensive when the use of technology in teaching was in its infancy, what role can modern technology have in addressing the improvements in learning?

What follows below is my outline thoughts and lesson plan with regards my teaching intervention and how I intend to use technology to improve the learning of structural behaviour.

Intended Learning Outcome: To appreciate and differentiate between the structural behaviour of determinate and indeterminate structures.

Lecture Duration: 1 Hour.

Lesson Schedule:

0-10 Mins: Introduction to determinate & indeterminate structures, introduction to the Physion.

10-30 Mins: Students work through Physion models and questions under supervision.

30-40 Mins: Reflective discussion about the behaviour witnessed in the exercises.

40-50 Mins: Puzzles worked through as a group.

50-60 Mins: Debrief/Feedback.

Methods of Delivery: Multiple methods will be used, including:

Show & Tell, worked examples, powerpoint slides, printed notes, exercises, reflective discussion, group working, puzzles.  The breadth of opportunity should increase the ability for the students to engage.  Through the experiential nature of the real time physics models the students will be to engage with the structures and obtain instant feedback from their decisions, giving formative rather than summative feedback as part of the learning experience.

Location: Newton Computer Suite

Number of Students: Approximately 6

Equipment needed: Laptop, Projector, Computers, Physion installed to CDROMs to be run locally from drives.

Measurement: The students learning will be measured via completion of the puzzles and the completion of a short test.  This will be followed by a discussion where the students can identify what they enjoyed about session, what they would change if possible….

UKPFS Relevance: A1-A4, V1-4, K4-5 (HEA, 2011)

References:

HEA. (2011). The UK Professional Standards Framework for teaching and supporting learning in higher education   Retrieved from http://www.heacademy.ac.uk/assets/documents/ukpsf/ukpsf.pdf

Another perspective…

Following my foray into VARK testing and my general uneasiness with the results, I was interested to hear of an alternative theory called ‘Multiple Intelligences’ by Howard Gardener.  As with the VARK test, some helpful soul has written an online test which is pretty painless to work through to gain an insight as to your strengths with regards different forms of intelligences.  Below is a copy of my results following the test and I think this better reflects what I feel my strengths (or intelligences) sit compared to the VARK scheme.

Looking at these results, I think this better reflects how I think I prefer to learn.  It’s worth noting that this is only my own personal perception though as I’ve never conducted an experiment to determine which style is genuinely most effective.  The Visual and Linguistic components generally suit how I approach problem solving, first by drawing sketches and diagrams to see how things behave and then discussing these thoughts with peers.  This is a frequent tactic employed by successful creative design engineers, with it being a common trait with the IStructE exam pass rate too.  However, engineers by their nature need to have a certain amount of numerical agility by the nature of their design work as noted by (Gardner, 1993, p135) mathematics deals with ‘abstract, non-linguistic entities’ and this is the challenge for the developing engineer.

The more I read about learning theories the less comfortable I become as a lecturer trying to shoehorn people into neat little boxes.  Instead of tailoring the session to neatly fit into styles of learning I’m intending to create diversity in approaches to allow the students to learn the same topic via a multitude of routes.  Similarly, by making the learning context engaging I’m hoping that the students will find this method of learning accessible regardless of their preferred learning style, which can make the learning experience more efficient (Poitras & Poitras, 2011).  I’ve collected some thoughts and used the headings of Multiple Intelligences for convenience below, the author himself acknowledges that these are not a learning style, but instead are a series strengths.

By introducing real time physics as a method of simulation will allow the students to visually develop an understanding of the basic structural behaviour by instantly seeing the consequences of their actions when exploring the models.  Through working in an open group with discussion about why they think the models collapsed, they will also have the opportunity to see if they can make the structures fail in a variety of methods to force behaviours to occur.

Logical-mathematical

The structural models presented can be analysed using the mathematical techniques covered in the traditional structural engineering modules.

Spatial

Through the digital visualisation of the structures, and their collapse mechanism, the students will have the opportunity to visualise the rare phenomenon of a structural failure occurring.

Linguistic

Through discussion with the lecturer and their peers, the students will be able to discuss and reflect on their experiences and to why they think the structures failed and why in the specific manner that they witnessed.

Bodily-kinesthetic

This particular component is debatable, parts of the experiential learning (Moon, 2004) process are contained within the programme through the inclusion of lab experiments (Fry, Ketteridge, & Marshal, 1999, Ch 11) and I feel that these puzzles by their nature are an extended form of these types of experiences, whilst they may not be truly physical in the sense of doing or touching the material the experience of ‘feeling’ the consequence of their actions as the boxes bounce around as if in a real environment perhaps presents a similar neurological experience.  We must also remember that not all of our students are able bodied and thus this may present a better opportunity to be involved in a laboratory as experiencing a process is key to understanding it’s relevance to a subject (Kolb, 1984).

Musical

This is a hard one for a structural engineering program to include, although I will permit whistling and self created sound effects whilst they manipulate their models and solve the problems…

Interpersonal

Discussion through groups, perhaps even having small groups working together to solve the problems may present a good opportunity the for the students to promote their interpersonal intelligences.  The dynamic, or real time physics will be carefully aligned to pedagogical outputs to help improve the progression of the students own personal development, this was shown by (Ploetzner, Lippitsch, Galmbacher, Heuer, & Scherrer, 2009) to have positive effects in teaching using dynamic visualisations.

Intrapersonal

Through reflective learning combined with the exploratory learning that puzzles bring (Freitas & Neumann, 2009) I hope that the students will also learn a little something about themselves.  This will be captured more perhaps in the focus groups after the process has been completed.

Naturalistic

Organic forms (Lim, 2009) and the creation of structure through the nature of Biomimicry (Forbes, 2006) could help promote their understanding of the natural world.  Similarly the more efficient a structure, the less material is needed and accordingly the lower it’s embedded carbon footprint.

Existential

This is one of the newer intelligences added and I do not intend to cover it within this blog post.

References:

Forbes, P. (2006). The Gecko’s Foot. Hammersmith: Harper Perennial.

Freitas, S. d., & Neumann, T. (2009). The use of ‘exploratory learning’ for supporting immersive learning in virtual environments. Computers & Education, 52(2), 343-352. doi: 10.1016/j.compedu.2008.09.010

Fry, H., Ketteridge, S., & Marshal, S. (1999). A Handbook for Teaching & Learning in Higher Education: Enhancing Academic Practice (First ed.). London: Kogan Page Limited.

Gardner, H. (1993). Frames of Mind: The Theory of Multiple Intelligences (10th Anniversary ed.). New York: Basic Books.

Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. New Jersey: Prentice-Hall.

Lim, J. (2009). Bio-Structural Analogues in Architecture. Amsterdam: BIS.

Moon, J. (2004). A handbook of reflective and experiential learning: Theory and practice. London: Routledge.

Ploetzner, R., Lippitsch, S., Galmbacher, M., Heuer, D., & Scherrer, S. (2009). Students’ difficulties in learning from dynamic visualisations and how they may be overcome. Computers in Human Behavior, 25(1), 56-65. doi: 10.1016/j.chb.2008.06.006

Poitras, G. r., & Poitras, E. (2011). A cognitive apprenticeship approach to engineering education: the role of learning styles. Engineering Education, 6(1), 62-72.