Key engineering education conferences in 2013

73rd Annual Meeting Academy of Management, "Capitalism in Question" | Abstracts due: January 15th 2013 | 9–13 August 2013 Orlando |

Society for Research in Higher Education | Abstracts due: Early 2013 | Early Dec 2013 (TBC)|

ICEER – International Conference on Engineering Education Research – organised by International Network for Engineering Education and Research, "Borderless Global Engineering Education" | Abstracts due: 30th January 2013 | 1-5 July 2013 Marrakesh |

HEA 9th Annual Conference, "Powerful Partnerships: defining the learning experience" | Abstracts due: January 21st 2013 | 3-4 July 2013, Warwick |

6th International Conference Engineering Education for Sustainable Development, "Rethinking the Engineer" | Abstracts due: January 18th 2013 |22- 25 Sept 2013 Cambridge |


SEFI 41st Annual Conference Engineering Education "Fast Forward 1973 – 2013" | Abstracts due: March 15th 2013 |16-20 September 2013 Leuven |

AAEE - Australasian Association for Engineering Education – Annual Conference, "Work Integrated Learning: Applying Theory to Practice in Engineering Education" | Abstracts due: TBA | 8 -11 Dec 2013 Gold Coast, Australia |

CIEC 2013 – Conference for Industry and Education Collaboration  - ASEE conference, "Engineering Education in an Era of Globalisation" | Abstracts due: deadline passed | 6 -8 Feb 2013 Phoenix, Arizona |


ASEE – American Society for Engineering Education 120th Annual Conference & Exposition, "Engineering Education: Frankly, We Do Give a D*mn" | Abstracts due: deadline passed | 23 – 26 June 2013, Atlanta, Georgia |

HEA – 2nd STEM Learning & Teaching Conference, "Where Practice and Pedagogy Meet" | Abstracts due:  deadline passed | 17-18 April 2013, Birmingham |

From ASEE Digest

Google Official: Start Early To Build Good Tech Workforce.

Bruce Johnson, the Atlanta site and engineering director for Google, writes in the Atlanta Journal-Constitution (12/23) about how to "maximize the number of qualified applicants" a company like Google can find. "There is no single set of discrete skills one can learn that will last an entire career in high-tech," Johnson writes. Instead, "ideal recruits are creative, adaptable and autonomous, and they have achieved a deep understanding of core subjects such as math, physics and computer science that make it possible to have a razor-sharp intuition and an ability to assimilate new subjects and technologies quickly, without even the expectation of being trained; they train themselves on the skills du jour as the need arises and with minimum help or structure." In order to boost this type of applicant, Johnson writes, students must be familiarized and comfortable with STEM subjects at a younger age.

Engineering education and management knowledge transfer

Can links be made between the academic literature on the transfer of management research to practice, and the academic literature on engineering education?

Research has shown that the transfer of management-related knowledge in academia to practice is ineffective (Pfeffer and Sutton 1999). Ven de Ven (2007) identified three groups of issues to explain this problem. Firstly, the lack of use of the outputs of management research may be a result of inappropriate communication methods (e.g. managers and consultants who advise them are unlikely to read academic literature regularly (Rynes et al. 2002; Rousseau 2006)).

Secondly, problems may relate to the differences in the type of knowledge. Scientific knowledge is focused upon building generalisations and theories, whereas practical knowledge in the professional domain is connected to the structure and dynamics of particular situations. Consequently, “Exhortations for academics to put their theories into practice and for managers to put their practices into theory may be misdirected because they assume that the relationship between knowledge of theory and knowledge of practice entails a literal transfer or translation of one into the other” (Van de Ven, 2007:4).

Thirdly, issues relating to the production of the knowledge. In relation to the development of management knowledge, a process of enquiry that is unengaged with the stakeholders beyond the academic environment may face problems in transfer and implementation. Approaches with the common theme of “involvement with members of an organization over a matter which is of genuine concern to them” (Eden and Huxham, 1996:75), i.e. action research, may be a potential solution.

How does this relate to engineering education? Given Trevelyan’s (2010) description of engineering as “distributed expertise enacted through social interactions between people”, there would seem to be clear ways in which the challenges of management knowledge transfer are linked to the discussion of the methods of engineering education. For example:

• Problems caused by inappropriate communication methods: Trevelyan (2009) identifies the importance of communication in the work of engineers, in order to allow them to operate effectively within the ‘distributed expertise’ model of engineering. It would be interesting to see how the communication-related issues found to hinder the transfer of management knowledge from academia compare to those identified by Trevelyan (2009, 2010).
• Problems caused by the nature of the knowledge: For engineering education the problem is perhaps not the nature of the knowledge, but the gap between knowledge of the practice of engineering and the content taught in universities (Pascail 2006; Trevelyan 2010).
• Problems caused by method of knowledge generation: For engineering education, this may point to the important role of in-company education activities (industrial projects, internships, etc.) where the problem and solution are more closely linked than in a class-based academic environment (Seagraves et al. 1996).

Pascail, L. (2006). "The emergence of a skills approach in industry and its consequences." European Journal of Engineering Education 31(1): 55-61.
Pfeffer, J. and R. I. Sutton (1999). "Knowing 'what' to do is not enough: Turning knowledge into action." California Management Review 42(1, Fall): 83-108.
Rousseau, D. M. (2006). "Is there such a thing as 'Evidence Based Management'?" Academy of Management Review 31(2): 256-269.
Rynes, S. L., A. E. Colbert and K. G. Brown (2002). "HR professionals' beliefs about effective human resource practices: Correspondence between research and practice." Human Resource Management 41(2): 149-174.
Seagraves, L., I. Kemp and M. Osborne (1996). "Are academic outcomes of higher education provision relevant and deliverable in the workplace setting." Higher Education 32: 157-176.
Trevelyan, J. P. (2009). Engineering education requires a better model of engineering practice. Research in Engineering Education Symposium 2009, Palm Grove, Queensland, Australia.
Trevelyan, J. P. (2010). "Reconstructing Engineering from Practice." Engineering Studies In Press.
Van de Ven, A. (2007). Engaged scholarship: A guide for organizational and social research, Oxford University Press, ISBN 978-0-19-922629-6. .

Investigating the Effect of 3D Simulation

Investigating the Effect of 3D Simulaton - Based Learning on the Motivation and Performance of Enginnering Students , Caroline Koh, Hock Soon Tan, Kim Cheng Tan, Linda Fang, Fook Meng Fong, Dominic Kan, Sau Lin Lye, and May Lin Wee, Journal of Engineering Education, July 2010 Vol 99 No 3.

Study of 2nd year technology students who were about to do workshop practice. Some of them were given practice on a simulator for machine tools prior to be introduced to the real thing the remainder of the class were a control group. The results are a bit inconclusive probably those who like computers were motivated by it, others weren't. Specifically thee was a gender biased. However there are some interesting takeaways:

Simulation Based Learning (SBL) appears to be a new acronym.

The amount of effort NTU/singapore can put into a simulator is very impressive.

The use of a behavioural psychologist to reference use Self Determination Theory (SDT) was excellent use of multi-disciplinary research

The impact of abstract vs contextualisation representation ad practice on learning

Pre-college Electrical Engineering Instruction: The Impact of Abstract vs. Contextualized Representation and Practice on Learning, Martin Reisslein, Roxanna Moreno and Gamze Ozogul, Journal of Engineering Education July 2010 Vol 99 No 3

This paper sets Year 9 students an the problem of calculating electrical resistences in parallell. A third get a standard circuit diagram (the abstract version), some got a picture with a battery and two light bulbs (the contextualised version) and some got both. In the same exercise some got two problems to solve and some got four problems. Using analysis of variance they then calculate whether the real life version helps learning and whether doing more problems improves learning.

The students with the contextual problem did better than those with the abstract picture, the authors point out another study that found the opposite (Moreno, Reisslein and Ozogul, 2009b). Thos doing 4 problems didn't seem to be better than those doing 2 problems. Presumably its an either you understand it or you dont type of problem.

The experiment design and analysis is probably of more interest than the results since it has components of an instruction piece, several problems and then measurement of the learning,

Predicting STEM Outcomes

Predicting STEM Degree Outcomes Based on Eighth Grade Data and Standard Test Scores, Gilliam M Nicholls, Harvey Wolfe, Mary Besterfield-Sacre, Larry J. Shuman. Journal of Engineering Education ,july 2010 Vol 99 No. 3

This paper looks at the progress of a group of students from eight grade to graduation with STEM degrees over a 12 year period. It starts with 11,320 students of which 740 become STEM graduates. The authors test for 68 variables which cover different measures of performance and motivation, some require an understanding of the US education system. most of the paper is dedicated to outlining and defending the statistical analysis.

The results show significant predictors to be:

Overall maths proficiency
Science quartile
Students ability group for mathematics
Maths grades from grade 6 through to grade 8
ACT(Mathematics)
Scholastic aptitute tests (mathematics)

How far in school parents expect child to go
Father's highest level of education - college or not
How far in school student thinks he/she will get
Race of student - Asian
Race of student African-American

This seems to simply boil down to ability and motivation. The literature review identifies another, possible more interesting study that looks at students expectations of what engineering at University is and how the realism of the expectations effects there motivation to stick with the course. Besterfield-Sacre, Mary, Cynthia J. Atman and Larry J. Schuman. 1997 Characteristics of Freshman engineering students: Models for determining student attrition in engineering, Journal of Engineering Education 86 (2): 139-49

Diffusion of Engineering Education Innovations

Diffusion of Engineering Education Innovations: A Survey of Awareness and Adoption Rates in US Engineering Departments. Maura Borrego, Jeffrey E. Froyd and T. Simin Hall. Journal of Engineering Education July 2010 Vol 99 No. 3

This paper is looking at 7 different 'new' ideas in engineering education and surveys Department Chairs in the US to see if they have heard of them and whether they had tried them. Several random snippets have caught my attention:

What are the new ideas -

1. Student Active Pedagogies - which means having the students do anything in class other than listen to lectures
2. Engineering Learning Communities and Integrated Curricula - Can't really understand what these are but could be Facebook/VLE jobs
3. Artifact Dissection - take the lawnmower apart
4. Summer Bridge Programme - these are pre-university courses
5. Design projects in First Year courses
6. Curriculum based Engineering Service -Learning Projects - I've had a brush with service based learning in Trinidad and it means integrating learning with voluntary community activity.
7. Interdisciplinary Capstone projects

For me at least three of these (1,3 & 7) are quite old ideas

The paper is very solid methodologically and a good example of whats needed for publication. The survey was done using a web survey and got 197 (12 percent) usuable response which is considered to be a reasonable response rate for this type of method.

The overall results are not very interesting there was an average awareness of 82% and an adoption rate of 47% but although the statistics looks robust you have to query how appropriate it is to aggegate these types of response. for example student active pedagogies had a high adoption but could cover a much wider range of possibilities than artifact dissection which works in mech eng as a simple lab but is a lot less useful in other disciplines.

Table 12 is very interesting it has a ranking of the more innovative engineering departments chosen by the respondents:
Rose-Hulman IoT
Purdue
MIT
Carnegie Mellon
Georgia IoT
Franklin W Olin College
Stanford
Harvey Mudd College
North Carolina State
U of Washington
Michigan State
Rowan U
Virginia Tech
Penn State U
UoC Berkeley
Bucknell U
Wocester Polytechnic Institute
Military Academies

Good target list of collaborators.