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
Monday, September 20, 2010
Sunday, September 19, 2010
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,
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,
Saturday, September 18, 2010
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
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
Friday, September 17, 2010
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 -
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.
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 -
- Student Active Pedagogies - which means having the students do anything in class other than listen to lectures
- Engineering Learning Communities and Integrated Curricula - Can't really understand what these are but could be Facebook/VLE jobs
- Artifact Dissection - take the lawnmower apart
- Summer Bridge Programme - these are pre-university courses
- Design projects in First Year courses
- 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.
- 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.
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