Preparing non-traditional students for engineering degrees
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A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Engineering employment in Australia is cyclic in nature. Australian Government reports indicate that in the past five years there has been a threefold increase in the average number of candidates for engineering positions and a doubling in the proportion of vacancies filled. Until relatively recently there was a surplus in engineering positions; making engineering an attractive career option for students. Students tend to decide on their study direction based on the present economic climate, thus the present downturn in the resource sector and the reduction of engineering positions may result in another shortage of engineering graduates in five years' time. Previous shortages in qualified engineers, combined with the Australian Government's widening participation agenda, have attracted many non-traditional students to pursue engineering degrees. The number of non-traditional students entering the Bachelor of Engineering at Central Queensland University has more than doubled between 2011 and 2014. As engineering bachelor degrees have mathematics prerequisites or assumed knowledge, non-traditional students use enabling programmes to gain entry into these degrees at Central Queensland University. In this study we examine the effectiveness of enabling mathematics units preparing non-traditional students for a bachelor of engineering degree. References N. Adams, A. Dekkers, and S. Elliott. Supportive frameworks that increase mathematical knowledge and confidence in students enrolled in bridging mathematics courses. In Proc. Int. Conf. Mathematics, Science and Technology Education, Kruger National Park, South Africa, 2012. University of South Africa. http://hdl.cqu.edu.au/10018/928333. N. Adams and C. Hayes. Does teaching with a tablet pc enhance the teaching experience and provide greater flexibility. 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Austral. 6:74–80, 1997. http://www.aair.org.au/articles/volume-6-no-2/6-2-how-do-rural-students-choose-their-higher-education-institutions-two-regional-australian-cases M. Brueckner, A. Durey, R. Mayes, and C. Pforr. The mining boom and Western Australia's changing landscape: Towards sustainability or business as usual? Rural Society, 22(2):111–124, 2013. doi:10.5172/rsj.2013.22.2.111. Central Queensland University, Australia. Student demographics. CQUniversity Intranet, 2015. G. E. Davis and M. A. McGowen. Formative feedback and mindful teaching of undergraduate mathematics. In Proc. 30th Conf. Int. Group Psychology of Mathematics Education, 241, 2006. http://www.cees.mak.ac.ug/sites/default/files/ED496931.pdf. Department of Employment. Labour market information portal, 2015. http://lmip.gov.au/default.aspx?LMIP. S. Doyle. STEPS: Celebrating 20 Years 1986–2006. Technical Report, Central Queensland University, 2006. http://hdl.cqu.edu.au/10018/1013477 T. Drewes and C. Michael. 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Labour Market Research, and Analysis Branch, Department of Employment. Labour market reserch–-engineering professions. Technical Report, 2015 https://docs.employment.gov.au/system/files/doc/other/ausengineeringprofessions.pdf. G. S. May and D. E. Chubin. A retrospective on undergraduate engineering success for underrepresented minority students. J. Engineer. Edu., 92(1):27–39, 2003. doi:10.1002/j.2168-9830.2003.tb00735.x. B. McDonald and D. Boud. The impact of self-assessment on achievement: The effects of self-assessment training on performance in external examinations. Assess. Edu.: Principles, Policy, Practice, 10(2):209–220, 2003. doi:10.1080/0969594032000121289. G. A. Miller. The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychol. Rev. 101(2):343, 1994. doi:10.1037/0033-295x.101.2.343. A. Porter and S. Denny. Building leadership capacity for development and sharing of mathematics learning resources across disciplines and universities. Technical Report, 2013. http://www.olt.gov.au/project-building-leadership-capacity-uow-2007. D. Robson, W. Abell, and T. Boustead. Scaffolding for learning equation solving. In Crossing divides. Proc. 32nd Ann. Conf. Mathematics Education Research Group of Australasia. Palmerston North, NZ, 2009. http://www.merga.net.au/node/38?year=2009. TechSmith Corporation. Camtasia studio version 8.6.0, 2015. https://www.techsmith.com. V. Validakis. Australia entering phase three of mining boom, 75,000 jobs to be cut. Australian Mining, July 2014. https://australianmining.com.au/news/australia-entering-phase-three-of-mining-boom-75000-jobs-to-be-cut-2/. J. J. van Merrienboer and J. Sweller. Cognitive load theory and complex learning: Recent developments and future directions. Edu. Psychol. Rev. 17(2):147–177, 2005. doi:10.1007/s10648-005-3951-0.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it