Learning engineering: Difference between revisions

Revision as of 17:55, 2 November 2020

Revision as of 18:19, 2 November 2020

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The multidisciplinary nature of learning engineering creates challenges. The problems that learning engineering attempts to solve often require expertise in diverse fields such as [[software engineering]], [[instructional design]], [[___domain knowledge]], [[pedagogy]]/[[andragogy]], [[psychometrics]], [[learning sciences]], [[data science]], and [[systems engineering]]. In some cases, an individual “learning engineer” with expertise in multiple disciplines might be sufficient. However, learning engineering problems often exceed any one person’s ability to solve.

Each discipline brings its own metaphors and use of figurative language. Often a term or metaphor is carries a different meaningsmeaning for professionals or academics from different domains. At times a term that is used positively in one ___domain carries a strong negative perception in another ___domain.<ref>{{Cite document|date=2020|last1=Chandler|first1=Chelsea|last2=Kessler|first2=Aaron|last3=Fortman|first3=Jacob|title=Language Matters:Exploring the Use of Figurative Language at ICICLE 2019 {{!}} IEEE IC Consortium on Learning Engineering {{!}} Proceedings of the 2019 Conference on Learning Engineering|url=http://sagroups.ieee.org/icicle/wp-content/uploads/sites/148/2020/07/ICICLE_Proceedings_Learning-Engineering.pdf}}</ref>

== See also ==

* [[Learning sciences]]