1 resultado para Bayesian inference, Behaviour analysis, Security, Visual surveillance
em Digital Commons - Montana Tech
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Resumo:
Part I What makes science hard for newcomers? 1) The background (briefly) of my research - (why the math anxiety model doesn’t fit) 2) The Tier analysis (a visual) – message: there are many types of science learners in your class than simply younger versions of yourself 3) Three approaches (bio, chem, physics) but only one Nature 4) The (different) vocabularies of the three Sciences 5) How mathematics is variously used in Science Part II Rules and rules-driven assignments- lQ vs OQ1) How to incorporate creativity into assignments and tests? 2) Tests- borrowing “thought questions" from other fields (If Columbus hadn't discovered the new World, when and under whose law would it have been discovered?) 3) Grading practices (partial credit, post-exam credit for finding and explaining nontrivial errors 4) Icing on the cake – applications, examples of science/engineering from Tuesdays NY Times Part III Making Change at the Departmental Level 1) Taking control of at least some portion of the curriculum 2) Varying style of presentation 3) Taking control of at least some portion of the exams 4) GRADING pros and cons of grading on a curve 5) Updating labs and lab reporting.