Picking Distractors For Multiple Choice Questions-PDF Free Download

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Picking Distractors for Multiple Choice Questions

Picking Distractors for Multiple Choice Questions

distractors for multiple choice questions in Maple T.A. Distractors should highlight common student mistakes This is the most fundamental rule of creating multiple choice questions. It may sound obvious, but it is commonly overlooked: distractors should represent actual incorrect results you would expect students to produce.

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Multiple-Choice Models: The Distractors

Multiple-Choice Models: The Distractors

Multiple-Choice Models: The Distractors Are Also Part of the Item David Thissen University of Kansas Lynne Steinberg Indiana University and Anne R. Fitzpatrick CTB/McGraw-Hill This paper describes an item response model for multiple-choice items and illustrates its application in item analysis. The model provides parametric and graphical summaries of the performance of each alternative ...

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An Automated Picking Workstation for Healthcare Applications

An Automated Picking Workstation for Healthcare Applications

An Automated Picking Workstation for Healthcare Applications ... Multiple instances and distractors: while in other image processing and computer vision applications the basic objective is to identify the single best instance of the target/query object, with pick-and-place applications the aim is not just to classify the first (or best) instance but to determine the locations, orientations and ...

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arXiv:1706.03285v2 [cs.CV] 15 Aug 2018

arXiv:1706.03285v2 [cs.CV] 15 Aug 2018

with cluttered background, the 2nd is interested in multi-instance, the 3rd has scenes with severely occluded objects, the 4th re ects the challenges found in bin-picking scenarios, and the 5th is related to similar-looking distractors. results tackling the aforesaid challenges in 6D. This improvement is of great

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Multi-Task Deep Networks for Depth-Based 6D Object Pose ...

Multi-Task Deep Networks for Depth-Based 6D Object Pose ...

occlusion, clutter, and similar-looking distractors. Most existing methods are, however, for single isolated object instances, while some recent methods tackle crowd scenarios as post-refinement which accounts multiple object relations. In this paper, we address recovering 6D poses of multiple instances in bin-picking scenarios in depth modality by multi-task learning in deep neural networks ...

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Tracking multiple targets with multifocal attention

Tracking multiple targets with multifocal attention

Tracking multiple targets with multifocal attention Patrick Cavanagh and George A. Alvarez Department of Psychology, Harvard University, 33 Kirkland Street, Cambridge, MA 02138, USA Attention allows us to monitor objects or regions of visual space and selectinformation fromthem for report or storage. Classical theories of attention assumed a single focus of selection but many everyday ...

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Multi-Task Deep Networks for Depth-Based 6D Object Pose ...

Multi-Task Deep Networks for Depth-Based 6D Object Pose ...

6D Object Pose and Joint Registration in Crowd Scenarios Juil Sock 1 [email protected] Kwang In Kim2 [email protected] Caner Sahin1 [email protected] Tae-Kyun Kim1 [email protected] Imperial Computer Vision and Learning Lab (ICVL), Imperial College, London, UK 2 Department of Computer Science, Uni-versity of Bath, Bath, UK Abstract In bin-picking scenarios, multiple ...

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Reaching for the unknown: Multiple target encoding and ...

Reaching for the unknown: Multiple target encoding and ...

Reaching for the unknown: Multiple target encoding and real-time decision-making in a rapid reach task Craig S. Chapmana,1, Jason P. Gallivanb,1, Daniel K. Woodb, Jennifer L. Milneb, Jody C. Culhama,b, Melvyn A. Goodalea,b,* a Department of Psychology, University of Western Ontario, London, Ontario, Canada N6A 5C2 bNeuroscience Program, University of Western Ontario, London, Ontario, Canada ...

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Recovering 6D Object Pose: A Review and Multi-modal Analysis

Recovering 6D Object Pose: A Review and Multi-modal Analysis

Recovering 6D Object Pose: A Review and Multi-modal Analysis Caner Sahin and Tae-Kyun Kim ICVL, Imperial College London Abstract. A large number of studies analyse object detection and pose estimation at visual level in 2D, discussing the effects of challenges such as occlusion, clutter, texture, etc., on the performances of the methods, which work in the context of RGB modality. Interpreting ...

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How can we develop multiple choice items that support ...

How can we develop multiple choice items that support ...

How can we develop multiple choice items that support assessment for learning? Bård Vinje, Olav Dalsegg Tokle and Grethe Ravlo AEA-conference 10.11.2018 . Overview • Background - national tests and MC • Research on MC • Our development process • Analysis of our MC-items. National tests in Numeracy (applied mathematics) • Item – Test – Teacher Support Material - Analysis ...

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On-Line Selection of Discriminative Tracking Features

On-Line Selection of Discriminative Tracking Features

On-Line Selection of Discriminative Tracking Features Robert Collins and Yanxi Liu (and later, Marius Leordeanu) ICCV 2003. CSE598G Collins Classification-based Tracking training frame test frame foreground background Classifier train a classifier label pixels F B B B. CSE598G Collins Observation Explicitly seek features that best discriminate between object and background samples ...

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