Student Assessment (Written Assessment)

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# Learning Objects Difficulty Media Type Version Price
1
Contextualizing assessment
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2
Hierarchy of Bloom’s taxonomy
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3
Assessing facts vs application
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4
Example of recall & application
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5
Challenges of writing basic science questions
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6
SBA structure
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7
MEQ structure
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8
Steps of developing an MEQ
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9
Effect of images in MCQs
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10
Item writing flaws of MCQs
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11
Strengths and weaknesses of SBAs & EMIs
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12
Number of options in an SBA
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13
Modified essay questions (MEQs)
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14
Purpose and process of workplace-based assessments
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15
Direct observation of procedural skills (DOPS) assessment form
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16
Sources of evidence for portfolios
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17
Progress test
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18
Assessment of recall vs application
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19
Neurobiological basis of test enhanced assessment
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20
How to overcome the harmful effects of test enhanced learning
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21
Overcoming inter-rater variability in mini-CEX
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22
Steps of constructing an MEQ
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23
Writing different types of MEQs using the same scenario
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24
Different types of MEQs
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25
Single best answer MCQ submission form with checklist
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26
MCQ writing best practices: front loading and cover testing
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27
Examples of good and bad options of SBAs
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28
Examples of good and bad lead-ins in SBAs
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29
Examples of SBAs assessing different cognitive levels
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30
Structure of an SBA-type MCQ
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31
SBA item writing flaws related to irrelevant item difficulty
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32
Common imprecise terms used in MCQs
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33
SBA item writing flaws that would aid the test-wise candidate
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34
Good Practices in Assessment Matters (Dos and Don’ts)
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35
Guidelines on Completion and Passing of Clinical Postings
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36
Recommended Guidelines on Mini-CEX
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37
OSCE Guidelines for AY19/20 onwards
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38
Borderline Regression Method (Video)
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39
Programmatic assessment by Cees van der Vleuten
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40
What is programmatic assessment? By Maastricht University
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41
Ottawa 2020 consensus statement for programmatic assessment - Part 1
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42
Ottawa 2020 consensus statement for programmatic assessment – Part 2
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43
Programmatic assessment: From assessment of learning to assessment for learning
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44
Introduction & Background
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45
Statistics, Do's & Don't, Comments & Flags
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46
Programmatic assessment: From assessment of learning to assessment for learning
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47
Generalisability Theory Overview
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48
Generalizability theory for the perplexed: A practical introduction and guide: AMEE Guide No. 68
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49
G theory made simple
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50
RASCH - why, when and how
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51
Item analysis video
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52
Forms used for WPBA
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53
Introduction & Background
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54
2023 Admissions Statistics
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55
The process of developing a rubric to assess the cognitive complexity of student-generated MCQs
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56
Item Writing Guide
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