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LAMP : A Framework for L arge-scale A ddressing of M uddy P oints

LAMP : A Framework for L arge-scale A ddressing of M uddy P oints . 1 - 2 - 3 - 4 - 5 - 6. Mechanism to solicit and respond to student queries in a large class. Rwitajit M ajumdar Sridhar Iyer. CS101 Spring 2013 IIT Bombay . I already know most of what prof is saying.

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LAMP : A Framework for L arge-scale A ddressing of M uddy P oints

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  1. LAMP: A Framework for Large-scale Addressing of Muddy Points 1 - 2 - 3 - 4 - 5 - 6 Mechanism to solicit and respond to student queries in a large class RwitajitMajumdar Sridhar Iyer

  2. CS101 Spring 2013 IIT Bombay I already know most of what prof is saying Batch of 2013

  3. What are the problems to tackle in this scenario? • Students vary in • pre-exposure to subject knowledge • learning styles • cultural background I already know most of what prof is saying How are threads scheduled in multi-core processors? What is a loop control variable? Will two threads that receive the same event, execute simultaneously? Can we make our own blocks in Scratch? How to use a C++ string class variable in a printf statement? Is P=NP? • various active learning strategies • Peer instruction • Just-in-Time-Teaching • Inverted Classroom What are the intuitive solution?

  4. LAMP: A Framework for Large-scale Addressing of Muddy Points Framework - a basic structure underlying a system, concept, or text. Muddy Points (MPs)- instructor typically asks the question ‘what was least clear to you?’ at the end of a class. A student’s response to this question is called a muddy point. G A P mechanisms for soliciting and addressing muddy points, efficiently and effectively in large classroom scenarios. Classification of muddy points Technology assisted mechanism for scaling Graesser and Person Costa et. al. Prior research degree of specification content question-generation mechanism Moodle 15 modules facilitating 7 different teaching learning activities 18 categories

  5. Our Framework

  6. Queries raised in class Queries to instructor outside class Different modes of collection Systematic collection of muddy points Queries posted on Moodle

  7. Categories of muddy points Mechanism to address muddy points 6 categories Advanced Clarification Core Deep Technical skill How are threads scheduled in multi-core processors? What is a loop control variable? Will two threads that receive the same event, execute simultaneously? Can we make our own blocks in Scratch? How to use a C++ string class variable in a printf statement? Is P=NP? Off-Topic

  8. Categories of muddy points Mechanism to address muddy points

  9. reflecting highlighting important MPs or recurring MPs to the whole class

  10. The pilot run • CS101 Spring 2013 IIT Bombay • Course format • Integration of the LAMP framework • Example queries

  11. What did we study in the pilot run? Research Questions (RQ) RQ1: How effective is the LAMP framework? a. For collection of muddy point from students. b. To address the muddy points of students. RQ2: How does the pattern of muddy change as the semester progresses?

  12. How did we study? RQ1a RQ1b RQ2 Methodology instrument sample Analysis Online survey Log Analysis perception of effectiveness of the collection perception of effectiveness of the addressal preference of mode for MPs Tracked logs on Moodle forum }Likert scale ------------Rank order (1st – 4th ) 343 queries 195 b.m.+ 148 b.e. 274 complete 340 responses 450 students Combined Likert scale to 3 group (agreed – neutral – disagreed) Checked distributions of responses % agreed χ2test to check whether one perception influenced other % compositionof categories

  13. Results N=274 (χ2 = 77.26, dof=4, P<0.001) shows that the perception of getting a satisfactory answer depends on the perception of whether they had enough opportunities to ask a query

  14. Rank distribution of each mode of asking MPs

  15. Stratified Attribute Tracking (SAT) Diagram ¾ agreed - agreed

  16. Trends in nature of questioning based on MP categories b.m. before mid-term b.e. before endterm

  17. 68% of students agree that the LAMPprovided them with satisfactory means to pose their MPs. 57% of students agree that their MPs were answered satisfactorily either in class or on forum. 44% Clarification (~1.5x) 71% T a k e a w a y 21% Deep (~0.3x) 7% 4 modes in LAMP integrates the advantages of face to face interaction, anonymous muddy point slips, and online forum, to elicit and address muddy points in a large class.

  18. 68% of students agree that the LAMPprovided them with satisfactory means to pose their MPs. 57% of students agree that their MPs were answered satisfactorily either in class or on forum. 44% Clarification (~1.5x) 71% T a k e a w a y 21% Deep (~0.3x) 7% LAMP: A Framework for Large-scale Addressing of Muddy Points 4 modes in LAMP integrates the advantages of face to face interaction, anonymous muddy point slips, and online forum, to elicit and address muddy points in a large class. Thank you RwitajitMajumdar rwitajit@iitb.ac.inrwitajit@gmail.com www.et.iitb.ac.in/~rwito Sridhar Iyer sri@iitb.ac.in www.it.iitb.ac.in/~sri

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