from __future__ import division
import random
class Drop():
    def __init__(self, r=1):
        self.x = (.5 - random.random()) * 2 * r
        self.y = (.5 - random.random()) * 2 * r
        self.incircle = (self.y) ** 2 + (self.x) ** 2 <= (r) ** 2

N = 10000
print 4 * len([k for k in range(N) if Drop().incircle]) / N
                    

• Python
• Sagemath
• LaTeX

Lab Sheets

Class meeting

Completion of ticks

“ Active learning increases student performance in science, engineering, and mathematics ”

Freeman et al. 2014

“ Other-rated personality and academic performance: evidence and implications ”

Poropat et al. 2015

1. Agreeableness
2. Extraversion
3. Neuroticism
4. Conscientiousness
5. Openness1
6. Openness2

Call:
lm(formula = Average_Mark_Other_Modules ~ Conscientiousness,
    data = Factors_with_marks)

Residuals:
    Min      1Q  Median      3Q     Max
-31.566  -8.448   1.575   8.652  31.377

Coefficients:
                  Estimate Std. Error t value Pr(>|t|)
(Intercept)         62.668      1.345   46.60   <2e-16 ***
Conscientiousness    3.075      1.366    2.25   0.0271 *
                    

Call:
lm(formula = CfM_Total ~ Openness1, data = Factors_with_marks)

Residuals:
    Min      1Q  Median      3Q     Max
-35.128  -7.733   0.497  10.046  22.899

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)   78.225      1.448  54.025  < 2e-16 ***
Openness1      4.474      1.533   2.918  0.00458 **
                    

So what?

1. Scaffolding.
2. Interest.
3. Perhaps: this pedagogic approach incentives deep learning.

Focus groups

“ I think it’s just a module that you get out of it what you put in, so all of us round this table, clearly put plenty in. ”

Tutor I

Summary

• Large flipped class.
• Research in to effect of personality of performance.
• Not leaving anyone behind.

+VincentKnight
@drvinceknight
www.vincent-knight.com

@Imogen_Dunne

vincent-knight.com/Talks/