Math Biology Video Project

Derek Sollberger

Data Analyst
UC Merced

Dr Emily Weigel

Course Instructor
Georgia Tech

Math Biology Video Project

Ecology course (prereq: Intro Bio)
Fall 2018 semester
91 students (85 students in study)
24 videos
- about 10 minutes per video

Learner Profile

math background

mostly sophomores
prior experience in flipped classrooms
mostly White and Asian students
77 percent female

Literature

Fall 2018 Semester

Our first glance at the survey data showed no significant results between the pre and post surveys.

Discretize

We grouped students into “unchanged”, “increase”, or “decrease” groups based on their pre- and post-semester survey results for the MBVI queries—where “unchanged” was a difference of -1, 0, or 1 on the 7-point Likert scales

Math Emotion

MBVI

Math Biology Values Instrument

Video Stats

Do some students stop watching videos across term?

Models

Multiple Views

What influences students to view students multiple times?


Call:
glm(formula = multiple_plays ~ intrigue_cat + fun_cat + appeals_cat + 
    interesting_cat + valuable_cat + important_cat + essential_cat + 
    useful_cat + work_harder_cat + worry_cat + intimidate_cat + 
    easy_hard + complicated_simple + confusing_clear + comfortable_uncomfortable + 
    satisfying_frustrating + challenging_not_challenging + pleasant_unpleasant + 
    chaotic_organized + GPA + pct_math + video_length + video_number, 
    family = "binomial", data = df)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-2.3229  -0.9405  -0.4840   1.0090   2.2857  

Coefficients: (1 not defined because of singularities)
                              Estimate Std. Error z value Pr(>|z|)    
(Intercept)                 -2.764e+00  1.859e+00  -1.487 0.137076    
intrigue_catincrease         1.150e-01  1.302e+00   0.088 0.929576    
intrigue_catdecrease         1.370e+00  1.173e+00   1.168 0.242842    
fun_catincrease             -8.922e-01  5.231e-01  -1.705 0.088116 .  
fun_catdecrease              2.311e+00  7.322e-01   3.156 0.001598 ** 
appeals_catincrease          2.869e-01  6.281e-01   0.457 0.647773    
appeals_catdecrease         -1.698e+00  6.447e-01  -2.634 0.008434 ** 
interesting_catincrease      1.707e+00  6.576e-01   2.595 0.009462 ** 
interesting_catdecrease     -2.212e+00  4.147e-01  -5.334 9.62e-08 ***
valuable_catincrease        -1.199e+00  7.577e-01  -1.582 0.113597    
valuable_catdecrease        -1.618e+01  5.354e+02  -0.030 0.975895    
important_catincrease       -8.767e-01  3.964e-01  -2.212 0.026967 *  
important_catdecrease       -1.594e+01  5.354e+02  -0.030 0.976256    
essential_catincrease       -3.513e-01  4.322e-01  -0.813 0.416374    
essential_catdecrease        1.932e+01  5.354e+02   0.036 0.971210    
useful_catincrease           4.869e-01  4.568e-01   1.066 0.286416    
useful_catdecrease                  NA         NA      NA       NA    
work_harder_catincrease      2.774e-01  2.685e-01   1.033 0.301604    
work_harder_catdecrease     -2.725e-01  4.216e-01  -0.647 0.517945    
worry_catincrease            5.338e-01  3.500e-01   1.525 0.127149    
worry_catdecrease            9.584e-01  3.564e-01   2.689 0.007159 ** 
intimidate_catincrease      -1.419e+00  4.625e-01  -3.068 0.002155 ** 
intimidate_catdecrease      -1.469e+00  3.275e-01  -4.485 7.28e-06 ***
easy_hard3                   1.374e+00  7.488e-01   1.834 0.066603 .  
easy_hard4                   2.940e-01  7.214e-01   0.408 0.683598    
easy_hard5                   1.593e+00  7.100e-01   2.243 0.024890 *  
easy_hard6                  -3.706e-01  8.303e-01  -0.446 0.655323    
easy_hard7                  -1.694e-01  1.037e+00  -0.163 0.870239    
complicated_simple          -6.506e-01  1.773e-01  -3.671 0.000242 ***
confusing_clear              2.877e-01  1.620e-01   1.776 0.075785 .  
comfortable_uncomfortable   -3.927e-01  1.298e-01  -3.026 0.002476 ** 
satisfying_frustrating       2.317e-01  1.159e-01   1.999 0.045608 *  
challenging_not_challenging -1.322e-01  1.641e-01  -0.805 0.420689    
pleasant_unpleasant          7.729e-01  1.475e-01   5.239 1.62e-07 ***
chaotic_organized            3.058e-01  9.865e-02   3.100 0.001935 ** 
GPA                          2.159e-01  4.056e-01   0.532 0.594511    
pct_math                    -3.338e-03  3.305e-03  -1.010 0.312373    
video_length                 1.076e-04  1.861e-04   0.578 0.563013    
video_number                -4.326e-02  1.217e-02  -3.555 0.000378 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 1198.6  on 867  degrees of freedom
Residual deviance: 1000.0  on 830  degrees of freedom
  (1089 observations deleted due to missingness)
AIC: 1076

Number of Fisher Scoring iterations: 12

Viewing multiple times is encouraged by

It is fun (decrease) to use math to understand biology
Using math to understand biology is interesting (increase)
I worry (decrease) about getting worse grades in a biology course that incorporates math than one that does not
pleasant versus unpleasant
chaotic versus organized

Viewing multiple times is discouraged by

Using math to understand biology appeals (decrease) to me
Using math to understand biology is interesting (decrease)
It is important (increase) for me to be able to do math for my career in the life sciences
Taking a biology course that incorporates math intimidates (both) me
complicated versus simple
comfortable versus uncomfortable
satisfying versus frustrating
time in semester (video number)

Viewing Time

What influences students to spend more time watching the videos?


Call:
glm(formula = as.numeric(avg_view_time_when_played) ~ intrigue_cat + 
    fun_cat + appeals_cat + interesting_cat + valuable_cat + 
    important_cat + essential_cat + useful_cat + work_harder_cat + 
    worry_cat + intimidate_cat + easy_hard + complicated_simple + 
    confusing_clear + comfortable_uncomfortable + satisfying_frustrating + 
    challenging_not_challenging + pleasant_unpleasant + chaotic_organized + 
    GPA + pct_math + video_length + video_number, family = "gaussian", 
    data = df)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-853.86  -128.02   -24.41   108.91  1139.41  

Coefficients: (1 not defined because of singularities)
                             Estimate Std. Error t value Pr(>|t|)    
(Intercept)                  180.5561   176.8864   1.021 0.307672    
intrigue_catincrease         153.1457   116.2658   1.317 0.188134    
intrigue_catdecrease         328.5588   104.4253   3.146 0.001712 ** 
fun_catincrease                2.3447    48.3834   0.048 0.961360    
fun_catdecrease              -40.4265    74.1309  -0.545 0.585667    
appeals_catincrease          -22.9577    56.2257  -0.408 0.683149    
appeals_catdecrease           28.4891    66.2874   0.430 0.667466    
interesting_catincrease       85.8513    60.3164   1.423 0.155011    
interesting_catdecrease       -6.5632    41.9026  -0.157 0.875575    
valuable_catincrease        -153.6194    72.3949  -2.122 0.034136 *  
valuable_catdecrease        -872.1688   246.4276  -3.539 0.000424 ***
important_catincrease        -16.3917    39.5645  -0.414 0.678758    
important_catdecrease       -842.0904   255.4479  -3.297 0.001020 ** 
essential_catincrease         78.0939    41.2858   1.892 0.058900 .  
essential_catdecrease        826.7246   268.3537   3.081 0.002133 ** 
useful_catincrease           -28.3670    41.7338  -0.680 0.496876    
useful_catdecrease                 NA         NA      NA       NA    
work_harder_catincrease      -14.9730    27.3546  -0.547 0.584274    
work_harder_catdecrease       36.4671    38.6517   0.943 0.345711    
worry_catincrease             13.4219    37.2188   0.361 0.718474    
worry_catdecrease             -2.8790    35.4262  -0.081 0.935249    
intimidate_catincrease        -2.7321    45.7014  -0.060 0.952344    
intimidate_catdecrease        33.5371    32.8474   1.021 0.307552    
easy_hard3                   -34.3803    74.1131  -0.464 0.642848    
easy_hard4                   -25.4733    71.6178  -0.356 0.722167    
easy_hard5                   -26.0246    69.5317  -0.374 0.708289    
easy_hard6                  -100.2542    82.3422  -1.218 0.223748    
easy_hard7                   221.9490    96.7221   2.295 0.021999 *  
complicated_simple           -21.7275    17.1182  -1.269 0.204705    
confusing_clear               31.3572    16.0778   1.950 0.051472 .  
comfortable_uncomfortable     28.3085    13.1634   2.151 0.031801 *  
satisfying_frustrating       -20.8471    12.0115  -1.736 0.083008 .  
challenging_not_challenging  -17.2412    16.4447  -1.048 0.294744    
pleasant_unpleasant           -0.3234    14.5043  -0.022 0.982217    
chaotic_organized            -19.1039     9.7751  -1.954 0.050996 .  
GPA                           61.4313    39.0669   1.572 0.116225    
pct_math                       0.1931     0.3323   0.581 0.561199    
video_length                   0.2106     0.0188  11.204  < 2e-16 ***
video_number                   3.1522     1.2089   2.607 0.009288 ** 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for gaussian family taken to be 51216.36)

    Null deviance: 59330647  on 867  degrees of freedom
Residual deviance: 42509579  on 830  degrees of freedom
  (1089 observations deleted due to missingness)
AIC: 11915

Number of Fisher Scoring iterations: 2

Viewing time is encouraged by

Using math to understand biology intrigues (decrease) me
comfortable versus uncomfortable
time in semester (video number)

Viewing time is discouraged by

Math is valuable (both) for me for my life science career
It is important (decrease) for me to be able to do math for my career in the life sciences

Take Home Messages

Students who viewed videos multiple times and/or for longer duration were

more pessimistic about math emotions
worried less about their course grade
not affected by the proportion of math content

Thank You

Derek Sollberger

Data Analyst
UC Merced
dsollberger@ucmerced.edu

Dr Emily Weigel

Course Instructor
Georgia Tech
emily.weigel@biosci.gatech.edu