This sheet presents results of the experiment conducted with two classrooms and aiming to show the effect in terms of learning outcome of the use of augmented reality in a task where learners had to understand basic optic principles related to IR sensors of Thymio.
The source code of this analysis is online here : [https://github.com/WafaJohal/RAnalysis_Thymio_AR_Optique.git]
The results can be see rendered here : [http://rpubs.com/wafajohal/286557]
In average across all the sessions
## concept_id condition N C_Score sd se ci
## 1 C1 WO_AR 45 0.4666667 0.4183300 0.06236096 0.1256802
## 2 C1 AR 42 0.6250000 0.4356450 0.06722149 0.1357565
## 3 C2 WO_AR 45 0.5666667 0.4343229 0.06474503 0.1304850
## 4 C2 AR 42 0.4761905 0.4410683 0.06805831 0.1374466
## 5 C3 WO_AR 45 0.2222222 0.3445096 0.05135646 0.1035021
## 6 C3 AR 42 0.2857143 0.3969493 0.06125060 0.1236981
## 7 C4 WO_AR 45 0.4500000 0.3616740 0.05391518 0.1086589
## 8 C4 AR 42 0.4107143 0.3508569 0.05413839 0.1093347For each session
## concept_id condition Session N C_Score sd se
## 1 C1 WO_AR 1 15 0.06666667 0.2581989 0.06666667
## 2 C1 WO_AR 2 15 0.55000000 0.3803194 0.09819805
## 3 C1 WO_AR 3 15 0.78333333 0.2288689 0.05909368
## 4 C1 AR 1 14 0.28571429 0.4688072 0.12529400
## 5 C1 AR 2 14 0.69642857 0.3559734 0.09513788
## 6 C1 AR 3 14 0.89285714 0.2129077 0.05690196
## 7 C2 WO_AR 1 15 0.33333333 0.4879500 0.12598816
## 8 C2 WO_AR 2 15 0.50000000 0.2672612 0.06900656
## 9 C2 WO_AR 3 15 0.86666667 0.3518658 0.09085135
## 10 C2 AR 1 14 0.07142857 0.2672612 0.07142857
## 11 C2 AR 2 14 0.50000000 0.2773501 0.07412493
## 12 C2 AR 3 14 0.85714286 0.3631365 0.09705232
## 13 C3 WO_AR 1 15 0.06666667 0.2581989 0.06666667
## 14 C3 WO_AR 2 15 0.20000000 0.2455961 0.06341265
## 15 C3 WO_AR 3 15 0.40000000 0.4309458 0.11126973
## 16 C3 AR 1 14 0.14285714 0.3631365 0.09705232
## 17 C3 AR 2 14 0.14285714 0.2154021 0.05756862
## 18 C3 AR 3 14 0.57142857 0.4322189 0.11551536
## 19 C4 WO_AR 1 15 0.20000000 0.4140393 0.10690450
## 20 C4 WO_AR 2 15 0.51666667 0.1997022 0.05156288
## 21 C4 WO_AR 3 15 0.63333333 0.3034197 0.07834262
## 22 C4 AR 1 14 0.07142857 0.2672612 0.07142857
## 23 C4 AR 2 14 0.51785714 0.2679029 0.07160007
## 24 C4 AR 3 14 0.64285714 0.2251034 0.06016142
## ci
## 1 0.1429858
## 2 0.2106139
## 3 0.1267433
## 4 0.2706812
## 5 0.2055329
## 6 0.1229292
## 7 0.2702177
## 8 0.1480043
## 9 0.1948568
## 10 0.1543120
## 11 0.1601372
## 12 0.2096688
## 13 0.1429858
## 14 0.1360066
## 15 0.2386498
## 16 0.2096688
## 17 0.1243694
## 18 0.2495558
## 19 0.2292873
## 20 0.1105914
## 21 0.1680282
## 22 0.1543120
## 23 0.1546825
## 24 0.1299708Is AR significantly different than WO_AR for the concept considered?
summary(aov(C_Score ~ condition))## Df Sum Sq Mean Sq F value Pr(>F)
## condition 1 0.05 0.04603 0.267 0.606
## Residuals 346 59.62 0.17230summary(aov(C_Score ~ Session))## Df Sum Sq Mean Sq F value Pr(>F)
## Session 2 17.56 8.779 71.93 <2e-16 ***
## Residuals 345 42.10 0.122
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(aov(C_Score ~ concept_id))## Df Sum Sq Mean Sq F value Pr(>F)
## concept_id 3 4.58 1.5251 9.524 4.66e-06 ***
## Residuals 344 55.09 0.1601
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1summary(aov(C_Score ~ group_id))## Df Sum Sq Mean Sq F value Pr(>F)
## group_id 1 0.09 0.08862 0.515 0.474
## Residuals 346 59.57 0.17218summary(aov(C_Score ~ condition*Session*concept_id))## Df Sum Sq Mean Sq F value Pr(>F)
## condition 1 0.05 0.046 0.434 0.5106
## Session 2 17.56 8.779 82.715 < 2e-16 ***
## concept_id 3 4.58 1.525 14.370 8.21e-09 ***
## condition:Session 2 0.13 0.064 0.604 0.5475
## condition:concept_id 3 0.80 0.266 2.505 0.0591 .
## Session:concept_id 6 1.66 0.276 2.602 0.0178 *
## condition:Session:concept_id 6 0.51 0.086 0.807 0.5647
## Residuals 324 34.39 0.106
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1