Otwarty dostęp

A Study of Goal Motivation Strategies Based on Dynamic Planning Methods to Enhance the Effectiveness of Public English Teaching in Universities

Xiaoli Huang

Xiaoli Huang

College of Literature, History and Culture, Longdong UniversityQingyang, China
Wyszukaj tego autora
Sciendo|Google Scholar
Huang, Xiaoli
  
26 wrz 2025
A Study of Goal Motivation Strategies Based on Dynamic Planning Methods to Enhance the Effectiveness of Public English Teaching in Universities's Cover Image
O artykule
Poprzedni artykuł
Następny artykuł
Zacytuj
Pobierz okładkę
Data publikacji: 26 wrz 2025
Otrzymano: 07 sty 2025
Przyjęty: 05 maj 2025
DOI: https://doi.org/10.2478/amns-2025-1077
Słowa kluczowe
© 2025 Xiaoli Huang, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

Forgetting module structure
Forgetting module structure

Figure 2.

RL4ALPR framework
RL4ALPR framework

Figure 3.

A2C structure
A2C structure

Figure 4.

Visualization of knowledge state change of two students
Visualization of knowledge state change of two students

Figure 5.

Logical evaluation results of path learning based on expert scores
Logical evaluation results of path learning based on expert scores

Figure 6.

Learning path length affects validation
Learning path length affects validation

Figure 7.

Learning path for completing_the_square_1 given by different methods
Learning path for completing_the_square_1 given by different methods

Comparison of Ep results

Model KSE KEE
KNN 0.000812 0.268027
GRU4Rec 0.007819 0.210638
MC-10 0.123466 0.002347
MC-50 0.112548 -0.005241
DQN 0.105724 0.002795
CN-Random 0.281973 0.140437
Cog 0.172039 0.175481
RL4ALPR 0.354762 0.412704

Experimental results of 8 models on 2 datasets

Model ASSIST15 ASSISTO9
AUC F1-Score AUC F1-Score
DKT 0.6673 0.4834 0.7128 0.6539
CKT 0.7142 0.4917 0.7345 0.6751
ContextKT 0.7125 0.4562 0.7684 0.6958
DKVMN 0.7153 0.5275 0.7628 0.6954
SPARSEKT 0.7121 0.4932 0.7625 0.6843
GKT 0.7156 0.5124 0.7758 0.7051
SKT 0.7311 0.5428 0.7647 0.6954
FDKT-ED 0.7558 0.6647 0.7932 0.7204

Independent sample t-test of students’ scores

Levin’s test for equality of variances T-test
Assuming F Sig. t df Sig.(2-tailed) 95% confidence interval of the difference
Lower limit Upper limit
Reading Equal variances 0.284 0.615 8.726 163 0.001 4.728 7.476
Unequal variances 8.742 161.829 0.001 4.728 7.476
Composition Equal variances 31.628 0.000 3.018 163 0.004 0.548 2.604
Unequal variances 3.026 131.584 0.004 0.552 2.603
Translation Equal variances 21.204 0.001 3.159 163 0.003 0.819 3.874
Unequal variances 3.167 139.715 0.003 0.821 3.862
Total points Equal variances 0.054 0.849 4.342 163 0.002 12.728 31.485
Unequal variances 4.341 162.758 0.002 12.756 31.486

Descriptive statistics of students’ scores in each item of the examination paper

Class Number Average score Standard deviation Standard error of mean value
Reading Experimental class 82 18.54 4.483 0.524
Control class 83 12.51 4.325 0.482
Composition Experimental class 82 14.52 2.427 0.271
Control class 83 13.25 4.136 0.464
Translation Experimental class 82 12.96 3.729 0.418
Control class 83 10.87 5.804 0.641
Total points Experimental class 82 65.13 7.418 0.829
Control class 83 51.52 14.213 1.514
Język:
Angielski
Częstotliwość wydawania:
1 razy w roku
Dziedziny czasopisma:
Nauki biologiczne, Nauki biologiczne, inne, Matematyka, Matematyka stosowana, Matematyka ogólna, Fizyka, Fizyka, inne
Kanał RSS czasopisma