AI-based Learning Assistants: Enhancing Math Learning for Migrant Students in German Schools

被引:0
|
作者
Kretzschmar, Vivian [1 ]
Seitz, Jurgen [1 ]
机构
[1] Stuttgart Media Univ, Inst Appl Artificial Intelligence IAAI, Stuttgart, Germany
关键词
AI; AI learning assistant; AI education; video-based learning; self-learning; migration; migrant students; TUTORIALS;
D O I
10.1109/CAI59869.2024.00035
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Increasing migration leads the education landscape to face the challenge of integrating children into the school system, accounting for inherent disadvantages. On average, as nearly half of them face socio-economic disadvantages, a persistent performance disparity was observed compared to domestic students. Remarkably, even after mitigating the influence of socioeconomic status, immigrant students' scores remained inferior. From March to May 2023, the AI Education (AIEDN) research project investigated how an AI-based learning assistant can compensate for existing impediments by enabling a better understanding through video-based learning. For this study, 275 students were selected from two secondary schools (N=137) and two grammar schools (N=138) in Baden-Wurttemberg, Germany. The experiment tested the extent to which learners solve more tasks, build broader (transfer) knowledge, and retain it. Students were repeatedly tested on mathematical problems, where the control group did not have access to the AI assistant. In contrast, the other group used the AI assistant to solve the problems. The students' performances from both school groups were statistically tested using t-tests. Within the test group of grammar schools, a significant change in the results between the two test days existed (T(41)=-2,28; p<.01) when the AI tool was used. In contrast, the control group showed no significant change T(37)=-.42; p>.05; d=.07) in performance. However, the results were insignificant for the secondary school students, as the given tasks and video content were considered too demanding. Further research is needed to determine AIEDN's performance for other target groups.
引用
收藏
页码:144 / 149
页数:6
相关论文
共 50 条
  • [41] Perceived value of AI-based recommendations service: the case of voice assistants
    Akdim, K.
    Casalo, Luis V.
    SERVICE BUSINESS, 2023, 17 (01) : 81 - 112
  • [42] Assessing Factors Influencing Customers' Adoption of AI-Based Voice Assistants
    Choudhary, Surbhi
    Kaushik, Neeraj
    Sivathanu, Brijesh
    Rana, Nripendra P.
    JOURNAL OF COMPUTER INFORMATION SYSTEMS, 2024,
  • [43] Perceived value of AI-based recommendations service: the case of voice assistants
    K Akdim
    Luis V. Casaló
    Service Business, 2023, 17 : 81 - 112
  • [44] AI-based Interactive Digital Assistants for Virtual Reality in Educational Contexts
    McKern, Arelia
    Mayer, Anjela
    Greif, Lucas
    Chardonnet, Jean-Remy
    Ovtcharova, Jivka
    2024 IEEE 3RD GERMAN EDUCATION CONFERENCE, GECON 2024, 2024,
  • [45] An AI-Based Deep Learning with K-Mean Approach for Enhancing Altitude Estimation Accuracy in Unmanned Aerial Vehicles
    Piyakawanich, Prot
    Phasukkit, Pattarapong
    DRONES, 2024, 8 (12)
  • [46] An AI-based Approach for Grading Students' Collaboration
    Tomic, Bojan B.
    Kijevcanin, Anisja D.
    Sevarac, Zoran, V
    Jovanovic, Jelena M.
    IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES, 2023, 16 (03): : 292 - 305
  • [47] AI for AI-based intrusion detection as a service: Reinforcement learning to configure models, tasks, and capacities
    Lin, Ying-Dar
    Huang, Hao-Xuan
    Sudyana, Didik
    Lai, Yuan-Cheng
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2024, 229
  • [48] Mobile math: Math educators and students engage in mobile learning
    Franklin T.
    Peng L.-W.
    Journal of Computing in Higher Education, 2008, 20 (2) : 69 - 80
  • [49] Enhancing Investors' Decision-Making - an Interdisciplinary AI-Based Case Study for Accounting Students
    Stancheva-Todorova, Eleonora
    Bogdanova, Boryana
    APPLICATIONS OF MATHEMATICS IN ENGINEERING AND ECONOMICS (AMEE20), 2021, 2333