Finger pointing to support learning from split-attention examples

被引:5
|
作者
Zhang, Shirong [1 ,3 ]
de Koning, Bjorn B. [1 ]
Paas, Fred [1 ,2 ]
机构
[1] Erasmus Univ, Dept Psychol Educ & Child Studies, Rotterdam, Netherlands
[2] Univ Wollongong, Sch Educ Early Start, Wollongong, Australia
[3] Erasmus Univ, Erasmus Sch Social & Behav Sci, Dept Psychol Educ & Child Studies, Burgemeester Oudlaan 50, NL-3062 PA Rotterdam, Netherlands
关键词
Cognitive load theory; self-management effect; split-attention effect; finger pointing; COGNITIVE-LOAD; WORKED EXAMPLES; MEMORY; PERFORMANCE; EFFICIENCY; POWER;
D O I
10.1080/01443410.2023.2193696
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
We investigated whether finger pointing is an effective cognitive-load self-management strategy to mitigate the split-attention effect during learning. This effect holds that learning from split-attention examples consisting of spatially separated, but mutually referring text and picture, is less effective than learning from equivalent spatially integrated sources. One-hundred-and-twenty-nine undergraduates studied a picture with accompanying text about the nephron in a between-subjects design with the factors strategy use (pointing vs. no pointing) and instructional format (split-attention vs. integrated). The split-attention effect was confirmed by results on a comprehension test and a combined measure of learning effort and test performance (i.e. instructional efficiency). However, evidence for the benefits of pointing was only found for retention performance (i.e. not for comprehension performance and cognitive load ratings) for participants who learned from the split-attention example (i.e. not for participants who learned from the integrated example). Replications are invited to examine pointing as a self-management strategy.
引用
收藏
页码:207 / 227
页数:21
相关论文
共 50 条
  • [31] Single image super-resolution reconstruction based on split-attention networks
    Peng, Yanfei
    Liu, Lanxi
    Wang, Gang
    Meng, Xin
    Li, Yongxin
    CHINESE JOURNAL OF LIQUID CRYSTALS AND DISPLAYS, 2024, 39 (07) : 950 - 960
  • [32] Do Measures of Cognitive Load Explain the Spatial Split-Attention Principle in Multimedia Learning Environments? A Systematic Review
    Schroeder, Noah L.
    Cenkci, Ada T.
    JOURNAL OF EDUCATIONAL PSYCHOLOGY, 2020, 112 (02) : 254 - 270
  • [33] Reducing the split-attention effect of subtitles during video learning: might the use of occasional keywords be an effective solution?
    Cojean, Salome
    Martin, Nicolas
    ANNEE PSYCHOLOGIQUE, 2021, 121 (04): : 417 - 442
  • [34] Adaptive diagrams: Handing control over to the learner to manage split-attention online
    Agostinho, Shirley
    Tindall-Ford, Sharon
    Roodenrys, Kylie
    COMPUTERS & EDUCATION, 2013, 64 : 52 - 62
  • [35] SPLIT-ATTENTION MECHANISMS WITH GRAPH CONVOLUTIONAL NETWORK FOR MULTI-CHANNEL SPEECH SEPARATION
    Tan, YingWei
    Ding, XueFeng
    2024 18TH INTERNATIONAL WORKSHOP ON ACOUSTIC SIGNAL ENHANCEMENT, IWAENC 2024, 2024, : 140 - 144
  • [36] Cognitive load and learner expertise: Split-attention and redundancy effects in reading with explanatory notes
    Yeung, AS
    Jin, PT
    Sweller, J
    CONTEMPORARY EDUCATIONAL PSYCHOLOGY, 1998, 23 (01) : 1 - 21
  • [37] A Lightweight Neural Learning Algorithm for Real-Time Facial Feature Tracking System via Split-Attention and Heterogeneous Convolution
    Mayuandong, Yuandong Ma
    Song, Qing
    Hu, Mengjie
    Zhu, Xiaotong
    NEURAL PROCESSING LETTERS, 2023, 55 (02) : 1555 - 1580
  • [38] What contributes to the split-attention effect? The role of text segmentation, picture labelling, and spatial proximity
    Florax, Mareike
    Ploetzner, Rolf
    LEARNING AND INSTRUCTION, 2010, 20 (03) : 216 - 224
  • [39] Semantic Segmentation of Aerial Imagery via Split-Attention Networks with Disentangled Nonlocal and Edge Supervision
    Zhang, Cheng
    Jiang, Wanshou
    Zhao, Qing
    REMOTE SENSING, 2021, 13 (06)
  • [40] Correction: A Lightweight Neural Learning Algorithm for Real-Time Facial Feature Tracking System via Split-Attention and Heterogeneous Convolution
    Yuandong Ma
    Qing Song
    Mengjie Hu
    Xiaotong Zhu
    Neural Processing Letters, 2023, 55 : 1581 - 1581