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According to the internal/external frame of reference (I/E) model (Marsh, 1986), individuals’ academic self-concept is strongly influenced by comparing their achievement in one domain with their achievement in other domains and with the achievement of others. Research has typically found contrast effects such that high-achieving others have a negative effect on students’ academic self-concept. Yet, what happens if the “other” is somebody very similar to oneself as in the case of monozygotic twins? We postulate and examine the mirror effect, which means that rather than serving as a contrast, the effect of the co-twin’s achievement parallels the effect of a monozygotic twin’s own achievement on academic self-concept. We used data from two school-aged cohorts (11- and 17-year-olds) from a representative sample (N = 4,202) of monozygotic and dizygotic twins in Germany. We regressed twins’ math and German self-concepts on their own and their co-twins’ mathematics and German achievement. Internal and external comparison effects as postulated in the I/E model were replicated for both monozygotic and dizygotic twins across both age groups. In line with our hypothesis, the mirror effect was found in monozygotic twins only: Co-twins’ achievement and twins’ own achievement showed a parallel pattern of positive effects on academic self-concept within each domain and negative effects on academic self-concept between domains, duplicating the I/E pattern. The mirror effect tended to be more pronounced for older monozygotic twins. We argue that the mirror effect is likely caused by high interpersonal similarity and constitutes a rare exception to the broad generalizability of contrast effects as assumed in the I/E model. 相似文献
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随着AI、5G、物联网、大数据、传感与全息等新兴技术的快速发展,尤其是虚拟现实技术从VR、AR、MR到XR的不断演进,促使数字孪生技术开始走向应用并备受学者关注。其正从制造业、城市管理、医疗服务向社会其他领域不断衍生拓展,并在教育领域呈现出广阔的应用前景。在数智融合驱动下,从“AI+大数据+学习分析”加持下的学习者数字画像,向“AI+5G+XR”与全息技术支撑下的数字孪生学习者的迭代更新,将成为AI赋能教育的一个演进趋势。数字孪生学习者基于“四个关键要素”和“五个基本原则”这一现实前提,遵循刻画学习者画像、仿真学习过程、预测学习发展、生成学习结果和共享学习智慧的生成过程,具有高度仿真、动态映射、虚实共生、迭代进化和智能应用的特征,可为“AI+学习者”呈现更精确的学习过程分析、更精准的学习内容推送、更科学的学习评价与无边界的学习生态;并助力学习者进行学习资源共享、学习行为调整、学习兴趣提高、学习体验改善、学习效率提升。因此,对数字孪生学习者进行前瞻性研究,可为数智融合驱动下的学习变革提供全新的视角与思路。 相似文献
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随着新技术的迅猛发展,“大数据+AI”已成为现代社会一种新的驱动力和思维方式。一种可有效实现物理世界和信息世界智能互联与交互融合的新技术——数字孪生应运而生。基于数字孪生技术,可构筑联通现实教学空间与虚拟教学空间的数字孪生讲台,并成为在线教学空间的“数字大动脉”。数字孪生讲台可分为在线学习特征分析技术和虚实教学空间融合分析技术,通过“在线教”与“在线学”间的深度融合、映射与镜像,能为在线沉浸式教学注入新的数字生产力。基于此,从教学、技术两方面,探索数字孪生讲台的在线沉浸式教学流程设计与技术运用,即基于混合式平台的教学数据采集与管理,基于多维分析的教学数据分析与建模,基于精准教学和精准管理的数据应用,基于增强现实技术的在线沉浸式教学体验,进而设计其教学流程。旨在通过数字孪生讲台的多源数据融合、虚实融合映射、教学服务融合优化,促进数字化、智能化课堂的形成,推动数智融合在教学方面的创新性应用,从而形成一种基于大数据的课堂数据互动、映射的新形态,进而革新与重塑现代教育体系。 相似文献