Zobrazeno 1 - 10
of 88 696
pro vyhledávání: '"Dragan IF"'
The spectral radius of a graph is the spectral radius of its adjacency matrix. A threshold graph is a simple graph whose vertices can be ordered as $v_1, v_2, \ldots, v_n$, so that for each $2 \le i \le n$, vertex $v_i$ is either adjacent or nonadjac
Externí odkaz:
http://arxiv.org/abs/2412.16019
Autor:
Li, Xinyu, Fan, Yizhou, Li, Tongguang, Rakovic, Mladen, Singh, Shaveen, van der Graaf, Joep, Lim, Lyn, Moore, Johanna, Molenaar, Inge, Bannert, Maria, Gasevic, Dragan
The focus of education is increasingly set on learners' ability to regulate their own learning within technology-enhanced learning environments (TELs). Prior research has shown that self-regulated learning (SRL) leads to better learning performance.
Externí odkaz:
http://arxiv.org/abs/2412.09763
Autor:
Fan, Yizhou, Tang, Luzhen, Le, Huixiao, Shen, Kejie, Tan, Shufang, Zhao, Yueying, Shen, Yuan, Li, Xinyu, Gašević, Dragan
With the continuous development of technological and educational innovation, learners nowadays can obtain a variety of support from agents such as teachers, peers, education technologies, and recently, generative artificial intelligence such as ChatG
Externí odkaz:
http://arxiv.org/abs/2412.09315
Self-regulated Learning Processes in Secondary Education: A Network Analysis of Trace-based Measures
Autor:
Cheng, Yixin, Guan, Rui, Li, Tongguang, Raković, Mladen, Li, Xinyu, Fan, Yizhou, Jin, Flora, Tsai, Yi-Shan, Gašević, Dragan, Swiecki, Zachari
While the capacity to self-regulate has been found to be crucial for secondary school students, prior studies often rely on self-report surveys and think-aloud protocols that present notable limitations in capturing self-regulated learning (SRL) proc
Externí odkaz:
http://arxiv.org/abs/2412.08921
Big Bang Nucleosynthesis (BBN), the process of creation of lightest elements in the early universe, is a highly robust, precise, and ultimately successful theory that forms one of the three pillars of the standard hot-Big-Bang cosmological model. Exi
Externí odkaz:
http://arxiv.org/abs/2412.07893
Autor:
Yang, Kaixun, Raković, Mladen, Liang, Zhiping, Yan, Lixiang, Zeng, Zijie, Fan, Yizhou, Gašević, Dragan, Chen, Guanliang
Students are increasingly relying on Generative AI (GAI) to support their writing-a key pedagogical practice in education. In GAI-assisted writing, students can delegate core cognitive tasks (e.g., generating ideas and turning them into sentences) to
Externí odkaz:
http://arxiv.org/abs/2412.07200
We consider the problem of least squares parameter estimation from single-trajectory data for discrete-time, unstable, closed-loop nonlinear stochastic systems, with linearly parameterised uncertainty. Assuming a region of the state space produces in
Externí odkaz:
http://arxiv.org/abs/2412.04157
For individuals who are blind or have low vision, tactile maps provide essential spatial information but are limited in the amount of data they can convey. Digitally augmented tactile maps enhance these capabilities with audio feedback, thereby combi
Externí odkaz:
http://arxiv.org/abs/2412.00946
A ($\lambda,\mu$)-bow metric was defined in (Dragan & Ducoffe, 2023) as a far reaching generalization of an $\alpha_i$-metric (which is equivalent to a ($0,i$)-bow metric). A graph $G=(V,E)$ is said to satisfy ($\lambda,\mu$)-bow metric if for every
Externí odkaz:
http://arxiv.org/abs/2411.16548
Autor:
Jin, Yueqiao, Yang, Kaixun, Yan, Lixiang, Echeverria, Vanessa, Zhao, Linxuan, Alfredo, Riordan, Milesi, Mikaela, Fan, Jie, Li, Xinyu, Gašević, Dragan, Martinez-Maldonado, Roberto
Learning analytics dashboards (LADs) simplify complex learner data into accessible visualisations, providing actionable insights for educators and students. However, their educational effectiveness has not always matched the sophistication of the tec
Externí odkaz:
http://arxiv.org/abs/2411.15597