The Impact of Presentation Format, Task Assignment, and Prior Knowledge on Students' Comprehension of Multiple Online Documents

2007 ◽  
Vol 39 (4) ◽  
pp. 445-470 ◽  
Author(s):  
Ludovic Le Bigot ◽  
Jean-François Rouet
2018 ◽  
Vol 32 (14) ◽  
pp. 1850166 ◽  
Author(s):  
Lilin Fan ◽  
Kaiyuan Song ◽  
Dong Liu

Semi-supervised community detection is an important research topic in the field of complex network, which incorporates prior knowledge and topology to guide the community detection process. However, most of the previous work ignores the impact of the noise from prior knowledge during the community detection process. This paper proposes a novel strategy to identify and remove the noise from prior knowledge based on harmonic function, so as to make use of prior knowledge more efficiently. Finally, this strategy is applied to three state-of-the-art semi-supervised community detection methods. A series of experiments on both real and artificial networks demonstrate that the accuracy of semi-supervised community detection approach can be further improved.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Regina Lenart-Gansiniec ◽  
Wojciech Czakon ◽  
Massimiliano Matteo Pellegrini

Purpose This study aims to identify context-specific antecedents to schools’ absorptive capacity (AC) and to show how those can enact “a virtuous learning circle.” Design/methodology/approach The study uses a mixed method: an exploration based on semi-structured interviews with educational experts; the development of a measurement scale and a partial least squares structural equation modelling to test the impact of the antecedents. Findings The results yielded four empirically-grounded antecedents and their measurement scales, namely, prior knowledge, employees’ skills, educational projects and interactions with the environment (Studies one and two). All antecedents are significantly and positively related to AC processes (study three). Using the organizational learning theory perspective, the results have been interpreted as an AC “virtuous learning circle.” Practical implications With increasing pressures to adapt, a case of which was the COVID-19 pandemic, schools can greatly benefit from absorbing knowledge flows. This suggests the construction a favourable environment for AC. To this end, the individual (employees’ prior knowledge and skills), organizational (educational projects) and institutional level of managerial action (interactions with the environment) can be effective when create a recursive organizational learning circle. In addition, this study offers an expert-validated measurement scale for self-assessment of a school’s specific contingencies, and thus, for planning of punctual interventions to develop AC. Originality/value This study advances the existing body of knowledge management in the educational context by rigorously identifying and validating a scale for measuring the antecedents of AC and developing an interpretive approach to the AC “virtuous circle.”


2021 ◽  
Vol 11 (18) ◽  
pp. 8321
Author(s):  
Zongming Liu ◽  
Zhihua Huang ◽  
Li Wang ◽  
Pengyuan Zhang

Vowel reduction is a common pronunciation phenomenon in stress-timed languages like English. Native speakers tend to weaken unstressed vowels into a schwa-like sound. It is an essential factor that makes the accent of language learners sound unnatural. To improve vowel reduction detection in a phoneme recognition framework, we propose an end-to-end vowel reduction detection method that introduces pronunciation prior knowledge as auxiliary information. In particular, we have designed two methods for automatically generating pronunciation prior sequences from reference texts and have implemented a main and auxiliary encoder structure that uses hierarchical attention mechanisms to utilize the pronunciation prior information and acoustic information dynamically. In addition, we also propose a method to realize the feature enhancement after encoding by using the attention mechanism between different streams to obtain expanded multi-streams. Compared with the HMM-DNN hybrid method and the general end-to-end method, the average F1 score of our approach for the two types of vowel reduction detection increased by 8.8% and 6.9%, respectively. The overall phoneme recognition rate increased by 5.8% and 5.0%, respectively. The experimental part further analyzes why the pronunciation prior knowledge auxiliary input is effective and the impact of different pronunciation prior knowledge types on performance.


2013 ◽  
Vol 03 (01) ◽  
pp. 1-9 ◽  
Author(s):  
James J. Burkitt ◽  
Lawrence E. M. Grierson ◽  
Victoria Staite ◽  
Digby Elliott ◽  
James Lyons

Author(s):  
Kathryn Woods

Advances in technology have increased opportunities for students to participate in online courses. While some instructors are beginning their careers teaching only online courses, others are discovering a need to teach sections of courses online after they have enjoyed a long career teaching in a traditional classroom. In either situation, it is important for instructors to recognize that students in online learning environments require the use of different strategies for encouraging engagement and participation in class. In this chapter, the author describes the challenges that students and instructors face specifically in the online learning environment as well as strategies for success, including how to maximize the impact of students' experiences and prior knowledge, using multiple platforms to deliver information, discouraging procrastination, setting clear expectations, encouraging individuality, capitalizing on diversity, and providing and utilizing helpful resources.


2010 ◽  
Vol 120 (547) ◽  
pp. 968-989 ◽  
Author(s):  
Simon Burgess ◽  
Carol Propper ◽  
Marisa Ratto ◽  
Stephanie von Hinke Kessler Scholder ◽  
Emma Tominey

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