ABSTRACT
Technology-based in-home reading and spelling programs have the potential to compensate for the lack of sufficient instructions provided at schools. However, the recent COVID-19 pandemic showed the immaturity of the existing remote teaching solutions. Consequently, many students did not receive the necessary instructions. This paper presents a model for developing intelligent reading and spelling programs. The proposed approach is based on an optimization model that includes artificial neural networks and linear regression to maximize the educational value of the pedagogical content. This model is personalized, tailored to the learning ability level of each user. Regression models were developed for estimating the lexical difficulty in the literacy tasks of auditory and visual lexical decision, word naming, and spelling. For building these regression models, 55 variables were extracted from French lexical databases that were used with the data from lexical mega-studies. Forward stepwise analysis was conducted to identify the top 10 most important variables for each lexical task. The results showed that the accuracy of the models (based on root mean square error) reached 88.13% for auditory lexical decision, 89.79% for visual lexical decision, 80.53% for spelling, and 83.86% for word naming. The analysis of the results showed that word frequency was a key predictor for all the tasks. For spelling, the number of irregular phoneme-graphemes was an important predictor. The auditory word recognition depended heavily on the number of phonemes and homophones, while visual word recognition depended on the number of homographs and syllables. Finally, the word length and the consistency of initial grapheme-phonemes were important for predicting the word-naming reaction times. © 2023 by the authors.
ABSTRACT
Innovation has the potential to propel organizations to unprecedented levels of performance and to strengthen their competitive advantage. Collaboration plays a significant role in boosting the innovation capabilities and reaching performance goals. Improving collaboration brings substantial overall benefits ranging from faster internal decision making, reduced costs through shared resources, and the development of more innovative products. The COViD-10 outbreak has radically altered traditional collaboration and teamwork patterns, requiring new approaches that would nurture creativity, engagement, and motivation at team level, and that would also streamline decision-making processes. This paper investigates the use of a collaborative platform that can enhance teamwork achievements and decision-making capabilities and presents an analysis of experiments carried out within software research projects. The approach considers key challenges in today's global and fast-changing research and business environments that demand improvements in collaboration among functions ranging from R&D to distribution. The authors explore techniques for improving the effectiveness of teams, capitalizing on the promises of cutting-edge software and the applicability of the Design Thinking methodology and its potential to boost collaboration. This research probes the capacity of technology to support team performance and better decision-making processes. © 2021 The Authors. Published by Elsevier B.V.
ABSTRACT
Digital location-based experiences, such as app-guided digital scavengers, depend on users being on-site. The requirement to be on-site is a virtue, but it can also be a shortcoming of location-based experiences, such as in the COVID 19 pandemic. This workshop addresses the possibilities of eliminating the on-site requirement, thus extending the potential application of location-based experiences. First, virtualization approaches will be presented, which allow eliminating the need to be on-site, such as the usage of 360° technologies or the employment of videoconferencing software. Further, various challenges, such as the application of existing design principles for location-based experiences and instructional design for virtualized location-based experiences, are discussed and options to overcome the limitations imposed by the virtualization. This paper provides insights into theoretical foundations relevant to solving the aspects of virtualizing location-based experiences. The workshop results are intended to provide lasting advancements to eliminating the on-site requirements for location-based experiences. © 2021, IFIP International Federation for Information Processing.