Article reports on a trace-based assessment of approaches to learning used by middle school aged children who interacted with NASA Mars Mission science, technology, engineering and mathematics (STEM) games in Whyville, an online game environment with 8 million registered young learners. Differences in approach to learning were found illustrating the potential value of the methodology to curriculum and game-based learning designers as well as other creators of online STEM content for pre-college youth.
Article provides assemblage maps showing the elements related to creativity, innovation, and creativity and innovation. These assemblage maps highlight virtual and dynamic flight lines that represent potentially active components with varying intensity and direction, which provides a tool for managers and practitioners to identify potentialities for future predictions better.
September 26, 2022
Turner, John R.; Baker, Rose M. & Thurlow, Nigel
Article discusses how as learners engage, test, and apply new subject knowledge, they often expend their cognitive capacity on the technological tools designed to capture their learning progress and outcomes. The author's research explores the value of developing digital literacy to improve learners’ cognitive flexibility by decreasing technological cognitive load and increasing learning fluency.
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Book chapter examining how unequal access to the internet and technology impacted the school context including teachers, students, parents, and administrators, and how English Learners from immigrant backgrounds navigated this experience. Implications apply to education stakeholders to reduce inequities in online learning contexts.
This article is an introduction to the special issue Assistive Technology Services During and After the COVID-19 Pandemic, which was created to provide a historical record of the impact of the COVID-19 pandemic on the provision of assistive technology services in schools.
Article presents a study employing multi-mode stimuli of learners’ eye movements and feedforward that aims to develop the effect of Stimulated Recall (SR) on activating learners’ metacognition in remote settings.
Paper presented at the 2019 ASEE Annual Conference & Exposition. The research presented studies achievement scores and affinity towards STEM scores of male and female students after participating in a unit focused on understanding a solenoid.
Tyler-Wood, Tandra L.; Smith, Daniella & Johnson, Karen R.
Article investigating the use of information and communication technologies (ICTs) in education. To investigate this issue, the technology adoption and gratification (TAG) model was validated and used to examine Malaysian university teachers' adoption and gratification of ICT for teaching and research purposes and then used to investigate the moderating effect of universities in different regions. This paper confirms the utility of the TAG model for comparing teachers' adoption and gratification of ICT.
December 11, 2018
Spector, J. Michael; Islam, A. Y. M. Atiquil; Mok, Magdalena Mo Ching; Gui, Xiaoqing & Hai-Leng, Chin
Article providing a review of the recent research literature on personalized learning as technology is changing how learning can be effectively personalized. The emphasis is on the terms used to characterize learning as those can suggest a framework for personalized and will eventually be used in meta-analyses of research on personalized learning.
Article reviews opportunities for novel brain-behavior characterizations. Emphasis is placed on the increasing concern of neuropsychology with these topics and the need for development in these areas to maintain relevance as a scientific discipline and advance scientific developments.
Article examines K-12 students and parents in the United States’ experiences and challenges during the sudden shift to distance learning during the COVID19 crisis. This article is part of the special issue: Learning and learning ecosystems in the time of Covid-19.
This article presents a study that examined how three auditory lectures delivered at different speeds – normal (1.0x), fast (1.5x) and very fast (3.0x) speeds – affected graduate students’ attention, cognitive load, and learning.
Lin, Lin; Yang, Xue; An, Yunjo; Yang, Xiaozhe; Wen, Yi & Cheng, Pei-Yu
This article covers the challenges brought about for teachers and learners from transitioning to online education due to the COVID-19 pandemic. The authors reflect on these challenges based on discussions at EDUsummIT2019 in Quebec about the theme “Learners and learning contexts: New alignments for the digital age." Informed by theoretical conceptualization and empirical evidence the authors identify micro-meso-macro alignments that need to be in place to move education into the digital age: alignments for quality learning contexts, alignments in support for teachers, and alignments through partnerships.
This article is a review of literature for skills comprised within the Accreditation Board of Engineering and Technology (ABET) criteria determined 26 topics necessary for the entry-level and continued success of engineers. The findings suggest that although entry-level engineers have proficiency in all of these ABET required skills, the entry-level engineers were not meeting the level of importance expressed by the organization for 24 of these 26 skills.
October 14, 2021
Hirudayaraj, Malar; Baker, Rose M.; Baker, Francie & Eastman, Mike
This article provides a content analysis of studies from 2010 to 2020 aiming to disclose how artificial intelligence (AI) has been applied to the education sector and explore the potential research trends and challenges of AI in education. The content analysis shows that the research questions can be classified into development layer (classification, matching, recommendation, and deep learning), application layer (feedback, reasoning, and adaptive learning), and integration layer (affection computing, role-playing, immersive learning, and gamification).
April 20, 2021
Zhai, Xuesong; Chu, Xiaoyan; Chai, Ching Sing; Jong, Morris Siu Yung; Istenic, Andreja; Spector, Michael et al.
In this article, a topic model was explored using unsupervised machine learning to summarized free-text narrative reports of 77,215 injuries that occurred in coal mines in the USA between 2000 and 2015. Latent Dirichlet Allocation modeling processes identified six topics from the free-text data. The modeling success enjoyed in this exploratory effort suggests that additional topic mining of these injury text narratives is justified, especially using a broad set of covariates to explain variations in topic emphasis and for comparison of surface mining injuries with injuries occurring during site preparation for construction.
December 14, 2018
Passmore, David L.; Chae, Chungil; Kustikova, Yulia; Baker, Rose M. & Yim, Jeong-Ha
This article explores networked learning technologies and the development of Massive Online Open Courses (MOOCs). The study examines and explains hybrid MOOCs and focuses on the use of bot-teachers within a post-humanist perspective. The research findings reveal that, while the use of bot-teachers is beneficial in terms of facilitating and increasing discourse/interaction, it is ineffective in providing other components of teaching presence. Yet ultimately, learners' positive behaviors indicate that bot-teachers hold promise as an educational tool.
July 20, 2018
Bozkurt, Aras; Kilgore, Whitney & Crosslin, Matt
Article evaluates the impact of new media on scientific literacy. Content analysis with a coding scheme was performed on 42 filtered websites and 20 microblogs to analyze the role of new media in disseminating scientific knowledge. The results showed that the quality of science-oriented websites was higher than that of microblogs. Suggestions about how to improve the quality of science-oriented new media and how to develop students’ scientific literacy through new media are also discussed.
This article seeks to support researchers by concisely reviewing key statistical assumptions associated with substantive statistical tests across the general linear model. Additionally, the article reviews techniques to check for statistical assumptions and identifies remedies and problems if data do not meet the necessary assumptions.