User Behavior in Multi-screen eLearning

Kapenieks, Atis; Žuga, Bruno; Gorbunovs, Aleksandrs; Jirgensons, Merija; Kapenieks, Janis; Vītoliņa, Ieva; Majore, Ginta; Jākobsone-Šnepste, Guna; Kudina, Ieva; Kapenieks, Kristaps; Timsans, Zanis; Gulbis, Rūdolfs; Tomsons, Dzinatrs; Ulmane-Ozolina, Lasma; Letinskis, Janis; Balode, Antra

doi:10.1016/j.procs.2015.09.021

Cited by 6 publications

(5 citation statements)

References 3 publications

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“…Park et al (2013) examined the effects of service quality and system quality on customer satisfaction and the intention to continue usage of N-screen services. Kapenieks et al (2015) examined user behaviors with respect to multi-screen services in an educational setting for supporting e-learning. Similarly, Kim et al (2014) conducted an examination of user acceptance of N-screen services from a consumer behavior perspective.…”

Section: Literature Reviewmentioning

confidence: 99%

Explicating user behavior toward multi-screen adoption and diffusion

Shin

Biocca

2017

Internet Research

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Purpose The purpose of this paper is to analyze user behavior toward multi-screen services by employing neural networks to predict overall customer satisfaction and to prioritize the factors that influence customer intentions. Design/methodology/approach Multi-screen experiences require a new approach incorporating multiple methods. A proposed multi-state analytic approach in which the research model is tested using structural equation modeling was utilized. The results were then used as inputs for a neural network model to predict multi-screen adoption. Findings The findings indicate that multi-screen quality significantly influences usability, which subsequently affects the adoption of the technology. Practical implications The policy and managerial implications of multi-screen development are discussed based on the models of acceptance and diffusion. Social implications The emergence of multi-screen services as well as the simultaneous and sequential engagement of users with multiple devices throughout the day challenges the ability of marketers to develop effective communication strategies. Originality/value This study provides an in-depth analysis and heuristic data regarding user drivers, market dynamics, and policy implications in the one-source multi-use ecosystem.

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Section: Literature Reviewmentioning

confidence: 99%

Explicating user behavior toward multi-screen adoption and diffusion

Shin

Biocca

2017

Internet Research

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“…Unlike in the past, today, online education does not require the use of a stationary computer. Content can be displayed on a tablet [13,14], a smartphone [15,16], a laptop, [17,18], or with the use of Virtual Reality (VR) goggles [19,20]. This enables students to obtain knowledge and understanding, and new solutions are being implemented globally.…”

Section: Distance Education-a Short Introductionmentioning

confidence: 99%

A Worldwide Journey through Distance Education—From the Post Office to Virtual, Augmented and Mixed Realities, and Education during the COVID-19 Pandemic

et al. 2021

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Surprisingly, distance education is quite an old concept. Its origins date back to the first correspondence-based course, which took place via the postal service in Boston, USA, in the 18th century. Rapid technological developments, especially in video and audio streaming, have increased the availability of such courses and moved learning into the virtual world. Due to the ongoing COVID-19 pandemic, we are witnessing an accelerated revolution in the learning process, as nearly all forms of education have been shifted online. Will this have a destructive effect on the human psyche? Is humanity sufficiently aware and ready for such a dramatic change? Will we return to physical in-classroom studies, or is remote distance education set to become the new norm? In particular, in medicine, computer science, fine arts, or architectural design, such a rapid change in the way students learn can be quite challenging. In this paper, we provide an overview of the history of distance learning, taking into account teachers’ and students’ points of view in both secondary and higher education.

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“…text messages from the internal message database), is provided. Multiscreen learning support technology, known as the eBig3 technology [25,26], is already approbated in a large scale pilots in Baltics. Domain model includes properties of LO and content as follows: type by activity, type by media, LO size (time, character numbers; size vs. course credits), usability (length of scrolling points; click numbers), terms/abbreviations explanation, pathway from simplicity to complexity (levels), complexity of LO (levels), complexity measurement (levels), interlinking (relationship) with other LO, responsiveness to the platform and other devices (and society), learning objectives included and reached (binary), methodology (binary), assessment (binary), feedback (binary), readability/ease of learning, language proofing (binary), special needs/accessibility, effectivity (study quality vs. time consumed), engagement/attractiveness of LO, LO usefulness, adaptation feature, adaptive learning style, variety of learning scenarios, type of LO (simulation, serious game, xAPI, etc.).…”

Section: Resultsmentioning

confidence: 99%

Conceptual design of the new generation adaptive learning management system

Gorbunovs¹,

Timsans²,

Žuga³

et al. 2018

IJET

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Taking into account that each new day an amount of daily processed data grows exponentially, it is obvious that knowledge society needs flexible, effective and high performing tools to retrieve, learn and apply necessary information. Learning management systems become more and more intelligent and adaptive. Learning analytics instruments give course developers a possibility to assess and analyze learners’ activities and behavior patterns within e-learning environment, allowing to propose them personalized self-paced learning path and types of learning objects. This paper discusses challenges in development of adaptive learning management system and outlines its prospective models and properties.

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User Behavior in Multi-screen eLearning

Cited by 6 publications

References 3 publications

Explicating user behavior toward multi-screen adoption and diffusion

Explicating user behavior toward multi-screen adoption and diffusion

A Worldwide Journey through Distance Education—From the Post Office to Virtual, Augmented and Mixed Realities, and Education during the COVID-19 Pandemic

Conceptual design of the new generation adaptive learning management system

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