Usability research in educational technology: a state-of-the-art systematic review

Lu, Jie; Schmidt, Matthew; Lee, Minyoung; Huang, Rui

doi:10.1007/s11423-022-10152-6

Cited by 34 publications

(16 citation statements)

References 141 publications

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“…However, we posit that theoretical, methodological, and design perspectives such as those from learning experience design can serve to balance the multifaceted tapestry of mHealth design. Finally, regarding the reported paucity of systematic methods to validate mHealth designs, our work illustrates a multimodal approach that incorporates both qualitative (e.g., cognitive walkthrough) and quantitative (e.g., SUS) measures during the evaluation phase, leading to more objective and reliable findings (Lu et al, 2022 ). Additionally, the iterative development process with multiple participants (i.e., Alpha release, Beta release) can provide mHealth designers with opportunities for not only remedying design flaws, but also validating refinements with different patients.…”

Section: Discussionmentioning

confidence: 99%

Learning experience design of an mHealth self-management intervention for adolescents with type 1 diabetes

Schmidt

Lu²,

Luo³

et al. 2022

Education Tech Research Dev

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Type 1 diabetes (T1D) is a lifelong and chronic condition that can cause severely compromised health. The T1D treatment regimen is complex, and is a particular challenge for adolescents, who frequently experience a number of treatment adherence barriers (e.g., forgetfulness, planning and organizational challenges, stress). Diabetes Journey is a gamified mHealth program designed to improve T1D self-management through a specific focus on decreasing adherence barriers and improving executive functioning skills for adolescents. Grounded in situativity theory and guided by a sociotechnical-pedagogical usability framework, Diabetes Journey was designed, developed, and evaluated using a learning experience design approach. This approach applied design thinking methods within a Successive Approximation Model design process. Iterative design and formative evaluation were conducted across three design phases, and improvements were implemented following each phase. Findings from the user testing phase indicate Diabetes Journey is a user-friendly mHealth program with high usability that holds promise for enhancing adolescents' T1D self-management. Implications for future designers and researchers are discussed regarding the social dimension of the sociotechnical-pedagogical usability framework. An extension to the framework is proposed to extend the social dimension to include socio-cultural and contextual considerations when designing mHealth applications. Consideration of the pedagogical and sociocultural dimensions of learning is imperative when developing psychoeducational interventions.

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Section: Discussionmentioning

confidence: 99%

Learning experience design of an mHealth self-management intervention for adolescents with type 1 diabetes

Schmidt

Lu²,

Luo³

et al. 2022

Education Tech Research Dev

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“…In the data‐checking step, the information needed to carry out the usability test (see resume in Table 1) is analyzed. As usability tests of educational technologies should be done at the early stages of the system and not only at the end [24], the deployment state of the system must be considered to consider which information is already being gathered and which not.…”

Section: Mut and Calmutmentioning

confidence: 99%

“…Evaluating usability is not an easy task, even more for nonexpert evaluators. This is often the case for learning and instructional designers as usability evaluation is not considered one of the core competencies of educational technology researchers [24,41]. Moreover, due to the increase in the availability of educational systems, often teachers become the ones who select the tools to be used what makes important to provide them with tools to facilitate carrying out the usability tests of those systems [7].…”

Section: Introductionmentioning

confidence: 99%

“…Usability evaluation analyzes how satisfied are users with the system and allows to assess how intuitive the system is, the problems that could arise during its use and the formation required to be able to use it correctly [42]. There are some aspects of usability that can be measured, but it has been noted in the literature that finding and selecting valid indicators for these aspects is not easy [1, 24]. There are many usability models that propose the use of different indicators to evaluate usability, but according to Hasan & Al‐Sarayreh [12] most of them use the indicators suggested in the ISO 9241‐11:2018 [16] which is the definition with the broadest perspective of usability.…”

Section: Introductionmentioning

confidence: 99%

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Facilitating and automating usability testing of educational technologies

Villamañe,

Alvarez

2024

Comp Applic In Engineering

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Usability evaluation is a key element to ensure a positive user experience with any software and it is especially important in educational software tools where there are many different actors involved (lecturers, students, administrators, etc.). However, evaluating usability is not an easy task for nonexpert evaluators. To facilitate this evaluation task, this article presents a Methodology for Usability Testing (MUT) and a system (CALMUT) that assists nonexpert evaluators in the application of the methodology by automatizing the calculations and facilitating their interpretation. This can be very useful for learning and instructional designers but also to people involved in the decision of introducing or not a new educational software. To develop the proposal, a literature review of different usability metrics, methods, and systems was carried out first, followed by a selection and adaptation for novice usability evaluators. This article also presents a case study where lecturers tested the usability of an educational software following the proposal and shows that using MUT and CALMUT helps people without previous experience detect the main usability problems of educational systems before deciding whether to use them or not.

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“…Art education is undergoing significant transformation in the digital era, with the emergence of AI digital technology opening up new possibilities in this field [45][46][47]. Figure 1 reveals the application scenarios of online teaching platforms, virtual art galleries, and intelligent assistive creation tools.…”

Section: A Application Research Of Ai Digital Technology In Art Educa...mentioning

confidence: 99%

The Analysis of Artificial Intelligence Digital Technology in Art Education Under the Internet of Things

Fang,

Jiang

2024

IEEE Access

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This study aims to explore the integration of Internet of Things (IoT) technology and artificial intelligence (AI) in art education, assessing its impact on learners' experiences and learning outcomes. The study first proposes a digital teaching system that enables the IoT and Generative Adversarial Networks (GANs) to play a role in art education by monitoring students' creative state in real-time, providing immediate feedback, and facilitating the generation of creative works. The system framework includes sensor nodes, an IoT platform, a GAN model, and a user interface to build a real-time interactive environment. Sensor nodes constantly collect physiological, movement, and environmental data from students, and the GAN model receives student data from the IoT platform, combining creative input from students to generate artwork in real-time. The generated works are transmitted to the discriminator through the IoT platform, which evaluates their quality and provides real-time feedback. Students interact with the system through the user interface, observe the generated artwork, adjust generator parameters, and propose new ideas. These interactions influence further artistic creation. The WikiArt public art creation dataset is selected to establish the experimental foundation, and the experimental evaluation focuses on image generation quality, system performance, and student learning outcomes. It is compared with Deep Convolutional Generative Adversarial Network (DCGAN) and Variational Autoencoder (VAE) models. The research results indicate that the designed IoT and GANs integrated system remarkably outperforms DCGAN and VAE in image generation quality, with an Inception Score of 4.5, which is more diverse and recognizable than other models. Regarding system performance, the IoT and GANs integrated system is significantly ahead in image generation speed and user interaction, with a transmission speed of up to 200 Mbps. Regarding student learning outcomes, the system performs excellently in emotional feedback, learning outcomes, and creative work quality, achieving 80% satisfaction and 90% positive feedback. Overall, the research conclusion clearly points out that the integration of IoT and GANs has a significant and comprehensive effect on improving the quality of art education. This study expands the field of art education by integrating IoT and GANs, enhancing students' creative experiences, and providing innovative methods for art teaching in the digital age.

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Usability research in educational technology: a state-of-the-art systematic review

Cited by 34 publications

References 141 publications

Learning experience design of an mHealth self-management intervention for adolescents with type 1 diabetes

Learning experience design of an mHealth self-management intervention for adolescents with type 1 diabetes

Facilitating and automating usability testing of educational technologies

The Analysis of Artificial Intelligence Digital Technology in Art Education Under the Internet of Things

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