Prepare for Success: Designing a Digital Badge Program with a School–University Partnership

Stork, Michele Garabedian; Turcotte, Nate; Rizzuto, Melissa; Wang, Charles Xiaoxue; Rodriguez-Meehan, Melissa

doi:10.1007/s41686-022-00065-1

Cited by 2 publications

(5 citation statements)

References 17 publications

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“…Rogers (1962) identified five general characteristics of innovations that, as a variety of diffusion studies had shown, consistently influence adoption. Rogers (1962) defined them as follows (Rogers, 2003, p. 36;Moore and Benbasat, 1991, p. 195;Lee et al, 2011;Stork et al, 2022):…”

Section: Idt Variables and Behavioral Intention To Use M-learningmentioning

confidence: 99%

“…Of these characteristics relative advantage refers to users' perception of the advantages or disadvantages of an innovation (Stork et al, 2022). In m-learning concept the relative advantage means to the fact that students perceive m-learning as useful for completing their educational tasks in the m-learning environment.…”

Section: Idt Variables and Behavioral Intention To Use M-learningmentioning

confidence: 99%

“…Another element is complexity. Complexity refers to the degree to which an innovation is perceived as difficult to understand and use (Stork et al, 2022). Although not as effective as a relative advantage in m-learning, it is essential to user interaction, interface, and usability.…”

Section: Idt Variables and Behavioral Intention To Use M-learningmentioning

confidence: 99%

“…Rogers (1962) defined them as follows (Rogers, 2003, p. 36; Moore and Benbasat, 1991, p. 195; Lee et al. , 2011; Stork et al. , 2022):Relative advantage: the degree to which an innovation is perceived as being better than its precursor;Compatibility: the degree to which an innovation is perceived as being consistent with the existing values, needs, and past experiences of potential adopters;Complexity: the degree to which an innovation is perceived as being difficult to use; observability: the degree to which the results of an innovation are observable to others;Trialability: the degree to which an innovation may be experimented with before adoption.…”

Section: Conceptual Model and Hypothesis Developmentmentioning

confidence: 99%

“…Of these characteristics relative advantage refers to users' perception of the advantages or disadvantages of an innovation (Stork et al. , 2022).…”

Section: Conceptual Model and Hypothesis Developmentmentioning

confidence: 99%

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Learning with smartphones: the acceptance of m-learning in higher education

Kurt

2022

OIR

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PurposeIn parallel with technological developments, mobile devices have become an important part of our daily lives. Nowadays, people, particularly generation Z, actively engage with the Internet and mobile technologies, including smartphones. The new technologies have also made electronic learning (e-learning) and mobile learning (m-learning) tempting for learners in higher education. Despite the growing use of m-learning, particularly in developed countries, its utilization in higher education is still at its early stage and far from its potential. This study investigates the university students' acceptance of using m-learning with smartphones in a developing country context.Design/methodology/approachQuantitative data collected through conducting questionnaires with 405 higher education students in Turkey were analyzed with structural equation modelling.FindingsThe findings show that the acceptance of using m-learning is affected by several factors, including perceived enjoyment, complexity and facilitating conditions. The findings are particularly relevant in the current context, where the COVID-19 pandemic has pushed many higher education institutions to adapt m-learning systems to enhance student learning experiences.Originality/valueThis study's findings offer fresh and important insights that can be used by m-learning developers and educators for designing m-learning systems and using m-learning applications in enhancing students' experience and performance with m-learning.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0516.

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Section: Idt Variables and Behavioral Intention To Use M-learningmentioning

confidence: 99%

Section: Idt Variables and Behavioral Intention To Use M-learningmentioning

confidence: 99%

Section: Idt Variables and Behavioral Intention To Use M-learningmentioning

confidence: 99%

Section: Conceptual Model and Hypothesis Developmentmentioning

confidence: 99%

“…Of these characteristics relative advantage refers to users' perception of the advantages or disadvantages of an innovation (Stork et al. , 2022).…”

Section: Conceptual Model and Hypothesis Developmentmentioning

confidence: 99%

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Learning with smartphones: the acceptance of m-learning in higher education

Kurt

2022

OIR

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The effectiveness of badging systems in engaging, motivating, and incentivizing students in the mastery of nursing licensure materials

Borines,

Adare-tasiwoopa api

2024

International Journal of Nursing Education Scholarship

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Introduction Integrating gamification methods into undergraduate nursing programs has prepared students to pass the nursing comprehensive predictor test and the licensure examination. Literature review Research demonstrates that the motivational factors of game elements like badging and leaderboards are of great value and utility to student engagement and motivation. The badges symbolize achievement, authority, and belonging, whereas leaderboards rank students based on different levels of course engagement. Discussion This paper explores the benefits, challenges, and strategies of incorporating digital badges and leaderboards in the undergraduate program. Immersion courses preparing students for professional practice are usually one of the last didactic courses offered in the undergraduate curriculum, designed to integrate all knowledge gained from the nursing program. Implications for an international audience The digital badging system can encourage nurse educators globally to engage, motivate, and power students to achieve professional goals. Furthermore, nursing programs worldwide can benefit from adding digital badges and leaderboards to final semester preparatory courses or any nursing course with the same emphasis. Conclusions Digital badges and leaderboards engage and motivate students to integrate knowledge and skills learned in the nursing program and successfully master nurse licensure materials.

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Prepare for Success: Designing a Digital Badge Program with a School–University Partnership

Cited by 2 publications

References 17 publications

Learning with smartphones: the acceptance of m-learning in higher education

Learning with smartphones: the acceptance of m-learning in higher education

The effectiveness of badging systems in engaging, motivating, and incentivizing students in the mastery of nursing licensure materials

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