Successful learning with whiteboard animations – A question of their procedural character or narrative embedding?

Schneider, Sascha; Krieglstein, Felix; Beege, Maik; Rey, Günter Daniel

doi:10.1016/j.heliyon.2023.e13229

Cited by 12 publications

(9 citation statements)

References 88 publications

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“…For instance, the present AFI format consisting of a combination of an expert talk with short examples was unable to achieve this goal despite targeting the determinants postulated in UTAUT. Looking to the field of instructional design and online learning research, in particular, whiteboard videos may pose an opportunity to development scalable and effective AFI ( 61 ). Following the cognitive theory of multimedia learning, information (e.g., on the personal benefit) could be divided in verbal and visual components to reduce cognitive load during the intervention ( 62 ).…”

Section: Discussionmentioning

confidence: 99%

“…Following the cognitive theory of multimedia learning, information (e.g., on the personal benefit) could be divided in verbal and visual components to reduce cognitive load during the intervention ( 62 ). Furthermore, a dynamic visualization of content and narrative style could potentially increase the effectiveness of whiteboard-based AFI ( 61 , 63 , 64 ). However, the effectiveness of such AFI in the context of smart sensing is currently unclear and needs to be explored.…”

Section: Discussionmentioning

confidence: 99%

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Acceptance of smart sensing: a barrier to implementation—results from a randomized controlled trial

Terhorst,

Weilbacher,

Suda

et al. 2023

Front. Digit. Health

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BackgroundAccurate and timely diagnostics are essential for effective mental healthcare. Given a resource- and time-limited mental healthcare system, novel digital and scalable diagnostic approaches such as smart sensing, which utilizes digital markers collected via sensors from digital devices, are explored. While the predictive accuracy of smart sensing is promising, its acceptance remains unclear. Based on the unified theory of acceptance and use of technology, the present study investigated (1) the effectiveness of an acceptance facilitating intervention (AFI), (2) the determinants of acceptance, and (3) the acceptance of adults toward smart sensing.MethodsThe participants (N = 202) were randomly assigned to a control group (CG) or intervention group (IG). The IG received a video AFI on smart sensing, and the CG a video on mindfulness. A reliable online questionnaire was used to assess acceptance, performance expectancy, effort expectancy, facilitating conditions, social influence, and trust. The self-reported interest in using and the installation of a smart sensing app were assessed as behavioral outcomes. The intervention effects were investigated in acceptance using t-tests for observed data and latent structural equation modeling (SEM) with full information maximum likelihood to handle missing data. The behavioral outcomes were analyzed with logistic regression. The determinants of acceptance were analyzed with SEM. The root mean square error of approximation (RMSEA) and standardized root mean square residual (SRMR) were used to evaluate the model fit.ResultsThe intervention did not affect the acceptance (p = 0.357), interest (OR = 0.75, 95% CI: 0.42–1.32, p = 0.314), or installation rate (OR = 0.29, 95% CI: 0.01–2.35, p = 0.294). The performance expectancy (γ = 0.45, p < 0.001), trust (γ = 0.24, p = 0.002), and social influence (γ = 0.32, p = 0.008) were identified as the core determinants of acceptance explaining 68% of its variance. The SEM model fit was excellent (RMSEA = 0.06, SRMR = 0.05). The overall acceptance was M = 10.9 (SD = 3.73), with 35.41% of the participants showing a low, 47.92% a moderate, and 10.41% a high acceptance.DiscussionThe present AFI was not effective. The low to moderate acceptance of smart sensing poses a major barrier to its implementation. The performance expectancy, social influence, and trust should be targeted as the core factors of acceptance. Further studies are needed to identify effective ways to foster the acceptance of smart sensing and to develop successful implementation strategies.Clinical Trial Registrationidentifier 10.17605/OSF.IO/GJTPH.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Acceptance of smart sensing: a barrier to implementation—results from a randomized controlled trial

Terhorst,

Weilbacher,

Suda

et al. 2023

Front. Digit. Health

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“…However, it is questionable whether a population with good mental health expects meaningful benefits from smart sensing, while a population of psychotherapy patients might have a clearer connection to the benefits of the technology. Lastly, we optimized the intervention by applying state of the art instructional design principles to split the cognitive load across auditory and visual channels in the white-board video and implemented a narrative explanation style in the AFI ( 40 – 42 ).…”

Section: Discussionmentioning

confidence: 99%

“…The video aimed to address the acceptance predictors outlined in the UTAUT model, with a particular focus on performance expectancy. The video was tailored to the target audience of psychotherapy patients, implemented a narrative style, and was based on a whiteboard design to achieve load reduction ( 40 – 42 ). Content within the video included an explanation of what smart sensing entails, how it can be utilized, information regarding data collection, data privacy considerations, and the benefits of smart sensing.…”

Section: Methodsmentioning

confidence: 99%

Enhancing the acceptance of smart sensing in psychotherapy patients: findings from a randomized controlled trial

Rottstädt,

Becker,

Wilz

et al. 2024

Front. Digit. Health

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ObjectiveSmart sensing has the potential to make psychotherapeutic treatments more effective. It involves the passive analysis and collection of data generated by digital devices. However, acceptance of smart sensing among psychotherapy patients remains unclear. Based on the unified theory of acceptance and use of technology (UTAUT), this study investigated (1) the acceptance toward smart sensing in a sample of psychotherapy patients (2) the effectiveness of an acceptance facilitating intervention (AFI) and (3) the determinants of acceptance.MethodsPatients (N = 116) were randomly assigned to a control group (CG) or intervention group (IG). The IG received a video AFI on smart sensing, and the CG a control video. An online questionnaire was used to assess acceptance of smart sensing, performance expectancy, effort expectancy, facilitating conditions and social influence. The intervention effects of the AFI on acceptance were investigated. The determinants of acceptance were analyzed with structural equation modeling (SEM).ResultsThe IG showed a moderate level of acceptance (M = 3.16, SD = 0.97), while the CG showed a low level (M = 2.76, SD = 1.0). The increase in acceptance showed a moderate effect in the intervention group (p < .05, d = 0.4). For the IG, performance expectancy (M = 3.92, SD = 0.7), effort expectancy (M = 3.90, SD = 0.98) as well as facilitating conditions (M = 3.91, SD = 0.93) achieved high levels. Performance expectancy (γ = 0.63, p < .001) and effort expectancy (γ = 0.36, p < .001) were identified as the core determinants of acceptance explaining 71.1% of its variance. The fit indices supported the model's validity (CFI = .95, TLI = .93, RMSEA = .08).DiscussionThe low acceptance in the CG suggests that enhancing the acceptance should be considered, potentially increasing the use and adherence to the technology. The current AFI was effective in doing so and is thus a promising approach. The IG also showed significantly higher performance expectancy and social influence and, in general, a strong expression of the UTAUT factors. The results support the applicability of the UTAUT in the context of smart sensing in a clinical sample, as the included predictors were able to explain a great amount of the variance of acceptance.

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“…c. Task analysis Students' mastery of science (biology) material related to new terms of the material is one of the obstacles, especially in one of the KD 3.4 of the structure and function of plant tissue delivered by the teacher requiring more visualization because it is closely related to everyday life. Student day, so that it becomes an advantage of the material If it can be visualized properly, it will be able to stimulate students' motivation and interest in the material (Schneider et al, 2023;Tsai & Yen, 2013), and also in the plant tissue sub-material which is material with characteristics that cannot be seen with the naked eye, so that it requires a big role of visualization, this is due to the limited school facilities for microscoes as a tool for viewing and online learning systems (on the network) that do not allow students to use microscopes at school.…”

Section: Define Stage a Font-end Analysismentioning

confidence: 99%

Learning media of digital booklets for class VIII junior high school

Andini

Saifuddin

2023

Biosfer

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The learning system that has changed to online causes teachers to be creative in delivering material through digital learning media. Thus, research on the development of booklets into digital learning media needs to be carried out to assist teachers in facilitating learning and assisting students in understanding the material. This study aims to determine the quality and appropriateness of the content and its presentation as a medium for learning science in class VIII SMP material on the structure and function of plant tissue. This research method is a Research and Development (R & D) study, adapted from Thiagarajan’s 4 D (Define, Design, Development, and Disseminate) model. The data taken is the result of product assessment with a data collection instrument in the form of a questionnaire analyzed using descriptive-quantitative data. The resulting assessment from four media experts, four material experts, and a teacher showed the digital booklet in the very good category, with an average of 78.13% (media), 88.28% (material), and 96.88% (teacher). Besides, students gave very good responses., indicated by the acquisition of an average assessment of 94.89%. The digital booklet could be used as an alternative learning media on the structure and function of plant tissue.

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Successful learning with whiteboard animations – A question of their procedural character or narrative embedding?

Cited by 12 publications

References 88 publications

Acceptance of smart sensing: a barrier to implementation—results from a randomized controlled trial

Acceptance of smart sensing: a barrier to implementation—results from a randomized controlled trial

Enhancing the acceptance of smart sensing in psychotherapy patients: findings from a randomized controlled trial

Learning media of digital booklets for class VIII junior high school

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