CME – A Web Application Framework Learning Technique Based on Concerns, Micro-Learning and Examples

Correa, Daniel; Isaza, Fernando Arango; Mazo, Raúl; Giraldo, Gloria Lucía

doi:10.1007/978-3-319-91662-0_2

Cited by 6 publications

(8 citation statements)

References 12 publications

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“…They found that students who used the interrupted learning application had increased engagement with the learning materials. Correa et al (2018) report that students engaging in course materials delivered in a microlearning format were quicker to complete tasks and also completed more iterations than students in the non microlearning group. Other research has found that students studying in a microlearning format completed tasks quicker and more accurately than other students (Gao, 2018).…”

Section: Microlearning For Improved Educational Outcomesmentioning

confidence: 91%

“…Liu, 2018;Lv et al, 2020;Miaomiao & Lili, 2015;Polasek & Javorcik, 2019a, 2019bSubramaniam & Muniandy, 2019;Wang et al, 2018;Zahirović Suhonjić et al, 2019), smartphone applications (Dingler et al, 2017;Edge et al, 2011Edge et al, , 2012Göschlberger, 2017;Kadhem, 2017;L. Liu et al, 2018; custom-developed platforms utilising web or alternative programming technologies (Correa et al, 2018;Hsu & Zhou, 2017;Matthews et al, 2014). Mobile and social media delivery platforms were typically chosen due to their popularity amongst student groups.…”

Section: Methods For Microlearning Designmentioning

confidence: 99%

“…In terms of learning motivation, Cai and Chen (2018) report that microlearning content delivered via mobile augmented reality increased both learning performance and self-reported motivation to learn. Evidence also suggests that learning interest and efficiency is also improved through microlearning (Correa et al, 2018;Han, 2019;Yu, 2016). For micro-lectures specifically, students rated that the ability to watch more lessons in a single session (due to shorter duration) and ease of repeat viewing as improving the learning experience (Van Der Westhuizen & Golightly, 2015), with some students preferring the micro-lecture format over traditional classroom lectures (Kävrestad & Nohlberg, 2019).…”

Section: Microlearning For Improved Learning and Teaching Experiencesmentioning

confidence: 99%

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Microlearning for improved student outcomes in higher education: A scoping review

Shatte¹,

Teague²

2020

Preprint

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This paper aims to synthesise the literature on technology-based microlearning in higher education. Six education, information technology, and interdisciplinary research databases were searched using key terms relating to technology-based microlearning in higher education. Articles were assessed by two reviewers, and data were extracted on the article’s microlearning features, supporting technologies, educational discipline, and outcomes for teaching and learning . Articles were then synthesised via narrative review. Forty papers focusing on the application of technology-based microlearning to higher education were identified. Three keys themes emerged, including: (i) methods for microlearning design and delivery; (ii) the impact of microlearning on objective student outcomes (e.g. academic performance and participation); and (iii) the impact of microlearning on subjective student outcomes (e.g. motivation to learn and user experience of using microlearning technologies). Overall, the application of microlearning to higher education has demonstrated a range of benefits for both objective and subjective student outcomes. With the majority of studies reporting on small-scale studies conducted across various disciplines, it is evident that there is significant room for further research on the application of technology-based microlearning to further understand the nuances of its application in higher education. Combined, the results of the current study collate the existing evidence on the benefits and limitations of microlearning in higher education, and can thus assist educational practitioners in incorporating microlearning content into their own teaching materials.

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Section: Microlearning For Improved Educational Outcomesmentioning

confidence: 91%

Section: Methods For Microlearning Designmentioning

confidence: 99%

Section: Microlearning For Improved Learning and Teaching Experiencesmentioning

confidence: 99%

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Microlearning for improved student outcomes in higher education: A scoping review

Shatte¹,

Teague²

2020

Preprint

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“…According to Lin et al (2019), the microlearning concept "aims to effectively utilize learners' fragmented time to carry out personalized learning activities through online education resources." For example, Correa et al (2018) used microlearning to accelerate the learning experience of novice software web developers. Redondo et al (2021) used micro-learning content in formal distance learning environments.…”

Section: Microlearning Environment Setupmentioning

confidence: 99%

A feedback model applied in a ubiquitous microlearning environment using SECA rules

et al. 2022

Self Cite

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Understanding learners’ behavior is the key to the success of any learning process. The more we know about them, the more likely we can personalize learning experiences and provide successful feedback. This paper presents a feedback model implemented in a ubiquitous microlearning environment based on contextual and behavioral information and evaluation results. The model uses SECA rules where the Scenario (S) represents the ubiquitous context variables reflecting the learner behavior during the learning process. The Event (E) identifies the probability that a learner fails or passes its evaluation. Condition (C) evaluates the results of the events. Moreover, Action (A) provides feedback to the learner. The proposal is developed through a controlled experiment whereby a microlearning environment can collect data from a ubiquitous context. The feedback model applies an analytics process to find the best context and behavior variables through different classification models. Those models predict whether a learner could fail, determine evaluation results’ causes, and provide feedback. The Random Forest was the model with the best performance. Thus, 94% accuracy, a 97% Recall, a 93% Precision, an F1 score of 95%, and a Jaccard of 91%. Hence, each scenario is defined from a branch of every tree obtained from the Random Forest model personalizing feedback actions applying clustering techniques. Finally, we presented an exemplified set of feedback rules, providing automatic recommendations and improving learner experiences. Thus, the experiment allows analyzing the learner behavior in a ubiquitous microlearning context from a feedback perspective.

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“…There are several trends in modern e-learning that can be defined as follows: -Micro-learning or Micro-eLearning education: It focuses on activities in the complex educational process divided into small chunks, called micro-contents. Often it is achieved with short multimedia objects that do not last more than a few minutes [33,34]. Unlike the 'traditional' approaches to e-learning, microlearning reduces the amount of knowledge that should be learned.…”

Section: Standards and Trends In E-learningmentioning

confidence: 99%

An approach to designing and developing an LMS framework appropriate for young pupils

Kraleva¹,

Sabani²,

Kralev³

et al. 2020

IJECE

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The lifestyle of the new people generation, called in the scientific literature Generation Z, is closely related to the Internet, computer and information technology. Therefore, people and children belonging to this group can be viewed in terms of software technology as specific users who have high requirements regarding the functions and interface of the software applications, connectivity to social networks and instant communication via the Internet. This influenced not only on the teaching and learning methods but also on the software applications used in the learning process. In recent years, new theoretical teaching methods have emerged, and the number of electronic learning systems increased. However, students lack motivation for the learning process. This requires developing new conceptual models of training and learning software, tailored to the skills and preferences of the end-users. The young students up to 12 years of age: from kindergartens to preschools and primary schools are special users who have not been studied exhaustively. In order to present the problem related to the development of learning and training software thoroughly, the most commonly used standards and current trends, as well as the advantages and disadvantages of LMS platforms have been reviewed. Attention is drawn to the commonly used software design and development technologies. This is the reason to propose a strategy for developing a web-based e-learning management system according to the possibilities of young pupils as a specific user. Having in mind this strategy we described a software architecture, based on SCORM's specification, and we developed an LMS prototype. Its design was tailored to the skills of young children. The basic methodology used in the design and creation of the system we propose is user-centered design. The document is intended for developers, educators and scientists, studying child-computer interaction.

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CME – A Web Application Framework Learning Technique Based on Concerns, Micro-Learning and Examples

Cited by 6 publications

References 12 publications

Microlearning for improved student outcomes in higher education: A scoping review

Microlearning for improved student outcomes in higher education: A scoping review

A feedback model applied in a ubiquitous microlearning environment using SECA rules

An approach to designing and developing an LMS framework appropriate for young pupils

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