Correlation between Teaching Behavior and Real-Time Student Evaluations

Kometani, Yusuke; Tomoto, Takahito; Akakura, Takako; Nagaoka, Keizo

doi:10.1109/t4e.2014.25

Cited by 2 publications

(1 citation statement)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Likewise, the quality of education can be evaluated by several dimensions that consist of information, systems, and services [89]. Studies have shown that lessons delivered simultaneously may lead to cognitive overload [47], while the over-delivery text could distract the learning process by reducing lesson content and focus [90]. Accordingly, only related and useful information is allowed to be employed during learning sessions.…”

Section: E Instructional Designmentioning

confidence: 99%

A Survey on Mobile Learning for Adult Learners: State-of-the-Art, Taxonomy, and Challenges

et al. 2022

View full text Add to dashboard Cite

Adult learner performance has become a significant challenge in the field of education. Adult learners are identified as being of productive age in engaging with multiple commitments, including studying. The multiple engagements make it difficult for them to manage their time and focus, which contributes to a high institutional dropout rate. This situation has led to a reduced number of highly skilled and professional workers in the country because of the failure to meet academic requirements. In the current digital world, every aspect of education includes some elements of technology. However, most adult learners are reluctant to utilise mobile technology for the purpose of learning. Therefore, this review paper aims to provide a state of art regarding mobile learning for adult learners. Considering a set of inclusion and exclusion criteria, 135 related articles from IEEE, Google Scholar, Springer Link, Science Direct, Taylor and Francis, and Wiley digital databases were extracted and reviewed. The state of the art of M-learning were discussed in terms of functions of m-learning, effectiveness, and m-learning as a tool. Keywords from articles were extracted and the taxonomy of M-learning was discussed under five classifications (Behavioural Intention, Technological Support, Educational Content, Learner Coordination, and Instructional Design) were created based on these keywords, which represented the same meaning and features that were discussed in the articles. The findings can raise awareness among mobile learning practitioners to provide more effective services for adult learners. Meanwhile, higher education institutions can be better redesigned in terms of pedagogy to fit the needs of adult learners with mobile learning.

show abstract

Section: E Instructional Designmentioning

confidence: 99%