English

Bioinformatics Knowledge Transmission (training, learning, and teaching): overview and flexible comparison of computer based training approaches

Computers and Society 2013-11-01 v1 Other Quantitative Biology

Abstract

The merger of computer science, mathematics, and life sciences has brought about the discipline known as bioinformatics. However, the transmission (e.g. training, learning, and teaching) of this knowledge becomes an important issue. Many tools have been developed to help the bioinformatics community with that transmission challenge. When selecting the best of these tools, called here BKTMS (Bioinformatics Knowledge Transmission Management Systems), there may be confusion. What makes a good BKTMS? How can we make this choice efficiently? These questions remain unanswered for many users (e.g. learner, teacher and student, trainer and trainee, administrator). This paper provides a critical review of 32 existing BKTMS and a flexible comparison. This review and evaluation will be used to gain insight into the tools, systems, and capabilities that will be added to or excluded from a new proposed model for the next generation of BKTMS, involving multidisciplinary, web semantic tools (e.g. web services, workflow) and standards like LOM, or SCORM.

Keywords

Cite

@article{arxiv.1310.8383,
  title  = {Bioinformatics Knowledge Transmission (training, learning, and teaching): overview and flexible comparison of computer based training approaches},
  author = {Etienne Z. Gnimpieba and Douglas Jennewein and Luke Fuhrman and Carol M. Lushbough},
  journal= {arXiv preprint arXiv:1310.8383},
  year   = {2013}
}

Comments

Proc. IKE'13, World Academy of Science

R2 v1 2026-06-22T01:58:00.107Z