Mobile Learning for Early Detection of Cancer

Dublin Core

Title

Mobile Learning for Early Detection of Cancer

Subject

cancer
early detection
mobile learning

Description

Information and communication technology continues to grow and affects many areas of life, including the field of health, especially cancer. The development of health knowledge can be disseminated by utilizing mobile application based learning technology as media. Many things have been done by the government through special programs, among others, carried out breast cancer awareness campaign through breast self-screening program. The positive impact of this effort has led to mobile applications for learning about early detection of cancer in Indonesia. The development of mobile learning is a continuation of previous online learning to help the process of early detection of cervical cancer. Data collection methods used observation, interview, and questionnaire techniques, while instructional designs use the ADDIE (Analysis Design Development Implementation Evaluations) model and methods for developing object-oriented programming systems using Unified Modeling Language (UML). The resulting output is the application of early detection of cancer-based mobile learning which is the virtue of this study.

Creator

Muljo, Hery Harjono
Perbangsa, Anzaludin Samsinga
Yulius, Yulius
Pardamean, Bens

Source

International Journal of Interactive Mobile Technologies (iJIM); Vol. 12 No. 2 (2018); pp. 39-53
1865-7923

Publisher

International Association of Online Engineering (IAOE), Vienna, Austria

Date

2018-03-29

Rights

Copyright (c) 2018 Hery Harjono Muljo, Anzaludin Samsinga Perbangsa, Yulius Yulius, Bens Pardamean

Relation

Format

application/pdf

Language

eng

Type

info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article

Identifier

Citation

Hery Muljo Harjono et al., Mobile Learning for Early Detection of Cancer, International Association of Online Engineering (IAOE), Vienna, Austria, 2018, accessed September 27, 2024, https://igi.indrastra.com/items/show/1300

Social Bookmarking