Open AccessE-mastering application utilizing pertinence heuristics evaluation for children
Author(s) -
D. Rajya Lakshmi,
R. Ponnusamy
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i1.9.10009
Subject(s) - heuristics , computer science , heuristic , usability , heuristic evaluation , set (abstract data type) , hyper heuristic , machine learning , strengths and weaknesses , artificial intelligence , human–computer interaction , psychology , programming language , social psychology , operating system , robot learning , mobile robot , robot
Choosing ease of use assessment techniques (UEMs) to uncover convenience issues in e-learning projects is affected by time, cost, simplicity of use, and effectiveness. Heuristic assessment has turned into a generally acknowledged technique for ease of use assessment in programming improvement. This paper presents Heuristic Assessment for Tyke E-learning applications (HECE), an exhaustive arrangement of heuristics for kid e-learning alongside a definite clarification for the ease of use specialists on the most proficient method to apply them. These arrangements of heuristics depend on Nielsen's unique ten heuristics produced for programming. Nielsen heuristics are essentially nonexclusive, and won't not include ease of use credits particular to kids or e-learning. The new HECE set would conquer these weaknesses. The legitimacy and viability of these heuristics were assessed against two created e-learning programs composed by ReDSOFT for KG-2 and exceptional need understudies. The outcomes showed that HECE distinguished subjective likenesses and contrasts with client testing, and that HECE is most appropriate for assessing general and kid ease of use. Consolidated with client testing, HECE offers another track that can help with directing the kid e-learning industry to outline applications that are both instructive and pleasurable for youngsters.