Review Process

PEER REVIEW PORCESS

The 5th ICON-ELT is an international conference hosted by English Education Department, Universitas Islam Malang, Indonesia. The manuscripts submitted to this conference will be double blind peer-reviewed by at least 2 (two) reviewers. The accepted manuscripts will be recommended for online publication following the conference peer-reviewing process. The language used in this conference is English.

For checking Plagiarism, the 5th ICON-ELT Editor will screen plagiarism manually (offline and online database) on the Title, Abstract, and Body Text of the manuscript, and by using Turnitin. If it is found a plagiarism indication, the editorial board will reject the manuscript immediately.

Review Process:

1. Editor will receive the manuscript from the author;

2. Editor will evaluate the manuscript (journal aim and scope, in-house style, supplementary data); (Rejected if not meets criteria)

3. Editor will do screening for plagiarism on offline and online databases manually; (Rejected if found major plagiarism, contact author if found redundancy or minor plagiarism for clarification). The similarity index is a maximum of 15%.

4. Editor will send the manuscript to the reviewer along with the review form (blind review);

5. Reviewer will send back his review form to Editor (with a revised manuscript if necessary);

6. Editor decision (rejected, requires major revision, needs minor revision, or accepted);

7. Confirmation to the Author.

8. If any revisions, the author will revise the manuscript, and should be returned to the editor without delay. Returned later than one month will be considered withdrawn.

This conference uses Harvard Dataverse to preserve research data, if the author intends to preserve and share his/her research data for greater impact on global knowledge. Our review policy regarding this issue is as follows:

Deposited datasets should be treated as part of the article for the purpose of peer review; OR

At acceptance, and prior to the final version of the manuscript, underlying data must be submitted along with a description of how the dataset was created (including any differences from prior versions, and the name of any software packages that were used).

Datasets that derive from work involving human participants should demonstrate that the study participants' privacy was preserved as indicated in the Data Availability Policy. They should also preferably meet the "minimal dataset" requirement described in the Data Availability Policy.