Enhancing Students’ Critical Thinking and Confidence through Indirect Explicit Grammar Instruction (IEGI) in Learning Grammar
DOI:
https://doi.org/10.30587/didaktika.v24i2.341Keywords:
indirect explicit grammar (EIGI), critical thinking, confidenceAbstract
The aim of this research is to find the strategy how Indirect Explicit Grammar Instruction
(IEGI) is able to enhance students‟ critical thinking and confidence in learning tenses. Since
students usually tend to memorize the form of patter in learning tenses, as a result they have
been repeated rule presentations of grammar structures and lose their sense of critical
thinking to discover. More over, learning grammar on isolated way also make students have
less confidence to speak because they can memorize the pattern, but they cannot use them
accurately. Using classroom action research in two cycle which every cycle consists of three
meetings, the data are collected by using observation cheklist, rubric, test, qestionnare and
students participation sheet. The observation cheklist is used to get the data of the
implementation of IEGI during teaching learning activities in the classroom which students
work in group. The result from rubric shows the improvement of students‟ ctitical thinking
ability improve from 54.05% into 82.50%. While from the test which covered the ability in
analyzing and answering questions which need Higher Order Thinking improve significantly
from 47.56% into 80.90 %. While students‟ confidence improves significantly from 55.56%
into 78.10%
Downloads
Published
How to Cite
Issue
Section
License
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- The work described has not been formally published before, except in the form of an abstract or as part of a published lecture, review, thesis, or overlay journal.
- That it is not under consideration for publication elsewhere,
- That its publication has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
Copyright
Authors who publish with DIDAKTIKA: Jurnal Pemikiran Pendidikan agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
Licensing for Data Publication
Open Data and Software Publishing and Sharing
The journal strives to maximize the replicability of the research published in it. Authors are thus required to share all data, code or protocols underlying the research reported in their articles. Exceptions are permitted but have to be justified in a written public statement accompanying the article.
Datasets and software should be deposited and permanently archived inappropriate, trusted, general, or domain-specific repositories (please consult http://service.re3data.org and/or software repositories such as GitHub, GitLab, Bioinformatics.org, or equivalent). The associated persistent identifiers (e.g. DOI, or others) of the dataset(s) must be included in the data or software resources section of the article. Reference(s) to datasets and software should also be included in the reference list of the article with DOIs (where available). Where no domain-specific data repository exists, authors should deposit their datasets in a general repository such as ZENODO, Dryad, Dataverse, or others.
Small data may also be published as data files or packages supplementary to a research article, however, the authors should prefer in all cases a deposition in data repositories.
