E3S Web Conf.
Volume 400, 2023International Conference on Sciences, Mathematics, and Education (ICoSMEd 2022)
|Number of page(s)
|Theory and Application in Chemistry
|03 July 2023
Does New Normal Learning Anxiety Scale (NNLAS) Worth to Measure Anxiety? A Study to Investigate Instrument Characteristic
Chemiatry Education, Universitas Palangka Raya, 74874 Kota Palangka Raya, Indonesia
* Corresponding author: firstname.lastname@example.org
During the COVID-19 pandemic, students developed study habits to adapt to online learning, enjoying discussing with lecturers and friends through meeting platforms. However, the lack of interaction gradually erodes their confidence. As a result, they become concerned about the new normal learning environment, where they will have to face lecturers and friends. They must be prepared and equipped to cope with this new environment. Building students’ readiness and confidence in the new normal learning setting can reduce anxiety. Nevertheless, students experience anxiety when it comes to returning to face-to-face learning. Consequently, an attempt has been made to develop the New Normal Learning Anxiety Scale (NNLAS) questionnaire to assess and verify its characteristics. The model development of NNLAS is based on the 4D model. In order to establish content validity, the initial product was evaluated by five experts and explored using Aiken’s formula. This research involved 209 undergraduates from Universitas Palangka Raya to assess construct validity. The Rasch model was employed to examine various characteristics of NNLAS, including unidimensionality, reliability, item difficulty, item fit, and rating scale. The results demonstrate that NNLAS is suitable for measuring students’ learning anxiety.
Key words: New Normal Learning Anxiety Scale (NNLAS) / anxiety / Rasch model
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.