Title: Self-regulated learning skills as the predictors for the positive perception of the online accelerated instruction learning experiences

Authors: Cherng-Jyh Yen; Chih-Hsiung Tu; Emrah Emre Ozkeskin; Laura E. Sujo-Montes

Addresses: Department of Educational Foundations and Leadership, Old Dominion University, New Education Building, Norfolk, Virginia 23529, USA ' Department of Educational Specialties, Northern Arizona University, P.O. Box 5774, Flagstaff, AZ 86011, USA ' Department of Distance Education, Open Education Faculty, Anadolu University, Yunus Emre Kampüsü, 26470, Tepebaşı/Eskişehir, Turkey ' Department of Educational Specialties, Northern Arizona University, P.O. Box 5774, Flagstaff, AZ 86011, USA

Abstract: Many institutions have adopted an online accelerated instruction model in which intensive classes are offered during the course of a normal semester to help students to complete classes. The goal of accelerated instructions is to offer students the advantage of completing classes in a shorter time span. Current research focused on comparing different instructional lengths, reporting mixed findings. Online accelerated instructions are not necessarily superior or inferior to traditional 16-week instructions. Research should focus on the preparation of students on how to succeed in accelerated online courses. This study examines how self-regulated learning skills may serve as predictors to successful learning experiences through online accelerated instructions. It concludes that all six self-regulated learning skills can predict online accelerated learning experience success and suggested that educators should identify and prepare students with relevant self-regulated learning skills prior to the accelerated instructions to prepare for positive learning.

Keywords: self-regulated learning; SRL; online learning; instruction lengths; course scheduling; predictive analytics.

DOI: 10.1504/IJIL.2021.112997

International Journal of Innovation and Learning, 2021 Vol.29 No.2, pp.129 - 153

Received: 27 Jan 2020
Accepted: 26 Apr 2020

Published online: 15 Dec 2020 *

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