Assessing the effectiveness of the different levels of instructional strategies (DLISt7) for online learning by undergraduate students from the University of Southern Queensland (USQ), Australia

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Authors: Syaril Izwann Jabar
Cited by: 2
References: 10

Abstract

Based on Chickering and Gamson’s (1987) Seven Principles for Good Practice, the purpose of this research project was to attempt to revitalize the principles by amalgamating them with Merrill’s (2006) Different Levels of Instructional Strategy. The primary aim was to develop an instrument for DLISt7 and obtain data that could facilitate its validation and standardization using a pretest-posttest Internet quasiexperimental research design. The proposed measure could then be put forward for use either as a rubric for facilitating the extrinsic implementation of DLISt7, or as a set of unobtrusive diagnostic indicators for assessing the quality of learning intrinsically experienced by students in blended and online courses. The study was conducted across five faculties at a regional Australian multi-campus university. The intent was to contribute to new knowledge by utilizing the data collected to generate awareness about the likelihood of thrusting into practice varying levels of instructional strategies for communicating expectations and relaying information in view of improving the instructional design of future online courses. The idea was to produce a tool that could create more opportunities for more of the principles to be put to good use as an effectiveness multiplier. The critical insight that can be extended to educational administrators, teaching staff and instructional designers is the importance of making good use of whatever was made available, while remaining autonomously eclectic when deciding the discretionary balance between utilizing asynchronous or synchronous communication technology and online resources for blended and online courses.

Fields of Study & Subjects

Online and Blended Learning Innovative Teaching and Learning Methods Online Learning and Analytics

Publication details

Journal / source
University of Southern Queensland ePrints (University of Southern Queensland)
Publication date
20 July 2026
Language
EN
Document type
Thesis