Abstract:

Well-designed instructional resources are essential for delivering and reinforcing lessons catering to adult learners' unique needs and preferences in online education. Such learners often exhibit diverse learning styles, prior knowledge, and life experiences, which demand tailored approaches to maximize their learning potential. In this regard, well-designed instructional resources are crucial for catering to varied needs and promoting a self-paced, adaptable learning environment. This study seeks to develop a quality indicator for self-instructional materials (SIM) in Open and Distance Learning environments, exploring their design, implementation, and relationship with cognitive load types and task sets. SIM, defined as self-explanatory, self-contained, self-directed, self-motivating, and self-evaluating, focus on optimizing cognitive load to enhance personalized learning experiences. The research methodology consists of an extensive SIM usability testing procedure that includes resource design, participant selection, and the utilization of learning analytics and survey data to evaluate cognitive load and task set. The study analyzes the relationship between the three cognitive load types (intrinsic, extraneous, and germane) and the task set using the S —> R formula, which is expressed as R = f(S, I, G), where R denotes the germane cognitive load level, S represents the intrinsic cognitive load level, I signifies the extraneous cognitive load level, and G stands for the task set. The results from the SIM usability testing reveal trends, patterns, and significant findings that either support or challenge the study's hypotheses. Descriptive and inferential statistics and visual data illustrations provide a thorough understanding of the outcomes. By reviewing existing literature on instructional resource design, cognitive load theory, and the usage of SIM and LMS in educational settings, this research highlights its importance to the field, identifies gaps in current understanding, and emphasizes the value of combining SIM, LMS, and cognitive load theory to create efficient, personalized learning experiences. The paper concludes with a summary of the main findings, stressing the implications for designing and implementing instructional resources in Open and Distance Learning environments, potential limitations, and suggestions for future research directions.

Keywords:

Self-Instructional Material (SIM), Cognitive Load, Personalized Learning Environments, Online Distance Education.