A Rasch Analysis of Students’ Academic Motivation toward Mathematics in an Adaptive Learning System

Abstract

Despite the criticality of considering student academic motivation as it influences learning, research within the field of adaptive learning technologies for education has so far focused more on customising instruction to implement personalised learning, than investigating how personalised learning is associated with learners’ motivation. Given this, a robust instrument is required to gather information about student academic motivation within the context of adaptive learning technologies. This study sought to validate the Academic Motivation Toward Mathematics Survey (AMTMS) currently used to measure motivation based on self-determination theory in mathematics education at pre-tertiary levels (grades 11 and 12) in Asia. A total of 196 participants recruited via availability sampling took part in this study, after interacting with an in-house mathematics adaptive learning system within a tertiary educational institution. The validation was performed based on modern test theory given that it overcomes some limitations of classical factor analytic approaches. Results supported the factorial structure of the AMTMS but 12 of the original 21 items had to be rescored to establish ordered thresholds. Further, the bifactor equivalent solution suggested the possibility of reporting a singular motivation index comprising the five factors within the AMTMS. Along with the results, this study offers researchers a robust and validated instrument to measure motivation toward mathematics that can be used within an adaptive learning environment.

Factors Influencing Students’ Achievements in the Content and Cognitive Domains in TIMSS 4th Grade Science and Mathematics in the United Arab Emirates

“…House and Telese [42] indicated that there is a significant positive relationship between student engagement and academic achievement. Students' engagement could be promoted through collaborative learning, as this has a positive impact on student learning behaviors and academic achievement [43]. Teamwork engagement has a positive influence on students' personal success, learning and work satisfaction [44].…”

Measuring Learner Satisfaction of an Adaptive Learning System

“…[ 12 ], researchers have further added that satisfaction and self-efficacy lead to user intentions of utilising learning systems [ 13 , 14 ]. Even though it is crucial to account for user satisfaction as it affects learning, research in the area of adaptive learning technologies for education has concentrated more on tailoring instruction to implement personalised learning, rather than exploring how personalised learning is related to learner satisfaction [ 15 ]. Further, multiple published instruments assessing learner satisfaction have been developed within the context of instructor-led courses, as opposed to student-centred, self-led adaptive learning courses.…”

“…[ 23 , 24 ] concurred with similar viewpoints by postulating that user satisfaction is one of the most important factors when addressing the success of an information system. Nonetheless, this has not been thoroughly evident within research of adaptive learning technologies for education, with more focussing on methods to personalise learning [ 15 ].…”

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“…Mathematical classes aim to develop the education seekers' logical thinking, provide a basis for acquiring scientific activity skills. At the same time, the implementation of personal qualities and acquisition of the abilities mentioned above by pupils and students requires intense and systematic independent work (Lim et al, 2022).…”