Predicting Learners’ Agility and Readiness for Future Learning Ecosystem
Bibliographic Data
| ID | 22048945 |
|---|---|
| Authors | Habibah Ab Jalil (0000-0003-4242-746X, Universiti Putra Malaysia, corresponding author), Ismi Arif Ismail (0000-0003-1583-2718, Universiti Putra Malaysia), Aini Marina Ma’rof (0000-0002-0373-9471, Universiti Putra Malaysia), Chee Leong Lim (0000-0001-6785-9280, Taylor's University), Nurhanim Hassan (0000-0002-4369-8483, Taylor's University), Nur Raihan Che Nawi (0000-0002-7210-9430, Universiti Putra Malaysia) |
| Year | 2022 |
| Volume | 12 |
| Issue | 10 |
| Pages | 680 |
| Publication date | 2022-10-06 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Education Sciences (JOURNAL) |
| Journal identifiers | ISSN: 2227-7102 • E-ISSN: 2227-7102 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/educsci12100680 |
| OpenAlex | W4303627786 |
| Language | EN |
| References cited | 30 |
Agility and future readiness are fundamental 21st-century skills that could guide university students globally to thriving and benefiting from a VUCA—volatile, uncertain, complex, and ambiguous—world. The ability to respond flexibly, make informed decisions, and adapt to rapid change reflects future-readiness capabilities. However, little is known about the empirical role of the university curriculum, learning ecosystem, and learning experience as perceived by university students in developing these skills. Therefore, we analysed data collected from 209 Malaysian university students from 16 universities to assess whether these three pertinent factors impact the students’ learning agility and determine how well learning agility predicts learners’ future readiness. The present study empirically assessed a theoretical model using a partial least squares structural equation modelling (PLS-SEM) approach. The analysis supported all the hypotheses proposed in this study, which implies that the extended model could effectively predict learners’ agility and future readiness. The results revealed that the university learning experience, ecosystem, and curriculum positively, directly, and significantly affected learning agility and future readiness. Furthermore, the findings showed that student agility significantly mediated the relationships between the student learning experience, university learning ecosystem, and curriculum and student future readiness. Taken together, these results highlight the importance of a future-ready education nurtured by a vibrant learning ecosystem that delivers lasting values and experiences for students and communities to appreciate the opportunities for a challenging yet exciting future offered by a VUCA environment. The established empirical model describing the empirical interplays between these correlates could, in turn, aid better evidence-based policy making in higher education
Curriculum · Empirical evidence · Empirical research · Knowledge management · Learning environment · Mathematics education · Pedagogy · Thriving · Computer Science · E-Learning and Knowledge Management · Educational Leadership and Innovation · Innovation and Socioeconomic Development · Psychology
The origins of intelligence in children.
Beyond a tandem analysis of SEM and PROCESS
Cross-Validatory Choice and Assessment of Statistical Predictions
An updated and expanded assessment of PLS-SEM in information systems research
A predictive approach to the random effect model
Assessing measurement model quality in PLS-SEM using confirmatory composite analysis
A new criterion for assessing discriminant validity in variance-based structural equation modeling
When to use and how to report the results of PLS-SEM
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Learning for and realising curriculum aspirations through schools as learning organisations
Relational processes between people and place
A case for culturally relevant science education in the summer for African American youth
Organizational learning with a pragmatic slant
Curricular innovations and trends
Towards Agility
| Citation velocity | historical |
|---|---|
| Highly cited | No |