Creating technology‐enabled lifelong learning: A heutagogical approach
Bibliographic record
Abstract
Abstract Can a new instructional approach influence lifelong learning and the development of competent lifelong learners? Blended and online learning provides a platform for learning that introduces technological affordance to enable learning. We seek to find an intersection between blended and online learning and lifelong learning through an instructional approach that encourages learners towards management of their own learning. This opens the door to becoming an autonomous, capable, self‐directed lifelong learner. In this context, heutagogy offers an instructional approach that may connect blended and online learning settings with the development of lifelong learning competence. After conducting a systematic literature review using the terms heutagogy, blended and online learning, and lifelong learning, literature that considers how to inspire and build human agency capabilities over the lifespan was chosen for Delphi method expert review. Using this methodology, we explore the possibility that online and blended higher education will contribute, where heutagogical experiences exist, to technology‐enabled lifelong learning. Results corroborate the idea that heutagogy and lifelong learning are intertwined by some common principles and that these are applicable to both blended and online learning settings and lifelong learning. Practitioner notes What is already known about this topic Recent, and what is often continuous, change is impacting all we do, including the design and delivery of education. This change requires new instructional models that improve immediate learning outcomes and prepares learners for learning across the lifespan. The use of instructional processes labeled heutagogy include the opportunity for, and application of, activities of learning self‐direction, ‐determination, and ‐regulation, which can be helpful, even essential, for lifelong learning. What this paper adds This paper identifies an informed perspective, from data, that heutagogical design must be consciously implemented and supported for online and blended learning by instructional designers, instructors, and institutional leadership and infrastructure. It is reasonable to suggest that online and blended learning could contribute, where heutagogical learning opportunities exist, to technology‐enabled lifelong learning. Instructional practices that include choice, flexible or negotiated assessment, facilitation of reflection, learner confidence development, and involvement of the learner in designing their learning can be considered heutagogical. Implications for practice and/or policy Develop policy in support of a change in instructional practice that embraces a heutagogical approach in the design of courses to foster greater self‐directed and lifelong learning. Educational development to support instructors to understand heutagogy and how it can be applied in the design and delivery of blended and online learning to foster technology enabled lifelong learning. With the implementation of a heutagogical approach, student orientation along with purposeful scaffolding needs to be implemented to support students as they become more autonomous learners in technology‐enabled settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.006 | 0.025 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".