Designing personalised instruction
A research and design framework
Bibliographic Data
| ID | 21297439 |
|---|---|
| Authors | N Kucirkova (0000-0002-2805-1745, The Open University, corresponding author), Libby Gerard (0000-0002-2708-5409, University of California‐Berkeley Graduate School of Education Way Berkeley CA USA), Marcia C Linn (0000-0003-2257-9474, University of California‐Berkeley Graduate School of Education Way Berkeley CA USA) |
| Year | 2021 |
| Volume | 52 |
| Issue | 5 |
| Pages | 1839-1861 |
| Publication date | 2021-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | British Journal of Educational Technology (JOURNAL) |
| Journal identifiers | ISSN: 0007-1013 • E-ISSN: 1467-8535 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/bjet.13119 |
| OpenAlex | W3165441394 |
| Language | EN |
| Citations received | 12 |
| References cited | 46 |
Advances in technology have increased the opportunities for designers to personalise instruction based on student actions. We conducted semi‐structured interviews with an international sample of educational professionals including researchers, teachers and designers, and reviewed interdisciplinary literature on personalisation to propose a framework for personalisation research and design. Thematic analysis of the interviews revealed that professionals value each type of personalisation opportunity (eg, customising for age‐appropriate content, supports for student choice, automated guidance based on learner responses) and identify challenges (eg, trade‐offs between adaptive and standardised instruction). Three research/design dilemmas emerged: individualisation and equity; group customisation and individual benefit; and adaptation and validity of measurement. We discuss these dilemmas in relation to three categories of personalisation: customisation by designers or teachers to support a specific audience (grade level, course, community); individualisation to support user choice (of book to read, project topic); and adaptation of instructional activities based on automated analysis of logged user performance (performance metrics, natural language processing, cumulative indicators). We suggest some guiding questions for a generative agenda for future research on personalised instruction. Practitioner notes What is already known about this topic Personalised learning is popular among educational professionals. Personalised design has multiple and inconsistent definitions. A shared framework for personalised instruction would facilitate research and design. What this paper adds A succinct but comprehensive definition of personalised education. Perspectives on personalisation from an international group of practitioners and designers. A framework including three dilemmas to guide future research on the design and practice of personalised instruction. Implications for practice and/or policy A shared definition of personalisation can support communication across diverse stakeholders. The framework can guide future design and instruction with personalised educational technology. The framework identifies dilemmas that illustrate ethical pathways for policy‐makers responsible for personalised education.
Adaptation (eye) · Instructional design · Knowledge management · Multimedia · Personalization · Qualitative research · Sociology · Thematic analysis · World Wide Web · Computer Science · E-Learning and Knowledge Management · Online Learning and Analytics · Psychology · Technology Use by Older Adults
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| Unique citing works | 12 |
|---|---|
| Citations per year | 2,4 |
| Citation span | 2021 - 2026 (6) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 11 |