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While the personalization design focuses on child-centered design, it restricts the child's contribution to the database, minimises children's agency in shaping it and reinforces individual models of learning. The paper recommends that reading recommendation systems provide opportunities for what Papert described as self-discovery, experimentation, and development of abstract knowledge. Recommendation algorithms need to work in conjunction with diversification mechanisms to challenge and widen children's thinking and diversification should not be conflated with randomization. Practical examples are provided so that the approach described in this article can be used as a foundation for conceptualising and designing children's reading recommendation systems and data-based personalized learning more broadly.<\/jats:p>","DOI":"10.4018\/ijmbl.2019100106","type":"journal-article","created":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T12:52:05Z","timestamp":1554382325000},"page":"80-95","source":"Crossref","is-referenced-by-count":8,"title":["The Learning Value of Personalization in Children's Reading Recommendation Systems"],"prefix":"10.4018","volume":"11","author":[{"given":"Natalia","family":"Kucirkova","sequence":"first","affiliation":[{"name":"UCL Institute of Education, UK & The Norwegian Centre for Learning Environment and Behavioural Research, University of Stavanger, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJMBL.2019100106-0","unstructured":"Azpiazu, I. M., Dragovic, N., & Pera, M. S. 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