Designing, Developing and Examining the Effectiveness of a Machine Learning–Based Mobile Recommendation System for Parents' Digital Parenting Skills.
It is of paramount importance that children are equipped with the requisite digital parenting skills to protect them from the risks and threats that they may encounter in the digital environment while also enabling them to seize the opportunities that the digital realm presents. Mobile recommendatio...
| Published in: | Child & Family Social Work Vol. 30; no. 4; pp. 794 - 860 |
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| Main Authors: | , , , , , |
| Format: | pictorial research tables/charts Journal Article |
| Published: |
Wiley-Blackwell
Nov2025
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188520392&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188520392 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13567500 ETB jtl: Child & Family Social Work issn: 13567500 maglogo: Y pubinfo: dt: Nov2025 vid: 30 iid: 4 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 188520392 178935002 188520392 188520392 10.1111/cfs.13218 188520392 ppf: 794 ppct: 66 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Designing, Developing and Examining the Effectiveness of a Machine Learning–Based Mobile Recommendation System for Parents' Digital Parenting Skills. aug: au: Özaydin Aydoğdu, Yıldız Yildiz Durak, Hatice Aydoğdu, Şeyhmus Somyürek, Sibel Güyer, Tolga Kurnaz, Furkan affil: UZEM, Nevşehir Hacı Bektaş Veli University, Nevşehir, Turkey sug: subj: Digital Technology Utilization Parents Education Parenting Education Online Education Machine Learning Mobile Applications Evaluation Software Design Evaluation Outcomes of Education Evaluation Human Funding Source Child Pilot Studies User-Computer Interface Course Content Neural Networks (Computer) Reliability and Validity Scales Child: 6-12 years ab: It is of paramount importance that children are equipped with the requisite digital parenting skills to protect them from the risks and threats that they may encounter in the digital environment while also enabling them to seize the opportunities that the digital realm presents. Mobile recommendation systems (MRS) represent a significant intervention for the development of digital parenting competencies among adults. Nevertheless, there is no evidence in the literature of any attempt to develop the system. The objective of this study is to examine the process of developing an MRS for parents' digital parenting skills and to evaluate the effectiveness of the developed system through a pilot study. The study employed the developmental research Type 1 model. The study was structured in three stages: the design of the MRS, the development of the recommendation system (RS) and the pilot study. In order to facilitate the development of the MRS, three distinct working groups were established. The research yielded several key findings. Primarily, it established the theoretical foundation of the MRS, delineated the design principles to be considered in system design and elucidated their application in the system. Additionally, it identified the essential components and functions that should be incorporated into the system. In light of the expert opinions on compliance with andragogical principles, it was observed that the consideration of environmental factors emerged as a prominent theme. It was observed that the experts assigned the highest suitability scores to fault tolerance, low physical effort and an instructional environment in the system design. The system was found to be effective in terms of redundancy, sound and picture quality for all content titles and multimedia principles. The findings of this study indicate that the MRS may be an effective tool for fostering digital parenting skills. However, further research is necessary to develop age‐appropriate measures and to assess the long‐term impact of the system. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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