Application of Artificial Intelligence in the BOPPPS Model: A Systematic Literature Review.
Background: The BOPPPS instructional model (Bridge‐in, Objective, Pre‐assessment, Participatory Learning, Post‐assessment, Summary) is widely used in higher education to promote structured and student‐centred learning. With the rapid advancement of artificial intelligence (AI), educators are increas...
| Publicado en: | Journal of Computer Assisted Learning Vol. 42; no. 4; pp. 1 - 21 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Aug2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=195655200&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 195655200 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Aug2026 vid: 42 iid: 4 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 195655200 195655200 195655200 10.1002/jcal.70272 195655200 ppf: 1 ppct: 20 formats: tig: atl: Application of Artificial Intelligence in the BOPPPS Model: A Systematic Literature Review. aug: au: Ma, Yangbao Chi, Changlong Yu, Xiang Wang, Yuzhou Xu, Yali Xin, Changzheng Wang, Lina Shi, Suyu Yang, Liu Wang, Zhengling Cai, Chang affil: College of Materials Engineering, Henan University of Engineering, Zhengzhou Henan,, China sug: subj: Artificial Intelligence Models, Educational Computer-Assisted Instruction Education, Masters Outcomes of Education Human Systematic Review PubMed Descriptive Statistics Confidence Intervals Funding Source ab: Background: The BOPPPS instructional model (Bridge‐in, Objective, Pre‐assessment, Participatory Learning, Post‐assessment, Summary) is widely used in higher education to promote structured and student‐centred learning. With the rapid advancement of artificial intelligence (AI), educators are increasingly exploring how AI technologies can support teaching and learning within this framework. However, existing research on AI‐integrated BOPPPS instruction remains scattered, and a systematic synthesis of current evidence is still lacking. Objectives: This study aims to systematically review research on the integration of AI technologies into the BOPPPS instructional model in higher education and examine their effects on teaching and learning outcomes. Methods: A systematic review was conducted following the PRISMA 2020 guidelines. Multiple academic databases were searched for empirical studies published between 2015 and 2025, and studies were screened using predefined inclusion criteria. Forty‐six eligible studies were included and analysed to identify the types of AI technologies used, their application across different BOPPPS stages, and their reported educational impacts. Results and Conclusions: The review shows a growing body of research, particularly after 2018, integrating technologies such as intelligent tutoring systems, machine learning, virtual and augmented reality, and generative AI into BOPPPS‐based teaching. These technologies were reported to support personalised learning, increase student engagement, and facilitate data‐informed instruction, leading to improved academic performance, enhanced higher‐order thinking skills, and stronger learning motivation. Nevertheless, many studies remain small‐scale and quasi‐experimental, and challenges related to data privacy, teacher readiness, and equitable access persist. Future research should prioritise large‐scale and theory‐driven studies to strengthen the evidence base and support effective implementation. Lay Summary: What is currently known about this topic? ○BOPPPS is a structured teaching model widely used in higher education.○Artificial intelligence is increasingly applied to support teaching.○AI can enable personalised learning and faster feedback for students.○Evidence on AI use within BOPPPS remains scattered and limited.What does this paper add? ○Provides a systematic review of AI integration within the BOPPPS model.○Identifies how AI tools support different stages of BOPPPS teaching.○Summarises evidence on impacts on learning outcomes and engagement.○Highlights current research gaps and implementation challenges.Implications for practice and/or policy ○AI tools can enhance structured teaching and active learning.○Teachers need training to effectively integrate AI into teaching.○Institutions should address data privacy and access equity issues.○More large‐scale studies are needed to guide policy and practice. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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