Explainable Rules and Heuristics in AI Algorithm Recommendation Approaches——A Systematic Literature Review and Mapping Study

The exponential use of artificial intelligence(AI)to solve and automated complex tasks has catapulted its popularity generating some challenges that need to be addressed.While AI is a powerfulmeans to discover interesting patterns and obtain predictive models,the use of these algorithms comes with a great responsibility,as an incomplete or unbalanced set of training data or an unproper interpretation of the models’outcomes could result in misleading conclusions that ultimately could become very dangerous.For these reasons,it is important to rely on expert knowledge when applying these methods.However,not every user can count on this specific expertise;non-AIexpert users could also benefit from applying these powerful algorithms to their domain problems,but they need basic guidelines to obtain themost out of AI models.The goal of this work is to present a systematic review of the literature to analyze studies whose outcomes are explainable rules and heuristics to select suitable AI algorithms given a set of input features.The systematic review follows the methodology proposed by Kitchenham and other authors in the field of software engineering.As a result,9 papers that tackle AI algorithmrecommendation through tangible and traceable rules and heuristics were collected.The reduced number of retrieved papers suggests a lack of reporting explicit rules and heuristics when testing the suitability and performance of AI algorithms.

Big Data Analytics in Healthcare——A Systematic Literature Review and Roadmap for Practical Implementation

The advent of healthcare information management systems(HIMSs)continues to produce large volumes of healthcare data for patient care and compliance and regulatory requirements at a global scale.Analysis of this big data allows for boundless potential outcomes for discovering knowledge.Big data analytics(BDA)in healthcare can,for instance,help determine causes of diseases,generate effective diagnoses,enhance Qo S guarantees by increasing efficiency of the healthcare delivery and effectiveness and viability of treatments,generate accurate predictions of readmissions,enhance clinical care,and pinpoint opportunities for cost savings.However,BDA implementations in any domain are generally complicated and resource-intensive with a high failure rate and no roadmap or success strategies to guide the practitioners.In this paper,we present a comprehensive roadmap to derive insights from BDA in the healthcare(patient care)domain,based on the results of a systematic literature review.We initially determine big data characteristics for healthcare and then review BDA applications to healthcare in academic research focusing particularly on No SQL databases.We also identify the limitations and challenges of these applications and justify the potential of No SQL databases to address these challenges and further enhance BDA healthcare research.We then propose and describe a state-of-the-art BDA architecture called Med-BDA for healthcare domain which solves all current BDA challenges and is based on the latest zeta big data paradigm.We also present success strategies to ensure the working of Med-BDA along with outlining the major benefits of BDA applications to healthcare.Finally,we compare our work with other related literature reviews across twelve hallmark features to justify the novelty and importance of our work.The aforementioned contributions of our work are collectively unique and clearly present a roadmap for clinical administrators,practitioners and professionals to successfully implement BDA initiatives in their organizations.

Quality of life in patients with gastroenteropancreatic tumours: A systematic literature review

BACKGROUND Gastroenteropancreatic neuroendocrine tumours(GEP-NETs)are slow-growing cancers that arise from diffuse endocrine cells in the gastrointestinal tract(GINETs)or the pancreas(P-NETs).They are relatively uncommon,accounting for 2%of all gastrointestinal malignancies.The usual treatment options in advanced GEP-NET patients with metastatic disease include chemotherapy,biological therapies,and peptide receptor radionuclide therapy.Understanding the impact of treatment on GEP-NET patients is paramount given the nature of the disease.Health-related quality of life(HRQoL)is increasingly important as a concept reflecting the patients’perspective in conjunction with the disease presentation,severity and treatment.AIM To conduct a systematic literature review to identify literature reporting HRQoL data in patients with GEP-NETs between January 1985 and November 2019.METHODS The PRISMA guiding principles were applied.MEDLINE,Embase and the Cochrane library were searched.Data extracted from the publications included type of study,patient population data(mid-gut/hind-gut/GI-NET/P-NET),sample size,intervention/comparators,HRQoL instruments,average and data spread of overall and sub-scores,and follow-up time for data collection.RESULTS Forty-three publications met the inclusion criteria.The heterogeneous nature of the different study populations was evident;the percentage of female participants ranged between 30%-60%,whilst average age ranged from 53.8 to 67.0 years.Eight studies investigated GI-NET patients only,six studies focused exclusively on P-NET patients and the remaining studies involved both patient populations or did not report the location of the primary tumour.The most commonly used instrument was the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-C30(n=28)with consistent results across studies;the GI-NET-specific module Quality of Life Questionnaire-GINET21 was used in six of these studies.A number of randomised trials demonstrated no HRQoL changes between active treatment and placebo arms.The Phase III NETTER-1 study provides the best data available for advanced GEP-NET patients;it shows that peptide receptor radionuclide therapy can significantly improve GEP-NET patients’HRQoL.CONCLUSION HRQoL instruments offer a means to monitor patients’general disease condition,disease progression and their physical and mental well-being.Instruments including the commonly used European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-C30 and GINET21 lack,however,validation and a defined minimal clinical important difference specifically for GINET and P-NET patients.

Locus of Control Theory,Productivity,Job Satisfaction,and Procrastination:A Systematic Literature Review in the Organizational Context of the 21st Century

Locus of control theory,which was developed by Rotter,suggests that there are two main types of peoples’behaviors when attributing their failure or success of their life events:external locus of control and internal.The way that individuals act is determined by their expectations of their specific behaviors and the value that they add to these expectations.For instance,people who fit in the internal category are more likely to attribute their life events to their own behaviors,skills,and attitudes,while people who fit in the external category,tend to attribute their acts to fate,chance,and other exterior factors that are out of their control.The aim of this systematic literature review was to define the fundamental concept of LOC theory,to investigate major findings of the theory in accordance with LOC and procrastination,job satisfaction,and performance and lastly,to discuss the practical use of the theory in the organizational context.

Ethical and legal implications of gene editing in plant breeding:a systematic literature review

Biotechnology policies and regulations must be revised and updated to reflect the most recent advances in plantbreeding technology. New Plant Breeding Techniques(NPBT) such as gene editing have been applied to address the myriad of challenges in plant breeding, while the use of NPBT as emerging biotechnological tools raises legal and ethical concerns. This study aims to highlight how gene editing is operationalized in the existing literature and examine the critical issues of ethical and legal issues of gene editing for plant breeding. We carried out a systematic literature review(SLR) to provide the current states of ethical and legal discourses surrounding this topic. We also identified critical research priority areas and policy gaps that must be addressed when designing the future governance of gene editing in plant breeding.

A systematic literature review to explore sustainable energy development practices in Mozambique

This study thoroughly evaluates sustainable energy practices in Mozambique,identifies suitable activities and suggests future re-search directions.The authors meticulously detail the research tasks undertaken to achieve the primary objective of the study,including organizing articles by publication year,journal and conference papers;identifying the most frequently cited articles;and recognizing countries that have made significant contributions to the concept of sustainable energy.The study highlights the most relevant sustainable energy development practices for Mozambique,identifies suitable activities and suggests future research direc-tions.Through rigorous analysis,six significant areas of sustainable energy development were identified,including renewable energy(RE)resources,environmental science,social sciences,computer science,management and accounting,and Earth and planetary sci-ences.The study used Scopus as the selected multidisciplinary peer-reviewed citation database on 20 February 2023,resulting in 76 publications.The study has been conducted nationwide for several months and thoroughly investigates various resources such as hydro,wind,solar,biomass and geothermal energy.It achieves this by evaluating and characterizing the power generation potential of each RE resource and,in addition,identifying and examining numerous projects at the technical and economic feasibility level to promote the potential of projects and the advantages of RE for the sustainable development of Mozambique.The findings indicate that for sustainable energy development in Mozambique,it is crucial to introduce more policies to support the effectiveness of RE systems while involving the private sector.To achieve this,measures such as reducing investment risks,guaranteeing investment returns and establishing a transparent regulatory framework are required.These steps will attract substantial investments,resolve conflicts and motivate key stakeholders to actively participate in the process.

Systematic Review of Literature for Smartphones Technology Acceptance Using Unified Theory of Acceptance and Use of Technology Model (UTAUT)

Systematic Review and Meta-analysis are techniques which attempt to associate the findings from similar studies and deliver quantitative summaries of the research literature [1]. The Systematic review of research literature identifies the common research methods, research design, sample size, parameters used, survey instruments, etc. used by the group of researchers. This study intends to fulfill this purpose in order to identify common research mythologies, dependent variables, sample sizes, moderators and mediators used in the field of analysing technology adoption based studies that utilizes the UTAUT2 model. This research collected over 59 published articles and conducted descriptive analytics. The results have revealed performance expectancy/perceived usefulness, trust and habit as the best predictors of consumer behavioural intentions towards the adoption of mobile application. Behavioural intention was the best predictor of use behaviour among the 57 articles selected. 274 was the mean sample size of research with 25 mean questionnaire items. SPSS and AMOS were the most common softwares used in all 57 studies, and 32 of those studies used UTAUT1 model while 14 researches incorporated the UTAUT2 model. There were also two promising predictors such as perceived risk on behavioural intention and habit on use behaviour.

Machine learning applied to road safety modeling:A systematic literature review

Road safety modeling is a valuable strategy for promoting safe mobility,enabling the development of crash prediction models(CPM)and the investigation of factors contributing to crash occurrence.This modeling has traditionally used statistical techniques despite acknowledging the limitations of this kind of approach(specific assumptions and prior definition of the link functions),which provides an opportunity to explore alternatives such as the use of machine learning(ML)techniques.This study reviews papers that used ML techniques for the development of CPM.A systematic literature review protocol was conducted,that resulted in the analysis of papers and their systematization.Three types of models were identified:crash frequency,crash classification by severity,and crash frequency and severity.The first is a regression problem,the second,a classificatory one and the third can be approached either as a combination of the preceding two or as a regression model for the expected number of crashes by severity levels.The main groups of techniques used for these purposes are nearest neighbor classification,decision trees,evolutionary algorithms,support-vector machine,and artificial neural networks.The last one is used in many kinds of approaches given the ability to deal with both regression and classification problems,and also multivariate response models.This paper also presents the main performance metrics used to evaluate the models and compares the results,showing the clear superiority of the ML-based models over the statistical ones.In addition,it identifies the main explanatory variables used in the models,which shows the predominance of road-environmental aspects as the most important factors contributing to crash occurrence.The review fulfilled its objective,identifying the various approaches and the main research characteristics,limitations,and opportunities,and also highlighting the potential of the usage of ML in crash analyses.

Serendipity in Recommender Systems:A Systematic Literature Review

A recommender system is employed to accurately recommend items,which are expected to attract the user's attention.The over-emphasis on the accuracy of the recommendations can cause information over-specialization and make recommendations boring and even predictable.Novelty and diversity are two partly useful solutions to these problems.However,novel and diverse recommendations cannot merely ensure that users are attracted since such recommendations may not be relevant to the user's interests.Hence,it is necessary to consider other criteria,such as unexpectedness and relevance.Serendipity is a criterion for making appealing and useful recommendations.The usefulness of serendipitous recommendations is the main superiority of this criterion over novelty and diversity.The bulk of studies of recommender systems have focused on serendipity in recent years.Thus,a systematic literature review is conducted in this paper on previous studies of serendipity-oriented recommender systems.Accordingly,this paper focuses on the contextual convergence of serendipity definitions,datasets,serendipitous recommendation methods,and their evaluation techniques.Finally,the trends and existing potentials of the serendipity-oriented recommender systems are discussed for future studies.The results of the systematic literature review present that the quality and the quantity of articles in the serendipity-oriented recommender systems are progressing.

A corpus-based approach to understanding market access in fisheries and aquaculture international business research:A systematic literature review

Although fisheries and aquaculture studies might seem marginal to international business(IB)studies in general,fisheries and aquaculture IB(FAIB)management is currently facing increasing pressure to meet global demand and consumption for fish in the next coming decades.In part address to this challenge,the purpose of this systematic review of literature(SLR)study is to investigate the use of the term‘market access’in its context of use in the generic literature and business sector discourse,in comparison to the more specific literature and discourse in fisheries,aquaculture and seafood.This SLR aims to uncover the knowledge/interest gaps between the academic subject discourses and business sector practices.Corpus driven in methodology and using a triangulation method of three different text analysis softwares including AntConc,VOSviewer and Web of Science(WoS)analytics,the SLR results indicate a gap in conceptual knowledge and business practices in how market access is conceived,studied and managed in the pharmaceutical and healthcare marketing industry in comparison to fisheries and aquaculture.FAIB's complexity is directly acknowledged in the 2030 Agenda for Sustainable Development and Zero Hunger.And while the product orientation of different business sectors might differ,this SLR study works with the assumption that both business sectors are international in orientation,and complex in their operations from product to market.To that extent,research scholars and practitioners in FAIB will need to broaden their efforts in understanding the multiplicity of forces that influences fisheries and aquaculture and its international orientation towards both emerging as well as mature markets.This SLR suggests a conceptual model in understanding the challenges,the potential barriers as well as avenues for solutions to developing market access for FAIB.

A systematic review of blockchain

Blockchain is considered by many to be a disruptive core technology.Although many researchers have realized the importance of blockchain,the research of blockchain is still in its infancy.Consequently,this study reviews the current academic research on blockchain,especially in the subject area of business and economics.Based on a systematic review of the literature retrieved from the Web of Science service,we explore the top-cited articles,most productive countries,and most common keywords.Additionally,we conduct a clustering analysis and identify the following five research themes:“economic benefit,”“blockchain technology,”“initial coin offerings,”“fintech revolution,”and“sharing economy.”Recommendations on future research directions and practical applications are also provided in this paper.

Big Data Analytics in Telecommunications: Literature Review and Architecture Recommendations

This paper focuses on facilitating state-of-the-art applications of big data analytics(BDA) architectures and infrastructures to telecommunications(telecom) industrial sector.Telecom companies are dealing with terabytes to petabytes of data on a daily basis. Io T applications in telecom are further contributing to this data deluge. Recent advances in BDA have exposed new opportunities to get actionable insights from telecom big data. These benefits and the fast-changing BDA technology landscape make it important to investigate existing BDA applications to telecom sector. For this, we initially determine published research on BDA applications to telecom through a systematic literature review through which we filter 38 articles and categorize them in frameworks, use cases, literature reviews, white papers and experimental validations. We also discuss the benefits and challenges mentioned in these articles. We find that experiments are all proof of concepts(POC) on a severely limited BDA technology stack(as compared to the available technology stack), i.e.,we did not find any work focusing on full-fledged BDA implementation in an operational telecom environment. To facilitate these applications at research-level, we propose a state-of-the-art lambda architecture for BDA pipeline implementation(called Lambda Tel) based completely on open source BDA technologies and the standard Python language, along with relevant guidelines.We discovered only one research paper which presented a relatively-limited lambda architecture using the proprietary AWS cloud infrastructure. We believe Lambda Tel presents a clear roadmap for telecom industry practitioners to implement and enhance BDA applications in their enterprises.

Evidences on adaptive mechanisms for cardiorespiratory diseases regarding extreme temperatures and air pollution:A comparative systematic review

The negative cardiorespiratory health outcomes due to extreme temperatures and air pollution are widely stud-ied,but knowledge about the effectiveness of the implementation of adaptive mechanisms remains unclear.The objective of this paper is to explore the evidence of adaptive mechanisms for cardiorespiratory diseases regard-ing extreme temperatures and air pollution by comparing the results of two systematic literature review(SLR)processes sharing the same initial research question but led by two research groups with different academic back-grounds working in the same multidisciplinary team.We start by presenting the methodological procedures and the results of the SLR triggered by the research group mainly composed by researchers with a background in ge-ography(named geographical strategy).We then compare these results with those achieved in the SLR led by the research group with a background in epidemiology(named epidemiological strategy).Both SLR were developed under the EU Horizon 2020 Project“EXHAUSTION”.The results showed:1)the lack of evidence regarding the effectiveness of adaptation measures,namely due to the limited number of studies about the topic,the prepon-derance of studies dedicated to heat extremes or the unbalance between different adaptation measures;2)that the choice of search terms in the geographical strategy,despite being more comprehensive at first sight,ended up retrieving less results,but it brought new studies that can complement the results of the epidemiological strategy.Therefore,it is suggested that to strengthen the empirical evidence of the effectiveness of adaptation measures,powerful multidisciplinary teams should work together in the preparation of SLR in topics of great complexity,such as the one presented in this paper.

Adoption of Improved Rice Varieties in the Global South:A Review

Improved rice varieties(IRVs)play a significant role in establishing food security and improving livelihood in the Global South since its introduction in the 1960s.However,the adoption of new IRVs has remained relatively low.This low adoption poses a challenge to rice-producing and consuming countries as they are increasingly threatened by production shortages,malnutrition,and poor rice quality.Many empirical studies have attempted to identify the determinants influencing the adoption of IRVs by distinguishing the characteristics between adopters and non-adopters.This review showed a consensus on the important determinants influencing the adoption of IRVs in the Global South.Findings synthesized from 99 studies suggested that variables(farm size,education,information access and farm location)examined extensively are not necessarily the most important determinants of adoption when undertaking a weighted analysis.Terrain,source of seed and technology-related attributes(perceived yield,maturity,ease of use,marketability and technical efficiency)are more important determinants of adoption,with determinants changing according to adoption type(probability or intensity of adoption),variety type and region.The recommendations for future adoption studies include:incorporating more technology-specific variables,increasing research for overlooked regions and variety types,shifting away from predominant static analysis by capturing the dynamics of the adoption process,and considering the potential biases in analyses.This review will facilitate the development of targeted interventions and policies that promote IRV adoption in the Global South.

Systematic Review of Graphical Visual Methods in Honeypot Attack Data Analysis

Mitigating increasing cyberattack incidents may require strategies such as reinforcing organizations’ networks with Honeypots and effectively analyzing attack traffic for detection of zero-day attacks and vulnerabilities. To effectively detect and mitigate cyberattacks, both computerized and visual analyses are typically required. However, most security analysts are not adequately trained in visualization principles and/or methods, which is required for effective visual perception of useful attack information hidden in attack data. Additionally, Honeypot has proven useful in cyberattack research, but no studies have comprehensively investigated visualization practices in the field. In this paper, we reviewed visualization practices and methods commonly used in the discovery and communication of attack patterns based on Honeypot network traffic data. Using the PRISMA methodology, we identified and screened 218 papers and evaluated only 37 papers having a high impact. Most Honeypot papers conducted summary statistics of Honeypot data based on static data metrics such as IP address, port, and packet size. They visually analyzed Honeypot attack data using simple graphical methods (such as line, bar, and pie charts) that tend to hide useful attack information. Furthermore, only a few papers conducted extended attack analysis, and commonly visualized attack data using scatter and linear plots. Papers rarely included simple yet sophisticated graphical methods, such as box plots and histograms, which allow for critical evaluation of analysis results. While a significant number of automated visualization tools have incorporated visualization standards by default, the construction of effective and expressive graphical methods for easy pattern discovery and explainable insights still requires applied knowledge and skill of visualization principles and tools, and occasionally, an interdisciplinary collaboration with peers. We, therefore, suggest the need, going forward, for non-classical graphical methods for visualizing attack patterns and communicating analysis results. We also recommend training investigators in visualization principles and standards for effective visual perception and presentation.

A Systematic Review of Economic Evaluation of CDK4/6 Inhibitors in HR+/HER2-Advanced Breast Cancer

Objective To review the domestic and foreign economic studies on CDK4/6 inhibitors in first-line or second-line treatment of HR+/HER2-advanced breast cancer,and to analyze the main methodologies and research results.Methods Systematic literature review was used to search PubMed,EMBASE,Cochrane Library,CNKI,CBM,and Wanfang database.The incremental cost-effectiveness ratio was taken as the main outcome index,and all pharmacoeconomic evaluations with CDK4/6 inhibitors as intervention measures were included,such as Palbociclib,Ribociclib,and Abemaciclib.According to the Quality of Health Economic Studies Instrument,the quality of the included articles was evaluated,and then the included literature was analyzed.Results and Conclusion A total of 16 pharmacoeconomic evaluation studies were included,mainly from the perspective of national healthcare systems or third-party payers.Only 2 studies focused on second-line treatment,and the remaining treatment levels were first-line treatment.In terms of model structure,7 studies adopted the Markov model,6 studies adopted the PSM model,and 3 studies adopted the DES model.The basic analysis results showed that CDK4/6 inhibitor combined with endocrine regimen was not economical compared with endocrine alone regimen when the threshold was the conventional willingness to pay(WTP)value of each country.The uncertainty analysis included deterministic sensitivity analysis and probability sensitivity analysis.The included studies are all Cost-Utility Analysis with high-quality evaluation,which can provide evidence support for health-related decision-makers in decision-making.It can also provide methodological reference for the economic evaluation of other targeted drugs.

Small-scale self-driving cars:A systematic literature review

The autonomous vehicle(AV)technology has the potential to significantly improve safety and efficiency of the transportation and logistics industry.Full-scale AV testing is limited by time,space,and cost,while simulation-based testing often lacks the necessary accuracy of AV and environmental modeling.In recent years,several initiatives have emerged to test autonomous software and hardware on scaled vehicles.This systematic literature review provides an overview of the literature surrounding small-scale self-driving cars,summarizing the current autonomous platforms deployed and focusing on the software and hardware developments in this field.The studies published in English-language journals or conference papers that present small-scale testing of self-driving cars were included.Web of Science,Scopus,Springer Link,Wiley,ACM Digital Library,and TRID databases were used for the literature search.The systematic literature search found 38 eligible studies.Research gaps in the reviewed papers were identified to provide guidance for future research.Some key takeaway emerging from this manuscript are:(i)there is a need to improve the models and neural network architectures used in autonomous driving systems,as most papers present only preliminary results;(ii)increasing datasets and sharing databases can help in developing more reliable control policies and reducing bias and variance in the training process;(iii)small-scaled vehicles to ensure safety is a major benefit,and incorporating data about unsafe driving behaviors and infrastructure problems can improve the accuracy of predictive models.

Systematic Analysis of Safety and Security Risks in Smart Homes

The revolution in Internet of Things(IoT)-based devices and applications has provided smart applications for humans.These applications range from healthcare to traffic-flow management,to communication devices,to smart security devices,and many others.In particular,government and private organizations are showing significant interest in IoT-enabled applications for smart homes.Despite the perceived benefits and interest,human safety is also a key concern.This research is aimed at systematically analyzing the available literature on smart homes and identifying areas of concern or risk with a view to supporting the design of safe and secure smart homes.For this systematic review process,relevant work in the most highly regarded journals published in the period 2016–2020(a section of 2020 is included)was analyzed.A final set of 99 relevant articles(journal articles,book sections,conference papers,and survey papers)was analyzed in this study.This analysis is focused on three research questions and relevant keywords.The systematic analysis results and key insights will help researchers and practitioners to make more informed decisions when dealing with the safety and security risks of smart homes,especially in emergency situations.

Barriers and Drivers of Sustainable Business Model Innovation:Present and Future Research Perspectiv

Sustainable business model innovation(SBMI)introduced a unique frontier in current business operations and innovation management.Despite the numerous advantages of SBMI to contemporary business strategy,most established firms face challenges in its successful implementation.Through a systematic review process(SRP),the paper attempted to critically evaluate and analyze the previous outcome on the barriers and drivers to SBMI.The research explored 42 prior studies to identify the thematic study areas,highlight the research gaps,and outline future propositions and agendas.The research thoroughly evaluates the state-of-the-art regarding barriers and drivers to implement SBMI.The SRP approach utilized in the study sheds light on the intricacies of SBMI by highlighting six critical barriers:institutional,organizational,strategic,resource allocation,technological,and financial barriers that hinder the successful deployment of SBMI.In addition,the study’s findings indicated that organizational learning,knowledge management,dynamic capabilities resource mobilization,innovative business activities,and human resource development could be a catalyst to the successful implementation of SBMI.Furthermore,the study highlighted some critical gaps and agendas for future research on SBMI.This study contributes to the literature on business model innovation and offers a practical outlook that can facilitate firms and policymakers in developing strategies to improve their business model.

How Cooperative Learning Is Conceptualized and Implemented in Chinese Physical Education:A Systematic Review of Literature

Purpose:The purpose of this literature review was to investigate how cooperative learning(CL)has been conceptualized and implemented in Chinese physical education(PE).CL is one of the most influential and widespread areas of theory,research,and practice in western education.With the promotion of Chinese government policies,CL has become a popular field of research and was widely used as a pedagogical practice in Chinese.Design/Approach/Methods:Shulruf’s five methodological steps were utilized as the process of screening and selecting relevant studies.Inductive analysis and constant comparison were conducted for analyzing the chosen literature.Findings:The analytic induction revealed four key themes:(a)historical development,(b)policy influence,(c)conceptualization of CL,and(d)implementation of CL.We found that the conceptualization of CL in Chinese PE was ambiguous,and the implementation of CL was predominantly documented by quantitative research methods.In addition,few studies were conducted at the elementary school level.Originality/Value:This is a comprehensive literature review on CL in Chinese PE.Findings and recommendations in this article will be beneficial for policymakers,scholars,and PE teachers to better understand and promote CL in China.