Engineering and intelligent systems increasingly require decision-making under heterogeneous evidence. These sources include multi-source data, predictive models, competing objectives, feasibility constraints, and uncertainty. Evolutionary algorithms (EAs) are widely used in such settings, yet the literature is typically organised by algorithmic lineage, which obscures how and where information is fused within the evolutionary process. This survey reframes EAs as adaptive information fusion architectures. We introduce a fusion-centric taxonomy spanning data-level integration of heterogeneous observations, model/feature-level integration through surrogate and learning components, objective-level integration through multi- and many-objective formulations, constraint handling as feasibility-signal integration, and decision-level integration through ensembles, distributed (island) evolution, and multi-run aggregation. Building on this perspective, we synthesise major EA families according to their dominant fusion mechanisms and review fusion-driven applications across structural and mechanical design, energy and smart grids, robotics and control, communications, healthcare engineering, and neural architecture search. To complement this qualitative synthesis, we propose lightweight quantitative indicators—integration depth, integration diversity, and decision outcome entropy—to characterise algorithm–fusion–domain alignment and to identify recurring success and failure modes, including surrogate bias, over-aggregation, and fusion over-complexity. We conclude with practical design guidelines and discuss emerging directions, including federated evolutionary fusion and reliability considerations in learning- and large language model (LLM)-assisted fusion.
Gamification of learning has been regarded as an important pedagogy to promote students’ learning outcomes, and attempts have been made to integrate it into STEM education. However, the influence of gamification of learning on K-12 students’ STEM educational outcomes, such as domain knowledge, higher-order thinking, and affective outcomes, remains under-researched. This study aims to investigate strategies for integrating gamified learning in STEM education, examine its effects on domain knowledge, higher-order thinking, and affective outcomes, and explore K-12 students’ perceived benefits and challenges of implementing gamified learning in STEM education. We systematically reviewed 86 empirical studies involving 7,128 participants from leading bibliographic databases, examined the effects of gamified learning in STEM using a meta-analysis, and investigated the benefits and challenges of implementing gamified learning in STEM education using a qualitative synthesis. Our findings revealed medium to large effect sizes in favour of gamified learning on domain knowledge (Hedges’ g = .823; p < .001), higher-order thinking (Hedges’ g = .880; p < .001), and affective outcomes (Hedges’ g = .577; p < .001) using a random-effects model. The thematic analysis of interview data from 26 articles identified three themes with 15 sub-themes of benefits and three themes with six sub-themes of challenges of implementing gamified learning in STEM education. This review synthesized findings on the impact of gamified learning across STEM learning outcomes and various moderating factors, while also providing rich insights into authentic participant perceptions of its application in STEM education. This study yielded pedagogical and theoretical insights to effectively implement gamified learning in STEM education.
Reading engagement is a multidimensional construct encompassing motivational, behavioural, and cognitive dimensions, each characterized by distinct features. Although prior research has identified associations among some of these features, few studies have examined them simultaneously or explored their interactions and joint relationships with reading comprehension. This gap limits our understanding of how multiple engagement-related variables may operate together to support reading. Thus, using psychometric network analysis to represent the intricate psychological constructs withinteractions among the variables, this study analysed student questionnaire and reading test data from Hong Kong participants in the Progress in International Reading Literacy Study 2021. The sample included 3830 fourth grade students with 49
Although deaf and hard-of-hearing (DHH) children face significant reading challenges and have been the focus of various interventions, a systematic synthesis of the influencing factors is still lacking. This systematic review addresses this gap by analyzing intervention components, participant characteristics, and methodological quality across studies. A systematic search across six databases (between January 2000 and August 2024) identified 39 studies on reading interventions targeting DHH children, coded for intervention-related components (design, approach, duration, sample size, delivery format, and outcome measures), participant characteristics (age, degree of hearing loss, hearing device usage, and communication modes), and methodological quality (RoB 2 for randomized controlled trials (RCTs), ROBINS-I V2 for quasi-experimental designs, and RoBiNT for single-case studies). Reading interventions for DHH students were predominantly studied using quasi-experimental or single-case studies, typically delivered individually or in small groups. Participants were mainly primary-school-aged children with heterogeneous hearing levels and communication modes; intervention approaches emphasized cognitive-linguistic methods for word reading in younger children and metacognitive strategy-based interventions for comprehension in older ones. Methodological quality assessments indicated low risk or some concerns in the two RCTs, low to serious risk in quasi-experimental studies, and moderate overall quality with critical internal validity weaknesses in single-case studies. These findings underscore the interconnected roles of intervention components, participant characteristics, and methodological quality in shaping reading intervention outcomes for DHH students. The heterogeneous participant profiles and methodological limitations emphasize the need to tailor intervention designs to individual needs and adopt rigorous methodologies to enhance intervention quality.
Parents’ happiness is vital for cultivating young children’s social-emotional competence. However, relatively little is known about the underlying processes through which parents foster children’s functioning. The present study investigated mindful parenting as a mediator for the relations between mothers’ and fathers’ happiness and young children’s social-emotional competence. Specifically, mothers and fathers of 238 first-year kindergarteners in Hong Kong were recruited to complete a set of questionnaires three times at a six-month interval. Cross-lagged path analysis demonstrated that mothers’ mindful parenting mediated the link between their own happiness and children’s social-emotional competence. Although fathers’ mindful parenting did not serve as a mediator, it was consistently related to their own happiness and children’s social-emotional competence over time. Furthermore, actor and partner effects of happiness and mindful parenting were also noted between mothers and fathers. The present findings revealed mother-to-father and father-to-mother effects, but not child-to-parent effects. Despite the bidirectional effects between mothers and fathers, mothers’ happiness is particularly crucial for their practice of mindful parenting. Both mothers’ and fathers’ mindful parenting practice is essential for children’s social-emotional development.
