Learning Component Research Articles

The Future of Feedback

Research shows that feedback practices significantly impact key student outcomes, including performance, engagement, and satisfaction (Esmaeeli, Shandiz, Shojaei, Fazli & Ahmadi 2023). Feedback is a crucial component of learning in Higher Education (HE) and plays a vital role in developing critical thinking, improving retention, and enhancing student engagement. The importance of timely dialogic feedback in enhancing student engagement and potentially improving retention is well understood (Advance HE 2020). However, academic staff are increasingly time-poor, with reduced opportunities to provide regular in-depth quality feedback outside of that given for summative assessment (Henderson, Ryan & Phillips 2019). Early experimentations with using Generative AI (GenAI) such as ChatGPT to provide feedback for formative assessment recognises that students will learn and work in an AI-enabled world beyond their university studies (Bowditch 2023). GenAI can be leveraged inside and outside the classroom to achieve positive student engagement and improved skill development thereby affording them the skills and knowledge necessary to succeed (Hooda et al. 2022). Engaging with GenAI for feedback purposes offers an opportunity to increase equitable access to feedback across the student cohort, to support and further develop their critical skills and learning outcomes. As Verhoeven and Rana (2023) note, “AI disruption may present an opportunity to shift the focus from assessment of learning to assessment for learning”. Utilising GenAI for feedback purposes can provide rapid, personalised learning support, and aid with planning, drafting, and revising student work. However, this adoption of GenAI for feedback must be driven and developed by the educator, keeping the human in the loop to ensure quality (Atchley, Pannell, Wofford, Hopkins & Atchley). Our project draws on the principles of feedback literacy, current research on using AI as learning tool (Verhoeven & Rana 2023b; Tubino & Adachi 2022) and emphasises student-centred learning through dialogic feedback practices. The project draws on scholarship from Mollick and Mollick’s seven approaches to student use of AI (2023), Perkins, Furze, Roe and MacVaugh’s framework for ethical integration of AI in assessment (2024), and emerging work from Liu, Brightman, and Miller on GenAI and feedback (2023). This presentation addresses the conference theme of Technology, providing an overview and reflection on staff development and adoption of GenAI for feedback processes for the benefit of student learning. We will showcase four use cases of the use of GenAI to design and implement feedback creation for undergraduate formative assessment across the three Colleges at the University of Newcastle. All cases engage innovation in Technology Enhanced Learning (TEL) practice in developing GenAI tools to support student learning via feedback. The presentation addresses the benefits and challenges of each approach. Recognising the value of feedback in student learning, this PechaKucha is aimed at a diverse audience in HE. Our presentation will demonstrate applicability and adaptability to a range of disciplines as we explore the impact new and emerging GenAI technologies can have on HE. We will introduce the possibilities of using GenAI for feedback purposes, and encourage staff to consider experimenting with and adopting their own innovative TEL practices.

Enhanced Learning Outcomes with Audio in E-learning: An Analysis

Audio in any form whether as narration, sound effects, background music, or commentary can make e-learning more interesting for a learner. It completes the sensory engagement in a learner where the visual meets the auditory to comprehend a learning component. As an instructional designer and trainer, over the years, I have created several e-learning courses for adult learners with and without audio. The learning outcomes of the two when compared using several surveys and other evaluation mechanisms showed that learners not only prefer learning instruction that has audio but were also able to retain the learning and apply it to their jobs. This paper analyses how the level of learning outcomes is better in e-learning courses with audio than without audio. It shares some of the science and research that supports this. In addition, it describes the learner surveys and evaluation mechanisms that I have used to prove this and discusses the national and international compliances that make audio a mandate in e-learning to support of my analysis.

Closing the gap between SGP4 and high-precision propagation via differentiable programming

The simplified general perturbations 4 (SGP4) orbital propagation model is one of the most widely used methods for rapidly and reliably predicting the positions and velocities of objects orbiting Earth. Over time, SGP models have undergone refinement to enhance their efficiency and accuracy. Nevertheless, they still do not match the precision offered by high-precision numerical propagators, which can predict the positions and velocities of space objects in low-Earth orbit with significantly smaller errors.In this study, we introduce a novel differentiable version of SGP4, named ∂SGP4. By porting the source code of SGP4 into a differentiable program based on PyTorch, we unlock a whole new class of techniques enabled by differentiable orbit propagation, including spacecraft orbit determination, state conversion, covariance similarity transformation, state transition matrix computation, and covariance propagation. Besides differentiability, our ∂SGP4 supports parallel propagation of a batch of two-line elements (TLEs) in a single execution and it can harness modern hardware accelerators like GPUs or XLA devices (e.g. TPUs) thanks to running on the PyTorch backend.Furthermore, the design of ∂SGP4 makes it possible to use it as a differentiable component in larger machine learning (ML) pipelines, where the propagator can be an element of a larger neural network that is trained or fine-tuned with data. Consequently, we propose a novel orbital propagation paradigm, ML-∂SGP4. In this paradigm, the orbital propagator is enhanced with neural networks attached to its input and output. Through gradient-based optimization, the parameters of this combined model can be iteratively refined to achieve precision surpassing that of SGP4. Fundamentally, the neural networks function as identity operators when the propagator adheres to its default behavior as defined by SGP4. However, owing to the differentiability ingrained within ∂SGP4, the model can be fine-tuned with ephemeris data to learn corrections to both inputs and outputs of SGP4. This augmentation enhances precision while maintaining the same computational speed of ∂SGP4 at inference time. This paradigm empowers satellite operators and researchers, equipping them with the ability to train the model using their specific ephemeris or high-precision numerical propagation data.

A Test Report Optimization Method Fusing Reinforcement Learning and Genetic Algorithms

Filtering high-variability and high-severity defect reports from large test report databases is a challenging task in crowdtesting. Traditional optimization algorithms based on clustering and distance techniques have made progress but are limited by initial parameter settings and significantly decrease in efficiency with an increasing number of reports. To address this issue, this paper proposes a method that integrates reinforcement learning with genetic algorithms for crowdsourced testing report optimization, called Reinforcement Learning-based Genetic Algorithm for Crowdsourced Testing Report Optimization (RLGA). Its core goal is to identify distinct, high-severity defect reports from a large set. The method uses genetic algorithms to generate the optimal report selection sequence and adjusts the crossover probability (Pc) and mutation probability (Pm) dynamically with reinforcement learning based on the population’s average fitness, best fitness, and diversity. The reinforcement learning component uses a hybrid SARSA and Q-Learning strategy to update the Q-value table, allowing the algorithm to learn quickly in early iterations and expand the search space later to avoid local optima, thereby improving efficiency. To validate the RLGA method, this paper uses four public datasets and compares RLGA with six classic methods. The results indicate that RLGA outperforms BDDIV in terms of execution time and is less sensitive to the total number of test reports. In terms of optimization objectives, the test reports selected by RLGA have higher levels of defect severity and diversity than those selected by the random choice, BDDIV, and TSE methods. Regarding population diversity, RLGA effectively enhances the uniformity and diversity of individuals compared to random initialization. In terms of convergence speed, RLGA is superior to the GA, GA-SARSA, and GA-Q methods.

Gaze and hand behaviors during haptic abilities testing-An update to multimedia learning theory.

The Cognitive Theory of Multimedia Learning (CTML) suggests humans learn through visual and auditory sensory channels. Haptics represent a third channel within CTML and a missing component for experiential learning. The objective was to measure visual and haptic behaviors during spatial tasks. The haptic abilities test (HAT) quantifies results in several realms, accuracy, time, and strategy. The HAT was completed under three sensory conditions using sight (S), haptics (H), and sight with haptics (SH). Subjects (n = 22, 13 females (F), 20-28 years) completed the MRT (10.6 ± 5.0, mean ± SD) and were classified as high or low spatial abilities scores with respect to mean MRT: high spatial abilities (HSA) (n = 12, 6F, MRT = 13.7 ± 3.0), and low spatial ability (LSA) groups (n = 10, 7F, MRT = 5.6 ± 2.0). Video recordings gaze and hand behaviors were compared between HSA and LSA groups across HAT conditions. The HSA group spent less time fixating on mirrored objects, an erroneous answer option, of HAT compared to the LSA group (11.0 ± 4.7 vs. 17.8 ± 7.3 s, p = 0.020) in S conditions. In haptic conditions, HSA utilized a hand-object interaction strategy characterized as palpation, significantly less than the LSA group (23.2 ± 16.0 vs. 43.1 ± 21.5 percent, p = 0.022). Before this study, it was unclear whether haptic sensory inputs appended to the mental schema models of the CTML. These data suggest that if spatial abilities are challenged, LSA persons both benefit and utilize strategies beyond the classic CTML framework by using their hands as a third input channel. This data suggest haptic behaviors offer a third type of sensory memory resulting in improved cognitive performance.

Cortical norepinephrine-astrocyte signaling critically mediates learned behavior.

Updating behavior based on feedback from the environment is a crucial means by which organisms learn and develop optimal behavioral strategies 1-3 . Norepinephrine (NE) release from the locus coeruleus (LC) has been shown to mediate learned behaviors 4-6 such that in a task with graded stimulus uncertainty and performance, a high level of NE released after an unexpected outcome causes improvement in subsequent behavior 7 . Yet, how the transient activity of LC-NE neurons, lasting tens of milliseconds, influences behavior several seconds later, is unclear. Here, we show that NE acts directly on cortical astrocytes via Adra1a adrenergic receptors to elicit sustained increases in intracellular calcium. Chemogenetic blockade of astrocytic calcium elevation prevents the improvement in behavioral performance. NE-activated calcium invokes purinergic pathways in cortical astrocytes that signal to neurons; pathway-specific astrocyte gene expression is altered in mice trained on the task, and blocking neuronal adenosine-sensitive A1 receptors also prevents post-reinforcement behavioral gain. Finally, blocking either astrocyte calcium dynamics or A1 receptors alters encoding of the task in prefrontal cortex neurons, preventing the post-reinforcement change in discriminability of rewarded and unrewarded stimuli underlying behavioral improvement. Together, these data demonstrate that astrocytes, rather than indirectly reflecting neuronal drive, play a direct, instrumental role in representing task-relevant information and signaling to neurons to mediate a fundamental component of learning in the brain.

Implementing Technology-Enhanced Support for First-Year Students on Blackboard: Lessons Learned.

Technology Enhanced Learning has become one of the key components of teaching and learning in the current environment and mainly because of Covid-19, hence the introduction of the Technology Enhanced Learning Programme. The Technology Enhanced Learning Student Assistants (TeL Assistants) programme supports students in the university with Blackboard (University choice of LMS). The programme was established in 2021 since there was a need to assist students in the use of Blackboard. With Covid, the university moved to strictly online and that became a challenge to the students. With most undergraduate students coming from disadvantaged high schools and backgrounds, there was a need for the programme. The TeL student assistants undergo training by the Teaching and Learning Consultants. The aim of this study was to evaluate how the TeL student Assistants supported the students of the University of Fort Hare on how to navigate Blackboard. This study examined the benefits of TeL student Assistant’s support in first-year students navigating their modules using Blackboard as an LMS. A purposive sample of undergraduate students that were trained by TeL student assistants submitted data through a qualitative survey in which they narratively conveyed their perspectives on support provided for Blackboard by the TeL Student Assistants. Data was analysed through coding, which were then assigned to themes and categories. The significant aspect of the TeL student assistants which enabled students to use Blackboard was the submission of assignments and tests, the facilitator’s knowledgeability and the patience students received from the TeL student assistants. The findings of the study directly benefit the university and higher education because they will provide information upon which we can take action to improve the support, retention, and throughput of students at the University of Fort Hare (UFH).

Artificial Intelligence Assistance and Cognitive Abilities: Harnessing AI-Assisted Heuristic Methods for Transitioning from Critical to Creative Thinking in English Language Learning

Transitioning from critical to creative thinking is an essential component of English language learning, fostering problem-solving abilities, innovative idea generation, and effective communication skills. Purpose. This study examines the potential of AI-assisted heuristic methods in facilitating this cognitive shift. Methodology. Three distinct AI-driven approaches are investigated: adaptive learning systems, intelligent tutoring, and data-driven feedback. A mixed-methods approach is employed to evaluate the effectiveness of the AI-assisted heuristic methods and learners' experiences during the intervention. The study involves 60 participants, divided into three groups of 20, each exposed to one of the three AI-driven methods. English language learning resources, including reading passages, audio recordings, and interactive exercises, are integrated with the AI-assisted techniques. The 8-week intervention commences with a pre-test assessing participants' initial critical and creative thinking skills. Post-tests and surveys are administered following the intervention to measure cognitive development and gather feedback on learners' experiences. Results. Results demonstrate significant improvements in problem-solving and originality of idea generation among participants. Furthermore, learners report positive experiences and recognize the value of AI-driven approaches in personalizing learning and promoting cognitive growth. However, challenges such as technological barriers and teacher training needs are highlighted. The current research underscores the potential of AI-assisted heuristic methods in English language learning, offering valuable insights into effective teaching strategies, learning tools, and platforms. Conclusion. Findings contribute to the development of innovative interventions supporting learners in acquiring essential thinking skills amidst rapid technological advancements, ultimately empowering them to succeed in today's interconnected and knowledge-driven world.

Exploring the Challenges and Opportunities of Blended Learning in a Technology–Enabled Education Environment

Technology integration in education has led to blended learning, a pedagogical approach combining traditional face-to-face instruction with online learning components. Through a comprehensive review of existing literature and empirical research, this investigation examines the impact of blended learning on both students and educators. It delves into this approach's diverse range of technologies, including Learning Management Systems, video conferencing tools, and digital content platforms. Through qualitative and quantitative analysis, the research identifies the opportunities that arise from adopting blended learning. It investigates the advantages of increased student flexibility, personalised learning experiences, and enhanced access to educational resources. The study explores how interactive content and virtual collaboration tools can boost student engagement and motivation. However, the study also uncovers educators' and students' challenges when implementing blended learning. These obstacles include technology access and proficiency issues, consistent communication, and addressing individual learning needs. The study addresses potential resistance to change from traditional teaching methods and the importance of teacher training and support. It compares students' achievements in blended learning environments with those in traditional classrooms and analyses the role of technology in influencing these outcomes. Based on the findings, the research concludes by providing insights into the future implications of blended learning in technology-enabled education environments. Keywords: Blended Learning; Learning Management System; Technology-enabled learning

To Evaluate Structured Competency-Based Curriculum for Health Programs among Community Medicine Postgraduates: Mixed Method Approach

Background: The postgraduate curriculum needs to be given a definite shape so as to make health programs more intensive and integrative. In the present scenario, most of the information is unclear and infrequent. A structured public health competency-based education is an important aspect to consider for integrative health care. Evaluate the structured competency-based curriculum (SCBC) prepared on health program matters. Methods: Mixed method model involving postgraduate students, faculties in community medicine departments of selected medical colleges and stakeholders from district administration. The SCBC was piloted and validated for use. The evaluation was then done based on pre- and posttest performance analysis, satisfaction survey, and questionnaires for reaction and learning components. Results: For a complete understanding of the program, students had to invest 52 hours of stipulated time. CBC assessment mean scores for a) problems in PHC and programmatic evaluation (78.9%) and b) identification of success and failure of programs (78.2%) were more than 75% mean score; whereas, assessment scores for topics on a) resource allocation and b) evaluation of program as write-up was 65% and 52%, respectively. As compared to the conventional method, the SCBC showed a critical evaluation score of 70% with a 0.001 significance level. Discussion and Conclusion: Students’ narratives were that they could understand as well as integrate them better on the field. There was enhanced satisfaction and encouragement. Structured curriculum will also help in making learning more student-centric and go a long way in boosting their creativity.

Where Theory and Practice Converge: Community-Based Learning as a Pedagogical Approach for Teaching AI Ethics

As artificial intelligence (AI) technologies continue to inundate the current information landscape, questions surrounding the ethics of AI and its responsible use in teaching and learning remain firmly on the forefront of the pedagogical discourse in the LIS field. Indeed, one implication of the ongoing AI revolution for LIS education that has become evident from these conversations is the pressing need to develop an ethical instructional framework that would enable students and educators alike to successfully navigate the rapidly evolving generative AI universe. This poster discusses the effectiveness of several pedagogical approaches that are currently being implemented to help students identify and address the ethical challenges associated with these technologies across a wide range of graduate level LIS courses, spanning such key areas of the professional practice as library and information center management, academic librarianship, and community-engaged librarianship. The common denominator in these courses is an emphasis on community-based learning that constitutes the core of complex sequential semester-long course projects students are asked to complete by designing and performing various community outreach, observational, and analytical exercises in an information organization of their choice. Based on the data collected from the above-mentioned courses during the past four semesters, the presenter demonstrates the value of the community-based learning component present in these activities for developing in LIS students a higher level of critical thinking about AI-related ethical dilemmas, all the while preparing soon-to-be information professionals for real-world applications of ethical considerations in their current and future professional roles.

Cartographic Review of Teacher Educators’ Professional Learning with an Aesthetic Approach

Experimenting with innovative and creative ways to conduct a literature review aligns with the paradigm shift from qualitative to post-qualitative research, which is concerned with doing and becoming rather than being. The aim of this article is twofold: to unfold the process of a cartographic approach to conducting a literature review; and by exploring the literature to discuss what an aesthetic approach activates in teacher educators’ collaborative professional learning activities. Inspired by Deleuze and Guattari (1988)’s cartographic principle of the rhizome, and post-qualitative inquiry more generally, this review generates knowledge through connections of concepts across 21 international research projects from teacher educators that use an aesthetic approach in their collaborative practices. New components of professional learning are found by mapping-and-tracing entangled concepts. A discussion of encounters within an aesthetic approach to professional learning shows how the processes involved in a cartographic review generates new directions in thinking, such as becoming-professional.

Exploring breed differences in discrimination, reversal learning, and resistance to extinction in the domestic dog (Canis familiaris)

Learning is crucial for shaping domestic dogs’ behaviour through life experiences, yet not all breeds exhibit the same learning aptitude towards a particular task. The current study’s objective was to identify differences in behaviour and learning performance across and within five breed clades and elucidate the underlying factors contributing into these variations. Dogs (n = 111) from five breed clades (UK Rural, Retrievers, Asian Spitz, European Mastiff, and New World) participated in a virtual learning task with their owners. Owners completed validated questionnaires of Impulsivity and Reward Responsiveness. The learning task comprised of reinforcing an arbitrary behaviour (hand-touch) through multiple sessions of Acquisition (reinforcing the hand-touch), Discrimination (reinforcing the hand-touch on one of two hands) and Reversal Learning (reinforcing the hand-touch on the opposite hand), followed by a single session of Extinction (hand-touch not reinforced). Results showed notable differences across the studied breed clades in certain learning and behavioural components. However, the observed disparities may not be entirely attributed to inherent cognitive differences among the breed clades but rather potentially influenced by contextual factors such as the human-dog communication dynamics associated with breeds’ cooperativity. Furthermore, breed clades differed in the contributing factors predicting individual learning performances, which could highlight the potential effect of breeds’ historical function.

RRT-guided experience generation for reinforcement learning in autonomous lane keeping

Reinforcement Learning has emerged as a significant component of Machine Learning in the domain of highly automated driving, facilitating various tasks ranging from high-level navigation to control tasks such as trajectory tracking and lane keeping. However, the agent’s action choice during training is often constrained by a balance between exploitation and exploration, which can impede effective learning, especially in environments with sparse rewards. To address this challenge, researchers have explored combining RL with sampling-based exploration methods such as Rapidly-exploring Random Trees to aid in exploration. This paper investigates the effectiveness of classic exploration strategies in RL algorithms, particularly focusing on their ability to cover the state space and provide a quality experience pool for learning agents. The study centers on the lane-keeping problem of a dynamic vehicle model handled by RL, examining a scenario where reward shaping is omitted, leading to sparse rewards. The paper demonstrates how classic exploration techniques often cover only a small portion of the state space, hindering learning. By leveraging RRT to broaden the experience pool, the agent can learn a better policy, as exemplified by the dynamic vehicle model’s lane-following problem.

Program Implementation of the Alternative Learning System

Educational stakeholders can enhance the effectiveness and impact of the Alternative Learning System (ALS) programs in providing educational opportunities for marginalized and underserved populations. It is on this premise that this study aimed to evaluate the extent of the ALS program’s implementation in a large school division within Central Philippines for the 2021-2022 academic year. Data needed for this descriptive study was taken from 51 ALS teacher-respondents using a self-made survey questionnaire that passed the rigorous test of validity and reliability. The study’s focus on program implementation revealed that the Assessment of Learning component exhibited a very high extent of implementation, as evidenced by mean scores surpassing 4.5 across all assessed aspects. Similarly, Learning Resources demonstrated a high level of implementation, with the majority of mean scores exceeding 3.5. However, implementing the Learning Environment aspect was deemed moderate, signifying potential areas for enhancement. Regardless of age, both younger and older educators experienced robust implementation in the Assessment of Learning and Learning Resources aspects. Similarly, male and female teachers encountered high implementation levels in these dimensions. While family income did not significantly impact the Assessment of Learning and Learning Resources domains, it did influence the Learning Environment aspect. Specifically, higher-income individuals benefited from a more extensive implementation of the Learning Environment. The study’s outcomes have important implications for designing future capability-building plans and enhancing the educational experience within the ALS program. Keywords: Alternative Learning System, ALS Program Implementation, ALS Teachers, ALS Community Learning Center, ALS Learning Resources, ALS Assessments Negros Occidental

A Study of the Significance of Vocational Education and Entrepreneurial Skill Generation in Sustainable Economic Development of India

Vocational and technical education are seen as essential components of the growth of the country. This is crucial to the continued development of the country. The general components of lifelong learning include attitudes, abilities, and knowledge. In India, Government’s emphasis and support to TVET and Startup Policies, has given many people who would otherwise face multiple challenges in their schooling access to employment and skills. India, in spite of being one of the fastest growing economies of the world, lags behind in terms of per capita income. Tapping its most vital resource, that is, the youth population by making them employable to meet the industry needs through vocational education and skill generation can act as a game changer for India. Thus, the main goals of this study are to draw attention to the importance of technical education, vocational training, and the development of entrepreneurial skills for the country's sustainable development in India through implementation of New Education Policy 2020 and several Government Policies.

Utilizing The Read-Arounds Strategy in Junior High School Students’ Dialogic Reading Activities

Reading is a requirement for almost all academic pursuits, it is a crucial component of language learning, especially for students. When learning English, this is especially important. Students must be able to read comprehension in order to absorb the material they are taught. Readability issues with fluency are often seen in students who have trouble understanding a foreign language. There have been several studies on Dialogic Reading activities, but few have utilized group reading strategies during these activities. Therefore, this research aims to investigate students' responses to the use of read-arounds strategy in dialogic reading activities for junior high school students at one of the junior high schools in Karawang. Micro-ethnography method is employed in this study. To collect the necessary data, observation and interviews are conducted. Reflective journaling is also used to enhance data accuracy. The results reveal that using the read-arounds technique improves students' understanding and reading interest. based on their comments, which show that using the read-arounds method can benefit children in three points: (1) increasing their self-confidence; (2) motivating them to read in English; and (3) improving their vocabulary and pronunciation. It can be concluded that using enjoyable reading strategies can help students become more confident and reduce their reading anxiety.

Dynamic adaptation in power transmission: integrating robust optimization with online learning for renewable uncertainties

IntroductionThe increasing integration of renewable energy sources, such as wind and solar, into power grids introduces significant challenges due to their inherent variability and unpredictability. Traditional fossil-fuel-based power systems are ill-equipped to maintain stability and cost-effectiveness in this evolving energy landscape.MethodsThis study presents a novel framework that integrates robust optimization with online learning to dynamically manage uncertainties in renewable energy generation. Robust optimization ensures system resilience under worst-case scenarios, while the online learning component continuously updates operational strategies based on real-time data. The framework was tested using an IEEE 30-bus test system under varying levels of renewable energy integration.ResultsSimulation results show that the proposed framework reduces operational costs by up to 12% and enhances system reliability by 1.4% as renewable energy integration increases from 10% to 50%. Additionally, the need for reserve power is significantly reduced, particularly under conditions of high variability in renewable energy outputs.DiscussionThe integration of robust optimization with online learning provides a dynamic and adaptive solution for the sustainable management of power transmission systems. This approach not only improves economic and environmental outcomes but also enhances grid stability, making it a promising strategy for addressing the challenges posed by the increasing reliance on renewable energy.

A mixed-methods investigation into complex components of multilingual international students' self-regulated learning in English as a foreign language context: A social cognitive perspective

Self-regulated learning serves as a fundamental framework for understanding the cognitive, motivational, and emotional dimensions of learning. Recently, a growing body of studies on such cognitive processes appears in multilingual populations. Applying a mixed-methods approach, this study examined the key components of the self-regulated learning process among 233 multilingual international students in China, specifically within the context of English as a Foreign Language learning. Qualitative data was analyzed through Pearson's correlation analysis, structural equation modeling, and path analysis, while semi-structured interviews were conducted to further confirm the results of the qualitative data analysis. 15 students were purposefully selected through purposive sampling to participate in follow-up interviews. Within the framework of social cognitive theory, the findings revealed that metacognition, motivation, self-efficacy, and feedback loops are the primary components of self-regulated learning. Additionally, path analysis confirmed that the four factors are positive predictors of self-regulated learning proficiency of multilingual international students in China. The interview outcomes further validated the integral role of these primary components in the self-regulated learning process within the context of multilingual study. This study underscores the significance of incorporating translanguaging backgrounds into teaching strategies and language policy. Findings may offer some insights for multilingual international students, language teachers, and language policymakers in the field of Chinese language instruction.

Young children's perceptions and experiences of school readiness during the transition from preschool to primary school in China

AbstractSchool readiness has a profound educational value for children's positive adjustment to primary school and holistic development. However, little research sufficiently addresses how young children view multifaceted components of learning, such as cognitive, affective and behavioural experiences on school readiness. A timely understanding of children's perceptions and experiences is crucial to shed light on how to promote transition and improve children's school readiness. This study investigated the perceptions and experiences of 41 children in China (5–6 years of age, 23 girls) regarding their school readiness based on Mosaic approach methods. The results indicated that young children have their own unique perceptions, emotional and behavioural experiences of school readiness. The perceptions of school readiness include four aspects of material supplies, subjects knowledge, interests and specialties and behavioural habits, which has similarities to that of adults in aspects of academic knowledge and social rules. Nevertheless, findings revealed young children view interests and strengths as important part of school readiness, reflecting their personal preferences and abilities. The emotional experiences could be considered positive or negative, with positive emotional experiences expressing children's curiosity and expectation, fulfilment and pleasure, and negative emotional experiences expressing academic burden, rules pressure and social worries, which need to be addressed. Young children's behavioural experiences with school readiness present two patterns of passive acceptance and active participation, they are eager to participate in activities and have a strong desire to explore and learn. Our findings extend beyond existing conception of school readiness, and give greater weight to children's interests and strengths, positive experiences and active participation. It is important to focus on children's intrinsic interests and strengths, accept children's ideas and choices, care for their emotional state and provide positive support.