Future Learning Research Articles

Students Exploring Health Disparities in Undergraduate Kinesiology Course

ABSTRACT Kinesiology courses that implement health disparities (HD) topics into the undergraduate curriculum engage students in critical and conscious thinking about health outcomes and strategies as they prepare for careers as future health and medical professionals. Health disparities are disproportionate differences in health based on race, gender, socioeconomic status, sexuality, and environmental factors that are preventable for providing opportunities to achieve optimal health. Implementing HD topics into undergraduate courses increases knowledge and awareness and inspires long-term interest in health equity work. This ethnographic case study assessed how 142 undergraduate Kinesiology majors navigated HD topics with critical consciousness as a guiding framework. Three themes emerged from student exploration: eye-opening experiences, lived experiences, and learning experiences. Upper-level students reported an increase in HD (75%–95%) awareness of the meaning of the term and the communities impacted. The lack of prior engagement (29%) with HD ignited tensions around learning experiences. Students who engage in HD topics earlier in their academic programs increase their knowledge and strategies for integrating HD into future learning and practices.

Preparation for future conceptual learning: Content-specific long-term effects of early physics instruction.

Preparation for future conceptual learning: Content-specific long-term effects of early physics instruction.

Integrating Youth Perspectives into the Design of AI-Supported Collaborative Learning Environments

This study highlights how middle schoolers discuss the benefits and drawbacks of AI-driven conversational agents in learning. Using thematic analysis of focus groups, we identified five themes in students’ views of AI applications in education. Students recognized the benefits of AI in making learning more engaging and providing personalized, adaptable scaffolding. They emphasized that AI use in education needs to be safe and equitable. Students identified the potential of AI in supporting teachers and noted that AI educational agents fall short when compared to emotionally and intellectually complex humans. Overall, we argue that even without technical expertise, middle schoolers can articulate deep, multifaceted understandings of the possibilities and pitfalls of AI in education. Centering student voices in AI design can also provide learners with much-desired agency over their future learning experiences.

Navigating uncertainty: The interplay of future job forecasting, learning agility, responsiveness, and adaptability

Background: According to the 2023 World Economic Forum report, the impact of Artificial Intelligence (AI) and automation on the job market was more significant than originally projected. Although 2018 research forecasted significant job losses balanced by job creation, current data indicates otherwise. Between 2023 and 2027, it is anticipated that 69 million new jobs will be created due to advancements in AI, however, this will be offset by the loss of 83 million jobs, leading to a net decrease of 14 million jobs worldwide. Roles related to AI, digitalization, and sustainability, such as AI specialists and renewable energy engineers are expected to grow, while those in clerical and administrative sectors are most at risk of decline. This shift underscores the need for reskilling and adapting to evolving fields, as nearly 44% of workers skills will face disruption by 2027. The demand for analytical thinking, technological literacy, and adaptability will grow as companies increasingly adopt frontier technologies. Objectives: (1) identify key variables influencing adaptability of college graduates in Indonesia, (2) quantify the strength of relationships between these variables to understand the combined effect on graduate adaptability. The research also aims to (3) develop theoretical and practical recommendations to strengthen ICIL policy and equip students with the relevant skills needed to thrive in an ever-changing job market. Methodology: The research focuses on predicting future employment trends, adaptability, and learning agility (LA), along with the implications for improving the Independent Campus Independent Learning (ICIL) policy. It focused on the significant unemployment rate among college graduates, along with the lack of research on the relationship between job change predictions, graduates’ adaptability, and the impact on graduates’ general well-being. The mixed-method strategy with quantitative analysis was used to conduct this research with data collected from 284 ICIL participants through online survey. The gathered data was evaluated using Structural Equation Modeling (SEM) with Lisrel version 10. Results: The result showed that job trend projections significantly influence responsiveness, which demonstrated a robust association between employment trend predictions and LA. Responsiveness significantly influenced learning agility which indicated no significant direct association between job trend projections and graduate adaptability. Conclusion: The research emphasized the need to consider adaptability as a concept with multiple dimensions. It proposed incorporating these factors into strategies for education and human resources development in order to better equip graduates for the demands of a constantly changing work market. Unique contribution: This research focused on adaptability as a multifaceted concept that consist of the ability to forecast job trends, be sensitive, and possess LA. It offered a deeper understanding of the relationships between these variables as discussed in the human resources literature. Technology, corporate culture, and training played a critical role in connecting employment trend prediction with the ability to respond effectively. Key recommendation: Institutions should implement a comprehensive approach to the development of human resources, with emphasis on fostering critical thinking, analytical abilities, and the practical application of information. By employing these tactics, higher education institutions may effectively equip graduates with both academic proficiency and the ability to adapt and thrive in quickly changing organizational environments, leading to the production of robust and versatile workers.

From early to future learner corpus research

Abstract The aim of this article is to survey the field of learner corpus research from its origins to the present day and to provide some future perspectives. Key aspects of the field — learner corpus design and collection, learner corpus methodology, statistical analysis, research focus and links with related fields, in particular SLA, FLT and NLP — are compared in first-generation LCR, which extends from the late 1980s to 2000, and second-generation LCR, which covers the period from the early 2000s until today. The survey shows that the field has undergone major theoretical and methodological changes and considerably extended its range of applications. Future developments that are likely to gain ground are grouped into three categories: increased diversity, increased interdisciplinarity and increased automation.

EDUCAÇÃO INFANTIL E A SUA IMPORTÂNCIA NO DESENVOLVIMENTO DAS CRIANÇAS

Early childhood education is an essential phase in children's development, which covers the first years of life, generally up to the age of five. This period is crucial for children's cognitive, emotional, social and physical development, providing the foundation for future learning. Early childhood education is not limited to teaching academic content, but also focuses on stimulating children's curiosity, creativity, autonomy and socio-emotional skills. Through playful, interactive activities focused on sensory experience, children explore the world around them, develop their language, motor coordination and social skills. In addition, early childhood education plays an essential role in promoting equal opportunities, social inclusion and preparing them for life in society. Therefore, investing in the quality and universal access to early childhood education is important to ensure the healthy and equitable development of children and to build a more just and democratic society in the future.

Challenges in Implementing Early Childhood Care and Education in Anganwadi Centres: A Case Study of Rangia Sub District of Kamrup District of Assam

Early Childhood Care and Education (ECCE) is essential for the cognitive, physical, and socio-emotional development of young children. In India, the National Education Policy (NEP 2020), along with the National Curriculum Framework for Foundational Stage (NCF-FS 2022), emphasizes the importance of providing quality ECCE through Anganwadi Centres to lay a strong foundation for children's overall growth and future learning. The study titled "Challenges in Implementing Early Childhood Care and Education in Anganwadi Centres: A Case Study of Rangia Sub Division of Kamrup District of Assam" examines the obstacles Anganwadi Centres (AWCs) face in delivering ECCE as outlined by NEP 2020. The research identifies key challenges such as inadequate infrastructure, a lack of essential classroom materials, insufficient indoor and outdoor play equipment, and irregular supplies of food and medical resources. Using a survey approach, the findings reveal that most AWCs in the Rangia Sub-Division are under-resourced, limiting their ability to provide the comprehensive educational experiences vital for early childhood development. The study advocates for targeted interventions, including better resource allocation, infrastructure upgrades, and improved training programs, to address these shortcomings and achieve the ECCE objectives set by NEP 2020 in the region.

Adaptive Energy Management Strategy for Hybrid Electric Vehicles in Dynamic Environments Based on Reinforcement Learning

Energy management strategies typically employ reinforcement learning algorithms in a static state. However, during vehicle operation, the environment is dynamic and laden with uncertainties and unforeseen disruptions. This study proposes an adaptive learning strategy in dynamic environments that adapts actions to changing circumstances, drawing on past experience to enhance future real-world learning. We developed a memory library for dynamic environments, employed Dirichlet clustering for driving conditions, and incorporated the expectation maximization algorithm for timely model updating to fully absorb prior knowledge. The agent swiftly adapts to the dynamic environment and converges quickly, improving hybrid electric vehicle fuel economy by 5–10% while maintaining the final state of charge (SOC). Our algorithm’s engine operating point fluctuates less, and the working state is compact compared with Deep Q-Network (DQN) and Deterministic Policy Gradient (DDPG) algorithms. This study provides a solution for vehicle agents in dynamic environmental conditions, enabling them to logically evaluate past experiences and carry out situationally appropriate actions.

Doctoral rhythms within an EdD: the case of group supervision

ABSTRACT This paper explores the application and use of group supervision with doctoral candidates studying a professional doctorate, the EdD, at a teaching intensive university. Group supervision is applied as a pedagogical strategy during the module stage of the award with candidates who were advanced practitioners in their fields with several working at the Post’92 university in question. Group supervision is an emergent idea has not been well described in the literature either as a concept or a practice. This paper aims to contribute to understandings of group supervision and its potential value as a doctoral learning approach. Rhythmanalysis is used to explore students’ experiences of group supervision particularly the advantages for advanced professionals from education who are at an early stage in their research career. The paper highlights the importance of the exploration and production of ideas within the group supervision process such as the containing of anxiety, development of identities, grappling with theories and methodologies and the value of peer learning and mattering. Group supervision itself could also be described as a meta-supervision approach with the supervisor stepping in and out of the doctoral learning to articulate and justify what was happening in relation to future learning demands.

Impact of Digital Game-based Learning Experiences on Reasoning Skills and Science Engagement

This research seeks to use games to promote scientific reasoning and inquiry skills among middle-school children. Particularly, it focuses on the Control of Variables Strategy (CVS), a fundamental component of scientific thinking which enables individuals to test hypotheses and make valid causal inferences based on evidence. The present study draws on and combines existing streams of research in the fields of science education, embodied cognition, and game-based learning to investigate the efficacy of an intervention using the Preparation for Future Learning paradigm in which students play an online text-based adventure simulation game about solving escape rooms in order to prime them for later formal instruction in CVS via a randomized-controlled trial, as well as whether structured or unstructured access to the game has a differential impact on immediate learning vs. retention after a delay. Students were given tests of scientific reasoning at baseline, immediately following the training phase, and a week thereafter. The impact of playing this game on motivation and engagement with science is also analyzed in this trial through the use of survey data. The study found significant effects of study condition on all measures, with students assigned to the game groups outperforming control students, and the unstructured play group showing the strongest performance in the post-study test while the structured play group performed the most poorly in the retention test. The unstructured play group also showed the highest level of intrinsic motivation, as well as higher self-determination and self-efficacy than the structured playing group in the science engagement survey.

Creating a City for All of Us: The Possible Role of the Fediverse in Archiving Civic Urban Memory

This paper attempts to build a case for adopting the model of the Fediverse to archive digital citizen-generated urban memory. Examining literature from several relevant fields of debate acts as a pragmatic foundation for reasoning to then outline potential core technical functionality for provision of such an archive, using the Mastodon app as an example. This ‘civic urban memory’ archive is considered as open, curated by citizens themselves and owned by them through civic public ownership in a context of technological sovereignty. Reflecting on issues of citizen self curated and moderated memory collection archives, and the potential for opt-in or anonymous archive posting may offer some mechanisms for fair and open curation, moderation and privacy protection in such archives. Conceptual backdrop for a civic urban memory archive is placed in current debates concerning civic technological platforms acting as a digital public good in a context of a techno-social contract for learning, with a co-constructed shared civic urban memory forming part of open incidental lifelong learning in a future learning city.

Exploring students' computer‐supported collaborative argumentation with socio‐scientific issues

AbstractBackgroundThis study examined the effect of computer‐supported collaborative argumentation (CSCA) on secondary school students' understanding of socio‐scientific issues (SSI). Engaging students in collaborative argumentation is known to help with deepening their understanding of SSI.MethodsIn this study, a mixed‐method design is used to investigate 84 students' collaborative argumentation processes and outcomes. The statistical analysis, epistemic network analysis and qualitative uptake analysis results showed that CSCA was effective in supporting secondary school students' evidence‐based argumentation skills on SSI.Findings and ConclusionSeveral cases were presented to show how students engaged in CSCA to explore meaningful learning opportunities and how CSCA helped students' learning on SSI.ImplicationsThe findings provided insights for future innovative teaching and learning SSI in authentic classroom settings.

Symbolic Representation of Young Children in Science: Insights into Preschoolers’ Drawings of Change of State of Matter

Research in early childhood education acknowledges the multimodal nature of learning, and the need to equip young learners with the abilities to encounter future communication and learning challenges is imperative. Drawing can play a crucial role in children’s learning in general and contribute to science learning in particular. In this paper, we study the drawings that young children (aged 4–6) produce during a teaching intervention about the change of state of matter. The research adopts a sociocultural perspective, considering drawing as a mediating tool to support children’s meaning-making and learning process. The objective is to understand better the type of drawing situations that can be proposed to young children in science and the scaffold these drawing tasks might provide to support meaning-making in science. Results show that children use iconic as well as symbolic modes of representation depending on the situation and that the resources available can have an impact on how children use different symbols.

Using Murojaah Wheel Media to Aid Qur'an Memorization in Young Children

The ability to read and memorize the Qur'an is crucial for young children, providing long-term benefits for their spiritual and cognitive growth. However, there is a growing concern about children’s decreasing engagement with the Qur'an due to the influence of modern distractions. This study addresses this gap by exploring the use of Murojaah wheel media as a tool to facilitate Qur'an memorization among children aged 4-5 years at As-Shoffah Early Childhood Education. The aim is to evaluate the effectiveness of this media in enhancing memorization skills. Using a quantitative ex-post facto design, the study involved 12 students selected through a saturated sampling technique. A questionnaire administered to teachers served as the primary instrument for data collection. Data were analyzed using simple linear regression with JASP software version 18.0. The results revealed a significant positive correlation between the use of the Murojaah wheel media and the students' ability to memorize the Qur'an (F=8.943, p=0.014). The novelty of this research lies in its focus on the application of interactive learning media in Islamic education for young children. Implications of these findings suggest that incorporating Murojaah wheel media in early childhood education can effectively support Qur'an memorization, providing a foundation for future Islamic learning. Further research on its application in various educational settings is recommended. Highlights: Murojaah wheel media significantly improves young children's ability to memorize the Qur'an. Integrating interactive learning media supports Islamic education from an early age. The study fills a knowledge gap in the application of innovative teaching methods in religious education. Keywords: Murojaah Wheel Media, Quran Memorization, Early Childhood, Islamic Education, Learning Tools

Learning About Sea Level Rise Uncertainty Improves Coastal Adaptation Decisions

AbstractAdaptive decision‐making allows decision‐makers to plan long‐term coastal infrastructure under uncertain sea level rise projections. To date, economic assessments of adaptive decision‐making that take into account future learning about sea level rise uncertainty are rare and the existing ones have relied on simple quantification of future learning not validated against sea level science. To address this gap, we develop an economic adaptive decision‐making framework that takes into account future learning about sea level rise uncertainty and apply it to a coastal case study in Lübeck, Germany, to answer the question of how adaptation to sea level rise can be improved through adaptive adaptation pathways as opposed to non‐adaptive pathways. To address this question, we use a Markov decision process to formulate the stochastic optimization problem. We quantify future learning about sea level rise uncertainty through sea level rise learning scenarios based on and validated against the latest scenarios of the Intergovernmental Panel on Climate Change. Our case study results show that the city of Lübeck is currently under‐protected against storm surges and that immediate adaptation actions are advisable in the face of future sea level rise. We find that adaptive adaptation pathways, in contrast to non‐adaptive pathways, generate sea level rise thresholds for adaptation actions that are similar across climate change scenarios and can reduce expected costs up to 1.8%.

Implementasi Kurikulum Merdeka dalam Menumbuhkan Kemampuan Critical Thinking di Kelas XI F1 pada Mata Pelajaran Pendidikan Agama Islam di SMAN 8 Padang

This study aims to describe: 1) the planning of implementing the Merdeka Curriculum in fostering critical thinking skills in Class XI F1 for Islamic Religious Education subjects; 2) the implementation of the Merdeka Curriculum in developing critical thinking skills in Class XI F1 for Islamic Religious Education subjects; 3) the challenges and efforts faced by Islamic Religious Education teachers in nurturing critical thinking in Class XI F1 for Islamic Religious Education subjects. The research method used is qualitative with a descriptive approach. The results of the study show that, first, in the planning stage, teachers attended training, prepared teaching modules that included learning objectives, teaching models, learning activities, and assessment/evaluation. Second, the implementation involved preparatory activities such as preparing media/tools and motivating students in line with the Pancasila Student Profile. The core activities included activities 1.1, 1.2, and 1.3, while closing activities consisted of summarizing the lesson, reflecting, providing information about future learning, and concluding with a prayer. Third, the challenges faced by teachers included inadequate training and continued use of lecture-based methods. The efforts made to address these challenges included attending further training and mastering various teaching models.

World Futures Day 2023 Global futures agenda by The Millennium Project

World Futures Day (WFD), the 24 h round-the-world participatory method hosted every year by The Millennium Project and others on March 1, stimulates conversations and collective intelligence on possible futures. The 2023 edition marked its tenth anniversary. The 2023 Global futures agenda coming out from the data analysis is composed of four main clusters, each listing future oriented topics and related contents. Cluster 1, Complex solutions for complex problems, includes topics such as Environmental regeneration, Predictable food systems, Energy transition, Homo Galaxia, and Synergetic relations for peace. Cluster 2, A hyper-technological humanity, includes topics such as A biological revolution, New definitions of truth, An emotional AGI, A conscious AGI, and AGI governance. Cluster 3, Education and learning for a better future, includes topics such as Intelligent agent teachers, Intergenerational storytelling, and A cultural shift to self-actualization. Cluster 4, Improving global foresight, includes topics such as Futurists as a contradiction, A new leadership agenda, Futures shapers, The power of stories, Judging trillions of scenarios, Committees and summits for the future. After discussing some changes in the contents addressed over the years and some potential next steps for the research on WFD, the conclusions report that one key takeaway from WFD 2023 is that we have a vital need for pragmatic hope.

Interactive Surgical Training in Neuroendoscopy: Real-Time Anatomical Feature Localization Using Natural Language Expressions.

This study addresses challenges in surgical education, particularly in neuroendoscopy, where the demand for optimized workflow conflicts with the need for trainees' active participation in surgeries. To overcome these challenges, we propose a framework that accurately identifies anatomical structures within images guided by language descriptions, facilitating authentic and interactive learning experiences in neuroendoscopy. Utilizing the encoder-decoder architecture of a conventional transformer, our framework processes multimodal inputs (images and language descriptions) to identify and localize features in neuroendoscopic images. We curate a dataset from recorded endoscopic third ventriculostomy (ETV) procedures for training and evaluation. Utilizing evaluation metrics, including "R@n," "IoU= θ," "mIoU," and top-1 accuracy, we systematically benchmark our framework against state-of-the-art methodologies. The framework demonstrates excellent generalization, surpassing the compared methods with 93.67 % accuracy and 76.08 % mIoU on unseen data. It also exhibits better computational speed compared with other methods. Qualitative results affirms the framework's effectiveness in precise localization of referred anatomical features within neuroendoscopic images. The framework's adeptness at localizing anatomical features using language descriptions positions it as a valuable tool for integration into future interactive clinical learning systems, enhancing surgical training in neuroendoscopy. The exemplary performance reinforces the framework's potential in enhancing surgical education, leading to improved skills and outcomes for trainees in neuroendoscopy.

Aging, brain plasticity, and motor learning.

Motor skill learning, the process of acquiring new motor skills, is critically important across the lifespan, from early development through adulthood and into older age, as well as in pathological conditions (i.e., rehabilitation). Extensive research has demonstrated that motor skill acquisition in young adults is accompanied by significant neuroplastic changes, including alterations in brain structure (gray and white matter), function (i.e., activity and connectivity), and neurochemistry (i.e., levels of neurotransmitters). In the aging population, motor performance typically declines, characterized by slower and less accurate movements. However, despite these age-related changes, older adults maintain the capacity for skill improvement through training. In this review, we explore the extent to which the aging brain retains the ability to adapt in response to motor learning, specifically whether skill acquisition is accompanied by neural changes. Furthermore, we discuss the associations between inter-individual variability in brain structure and function and the potential for future learning in older adults. Finally, we consider the use of non-invasive brain stimulation techniques aimed at optimizing motor learning in this population. Our review provides insights into the neurobiological underpinnings of motor learning in older adults and emphasizes strategies to enhance their motor skill acquisition.

Changes in Intrinsic Motivation and Self-Efficacy

Grades in introductory STEM courses can impact intrinsic motivation (IM) and self-efficacy (SE). We used an exploratory approach to examine trends in grades and how IM and SE impact students’ grades. It is known that most first-generation (FG) college students are from underrepresented backgrounds (URM), and that these students are least likely to persist in STEM fields. Therefore, gaining a better understanding of motivation in our most underserved students could be critical to improving their success in introductory biology courses and ultimately future persistence in STEM. We found that, on average, URM FG students received the lowest final grades and experienced the greatest declines in IM and SE. This research informs the way we may think about changes in motivation and self-efficacy in our introductory biology courses as these lay the foundation for future learning and success.