Complex Perspective Research Articles

Pengaruh Penyaluran Zakat Oleh Baznas Terhadap Jumlah Mustahik Miskin Di Kota Jambi Periode 2014-2018

The purpose of this study was to determine how the development of zakat distribution in BAZNAS and the number of poor mustahik in Jambi city during 2014-2018 and how the influence of zakat distribution by BAZNAS on the number of poor mustahik in Jambi City during 2014-2018. The method used in this research is In this study the authors conducted research with qualitative methods. Qualitative method is a research approach used to understand social phenomena or human behavior from an in-depth and complex perspective. In contrast to quantitative methods that focus more on measuring numbers and statistics, qualitative methods emphasize the collection and analysis of data that is descriptive, contextual, and interpretative. The results showed that there was a significant increase in the receipt and distribution of zakat funds by BAZNAS Jambi City from 2014 to 2018. This shows the efforts of the Jambi City government in increasing the distribution of zakat funds as a way to overcome poverty. The number of poor mustahik who receive zakat from BAZNAS Jambi City has also increased significantly every year. This shows that the increase in the distribution of zakat funds has succeeded in reaching the target population in need.

Modeling post-Pleistocene megafauna extinctions as complex social-ecological systems

Abstract The role of human hunting behavior versus climate change in the mass extinction of megafauna during the Late Quaternary is much debated. To move beyond monocausal arguments, we treat human–megafauna–environment relationships as social–ecological systems from a complex adaptive systems perspective, to create an agent-based model that tests how human hunting may interact with environmental stress and animal life history to affect the probability of extinction. Using the extinction of Syncerus antiquus in South Africa at 12–10 ka as a loose inspirational case study, we parameterized a set of experiments to identify cross-feedbacks among environmental dynamics, prey life history, and human hunting pressure that affect extinction probability in a non-linear way. An important anthropogenic boundary condition emerges when hunting strategies interrupt prey animal breeding cycles. This effect is amplified in patchy, highly seasonal environments to increase the chances of extinction. This modeling approach to human behavior and biodiversity loss helps us understand how these types of cross-feedback effects and boundary conditions emerge as system components interact and change. We argue that this approach can help translate archaeological data and insight about past extinction for use in understanding and combating the current mass extinction crisis.

Shape Recognition and Corner Points Detection in 2D Drawings Using a Machine Learning Long Short-Term Memory (LSTM) Approach

Creating a 2D geometry model from an image poses challenges for CAD users due to factors such as noise, segmentation difficulties, complex geometric structures, scale and perspective variations, and the need for CAD system compatibility. In this paper, we propose a novel deep learning approach utilizing Long-Short Term Memory (LSTM) to address these challenges. Our approach decomposes the shapes in the images into line and curve segments and accurately locates their intersection points. To enhance the model’s performance, we introduce two distinct types of features (angle and curvature features) and optimize the model through hyperparameter tuning. The resulting model exhibits robustness against noise, varying image sizes, and can effectively locate different types of intersection points. To evaluate the proposed model, we have developed a Python-based software and conducted experiments on a dataset comprising of 200 shapes with seven different resolutions. Comparative analysis against a state-of-the- art method (TCVD) from the literature demonstrates that our approach achieves higher accuracy in terms of line, curve, and intersection point detection.

WOMEN OF MEDIEVAL AND MODERN ROMANIA AND THE ART OF WRITING AND TRANSLATION

Romanian history, from ancient times until today contains numerous events, facts, events that can be analyzed from a complex perspective. However male and female personalities bear the imprint that was involved throughout the passage of time. The article intends to follow, chronologically, biographies of the firrst women writer-translator or journalist in Romania's history.

An Exploration of Dutch Dermatologists' Experience and Satisfaction With Teledermatology: Sociotechnical and Complex Adaptive System Perspective.

Despite the global upscale of teledermatology during the COVID-19 pandemic, persistent barriers, such as the poor anamnesis and photo quality, hinder its effective use in practice. Understanding Dutch dermatologists' experiences and satisfaction with using the teledermatology system in the Dutch health care system is needed. A holistic evaluation may provide valuable insight to understand how barriers interrelate which is deemed necessary for the innovation of teledermatology in practice. Guided by a complex adaptive system perspective, this study aims to understand Dutch dermatologists' experience and satisfaction with their training, support communication, interaction, and usage of a teledermatology platform of a Dutch digital hospital during the COVID-19 pandemic, uncovering insights to improve teledermatology services for the future. A web-based questionnaire was sent in December 2021 to Dutch dermatologists who (1) had an active teledermatology platform account, and (2) responded to a teledermatology consultation between October 1, 2019, and September 30, 2021. The questionnaire consisted of the validated Store-and-Forward Telemedicine Service User-satisfaction Questionnaire (SAF-TSUQ) questionnaire, and new questions regarding; demographics of teledermatologists, the use of teledermatology during the COVID-19 pandemic, the performance of teledermatology by general practitioners (GP), and the role of dermatologists in the teledermatology process. The open-ended questions were analyzed by a grounded theory approach guided by a sociotechnical model and complemented by a complex adaptive system perspective. A panel discussion with 3 dermatologists was performed to provide additional insight into the responses to the questionnaire. We obtained responses from 25 out of the 249 (10%) invited dermatologists. Overall, dermatologists had a positive experience with teledermatology. Interestingly, teledermatology use frequency remained unaffected by the COVID-19 pandemic. However, the insufficient quality and incompleteness of the clinical content (photos and anamneses information) of the teledermatology consultation impacted the efficiency of the teledermatology workflow. Dermatologists expressed the need for improvement to avoid time-consuming processes or physical referrals. The panel discussion enriched and confirmed the responses, suggesting solutions like mandatory fields for the GPs for a complete anamnesis. Dutch Dermatologists view teledermatology as a valuable tool to provide access to dermatology care. However, improvements regarding the quality and completeness of the provided clinical content are necessary for the effectiveness and efficiency of the complex teledermatology system in Dutch health care. This could increase both the dermatologists' satisfaction and the quality of teledermatology services. Managing trade-offs, such as time investments versus image quality, is crucial for teledermatology implementation and should be assessed from a complexity perspective to understand trade-offs and prevent unintended consequences.

Craft representation network and innovative heritage: the Forbidden City’s cultural and creative products in a complex perspective

PurposeWith the development of science and technology, more creators are trying to use new crafts to represent the cultural trends of the social media era, which makes cultural heritage innovative and new genres emerge. This compels the academic community to examine craft from a new perspective. It is very helpful to understand the hidden representational structure of craft more deeply and improve the craft innovation system of cultural and creative products that we deconstruct the craft based on Complex Network and discover its intrinsic connections.Design/methodology/approachThe research crawled and cleaned the craft information of the top 20% products on the Forbidden City’s cultural and creative products online and then performed Complex Network modeling, constructed three craft representation networks among function, material and technique, quantified and analyzed the inner connections and network structure of the craft elements, and then analyzed the cultural inheritance and innovation embedded in the craft representation networks.FindingsThe three dichotomous craft representation networks constructed by combining function, material and technique: (1) the network density is low and none of them has small-world characteristics, indicating that the innovative heritage of the craft elements in the Forbidden City’s cultural and creative products is at the stage of continuous exploration and development, and multiple coupling innovation is still insufficient; (2) all have scale-free characteristics and there is still a certain degree of community structure within each network, indicating that the coupling innovation of craft elements of the Forbidden City’s cultural and creative products is seriously uneven, with some specific “grammatical combinations” and an Island Effect in the network structure; (3) the craft elements with high network centrality emphasize the characteristics of decorative culture and design for the masses, as well as the pursuit of production efficiency and economic benefits, which represent the aesthetic purport of contemporary Chinese society and the ideological trend of production and life.Originality/valueThe Forbidden City’s cultural and creative products should continue to develop and enrich the multi-coupling innovation of craft elements, clarify and continue their own brand unique craft genes, and make full use of the network important nodes role.

A participatory approach to model the neighbourhood food environment.

Inequalities in exposure to a health-promoting local food environment have been implicated in the generation of inequalities in diet-related behaviours and outcomes, including obesity and diabetes. Increasingly, poor diet and diet-related disease have been characterised as an emergent property of a complex system and, as such, the drivers of poor diet may be better understood by using a complex system perspective. In this study, we describe a participatory approach for understanding the system drivers of unhealthy food consumption. System dynamics (SD) was used to identify, understand, and visualise the elements of the neighbourhood food retail system that influence individuals' eating behaviour. Group Model Building (GMB), undertaken online with stakeholders (n = 11), was used to funnel existing knowledge and evidence on urban food environments and to build a conceptual system map of the local food retail environment inclusive of the drivers that influence the decision to purchase and consume meals that are high in fat, salt, and sugar (HFSS), and calories. The GMB was organised as a knowledge elicitation process involving a questionnaire, a workbook, and a structured workshop. The GMB generated a comprehensive causal loop diagram (CLD) of the retail environment inclusive of the drivers that influence the decision to purchase and consume unhealthy meals. The CLD was designed around two main variables (i) exposure to food outlets and (ii) food consumption. The system map built during the Group Model Building session linked exposure to food outlets with the possibility to purchase and consume unhealthy meals. The effectiveness of this link will be tested in an Agent-Based model. The conceptual model illustrates the complexity of the factors responsible for inequalities in unhealthy eating. The GMB approach provides a basis for building an agent-based model for local authorities to characterise their food retail environment, uncover potential leverage points for interventions and test them 'in silico' in a virtual environment.

Uncovering Key Factors in Graphene Aerogel-Based Electrocatalysts for Sustainable Hydrogen Production: An Unsupervised Machine Learning Approach.

The application of principal component analysis (PCA) as an unsupervised learning method has been used in uncovering correlations among diverse features of aerogel-based electrocatalysts. This analytical approach facilitates a comprehensive exploration of catalytic activity, revealing intricate relationships with various physical and electrochemical properties. The first two principal components (PCs), collectively capturing nearly 70% of the total variance, attested the reliability and efficacy of PCA in unveiling meaningful patterns. This study challenges the conventional understanding that a material's reactivity is solely dictated by the quantity of catalyst loaded. Instead, it unveils a complex perspective, highlighting that reactivity is intricately influenced by the material's overall design and structure. The PCA bi-plot uncovers correlations between pH and Tafel slope, suggesting an interdependence between these variables and providing valuable insights into the complex interactions among physical and electrochemical properties. Tafel slope stands to be positively correlated with PC1 and PC2, showing an evident positive correlation with the pH. These findings showed that the pH can have a positive correlation with the Tafel slope, however, it does not necessarily reflect a direct positive correlation with the overpotential. The impact of pH on current density (j)and Tafel slope underscores the importance of adjusting pH to lower overpotential effectively, enhancing catalytic activity. Surface area (from 30 to 533 m2 g-1) emerges as a key physical property, inclusively inverse correlation with overpotential, indicating its direct role in lowering overpotential and increasing catalytic activity. The introduction of PC3, in conjunction with PC1, enriches the analysis by revealing consistent trends despite a slightly lower variance (60%). This reinforces the robustness of PCA in delineating distinct characteristics of graphene aerogels, affirming their potential implications in diverse electrocatalytic applications. In summary, PCA proves to be a valuable tool for unraveling complex relationships within aerogel-based electrocatalysts, extending insights beyond catalytic sites to emphasize the broader spectrum of material properties. This approach enhances comprehension of dataset intricacies and holds promise for guiding the development of more effective and versatile electrocatalytic materials.

A Systemic Circular Model for innovative sustainable recycling of thermoplastics

Sustainable recovery and recycling of plastics is becoming an increasingly important global issue. Waste from the plastics industry has seen an exponential increase, which is expected to continue in the future. Currently, the majority of the plastic waste generated is discarded and the gap between the amount of plastic waste discarded and incinerated compared to recycled is huge. Closing this gap requires addressing many systemic issues in the value chain through a more holistic, complex systems approach that better understands the different values, norms and behaviours intrinsic in patterns of relations between key stakeholders. Taking a complex systems perspective necessitates the advancement of new innovations and a more circular model for the recycling industry. It highlights specific innovations that provide disruptive ways to design and develop processes and products that go beyond traditional recycling technologies and systems to find new cost-competitive uses for plastic waste streams that are currently too expensive or not convenient to process. The work outlines a circular model for the plastics value chain to support these innovations. On the one hand, it focuses on increasing the level of global awareness and changing the mindset of society to move away from plastics and towards more innovative solutions. And on the other hand, it promotes legislation and financing that motivates companies in the plastics value chain to scale and grow these innovations. Such a circular model will not only ensure more sustainable production and consumption of plastics but provide a paradigm for addressing other global challenges.

Psicologia Indígena, ou a construção de um lócus de mediação

Abstract This essay aims to explore the practical, theoretical, and methodological specificities of Indigenous Psychology, proposing the use of audiovisual languages as a means to research, document, and deepen the dialogue between academic and Indigenous communities. This field is under development and reflection, adopting a transdisciplinary, complex, systemic, and dialogical perspective that contributes to the decolonization of psychology itself by creating spaces, or mediation locus, for the recognition of the existence and resilience of Indigenous cosmology and good living. We discuss audiovisual media as a mediating instance between distinct ways of understanding the historical world through image and sound capture and editing processes. We conclude that this strategy de-hierarchizes the relationship between academia and communities, striving to empower, amplify, and enhance the voices and visibility of all involved, bringing practical, theoretical, technical, methodological, and ethical advancements in constructing, disseminating, and sharing knowledge.

EEG-Based Brain Functional Network Analysis for Differential Identification of Dementia-Related Disorders and Their Onset.

Diagnosing and treating dementia, including mild cognitive impairment (MCI), is challenging due to diverse disease types and overlapping symptoms. Early MCI detection is vital as it can precede dementia, yet distinguishing it from later stage dementia is intricate due to subtle symptoms. The primary objective of this study is to adopt a complex network perspective to unravel the underlying pathophysiological mechanisms of dementia-related disorders. Leveraging the extensive availability of electroencephalogram (EEG) data, our study focuses on the meticulous identification and analysis of EEG-based brain functional network (BFNs) associated with dementia-related disorders. To achieve this, we employ the Phase Lag Index (PLI) as a connectivity measure, offering a comprehensive view of neural interactions. To enhance the analytical rigor, we introduce a data-driven threshold selection technique. This innovative approach allows us to compare the topological structures of the formulated BFNs using complex network measures quantitatively and statistically. Furthermore, we harness the power of these BFNs by utilizing them as pre-defined graph inputs for a Graph Convolution Network (GCN-net) based approach. The results demonstrate that graph theory metrics, such as the rich-club coefficient, transitivity, and assortativity coefficients, effectively distinguish between MCI, Alzheimer's disease (AD) and vascular dementia (VD). Furthermore, GCN-net achieves high accuracy (95.07% delta, 80.62% theta) and F1-scores (0.92 delta, 0.67 theta), highlighting the effectiveness of EEG-based BFNs in the analysis of dementia-related disorders.

The multifaceted role of emotion regulation in suicidality: Systematic reviews and meta-analytic evidence.

Despite the number of empirical contributions on the topic, scientists have offered contrasting perspectives on the role of adaptive versus maladaptive emotion regulation (ER) strategies in suicidality. Moreover, suicidal attempts and suicidal ideation are likely to be differentially related to single ER strategies. To provide more systematic knowledge that can be used to draw sound conclusions and formulate clinical indications, we carried out a systematic review and meta-analysis that we reported in compliance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards (Moher et al., 2009). From an initial pool of 16,530 articles retrieved from scientific databases (APA PsycInfo, APA PsycArticles, Medline, Scopus, Web of Science, and PubMed) and a search for gray literature, 226 articles were selected to perform 15 meta-analyses. In addition, metaregressions were carried out to test a series of moderators, including the type of suicidality investigated. Among adaptive strategies, results evidenced the role of reappraisal, mindfulness, and several aspects of problem solving. In contrast to our hypothesis, reflective attitude was positively associated with suicidality, calling into question the traditional distinction between adaptive and maladaptive strategies. Regarding maladaptive ER strategies, suppression, avoidance, rumination, brooding, negative problem orientation, and both impulsive and avoidant problem solving proved to be significantly associated with suicidality. Finally, several moderation effects involving age, gender composition, and type of suicidality were observed, supporting the importance of adopting a complex perspective when approaching the topic. Despite the interesting preliminary results, additional research is needed to provide a greater understanding of the interplay between the different ER strategies and suicidality and to develop effective protocols of intervention. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Landscapes of Movement Along the (Pre)Historical Libyan Sea: Keys for a Socio-Ecological History

Abstract This study examines the influence of Human Ecodynamics and Historical Ecology to understand the complexities of historical mobility. Based on Landscape Archaeology, this study considers some of these theoretical principles for studying and reconstructing the movements of past human populations. This discussion is grounded on the example of a research project focused on modelling movement and interaction patterns between the Aegean area (Crete) and northeastern African region (Marmarica) from the Late Bronze to Roman times. The project works with multivariate data representative of the routes and non-human factors that may interplay in biocultural processes. Three key aspects structure this article: (1) the emergence of Human Ecodynamics and Historical Ecology in archaeology, (2) their impact on the theoretical evolution of Landscape Archaeology, and (3) the methodological implementation of these principles through a case study. We specifically discuss the strengths of Human Ecodynamics and Historical Ecology to enhance the conceptualisation of mobility by considering the heterarchical interrelationships between human and non-human agents. Our methodological implementations showcase this by using computational approaches to model human pathways influenced by and in constant relationship with their environment. This research thus highlights the importance of transdisciplinary approaches to studying historical mobility from an archaeological and complex systems perspective.

A hybrid causal machine learning to reveal driving factors responsible coal market: Case of the Chinese industry

To achieve carbon neutrality, China must grasp the intricate factors driving coal market, as it addresses coal consumption and reduces the carbon footprint. While previous studies have identified certain factors, they have largely overlooked the impact of the overall industry sector on the coal market. In this paper, a hybrid causal machine learning model was proposed that combine with least absolute shrinkage and selection operator (LASSO), multiple linear regression (MLR), peter and clark momentary conditional independence (PCMCI) and interpretable machine learning. The approach employed a complex network perspective to identify 10 key factors in China's coal market from three dimensions: industrial sector, foreign trade and energy market. The hierarchical pattern of these factors is classified into two levels: direct factors, primarily encompassing crude oil futures, exchange rates and architectural decoration, and intermediary factors, mainly including the chemical industry and building material. Interestingly, this paper reaffirms the roles of crude oil futures and exchange rates in the coal market, as identified in prior studies. Additionally, it uncovers new influential factors primarily driven by the chemical industry and architectural decoration, previously unexplored. Furthermore, this paper found a significant contemporaneous relationship between crude oil futures and coal price index (0.151) as well as coal consumption (0.102), and the strong relationship between coal consumption and the Indonesian Rupiah to Chinese Yuan exchange rate (0.063) was also confirmed. Among the emerging dominant factors, the coal price index and the chemical industry (0.145), along with coal consumption and building materials (0.250), also exhibit a strong contemporaneous relationship. These findings highlight the importance of considering the entire industry sector while analyzing the coal market and promoting a cleaner transformation of the industry in China, and the paradigm presented not only applicable to the coal market, but can be extended to other industries.

Pharmacological reactivation of p53 in the era of precision anticancer medicine.

p53, which is encoded by the most frequently mutated gene in cancer, TP53, is an attractive target for novel cancer therapies. Despite major challenges associated with this approach, several compounds that either augment the activity of wild-type p53 or restore all, or some, of the wild-type functions to p53 mutants are currently being explored. In wild-type TP53 cancer cells, p53 function is often abrogated by overexpression of the negative regulator MDM2, and agents that disrupt p53-MDM2 binding can trigger a robust p53 response, albeit potentially with induction of p53 activity in non-malignant cells. In TP53-mutant cancer cells, compounds that promote the refolding of missense mutant p53 or the translational readthrough of nonsense mutant TP53 might elicit potent cell death. Some of these compounds have been, or are being, tested in clinical trials involving patients with various types of cancer. Nonetheless, no p53-targeting drug has so far been approved for clinical use. Advances in our understanding of p53 biology provide some clues as to the underlying reasons for the variable clinical activity of p53-restoring therapies seen thus far. In this Review, we discuss the intricate interactions between p53 and its cellular and microenvironmental contexts and factors that can influence p53's activity. We also propose several strategies for improving the clinical efficacy of these agents through the complex perspective of p53 functionality.

INTERDISCIPLINARITY AS AN INNOVATIVE APPROACH TO TEACHING NATURAL SCIENCES

The article "Interdisciplinarity as an Innovative Approach to Teaching Natural Sciences" explores the importance of an interdisciplinary approach in teaching natural sciences. The authors argue that the interdisciplinary approach allows for a deeper understanding of the subjects and involvement of students in active work with more sources of information. The article focuses on how interdisciplinarity can be applied in the teaching of science subjects such as physics, chemistry, and biology. The authors provide specific examples of how these different disciplines can be integrated to create a holistic approach to learning. For example, you can learn physical laws by applying them to chemical experiments or study biological processes using physical principles.
 The authors also explore the challenges that arise when applying an interdisciplinary approach to teaching science, including the need to ensure sufficient time for in-depth study of each discipline. However, with the help of innovative teaching methods, such as the use of interactive materials and computer programs, it is possible to reduce this challenge and ensure effective learning. Natural sciences are the key to understanding the world around us, because they help us unravel natural laws and determine the relationships between various phenomena. Teaching science can be challenging because it often requires a deep understanding of many different topics.
 One of the innovative approaches to teaching natural sciences is interdisciplinarity. It is an approach that combines different disciplines in order to understand a problem or phenomenon from a deeper and more complex perspective. The relevance of the research lies in the fact that in the modern conditions of the development of science and technology, an interdisciplinary approach in the teaching of natural sciences is of great importance. This allows students to expand their horizons and cover a wider range of knowledge, which contributes to their further professional development and career success.
 In addition, the article suggests new approaches and teaching methods that may be useful for science teachers. The practical value of the article lies in the fact that it provides recommendations for the application of an interdisciplinary approach in teaching natural sciences, which will help teachers create more interesting and effective lessons for students. In addition, the article can be useful for students who want to broaden their horizons and increase their knowledge in natural sciences.

Assessing road network resilience in disaster areas from a complex network perspective: A real-life case study from China

Recently, resilience assessment has become a significant research topic, as it is crucial for regional disaster mitigation. It is important to identify road network resilience characteristics to improve regional traffic and handling capacity during emergencies, which ensures regional transport safety management and sustainable development. In this paper, a complex-network-based resilience assessment framework coupled with resilience curve characteristics, such as vulnerability, survivability, adaptability, responsiveness and resilience, was established. Typical Chinese regions with the most extensive disaster distribution were selected to reproduce real historical disaster scenarios for comparative analysis and research. The results showed that 1) the process of the change in the resilience of the road network during a disaster conforms to the characteristics of the resilience curve; 2) dense, homogeneous networks are more resilient than sparse, clustered networks; 3) road sections with more redundancy and substitutability are more resilient; and 4) the severity of the decline in traffic network performance in disaster areas is related to the attributes of road segments and network interference methods.

Understanding response to perturbations in collaborative projects from a complex generative and adaptive systems perspective

Continuity in collaborative projects may be affected by perturbations originated by unknown or unexpected situations. This research addresses the knowledge gap related to how teams effectively overcome disruptions in collaborative projects in order to reach resilience. The study explores the relationships amongst three interconnected constructs— equivocality, governance, and interorganizational learning— as key factors to be considered during perturbations.A systemic perspective using the lenses of complex adaptive and generative systems (complexity theory) has been approached. Using a cross-case analysis, the research's contribution is summarized through a model that offers explanations into how a successful case (the LOCUTIOS project) overcame effectively two instances of perturbations, within a high-uncertainty context.The model proposes two different reaction patterns, characterized by different learning behaviours (adaptive or generative), governance approaches (complementarity or substitution), and role of equivocality (driver or barrier) to knowledge exploration. Highlights of various forms of resilience within collaborative projects when unknown unknowns arise were exposed.

Yönetişim ile İnsani Gelişmişliğin Sürdürülebilirliği: Ülkelerin Nitel Karşılaştırmalı Analizi

This study examines the sustainability of human development through various governance configurations using a qualitative comparative analysis of countries from a complex adaptive systems perspective. The World Bank's six governance dimensions are used, and 11 unique configurations are identified for different levels of human development. The research reveals that the relationship between governance and human development is complex and context-specific, with different governance models contributing to different outcomes. The results suggest that a universal governance approach is not effective in promoting human development, and it is crucial to customize policy interventions based on the specific governance dynamics of each country. This study contributes to the existing literature on the significance of governance in the context of sustainable development and highlights the need for tailored strategies that consider the intricate relationship between different governance dimensions to effectively promote sustainable human development.

Motivational Dynamics of Intermediate Chinese Learners in a COVID-Induced Remote IPA-Informed CSL Curriculum: A Case Study From a CDST Lens

Abstract Grounded in a complex and dynamic systems theory (CDST) perspective of L2 learning motivation, this year-long longitudinal study examines evolving motivational dynamics of two intermediate Chinese as a Second Language (CSL) learners at a Sino-US joint-venture university in China during the COVID-19 pandemic. Adopting Higgins’ framework of motivation, this case study focuses on the interplay of learner motivation for value, control, and truth effectiveness and contextual factors in shaping the contrastive motivational trajectories of two CSL learners who displayed discrepancy in the improvement of Mandarin oral proficiency. In particular, the two contextual factors of interest are an Integrated Performance Assessment (IPA) -informed CSL curriculum and COVID-induced remote online learning. We focus on how learners co-adapted with the “here-and-now” manifestations of these contextual factors and how their motivational dynamics and learning behaviors evolved based on multiple interrelated layers of the temporal-spatial context. The findings show that CSL learners’ motivational dynamics were shaped by multiple overlapping and interrelated motivations related to value, control, and truth effectiveness, which emerged out of the contingencies and affordances in the learning context. The learner-context co-adaptations play a significant role in directing relevant motivational dimensions and thereby shaping the overall identity of the whole system. This empirical study contributes to CSL and L2 motivational studies by exploring the applicability of a CDST approach and a global motivational framework to study intermediate CSL learners’ motivational dynamics and how they individually co-adapted with an innovative curricular design and the perturbance during the COVID-19 online teaching and learning process. The paper reflects on the effectiveness and applicability of IPA in an intermediate-level CSL curriculum from a motivational perspective and offers insights into understanding and promoting the complex learner motivation during COVID-19 for language educators.