Modeling Analysis Research Articles

Relationship between root system-soil C:N:P and soil microbial diversity at different evolutionary stages of Caragana tibetica scrub in arid desert grassland, Northern China.

Scrub root systems play a crucial role in preventing soil erosion and nutrient loss. However, the effects of the root system configuration on soil nutrient dynamics and microbial changes at various evolutionary stages remain poorly understood. In this study, we investigated the relationship between soil physical and chemical properties and the diversity of bacteria and fungi throughout the evolutionary stages of the scrub root systems. This was achieved through a combination of whole-root excavation and root tracing techniques. The results indicated that root diameter was the main factor contributing to the continuous increase in carbon (C): phosphorus (P) and nitrogen (N): P ratios as the scrub sand pile developed. The soil organic carbon (SOC), total soil nitrogen (TN), and total soil phosphorus (TP) contents in the soil in the four evolutionary stages were the highest during the developmental stage, but the change in TP content was not statistically significant (P > 0.05). Partial least squares path modeling and redundancy analysis (RDA) indicated that root system stoichiometric C and N contents were positively correlated with microbial diversity (R2 = 0.85). There was no correlation between the evolutionary stage and soil nutrient TN, whereas soil nutrient TN was negatively correlated with microbial diversity (R2 = -0.92). These findings elucidate the relationship between the evolutionary stage of root chemical measurement characteristics, soil elements and microorganisms, and their subsequent effects on root elemental composition and microbial diversity. This study enhances the current understanding of plant-soil interactions in desert steppe ecosystems.

The influence of remote work on scrum-based information technology projects management: insights for success

PurposeThis research examines how recent changes in working practices as a result of COVID-19 – most often making knowledge-based work for technologists remote to the main office – are influencing the success of software projects managed by the Scrum process model. It explores the relationship between remote working and aspects that past empirical research has identified as important to project success within Scrum.Design/methodology/approachThe research used SPSS for descriptive analysis and structural equation modeling (SEM) to test the hypotheses relationships using SmartPLS 4, using a quantitative research design, a questionnaire was used and distributed electronically to the intended sample, which includes IT project managers, developers and designers in Jordan who work in projects that use Scrum methodology for their IT projects.FindingsThe study found that working from home on Scrum projects had a significant influence on project success and highlighted the need to meet the three basic psychological requirements of autonomy, competence and relatedness. Furthermore, this research revealed that both the ability to work from home and the use of Scrum contribute to project success, with Scrum acting as a mediator.Originality/valueThis study provides an understanding of the impact of adapting to remote working on project success using the Scrum framework. By filling this gap in the literature, the study generates insights that can also be extrapolated to situations in which people do not need to work remotely after a pandemic but might still anticipate and plan for new types of disruptions in the workplace.

Strategies to enhance civic awareness for state defence in Indonesia: Measurement and benchmarking of the State Defence Index (SDI)

Countries employ various strategies to strengthen their soft power through education, public campaigns, mandatory service, and community involvement, essential for building a well-informed, prepared, and resilient citizenry. In Indonesia, the Civic Awareness for State Defence (CASD) program is designed to instil state defence awareness among citizens. This study introduces the Indonesia State Defence Index (SDI), a novel metric grounded in theoretical constructs such as national identity, nationalism, patriotism, and national pride. Differentiating from previous indices, our SDI employs advanced methodologies including Principal Component Analysis (PCA) and Structural Equation Modeling (SEM) to enhance measurement accuracy. Unlike earlier approaches that used traditional aggregation methods, our use of PCA ensures the reduction of dimensions for each state defence indicator, thereby guaranteeing that only the intended dimensions are measured. Utilising data from the State Defence Survey conducted by the Indonesian Ministry of Defence from 1 March to 26 June 2024, we aim to measure and benchmark SDI values across Indonesian regions, thereby elucidating the civic awareness profile in the context of state defence. The refined SDI provides critical insights for policymakers, highlighting regions that require focused interventions to bolster state defence preparedness.

Examining the AISAS Model and Tourist Citizenship Behaviour in context of Mining Heritage Tourism

Therefore, the objective of the research is to test the effectiveness of the Attention-Interest-Search-Action-Share model in mining heritage tourism but replacing the Action component with tourist citizenship behaviour. This will therefore yield new and key insights because there are few studies conducted in this area. The current study selected 220 tourists through a convenience sampling technique. The gathered data was treated with exploratory factor analysis and structural equation modelling techniques. Confirmatory results found on the acceptance of the first hypothesis, which is Attention Influences Interest, attention becomes very important in ensuring riveting tactics are put in place when promoting mining heritage tourism. The second hypothesis, Curiosity influences Search, is also supported and confirms that only in the condition of a deep level of curiosity, tourists search for information. The third hypothesis is stating that interest influences TCB. The fourth hypothesis postulates that interest influences Share. It supported the sixth hypothesis stating that Search influences TCB. The rejection was of the sixth hypothesis that stated Search influences Share. The seventh theory stated that TCB influences Share, thereby is accepted. These findings bear some significant implications for attaining the sustainable development goals. Precisely, it means that the promotion of mining heritage tourism advances SDG 11—Sustainable Cities and Communities—since this ensures cultural heritage is preserved and contributes to inclusive and sustainable urban development. Likewise, with increased engagement of tourists during citizenship behaviours, this particular act contributes to SDG 12 through the aspect of sustainable tourism and raising awareness. Similarly, the positive experiences that are increasingly wide follow up essentially give rise to SDG 8 through the promotion of tourism as one of the prime movers for improving the economy.

Reflecting the voices of EFL teachers in the world of Intelligent Computer-Assisted Language Assessment (ICALA): an insight into teacher immunity, reflective teaching, job satisfaction, and L2-teacher grit

Artificial intelligence (AI) and Intelligent Computer-Assisted Language Assessment (ICALA) are transforming the educational landscape by radically changing how lessons are taught and students are evaluated. As the masterminds behind the curriculum, it is critical to consider the emotional and mental health of teachers who applied ICALA as part of their language instruction. To this end, this study’s primary objective was to examine the connections between ICALA, teacher immunity, reflective teaching, job satisfaction, and l2-teacher grit. To achieve this goal, 221 English as a foreign language (EFL) university teachers from Afghanistan participated in the current research. The research outcomes identified and quantified the influences of teacher immunity and reflective teaching on job satisfaction and L2 teacher grit by data screening utilizing confirmatory factor analysis (CFA) and structural equation modeling (SEM). According to the results, TI and RT are vital in implementing AI into language assessment by maintaining an uninterrupted JS and L2TG. The study’s ramifications are further elaborated upon.

Characterizing impulsivity in individuals with methamphetamine and methcathinone use disorders.

Individuals with substance use disorder (SUD) are characterized by loss of control in drug use, such as increased impulsivity. Methamphetamine and methcathinone are psychostimulants, the use of which is accompanied by a high level of impulsivity. Whether individuals with methamphetamine use disorder (MUD) and methcathinone use disorder (MCUD) differ in different aspects of impulsivity is unclear. We investigated impulsivity traits and behaviors in individuals with MUD and MCUD. The Barratt Impulsiveness Scale (BIS), Sensation Seeking Scale (SSS), and delay discounting task (DDT) were assessed in individuals with MUD and MCUD and in healthy controls (HCs); then, we performed network-based analysis and computational modeling to understand the potential differences among the three groups. MUD subjects scored higher than MCUD subjects in terms of motor impulsivity, nonplanning impulsivity, and total BIS scores. The network analysis revealed that there were no significant differences between MUD and MCUD subjects in any centrality indices. The discount rate of MUD and MCUD subjects was significantly greater than that of HCs, whereas there was no difference in the discount rate between the two addiction groups. These findings suggest that MUD and MCUD participants differ in impulsivity traits but not in impulsive behaviors, implying that impulsive traits and behaviors represent different aspects of impulsivity.

Satisfaction with the Exercise Program and Successful Aging Among Older Adults Who Exercise Regularly: The Multiple Mediation of Physical Self-Efficacy and Exercise Adherence.

As the Republic of Korea transitions towards a super-aged society, the health and mental well-being of older adults are emerging as critical issues. While many researchers are focusing on successful aging among older adults who participate in exercise, there is a research gap in the Korean literature regarding the preconditions that foster this outcome. Therefore, this study analyzed the relationship between satisfaction and exercise, physical self-efficacy (PSE), exercise adherence, and successful aging among Korean older adults who exercise regularly. The participants were 369 (234 male and 135 female) older adults aged 65 or older living in the Republic of Korea, with an average age of 69.91 years. Data were collected from March 2024 to June 2024 and analyzed using descriptive statistics, correlation analysis, and structural equation modeling. There was no problem with the model fit. Satisfaction with exercise positively affected PSE (β = 0.317, p < 0.001), exercise adherence (β = 0.487, p < 0.001), and successful aging (β = 0.669, p < 0.001). PSE positively affected exercise adherence (β = 0.356, p < 0.001), and exercise adherence positively affected successful aging (β = 0.190, p < 0.05). Furthermore, PSE (β = 0.019, p < 0.01) and exercise adherence (β = 0.081, p < 0.05) mediated the relationship between satisfaction with exercise and successful aging. Satisfaction with exercise is important for promoting successful aging among Korean older adults who exercise. Satisfaction with exercise can increase their efficacy for performing physical activities and encourage them to continue exercising. This can ultimately lead to a happy life in old age.

Chemical composition alterations in rat brain hypothalamus induced by irisin administration using spectroscopic and machine learning techniques

This study employed Fourier transform infrared (FTIR) spectroscopy to determine the chemical composition of brain tissues and the changes induced by irisin at doses of 50 mg and 100 mg. Brain tissues were collected from control rats and those administered with irisin, and key vibrational peaks were analyzed. In the 50 mg irisin group, all described vibrations decreased compared to control tissues, while the 100 mg group showed a decrease only in lipid vibrations. Comparatively, the 50 mg group had lower absorbance of phospholipids, amides, and lipid functional groups than the 100 mg group. Lower amounts of these compounds were found in treated tissues compared to controls, with higher levels in the 100 mg group. Ratios between amide peaks revealed significant differences between groups. Principal component analysis (PCA) differentiated control and irisin-treated tissues, primarily using PC1 and PC3. The decision tree model exhibited high classification accuracy, especially in the 800–1800 cm⁻1 range, with high sensitivity and specificity. FTIR spectroscopy effectively highlighted chemical changes in brain tissues due to irisin, demonstrating dose-dependent variations. The combination of PCA, ROC analysis, and decision tree modeling underscored the potential of FTIR spectroscopy for studying the biochemical effects of compounds like irisin.

Genetic analysis of a Yayoi individual from the Doigahama site provides insights into the origins of immigrants to the Japanese Archipelago.

Mainland Japanese have been recognized as having dual ancestry, originating from indigenous Jomon people and immigrants from continental East Eurasia. Although migration from the continent to the Japanese Archipelago continued from the Yayoi to the Kofun period, our understanding of these immigrants, particularly their origins, remains insufficient due to the lack of high-quality genome samples from the Yayoi period, complicating predictions about the admixture process. To address this, we sequenced the whole nuclear genome of a Yayoi individual from the Doigahama site in Yamaguchi prefecture, Japan. A comprehensive population genetic analysis of the Doigahama Yayoi individual, along with ancient and modern populations in East Asia and Northeastern Eurasia, revealed that the Doigahama Yayoi individual, similar to Kofun individuals and modern Mainland Japanese, had three distinct genetic ancestries: Jomon-related, East Asian-related, and Northeastern Siberian-related. Among non-Japanese populations, the Korean population, possessing both East Asian-related and Northeastern Siberian-related ancestries, exhibited the highest degree of genetic similarity to the Doigahama Yayoi individual. The analysis of admixture modeling for Yayoi individuals, Kofun individuals, and modern Japanese respectively supported a two-way admixture model assuming Jomon-related and Korean-related ancestries. These results suggest that between the Yayoi and Kofun periods, the majority of immigrants to the Japanese Archipelago originated primarily from the Korean Peninsula.

Boron nitride: The key material in polymer composites for electromobility

AbstractDespite the continuous development and improvement of many technologies and multifunctional materials for the electric powertrain (ePowertrain) for electric vehicles, there are still technical issues and challenges to address such as thermal management in batteries, electric motors, and power electronic devices, as most of their failures are due to poor thermal management. Consequently, conventional engineering polymer materials already used must be replaced since most of them have low thermal conductivity and are therefore limited in performance for thermal management applications. A key solution is to develop highly thermally conductive polymer composites that combine other features, such as flame‐retardant, electrical insulation, and mechanical and barrier properties, by incorporating fillers into the polymer matrix. This approach has attracted intensive research efforts. In this review, we first examine the key drivers, trends, and solutions of the ePowertrain segment, emphasizing thermal management. Second, special attention is given to the state‐of‐the‐art boron nitride (BN) polymer composites with current or potential applications in the automotive industry, especially, in batteries, electric motors, and power electronics. Third, analysis and prediction of thermal properties of BN polymer composites by finite element simulation are presented. Finally, outlooks for future research in this field are highlighted.Highlights Thermal management of batteries, electric motors and power electronics, using BN polymer composites, optimizes the functionality of electric vehicles. Cross‐linked polymers with BNNSs provide resins for high power motors, film capacitors, and Li‐metal battery electrolytes for electric vehicles. Mathematical modeling and life cycle analysis can predict trends and research gaps in ePowertrain applications.

Revealing the brain behind travel: an analysis of neuro-tourism research using structural topic models and network analysis

ABSTRACT Neuro-tourism is a growing field that could revolutionize the tourism industry by uncovering the neurological mechanisms behind the tourist experience. However, the underlying mechanisms and interrelationships shaping the evolving landscape of neuro-tourism research have not yet been fully elucidated. This study analyzes research trends in neuro-tourism from 2006 to 2024 and identifies academic collaboration networks. We utilized structural topic modeling and network analysis to uncover the underlying academic topics in neuro-tourism. Our analysis found eight growing and four declining subfields in neuro-tourism. The network analysis showed significant contributions from countries, institutions, and journals. This research adds to existing theory by explaining the mechanisms and connections impacting the evolving neuro-tourism research field. It provides valuable insights for scholars and researchers studying the intersection of neuroscience and tourism. Understanding how research is categorized in databases like the Web of Science can help make strategic publishing decisions, encouraging interdisciplinary collaboration and innovation.

Unveiling public perceptions at the beginning of lockdown: an application of structural topic modeling and sentiment analysis in the UK and India

BackgroundThe appearance of the COVID-19 virus in December 2019, quickly escalated into a global crisis, prompting the World Health Organization to recommend regional lockdowns. While effective in curbing the virus’s spread, these measures have triggered intense debates on social media platforms, exposing widespread public anxiety and skepticism. The spread of fake news further fueled public unrest and negative emotions, potentially undermining the effectiveness of anti-COVID-19 policies. Exploring the narratives surrounding COVID-19 on social media immediately following the lockdown announcements presents an intriguing research avenue. The purpose of this study is to examine social media discourse to identify the topics discussed and, more importantly, to analyze differences in the focus and emotions expressed by the public in two countries (the UK and India). This is done with an analysis of a big corpus of tweets.MethodsThe datasets comprised of COVID-19-related tweets in English, published between March 29th and April 11th 2020 from residents in the UK and India. Methods employed in the analysis include identification of latent topics and themes, assessment of the popularity of tweets on topic distributions, examination of the overall sentiment, and investigation of sentiment in specific topics and themes.ResultsSafety measures, government responses and cooperative supports are common themes in the UK and India. Personal experiences and cooperations are top discussion for both countries. The impact on specific groups is given the least emphasis in the UK, whereas India places the least focus on discussions related to social media and news reports. Supports, discussion about the UK PM Boris Johnson and appreciation are strong topics among British popular tweets, whereas confirmed cases are discussed most among Indian popular tweets. Unpopular tweets in both countries pay the most attention to issues regarding lockdown. According to overall sentiment, positive attitudes are dominated in the UK whilst the sentiment is more neutral in India. Trust and anticipation are the most prevalent emotions in both countries. In particular, the British population felt positive about community support and volunteering, personal experiences, and government responses, while Indian people felt positive about cooperation, government responses, and coping strategies. Public health situations raise negative sentiment both in the UK and India.ConclusionsThe study emphasizes the role of cultural values in crisis communication and public health policy. Individualistic societies prioritize personal freedom, requiring a balance between individual liberty and public health measures. Collectivistic societies focus on community impact, suggesting policies that could utilize community networks for public health compliance. Social media shapes public discourse during pandemics, with popular and unpopular tweets reflecting and reshaping discussions. The presence of fake news may distort topics of high public interest, necessitating authenticity confirmation by official bloggers. Understanding public concerns and popular content on social media can help authorities tailor crisis communication to improve public engagement and health measure compliance.

Organizational Innovation as a Mediation of the Influence of Innovation Capability on Organizational Performance in Manufacturing Companies in East Java

This research aims to analyze the influence of innovation capabilities on organizational innovation, analyze the influence of innovation capabilities on organizational performance, analyze the influence of organizational innovation on organizational performance, and analyze the influence of innovation capabilities on organizational performance through organizational innovation. The sample in this study involved 140 respondents. Sampling in this study was carried out using a simple random sampling technique. The analyses techniques used were descriptive analysis and structural equation modeling (SEM) analysis. The results of the analyses show that innovation capability influences organizational innovation. Innovation ability influences organizational performance. Organizational innovation influences organizational performance. Organizational innovation as a mediator of the influence of innovation capability on organizational performance. Implementing effective innovation capabilities and promoting a culture of innovation in organizations can be an effective strategy for improving organizational performance. In a competitive business era, the involvement of high-quality human resources and the ability to innovate is the key to achieving competitive advantage and sustainable growth. Keywords: innovation capability, organizational innovation, organizational performance

Exploring attitudes toward ChatGPT among college students: An empirical analysis of cognitive, affective, and behavioral components using path analysis

The advent of generative artificial intelligence (AI) applications, such as ChatGPT, has significantly impacted various aspects of human life, including higher education. This study explores university students' attitudes toward ChatGPT, focusing on the cognitive, affective, and behavioral components of attitudes, on the basis of Mitcham's philosophical framework of attitudes toward technology. A total of 595 university students from six public and private universities in northern Peru participated in an online survey. The results of the structural equation modeling (SEM) analysis revealed that the affective component (β = 0.672∗∗∗) and the cognitive component (β = 0.260∗∗) positively influence the behavioral component of students' attitudes when ChatGPT is used. Moreover, the cognitive component (β = 0.931∗∗∗) positively influences the affective component of students' attitudes. However, gender and age did not have significant moderating effects on the relationships between the cognitive and affective components and the behavioral component. The discussion highlights that these findings contribute to understanding the psychological mechanisms underlying the adoption of ChatGPT in educational settings and offer valuable guidance for implementing this technology in teaching and learning processes. In conclusion, this study represents a significant advancement in comprehending attitudes toward generative AI technologies in higher education and opens new avenues for future research in this field.

Synthesis, C-N/N-N bond conformational analysis and evaluation of naphtho[2,3-d][1,2,3]triazole-4,9-dione tethered N-acyl hydrazones as α-amylase inhibitors: Insights from molecular modeling and ADMET analysis

In an effort to expand the repertoire of potent α-amylase inhibitors, we sought to develop novel inhibitors by combining 1,4-naphthoquinone, 1,2,3-triazole, and N-acyl hydrazone scaffolds in a single matrix. To achieve this, twelve novel naphtho[2,3-d][1,2,3]triazole-4,9‑dione tethered N-acyl hydrazones were synthesized through condensation reaction of 2-(4,9-dioxo-4,9-dihydro-1H-naphtho[2,3-d][1,2,3]triazol-1-yl)acetohydrazide with various substituted aryl aldehydes. Structural elucidation for all the compounds was performed using 1D, 2D-NMR, FTIR, and mass spectral analyses. The synthesized molecules were evaluated for their ability to inhibit α-amylase activity using acarbose as the standard drug. All the derivatives exhibited potent inhibition of α-amylase, with IC50 values ranging between 17.26 ± 0.07 to 25.62 ± 0.03 μg/mL. Notably, compound 9c possessing –meta substituted –NO2 group displayed the highest activity (IC50 = 17.26 ± 0.07 μg/mL) among the series. Structure-activity relationship (SAR) revealed the pivotal role of aryl ring substitutions in determining inhibitory efficacy. To validate these findings and to assess the binding stability of 9c within the catalytic site α-amylase dervied for A. oryzae (PDB ID:7TAA), in silico studies were performed. The compound 9c effectively occupies the enzyme's active pocket, with minimal RMSD fluctuations observed over 100 ns simulation, indicating stable protein-ligand complex. ADMET predictions suggested favorable drug-like properties, underscoring the potential of these compounds as novel α-amylase inhibitors for managing type 2 diabetes mellitus

행동기준 평정척도(BARS)를 적용한 대학생 핵심역량 측정도구 개발 및 타당화 연구: D대학의 의사소통역량을 중심으로

Objectives This study attempted to develop the core competency’s measurement tool and secure its validity by focusing on the D University’s communication capabilities and applying the behaviorally anchored rating scale based on experiences or behaviors closely related to students’ university education and life. Methods This study applied appropriate research methods according to a six-step’s systematic research procedure, including core competency analysis and competency modeling, analysis of behavioral characteristics of excellent students through FGI for professors and BEI for students, development of core competency’s measurement tool through expert council, validation through expert delphi survey, pilot test and analysis, and finalizations stage of system, definition, and measurement tool. Results The research results are as follows. First, the core competency’s system and definition with a high consistent were derived through a systematic competency modeling process. Second, the behavioral characteristics of hyperformers(high-performing students) were analyzed through interview with professors and students and reflected in the behaviorally anchored rating scale. Third, the core competency’s measurement tool(draft) with a high consistent were confirmed. Fourth, a core competency measurement tool(revised version) was tentatively derived by verifying its validity through two expert delphi surveys. Fifth, a pilot test was conducted to improve effectiveness of the core competency’s measurement tool, and reliability and validity were secured. Sixth, the finalizations stage was completed, and the system, definition, and measurement tool of core competencies were confirmed. Conclusions By developing a core competency’s measurement tool based on the behaviorally anchored rating scale focusing on D University’s communication capabilities and then revealing the process of securing reliability and validity, It could play a significant role in suggesting alternative methods to objectively measure the core competencies of each university.

뉴스 기사 빅데이터 분석을 통한 북한이탈주민의 사회적 이슈와 언어 문제 탐색: 2019-2024

Objectives The purpose of this study is to explore social issues and language problems that appear in news articles related to North Korean defectors and to suggest their implications. Methods 561 news articles related to North Korean defectors covered by major domestic newspapers and media companies from 2019 to June 2024 were collected. For analysis tools, language network analysis and topic modeling techniques were used to analyze major keywords and topics and visualize them. In addition, based on the analysis results, social issues and language problems of North Korean defectors were explored, and Korean language education implications were presented. Results he research results are as follows. First, the amount of news coverage has been increasing significantly over the past three years, and political articles have shown an overwhelmingly high proportion. Second, the main keywords are ‘government, support, human rights, protection, and settlement’. The main topics were protection of human rights of North Korean defectors, increasing number of North Korean defectors among elites and the 2030 generation, and complaints of difficulties due to mental and economic discrimination and prejudice in the process of settling in Korea. The content of the government's integrated support policy accounted for a high proportion. Third, it was found that North Korean defectors were struggling with the language difference between North and South Korea, and Korean language education focusing on pronunciation, accent, and vocabulary in each area was necessary for them. Conclusions The main topic of the news article was the integrated support for the protection of human rights and stable settlement of North Korean defectors. However, although North Korean defectors complain of ‘difficulty’ due to economic, psychological, emotional, and linguistic differences, these related topics are hardly covered in the media. Therefore, this paper suggested implications for Korean language education research for North Korean defectors' language adaptation.

How can we improve AI competencies for tomorrow's leaders: Insights from multi-stakeholders’ interaction

This study investigates factors influencing artificial intelligence (AI) competencies in higher education for sustainable development using learning theories. Utilizing a mixed-method approach, it analyzes responses from 525 students and interviews with 35 faculty members from five Indian universities. The study employs confirmatory factor analysis (CFA) and structural equation modeling (CB-SEM) to explore relationships between various learning approaches and AI competencies. Findings indicate that collaborative learning, problem-solving, and cognitive competence significantly contribute to AI proficiency. Human-tool collaboration and self-learning also enhance students' understanding of AI concepts, fostering strategic decision-making in business contexts. Additionally, thematic analysis from qualitative interviews identifies critical themes for developing an AI curriculum framework, including curriculum design, pedagogical strategies, ethical considerations, and global perspectives. The research provides an integrated theoretical model and offers practical recommendations for enhancing AI education, emphasizing the importance of interdisciplinary collaboration and ethical AI usage in management education.

Interconnecting peer feedback literacy: Exploring the relationship between providing and acting on peer feedback

Recent research highlights the concept of feedback literacy, focusing on students’ active engagement in feedback processes, including giving and receiving peer feedback. However, most studies rely on self-assessments through surveys and interviews, with few examining actual feedback behaviors. This study explores the behavioral aspects of peer feedback literacy among 844 high school students using an online system for peer feedback and revisions. Multiple measures related to provided ratings and comments as well as use in revisions were extracted using systematic coding. Factor analysis and structural equation modeling identified two distinct elements of high-quality feedback provision—providing features and rating validity—and confirmed a moderate correlation between the ability to provide quality feedback and the use of feedback. These skills were weakly correlated with writing ability. This research contributes to the emerging literature of peer feedback literacy and supports the development of more effective peer feedback training approaches.

Open-source software integration: A tutorial on species distribution mapping and ecological niche modelling

Over the last decade, access to global data has become increasingly critical for research, allowing insights into diverse biological, environmental and societal questions at a macro scale. Digitisation has greatly enhanced the use of herbarium data in the analysis of species distributions and ecological niche modelling. Yet, sources on modelling and mapping methodology using open-source software is greatly lacking for beginners. We have created a replicable and thorough tutorial to visualise species occurrence data and exploratory analysis that was developed by undergraduates with broad backgrounds and levels of experience. This tutorial integrates the open-source programmes QGIS, MaxEnt and R to develop distribution maps, using bryophytes as a case study, to promote the accessibility of open-source software and remote access learning. This tutorial has already set the foundation for further research into distribution modelling of rare Illinois bryophytes to better understand the potential impact of climate change.