The Effects of Social Messaging on Students’ Learning and Intrinsic Motivation in Peer Assessment

This study aims to gain a better understanding of how the newly arisen social messaging may impact the practice of peer assessment. Seventy-nine ESL (English as Second Language) students reviewed each other’s English essays in three peer assessment groups: a three-member group using wiki (wiki group), a three-member group using social messaging (small messaging group), and a six-member group using social messaging (big messaging group). Data analysis suggested that peer assessment facilitated by social messaging can be at least of the same effectiveness as wiki-facilitated peer assessment on ESL students’ writing skills and intrinsic motivation. In addition, the findings indicated that students in the small messaging group outperformed students in the big messaging group on essay writing, and reported a significantly higher rating on Perceived Competence, a positive indicator of the behavioral measures of intrinsic motivation, than students in the big messaging group

Less is More? An Empirical Study on Configuration Issues in Python PyPI Ecosystem

Python is widely used in the open-source community, largely owing to the extensive support from diverse third-party libraries within the PyPI ecosystem. Nevertheless, the utilization of third-party libraries can potentially lead to conflicts in dependencies, prompting researchers to develop dependency conflict detectors. Moreover, endeavors have been made to automatically infer dependencies. These approaches focus on version-level checks and inference, based on the assumption that configurations of libraries in the PyPI ecosystem are correct. However, our study reveals that this assumption is not universally valid, and relying solely on version-level checks proves inadequate in ensuring compatible run-time environments. In this paper, we conduct an empirical study to comprehensively study the configuration issues in the PyPI ecosystem. Specifically, we propose PyCon, a source-level detector, for detecting potential configuration issues. PyCon employs three distinct checks, targeting the setup, packing, and usage stages of libraries, respectively. To evaluate the effectiveness of the current automatic dependency inference approaches, we build a benchmark called VLibs, comprising library releases that pass all three checks of PyCon. We identify 15 kinds of configuration issues and find that 183,864 library releases suffer from potential configuration issues. Remarkably, 68% of these issues can only be detected via the source-level check. Our experiment results show that the most advanced automatic dependency inference approach, PyEGo, can successfully infer dependencies for only 65% of library releases. The primary failures stem from dependency conflicts and the absence of required libraries in the generated configurations. Based on the empirical results, we derive six findings and draw two implications for open-source developers and future research in automatic dependency inference.Comment: This paper has been accepted by ICSE 202

Towards Modeling Software Quality of Virtual Reality Applications from Users' Perspectives

Virtual Reality (VR) technology has become increasingly popular in recent years as a key enabler of the Metaverse. VR applications have unique characteristics, including the revolutionized human-computer interaction mechanisms, that distinguish them from traditional software. Hence, user expectations for the software quality of VR applications diverge from those for traditional software. Investigating these quality expectations is crucial for the effective development and maintenance of VR applications, which remains an under-explored area in prior research. To bridge the gap, we conduct the first large-scale empirical study to model the software quality of VR applications from users' perspectives. To this end, we analyze 1,132,056 user reviews of 14,150 VR applications across seven app stores through a semiautomatic review mining approach. We construct a taxonomy of 12 software quality attributes that are of major concern to VR users. Our analysis reveals that the VR-specific quality attributes are of utmost importance to users, which are closely related to the most unique properties of VR applications like revolutionized interaction mechanisms and immersive experiences. Our examination of relevant user complaints reveals the major factors impacting user satisfaction with VR-specific quality attributes. We identify that poor design or implementation of the movement mechanisms, control mechanisms, multimedia systems, and physics, can significantly degrade the user experience. Moreover, we discuss the implications of VR quality assurance for both developers and researchers to shed light on future work. For instance, we suggest developers implement sufficient accessibility and comfort options for users with mobility limitations, sensory impairments, and other specific needs to customize the interaction mechanisms. Our datasets and results will be released to facilitate follow-up studies

Measurement Invariance of the Depression Anxiety Stress Scales-21 Across Gender in a Sample of Chinese University Students

The Depression Anxiety Stress Scales-21 (DASS-21) has three 7-item subscales (depression, anxiety, and stress). The current study aims assess the gender-based measurement invariance of the DASS-21 questionnaire in a Chinese university student sample from five different cities. The sample was composed of 13208 participants (62.3% female, mean age of 19.7 years, and SD age = 1.8). Multi-group confirmatory factor analysis supported full measurement invariance for the three subscales. The findings support the measurement invariance of DASS-21 scores across gender. Future research on the DASS should include additional validation across ethnicities and testing of all versions of the DASS

Neurological Manifestation of Incretin-Based Therapies in Patients with Type 2 Diabetes: A Systematic Review and Network Meta-Analysis.

As a new class of antidiabetic drug, incretin-based therapies, which include dipeptidyl peptidase-4 inhibitors (DPP-4Is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs), have raised concerns about symptoms of withdrawal in patients with type 2 diabetes mellitus (T2DM), such as dizziness and headache. To systematically evaluate whether incretin-based therapies may lead to dizziness and headache in patients with T2DM compared to other traditional antidiabetic drugs or placebo. We searched Medline, Embase, the Cochrane library, and clinicaltrials.gov from inception through June 23, 2017, to identify randomized controlled trials of the safety of DPP-4Is or GLP-1 RAs versus placebo or other antidiabetic drugs in T2DM patients. We used the network meta-analysis under the frequentist framework to compare the association between multiple antidiabetic drugs and dizziness and headache. A total of 233 clinical trials with nine treatments and 147,710 patients were included: two incretin-based therapies, one placebo, and six traditional antidiabetic drugs (metformin, insulin, sulfonylurea, thiazolidinediones, alpha-glucosidase inhibitor, and sodium-glucose co-transporter 2). Compared to insulin, thiazolidinediones, or placebo, GLP-1 RAs statistically significantly increased the risk of dizziness (odds ratios [ORs]: 1.92, 1.57, and 1.40, respectively) and headache (ORs: 1.34, 1.41, and 1.18, respectively). DPP-4Is increased the risk of headache (OR: 1.22, 95% confidence interval [CI]: 1.02 to 1.46; moderate quality) and dizziness (OR: 1.46, 95% CI: 1.05 to 2.03; moderate quality) compared to insulin. Of the incretin-based therapies, DPP-4Is had a lower risk of dizziness than GLP-1 RAs (OR: 0.76, 95% CI: 0.67 to 0.87; high quality). Ranking probability analysis indicated that GLP-1 RAs may have the greatest risk of both dizziness and headache among the nine treatments (22.5% and 23.4%, respectively), whereas DPP-4Is were in the middle (46.2% and 45.0%, respectively). Incretin-based therapies increase the risk of dizziness and headache compared to insulin, thiazolidinediones, and placebo

How to Use Live Streaming to Improve Consumer Purchase Intentions: Evidence from China

As a new business model, live-streaming commerce has great commercial value. This study used the stimulus–organism–response framework to explore the psychological mechanisms of how live peculiarities impact consumer behavioral responses as well as the effects of gender and platform differences, and to make clear how to choose the two dependent variables of engagement and purchase intentions. Using 454 valid questionnaires from consumers who had made purchases during live streaming, the authors employed partial least squares structural equation modeling to analysis the research model. The results suggest that interactivity, visualization, entertainment, and professionalization play considerable roles in consumer behavioral responses and that their psychological mechanisms are different. Male respondents are more satisfied with interactivity than females. E-commerce platforms are more interactive, visible and professional than social media platforms, and the trust mechanism of social media platforms is immature. If we use engagement to describe consumer behavioral responses of interactivity and purchase intentions to describe consumer behavioral responses of visualization, entertainment, and professionalization, this provides a basis for selecting the two dependent variables in live-streaming commerce. This study extends existing theoretical research on live-streaming commerce and provides some managerial implications for platforms, stores, and streamers

CHARACTERIZATION OF BULK SOIL HUMIN AND ITS ALKALINE-SOLUBLE AND ALKALINE-INSOLUBLE FRACTIONS

Humic substances are the major components of soil organic matter. Among the three humic substance components (humic acid, fulvic acid, and humin), humin is the most insoluble in aqueous solution at any pH value and, in turn, the least understood. Humin has poor solubility mainly because it is tightly bonded to inorganic soil colloids. By breaking the linkage between humin and inorganic soil colloids using inorganic or organic solvents, bulk humin can be partially soluble in alkali, enabling a better understanding of the structure and properties of humin. However, the structural relationship between bulk humin and its alkaline-soluble (AS) and alkaline-insoluble (AIS) fractions is still unknown. In this study, we isolated bulk humin from two soils of Northeast China by exhaustive extraction (25 to 28 times) with 0.1 mol L-1 NaOH + 0.1 mol L-1 Na4P2O7, followed by the traditional treatment with 10 % HF-HCl. The isolated bulk humin was then fractionated into AS-humin and AIS-humin by exhaustive extraction (12 to 15 times) with 0.1 mol L-1 NaOH. Elemental analysis and solid-state 13C cross-polarization magic angle spinning nuclear magnetic resonance (13C CPMAS NMR) spectroscopy were used to characterize and compare the chemical structures of bulk humin and its corresponding fractions. The results showed that, regardless of soil types, bulk humin was the most aliphatic and most hydrophobic, AS-humin was the least aliphatic, and AIS-humin was the least alkylated among the three humic components. The results showed that bulk humin and its corresponding AS-humin and AIS-humin fractions are structurally differed from one another, implying that the functions of these humic components in the soil environment differed

Effect of Heat Treatment on Microstructure and Tribological Properties of Laser Cladding CeO₂/Ni60 Composite Coating on 35CrMoV Steel

A Ni60 cladding layer with addition of 6.0% CeO2 was prepared on 35CrMoV steel by laser cladding technology. The prepared sample was placed at 500 °C, 600 °C and 700 °C for 60 min to explore the effects of heat treatment on the tribological properties of the composite coating. The microstructure, phase composition, microhardness and tribological properties of the composite coating were characterized by optical microscopy and scanning electron microscopy (SEM), X-ray diffraction (XRD), micro-Vickers hardness tester and MicroXAM-800 optical surface photometer, respectively. According to the above experimental results analysis, the main components of 6.0% CeO2/Ni60 cladding layer are γ-(Fe,Ni),Cr7C3,Cr23C6,CrB, CrFeB and Cr2Ni3. By calculating the FWHM value and the left shift of the XRD diffraction peak, it is found that the coating grains are remarkably refined and the microstructure uniformity is significantly improved under the condition of heat treatment at 500 °C. The experimental results show that the Ni60 composite coating with 6.0% CeO2 has the best friction and wear performance at 500 °C. The wearing quality of the composite coating at 500 °C was reduced by 43%