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The computer-supported writing assessment (CSWA) has been widely used to reduce instructor workload and provide real-time feedback. Interpretability of CSWA draws extensive attention because it can benefit the validity, transparency, and knowledge-aware feedback of academic writing assessments. This study proposes a novel assessment tool, EduNERScore, which enables raters to identify different types of domain knowledge from unstructured educational texts and strengthen the interpretation of assessment through knowledge-aware evidence. This research uses an educational experiment to examine raters' validity, efficiency, interpretability and user perception with and without the support of EduNERScore. The findings show that the experimental group with the support of EduNERScore achieves human-expert validity, high efficiency, interpretability and good use perception, compared with the control group. Finally, based on the empirical results, this research discusses the technological and educational implications for developing and applying the interpretable CSWA system in education.

Group formation is a critical factor which influences collaborative processes and performances in computer-supported collaborative learning (CSCL). Automatic grouping has been widely used to generate groups with heterogeneous attributes and to maximize the diversity of students' characteristics within a group. But there are two dominant challenges that automatic grouping methods need to address, namely the barriers of uneven group size problem, and the inaccessibility of student characteristics. This research proposes an optimized, genetic algorithm-based grouping method that includes a conceptual model and an algorithm module to address these challenges. Through a quasi-experiment research, we compare collaborative groups' performance, processes, and perceptions in China's higher education. The results indicate that the experimental groups outperform the traditional grouping methods (i.e., random groups and student-formed groups) in terms of final performances, collaborative processes, and student perceptions. Based on the results, we propose implications for implementation of automatic grouping methods, and the use of collaborative analytics methods in CSCL.

The design of social learning analytics (SLA) tools has become a practical means to make available learning information with a goal to improve students' regulation, reflection, and engagement in online learning. This design-based research uses the multi-method analytics to iteratively design, implement, and modify the SLA tool that makes available social, topic, and cognitive information to students in online discussions. This tool demonstrates students' online discussions from social, sematic, and cognitive aspects. This research further uses online questionnaire and interview methods to investigate students' perceptions about the tool's usefulness and usability. After experiencing this tool, students proposed critical feedback for tool improvement from the network visualization, peer reference, and explanation support perspectives. Overall, the SLA tool is a beneficial tool to foster students' awareness of their own learning and peer learning process to improve students' regulation and reflection of learning and eventually improve student engagement in online discussions.

Amyotrophic lateral sclerosis is a neurodegenerative disease, and the molecular mechanism underlying its pathology remains poorly understood. However, inflammation is known to play an important role in the development of this condition. To identify driver genes that affect the inflammatory response in amyotrophic lateral sclerosis, as well as potential treatment targets, it is crucial to analyze brain tissue samples from patients with both sporadic amyotrophic lateral sclerosis and C9orf72-related amyotrophic lateral sclerosis. Therefore, in this study we used a network-driven gene analysis tool, NetBID2.0, which is based on SJARACNe, a scalable algorithm for the reconstruction of accurate cellular networks, to experimentally analyze sequencing data from patients with sporadic amyotrophic lateral sclerosis. The results showed that the OSMR gene is pathogenic in amyotrophic lateral sclerosis and participates in the progression of amyotrophic lateral sclerosis by mediating the neuroinflammatory response. Furthermore, there were differences in OSMR activity and expression between patients with sporadic amyotrophic lateral sclerosis and those with C9orf72-related amyotrophic lateral sclerosis. These findings suggest that OSMR may be a diagnostic and prognostic marker for amyotrophic lateral sclerosis. [ABSTRACT FROM AUTHOR]

Background: Colon cancer is one of the most common digestive tract malignancies. Although immunotherapy has brought new hope to colon cancer patients, there is still a large proportion of patients who do not benefit from immunotherapy. Studies have shown that neutrophils can interact with immune cells and immune factors to affect the prognosis of patients. Methods: We first determined the infiltration level of neutrophils in tumors using the CIBERSORT algorithm and identified key genes in the final risk model by Spearman correlation analysis and subsequent Cox analysis. The risk score of each patient was obtained by multiplying the Cox regression coefficient and the gene expression level, and patients were divided into two groups based on the median of risk score. Differences in overall survival (OS) and progression‐free survival (PFS) were assessed by Kaplan–Meier survival analysis, and model accuracy was validated in independent dataset. Differences in immune infiltration and immunotherapy were evaluated by immunoassay. Finally, immunohistochemistry and western blotting were performed to verify the expression of the three genes in the colon normal and tumor tissues. Results: We established and validated a risk scoring model based on neutrophil‐related genes in two independent datasets, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, with SLC11A1 and SLC2A3 as risk factors and MMP3 as a protective factor. A new nomogram was constructed and validated by combining clinical characteristics and the risk score model to better predict patients OS and PFS. Immune analysis showed that patients in the high‐risk group had immune cell infiltration level, immune checkpoint level and tumor mutational burden, and were more likely to benefit from immunotherapy. Conclusions: The low‐risk group showed better OS and PFS than the high‐risk group in the neutrophil‐related gene‐based risk model. Patients in the high‐risk group presented higher immune infiltration levels and tumor mutational burden and thus may be more responsive to immunotherapy. [ABSTRACT FROM AUTHOR]

Introduction: This study aimed to compare the efficacy and safety of docetaxel + trastuzumab + pertuzumab and docetaxel + carboplatin + trastuzumab + pertuzumab for treating HER2-positive breast cancer. Method: HER2-positive breast cancer from patients diagnosed between January 2020 and September 2022 were included in this retrospective study. Docetaxel + trastuzumab + pertuzumab or docetaxel + carboplatin + trastuzumab + pertuzumab was selected as the neoadjuvant regimen. The primary endpoint was a complete pathological remission rate. Secondary endpoints were toxicity during neoadjuvant treatment, adjustment of the neoadjuvant therapy scheme, and adjuvant medication. Result: A total of 81 patients were included in this study (38 in the docetaxel + carboplatin + trastuzumab + pertuzumab treatment group and 43 in the docetaxel + trastuzumab + pertuzumab group). The complete pathological remission rates in the docetaxel + carboplatin + trastuzumab + pertuzumab and docetaxel + trastuzumab + pertuzumab groups were 44.7% (95% confidence interval: 30.2%-60.3%) and 51.2% (95% confidence interval: 36.8%-65.4%), respectively. The incidence of grade 3 or higher toxicity in the docetaxel + carboplatin + trastuzumab + pertuzumab group was significantly higher than that in the docetaxel + trastuzumab + pertuzumab group (68.4% vs 39.5%, P =.009). Neutropenia and asthenia were the most common grade 3 or higher toxicities. The incidence of neoadjuvant scheme adjustment was significantly higher in the docetaxel + carboplatin + trastuzumab + pertuzumab group than in the docetaxel + trastuzumab + pertuzumab group (26.3% vs 7.0%, P =.039). The proportion of patients who received <6 cycles of neoadjuvant therapy was significantly higher in the docetaxel + carboplatin + trastuzumab + pertuzumab group than in the docetaxel + trastuzumab + pertuzumab group (31.6% vs 4.7%, P =.004). Patients in the docetaxel + carboplatin + trastuzumab + pertuzumab group received higher doses of granulocyte-macrophage colony-stimulating factor. Conclusion: In the neoadjuvant treatment of HER2-positive breast cancer, the docetaxel + trastuzumab + pertuzumab regimen might be more tolerated than the docetaxel + carboplatin + trastuzumab + pertuzumab regimen and did not show a lower complete pathological remission rate. However, our findings require further validation through prospective studies. [ABSTRACT FROM AUTHOR]

The computer-supported writing assessment (CSWA) has been widely used to reduce instructor workload and provide real-time feedback. Interpretability of CSWA draws extensive attention because it can benefit the validity, transparency, and knowledge-aware feedback of academic writing assessments. This study proposes a novel assessment tool, EduNERScore, which enables raters to identify different types of domain knowledge from unstructured educational texts and strengthen the interpretation of assessment through knowledge-aware evidence. This research uses an educational experiment to examine raters' validity, efficiency, interpretability and user perception with and without the support of EduNERScore. The findings show that the experimental group with the support of EduNERScore achieves human-expert validity, high efficiency, interpretability and good use perception, compared with the control group. Finally, based on the empirical results, this research discusses the technological and educational implications for developing and applying the interpretable CSWA system in education. [ABSTRACT FROM AUTHOR]

Design is a powerful weapon for modern companies so it is important to have excellent designers in the industry. The purpose of this study is to explore the learning problems and the resources that students use to overcome problems in undergraduate industrial design studio courses. A survey with open-type questions was conducted to collect data. Participants in this study were 189 undergraduate industrial design students from three universities, and two coding schema were formulated for analysing the data. The results demonstrated that the most difficult design tasks included concept generation, design presentation, and design research. The learning resources used to solve the learning problems included four categories: people, object, method, and environment. This information will increase the understanding of the learning process of students and provide a reference for teaching and the setting of learning resources in industrial design education.