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关键词： Teamwork   Guidelines   Mathematical models   Education   Computer science   Collaborative work   Task analysis   Collaborative learning   computer science education   guidelines   peer assessment (PS)  

摘要： Contribution: Students do not naturally give unbiased, accurate peer assessments (PAs). Hence, giving teamwork guidelines to students can improve their cooperation, understanding of one another, PA attitude, and PA accuracy. Background: During collaborative learning, PA can improve students' autonomy, evaluation, and communication, which often enhances their task performance and learning outcomes. However, student bias, low effort, or imprecision can bias PA. Hypothesis: This study hypothesized that teamwork guidelines can improve students' collaboration and hence their: 1) PA accuracy and 2) attitudes toward PA. Design/Method: This comparison study examined the 447 PAs and 143 survey responses of 143 university students studying computer science in 49 teams. 58 students received teamwork guidelines and 85 students did not. PAs and teacher assessments (TAs) were analyzed with a multilevel, structural equation model, and survey responses were analyzed with a multivariate outcome, multilevel, and ordered logit regression. Findings: PAs often exceeded TAs of the same student (positive bias), especialy for low-performing students. Compared to other students, students receiving teamwork guidelines gave PAs that resembled TAs more but had a similar positive bias. The relative and absolute differences in peer and TAs (PA - TA, PA - TA) mostly differed across teams rather than students. Also, students receiving teamwork guidelines viewed PA as more supportive of their learning, compared to other students without the teamwork guidelines.

关键词： Fairness   Transparency   Data   Computer science   Criminal justice  

摘要： Correctional offender management profiling for alternative sanctions (COMPAS) is a risk assessment instrument currently used in the US criminal justice system. COMPAS has sparked a lively debate on fairness that still goes on today;however, this debate has barely been taken up so far in the German-speaking context. The present paper first provides a systematic account of risk assessment by COMPAS and discusses its current use in the USA. The paper then turns to three important aspects of the debate on COMPAS, viz. fairness, transparency, and data. Finally, the paper considers possible consequences of this discussion for the German-speaking context.

关键词： Microalgae growth   Algae-bacteria symbiotic system   Black odorous water   Soluble algal products   Nutrient recycling   Harvesting efficiency  

摘要： To achieve the sustainable and effective removal efficiency of nutrients in black odorous water, light source, inter-species microalgae mixed culture, and the harvesting effect were all explored. The results showed that under a LED light source, the addition of interspecific soluble algal products (SAP) promoted the growth of Haematococcus pluvialis (H. pluvialis) M1, and its maximum specific growth rate was 1.76 times that of H. pluvialis cultivated alone. That was due to the hormesis effect between the two kinds of microalgae, the SAP produced by Scenedesmus could stimulate the growth of H. pluvialis. The algae and bacteria symbiotic system with black odorous water as the medium showed excellent performance to treat nutrients, where the concentration of ammonia nitrogen (NH3-N) and total phosphorus (TP) (0.84, 0.23 mg/L) met the requirements of landscape water. The microbial diversity analysis revealed that the introduction of microalgae changed the dominant species of the bacterial community from Bacteroidota to Proteobacteria. Furthermore, timely microalgae harvesting could prevent water quality from deteriorating and was conducive to microalgae growth and resource recycling. The higher harvest efficiency (98.1%) of H. pluvialis was obtained when an inoculation size of 20% and 0.16 g/L FeCl3 were provided.

关键词： Collaboration   Collaborative work   Education   Shape   Task analysis   Computer science   Technological innovation   Collaborative problem solving   engineering education   gender   group size  

摘要： Contribution: This article presents a study that adds evidence to the field of computer education by focusing on the interaction between shapes of tables, group size, and gender, and their effects on on-task collaborative learning actions. By studying the collaborative learning environment in the context of computer education, the aim is to understand how different on-task actions are affected by the mentioned factors. Background: Previous research on collaborative learning space in the collaborative computer education context with the focus on the group formation, gender aspect, and analysis of on-task actions. Research Questions: Do different table shapes have different effects on open-ended computer education on-task actions for different groups sizes (two and three participants) and for different genders? Methodology: In order to study a collaborative problem-solving activity that is based on creating a prototype of a responsive toy, two main conditions were examined: table shape (round or rectangular) and how this interacts with group size (two or three participants) and gender. University students were engaged in design tasks conducted in small groups following the Jigsaw pattern. Findings: Results show that students engage more in interaction with physical artifacts when collaboration is conducted in dyads. In terms of gender, the analysis shows a tendency of female students to engage more when the activity is conducted in dyads. Furthermore, the combination of a dyad structure and a round table resulted in more discussion and nonverbal interaction.

关键词： Insurance   Portfolios   Investment   Optimization   Computer science   Resource management   Computational modeling   Cooperative coevolution (CC)   estimation of distribution algorithm (EDA)   insurance portfolio   particle swarm optimization (PSO)  

摘要： With the rapid development of the insurance industry, more diverse insurance products are produced for consumers. Insurance portfolio problems have received increasing attention. While most studies focus on insurance portfolio problem for a single insured, insurance portfolio problems for a specific group of insured are even more intricate but little attention has been paid to. In this article, we propose a group insurance portfolio model for investment allocation of several insurance policies so that the total payout of the whole group can be maximized. The statistical average value of each parameter is considered in the model to approximate the expectation payout of the group insurance portfolio problem. To solve this problem, a coevolutionary estimation of distribution algorithm (EDA) utilizing the divide-and-conquer strategy is proposed. First, as the payout of each insured under a certain portfolio plan can be calculated separately, the proposed approach decomposes the group insurance portfolio problem into several single-insured insurance portfolio problems. In this way, the dimension of the optimization problem becomes lower compared to the original problem. An adaptive EDA is proposed to optimize the portfolio plan of each insured independently. Second, the group insurance portfolio problem remains a nonseparable problem since the investment amount of each insured is limited by the total investable amount of the whole group. A particle swarm optimization algorithm is adopted to cooperate with the EDA to optimize the proportion of allocation to each insured. The proposed algorithm is verified on various scenarios. The experimental results validate that the proposed approach is effective for the group insurance portfolio problem.

关键词： Learning systems   Training   Neural networks   High frequency   Computer science   Time series analysis   Task analysis   Broad learning system (BLS)   Fourier analysis   frequency principle   incremental learning  

摘要： Deep neural networks have achieved breakthrough improvement in various application fields. Nevertheless, they usually suffer from a time-consuming training process because of the complicated structures of neural networks with a huge number of parameters. As an alternative, a fast and efficient discriminative broad learning system (BLS) is proposed, which takes the advantages of flat structure and incremental learning. The BLS has achieved outstanding performance in classification and regression problems. However, the previous studies ignored the reason why the BLS can generalize well. In this article, we focus on the interpretation from the viewpoint of the frequency domain. We discover the existence of the frequency principle in BLS, i.e., the BLS preferentially captures low-frequency components quickly and then fits the high frequencies during the incremental process of adding feature nodes and enhancement nodes. The frequency principle may be of great inspiration for expanding the application of BLS.

关键词： death penalty   Herod Antipas   Herodias   John the Baptist   Julius Jones   Mark 6:14-29  

摘要： The story of John the Baptist's execution in Mark 6:14-29 has intrigued artists and biblical interpreters alike. The daughter's dance, Herodias's grudge, and Herod's impulsive oath have proven to be fertile ground to speculate on internal motivations and private conversations absent from the Markan account. The daughter has been blamed for John's death because her erotic dancing tricked Herod into making his promise. Herodias gets blamed for orchestrating the events of the banquet that lead to John's death. Herod gets blamed for losing control of himself and making an oath without considering the implications. This article reconsiders this scene with attention to the function of the dinner guests who legitimate Herod's authority, thereby implicating them as much as anyone else in John's death. Furthermore, John's execution is compared with the commutation of Julius Jones's death sentence in Oklahoma in 2021 to highlight the role of the public in determining the exertion of power.

关键词： 6 G Mobile Communication   Machine Learning   Mathematics   Learning Systems   Computer Science   Agile   Software Engineering   Machine Learning   ML Enabled Systems   Development Methodology  

摘要： Increased adoption of machine learning (ML) in business has led to a surge in ML-enabled systems in the market giving rise to new challenges. This article provides insights into Agile4MLS, highlighting the challenges we faced and the process we followed.

关键词： 21st century abilities   distance education and online learning   learning communities   social media  

摘要： Live streaming platforms like *** count millions of viewers and performers, pointing to novel practices and interactions. Instructional applications of this phenomenon are rising with thematic channels and shows aimed at teaching and debating a variety of subjects ranging from art to programming. However, few research publications have specifically explored trends in pedagogical strategies and learning behaviours of viewing audiences. This study responded to this need by analysing computer science shows on ***. A total of 40 hours of live streaming were analysed within a Community of Inquiry framework using the concepts of social affordances, computational thinking, and teaching style. Data collected from both expert and novice streamers included streamers' actions, on-screen activity, and online discussions. Results pointed to specific tactics employed by both performers and viewers for exploring computer science issues and dynamics together, with instances of peer-tutoring, construed learning, and significant transparency, even when top-down instruction was staged. Practitioners notes What is already known about this topic Live streaming is a popular media practice all around the world, with *** as the leading hosting platform. A rising number of live streaming shows are focusing on education and learning topics, from STEM to art. What this paper adds A first exploration of instructional streaming focused on computer science education. An analysis of best practices in instructional streaming in terms of community building, teaching style, and computational thinking processes. A better understanding of how communities of inquiry can be hosted on ***. Implications for practice and/or policy Practitioners can harness this study's results for informing better educational streaming. Educators may refer to this article's highlights for selecting and evaluating educational streaming shows. Policy makers will be able to use this article's insights

关键词： Impact prediction   h-index   Gender   Discrimination   Machine learning  

摘要： The advent of large-scale bibliographic databases and powerful prediction algorithms led to calls for data-driven approaches for targeting scarce funds at researchers with high predicted future scientific impact. The potential side-effects and fairness implications of such approaches are unknown, however. Using a large-scale bibliographic data set of N = 111,156 Computer Science researchers active from 1993 to 2016, I build and evaluate a realistic scientific impact prediction model. Given the persistent under-representation of women in Computer Science, the model is audited for disparate impact based on gender. Random forests and Gradient Boosting Machines are used to predict researchers' h-index in 2010 from their bibliographic profiles in 2005. Based on model predictions, it is determined whether the researcher will become a high-performer with an h-index in the top-25% of the discipline-specific h-index distribution. The models predict the future h-index with an accuracy of R-2 = 0.875 and correctly classify 91.0% of researchers as high-performers and low-performers. Overall accuracy does not vary strongly across researcher gender. Nevertheless, there is indication of disparate impact against women. The models underestimate the true h-index of female researchers more strongly than the h-index of male researchers. Further, women are 8.6% less likely to be predicted to become high-performers than men. In practice, hiring, tenure, and funding decisions that are based on model predictions risk to perpetuate the under-representation of women in Computer Science.