Research has shown that female students cannot profit as much as male students can from cooperative learning in physics, especially in mixed-gender dyads. This study has explored the influence of partner gender on female students’ learning achievement, interaction and the problem-solving process during cooperative learning. In Shanghai, a total of 50 students (26 females and 24 males), drawn from two classes of a high school, took part in the study. Students were randomly paired, and there were three research groups: mixed-gender dyads (MG), female–female dyads (FF) and male–male dyads (MM). Analysis of students’ pre- and post-test performances revealed that female students in the single-gender condition solved physics problems more effectively than did those in the mixed-gender condition, while the same was not the case for male students. We further explored the differences between female and male communication styles, and content among the three research groups. It showed that the females’ interaction content and problem-solving processes were more sensitive to partner gender than were those for males. This might explain why mixed-gender cooperation in physics disadvantages females in high schools.
MULTIFILE
Research has shown that female students cannot profit as much as male students can from cooperative learning in physics, especially in mixed-gender dyads. This study has explored the influence of partner gender on female students’ learning achievement, interaction and the problem-solving process during cooperative learning. In Shanghai, a total of 50 students (26 females and 24 males), drawn from two classes of a high school, took part in the study. Students were randomly paired, and there were three research groups: mixed-gender dyads (MG), female–female dyads (FF) and male–male dyads (MM). Analysis of students’ pre- and post-test performances revealed that female students in the single-gender condition solved physics problems more effectively than did those in the mixed-gender condition, while the same was not the case for male students. We further explored the differences between female and male communication styles, and content among the three research groups. It showed that the females’ interaction content and problem-solving processes were more sensitive to partner gender than were those for males. This might explain why mixed-gender cooperation in physics disadvantages females in high schools.
MULTIFILE
Purpose – The purpose of this paper is to examine the prevalence of psychopathology including substance use disorders in a sample of detained female systematic offenders.Design/methodology/approach – All case files of female systematic offenders who had been subjected to a special court order for systematic offenders in the period 2004-2014 were studied. A total of 81 fairly complete case files were selected for the study. These were all systematic offenders as they had been sentenced for at least 25 offences with an average of 102 offences over a period of 17.5 years. Findings – All except one woman were addicted to substances in the past year, with an average duration of addiction of 21 years. In addition, 53 per cent were diagnosed with another DSM Axis I disorder and 73 per cent were diagnosed with a personality disorder. Furthermore, 32-59 per cent were found to haveintellectual dysfunctions. In total, 12 per cent had one type of the above disorders, 43 per cent two types, 31 per cent three types and 14 per cent all four types. The prevalence rates of these disorders were higher than those reported in other prison studies.Research limitations/implications – It is concluded that female systematic offenders can be characterised as problematic in many respects. Even in such a problematic group treatment can be provided.Originality/value – The present study is the only study that provides prevalence data of mental disorders among female systematic offenders.
The production, use, disposal and recovery of packaging not only generates massive volumes of waste, it also consumes raw materials, water and energy (Fitzpatrick et al. 2012). Simultaneously, consumers have shown an increasing interest in products incorporating sustainable and social attributes (Kletzan et al., 2006). As a result, environmentally friendly packaging, also called ecofriendly or sustainable packaging, has become mainstream. In this context, packaging is more than just ensuring the product's protection and easing transportation, it is also a communicative tool (Palmer, 2000) and it becomes associated with multiple drivers of the purchasing process. Consequently, companies face pressure to innovate responding to consumer demands, and focusing on sustainable solutions that reduce harmful materials and favour green alternatives for both, the product and the packaging. Although the above has triggered research on consumer choice for sustainable products and alternatives on sustainable packaging, the relation between sustainable packaging and consumer behaviour remains underexplored. This research unpacks this relationship, i.e., empirically verifies which dimensions (recyclability, biodegradability, reusability) of sustainable packaging are perceived and valued by consumers. Put differently, this research investigates consumer behaviour towards the functions of sustainable packaging in terms of product protection, convenience, reliability of information and promotion, and scrutinises the perceived credibility of the associated ethical responsibility claims. It aims to identify those packaging materials and/or sustainability characteristics perceived as more sustainable by consumers as well as the factors influencing actual consumer choice towards sustainable packaged products. We aim to gain more insights in the perceptual frame that different types of consumers apply when exposed to sustainable packaging. To this end, we will make use of revealed preference methods to measure consumer valuations of sustainable packaged products. This game-theoretic approach should provide a more complete depiction of consumers' perceptions and preferences.
Multiple sclerosis (MS) is a severe inflammatory condition of the central nervous system (CNS) affecting about 2.5 million people globally. It is more common in females, usually diagnosed in their 30s and 40s, and can shorten life expectancy by 5 to 10 years. While MS is rarely fatal; its effects on a person's life can be profound, which signifies comprehensive management and support. Most studies regarding MS focus on how lymphocytes and other immune cells are involved in the disease. However, little attention has been given to red blood cells (erythrocytes), which might also be important in developing MS. Artificial intelligence (AI) has shown significant potential in medical imaging for analyzing blood cells, enabling accurate and efficient diagnosis of various conditions through automated image analysis. The project aims to implement an AI pipeline based on Deep Learning (DL) algorithms (e.g., Transfer Learning approach) to classify MS and Healthy Blood cells.
In societies where physical activity levels are declining, stimulating sports participation in youth is vital. While sports offer numerous benefits, injuries in youth are at an all-time high with potential long-term consequences. Particularly, women football's popularity surge has led to a rise in knee injuries, notably anterior cruciate ligament (ACL) injuries, with severe long-term effects. Urgent societal attention is warranted, supported by media coverage and calls for action by professional players. This project aims to evaluate the potential of novel artificial intelligence-based technology to enhance player monitoring for injury risk, and to integrate these monitoring pathways into regular training practice. Its success may pave the way for broader applications across different sports and injuries. Implementation of results from lab-based research into practice is hindered by the lack of skills and technology needed to perform the required measurements. There is a critical need for non-invasive systems used during regular training practice and allowing longitudinal monitoring. Markerless motion capture technology has recently been developed and has created new potential for field-based data collection in sport settings. This technology eliminates the need for marker/sensor placement on the participant and can be employed on-site, capturing movement patterns during training. Since a common AI algorithm for data processing is used, minimal technical knowledge by the operator is required. The experienced PLAYSAFE consortium will exploit this technology to monitor 300 young female football players over the course of 1 season. The successful implementation of non-invasive monitoring of football players’ movement patterns during regular practice is the primary objective of this project. In addition, the study will generate key insights into risk factors associated with ACL injury. Through this approach, PLAYSAFE aims to reduce the burden of ACL injuries in female football players.
