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Service-Learning and Social Change in Criminal Justice
No full textCaron Jacobson, Senior Lecturer in Criminal Justice at Governors State University and a 2021-22 Media Research Institute Fellow, developed a video to advocate the use of service learning in criminal justice curricula. As her research demonstrates, service learning is under-utilized in criminal justice higher education and provides a unique opportunity for criminal justice undergraduate students to interact with justice-involved people face-to-face. This pedagogical approach is an effective way to challenge dualistic thinking and build students’ capacity for empathy. After participating in service learning projects, students express their desire to support community engagement and get involved in social justice issues pertaining to the field. This interest in community engagement represents their newfound understanding that the experiences and perspectives of others are valid and worth recognizing. Prof. Jacobson hopes to build a more compassionate generation of criminal justice professionals and spearhead social change with this practice. Prof. Jacobson’s video project was produced by the Department of Digital Learning & Media Design as part of the Media Research Institute of the Center for Community Media at Governors State University
Rational Love: How Personality Types Can Influence Conflict Resolution
Get PDFIs love rational? Current literature tells us that personalities impact how an individual handles general conflict (Deventer et al., 2019; Geukes et al., 2019). Due to previous research, we now hypothesize that parties with dissimilar love languages and/or enneagram types may experience conflict more intensely than those similar. Love languages and enneagram types both help to explain human personality and interpersonal interactions. Personalities impact how an individual handles general conflict and the duration of any conflict (Deventer et al.,2019; Geukes et al.,2019). Conflict duration is prolonged with those who take conflict personally, believing that their personality is viewed negatively (Squires, 2022). In addition, TCP type is less likely to resolve conflict and more likely to grow the conflict into a serial argument (Squires, 2022). Additionally, while conflict may be more hostile for those in a committed relationship, less committed individuals experience fewer conflicts overall (Lemay, 2015). Individuals often assume that others hold similar personality traits which may cause conflict (Liu, 2018). When comparing themselves to their partner, the individual will tend to believe that their personality is better than their partner’s (El, 2015). Here, we see confirmation bias (i.e., the tendency to only seek out information that supports one idea) in action which is likely to prolong the conflict overall.? Our previous research indicates that an individual’s love language & enneagram type (i.e., personality type) influences the way that they resolve conflict within their interpersonal relationships. For example, those with quality time as their primary love language tend to be level-headed during conflict resolution and may step away for a cooling off period, except for peacemakers, who may prefer to solve the conflict right away.? Our current study will explore how perfectionists, givers, challengers, & peacemakers act when resolving conflict with those who are different than them. Because we found that individuals look for similar personality traits in friendships and romantic relationships, we hypothesize that individuals with dissimilar personality types may endure conflict more intensely
Media Research Institute (MRI) Fellowship 2022-2023: Bolstering the Gender and Sexuality Studies Degree Using Storytelling and Practical Narratives
No full textDr. Lara Stache presents the progress of the Media Research Institute (MRI) Fellowship 2022-2023 with a discussion of the evolution of a project focused on storytelling from the gender and sexuality studies (GNSX) students and research on practical narratives. In this presentation, I first explain the original concept for the project, the evolution from LGBTQI+ narratives to the narratives specifically from GNSX students, and then discuss the process, value, and significance of the work completed by the MRI fellow in conjunction with GSU’s Center for Community Media and the DLMD team. The completed project is scheduled for May 2023, and we envision the final product resulting in a media package that could be aired internally on the GSU campus, and material for recruitment to the GNSX major that we hope can live on the program webpage
Drifting Streaming Peaks-Over-Threshold-Enhanced Self-Evolving Neural Networks for Short-Term Wind Farm Generation Forecast
No full textThis paper investigates the short-term wind farm generation forecast. It is observed from the real wind farm generation measurements that wind farm generation exhibits distinct features, such as the non-stationarity and the heterogeneous dynamics of ramp and non-ramp events across different classes of wind turbines. To account for the distinct features of wind farm generation, we propose a Drifting Streaming Peaks-over-Threshold (DSPOT)-enhanced self-evolving neural networks-based short-term wind farm generation forecast. Using DSPOT, the proposed method first classifies the wind farm generation data into ramp and non-ramp datasets, where time-varying dynamics are taken into account by utilizing dynamic ramp thresholds to separate the ramp and non-ramp events. We then train different neural networks based on each dataset to learn the different dynamics of wind farm generation by the NeuroEvolution of Augmenting Topologies (NEAT), which can obtain the best network topology and weighting parameters. As the efficacy of the neural networks relies on the quality of the training datasets (i.e., the classification accuracy of the ramp and non-ramp events), a Bayesian optimization-based approach is developed to optimize the parameters of DSPOT to enhance the quality of the training datasets and the corresponding performance of the neural networks. Based on the developed self-evolving neural networks, both distributional and point forecasts are developed. The experimental results show that compared with other forecast approaches, the proposed forecast approach can substantially improve the forecast accuracy, especially for ramp events. The experiment results indicate that the accuracy improvement in a 60 min horizon forecast in terms of the mean absolute error (MAE) is at least 33.6% for the whole year data and at least 37% for the ramp events. Moreover, the distributional forecast in terms of the continuous rank probability score (CRPS) is improved by at least 35.8 for the whole year data and at least 35.2 for the ramp events.https://opus.govst.edu/fac/1050/thumbnail.jp
Particle Size Determines the Phytotoxicity of ZnO Nanoparticles in Rice (Oryza sativa L.) Revealed by Spatial Imaging Techniques
No full textTo understand the nanotoxicity effects on plants, it is necessary to systematically study the distribution of NPs in vivo. Herein, elemental and particle-imaging techniques were used to unravel the size effects of ZnO NPs on phytotoxicity. Small-sized ZnO NPs (5, 20, and 50 nm) showed an inhibitory effect on the length and biomass of rice (Oryza sativa L.) used as a model plant. ZnO NP nanotoxicity caused rice root cell membrane damage, increased the malondialdehyde content, and activated antioxidant enzymes. As a control, the same dose of Zn2+ salt did not affect the physiological and biochemical indices of rice, suggesting that the toxicity is caused by the entry of the ZnO NPs and not the dissolved Zn2+. Laser ablation inductively coupled plasma optical emission spectroscopy analysis revealed that ZnO NPs accumulated in the rice root vascular tissues of the rhizodermis and procambium. Furthermore, transmission electron microscopy confirmed that the NPs were internalized to the root tissues. These results suggest that ZnO NPs may exist in the rice root system and that their particle size could be a crucial factor in determining toxicity. This study provides evidence of the size-dependent phytotoxicity of ZnO NPs.https://opus.govst.edu/fac/1176/thumbnail.jp
Sharing Hope Together
Get PDFThe primary purpose was to raise donations and aid those in need. Establishing a resource center to serve as an information center and library for farmers to gain the most up-to-date knowledge on climate change is a realistic aim and a solid sign of a successful fundraising event. It seemed like a great opportunity to engage with key contributors and supporters, so the team went ahead with it. Indeed, it may provide an opportunity to show thanks for their cooperation and provide an update on critical activities. Furthermore, it may provide an excellent opportunity to invite influencers and notable corporate leaders who are not currently involved with the charity and use it to gain new support. Knowing that a small number of people have made nearly all the campaign goal\u27s progress can inspire more giving than learning that many people have made all the goal\u27s progress. The MVC framework 7 in Dot Net Core was chosen by our team to create the website\u27s back-end, while HTML5, CSS3, Bootstrap, JavaScript, and Ajax were chosen to create the front end. Data was stored in MS-SQL. Users, Donors, and Administrators all use the fund-raising mechanism. The application is managed by the administrator. The campaigns can be posted by people as needed. Donors can sponsor campaigns or reserve events
Office of Sponsored Programs and Research Annual Report 2023
Get PDFThis annual report provides a snapshot of GovState’s diverse and impactful sponsored programs and research activities during the fiscal year. These grants help GovState to prepare our students to be competitive as they complete their studies and begin their careers and to serve as a beacon of light to the Southland community and beyond. We look forward to collaborating with the campus community to find new paths for student support, faculty research and community service in the coming year
Faculty Senate Minutes, Academic Year 2023-2024, September 23, 2023
Get PDFMinutes for the Governors State University Faculty Senate Meeting held September 21, 2023
Faculty University Service Roster - November 2023
Get PDFA list distributed in November 2023 by the Faculty Senate of members of the governance body and affiliated committees
How technology may be used for future disease predictions
Get PDFExasperated by the ongoing global pandemic, the healthcare system is grappling with the formidable challenges posed by proper and effective disease treatments. Nevertheless, amidst these growing difficulties, the healthcare field has witnessed significant technological advancements, offering promising avenues for disease prediction. Notably, a positive correlation exists between the utilization of technologies and their potential to serve as valuable tools for disease prediction. As our reliance on technological sophistication continues progressing, current research highlights numerous viable options to augment the healthcare sector. This review explores the current state of utilizing technologies and their potential to enhance healthcare, shedding light on their impact and future possibilities. By examining the existing literature, this study intends to provide a comprehensive overview of the diverse applications and benefits of technology in healthcare, offering insights into how technology can be harnessed to improve disease prediction and patient outcomes. Through analysis of the existing body of knowledge, this review aims to contribute to the ongoing discourse surrounding the integration of technology in healthcare, thereby informing future research and guiding policymakers and healthcare professionals in leveraging the full potential of technology to address the challenges faced by the healthcare system