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Willard Hall, Undated
No full textColor photo of Willard Hall with cars parked out front. A second sign hangs below the Frances Willard Hall for Girls 1923 engraving, but cannot be made out. Potentially a Campus Security Office sign as Willard served as that space for a period, at least in 1970.https://digitalcommons.pittstate.edu/willardbuilding/1111/thumbnail.jp
AI in Higher Ed, Where Are We Now?: Insights from the 2025 EDUCAUSE AI Landscape Study
Get PDFCurious about how higher education is really using AI? Wondering what’s next for AI policies, workforce impacts, and leadership strategies? The 2025 EDUCAUSE AI Landscape Study has the answers! Based on fresh data from institutions across higher ed, this study highlights key trends, challenges, and opportunities in AI adoption. Stop by our poster session to get a quick snapshot of where AI stands today—and where it’s headed. Let’s talk about what these findings mean for PSU and the future of AI in higher education!https://digitalcommons.pittstate.edu/ai-posters-2025/1000/thumbnail.jp
Generating Rubrics via ChatGPT
Get PDFRubrics serve as essential tools in education, providing clear expectations, objective grading criteria, and structured feedback for both instructors and students. Well-designed rubrics enhance transparency, promote consistency in assessment, and support student learning by clarifying performance standards. However, developing effective rubrics can be time-consuming and challenging, particularly for instructors managing multiple courses or diverse assignments.
The integration of artificial intelligence (AI), particularly ChatGPT, offers an efficient approach to rubric generation. By leveraging natural language processing, ChatGPT can create detailed, customizable rubrics that align with specific learning objectives and assessment needs. This process enables instructors to quickly generate rubrics tailored to various assignment types, disciplines, and proficiency levels. Additionally, AI-assisted rubric creation supports instructors by providing templates that can be refined based on course-specific requirements, thereby reducing workload while maintaining high-quality assessment standards.
For students, clearly defined rubrics contribute to a deeper understanding of expectations, fostering self-regulation and improved academic performance. AI-generated rubrics can also facilitate timely feedback, aiding students in identifying areas for improvement. Moreover, the adaptability of AI tools allows for rapid revisions and modifications, ensuring rubrics remain relevant to evolving instructional goals.
This presentation explores the benefits and challenges of generating rubrics via ChatGPT, highlighting its potential to enhance assessment practices in educational settings.https://digitalcommons.pittstate.edu/ai-posters-2025/1001/thumbnail.jp
John E. Susky
No full textPhoto of a faculty member who served as editor for the Midwest Quarterlyhttps://digitalcommons.pittstate.edu/yearbookphotos/1041/thumbnail.jp
Poster Break
No full textAnna Beth Gilmore stands next to her poster as she waits to be interviewed.https://digitalcommons.pittstate.edu/aisymp-photos-2025/1025/thumbnail.jp
Panelists and Symposium Committee
No full textJorge Leon, Susan Bon, Michelle Hudiburg, Scott Parish, Santiago Morel Berni, Ryan McFarlane, Magdalene Moy, Andra Stefanoni, and Heather Carterhttps://digitalcommons.pittstate.edu/aisymp-photos-2025/1000/thumbnail.jp
Demographic and socioeconomic determinants of cancer rates
No full textCancer is one of the leading causes of death in the United States. The National Cancer Institute defines cancer as a disease in which some of the body\u27s cells grow uncontrollably and spread to other parts of the body. Even with advancements in treatment methods there is no cure and even once in remission the cancer can come back. This study aims to answer how demographic and socioeconomic factors impact the cancer rate around the United States. A multivariate pooled regression analysis is conducted using linear panel data. To run the regression, we are using ordinary least squares. Cancer rate is the dependent variable. Population, gender, age, race, median household income, and marriage rate are the independent variables. Results from the regression show that male, female, median household income and marriage cause the cancer rate to increase, and they are all significant. Population, ages, and races all cause the cancer rate to decrease. They are all significant but the age group 0-24. AR (1) and AR (2) were used to help the regression model. The implication of these results shows that population, gender, ages 25 and above, ethnicity, median household income, and marriage rates play a significant role in shaping cancer rates in the United States
Hyperbranched Polyesters Containing Natural Antibacterial Compounds
No full textBacterial infections and bacterial contamination of food is a growing concern with the rise of antibiotic resistance bacteria. Several approaches such as antimicrobial peptides, silver nanoparticles, imidazolium salts, or carbohydrate polymers have shown promise in combating bacteria. Another approach which has received considerable attention is the use of polyphenols. Polyphenols are known are naturally occurring antibacterial compounds. Here, we are reporting the incorporation of salicylic acid, aspirin, or ibuprofen into a hyperbranched polymer for antibacterial applications. The synthesis of these materials is a straight forward one-pot, two-step process. (see figure below) Adipic acid was reacted with glycerol triglycidyl ether in refluxing IPA overnight. Salicylic acid, aspirin, or ibuprofen was then added to the flask to react with the resulting hyperbranched polymer at reflux. These materials were characterized by IR and H-NMR spectroscopy. Following characterization, the antibacterial properties of each material was tested with gram-positive and gram-negative bacteria. The test involved addition of the hyperbranched polymer to a membrane. The membrane was added to a petri dish containing Agar followed by addition of the bacteria. The bacteria were then cultured followed by determination of bacterial inhibition
Descriptive Effects Pedal
No full textThe Descriptive Effects Pedal, DEP for short, is a new effect pedal for electronic instruments that uses descriptions of musical sounds to change the output signal of the connected instrument. The DEP will be primarily used with instruments who are electric by nature such as an electric guitar or an electronic keyboard. The device serves to aid those who are aspiring to learn about effects for their instrument, without any sound design or music theory background. The DEP will allow a user to describe the sound of the instrument they want to create by selecting pre-programmed descriptions using the on-board touch screen. These descriptions correspond to digital effects that will take the input sound of the connected instrument and shape it into a sound in which they describe. The digital effects will be added to the signal of the instrument using a microcontroller. The device will have up to three active effects at once. The DEP will have up to seven different effects to choose from. In addition to altering the signal with digital effects, pre- and post-processing circuitry will be used to alter the signal for proper use within the DEP. This sound can either be played through the on-board speakers, or though other connected devices such as a speaker or headphones
The Effect of Post-Processing Conditions on Injection Molded Part Performance
No full textPlastics recycling is a growing environmental concern. When choosing recycled plastics for new parts, manufacturers prefer post-industrial material rather than post-consumer plastics because they are less contaminated, allowing for easier reprocessing into new products. Despite the advantages over post-consumer plastics, post-industrial plastic can experience temperature extremes. This investigation focuses on the effect of post-processing conditions on HDPE parts\u27 thermal and mechanical properties. Materials used in this study were two different grades of HDPE material: Virgin HDPE and Crate HDPE. Each material was injection molded into test bars and conditioned after processing. Standard conditioning was one week at ambient temperature, pressure, and humidity. Two elevated temperatures were examined: 70C or 110℃ for 24 hours. Three reduced temperatures were also studied: 4℃ or - 25℃ for 24 hours, and ice bath quenching for one hour. Subsequently, we evaluated samples for thermal and mechanical properties. Mechanical properties included tensile and flexural modulus, ultimate elongation, and Izod impact strength. Tc and Tm were determined via DSC. Virgin HDPE had greater elongation than Crate HDPE under all conditions. Ice bath quenched Virgin HDPE showed greater tensile and flexural moduli. Both 70C and 110C Virgin HDPE had lower flexural moduli compared to other conditions and Crate HDPE. Crate HDPE had lower impact strength than Virgin HDPE overall. Virgin HDPE (70℃) and Crate HDPE (110C) showed improved notched impact strength. Tm was not affected in Virgin HDPE by conditioning, but Crate HDPE showed a 5 to 15% crystallization increase. Overall, post-processing of HDPE does affect important material properties