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Articles 1 - 5 of 5
Full-Text Articles in Higher Education
Ethical Imperatives And Challenges: Review Of The Use Of Machine Learning For Predictive Analytics In Higher Education, Emily Barnes, James Hutson, Karriem Perry
Ethical Imperatives And Challenges: Review Of The Use Of Machine Learning For Predictive Analytics In Higher Education, Emily Barnes, James Hutson, Karriem Perry
Faculty Scholarship
The escalating integration of machine learning (ML) in higher education necessitates a critical examination of its ethical implications. This article conducts a comprehensive review of the application of ML for predictive analytics within higher education institutions (HEIs), emphasizing the technology's potential to enhance student outcomes and operational efficiency. The study identifies significant ethical concerns, such as data privacy, informed consent, transparency, and accountability, that arise from the use of ML. Through a detailed analysis of current practices, this review underscores the need for HEIs to develop robust ethical frameworks and technological infrastructures to navigate these challenges effectively. The findings reveal …
Optimizing Adult Learner Success: Applying Random Forest Classifier In Higher Education Predictive Analytics, Emily Barnes, James Hutson, Karriem Perry
Optimizing Adult Learner Success: Applying Random Forest Classifier In Higher Education Predictive Analytics, Emily Barnes, James Hutson, Karriem Perry
Faculty Scholarship
This study examines the application of the Random Forest Classifier (RF) model in predicting academic success among adult learners in higher education. It focuses on evaluating the model's effectiveness using key statistical measures like accuracy, precision, recall, and F1 score across a comprehensive dataset from 2013–14 to 2021–22, which includes variables such as age, ethnicity, gender, Pell Grant eligibility, and academic performance metrics. The research highlights the RF model's capability to handle large datasets with varying data types and demonstrates its superiority over traditional regression models in predictive accuracy. Through an iterative process, the study refines the RF model to …
Teaching Software Development For Real-World Problems Using A Microservice-Based Collaborative Problem-Solving Approach, Yi Meng Lau, Christian Michael Koh, Lingxiao Jiang
Teaching Software Development For Real-World Problems Using A Microservice-Based Collaborative Problem-Solving Approach, Yi Meng Lau, Christian Michael Koh, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Experienced and skillful software developers are needed in organizations to develop software products effective for their business with shortened time-to-market. Such developers will not only need to code but also be able to work in teams and collaboratively solve real-world problems that organizations arefacing. It is challenging for educators to nurture students to become such developers with strong technical, social, and cognitive skills. Towards addressing the challenge, this study presents a Collaborative Software Development Project Framework for a course that focuses on learning microservices architectures anddeveloping a software application for a real-world business. Students get to work in teams to …
Seeing Eye To Eye? Comparing Faculty And Student Perceptions Of Biomolecular Visualization Assessments, Josh T. Beckham, Daniel R. Dries, Bonnie L. Hall, Rarchel M. Mitton-Fry, Shelly Engelman, Charmita Burch, Roderico Acevedo, Pamela S. Mertz, Didem Vardar-Ulu, Swati Agrawal, Kristin M. Fox, Shane Austin, Margaret A. Franzen, Henry V. Jakubowski, Walter R. P. Novak, Rebecca Roberts, Alberto I. Roca, Kristen Procko
Seeing Eye To Eye? Comparing Faculty And Student Perceptions Of Biomolecular Visualization Assessments, Josh T. Beckham, Daniel R. Dries, Bonnie L. Hall, Rarchel M. Mitton-Fry, Shelly Engelman, Charmita Burch, Roderico Acevedo, Pamela S. Mertz, Didem Vardar-Ulu, Swati Agrawal, Kristin M. Fox, Shane Austin, Margaret A. Franzen, Henry V. Jakubowski, Walter R. P. Novak, Rebecca Roberts, Alberto I. Roca, Kristen Procko
Chemistry Faculty Publications
While visual literacy has been identified as a foundational skill in life science education, there are many challenges in teaching and assessing biomolecular visualization skills. Among these are the lack of consensus about what constitutes competence and limited understanding of student and instructor perceptions of visual literacy tasks. In this study, we administered a set of biomolecular visualization assessments, developed as part of the BioMolViz project, to both students and instructors at multiple institutions and compared their perceptions of task difficulty. We then analyzed our findings using a mixed-methods approach. Quantitative analysis was used to answer the following research questions: …
In Pursuit Of Consumption-Based Forecasting, Charles Chase, Kenneth B. Kahn
In Pursuit Of Consumption-Based Forecasting, Charles Chase, Kenneth B. Kahn
Marketing Faculty Publications
[Introduction] Today's most mature, most sophisticated, best-in-class forecasting is what we call consumption-based forecasting (CBF). In contrast, the least sophisticated companies typically do not forecast at all, but rather set financial targets based on management expectations. Companies beginning to use statistical forecasting techniques usually take a supply-centric orientation, relying on time series techniques applied to shipment and/or order history. The next stage of progression is to incorporate promotions data, economic data, and market data alongside supply-centric data so that regression and other advanced analytics can be used. Companies pursing CBF utilize even more advanced capabilities to capture, examine, and understand …