Enhancing Institutional Assessment and Reporting Through Conversational Technologies: Exploring the Potential of AI-Powered Tools and Natural Language Processing

This study explores the potential of conversational technologies, AI-powered tools, and natural language processing (NLP) in enhancing institutional assessment and reporting processes in higher education. The traditional approach to assessment often involves labor-intensive manual analysis of extensive data and documents, which burdens institutions. To address these challenges, AI-powered tools, such as ChatGPT, LangChain, Poe, Claude, and others, along with NLP techniques, are investigated in relationship to their ability to improve institutional assessment practices and output. By leveraging these advanced technologies, assessment officers and institutional effectiveness, researchers can engage in dynamic conversations with data, transforming spreadsheets and documents from static artifacts into interactive resources. These tools streamline communication, collaboration, and decision-making processes, empowering committees and working groups to achieve their goals effectively. Additionally, the potential applications of NLP in analyzing vast amounts of institutional data, including student feedback, faculty evaluations, and institutional documents, shall be discussed. Language models enable the extraction of meaningful insights from unstructured data sources, facilitating real-time decision-making processes. Ethical considerations related to data privacy, mining, and compliance with regulations like FERPA are crucial aspects addressed in this study. The contribution of this research lies in uncovering the transformative impact of conversational technologies, AI-powered tools, and NLP techniques on institutional assessment and reporting. By embracing these advancements responsibly and ensuring alignment with ethical principles, institutions can unlock the full potential of these tools, facilitating more efficient, data-driven decision-making processes in higher education. The study showcases how conversational technologies, AI-powered tools, and NLP techniques offer new possibilities for improving institutional assessment and reporting practices. By integrating these technologies responsibly and addressing ethical considerations, institutions can enhance their assessment processes and make more informed decisions based on comprehensive, real-time insights

Framework to Enhance Teaching and Learning in System Analysis and Unified Modelling Language

Cowling, MA ORCiD: 0000-0003-1444-1563; Munoz Carpio, JC ORCiD: 0000-0003-0251-5510Systems Analysis modelling is considered foundational for Information and Communication Technology (ICT) students, with introductory and advanced units included in nearly all ICT and computer science degrees. Yet despite this, novice systems analysts (learners) find modelling and systems thinking quite difficult to learn and master. This makes the process of teaching the fundamentals frustrating and time intensive. This paper will discuss the foundational problems that learners face when learning Systems Analysis modelling. Through a systematic literature review, a framework will be proposed based on the key problems that novice learners experience. In this proposed framework, a sequence of activities has been developed to facilitate understanding of the requirements, solutions and incremental modelling. An example is provided illustrating how the framework could be used to incorporate visualization and gaming elements into a Systems Analysis classroom; therefore, improving motivation and learning. Through this work, a greater understanding of the approach to teaching modelling within the computer science classroom will be provided, as well as a framework to guide future teaching activities

Development of Digital Education in the Age of Digital Transformation: Citing China’s Practice in Smart Education as a Case Study

Digital education has been catalyzing educational transition, transforming the educational views and instructional techniques while also providing opportunities for high-quality educational development. This is a subject that all nations throughout the world are concerned about. The worldwide practice of integrating digital technologies in teaching has yielded positive results. The Global Digital Education Conference, which was held in Beijing, China, in 2023, called for global collaboration on digital education development. This paper sought to illustrate the significance of digital education for educational reform and to investigate ways for digital education development in this context, using China’s smart education practice as evidence

Corporate influence and the academic computer science discipline. [4: CMU]

Prosopographical work on the four major centers for computer research in the United States has now been conducted, resulting in big questions about the independence of, so called, computer science

Institutional Research-Focused Conversational Artificial Intelligence Agent

A capstone submitted in partial fulfillment of the requirements for the degree of Doctor of Education in the Ernst and Sara Lane Volgenau College of Education at Morehead State University by Joshua C. Frisby on March 8, 202

NMC Horizon Report: 2017 Library Edition

What is on the five-year horizon for academic and research libraries? Which trends and technology developments will drive transformation? What are the critical challenges and how can we strategize solutions? These questions regarding technology adoption and educational change steered the discussions of 77 experts to produce the NMC Horizon Report: 2017 Library Edition, in partnership with the University of Applied Sciences (HTW) Chur, Technische Informationsbibliothek (TIB), ETH Library, and the Association of College & Research Libraries (ACRL). Six key trends, six significant challenges, and six developments in technology profiled in this report are poised to impact library strategies, operations, and services with regards to learning, creative inquiry, research, and information management. The three sections of this report constitute a reference and technology planning guide for librarians, library leaders, library staff, policymakers, and technologists

IoT-Enhanced Learning Environment Optimization and Student Outcome

This proposed system leverages Internet of Things (IoT) technology to enhance the learning environment in educational settings through two synergistic techniques. Firstly, a search-based optimization algorithm, driven by a genetic-based approach, is implemented for scheduling courses and faculty within each department to improve overall student performance and departmental percentages. Secondly, a classification task is performed to predict student outcomes, employing Neural Networks (NN) including ResNet 50, ResNet34, and a hybrid ResNet34 and ResNet50 model. The classification is based on eye-gaze monitoring during active student engagement in class, using input video samples as training and testing datasets. The system integrates optimization, activity monitoring, and classification to create a comprehensive approach aimed at improving the overall learning environment and student outcomes in educational institutions