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246 research outputs found
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Teaching smarter, not harder: Leveraging Outlook to stay organized
No full textAre you making the most of Outlook? This session will help faculty maximize their efficiency by exploring essential features that streamline email, scheduling, and task management. Learn how to organize your inbox with folders and rules, integrate Zoom seamlessly into your calendar, set up an efficient to-do list, and make the most of Outlook’s Bookings tool and more! Plus, discover how to optimize the Outlook app for on-the-go productivity, including mobile calendar management, email triaging with swipe gestures, and syncing across devices. Whether you’re drowning in emails or looking to fine-tune your workflow, this session will give you practical strategies to take control of your Outlook experience
Navigating difficult conversations and recognizing persons of concerns: Confrontation, de-escalation, and threat awareness
No full textA student angry about their grade, a peer not pulling their weight, a supervisor sharing criticism; all can trigger anxiety and stress. Human beings experience physiological responses to stressful encounters that inhibit our ability to communicate, problem solve and listen when it’s most important to do so. Targeted attacks, like active shooters incidents, are not spontaneous, sudden events which occur without warning. They are predictable and, consequently, preventable. Students, co-workers or others may exhibit risk factors or observable behaviors that would indicate they may be on the “pathway to violence.”
In this interactive presentation, participants will be introduced to methods to manage stress during a confrontation to remain intellectually competent to manage the encounter without succumbing to the instinctive visceral reactions that derail our rational responses. Several tools will be introduced for managing difficult conversations and confrontations. Participants will discover, through a self-assessment, their own personal conflict management style and understand how it affects their ability to collaborate toward reaching mutually positive outcomes.
Additionally, this program will provide a basic understanding of the behavioral evolution of an attacker and help participants to recognize and respond to potential signs or cues that may indicate an individual is in distress, in need of help, or may be planning violence, and what interventions might help prevent an attack.
Learning Objectives: Participants will gain insight into the natural physiological stress responses that affect cognitive capacity. Participants will learn skills to mitigate visceral responses to confrontation that inhibit problem solving. Participants will complete a self-assessment to determine their dominant conflict management style. Participants will learn and practice tools for effective de-escalation and confrontation. Participants will gain an understanding of basic threat assessment principles
What it means to be a Lasallian coach
No full textWhat exactly does it mean to be a Lasallian Coach and how does it fit with the values of Lewis University.
Discussion that compares and connects what it means to be a Lasallian Coach and the core mission values of Lewis University - Knowledge, Fidelity, Wisdom, Justice, and Association. How can we utilize this connection to create a program mission statement, team core values, and standards that are utilized to drive behavior, development, and success. (This part of the presentation is intended to tie together our values and how they can shape how we do our work).
What are the traits of Lasallian athletes and coaches and how does it direct our coach/player interactions, program plans and most importantly the culture we build within the program.
Discussion that specifies what is different about Lasallian Athletes and Coaches and how they utilizes these traits to create an amazing culture within the program, getting players to buy in and how it impacts anyone that encounters the program. How this methodology crosses over into academics. (This part of the presentation is intended to give concrete examples of how their program builds culture and how that culture permeates the program and the surrounding community).
How can faculty and staff both utilize what it means to be a Lasallian Coach as a method for developing students.
What lessons has she learned as a Lasallian Coach that can cross over to the academic world. As faculty work to develop our students, can we provide them a framework for a different setting (classroom), what are the similarities to our classroom (court or field) and can these shared
values and traits work across campus to impact our students. (This part of the presentation is intended to bridge the gap between Academics and Athletics on a college campus. How can the methods of running an Athletics program translate to the classroom)
Enhancing Software Testing Using AI and Graph Similarity
No full textSoftware testing plays a vital role in the development lifecycle, ensuring the prevention of failures and the enhancement of software quality. Despite its importance, the testing phase is often resource-intensive, involving numerous test cases that can become redundant or overlapping over time-leading to increased complexity and prolonged testing durations. To address these inefficiencies, this paper proposes a novel approach that integrates graph similarity analysis with generative AI and deep learning to optimize test suites. By leveraging call graphs derived from test cases, the method identifies redundant and closely related test scenarios. A machine learning model is used to predict similarity scores between these call graphs, facilitating the classification and prioritization of test cases. Lower similarity scores correspond to test cases with more unique code coverage and are thus assigned higher priority. This prioritization enables test engineers to focus on a more diverse and effective subset of test cases, ensuring thorough code coverage while improving efficiency. The proposed framework ultimately reduces redundancy, lowers testing costs, and upholds high standards of software quality, offering a systematic solution for determining the optimal level of testing required to meet study objectives. While the current study experimentally validates the use of graph similarity metrics for test case prioritization, the application of generative AI models is proposed as part of future extensions
Incorporating Visualization into Introductory Accounting Courses to Increase Students\u27 Interests in Accounting
No full textThe primary objective of this study is to explore whether data visualization, which combines analysis and communication, can stimulate students’ interest in accounting and, as a result, draw them to the accounting profession. The study measured college students’ intentions to choose accounting by focusing on three intrinsic factors within the concept of personal interest: self-efficacy in analytical skills, perceptions of the accounting profession and courses, and beliefs about post-graduate employability. We carried out a 2 × 1 between-subjects design experiment involving undergraduate students from two sections of Principles of Accounting classes. The two sections had similar enrollments and student demographics and followed the same syllabus. One section performed ratio analysis, and the other visualization analysis using the same financial data case. Results show that students in the visualization analysis section reported stronger perceptions of their analytical abilities and post-graduate employability compared to those in the ratio analysis section. Students’ perceptions of the accounting profession were not different, but students’ perceptions of accounting courses differed. There were no differences between groups on interest in accounting or intentions to major in accounting. Further research is needed to identify effective strategies for generating interest in accounting
AI‐Assisted Integration of Computational Thinking: Pre‐service Teachers’ Experiences in Early Childhood Mathematics Education
No full textThis study examined how pre-service teachers utilize artificial intelligence (AI) tools to integrate computational thinking (CT) in early childhood mathematics education. Through a qualitative case study guided by the TPACK framework, we examined 24 early childhood pre-service teachers enrolled in a mathematics methods course as they developed CT-integrated math lesson plans using AI assistance. Data sources included pre- and post-course open-ended questionnaires, CT exploration assignments, AI interaction documentation, lesson plans, and reflection papers. The findings revealed three patterns in how pre-service teachers leveraged AI as a scaffold: generating initial ideas for CT integration, refining these ideas for specific teaching contexts, and clarifying CT concepts for deeper understanding. Pre-service teachers demonstrated strategic decision-making in their AI use, successfully designing developmentally appropriate CT-integrated activities while maintaining professional judgment in content adaptation. This study highlights the critical need for structured approaches to AI integration in teacher preparation programs that effectively balance technological proficiency with pedagogical integrity. The implications suggest the importance of developing comprehensive frameworks for AI use in early childhood teacher preparation, addressing both theoretical foundations and practical implementation strategies
Integrating ChatGPT in Teacher Education: Examining Early Childhood and Elementary Pre-Service Teachers’ Experiences in AI-Assisted Math Lesson Planning
No full textThis study examines how pre-service teachers in early childhood education (ECE) and elementary education (ELE) integrate ChatGPT into mathematics lesson planning. Using a mixed-methods case study framed by the Technological Pedagogical Content Knowledge (TPACK) with Contextual Knowledge (XK) framework and AI literacy, we analyzed the experiences of 44 pre-service teachers (24 ECE, 20 ELE) in mathematics method courses at a university in the Midwestern United States. Data sources included pre- and post-assessments, documentation of ChatGPT interactions, lesson plans, and reflection papers. Findings reveal significant gains in participants’ knowledge of and confidence in using ChatGPT, with increased willingness to incorporate generative AI tools into their teaching practices. Thematic analysis identified six categories of ChatGPT use in lesson planning, from content generation to final refinement, while highlighting challenges in adapting AI-generated content to meet developmentally appropriate practices and specific classroom needs. While both ECE and ELE groups followed similar patterns in ChatGPT usage, their approaches varied based on grade-level contexts. This study demonstrates how the development of integrated TPACK-XK competencies and AI literacy supports effective ChatGPT integration in math lesson planning. Findings contribute to understanding how teacher education programs can prepare future educators to integrate generative AI technologies while maintaining pedagogical integrity
