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Monday, April 7
Research Awards Reception
2:00–4:00 p.m.
PNC Room, KCAC (by invitation)
This annual, invitation-only event recognizes and celebrates outstanding research by faculty and graduate students and the commitment to sponsored research by faculty and staff.
Basics of Spatial Analysis
3:00–4:30 p.m.
Stabley Library, Room 201, or Zoom
Join Elena Frye, ARL graduate assistant, for this workshop, designed to introduce graduate students, faculty, and upper-level undergraduate students to the key concepts used in spatial analysis with GIS software.
Tuesday, April 8
Artificial Intelligence Summit
8:30 a.m.–3:30 p.m.
Stabley Library and Online
Join the Center for Scholarly Communication for the second annual Artificial Intelligence Summit. The 2025 summit will be an exciting and informative day of workshops that offers attendees three separate tracks: AI Exploration, AI Pedagogy, and AI Research and Scholarship. View the full schedule of events, or contact the Center for Scholarly Communication at scholarly-communication@iup.edu.
Wednesday, April 9
Scholars Forum
9:00 a.m.–noon
KCAC
Stop by the KCAC and check out the dynamic and diverse research being conducted by IUP undergraduate and graduate students! This annual event features poster presentations, oral presentations, juried art exhibitions, and much more. View more information about the Scholars Forum.
Thursday, April 10
Python Basics
11:00 a.m.–noon
Stabley Library, Room 201, or Zoom
Join Joshua Petteno, ARL graduate assistant, for an introductory Python workshop. This workshop will provide a practical understanding of Python’s core elements and will cover fundamental concepts like variables, data types, lists, and loops.
Preparing for Spatial Analysis in ArcGIS
3:00–4:30 p.m.
Stabley Library, Room 201
This in-person workshop, led by Elena Frye, ARL graduate assistant, is designed to introduce graduate students, faculty, and upper-level undergraduate students to the ArcGIS Pro workspace. Participants will gain a basic understanding of the ArcGIS Pro layout, workspace, and tools. They will also learn how to import existing spatial data into ArcGIS Pro, add new spatial data, and create a basic but effective map layout to communicate spatial findings in work such as posters, presentations, and written articles. This session will build on the Basics of Spatial Analysis workshop.
Processing Data
5:00–6:00 p.m.
Stabley Library, Room 201, or Zoom
Join Paul Hawkins, ARL director, for an overview of data processing. Data processing includes the steps taken to collect, enter, code, and prepare data for valid and reliable analysis. Special attention will be given to the preparation process, such as the importance of conducting preliminary analysis to identify and deal with missing data and outliers. Participants will learn strategies for becoming more efficient when preparing raw data for final analysis.
Friday, April 11
Exploratory Data Analysis (EDA)
11:00 a.m.–noon
Stabley Library, Room 201, or Zoom
Paul Hawkins, ARL director, will discuss the exploratory perspective of data analysis. Special focus will be given to the importance of visualizing and assessing distributions of single variables, assessing relationships between variables, looking for (and being open, but skeptical) to structure and trends, also known as reexpression, and putting it all together with multivariate analysis. Participants will learn the exploratory data analysis (EDA) perspective and how it can be incorporated with the traditional model of data analysis into any data analyst’s toolbox.
Unlocking Data: First Steps in Data Exploration with Python and Pandas
2:00–3:30 p.m.
Stabley Library, Room 201
Join Joshua Petteno, ARL graduate assistant, for this in-person workshop, which transitions from foundational Python to the practical application of data analysis. Participants will be introduced to the Pandas library, a cornerstone tool for data manipulation and exploration. This workshop will empower researchers to confidently load, access, and modify datasets within the Python environment and will provide hands-on experience in addressing common data challenges, such as handling missing values and data formatting issues, and how to transform data to extract meaningful insights. Techniques for summarizing data and visualizing patterns through basic graphs will also be explored.