The Virtual Mystery Project (phase 2): the Virtual Mystery custom web tool
The Virtual Mystery Project (Phase 2): The Virtual Mystery Custom Web-Tool
“The VM web-tool provides small group active learning experiences in a cost-effective user-friendly manner for self-directed independent learning.”
The Virtual Mystery (VM) project is an online hybridized problem-based learning (PBL) teaching tool that self-releases weekly clues with images to engage small student groups in collaborative active learning within large courses. A 2017 LEAF seed grant supported the successful implementation and evaluation of the VM project through the Learning Management Engine (LME) in Introduction to Biological Anthropology and Archaeology. When the VM project outgrew LME capabilities, a custom VM web-tool was developed to self-release weekly clues with images in a user-friendly manner with an interface between facilitators and PBL groups. The VM web-tool generated interest from other disciplines across the Humanities (Language Studies), Sciences (Forensic Science) and Social Sciences (Psychology). The current phase of the VM project will demonstrate the web-tool’s capacity as a user-friendly online hybridized problem-based learning application for any subject material. Four courses across these disciplines will create and implement virtual mysteries to evaluate the VM web-tool in their subject areas. The VM web-tool provides small group active learning experiences in a cost-effective user-friendly manner for self-directed independent learning. This project aligns with UTM Undergraduate Learning Expectations emphasizing student development of transferable skills across disciplines (collaboration, critical thinking, and problem solving).
Department of Anthropology, University of Toronto Mississauga;
Year LEAF Granted
Phase 1: 2017
Phase 2: 2019-2023
LEAF Priority Area(s)
Impact of the Project on Students
This project has impacted students in a wide variety of courses including:
- ANT317H N=50 students (2019)
- ANT101H N=800 students in Winter and 100 students in summer (2020)
- FSC402H N= 40 students (2020)
- PSY290H N=500 students (2021)
- FSL205Y N=45 students (2022)
- ANT200H N=150 students (2022)
Impact of the Project on Faculty
Phase two will disseminate the VM web-tool across disciplines in four courses from varying undergraduate years and class sizes in Humanities (Language Studies, FSL205Y5, N=45 students, 10 virtual mysteries), Sciences (Forensic Science, FSC402H5, N=40 students, 30 virtual mysteries) and Social Sciences (Psychology, PSY290H5, N=500 students, 50 virtual mysteries).
This phase of the VM project will ensure the VM web-tool shell provides a user-friendly application easily populated by any course material to adapt hybridized PBL cases across disciplines. With the success of this phase, we anticipate the release of the tool to other institutions (universities, colleges, museums) expressing an interest in the VM project. The University of Guelph implemented the Virtual Mystery Project in their first year anthropology course in September 2020.
A guide accompanying the web-tool will explain the concepts of problem-based learning and include examples from the discipline of anthropology. The VM web-tool will enable the project to move beyond the Anthropology Department across disciplines and eventually have applications in a variety of institutions.
Resources Developed from the Project
Virtual Mystery Web-tool, with accompanying instructor and student guides.
The webtool will continue to be used throughout UTM and piloted at other institutions.
The VM web-tool was developed in partnership between students from the Department of Mathematical and Computational Sciences under the supervision of Andrew Petersen and students from the Anthropology Department under the supervision of Sherry Fukuzawa.
The webtool is being implemented across UTM (anthropology, psychology, forensic science, language studies) and the virtual mystery project is being run through the LME at the University of Guelph Department of Anthropology under Dr. Travis Steffens.