InForMID
Tufts Initiative for the Forecasting and Modeling of Infectious Diseases
InForMID
Tufts Initiative for the Forecasting and Modeling of Infectious Diseases

Solstice Accordian – 1.5

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Step 1: Learning about the SOLSTICE approach

The development of the SOLution-oriented, STudent-Intiated, Computationally-Enriched (SOLSTICE) project-based teaching and learning approach is funded by the National Science Foundation's (NSF) Innovations in Graduate Education (IGE) Program. This project aims to teach graduate students to solve complex problems, think critically, and effectively communicate across inter-generational, trans-disciplinary research terms. Using a data-intensive, project-based learning approach, graduate students work collaboratively to design, evaluate, and disseminate research in team environments. As data scientists, these students will learn how to pose research questions, translate information into potential actions, develop data collection, analysis and visualization schemes and protocols, and exchange information, data methods, and results in a tailored manner to various audiences. For more information, please see this overview document.

  • Principal Investigators (PIs)
    • Dr. Elena Naumova, Chair of the Department of Nutrition Epidemiology and Data Science, Tufts Friedman School of Nutrition Science and Policy
    • Dr. Barbara Brizuela, Dean of Academic Affairs, Tufts University School of Arts and Sciences
    • Dr. Remco Chang, Associate Professor in the Department of Computer Science, Tufts School of Engineering.
  • Research Coordinators (RC)
    • Ryan Simpson, PhD Candidate, Nutrition Epidemiology and Data Science, Tufts Friedman School of Nutrition Science and Policy
Step 2. Understanding the SOLSTICE aims

The project-based design of the SOLSTICE approach centers on feedback and collaboration. This includes students providing feedback on one another's works as well as providing feedback on the feedback they are given to ensure transparent, communicative teamwork. Students will also be challenged to organize and manage their semester-long projects by creating data management flows and building and executing data analysis plans. To do this, SOLSTICE employs team role-play where students serve as Team Leaders, Collaborators, and Reviewers of their own and their peers’ works.

  • As a Team Leader, students will serve as principal investigator to direct their own individual project. This includes defining a testable hypothesis, proposing a plan of execution, and designing a plan of evaluation for their project. Students will also perform data cleaning, analyses, and summaries for in-class presentations and a final report.
  • As a Collaborator, students will serve as a co-principal investigator to revise the works of their partners. This includes helping to find solutions for identified challenges and evaluating whether partners' study results are communicated to a broad range of stakeholders in a suitable language.
  • As a Reviewer, students will provide constructive criticism to partners by identifying flaws and weaknesses of presentations, manuscripts, and analysis plans. The reviewer is not meant to play an adversary role - all feedback should offer possible solutions by providing a big picture perspective that may have been missed by investigators.

In short, SOLSTICE aims to:

  • Teach students to solve complex problems and think critically about data analytics
  • Train students to effectively communicate research findings across disciplines and diverse audiences
  • Use a data-intensive, project-based learning approach to design, evaluate, and disseminate research in team environments
  • Build strong technical and leadership skills to lead and evaluate research projects
Step 3. Becoming enrolled as a participating course

Spring 2021 Semester

Fall 2020 Semester

Spring 2020 Semester

Fall 2019 Semester (Pilot)

Step 4. How do faculty get involved

We are seeking project-based graduate courses in statistics or data-related fields from across all Tufts campuses to participate in this study. Faculty teaching those courses will be asked to share information on students’ performance in their classes and administer the anonymous surveys and assessments above. We will share with you the results of the study for all enrolled courses on students’ preparation and skills in statistical and computational software, performance of data-related tasks, and interests in project-based, team-based learning.

Involvement is easy and requires just 3 steps:

  1. The First Pilot Year will introduce faculty to the SOLSTICE approach. Course curricula will not be modified or adapted in any way. We will simply use this year to understand student development and progression in the current structure of the course. Faculty will be asked to administer consent forms, surveys, and assessments and provide information on student midterm and final assessments.
  2. Attend the Summer SOLSTICE Workshop to discuss how the SOLSTICE approach can be implemented incorporated into course syllabi. This includes a range of options including adapting course lectures to address key SOLSTICE aims, revising midterm or final presentation rubric, or revising midterm and final project requirements to target specific student skill development.
  3. The Second SOLSTICE Year is when faculty with teach revised course curricula modified to include SOLSTICE-based ideas. As noted above, faculty will have the choice of including a range of SOLSTICE approaches into their course and some courses may already follow these approaches already. We will use student development and progression in this second year to evaluate the benefits of the SOLSTICE approach. As in the pilot year, faculty will be asked to administer consent forms, surveys, and assessments and provide information on student midterm and final assessments.
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