IN LSAMP 2020 Annual Research Conference

Fly High with STEM

October 3, 2020

Ball State University, Muncie, IN

The 2020 Annual Research Conference was hosted by the Ball State University via the virtual conference platform, Whova, on October 3, 2020.

With the theme, Fly High with STEM, the conference aimed to inspire, connect, and broaden participation of underrepresented minority students in STEM. Unequivocally, each of these goals was achieved, and the resonating sense among the attendees was that of community, encouragement, and professional growth.

Registered conference attendees can access all of the conference materials and continue interacting with each other via Whova. Conference content will be archived in its entirety in Whova’s mobile app and on the web until March 31, 2021.

Conference Recordings & Proceedings

Speakers

Click below to see the complete list of IN LSAMP 2020 Conference Speakers

Agenda

Click below to see the full IN LSAMP 2020 Conference Agenda

Webpage Archive

Since its launch in July 2020, this conference page has featured the most current IN LSAMP 2020 Annual Research Conference content. It now serves as the conference archive.

Assessment Institute in Indianapolis

The Assessment Institute in Indianapolis is the nation's oldest and largest event focused exclusively on outcomes assessment in higher education. We anticipate that some 1000 educators from virtually every state and several other countries will take part in the 2018 Institute.

The Assessment Institute in Indianapolis is designed to provide opportunities for (1) individuals and campus teams new to outcomes assessment to acquire fundamental knowledge about the field, (2) individuals who have worked as leaders in outcomes assessment to share and extend their knowledge and skills, and (3) those interested in outcomes assessment at any level to establish networks that serve as sources of support and expertise beyond the dates of the Institute.

Future Assessment Institute Dates

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. IN LSAMP is supported by NSF Award Number: HRD-1618408, 2016-2022