Despite Online Challenges, Faculty Optimistic About Future of STEM Education

STEM illustration

Seventy-three percent of STEM faculty in a recent survey had to shift from face-to-face to remote learning in fall 2020, experiencing a multitude of barriers to teaching STEM courses online. Yet most survey respondents remain optimistic about the future of STEM postsecondary education, according to a new report from the Online Learning Consortium and Bay View Analytics. The research, conducted in partnership with Every Learner Everywhere, Carolina Distance Learning and Digital Ed, with support from HHMI BioInteractive, was drawn from a national survey of 869 faculty across all STEM disciplines and institution types.  

In teaching STEM courses online, challenges faced by faculty included:

  • Inability to ensure academic integrity (cited by 52 percent of respondents);
  • Students not sufficiently motivated (48 percent);
  • Equity issues for some students (42 percent);
  • Student internet and computer access (38 percent);
  • Inadequate online laboratories (34 percent);
  • Students not technologically prepared (29 percent);
  • Lower retention rates in online courses (27 percent); and
  • Support in developing or delivering online courses (24 percent).

When asked which barrier was the most serious, the largest share of faculty (24 percent) cited student motivation, noting instances of students not showing up for lectures, shy students who were reluctant to participate or turn on their webcams, and students leaving a lecture early. Faculty also recognized students' high level of stress as well as the lack of interpersonal contact between student and instructor as factors negatively impacting student engagement.

In spite of the barriers, most faculty — 66 percent — said they were optimistic about the future of STEM education at their institutions. Optimism level varied in interesting ways across respondent subgroups. For example, 81 percent of faculty at public two-year colleges felt optimistic about the future of STEM education, compared to 67 percent at four-year private nonprofit institutions and 64 percent of four-year publics. Sixty-seven percent of faculty who had taught one or more online STEM courses felt optimistic, compared to 57 percent of those who had not taught online. And faculty teaching courses with accompanying labs were less optimistic that those whose courses did not have a lab component (62 percent vs. 69 percent, respectively).

The full report is available on the Bay View Analytics site.

About the Author

Rhea Kelly is editor in chief for Campus Technology, THE Journal, and Spaces4Learning. She can be reached at [email protected].

Featured

  • pattern featuring interconnected lines, nodes, lock icons, and cogwheels

    Red Hat Enterprise Linux 9.5 Expands Automation, Security

    Open source solution provider Red Hat has introduced Red Hat Enterprise Linux (RHEL) 9.5, the latest version of its flagship Linux platform.

  • glowing lines connecting colorful nodes on a deep blue and black gradient background

    Juniper Launches AI-Native Networking and Security Management Platform

    Juniper Networks has introduced a new solution that integrates security and networking management under a unified cloud and artificial intelligence engine.

  • a digital lock symbol is cracked and breaking apart into dollar signs

    Ransomware Costs Schools Nearly $550,000 per Day of Downtime

    New data from cybersecurity research firm Comparitech quantifies the damage caused by ransomware attacks on educational institutions.

  • landscape photo with an AI rubber stamp on top

    California AI Watermarking Bill Garners OpenAI Support

    ChatGPT creator OpenAI is backing a California bill that would require tech companies to label AI-generated content in the form of a digital "watermark." The proposed legislation, known as the "California Digital Content Provenance Standards" (AB 3211), aims to ensure transparency in digital media by identifying content created through artificial intelligence. This requirement would apply to a broad range of AI-generated material, from harmless memes to deepfakes that could be used to spread misinformation about political candidates.