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Framework and Foundations

Brief History of SOSSI

SOSSI, version 1.0, was developed approximately ten years ago by a cross-functional, multi-disciplinary team of campus-based stakeholders and System administration staff as an in-house alternative to SmarterMeasure, a vendor-provided readiness tool that offered no capacity for campus customization and was a budgeting cost to SUNY and campuses.

Early research revealed two distinct student patterns: those who assumed online classes would be significantly easier and require less time commitment, and those intimidated by the technology and/or format. SOSSI v1.0 was designed to surface those misconceptions early, before students entered high-stakes academic situations. We wanted to assess both student attitudes (self-efficacy, mindset, grit) and behaviors (self-regulated learning, reading/writing habits) to identify disconnects between what students believed about online learning and what they were prepared to do.

The COVID-19 pandemic tested that design at scale. When programs that were exclusively campus-based were forced to pivot to remote learning, S.

SOSSI v2.0 is a significant departure from that original instrument. If you’ve used the previous version, expect something different. Constructs were rebuilt from the ground up, informed by original research with SUNY online students. This is not an incremental update; it is a redesign grounded in student voice.

How is it Structured?

SOSSI v2.0 is organized around five modules, each targeting a dimension of online student readiness that research identified as linked to early persistence:

  • Digital Resilience measures how students approach unfamiliar technology and inevitable tech failures, because their response matters more than their baseline digital footprint. A student who knows how to problem-solve through disruption is more likely to persist than one who has never been tested.
  • Technical Access & Reliability establishes whether students have the hardware, connectivity, and stable environment that online learning requires. Without it, every other strength a student brings is at risk of being undermined before it can matter.
  • Help-Seeking Behavior assesses a student’s personal willingness to reach out, as well as their knowledge of how and when to ask for help. It is one of the strongest predictors of whether a struggling student recovers or disappears.
  • Self-Regulation examines the planning, follow-through, and adjustment habits that determine whether students can manage the autonomy that online learning demands. Online learning removes the external structure that on-campus attendance provides; students who haven’t developed their own system must build it while learning so they don’t fail quietly.
  • Online Learning Expectations surfaces the assumptions and prior experiences students bring, because mismatched expectations are among the earliest predictors of attrition. Students who enroll believing that online programs will be easier than they are may disengage before anyone realizes they’re struggling.

Each module measures multiple constructs – the specific dimensions within the domain. For example, Digital Resilience measures Risk Awareness, Strategic Problem-Solving, Adaptive Flexibility, and more. (See Appendix 5 for the full question bank including constructs.) Student responses are scored at the construct level and rolled up into an overall module score, giving campuses a clear, structured basis for determining which students need immediate high-touch support and which need a lighter hand.

Campuses also have the option to pipe students directly into a campus-specific assessmet the end of the SOSSI v2.0 workflow, allowing institutions to gather information unique to their population or priorities without disrupting the core experience.

The SOSSI v2.0 tool is built around five core principles:

  • It is developmental, not diagnostic, focused on growth rather than deficit labeling.
  • It aims to be inclusive, designed to reduce cultural bias and recognize multiple pathways to readiness.
  • It is brief and scalable.
  • It uses a triage approach to help campuses distinguish which students need light-touch, moderate, or intensive support.
  • Results connect directly to specific supports and services.

What SOSSI Produces

SOSSI v2.0 generates two distinct outputs designed for two distinct audiences.

  • Students receive an email report written in accessible, constructive language including friendly charts that highlight their strengths and identify areas where early attention can set them up for success. The report is designed to be actionable without being alarming. This email can also be sent to a designated campus contact by request.
  • Campus advisors, coaches, and support staff receive a more detailed data view of student responses, organized by construct and numerically scored to support triage and outreach decisions. This is the data that drives follow-up.

The individual student report is generated automatically when a student completes the inventory. Campus-wide data is exported periodically and can be imported directly into your institution’s existing advising or early alert system, or reviewed in a FERPA-compliant tool such as Excel if direct integration is not available.

What happens next depends on the structures your campus builds around that data.

For technical specifications including question types, construct scoring, and readiness cut points, see Appendix 5.

How Can Campuses Use the SOSSI?

Campuses across SUNY have integrated SOSSI in ways that reflect their own structures, staffing, and student populations. No two implementations look identical, by design. The examples below illustrate the range of what’s possible. Fuller case studies drawn from actual SUNY campus implementations are available in Appendix 2.

When a program has clear ownership from admissions and a defined population, SOSSI can be built directly into intake. At Seventeen College Program, SOSSI is completed before a student’s first advising meeting. Advisors enter that conversation already knowing where a student may need support, enabling immediate on-the-ground assistance rather than a general check-in.

When orientation is the entry point, SOSSI works as an early signal within an existing structure. At Twice State University, embedding SOSSI within required orientation increased completion and gave advisors consistent, timely data. Students who completed both orientation and SOSSI showed stronger first-semester GPA, suggesting that structured onboarding and early insight reinforce each other.

When staffing is limited, SOSSI can still drive impact through triage. At BTS Community College, not every student who completes SOSSI receives a direct follow-up, but students with the highest levels of identified need do. That prioritization is itself a use of the data.

When implementation is still evolving, SOSSI can serve as a foundation to build on. At Exo County Community College, optional participation and emerging follow-up processes have generated faculty interest and surfaced student needs, creating momentum toward more integrated use over time.

The common thread across all four: SOSSI generates early insight. What institutions do with that insight depends on the structures they build around it.

For full implementation detail on each campus, see Appendix 2: Case Studies.